Publications by authors named "Yongfeng Yang"

173 Publications

Technical note: A preliminary study of dual-tracer PET image reconstruction guided by FDG and/or MR kernels.

Med Phys 2021 Jul 12. Epub 2021 Jul 12.

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Purpose: Clinically, single radiotracer positron emission tomography (PET) imaging is a commonly used examination method; however, since each radioactive tracer reflects the information of only one kind of cell, it easily causes false negatives or false positives in disease diagnosis. Therefore, reasonably combining two or more radiotracers is recommended to improve the accuracy of diagnosis and the sensitivity and specificity of the disease when conditions permit.

Methods: This paper proposes incorporating F-fluorodeoxyglucose (FDG) as a higher-quality PET image to guide the reconstruction of other lower-count C-methionine (MET) PET datasets to compensate for the lower image quality by a popular kernel algorithm. Specifically, the FDG prior is needed to extract kernel features, and these features were used to build a kernel matrix using a k-nearest-neighbor (kNN) search for MET image reconstruction. We created a 2-D brain phantom to validate the proposed method by simulating sinogram data containing Poisson random noise and quantitatively compared the performance of the proposed FDG-guided kernelized expectation maximization (KEM) method with the performance of Gaussian and non-local means (NLM) smoothed maximum likelihood expectation maximization (MLEM), MR-guided KEM, and multi-guided-S KEM algorithms. Mismatch experiments between FDG/MR and MET data were also carried out to investigate the outcomes of possible clinical situations.

Results: In the simulation study, the proposed method outperformed the other algorithms by at least 3.11% in the signal-to-noise ratio (SNR) and 0.68% in the contrast recovery coefficient (CRC), and it reduced the mean absolute error (MAE) by 8.07%. Regarding the tumor in the reconstructed image, the proposed method contained more pathological information. Furthermore, the proposed method was still superior to the MR-guided KEM method in the mismatch experiments.

Conclusions: The proposed FDG-guided KEM algorithm can effectively utilize and compensate for the tissue metabolism information obtained from dual-tracer PET to maximize the advantages of PET imaging.
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http://dx.doi.org/10.1002/mp.15089DOI Listing
July 2021

Unique structural features of the adenylate kinase hCINAP/AK6 and its multifaceted functions in carcinogenesis and tumor progression.

FEBS Lett 2021 Jul 10. Epub 2021 Jul 10.

State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China.

Human coilin-interacting nuclear ATPase protein (hCINAP), also known as adenylate kinase 6 (AK6), is an atypical adenylate kinase with critical roles in many biological processes, including gene transcription, ribosome synthesis, cell metabolism, cell proliferation and apoptosis, DNA damage responses, and genome stability. Furthermore, hCINAP/AK6 dysfunction is associated with cancer and various inflammatory diseases. In this review, we summarize the structural features and biological roles of hCINAP in several important signaling pathways, as well as its connection with tumor onset and progression.
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http://dx.doi.org/10.1002/1873-3468.14158DOI Listing
July 2021

Weak Association Between the Glutamate Decarboxylase 1 Gene (GAD1) and Schizophrenia in Han Chinese Population.

Front Neurosci 2021 21;15:677153. Epub 2021 Jun 21.

Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.

Objectives: Schizophrenia (SZ) is a complex psychiatric disorder with high heritability, and genetic components are thought to be pivotal risk factors for this illness. The glutamate decarboxylase 1 gene (GAD1) was hypothesized to be a candidate risk locus for SZ given its crucial role in the GABAergic neurotransmission system, and previous studies have examined the associations of single nucleotide polymorphisms (SNPs) spanning the GAD1 gene with SZ. However, inconsistent results were obtained. We hence examined the associations between GAD1 SNPs and SZ in two independent case-control samples of Han Chinese ancestry.

Materials And Methods: Two Han Chinese SZ case-control samples, referred as the discovery sample and the replication sample, respectively, were recruited for the current study. The discovery sample comprised of 528 paranoid SZ cases (with age of first onset ≥ 18) and 528 healthy controls; the independent replication sample contained 1,256 early onset SZ cases (with age of first onset < 18) and 2,661 healthy controls. Logistic regression analysis was performed to examine the associations between GAD1 SNPs and SZ.

Results: Ten SNPs covering GAD1 gene were analyzed in the discovery sample, and two SNPs showed nominal associations with SZ (rs2241165, = 0.0181, OR = 1.261; rs2241164, = 0.0225, OR = 1.219). SNP rs2241164 was also nominally significant in the independent replication sample ( = 0.0462, OR = 1.110), and the significance became stronger in a subsequent meta-analysis combining both discovery and replication samples ( = 0.00398, OR = 1.138). Nevertheless, such association could not survive multiple corrections, although the effect size of rs2241164 was comparable with other SZ risk loci identified in genome-wide association studies (GWAS) in Han Chinese population. We also examined the associations between GAD1 SNPs and SZ in published datasets of SZ GWAS in East Asians and Europeans, and no significant associations were observed.

Conclusion: We observed weak associations between GAD1 SNPs and risk of SZ in Han Chinese populations. Further analyses in larger Han Chinese samples with more detailed phenotyping are necessary to elucidate the genetic correlation between GAD1 SNPs and SZ.
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http://dx.doi.org/10.3389/fnins.2021.677153DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8255988PMC
June 2021

3-year Treatment of Tenofovir Alafenamide . Tenofovir Disoproxil Fumarate for Chronic HBV Infection in China.

J Clin Transl Hepatol 2021 Jun 28;9(3):324-334. Epub 2021 Apr 28.

The Sixth People's Hospital of Shenyang, Shenyang, Liaoning, China.

Background And Aims: Tenofovir alafenamide (TAF) has similar efficacy to tenofovir disoproxil fumarate (TDF) but with improved renal and bone safety in chronic hepatitis B patients studied outside of China. We report 3-year results from two phase 3 studies with TAF in China (Clinicaltrials.gov: NCT02836249 and NCT02836236).

Methods: Chinese hepatitis B e antigen (HBeAg)-positive and -negative chronic hepatitis B patients with viremia and elevated alanine aminotransferase were randomized 2:1 to TAF or TDF treatment groups and treated in a double-blind fashion for 144 weeks (3 years). Efficacy responses were assessed by individual study while safety was assessed by a pooled analysis.

Results: Of the 334 patients (180 HBeAg-positive and 154 HBeAg-negative) randomized and treated, baseline characteristics were similar between groups. The overall mean age was 38 years and 73% were male. The mean HBV DNA was 6.4 log IU/mL. The median alanine aminotransferase was 88 U/L, and 37% had a history of antiviral use. At week 144, the proportion with HBV DNA <29 IU/mL was similar among the two groups, with TAF at 83% vs. TDF at 79%, and TAF at 93% vs. TDF at 92% for the HBeAg-positive and -negative patients, respectively. In each study, higher proportions of TAF than TDF patients showed normalized alanine aminotransferase (via the American Association for the Study of Liver Diseases and the China criteria) and showed loss of HBsAg; meanwhile, the HBeAg seroconversion rates were similar. Treatment was well-tolerated among the TAF patients, who showed a smaller median decline in creatinine clearance (-0.4 vs. -3.2 mL/min; =0.014) and less percentage change in bone mineral density vs. TDF at hip (-0.95% vs. -1.93%) and spine (+0.35% vs. -1.40%).

Conclusions: In chronic hepatitis B patients from China, TAF treatment provided efficacy similar to TDF but with better renal and bone safety at 3 years.
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http://dx.doi.org/10.14218/JCTH.2020.00145DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8237145PMC
June 2021

MRI-aided kernel PET image reconstruction method based on texture features.

Phys Med Biol 2021 Jul 26;66(15). Epub 2021 Jul 26.

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.

We investigate the reconstruction of low-count positron emission tomography (PET) projection, which is an important, but challenging, task. Using the texture feature extraction method of radiomics, i.e. the gray-level co-occurrence matrix (GLCM), texture features can be extracted from magnetic resonance imaging images with high-spatial resolution. In this work, we propose a kernel reconstruction method combining autocorrelation texture features derived from the GLCM. The new kernel function includes the correlations of both the intensity and texture features from the prior image. By regarding the GLCM as a discrete approximation of a probability density function, the asymptotically gray-level-invariant autocorrelation texture feature is generated, which can maintain the accuracy of texture features extracted from small image regions by reducing the number of quantized image gray levels. A computer simulation shows that the proposed method can effectively reduce the noise in the reconstructed image compared to the maximum likelihood expectation maximum method and improve the image quality and tumor region accuracy compared to the original kernel method for low-count PET reconstruction. A simulation study on clinical patient images also shows that the proposed method can improve the whole image quality and that the reconstruction of a high-uptake lesion is more accurate than that achieved by the original kernel method.
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http://dx.doi.org/10.1088/1361-6560/ac1024DOI Listing
July 2021

Protocol for a pharmacogenomic study on individualised antipsychotic drug treatment for patients with schizophrenia.

BJPsych Open 2021 Jun 29;7(4):e121. Epub 2021 Jun 29.

Institute of Mental Health, The Sixth Hospital of Peking University, China; and Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders (Peking University), China.

Background: Schizophrenia is a severe and complex psychiatric disorder that needs treatment based on extensive experience. Antipsychotic drugs have already become the cornerstone of the treatment for schizophrenia; however, the therapeutic effect is of significant variability among patients, and only around a third of patients with schizophrenia show good efficacy. Meanwhile, drug-induced metabolic syndrome and other side-effects significantly affect treatment adherence and prognosis. Therefore, strategies for drug selection are desperately needed. In this study, we will perform pharmacogenomics research and set up an individualised preferred treatment prediction model.

Aims: We aim to create a standard clinical cohort, with multidimensional index assessment of antipsychotic treatment for patients with schizophrenia.

Method: This trial is designed as a randomised clinical trial comparing treatment with different kinds of antipsychotics. A total sample of 2000 patients with schizophrenia will be recruited from in-patient units from five clinical research centres. Using a computer-generated program, the participants will be randomly assigned to four treatment groups: aripiprazole, olanzapine, quetiapine and risperidone. The primary outcomes will be measured as changes in the Positive and Negative Syndrome Scale of schizophrenia, which reflects the efficacy. Secondary outcomes include the measure of side-effects, such as metabolic syndromes. The efficacy evaluation and side-effects assessment will be performed at baseline, 2 weeks, 6 weeks and 3 months.

Results: This trial will assess the efficacy and side effects of antipsychotics and create a standard clinical cohort with a multi-dimensional index assessment of antipsychotic treatment for schizophrenia patients.

Conclusion: This study aims to set up an individualized preferred treatment prediction model through the genetic analysis of patients using different kinds of antipsychotics.
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http://dx.doi.org/10.1192/bjo.2021.945DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8269926PMC
June 2021

Synthesizing PET/MR (T1-weighted) images from non-attenuation-corrected PET images.

Phys Med Biol 2021 Jun 24;66(13). Epub 2021 Jun 24.

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, China Academy of Sciences, Shenzhen 518055, People's Republic of China.

Positron emission tomography (PET) imaging can be used for early detection, diagnosis and postoperative patient monitoring of many diseases. Traditional PET imaging requires not only additional computed tomography (CT) imaging or magnetic resonance imaging (MR) to provide anatomical information but also attenuation correction (AC) map calculation based on CT images or MR images for accurate quantitative estimation. During a patient's treatment, PET/CT or PET/MR scans are inevitably repeated many times, leading to additional doses of ionizing radiation (CT scans) and additional economic and time costs (MR scans). To reduce adverse effects while obtaining high-quality PET/MR images in the course of a patient's treatment, especially in the stage of evaluating the effect of postoperative treatment, in this work, we propose a new method based on deep learning, which can directly obtain synthetic attenuation-corrected PET (sAC PET) and synthetic T1-weighted MR (sMR) images based only on non-attenuation-corrected PET (NAC PET) images. Our model, based on the Wasserstein generative adversarial network, first removes noise and artifacts from the NAC PET images to generate sAC PET images and then generates sMR images from the obtained sAC PET images. To evaluate the performance of this generative model, we evaluated it on paired PET/MR images from a total of eighty clinical patients. Based on qualitative and quantitative analysis, the generated sAC PET and sMR images showed a high degree of similarity to the real AC PET and real MR images. These results indicated that our proposed method can reduce the frequency of additional anatomical imaging scans during PET imaging and has great potential in improving doctors' clinical diagnosis efficiency, saving patients' economic expenditure and reducing the radiation risk brought by CT scanning.
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http://dx.doi.org/10.1088/1361-6560/ac08b2DOI Listing
June 2021

Contrast-enhanced to noncontrast CT transformation via an adjacency content-transfer-based deep subtraction residual neural network.

Phys Med Biol 2021 Jul 16;66(14). Epub 2021 Jul 16.

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.

To reduce overall patient radiation exposure in some clinical scenarios (since cancer patients need frequent follow-ups), noncontrast CT is not used in some institutions. However, although less desirable, noncontrast CT could provide additional important information. In this article, we propose a deep subtraction residual network based on adjacency content transfer to reconstruct noncontrast CT from contrast CT and maintain image quality comparable to that of a CT scan originally acquired without contrast. To address the slight structural dissimilarity of the paired CT images (noncontrast CT and contrast CT) due to involuntary physiological motion, we introduce a contrastive loss network derived from the adjacency content-transfer strategy. We evaluate the results of various similarity metrics (MSE, SSIM, NRMSE, PSNR, MAE) and the fitting curve (HU distribution) of the output mapping to estimate the reconstruction performance of the algorithm. To build the model, we randomly select a total of 15,405 CT paired images (noncontrast CT and contrast-enhanced CT) for training and 10,270 CT paired images for testing. The proposed algorithm preserves the robust structures from the contrast-enhanced CT scans and learns the noncontrast attenuation pattern from the noncontrast CT scans. During the evaluation, the deep subtraction residual network achieves higher MSE, MAE, NRMSE, and PSNR scores (by 30%) than those of the baseline models (BEGAN, CycleGAN, Pixel2Pixel) and better simulates the HU curve of noncontrast CT attenuation. After validation based on an analysis of the experimental results, we can report that the noncontrast CT images reconstructed by our proposed algorithm not only preserve the high-quality structures from the contrast-enhanced CT images, but also mimic the CT attenuation of the originally acquired noncontrast CT images.
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http://dx.doi.org/10.1088/1361-6560/ac0758DOI Listing
July 2021

The Chinese Society of Hepatology position statement on the redefinition of fatty liver disease.

J Hepatol 2021 Aug 19;75(2):454-461. Epub 2021 May 19.

Department of Infectious Diseases, Guizhou Provincial People's Hospital, Guiyang 550002, China.

Fatty liver disease associated with metabolic dysfunction is of increasing concern in mainland China, the world's most populous country. The incidence of fatty liver disease is highest in China, surpassing the incidence in European countries and the USA. An international consensus panel recently published an influential report recommending a novel definition of fatty liver disease associated with metabolic dysfunction. This recommendation includes a switch in name from non-alcoholic fatty liver disease (NAFLD) to metabolic (dysfunction)-associated fatty liver disease (MAFLD) and adoption of a set of positive criteria for disease diagnosis that are independent of alcohol intake or other liver diseases. Given the unique importance of this proposal, the Chinese Society of Hepatology (CSH) invited leading hepatologists and gastroenterologists representing their respective provinces and cities to reach consensus on alternative definitions for fatty liver disease from a national perspective. The CSH endorses the proposed change from NAFLD to MAFLD (supported by 95.45% of participants). We expect that the new definition will result in substantial improvements in health care for patients and advance disease awareness, public health policy, and political, scientific and funding outcomes for MAFLD in China.
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http://dx.doi.org/10.1016/j.jhep.2021.05.003DOI Listing
August 2021

Risk factors for early-onset seizures after stroke: A systematicreview and meta-analysis of 18 observational studies.

Brain Behav 2021 06 4;11(6):e02142. Epub 2021 May 4.

Shaanxi University of Chinese Medicine, Shaanxi, China.

Objectives: To systematically evaluate the risk factors of early-onset seizures after stroke, in order to better provide evidence-based results for early detection, identification, targeted prevention, and treatment of this disease.

Methods: PubMed, EMBASE, The Cochrane Library, CNKI, and WanFang databases were searched to collect relevant studies on the risk factors of early-onset seizures after stroke from January 2010 to January 2020. Meta-analysis of all included studies was performed by using RevMan version 5.3 and Stata version 14.0 software.

Results: Eighteen case-control studies with a total sample size of 13,289 cases, including 813 cases with early-onset seizures after stroke, and 12,476 cases with non-early-onset seizures after stroke were included. The results of meta-analysis showed that cortical involvement [Odds Ratio (OR) = 5.00, 95%Confidence Interval (CI) (2.85, 8.74), p < .00001], cerebral infarction with hemorrhagic transformation [OR = 2.77, 95%CI (1.87, 4.11), p < .00001] and intracerebral hemorrhage [OR = 1.83, 95%CI (1.13, 2.97), p = .01]-related factors showed greater association with the occurrence of early-onset seizures after stroke.

Conclusions: These findings suggest that cortical involvement, intracerebral hemorrhage, and cerebral infarction with hemorrhagic transformation are important predictors and risk factors for early seizures after stroke, while the patient's gender, age, NHISS score, alcoholism, smoking, high blood pressure, diabetes, atrial fibrillation, dyslipidemia, receiving surgical treatment, and reperfusion therapy showed no association with the occurrence of early-onset seizures after stroke.
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http://dx.doi.org/10.1002/brb3.2142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213649PMC
June 2021

A missense variant in NDUFA6 confers schizophrenia risk by affecting YY1 binding and NAGA expression.

Mol Psychiatry 2021 Apr 30. Epub 2021 Apr 30.

Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.

Genome-wide association studies (GWASs) have revealed that genetic variants at the 22q13.2 risk locus were robustly associated with schizophrenia. However, the causal variants at this risk locus and their roles in schizophrenia remain elusive. Here we identify the risk missense variant rs1801311 (located in the 1st exon of NDUFA6 gene) as likely causal for schizophrenia at 22q13.2 by disrupting binding of YY1, TAF1, and POLR2A. We systematically elucidated the regulatory mechanisms of rs1801311 and validated the regulatory effect of this missense variant. Intriguingly, rs1801311 physically interacted with NAGA (encodes the alpha-N-acetylgalactosaminidase, which is mainly involved in regulating metabolisms of glycoproteins and glycolipids in lysosome) and showed the most significant association with NAGA expression in the human brain, with the risk allele (G) associated with higher NAGA expression. Consistent with eQTL analysis, expression analysis showed that NAGA was significantly upregulated in brains of schizophrenia cases compared with controls, further supporting that rs1801311 may confer schizophrenia risk by regulating NAGA expression. Of note, we found that NAGA regulates important neurodevelopmental processes, including proliferation and differentiation of neural stem cells. Transcriptome analysis corroborated that NAGA regulates pathways associated with neuronal differentiation. Finally, we independently confirmed the association between rs1801311 and schizophrenia in a large Chinese cohort. Our study elucidates the regulatory mechanisms of the missense schizophrenia risk variant rs1801311 and provides mechanistic links between risk variant and schizophrenia etiology. In addition, this study also revealed the novel role of coding variants in gene regulation and schizophrenia risk, i.e., genetic variant in coding region of a specific gene may confer disease risk through regulating distal genes (act as regulatory variant for distal genes).
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http://dx.doi.org/10.1038/s41380-021-01125-xDOI Listing
April 2021

Genome wide association study identifies four loci for early onset schizophrenia.

Transl Psychiatry 2021 04 27;11(1):248. Epub 2021 Apr 27.

Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.

Early onset schizophrenia (EOS, defined as first onset of schizophrenia before age 18) is a rare form of schizophrenia (SCZ). Though genome-wide association studies (GWASs) have identified multiple risk variants for SCZ, most of the cases included in these GWASs were not stratified according to their first age at onset. To date, the genetic architecture of EOS remains largely unknown. To identify the risk variants and to uncover the genetic basis of EOS, we conducted a two-stage GWAS of EOS in populations of Han Chinese ancestry in this study. We first performed a GWAS using 1,256 EOS cases and 2,661 healthy controls (referred as discovery stage). The genetic variants with a P < 1.0 × 10 in discovery stage were replicated in an independent sample (903 EOS cases and 3,900 controls). We identified four genome-wide significant risk loci for EOS in the combined samples (2,159 EOS cases and 6,561 controls), including 1p36.22 (rs1801133, P = 4.03 × 10), 1p31.1 (rs1281571, P = 4.14 × 10), 3p21.31 (rs7626288, P = 1.57 × 10), and 9q33.3 (rs592927, P = 4.01 × 10). Polygenic risk scoring (PRS) analysis revealed substantial genetic overlap between EOS and SCZ. These discoveries shed light on the genetic basis of EOS. Further functional characterization of the identified risk variants and genes will help provide potential targets for therapeutics and diagnostics.
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http://dx.doi.org/10.1038/s41398-021-01360-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079394PMC
April 2021

Maternal immune activation alters adult behavior, intestinal integrity, gut microbiota and the gut inflammation.

Brain Behav 2021 05 1;11(5):e02133. Epub 2021 Apr 1.

Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.

Background: Schizophrenia is characterized by several core behavioral features, in which the gastrointestinal symptoms are frequently reported. Maternal immune activation (MIA) has been developed in a rodent model to study neurodevelopmental disorders such as schizophrenia. However, the changes in the gut environment of MIA rats remain largely unknown.

Methods: 10 mg/kg of polyinosinic:polycytidylic acid (Poly I:C) on gestational day 9 was intravenously administered to rats to induce MIA in order to assess changes in behavior, the intestinal barrier and microbiota in offspring.

Results: Maternal immune activation offspring shown increased anxiety as indicated by reduced exploration of central area in open field test and decreased exploration of open arms in elevated plus test. Cognitive impairment of MIA offspring was confirmed by reduced exploration of novel arm in Y maze test and deficiency of PPI. Intestinal muscle thickness became thinner and some specific microbial anomalies previously identified clinically were observed in MIA offspring. In addition, an increase of inflammatory responses was found in the gut of MIA offspring.

Conclusions: Maternal immune activation alters behavior, intestinal integrity, gut microbiota and the gut inflammation in adult offspring.
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http://dx.doi.org/10.1002/brb3.2133DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8119836PMC
May 2021

A thick semi-monolithic scintillator detector for clinical PET scanners.

Phys Med Biol 2021 03 12;66(6):065023. Epub 2021 Mar 12.

Center for Advanced Material Diagnostic Technology, Shenzhen Technology University, Shenzhen 518118, People's Republic of China. Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.

Both monolithic and semi-monolithic scintillator positron emission tomography (PET) detectors can measure the depth of interaction with single-ended readout. Usually scintillators with a thickness of 10 mm or less are used since the position resolutions of the detectors degrade as the scintillator thickness increases. In this work, the performance of a 20 mm thick long rectangular semi-monolithic scintillator PET detector was measured by using both single-ended and dual-ended readouts with silicon photomultiplier (SiPM) arrays to provide a high detection efficiency. The semi-monolithic scintillator detector consists of nine lutetium-yttrium oxyorthosilicate slices measuring 1.37 × 51.2 × 20 mm with erythrocyte sedimentation rate foils of 0.065 mm thickness in between the slices. The SiPM array at each end of the scintillator detector consists of 16 × 4 SiPMs with a pixel size of 3.0 × 3.0 mm and a pitch of 3.2 mm. The 64 signals of each SiPM array are processed by using the TOFPET2 application-specific integrated circuit individually. All but the edge slices can be clearly resolved for the detectors with both single-ended and dual-ended readouts. The single-ended readout detector provides an average full width at half maximum (FWHM) Y (continuous direction) position resolution of 2.43 mm, Z (depth direction) position resolution of 4.77 mm, energy resolution of 25.7% and timing resolution of 779 ps. The dual-ended readout detector significantly improves the Y and Z position resolutions, slightly improves the energy and timing resolution at the cost of two photodetectors required for one detector module and provides an average FWHM Y position resolution of 1.97 mm, Z position resolution of 2.60 mm, energy resolution of 21.7% and timing resolution of 718 ps. The energy and timing resolution of the semi-monolithic scintillator detector in this work are worse than those of the segmented scintillator array detector and need to be further improved. The semi-monolithic scintillator detector described in this work reduces costs as compared to the traditional segmented scintillator array detector and reduces the edge effect as compared to the monolithic scintillator detector.
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http://dx.doi.org/10.1088/1361-6560/abe761DOI Listing
March 2021

Blood microRNA Signatures Serve as Potential Diagnostic Biomarkers for Hepatic Sinusoidal Obstruction Syndrome Caused by Containing Pyrrolizidine Alkaloids.

Front Pharmacol 2021 19;12:627126. Epub 2021 Feb 19.

The MOE Key Laboratory for Standardization of Chinese Medicines and the SATCM Key Laboratory for New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

The -induced hepatic sinusoidal obstruction syndrome (HSOS) is closely related to pyrrolizidine alkaloids (PAs), and its prevalence has been increasing worldwide in recent years. However, no effective therapy for PA-induced HSOS in clinics is available, partially due to the failure of quick diagnosis. This study aims to identify blood microRNA (miRNA) signatures as potential biomarkers for PA-induced HSOS in clinics. The microarray-based miRNA profiling was performed on blood samples of the discovery cohort, which consisted of nine patients with HSOS and nine healthy donors. Differentially expressed miRNAs were further confirmed using a validation cohort, which consisted of 20 independent patients with HSOS. In addition, the rat model was established through the oral administration of the total alkaloid extract from to investigate the association of miRNA biomarkers with the progression of HSOS. Bioinformatic analyses, including GO and KEGG enrichment, receiver operating characteristics curve, and correlation analyses were conducted to evaluate the accuracy of the potential miRNA biomarkers. Three miRNAs, namely miR-148a-3p, miR-362-5p, and miR-194-5p, were overexpressed in patients and rats with PA-induced HSOS. These miRNAs were positively related to the severity of liver injury and displayed considerable diagnostic accuracy for patients with HSOS with areas under the curve over 0.87. In summary, this study demonstrated that three miRNAs, hsa-miR-148a-3p, hsa-miR-362-5p, and hsa-miR-194-5p, might serve as potential biomarkers for PA-induced HSOS in clinics.
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http://dx.doi.org/10.3389/fphar.2021.627126DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933570PMC
February 2021

Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented with an Attention Mechanism for Low-dose CT Imaging on Clinical Patient Data from Multiple Anatomical Sites.

IEEE J Biomed Health Inform 2021 Feb 24;PP. Epub 2021 Feb 24.

Dose reduction in computed tomography (CT) has gained considerable attention in clinical applications because it decreases radiation risks. However, a lower dose generates noise in low-dose computed tomography (LDCT) images. Previous deep learning (DL)-based works have investigated ways to improve diagnostic performance to address this ill-posed problem. However, most of them disregard the anatomical differences among different human body sites in constructing the mapping function between LDCT images and their high-resolution normal-dose CT (NDCT) counterparts. In this paper, we propose a novel deep convolutional neural network (CNN) denoising approach by introducing information of the anatomical prior. Instead of designing multiple networks for each independent human body anatomical site, a unified network framework is employed to process anatomical information. The anatomical prior is represented as a pattern of weights of the features extracted from the corresponding LDCT image in an anatomical prior fusion module. To promote diversity in the contextual information, a spatial attention fusion mechanism is introduced to capture many local regions of interest in the attention fusion module. Although many network parameters are saved, the experimental results demonstrate that our method, which incorporates anatomical prior information, is effective in denoising LDCT images. Furthermore, the anatomical prior fusion module could be conveniently integrated into other DL-based methods and avails the performance improvement on multiple anatomical data.
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http://dx.doi.org/10.1109/JBHI.2021.3061758DOI Listing
February 2021

A thick semi-monolithic scintillator detector for clinical PET scanner.

Phys Med Biol 2021 Feb 17. Epub 2021 Feb 17.

Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen, Guangdong, CHINA.

Both monolithic and semi-monolithic scintillator PET detectors can measure the depth of interaction with single-ended readout. Usually scintillators with a thickness of 10 mm or less are used since the position resolutions of the detectors degrade as the scintillator thickness increases. In this work, the performance of a 20 mm thick long rectangular semi-monolithic scintillator PET detector was measured by using both single-ended and dual-ended readouts with SiPM arrays to provide a high detection efficiency. The semi-monolithic scintillator detector consists of 9 LYSO slices measuring 1.37×51.2×20 mm3 with ESR foils of 0.065 mm thick in between the slices. The SiPM array at each end of the scintillator detector consists of 16×4 SiPMs with a pixel size of 3.0×3.0 mm2 and a pitch of 3.2 mm. The 64 signals of each SiPM array are processed by using the TOFPET2 ASIC individually. All but the edge slices can be clearly resolved for the detectors with both single-ended and dual-ended readouts. The single-ended readout detector provides an average full width at half maximum (FWHM) Y (continuous direction) position resolution of 2.43 mm, Z (depth direction) position resolution of 4.77 mm, energy resolution of 25.7% and timing resolution of 779 ps. The dual-ended readout detector significantly improves the Y and Z position resolutions, slightly improve the energy and timing resolution at the cost of two photodetectors required for one detector module and provides an average FWHM Y position resolution of 1.97 mm, Z position resolution of 2.60 mm, energy resolution of 21.7% and timing resolution of 718 ps. The energy and timing resolution of the semi-monolithic scintillator detector of this work are worse than those of the segmented scintillator array detector and need to be further improved. The semi-monolithic scintillator detector of this work reduces the cost of detector as compared to the traditional segmented scintillator array detector and reduces the edge effect as compared to the monolithic scintillator detector.
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http://dx.doi.org/10.1088/1361-6560/abe761DOI Listing
February 2021

LCPR-Net: low-count PET image reconstruction using the domain transform and cycle-consistent generative adversarial networks.

Quant Imaging Med Surg 2021 Feb;11(2):749-762

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Background: Reducing the radiation tracer dose and scanning time during positron emission tomography (PET) imaging can reduce the cost of the tracer, reduce motion artifacts, and increase the efficiency of the scanner. However, the reconstructed images to be noisy. It is very important to reconstruct high-quality images with low-count (LC) data. Therefore, we propose a deep learning method called LCPR-Net, which is used for directly reconstructing full-count (FC) PET images from corresponding LC sinogram data.

Methods: Based on the framework of a generative adversarial network (GAN), we enforce a cyclic consistency constraint on the least-squares loss to establish a nonlinear end-to-end mapping process from LC sinograms to FC images. In this process, we merge a convolutional neural network (CNN) and a residual network for feature extraction and image reconstruction. In addition, the domain transform (DT) operation sends a priori information to the cycle-consistent GAN (CycleGAN) network, avoiding the need for a large amount of computational resources to learn this transformation.

Results: The main advantages of this method are as follows. First, the network can use LC sinogram data as input to directly reconstruct an FC PET image. The reconstruction speed is faster than that provided by model-based iterative reconstruction. Second, reconstruction based on the CycleGAN framework improves the quality of the reconstructed image.

Conclusions: Compared with other state-of-the-art methods, the quantitative and qualitative evaluation results show that the proposed method is accurate and effective for FC PET image reconstruction.
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http://dx.doi.org/10.21037/qims-20-66DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779905PMC
February 2021

An improved patch-based regularization method for PET image reconstruction.

Quant Imaging Med Surg 2021 Feb;11(2):556-570

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Background: Statistical reconstruction methods based on penalized maximum likelihood (PML) are being increasingly used in positron emission tomography (PET) imaging to reduce noise and improve image quality. Wang and Qi proposed a patch-based edge-preserving penalties algorithm that can be implemented in three simple steps: a maximum-likelihood expectation-maximization (MLEM) image update, an image smoothing step, and a pixel-by-pixel image fusion step. The pixel-by-pixel image fusion step, which fuses the MLEM updated image and the smoothed image, involves a trade-off between preserving the fine structural features of an image and suppressing noise. Particularly when reconstructing images from low-count data, this step cannot preserve fine structural features in detail. To better preserve these features and accelerate the algorithm convergence, we proposed to improve the patch-based regularization reconstruction method.

Methods: Our improved method involved adding a total variation (TV) regularization step following the MLEM image update in the patch-based algorithm. A feature refinement (FR) step was then used to extract the lost fine structural features from the residual image between the TV regularized image and the fused image based on patch regularization. These structural features would then be added back to the fused image. With the addition of these steps, each iteration of the image should gain more structural information. A brain phantom simulation experiment and a mouse study were conducted to evaluate our proposed improved method. Brain phantom simulation with added noise were used to determine the feasibility of the proposed algorithm and its acceleration of convergence. Data obtained from the mouse study were divided into event count sets to validate the performance of the proposed algorithm when reconstructing images from low-count data. Five criteria were used for quantitative evaluation: signal-to-noise ratio (SNR), covariance (COV), contrast recovery coefficient (CRC), regional relative bias, and relative variance.

Results: The bias and variance of the phantom brain image reconstructed using the patch-based method were 0.421 and 5.035, respectively, and this process took 83.637 seconds. The bias and variance of the image reconstructed by the proposed improved method, however, were 0.396 and 4.568, respectively, and this process took 41.851 seconds. This demonstrates that the proposed algorithm accelerated the reconstruction convergence. The CRC of the phantom brain image reconstructed using the patch-based method was iterated 20 times and reached 0.284, compared with the proposed method, which reached 0.446. When using a count of 5,000 K data obtained from the mouse study, both the patch-based method and the proposed method reconstructed images similar to the ground truth image. The intensity of the ground truth image was 88.3, and it was located in the 102 row and the 116 column. However, when the count was reduced to below 40 K, and the patch-based method was used, image quality was significantly reduced. This effect was not observed when the proposed method was used. When a count of 40 K was used, the image intensity was 58.79 when iterated 100 times by the patch-based method, and it was located in the 102 row and the 116 column, while the intensity when iterated 50 times by the proposed method was 63.83. This suggests that the proposed method improves image reconstruction from low-count data.

Conclusions: This improved method of PET image reconstruction could potentially improve the quality of PET images faster than other methods and also produce better reconstructions from low-count data.
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http://dx.doi.org/10.21037/qims-20-19DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779915PMC
February 2021

Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.

Biomed Phys Eng Express 2020 02 18;6(2):025009. Epub 2020 Feb 18.

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.

Background: Magnetic resonance cine imaging is the accepted standard for cardiac functional assessment. Left ventricular (LV) segmentation plays a key role in volumetric functional quantification of the heart. Conventional manual analysis is time-consuming and observer-dependent. Automated segmentation approaches are needed to improve the clinical workflow of cardiac functional quantification. Recently, deep-learning networks have shown promise for efficient LV segmentation.

Purpose: The routinely used V-Net is a convolutional network that segments images by passing features from encoder to decoder. In this study, this method was advanced as DenseV-Net by replacing the convolutional block with a densely connected algorithm and dense calculations to alleviate the vanishing-gradient problem, prevent exploding gradients, and to strengthen feature propagation. Thirty patients were scanned with a 3 Tesla MR imager. ECG-free, free-breathing, real-time cines were acquired with a balanced steady-state free precession technique. Linear regression and the dice similarity coefficient (DSC) were performed to evaluate LV segmentation performance of the classic neural networks FCN, UNet, V-Net, and the proposed DenseV-net methods, using manual analysis as the reference. Slice-based LV function was compared among the four methods.

Results: Thirty slices from eleven patients were randomly selected (each slice contained 73 images), and the LVs were segmented using manual analysis, UNet, FCN, V-Net, and the proposed DenseV-Net methods. A strong correlation of the left ventricular areas was observed between the proposed DenseV-Net network and manual segmentation (R = 0.92), with a mean DSC of 0.90 ± 0.12. A weaker correlation was found between the routine V-Net, UNet, FCN, and manual segmentation methods (R = 0.77, 0.74, 0.76, respectively) with a lower mean DSC (0.85 ± 0.13, 0.84 ± 0.16, 0.79 ± 0.17, respectively). Additionally, the proposed DenseV-Net method was strongly correlated with the manual analysis in slice-based LV function quantification compared with the state-of-art neural network methods V-Net, UNet, and FCN.

Conclusion: The proposed DenseV-Net method outperforms the classic convolutional networks V-Net, UNet, and FCN in automated LV segmentation, providing a novel way for efficient heart functional quantification and the diagnosis of cardiac diseases using cine MRI.
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http://dx.doi.org/10.1088/2057-1976/ab7363DOI Listing
February 2020

Temporal feature prior-aided separated reconstruction method for low-dose dynamic myocardial perfusion computed tomography.

Phys Med Biol 2021 02 3;66(4):045012. Epub 2021 Feb 3.

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.

Dynamic myocardial perfusion computed tomography (DMP-CT) is an effective medical imaging technique for coronary artery disease diagnosis and therapy guidance. However, the radiation dose received by the patient during repeated CT scans is a widespread concern of radiologists because of the increased risk of cancer. The sparse few-view CT scanning protocol can be a feasible approach to reduce the radiation dose of DMP-CT imaging; however, an advanced reconstruction algorithm is needed. In this paper, a temporal feature prior-aided separated reconstruction method (TFP-SR) for low-dose DMP-CT images reconstruction from sparse few-view sinograms is proposed. To implement the proposed method, the objective perfusion image is divided into the baseline fraction and the enhancement fraction introduced by the arrival of the contrast agent. The core of the proposed TFP-SR method is the utilization of the temporal evolution information that naturally exists in the DMP-CT image sequence to aid the enhancement image reconstruction from limited data. The temporal feature vector of an image pixel is defined by the intensities of this pixel in the pre-reconstructed enhancement sequence, and the connection between two related features is calculated via a zero-mean Gaussian function. A prior matrix is constructed based on the connections between the extracted temporal features and used in the iterative reconstruction of the enhancement images. To evaluate the proposed method, the conventional filtered back-projection algorithm, the total variation regularized PWLS (PWLS-TV) and the prior image constrained compressed sensing are compared in this paper based on studies on a digital extended cardiac-torso (XCAT) thoracic phantom and a preclinical porcine DMP-CT data set that take image misregistration into account. The experimental results demonstrate that the proposed TFP-SR method has superior performance in sparse DMP-CT images reconstruction in terms of image quality and the analyses of the time attenuation curve and hemodynamic parameters.
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http://dx.doi.org/10.1088/1361-6560/abd4baDOI Listing
February 2021

Insulin Resistance and Oxidative Stress: In Relation to Cognitive Function and Psychopathology in Drug-Naïve, First-Episode Drug-Free Schizophrenia.

Front Psychiatry 2020 19;11:537280. Epub 2020 Nov 19.

Department of Psychiatry, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.

The present study aimed to examine whether insulin resistance and oxidative stress are associated with cognitive impairment in first-episode drug-free schizophrenia (SZ) patients. Ninety first-episode SZ patients and 70 healthy controls were enrolled. Fasting insulin (FINS) and markers of oxidative stress [oxidized glutathione (GSSG), superoxide dismutase (SOD), nitric oxide (NO) and uric acid (UA) levels] were measured in serum before pharmacological treatment was initiated. Psychiatric symptoms and cognitive function were assessed with the Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery (MCCB), respectively. In addition, the homeostatic model assessment of insulin resistance (HOMA-IR) was also studied. HOMA-IR and serum levels of GSSG and NO were significantly higher in SZ patients than in healthy controls ( < 0.001), while the serum levels of SOD were significantly lower than in healthy controls ( < 0.001). HOMA-IR, GSSG and NO levels were significantly correlated to the total cognitive function scores of the patient group ( = -0.345,-0.369,-0.444, respectively, < 0.05). But these factors were not co-related to the cognitive functions in the healthy control group. And, levels of SOD, UA were not associated with the total cognitive function scores in both the patient and the healthy control groups. NO was positively correlated with general pathological and the total score in the PANSS, and was negatively correlated with six cognitive domains ( = -0.316 to -0.553, < 0.05). The levels of insulin resistance and oxidative stress are elevated, and correlated with the severity of cognitive impairment in drug-naïve, first-episode SZ patients. Treatment approaches targeting on reducing insulin resistance and oxidative stress may improve cognitive function in SZ patients.
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http://dx.doi.org/10.3389/fpsyt.2020.537280DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732418PMC
November 2020

Novel Risk Loci Associated With Genetic Risk for Bipolar Disorder Among Han Chinese Individuals: A Genome-Wide Association Study and Meta-analysis.

JAMA Psychiatry 2021 Mar;78(3):320-330

Affiliated Wuhan Mental Health Center, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

Importance: The genetic basis of bipolar disorder (BD) in Han Chinese individuals is not fully understood.

Objective: To explore the genetic basis of BD in the Han Chinese population.

Design, Setting, And Participants: A genome-wide association study (GWAS), followed by independent replication, was conducted to identify BD risk loci in Han Chinese individuals. Individuals with BD were diagnosed based on DSM-IV criteria and had no history of schizophrenia, mental retardation, or substance dependence; individuals without any personal or family history of mental illnesses, including BD, were included as control participants. In total, discovery samples from 1822 patients and 4650 control participants passed quality control for the GWAS analysis. Replication analyses of samples from 958 patients and 2050 control participants were conducted. Summary statistics from the European Psychiatric Genomics Consortium 2 (PGC2) BD GWAS (20 352 cases and 31 358 controls) were used for the trans-ancestry genetic correlation analysis, polygenetic risk score analysis, and meta-analysis to compare BD genetic risk between Han Chinese and European individuals. The study was performed in February 2020.

Main Outcomes And Measures: Single-nucleotide variations with P < 5.00 × 10-8 were considered to show genome-wide significance of statistical association.

Results: The Han Chinese discovery GWAS sample included 1822 cases (mean [SD] age, 35.43 [14.12] years; 838 [46%] male) and 4650 controls (mean [SD] age, 27.48 [5.97] years; 2465 [53%] male), and the replication sample included 958 cases (mean [SD] age, 37.82 [15.54] years; 412 [43%] male) and 2050 controls (mean [SD] age, 27.50 [6.00] years; 1189 [58%] male). A novel BD risk locus in Han Chinese individuals was found near the gene encoding transmembrane protein 108 (TMEM108, rs9863544; P = 2.49 × 10-8; odds ratio [OR], 0.650; 95% CI, 0.559-0.756), which is required for dendritic spine development and glutamatergic transmission in the dentate gyrus. Trans-ancestry genetic correlation estimation (ρge = 0.652, SE = 0.106; P = 7.30 × 10-10) and polygenetic risk score analyses (maximum liability-scaled Nagelkerke pseudo R2 = 1.27%; P = 1.30 × 10-19) showed evidence of shared BD genetic risk between Han Chinese and European populations, and meta-analysis identified 2 new GWAS risk loci near VRK2 (rs41335055; P = 4.98 × 10-9; OR, 0.849; 95% CI, 0.804-0.897) and RHEBL1 (rs7969091; P = 3.12 × 10-8; OR, 0.932; 95% CI, 0.909-0.956).

Conclusions And Relevance: This GWAS study identified several loci and genes involved in the heritable risk of BD, providing insights into its genetic architecture and biological basis.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.3738DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711567PMC
March 2021

Abnormal functional connectivity based on nodes of the default mode network in first-episode drug-naive early-onset schizophrenia.

Psychiatry Res 2021 01 18;295:113578. Epub 2020 Nov 18.

Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry of Xinxiang Medical University, Xinxiang 453002, China; International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China. Electronic address:

Schizophrenia is considered a connectivity disorder. Further, the functional connectivity (FC) of the default-mode network (DMN) has gained the interest of researchers. However, few studies have been conducted on the abnormal connectivity of DMN in early-onset schizophrenia (EOS). In this study, the key brain regions of the DMN were used as seed regions to analyze the FC of the whole brain in EOS. When the seed was located in the medial prefrontal cortex (mPFC), patients with EOS exhibited decreased FC between mPFC and other brain regions compared with healthy controls (voxel P value < 0.001, cluster P value < 0.05, Gaussian random field corrected). When the seed was located in the posterior cingulate cortex (PCC), the FC between PCC and other brain regions was enhanced and weakened (voxel P value < 0.001, cluster P value < 0.05, Gaussian random field corrected), and PCC connectivity with the right parahippocampal gyrus was associated with Positive and Negative Syndrome Scale scores for the general score (r = -0.315, P = 0.02). The results showed that the FC within the DMN and that between DMN and visual networks were abnormal, suggesting that the DMN might be involved in the pathogenesis of EOS.
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http://dx.doi.org/10.1016/j.psychres.2020.113578DOI Listing
January 2021

Solute Carrier Family 1 () Contributes to Susceptibility and Psychopathology Symptoms of Schizophrenia in the Han Chinese Population.

Front Psychiatry 2020 23;11:559210. Epub 2020 Sep 23.

Department of Mental Health, The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, China.

Objective: Schizophrenia (SZ) is a common and complex psychiatric disorder that has a significant genetic component. The glutamate hypothesis describes one possible pathogenesis of SZ. The solute carrier family 1 gene () is one of several genes thought to play a critical role in regulating the glutamatergic system and is strongly implicated in the pathophysiology of SZ. In this study, we identify polymorphisms of the gene that may confer susceptibility to SZ in the Han Chinese population.

Methods: We genotyped 36 single-nucleotide polymorphisms (SNPs) using Illumina GoldenGate assays on a BeadStation 500G Genotyping System in 528 paranoid SZ patients and 528 healthy controls. Psychopathology was rated by the Positive and Negative Symptom Scale.

Results: Significant associations were found in genotype and allele frequencies for SNPs rs10815017 ( = 0.002, 0.030, respectively) and rs2026828 ( = 0.020, 0.005, respectively) between SZ and healthy controls. There were significant associations in genotype frequency at rs6476875 ( = 0.020) and rs7024664 ( = 0.021) and allele frequency at rs3780412 ( = 0.026) and rs10974573 ( = 0.047) between SZ and healthy controls. Meanwhile, significant differences were found in genotype frequency at rs10815017 ( = 0.015), rs2026828 ( = 0.011), and rs3780411 ( = 0.040) in males, and rs7021569 in females ( = 0.020) between cases and controls when subdivided by gender. Also, significant differences were found in allele frequency at rs2026828 ( = 0.003), and rs7021569 ( = 0.045) in males, and rs10974619 in females ( = 0.044). However, those associations disappeared after Bonferroni's correction ('s > 0.05). Significant associations were found in the frequencies of four haplotypes (AA, CA, AGA, and GG) between SZ and healthy controls ( = 3.974, 7.433, 4.699, 4.526, = 0.046, 0.006, 0.030, 0.033, respectively). There were significant associations between rs7032326 genotypes and PANSS total, positive symptoms, negative symptoms, and general psychopathology in SZ ( = 0.002, 0.011, 0.028, 0.008, respectively).

Conclusion: The present study provides further evidence that may be not a susceptibility gene for SZ. However, the genetic variations of may affect psychopathology symptoms.
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http://dx.doi.org/10.3389/fpsyt.2020.559210DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538510PMC
September 2020

DaNet: dose-aware network embedded with dose-level estimation for low-dose CT imaging.

Phys Med Biol 2021 01 13;66(1):015005. Epub 2021 Jan 13.

Wuhan National Laboratory for Optoelectronics, Huazhong University of Science & Technology, Wuhan 430074, People's Republic of China. School of Computer Science & Technology, Huazhong University of Science & Technology, Wuhan 430074, People's Republic of China. Key Laboratory of Information Storage System, Engineering Research Center of Data Storage Systems and Technology, Ministry of Education of China, Wuhan 430074, People's Republic of China. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.

Many deep learning (DL)-based image restoration methods for low-dose CT (LDCT) problems directly employ the end-to-end networks on low-dose training data without considering dose differences. However, the radiation dose difference has a great impact on the ultimate results, and lower doses increase the difficulty of restoration. Moreover, there is increasing demand to design and estimate acceptable scanning doses for patients in clinical practice, necessitating dose-aware networks embedded with adaptive dose estimation. In this paper, we consider these dose differences of input LDCT images and propose an adaptive dose-aware network. First, considering a large dose distribution range for simulation convenience, we coarsely define five dose levels in advance as lowest, lower, mild, higher and highest radiation dose levels. Instead of directly building the end-to-end mapping function between LDCT images and high-dose CT counterparts, the dose level is primarily estimated in the first stage. In the second stage, the adaptively learned low-dose level is used to guide the image restoration process as the pattern of prior information through the channel feature transform. We conduct experiments on a simulated dataset based on original high dose parts of American Association of Physicists in Medicine challenge datasets from the Mayo Clinic. Ablation studies validate the effectiveness of the dose-level estimation, and the experimental results show that our method is superior to several other DL-based methods. Specifically, our method provides obviously better performance in terms of the peak signal-to-noise ratio and visual quality reflected in subjective scores. Due to the dual-stage process, our method may suffer limitations under more parameters and coarse dose-level definitions, and thus, further improvements in clinical practical applications with different CT equipment vendors are planned in future work.
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http://dx.doi.org/10.1088/1361-6560/abc5ccDOI Listing
January 2021

Efficacy and Safety of All-oral Emitasvir and Sofosbuvir in Patients with Genotype 1b HCV Infections without Cirrhosis.

J Clin Transl Hepatol 2020 Sep 11;8(3):255-261. Epub 2020 Sep 11.

Department of Infectious Diseases, Wuhan central hospital, Wuhan, Hubei, China.

Emitasvir is a new type of hepatitis C virus (HCV) nonstructural protein 5A (NS5A) inhibitor, and the data of phase 2 trial has shown emitasvir-sofosbuvir to have good safety and tolerance. We conducted this phase 3 trial to further verify the efficacy and safety. We evaluated the antiviral activity and safety of a 12-week regimen of emitasvir phosphate (100 mg) combined with sofosbuvir (400 mg) once daily in non-cirrhotic patients with genotype 1 HCV infection. The primary endpoint was a sustained virological response at 12 weeks (SVR12) after the end of treatment. Of the 362 patients enrolled in the trial, 39.8% were male, 99.2% had HCV genotype 1b, 0.8% had genotype 1a and 79.8% were treatment-naïve. The average age was 47.2 years. All patients completed the treatment and follow-up. All 3 patients with genotype 1a achieved SVR. Two genotype 1b treatment-naïve patients experienced virologic relapse. The rate of SVR12 was 99.7% (358/359), and SVR24 was 99.4% (357/359) in genotype 1b. Overall, 36.2% had resistance-associated substitutions (RASs) in NS5A and 98.3% had RASs in NS5B at baseline. The RASs at baseline had no effect on the rates of response. Serious adverse events were reported in 16 patients and were not related to emitasvir-sofosbuvir. Most adverse events did not require therapy. The 12 weeks of treatment with emitasvir-sofosbuvir was a highly efficient and safe treatment for a wide range of patients with HCV genotype 1b infection without cirrhosis, who had not been treated or who had been treated with interferon-based regimen previously.
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http://dx.doi.org/10.14218/JCTH.2020.00031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7562795PMC
September 2020

Coblopasvir and sofosbuvir for treatment of chronic hepatitis C virus infection in China: A single-arm, open-label, phase 3 trial.

Liver Int 2020 11 13;40(11):2685-2693. Epub 2020 Oct 13.

Department of Hepatology, the First Hospital of Jilin University, Changchun, China.

Background & Aim: An affordable, pangenotypic regimen remains as an unmet medical need for chronic hepatitis C patients in China. This single-arm, open-label, multicenter, phase 3 trial evaluated the efficacy and safety of coblopasvir, a pangenotypic non-structural protein 5A (NS5A) inhibitor, combined with sofosbuvir for treating Chinese patients with chronic hepatitis C virus (HCV) infection.

Methods: Treatment-naïve and interferon-experienced adult patients, including those with advanced fibrosis (F3) or compensated cirrhosis (F4), were treated with a universal, combinational regimen of coblopasvir 60 mg and sofosbuvir 400 mg, once daily, for 12 weeks. The primary efficacy endpoint was sustained virological response at post-treatment week 12 (SVR12).

Results: Overall, 371 patients (men, 51%; age, 47 ± 11 years; genotype 1a < 1%, 1b 48%, 2a 26%, 3a 6%, 3b 7% and 6 12%) were enrolled from 19 sites. Fifty-one patients (14%) had F3, 39 patients (11%) had F4 and 39 patients (11%) were interferon experienced. The overall SVR12 was 97% (95% CI, [94%, 98%]) for the full analysis set and was equal to or above 90% for all predefined subsets. Ten patients (3%) experienced virological relapse and two patients did not complete follow-up. No adverse events (AEs) occurred at a frequency ≥5%, and the most often reported AEs (≥1%) were neutropenia and fatigue. The majority of AEs were mild to moderate and transient without specific medical intervention.

Conclusions: The universal, pangenotypic combo of coblopasvir plus sofosbuvir is an efficacious and safe treatment for Chinese patients monoinfected with HCV of genotype 1, 2, 3 and 6, including those with compensated cirrhosis.

Lay Summary: The regimen of coblopasvir and sofosbuvir is a safe and effective treatment for Chinese patients with genotype 1, 2, 3 and 6 HCV infection, including those with compensated cirrhosis. Therefore, this regimen would be a novel choice of treatment for this patient population.
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http://dx.doi.org/10.1111/liv.14633DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7702130PMC
November 2020

Low-dose CT reconstruction method based on prior information of normal-dose image.

J Xray Sci Technol 2020 ;28(6):1091-1111

Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Background: Radiation risk from computed tomography (CT) is always an issue for patients, especially those in clinical conditions in which repeated CT scanning is required. For patients undergoing repeated CT scanning, a low-dose protocol, such as sparse scanning, is often used, and consequently, an advanced reconstruction algorithm is also needed.

Objective: To develop a novel algorithm used for sparse-view CT reconstruction associated with the prior image.

Methods: A low-dose CT reconstruction method based on prior information of normal-dose image (PI-NDI) involving a transformed model for attenuation coefficients of the object to be reconstructed and prior information application in the forward-projection process was used to reconstruct CT images from sparse-view projection data. A digital extended cardiac-torso (XCAT) ventral phantom and a diagnostic head phantom were employed to evaluate the performance of the proposed PI-NDI method. The root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR) and mean percent absolute error (MPAE) of the reconstructed images were measured for quantitative evaluation of the proposed PI-NDI method.

Results: The reconstructed images with sparse-view projection data via the proposed PI-NDI method have higher quality by visual inspection than that via the compared methods. In terms of quantitative evaluations, the RMSE measured on the images reconstructed by the PI-NDI method with sparse projection data is comparable to that by MLEM-TV, PWLS-TV and PWLS-PICCS with fully sampled projection data. When the projection data are very sparse, images reconstructed by the PI-NDI method have higher PSNR values and lower MPAE values than those from the compared algorithms.

Conclusions: This study presents a new low-dose CT reconstruction method based on prior information of normal-dose image (PI-NDI) for sparse-view CT image reconstruction. The experimental results validate that the new method has superior performance over other state-of-art methods.
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http://dx.doi.org/10.3233/XST-200716DOI Listing
January 2020

Risk Factor Analysis of Acute Kidney Injury After Microwave Ablation of Hepatocellular Carcinoma: A Retrospective Study.

Front Oncol 2020 4;10:1408. Epub 2020 Sep 4.

Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China.

Acute kidney injury (AKI) is a recently observed side effect in patients after microwave ablation (MWA) of hepatocellular carcinoma (HCC) and is associated with negative outcomes. The aim of this study is to explore the risk factors of affecting the occurrence of AKI (stages 1b, 2, and 3), because they have a higher mortality rate than patients with AKI (stage 1a) and without AKI. In this retrospective study, a total of 1,214 patients with HCC who were treated with MWA under ultrasound (US) guidance in our department between January 2005 and November 2017 were enrolled. We evaluated the influence of 20 risk factors. Univariate and multivariate analysis were used for statistical analysis. The possible risk factors of AKI after MWA for HCC were summarized. AKI, AKI (stage 1a), and AKI (stages 1b, 2, and 3) after MWA were found in 34, 15, and 19 patients (2.80, 1.24, and 1.57%), respectively. Among 34 patients with AKI, 10 cases with AKI (stage 1a) and 6 cases with AKI (stages 1b, 2, and 3) recovered before their discharge without any treatment for AKI and 9 cases with AKI (stages 1b, 2, and 3) with further treatment. Four cases who had chronic renal failure before MWA of liver accepted renal dialysis. By univariate analysis, the number of antenna insertions ( = 0.027, OR = 3.3), MWA time ≥20 min ( = 0.029, OR = 4.3), creatinine (Cr)-pre above the upper limit of the reference value ( < 0.001, OR = 35.5), albumin (Alb)-pre ( = 0.030, OR = 0.9), and red blood cell (RBC)-pre ( < 0.001, OR = 0.3) were significant risk factors. By multivariate analysis, Cr-pre ≥ 110 μmol/L ( < 0.001, OR = 31.4) and MWA time ≥20 min ( = 0.043 OR = 9.9) were the independent risk factors. AKI (stages 1b, 2, and 3) is a relatively serious complication after MWA for HCC, which is related to MWA time and Cr-pre. It requires attention by clinicians. So it is of great necessity to assess the Cr-pre level and reduce the MWA time to <20 min to minimize the risk of AKI after MWA for HCC.
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http://dx.doi.org/10.3389/fonc.2020.01408DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498714PMC
September 2020
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