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• For the reason that Polarimetric synthetic aperture radar (PolSAR) data is complex-valued, we use a complex-valued classification network in this paper. • PolSAR data has the problem of lacking labeled samples, so we make full use of a small number of labeled samples to propose a novel semi-supervised recurrent classification method. • The problem of network overfitting could be solved to some extent by our methods, especially for very small training samples and large testing samples. • The classification accuracy of three datasets are improved only by using very small number of labeled training samples. Due to that polarimetric synthetic aperture radar (PolSAR) data suffers from missing labeled samples and complex-valued data, this article presents a novel semi-supervised PolSAR terrain classification method named recurrent complex-valued convolution neural network (RCV-CNN) which combines semi-supervised learning and complex-valued convolution neural network (CV-CNN). The proposed method only needs a small number of labeled samples to achieve good classification results. First, a Wishart classifier is used to select some reliable PolSAR samples. Then, two new semi-supervised deep classification model RCV-CNN1 and RCV-CNN2 have been proposed to improve PolSAR image classification accuracy. Moreover, our proposed methods could solve the problem of network overfitting phenomenon to some extend when the number of training samples is too small. Finally, three real PolSAR dataset are applied to verify the effectiveness of our algorithms. Compared with the other five state-of-the-art methods, the proposed RCV-CNN1 and RCV-CNN2 classification models show good performance in accuracy and generalization. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia (SCZ) is a complex, heritable, and devastating psychiatric disorder. Mutations in the members of ABC transporters have been associated with psychiatric illnesses. Aims: In this study, we investigated whether 9 SNPs in ABCB1 (rs6946119, rs28401781, rs4148739, and rs3747802), ABCB6 (rs1109866, rs1109867, rs3731885, and rs3755047), and ABCG1 (rs182694) contribute to the risk of SCZ in a Han Chinese population. Methods: We conducted a case-control study in a Han Chinese population, involving 1,034 SCZ patients and 1,034 unrelated healthy controls to genotype 9 SNPs. Results: The analysis demonstrated that rs182694 of ABCG1 was significantly different between SCZ patients and controls as to allele (rs182694: p = 0.0070, χ2 = 7.27) and genotype frequencies (rs182694: p = 0.0013, χ2 = 13.35). Conclusions: Our findings support an association between ABCG1 polymorphism and SCZ in a Han Chinese population. [ABSTRACT FROM AUTHOR]

Highlights • Type I interferon induces antiviral response to inhibit PRRSV early replication. • IRF7 transcription and expression are counteracted by PRRSV infection. • PRRSV nsp7 impair IRF7 transcription and expression. Abstract Porcine reproductive and respiratory syndrome (PRRS) is an economically important disease with a significant impact on the pig industry. It is caused by PRRS virus (PRRSV), which predominantly infects and replicates in porcine pulmonary alveolar macrophages (PAMs). We pretreated PAMs with porcine interferon (IFN)-α to induce an antiviral state within the cells and subsequently infected them with highly pathogenic PRRSV. Changes in global gene expression in IFN-α-pretreated PAMs in response to PRRSV infection were determined by RNA-sequence analysis and confirmed by real-time PCR. We found that IRF7 and other antiviral interferon stimulating genes (ISG)s were suppressed by PRRSV infection. Further studies demonstrated that PRRSV could down-regulate the expression of IRF7 by the non-structure protein 7 (nsp7). In conclusion, PRRSV infection had a strong immunosuppressive effect of IFN. PRRSV nsp7 inhibits the expression of IRF7, thereby down-regulating the expression of IFN and downstream ISGs and facilitated the virus to replicate. [ABSTRACT FROM AUTHOR]

Background: . The development of depressive symptoms (DSs) is a complex process caused by both genetic and environmental factors. CEND1 gene coordinates cell division, differentiation and maturation of neural precursor cells, which affects brain structure and function. Our study investigated whether CEND1 was a genetic factor for DSs, particularly under negative life events.Methods: . 272 freshmen with DSs and 467 healthy controls were recruited via the Center for Epidemiologic Studies Depression Scale (CES-D). The adolescent Self-rating Life Event Checklist (ASLEC) was adopted to assess stressful life events during the past 12 months. Two SNPs (rs7946354, rs6597982) within the CEND1 gene were genotyped using Agena MassARRAY iPLEX technology. We combined generalized multifactor dimensionality reduction (GMDR) with RStudio programming to assess the direct association and gene-environment interaction (G × E).Results: . Rs7946354 was associated with DSs in an overdominant model (GT vs. GG+TT). In addition, both rs7946354 and rs6597982 had considerable impacts on negative life events. GMDR showed a statistical G × E that the AG genotype of rs6597982 and GT genotype of rs7946354 contribute to the maximum risk of DSs under high negative life events.Limitations: . Only two single nucleotide polymorphisms (SNPs) were examined. Verification studies with bigger sample size and more varied demographic background information could be adopted to further support the generalization of these findings.Conclusions: .CEND1 can potentially cause high sensitivity to life events and affect DSs especially in the presence of negative life events, which contribute to the field of depression prevention and treatment. [ABSTRACT FROM AUTHOR]

Schizophrenia is a kind of neurodevelopmental disease. Epidemiological data associates schizophrenia with prenatal exposure to famine. Relevant prenatal protein deprivation (PPD) rodent models support this result by observing decreasing prepulse inhibition, altered hippocampal morphology and impaired memory in offspring. All these abnormalities are highly consistent with the pathophysiology of schizophrenia. We developed a prenatal famine rat model by restricting daily diet of the pregnant rat to 50% of low protein diet. A metabolomics study of prefrontal cortex was performed to integrate GC-TOFMS and UPLC-QTOFMS. Thirteen controls and thirteen famine offspring were used to differentiate in PLS-DA (partial least squares-discriminate analysis) model. Furthermore, metabolic pathways and diseases were enriched via KEGG and HMDB databases, respectively. A total of 67 important metabolites were screened out according to the multivariate analysis. Schizophrenia was the most statistical significant disease (P = 0.0016) in our famine model. These metabolites were enriched in key metabolic pathways related to energy metabolism and glutamate metabolism. Based on these important metabolites, further discussion speculated famine group was characterized by higher level of oxidized damage compared to control group. We proposed that oxidative stress might be the pathogenesis of prenatal undernutrition which is induced schizophrenia. [ABSTRACT FROM AUTHOR]

Purpose: Venlafaxine is one of the commonly prescribed antidepressants for major depressive disorder (MDD). Accumulated evidence revealed the involvement of glutamatergic system in the pathophysiology of MDD and antidepressant treatment.  Methods: We recruited 193 MDD patients who have been taking venlafaxine for 6 weeks, and investigated whether single nucleotide polymorphisms (SNPs) in GSK-3β and BDNF were associated with treatment response. Nine SNPs were selected randomly depending on association studies. Efficacy of treatment was determined by 17-item Hamilton Rating Scale. Allele and genotype frequencies were compared between responders and nonresponders. Results: After adjusting the false discovery rate, no significant difference was observed between response and nonresponse groups in allele or genotype distributions after venlafaxine treatment for 6 weeks. Conclusion: Our results indicated that genetic variants in the GSK-3β and BDNF may not be associated with treatment response in MDD patients treated with venlafaxine. [ABSTRACT FROM AUTHOR]

Despite there is a wide range of antidepressants available, with various mechanisms of actions, the efficacy of current therapeutic options is yet satisfactory. Previous shreds of evidence have indicated that genetics, cognitive, neuroendocrine, as well as personality factors, are all intrinsically linked and contribute to the diversity of treatment outcomes. We, therefore, sought to investigate this hypothesis in this study. Based on 610 samples treated with a selection of serotonin reuptake inhibitor (SSRI), serotonin-norepinephrine reuptake inhibitors (SNRI), noradrenergic and specific serotonergic antidepressant (NaSSA) or tricyclic antidepressant (TCA), we compared the therapeutic effects of these four classes of drugs by survival analyses. Pharmacogenomic and survival analyses were carried out to explore the hereditary factors for curative effect and the accumulation of genetic factors was further discussed through pathway analysis and the global test. We built a machine learning-based prediction model that integrates genetic and non-genetic factors (including cognition, endocrinology, personality intelligence) to distinguish drug efficacy in single class drug situations. The values of the non-genetic makers after 6 weeks' treatment were collected to evaluate the efficacy of the model. Our results from the 6-week antidepressant therapeutic study indicated that SSRI and SNRI are better treatments than those of TCA and NaSSA in the Chinese population. Among all possible paired single-agent survival analyses, citalopram and venlafaxine were more effective than mirtazapine. Allele C carriers at rs6354 (SLC6A4) and allele G carriers at rs12150214 (SLC6A4) were significantly prone to poorer treatment response to fluoxetine. Besides, the combination of three loci (rs929377-rs6191-rs32897) located in HPA pathway was significantly associated with the treatment outcome of fluoxetine. In female MDD patients, the minor allele of rs6323 and rs1137070 on the MAOA gene likely lead to a worse response to venlafaxine. Furthermore, genetic variants linked to drug efficacy tended to concentrate on the neurotrophin pathway in depressed patients comorbid with anxiety. From multivariate models, more severe cognitive deficits, psychopathic personality and lower levels of operational intelligence, and higher levels of cortisol predicted worse response status with SSRI or SNRI after 6-week treatment. Notably, genetic factors in the multi-dimensional prediction model for both classes of drugs include loci in HTR2A and CRHBP genes. SSRI and SNRI are more suitable for the treatment of Chinese people with depression. SLC6A4 genetic variants, as well as HPA pathway, play an important role in the fluoxetine antidepressant therapeutic response while the polymorphism of MAOA gene involved in the pharmacological action of venlafaxine among female MDD patients. The presence of anxiety in MDD patients was related to the neurotrophin pathway. Genetic, cognitive, neuroendocrine, and personality intelligence factors combined have an ensemble impact on the medication effect of patients with major depression, leading to more precise and personalized medicine for specific groups of people. • SSRI and SNRI are better treatments in the Chinese population • SLC6A4 gene and HPA pathway play an important role in the fluoxetine antidepressant therapeutic response • The polymorphism of MAOA gene involved in the pharmacological action of venlafaxine among female patients • anxiety in MDD patients was related to the neurotrophin pathway • Genetic, cognition and concomitant symptom are critical factors in the selection of antidepressants for specific patients [ABSTRACT FROM AUTHOR]

Objective: We aimed to study the association among venlafaxine antidepressive outcome, NR3C2 gene polymorphisms and the change of two neuroendocrine hormones during treatment. Methods: 195 Chinese Han major depressive disorder (MDD) patients were recruited and received a 6-week venlafaxine treatment in this study. Adrenocorticotropic hormone (ACTH), thyroid-stimulating hormone (TSH) levels were measured at the beginning and at the end of treatment. Six single-nucleotide polymorphisms (SNPs) (NR3C2 : rs1512325, rs1512342, rs2070951; NR3C1 : rs6191, rs6196, rs10482614) were selected for high-throughput SNP genotyping. Allele and genotype frequencies of them were compared between remission and non-remission groups. Results: We found that genotype frequency of the rs1512325 located in the NR3C2 gene was significantly different between remission and non-remission groups respectively (p < 0.05). Meanwhile, the frequency of the rs1512325 C-allele was significantly lower (p < 0.05) in remission group. The TSH concentration significantly increased after venlafaxine treatment in remission group (p < 0.05). Conclusion: The rs1512325 in NR3C2 gene and TSH concentration may be related to venlafaxine treatment outcome in Chinese Han MDD patients. [ABSTRACT FROM AUTHOR]