Integrative Analyses of scRNA-seq, Bulk mRNA-seq, and DNA Methylation Profiling in Depressed Suicide Brain Tissues.

BACKGROUND: Suicidal behaviors have become a serious public health concern globally due to the economic and human cost of suicidal behavior to individuals, families, communities, and society. However, the underlying etiology and biological mechanism of suicidal behavior remains poorly understood. METHODS: We collected different single omic data, including single-cell RNA sequencing (scRNA-seq), bulk mRNA-seq, DNA methylation microarrays from the cortex of Major Depressive Disorder (MDD) in suicide subjects' studies, as well as fluoxetine-treated rats brains. We matched subject IDs that overlapped between the transcriptome dataset and the methylation dataset. The differential expression genes and differentially methylated regions were calculated with a 2-group comparison analysis. Cross-omics analysis was performed to calculate the correlation between the methylated and transcript levels of differentially methylated CpG sites and mapped transcripts. Additionally, we performed a deconvolution analysis for bulk mRNA-seq and DNA methylation profiling with scRNA-seq as the reference profiles. RESULTS: Difference in cell type proportions among 7 cell types. Meanwhile, our analysis of single-cell sequence from the antidepressant-treated rats found that drug-specific differential expression genes were enriched into biological pathways, including ion channels and glutamatergic receptors. CONCLUSIONS: This study identified some important dysregulated genes influenced by DNA methylation in 2 brain regions of depression and suicide patients. Interestingly, we found that oligodendrocyte precursor cells (OPCs) have the most contributors for cell-type proportions related to differential expression genes and methylated sites in suicidal behavior.

Hypericin Ameliorates Depression-like Behaviors via Neurotrophin Signaling Pathway Mediating m6A Epitranscriptome Modification.

Hypericin, one of the major antidepressant constituents of St. John's wort, was shown to exert antidepressant effects by affecting cerebral CYP enzymes, serotonin homeostasis, and neuroinflammatory signaling pathways. However, its exact mechanisms are unknown. Previous clinical studies reported that the mRNA modification N6-methyladenosine (m6A) interferes with the neurobiological mechanism in depressed patients, and it was also found that the antidepressant efficacy of tricyclic antidepressants (TCAs) is related to m6A modifications. Therefore, we hypothesize that the antidepressant effect of hypericin may relate to the m6A modification of epitranscriptomic regulation. We constructed a UCMS mouse depression model and found that hypericin ameliorated depressive-like behavior in UCMS mice. Molecular pharmacology experiments showed that hypericin treatment upregulated the expression of m6A-modifying enzymes METTL3 and WTAP in the hippocampi of UCMS mice. Next, we performed MeRIP-seq and RNA-seq to study m6A modifications and changes in mRNA expression on a genome-wide scale. The genome-wide m6A assay and MeRIP-qPCR results revealed that the m6A modifications of Akt3, Ntrk2, Braf, and Kidins220 mRNA were significantly altered in the hippocampi of UCMS mice after stress stimulation and were reversed by hypericin treatment. Transcriptome assays and qPCR results showed that the Camk4 and Arhgdig genes might be related to the antidepressant efficacy of hypericin. Further gene enrichment results showed that the differential genes were mainly involved in neurotrophic factor signaling pathways. In conclusion, our results show that hypericin upregulates m6A methyltransferase METTL3 and WTAP in the hippocampi of UCMS mice and stabilizes m6A modifications to exert antidepressant effects via the neurotrophin signaling pathway. This suggests that METTL3 and WTAP-mediated changes in m6A modifications may be a potential mechanism for the pathogenesis of depression and the efficacy of antidepressants, and that the neurotrophin signaling pathway plays a key role in this process.

The Progression of N6-methyladenosine Study and Its Role in Neuropsychiatric Disorders.

Epitranscriptomic modifications can affect every aspect of RNA biology, including stability, transport, splicing, and translation, participate in global intracellular mRNA metabolism, and regulate gene expression and a variety of biological processes. N6-methyladenosine (m6A) as the most prevalent modification contributes to normal embryonic brain development and memory formation. However, changes in the level of m6A modification and the expression of its related proteins cause abnormal nervous system functions, including brain tissue development retardation, axon regeneration disorders, memory changes, and neural stem cell renewal and differentiation disorders. Recent studies have revealed that m6A modification and its related proteins play key roles in the development of various neuropsychiatric disorders, such as depression, Alzheimer's disease, and Parkinson's disease. In this review, we summarize the research progresses of the m6A modification regulation mechanism in the central nervous system and discuss the effects of gene expression regulation mediated by m6A modification on the biological functions of the neuropsychiatric disorders, thereby providing some insight into new research targets and treatment directions for human diseases.

Progress on COVID-19 Chemotherapeutics Discovery and Novel Technology.

COVID-19 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel highly contagious and pathogenic coronavirus that emerged in late 2019. SARS-CoV-2 spreads primarily through virus-containing droplets and small particles of air pollution, which greatly increases the risk of inhaling these virus particles when people are in close proximity. COVID-19 is spreading across the world, and the COVID-19 pandemic poses a threat to human health and public safety. To date, there are no specific vaccines or effective drugs against SARS-CoV-2. In this review, we focus on the enzyme targets of the virus and host that may be critical for the discovery of chemical compounds and natural products as antiviral drugs, and describe the development of potential antiviral drugs in the preclinical and clinical stages. At the same time, we summarize novel emerging technologies applied to the research on new drug development and the pathological mechanisms of COVID-19.

Progression of Antiviral Agents Targeting Viral Polymerases.

Viral DNA and RNA polymerases are two kinds of very important enzymes that synthesize the genetic materials of the virus itself, and they have become extremely favorable targets for the development of antiviral drugs because of their relatively conserved characteristics. There are many similarities in the structure and function of different viral polymerases, so inhibitors designed for a certain viral polymerase have acted as effective universal inhibitors on other types of viruses. The present review describes the development of classical antiviral drugs targeting polymerases, summarizes a variety of viral polymerase inhibitors from the perspective of chemically synthesized drugs and natural product drugs, describes novel approaches, and proposes promising development strategies for antiviral drugs.

Inosine and D-Mannose Secreted by Drug-Resistant Klebsiella pneumoniae Affect Viability of Lung Epithelial Cells.

The antibiotic resistance rates of Klebsiella pneumoniae have been steadily increasing in recent years. Nevertheless, the metabolic features of the drug-resistant Klebsiella pneumoniae and its associated benefits for bacterial pathogenicity are far from expounded. This study aims to unravel the unique physiological and metabolic properties specific to drug-resistant K. pneumoniae. Using scanning electron microscopy (SEM), we observed a thicker extracellular mucus layer around a drug-resistant K. pneumonia strain (Kp-R) than a drug-sensitive K. pneumonia strain (Kp-S). Kp-R also produced more capsular polysaccharide (CPS) and biofilm, and appeared to have a significant competitive advantage when co-cultured with Kp-S. Moreover, Kp-R was easier to adhere to and invade A549 epithelial cells than Kp-S but caused less cell-viability damage according to cell counting kit-8 (CCK-8) tests. Immunofluorescence revealed that both Kp-R and Kp-S infection destroyed the tight junctions and F-actin of epithelial cells, while the damage caused by Kp-S was more severe than Kp-R. We detected the extracellular metabolites secreted by the two strains with UHPLC-Q-TOF MS to explore the critical secretion products. We identified 16 predominant compounds that were differentially expressed. Among them, inosine increased the viability of epithelial cells in a dose-dependent manner, and an A2AR antagonist can abolish such enhancement. D-mannose, which was secreted less in Kp-R, inhibited the viability of A549 cells in the range of low doses. These findings provide potential targets and research strategies for preventing and treating drug-resistant K. pneumoniae infections.

Plasma periostin as a biomarker of osteoporosis in postmenopausal women with type 2 diabetes.

INTRODUCTION: Periostin, as an emerging biomarker, is involved in multiple steps in bone metabolism. This study aimed to investigate the correlation between periostin levels and bone mineral density as well as bone turnover markers in postmenopausal women with type 2 diabetes (T2DM). MATERIALS AND METHODS: This study was a cross-sectional study that included 164 postmenopausal women with T2DM as study subjects and 32 age-matched nondiabetic postmenopausal women with normal bone mineral density (BMD) as healthy control subjects. A total of 164 subjects with T2DM were then divided into three groups according to BMD: the normal BMD group (n = 29), the osteopenia group (n = 70), and the osteoporosis group (n = 65). The clinical data of all subjects along with the relevant biochemical parameter data were collected. Plasma periostin was detected using an enzyme-linked immunosorbent assay (ELISA). RESULTS: Plasma periostin levels were significantly increased in T2DM patients with normal BMD compared with healthy controls (p < 0.05). In the diabetic group, plasma periostin levels were significantly elevated with decreased BMD, were positively correlated with osteocalcin levels (r = 0.162, p = 0.039) and were inversely associated with femoral neck BMD (r = - 0.308, p < 0.001) and total femur BMD (r = - 0.295, p < 0.001). In the case of chronic complications, periostin levels were slightly increased in individuals with complications of diabetic retinopathy, diabetic nephropathy and fracture (p > 0.05). CONCLUSIONS: The current study demonstrated that plasma periostin levels were significantly associated with BMD in patients with T2DM, and periostin might act as a novel biochemical marker of osteoporosis in postmenopausal women with type 2 diabetes.

COVID-19-another influential event impacts on laboratory medicine management.

BACKGROUND: Before public health emergencies became a major challenge worldwide, the scope of laboratory management was only related to developing, maintaining, improving, and sustaining the quality of accurate laboratory results for improved clinical outcomes. Indeed, quality management is an especially important aspect and has achieved great milestones during the development of clinical laboratories. CURRENT STATUS: However, since the coronavirus disease 2019 (COVID-19) pandemic continues to be a threat worldwide, previous management mode inside the separate laboratory could not cater to the demand of the COVID-19 public health emergency. Among emerging new issues, the prominent challenges during the period of COVID-19 pandemic are rapid-launched laboratory-developed tests (LDTs) for urgent clinical application, rapid expansion of testing capabilities, laboratory medicine resources, and personnel shortages. These related issues are now impacting on clinical laboratory and need to be effectively addressed. CONCLUSION: Different from traditional views of laboratory medicine management that focus on separate laboratories, present clinical laboratory management must be multidimensional mode which should consider consolidation of the efficient network of regional clinical laboratories and reasonable planning of laboratories resources from the view of overall strategy. Based on relevant research and our experience, in this review, we retrospect the history trajectory of laboratory medicine management, and also, we provide existing and other feasible recommended management strategies for laboratory medicine in future.

RNA-Seq based transcriptome analysis in oral lichen planus.

OBJECTIVES: Oral lichen planus (OLP) is a T cell-mediated autoimmune disease recognized as an oral potential malignant disorder (OPMD) with the precise mechanism unknown. This study focused on the transcriptional profiles of OLP to elucidate its potential pathogenesis. METHODS: We conducted RNA sequencing on matched 6 OLP tissues and 6 normal oral mucosal tissues. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and weighted gene co-expression network analysis (WGCNA) were performed on differentially expressed genes (DEGs). We utilized qRT-PCR to validated the top dysregulated genes and hub genes in another 10 pairs of specimens. RESULTS: A total of 153 DEGs (p-values< 0.05) were detected from RNA-Seq. According to GO and KEGG analysis, the dysregulated genes were mainly related to T cell related pathway and Wnt signaling. Based on the WGCNA analysis, 5 modules with high intramodular connectivity and hub genes in each module were gained. CONCLUSIONS: RNA-Seq and bioinformatic methods offered a valuable understanding of the biological pathways and key genes in the regulation of OLP. The identified DEGs and hub genes categorized into 2 groups including T cell regulation and inflammation and Wnt signaling pathway may serve as potential novel molecular targets for therapy.

Over-expression of Tgs1 in Mycobacterium marinum enhances virulence in adult zebrafish.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), can persist in the host for decades without causing TB symptoms and can cause a latent infection, which is an intricate challenge of current TB control. The DosR regulon, which contains approximately 50 genes, is crucial in the non-replicating persistence of Mtb. tgs1 is one of the most powerfully induced genes in this regulon during Mtb non-replicating persistence. The gene encodes a triacyl glycerol synthase catalyzing synthesis of triacyl glycerol (TAG), which is proposed as an energy source during bacilli persistence. Here, western blotting showed that the Tgs1 protein was upregulated in clinical Mtb strains. To detect its physiological effects on mycobacterium, we constructed serial recombinant M. marinum including over-expressed Tgs1(Tgs1-H), reduced-expressed Tgs1(Tgs1-L), and wild type M. marinum strains as controls. Tgs1 over-expression did not influence M. marinum growth under aerobic shaking and in hypoxic cultures, while growth advantages were observed at an early stage under nutrient starvation. Transmission electron microscopy revealed more lipid droplets in Tgs1-H than the other two strains; the droplets filled the cytoplasm. Two-dimensional thin-layer chromatography revealed more phosphatidyl-myo-inositol mannosides in the Tgs1-H cell wall. To assess the virulence of recombinant M. marinum in the natural host, adult zebrafish were infected with Tgs1-H or wild type strains. Hypervirulence of Tgs1-H was characterized by markedly increased bacterial load and early death of adult zebrafish. Remarkably, zebrafish infected with Tgs1-H developed necrotizing granulomas much more rapidly and in higher amounts, which facilitated mycobacterial replication and dissemination among organs and eventual tissue destruction in zebrafish. RNA sequencing analysis showed Tgs1-H induced 13 genes differentially expressed under aerobiosis. Among them, PE_PGRS54 (MMAR_5307),one of the PE_PGRS family of antigens, was markedly up-regulated, while 110 coding genes were down-regulated in Tgs1-L.The 110 genes included 22 member genes of the DosR regulon. The collective results indicate an important role for the Tgs1 protein of M. marinumin progression of infection in the natural host. Tgs1 signaling may be involved in a previously unknown behavior of M. marinum under hypoxia/aerobiosis.

Long Noncoding RNA-Associated Transcriptomic Changes in Resiliency or Susceptibility to Depression and Response to Antidepressant Treatment.

Background: Recent emergence of long noncoding RNAs in regulating gene expression and thereby modulating physiological functions in brain has manifested their possible role in psychiatric disorders. In this study, the roles of long noncoding RNAs in susceptibility and resiliency to develop stress-induced depression and their response to antidepressant treatment were examined. Methods: Microarray-based transcriptome-wide changes in long noncoding RNAs were determined in hippocampus of male Holtzman rats who showed susceptibility (learned helplessness) or resiliency (nonlearned helplessness) to develop depression. Changes in long noncoding RNA expression were also ascertained after subchronic administration of fluoxetine to learned helplessness rats. Bioinformatic and target prediction analyses (cis- and trans-acting) and qPCR-based assays were performed to decipher the functional role of altered long noncoding RNAs. Results: Group-wise comparison showed an overrepresented class of long noncoding RNAs that were uniquely associated with nonlearned helplessness or learned helplessness behavior. Chromosomal mapping within the 5-kbp flank region of the top 20 dysregulated long noncoding RNAs in the learned helplessness group showed several target genes that were regulated through cis- or trans-actions, including Zbtb20 and Zfp385b from zinc finger binding protein family. Genomic context of differentially expressed long noncoding RNAs showed an overall blunted response in the learned helplessness group regardless of the long noncoding RNA classes analyzed. Gene ontology exhibited the functional clustering for anatomical structure development, cellular architecture modulation, protein metabolism, and cellular communications. Fluoxetine treatment reversed learned helplessness-induced changes in many long noncoding RNAs and target genes. Conclusions: The involvement of specific classes of long noncoding RNAs with distinctive roles in modulating target gene expression could confer the role of long noncoding RNAs in resiliency or susceptibility to develop depression with a reciprocal response to antidepressant treatment.

Role played by the SP4 gene in schizophrenia and major depressive disorder in the Han Chinese population.

BACKGROUND: Psychiatric disorders such as schizophrenia and major depressive disorder (MDD) are likely to be caused by multiple susceptibility genes, each with small effects in increasing the risk of illness. Identifying DNA variants associated with schizophrenia and MDD is a crucial step in understanding the pathophysiology of these disorders. AIMS: To investigate whether the SP4 gene plays a significant role in schizophrenia or MDD in the Han Chinese population. METHOD: We focused on nine single nucleotide polymorphisms (SNPs) harbouring the SP4 gene and carried out case-control studies in 1235 patients with schizophrenia, 1045 patients with MDD and 1235 healthy controls recruited from the Han Chinese population. RESULTS: We found that rs40245 was significantly associated with schizophrenia in both allele and genotype distributions (Pallele = 0.0005, Pallele = 0.004 after Bonferroni correction; Pgenotype = 0.0023, Pgenotype = 0.0184 after Bonferroni correction). The rs6461563 SNP was significantly associated with schizophrenia in the allele distributions (Pallele = 0.0033, Pallele = 0.0264 after Bonferroni correction). CONCLUSIONS: Our results suggest that common risk factors in the SP4 gene are associated with schizophrenia, although not with MDD, in the Han Chinese population.

Loci with genome-wide associations with schizophrenia in the Han Chinese population.

BACKGROUND: A large schizophrenia genome-wide association study (GWAS) and a subsequent extensive replication study of individuals of European ancestry identified eight new loci with genome-wide significance and suggested that the MIR137-mediated pathway plays a role in the predisposition for schizophrenia. AIMS: To validate the above findings in a Han Chinese population. METHOD: We analysed the single nucleotide polymorphisms (SNPs) in the newly identified schizophrenia candidate loci and predicted MIR137 target genes based on our published Han Chinese populations (BIOX) GWAS data. We then analysed 18 SNPs from the candidate regions in an independent cohort that consisted of 3585 patients with schizophrenia and 5496 controls of Han Chinese ancestry. RESULTS: We replicated the associations of five markers (P<0.05), including three that were located in the predicted MIR137 target genes. Two loci (ITIH3/4: rs2239547, P = 1.17 × 10(-10) and CALN1: rs2944829, P = 9.97 × 10(-9)) exhibited genome-wide significance in the Han Chinese population. CONCLUSIONS: The ITIH3/4 locus has been reported to be of genome-wide significance in the European population. The successful replication of this finding in a different ethnic group provides stronger evidence for the association between schizophrenia and ITIH3/4. We detected the first genome-wide significant association of schizophrenia with CALN1, which is a predicted target of MIR137, and thus provide new evidence for the associations between MIR137 targets and schizophrenia.

Genetic association of ACSM1 variation with schizophrenia and major depressive disorder in the Han Chinese population.

Schizophrenia (SCZ) and major depressive disorder (MDD) are two of the most common and severe mental disorders, the etiologies of which are not yet clearly elucidated. The ACSM1 gene has been identified as a susceptibility gene for SCZ in two previous genome-wide association studies (GWAS). ACSM1 catalyzes the activation of fatty acids and plays an important role in the metabolic system. Some evidence has suggested that ACSM1 contributes to a genetic risk for MDD. The present study aimed to evaluate the common genetic risk of the ACSM1 gene in these two disorders in the Han Chinese population. In total, 1235 patients with SCZ, 1045 patients with MDD and 1235 control subjects of Chinese origin were recruited. Six single nuclear polymorphisms (SNPs) in ACSM1 were genotyped to test their associations with SCZ and MDD. SNP rs163234 was found to be significantly associated with both SCZ (permutated Pallele=1.700×10(-3), OR=1.350 [95% CI=1.152-1.581]) and MDD (permutated Pallele=4.800×10(-3), OR=1.329 [95% CI=1.127-1.567]). SNP rs433598 showed a strong association with SCZ (permutated Pallele=4.300×10(-3), OR=1.303 [95% CI=1.117-1.520]). Haplotype analysis of the blocks containing the two positive markers also revealed a significant association. This is the first study to assess the possible association of the ACSM1 gene with a genetic susceptibility for MDD. Our data are the first to suggest a positive association of the ACSM1 gene with a genetic susceptibility for SCZ and MDD in the Han Chinese population.

CACNA1C, schizophrenia and major depressive disorder in the Han Chinese population.

BACKGROUND: Common psychiatric disorders are highly heritable, indicating that genetic factors play an important role in their aetiology. The CACNA1C gene, which codes for subunit alpha-1C of the Cav1.2 voltage-dependent L-type calcium channel, has been consistently found to be the shared risk gene for several kinds of mental disorder. AIMS: To investigate whether CACNA1C is a susceptibility gene for schizophrenia and major depressive disorder in the Han Chinese population. METHOD: We carried out a case-control study of 1235 patients with schizophrenia, 1045 with major depressive disorder and 1235 healthy controls. A tag single nucleotide polymorphism (SNP) rs1006737 along with another 10 tag SNPs in the CACNA1C gene were genotyped in all samples. RESULTS: We found that rs1006737 was associated with both schizophrenia (P(allele) = 0.0014, P(genotype) = 0.006, odds ratio (OR) = 1.384, 95% CI 1.134-1.690) and major depressive disorder (P(allele) = 0.0007, P(genotype) = 0.003, OR = 1.425, 95% CI 1.160-1.752). CONCLUSIONS: Our findings support CACNA1C being a risk gene for both schizophrenia and major depressive disorder in the Han Chinese population.

Association study of 15q14 and 15q25 with high myopia in the Han Chinese population.

BACKGROUND: Refractive errors and high myopia are the most common ocular disorders, and both of them are leading causes of blindness in the world. Recently, genetic association studies in European and Japanese population identified that common genetic variations located in 15q14 and 15q25 were associated with high myopia. To validate whether the same variations conferred risk to high myopia in the Han Chinese population, we genotyped 1,461 individuals (940 controls and 521 cases samples) recruited of Han Chinese origin. RESULT: We found rs8027411 in 15q25 (P = 0.012 after correction, OR = 0.78) was significantly associated with high myopia but rs634990 in 15q14 (P = 0.54 after correction), OR = 0.88) was not. CONCLUSIONS: Our findings supported that 15q25 is a susceptibility locus for high myopia, and gene RASGRF1 was possible to play a role in the pathology of high myopia.

Common variants in the CDH7 gene are associated with major depressive disorder in the Han Chinese population.

Cadherin-7 (CDH7) gene encodes a calcium dependent cell-cell adhesion glycoprotein. Gene loci of cadherins family have been supposed to be involved in the pathogenesis of psychiatric disorders. Recent genome-wide association study also demonstrated that CDH7 was significant associated with bipolar disorder. Due to the fact that the same genetic risk factor can be shared by different kinds of psychiatric disorders, we examined whether CDH7 is also associated with major depressive disorder (MDD) in this study, with a large Han Chinese sample set. We carried out a 2-stage case-control study to examine the association between CDH7 and MDD in the Han Chinese population. Ten tag SNPs were genotyped using Taqman technology in 1,045 MDD patients and 1,520 healthy controls. Single-nucleotide polymorphisms with significance were additionally genotyped in another independent sample set with 576 MDD cases and 576 healthy controls. Among ten genotyped SNPs, rs1444067 and rs12605720 was found to be significantly associated with MDD (rs1444067: P(allele) = 0.00571, OR 0.830, 95 % CI 0.728-0.947; rs12605720: P(allele) = 0.00321, OR 1.245, 95 % CI 1.076-1.441). We successfully replicated these two SNPs association with independent sample sets (rs1444067: P(allele) = 0.00518; rs12605720: P(allele) = 0.0227). Finally we have combined these results by a meta-analysis (rs1444067: P(allele) = 0.000174, OR 0.817; rs12605720: P(allele) = 0.000199, OR 1.255). Our results support CDH7 to be a risk factor of MDD in the Han Chinese population. However, further studies with more markers and independent samples were suggested to validate our findings.

[Chemical constituents from traditional Chinese medicine Siegesbeckia pubescens].

Column chromatography on silica gel was used to study the chemical constituents of traditional Chinese medicine Siegesbeckia pubescens. The chemical structures of the separated compounds were elucidated by spectroscopic data analyses. As a result, eighteen compounds were obtained and identified as 3, 4'-dimethoxy quercetin(1), 3, 3', 4'-trimethoxy quercetin(2), 3, 3'-dimethoxy quercetin(3), 7, 3', 4'-trimethoxy luteolin(4), ursolic acid(5), 2ß,19α-dihydroxyursolic acid(6), 2ß-hydroxyursolic acid (7), stigmasterol-7-one(8), 5α, 8α-epidioxy-24(R)-methyl-cholesta-6, 22-diene-3ß-ol(9), ß-sitosterol(10), 2, 6-di(3-hydroxy-4-methoxyphenyl)-3, 7-dioxacyclo [3. 3. 0] octane (11), aurantiamide acetate (12), 3-(m-hydroxyl-p-methoxy)-N-(2'-p-hydroxyl-phenethyl)-2E-acrylamide(13), p-hydroxy benzaldehyde (14), m-hydroxy-p-methoxy benzaldehyde (15), 3, 4, 5-trimethoxybenzoic acid(16), monoethyl malonate(17), and p-hydroxylcinnamic acid(18). Among them, compounds 1-9, 11-18 were isolated from this plant for the first time.

Integrated Long Noncoding RNA and Messenger RNA Expression Analysis Identifies Molecules Specifically Associated With Resiliency and Susceptibility to Depression and Antidepressant Response.

Background: Depression involves maladaptive processes impairing an individual's ability to interface with the environment appropriately. Long noncoding RNAs (lncRNAs) are gaining traction for their role in higher-order brain functioning. Recently, we reported that lncRNA coexpression modules may underlie abnormal responses to stress in rats showing depression-like behavior. The current study explored the global expression regulation of lncRNAs and messenger RNAs (mRNAs) in the hippocampus of rats showing susceptibility (learned helplessness [LH]) or resiliency (non-LH) to depression and fluoxetine response to LH (LH+FLX). Methods: Multiple comparison analysis was performed with an analysis of variance via the aov and summary function in the R platform to identify the differential expression of mRNAs and lncRNAs among LH, non-LH, tested control, and LH+FLX groups. Weighted gene coexpression network analysis was used to identify distinctive modules and pathways associated with each phenotype. A machine learning analysis was conducted to screen the critical target genes. Based on the combined analysis, the regulatory effects of lncRNAs on mRNA expression were explored. Results: Multiple comparison analyses revealed differentially expressed mRNAs and lncRNAs with each phenotype. Integrated bioinformatics analysis identified novel transcripts, specific modules, and regulatory pairs of mRNA-lncRNA in each phenotype. In addition, the machine learning approach predicted lncRNA-regulated Spp2 and Olr25 genes in developing LH behavior, whereas joint analysis of mRNA-lncRNA pairs identified Mboat7, Lmod1, I l 18, and Rfx5 genes in depression-like behavior and Adam6 and Tpra1 in antidepressant response. Conclusions: The study shows a novel role for lncRNAs in the development of specific depression phenotypes and in identifying newer targets for therapeutic development.

We explored transcriptional signatures and regulatory patterns of mRNA and lncRNA in the rat hippocampus of a learned helplessness animal model, including stress-induced depression susceptibility and resilience and changes after antidepressant fluoxetine treatment to learned helpless rats. With the help of integrated bioinformatics analysis, we identified novel transcripts, specific modules, and mRNA-lncRNA regulatory pairs in each phenotype. This study built the foundation for the identification of specific drug targets for depression susceptibility and resilience.

Learning Discriminative Features for Crowd Counting.

Crowd counting models in highly congested areas confront two main challenges: weak localization ability and difficulty in differentiating between foreground and background, leading to inaccurate estimations. The reason is that objects in highly congested areas are normally small and high-level features extracted by convolutional neural networks are less discriminative to represent small objects. To address these problems, we propose a learning discriminative features framework for crowd counting, which is composed of a masked feature prediction module (MPM) and a supervised pixel-level contrastive learning module (CLM). The MPM randomly masks feature vectors in the feature map and then reconstructs them, allowing the model to learn about what is present in the masked regions and improving the model's ability to localize objects in high-density regions. The CLM pulls targets close to each other and pushes them far away from background in the feature space, enabling the model to discriminate foreground objects from background. Additionally, the proposed modules can be beneficial in various computer vision tasks, such as crowd counting and object detection, where dense scenes or cluttered environments pose challenges to accurate localization. The proposed two modules are plug-and-play, incorporating the proposed modules into existing models can potentially boost their performance in these scenarios.