Blocking interaction between SHP2 and PD‐1 denotes a novel opportunity for developing PD‐1 inhibitors

Small molecular PD‐1 inhibitors are lacking in current immuno‐oncology clinic. PD‐1/PD‐L1 antibody inhibitors currently approved for clinical usage block interaction between PD‐L1 and PD‐1 to enhance cytotoxicity of CD8+ cytotoxic T lymphocyte (CTL). Whether other steps along the PD‐1 signaling pathway can be targeted remains to be determined. Here, we report that methylene blue (MB), an FDA‐approved chemical for treating methemoglobinemia, potently inhibits PD‐1 signaling. MB enhances the cytotoxicity, activation, cell proliferation, and cytokine‐secreting activity of CTL inhibited by PD‐1. Mechanistically, MB blocks interaction between Y248‐phosphorylated immunoreceptor tyrosine‐based switch motif (ITSM) of human PD‐1 and SHP2. MB enables activated CTL to shrink PD‐L1 expressing tumor allografts and autochthonous lung cancers in a transgenic mouse model. MB also effectively counteracts the PD‐1 signaling on human T cells isolated from peripheral blood of healthy donors. Thus, we identify an FDA‐approved chemical capable of potently inhibiting the function of PD‐1. Equally important, our work sheds light on a novel strategy to develop inhibitors targeting PD‐1 signaling axis

Multi-Label Knowledge Distillation

Existing knowledge distillation methods typically work by imparting the knowledge of output logits or intermediate feature maps from the teacher network to the student network, which is very successful in multi-class single-label learning. However, these methods can hardly be extended to the multi-label learning scenario, where each instance is associated with multiple semantic labels, because the prediction probabilities do not sum to one and feature maps of the whole example may ignore minor classes in such a scenario. In this paper, we propose a novel multi-label knowledge distillation method. On one hand, it exploits the informative semantic knowledge from the logits by dividing the multi-label learning problem into a set of binary classification problems; on the other hand, it enhances the distinctiveness of the learned feature representations by leveraging the structural information of label-wise embeddings. Experimental results on multiple benchmark datasets validate that the proposed method can avoid knowledge counteraction among labels, thus achieving superior performance against diverse comparing methods. Our code is available at: https://github.com/penghui-yang/L2DComment: Accepted by ICCV 2023. The first two authors contributed equally to this wor

Exploring potential genes and mechanisms linking erectile dysfunction and depression

BackgroundThe clinical correlation between erectile dysfunction (ED) and depression has been revealed in cumulative studies. However, the evidence of shared mechanisms between them was insufficient. This study aimed to explore common transcriptomic alterations associated with ED and depression.Materials and methodsThe gene sets associated with ED and depression were collected from the Gene Expression Omnibus (GEO) database. Comparative analysis was conducted to obtain common genes. Using R software and other appropriate tools, we conducted a range of analyses, including function enrichment, interactive network creation, gene cluster analysis, and transcriptional and post-transcriptional signature profiling. Candidate hub crosslinks between ED and depression were selected after external validation and molecular experiments. Furthermore, subpopulation location and disease association of hub genes were explored.ResultsA total of 85 common genes were identified between ED and depression. These genes strongly correlate with cell adhesion, redox homeostasis, reactive oxygen species metabolic process, and neuronal cell body. An interactive network consisting of 80 proteins and 216 interactions was thereby developed. Analysis of the proteomic signature of common genes highlighted eight major shared genes: CLDN5, COL7A1, LDHA, MAP2K2, RETSAT, SEMA3A, TAGLN, and TBC1D1. These genes were involved in blood vessel morphogenesis and muscle cell activity. A subsequent transcription factor (TF)–miRNA network showed 47 TFs and 88 miRNAs relevant to shared genes. Finally, CLDN5 and TBC1D1 were well-validated and identified as the hub crosslinks between ED and depression. These genes had specific subpopulation locations in the corpus cavernosum and brain tissue, respectively.ConclusionOur study is the first to investigate common transcriptomic alterations and the shared biological roles of ED and depression. The findings of this study provide insights into the referential molecular mechanisms underlying the co-existence between depression and ED

Exploration and identification of six novel ferroptosis-related hub genes as potential gene signatures for peripheral nerve injury

Specific biomarkers of ferroptosis after peripheral nerve injury (PNI) are still under debate. In this study, 52 differentially expressed ferroptosis-related genes (DE-FRGs) were retrieved from publicly accessible sequencing data of intact and injured samples of rats with sciatic nerve crush injury. Functional enrichment analyses revealed that adipogenesis, mitochondrial gene sets, and pathways of MAPK, p53, and CD28 family were predominantly engaged in ferroptosis after PNI. Next, Cdkn1a, Cdh1, Hif1a, Hmox1, Nfe2l2, and Tgfb1 were investigated as new ferroptosis-associated hub genes after PNI. Subsequently, clustering correlation heatmap shows six hub genes are linked to mitochondria. The immunofluorescence assay at 0, 1, 4, 7, and 14 days indicated the temporal expression patterns of Tgfb1, Hmox1, and Hif1a after PNI were consistent with ferroptosis validated by PI and ROS staining, while Cdh1, Cdkn1a, and Nfe2l2 were the opposite. In summary, this study identified six hub genes as possible ferroptosis-related biomarkers for PNI, which may offer therapeutic targets for peripheral nerve regeneration and provide a therapeutic window for ferroptosis

Exploration of the common genetic landscape of COVID-19 and male infertility

BackgroundCOVID-19 has spread widely across continents since 2019, causing serious damage to human health. Accumulative research uncovered that SARS-CoV-2 poses a great threat to male fertility, and male infertility (MI) is a common comorbidity for the COVID-19 pandemic. The aim of the study was to explore the cross-talk molecular mechanisms between COVID-19 and MI.Materials and methodsA total of four transcriptome data regarding COVID-19 and MI were downloaded from the Gene Expression Omnibus (GEO) repository, and were divided for two purposes (initial analysis and external validation). Differentially expressed genes (DEGs) analysis, GO and pathway annotation, protein-protein interaction (PPI) network, connectivity ranking, ROC analysis, immune infiltration, and translational and post-translational interaction were performed to gain hub COVID-19-related DEGs (CORGs). Moreover, we recorded medical information of COVID-19 patients with MI and matched healthy controls, and harvested their sperm samples in the university hospital. Expressions of hub CORGs were detected through the qRT-PCR technique.ResultsWe identified 460 overlapped CORGs in both the COVID-19 DEGs and MI DEGs. CORGs were significantly enriched in DNA damage and repair-associated, cell cycle-associated, ubiquitination-associated, and coronavirus-associated signaling. Module assessment of PPI network revealed that enriched GO functions were closely related to cell cycle and DNA metabolism processes. Pharmacologic agent prediction displayed protein-drug interactions of ascorbic acid, biotin, caffeine, and L-cysteine with CORGs. After connectivity ranking and external validation, three hub CORGs (ENTPD6, CIB1, and EIF3B) showed good diagnostic performance (area under the curve > 0.75). Subsequently, three types of immune cells (CD8+ T cells, monocytes, and macrophages M0) were dominantly enriched, and 24 transcription factor-CORGs interactions and 13 miRNA-CORGs interactions were constructed in the network. Finally, qRT-PCR analysis confirmed that there were significant differences in the expression of hub CORGs (CIB1 and EIF3B) between the patient and control groups.ConclusionThe present study identified and validated hub CORGs in COVID-19 and MI, and systematically explored molecular interactions and regulatory features in various biological processes. Our data provide new insights into the novel biomarkers and potential therapeutic targets of COVID-19-associated MI

13C-Metabolic Flux Analysis Reveals the Metabolic Flux Redistribution for Enhanced Production of Poly-γ-Glutamic Acid in dlt Over-Expressed Bacillus licheniformis

Poly-γ-glutamic acid (γ-PGA) is an anionic polymer with various applications. Teichoic acid (TA) is a special component of cell wall in gram-positive bacteria, and its D-alanylation modification can change the net negative charge of cell surface, autolysin activity and cationic binding efficiency, and might further affect metabolic production. In this research, four genes (dltA, dltB, dltC, and dltD) of dlt operon were, respectively, deleted and overexpressed in the γ-PGA producing strain Bacillus licheniformis WX-02. Our results implied that overexpression of these genes could all significantly increase γ-PGA synthetic capabilities, among these strains, the dltB overexpression strain WX-02/pHY-dltB owned the highest γ-PGA yield (2.54 g/L), which was 93.42% higher than that of the control strain WX-02/pHY300 (1.31 g/L). While, the gene deletion strains produced lower γ-PGA titers. Furthermore, 13C-Metabolic flux analysis was conducted to investigate the influence of dltB overexpression on metabolic flux redistribution during γ-PGA synthesis. The simulation data demonstrated that fluxes of pentose phosphate pathway and tricarboxylic acid cycle in WX-02/pHY-dltB were 36.41 and 19.18 mmol/g DCW/h, increased by 7.82 and 38.38% compared to WX-02/pHY300 (33.77 and 13.86 mmol/g DCW/h), respectively. The synthetic capabilities of ATP and NADPH were also increased slightly. Meanwhile, the fluxes of glycolytic and by-product synthetic pathways were all reduced in WX-02/pHY-dltB. All these above phenomenons were beneficial for γ-PGA synthesis. Collectively, this study clarified that overexpression of dltB strengthened the fluxes of PPP pathway, TCA cycle and energy metabolism for γ-PGA synthesis, and provided an effective strategy for enhanced production of γ-PGA

A Novel Unsupervised Video Anomaly Detection Framework Based on Optical Flow Reconstruction and Erased Frame Prediction

Reconstruction-based and prediction-based approaches are widely used for video anomaly detection (VAD) in smart city surveillance applications. However, neither of these approaches can effectively utilize the rich contextual information that exists in videos, which makes it difficult to accurately perceive anomalous activities. In this paper, we exploit the idea of a training model based on the “Cloze Test” strategy in natural language processing (NLP) and introduce a novel unsupervised learning framework to encode both motion and appearance information at an object level. Specifically, to store the normal modes of video activity reconstructions, we first design an optical stream memory network with skip connections. Secondly, we build a space–time cube (STC) for use as the basic processing unit of the model and erase a patch in the STC to form the frame to be reconstructed. This enables a so-called ”incomplete event (IE)” to be completed. On this basis, a conditional autoencoder is utilized to capture the high correspondence between optical flow and STC. The model predicts erased patches in IEs based on the context of the front and back frames. Finally, we employ a generating adversarial network (GAN)-based training method to improve the performance of VAD. By distinguishing the predicted erased optical flow and erased video frame, the anomaly detection results are shown to be more reliable with our proposed method which can help reconstruct the original video in IE. Comparative experiments conducted on the benchmark UCSD Ped2, CUHK Avenue, and ShanghaiTech datasets demonstrate AUROC scores reaching 97.7%, 89.7%, and 75.8%, respectively

Cognitive Decline, Dementia, Alzheimer’s Disease and Presbycusis: Examination of the Possible Molecular Mechanism

The incidences of presbycusis and dementia are high among geriatric diseases. Presbycusis is the general term applied to age-related hearing loss and can be caused by many risk factors, such as noise exposure, smoking, medication, hypertension, family history, and other factors. Mutation of mitochondrial DNA in hair cells, spiral ganglion cells, and stria vascularis cells of the cochlea is the basic mechanism of presbycusis. Dementia is a clinical syndrome that includes the decline of cognitive and conscious states and is caused by many neurodegenerative diseases, of which Alzheimer’s disease (AD) is the most common. The amyloid cascade hypothesis and tau hypothesis are the two major hypotheses that describe the AD pathogenic mechanism. Recent studies have shown that deposition of Aβ and hyperphosphorylation of the tau protein may cause mitochondrial dysfunction. An increasing number of papers have reported that, on one hand, the auditory system function in AD patients is damaged as their cognitive ability declines and that, on the other hand, hearing loss may be a risk factor for dementia and AD. However, the relationship between presbycusis and AD is still unknown. By reviewing the relevant literature, we found that the SIRT1-PGC1α pathway and LKB1 (or CaMKKβ)-AMPK pathway may play a role in the preservation of cerebral neuron function by taking part in the regulation of mitochondrial function. Then vascular endothelial growth factor signal pathway is activated to promote vascular angiogenesis and maintenance of the blood–brain barrier integrity. Recently, experiments have also shown that their expression levels are altered in both presbycusis and AD mouse models. Therefore, we propose that exploring the specific molecular link between presbycusis and AD may provide new ideas for their prevention and treatment

Effects of perioperative blood transfusion in gastric cancer patients undergoing gastrectomy: A systematic review and meta-analysis

BackgroundThe short-term and long-term effects of perioperative blood transfusion (PBT) on patients with gastric cancer are still intriguing. This systematic review and meta-analysis aimed to investigate the effects of blood transfusion on clinical outcomes in patients with gastric cancer undergoing gastrectomy.MethodsWe searched PubMed, Web of Science, Embase, and The Cochrane Library on December 31th 2021. The main outcomes were overall survival (OS), disease-free survival (DFS), disease-specific survival (DFS), and postoperative complications. A fixed or random-effects model was used to calculate the hazard ratio (HR) with 95% confidence intervals (CIs).ResultsFifty-one studies with a total of 41,864 patients were included for this review and meta-analysis. Compared with patients who did not receive blood transfusions (NPBT), PBT was associated with worse 5-year OS (HR = 2.39 [95%CI: 2.00, 2.84]; p < 0.001; Multivariate HR = 1.43 [95%CI: 1.24, 1.63]; p < 0. 001), worse 5-year DFS (HR = 2.26 [95%CI: 1.68, 3.05]; p < 0.001; Multivariate HR = 1.45 [95%CI: 1.16, 1.82]; p < 0. 001), and worse 5-year DSS (HR = 2. 23 [95%CI: 1.35, 3.70]; p < 0.001; Multivariate HR = 1.24 [95%CI: 0.96, 1.60]; p < 0.001). Moreover, The PBT group showed a higher incidence of postoperative complications [OR = 2.30 (95%CI:1.78, 2. 97); p < 0.001] than that in the NPBT group, especially grade III-V complications, according to the Clavien-Dindo classification. [OR = 2.50 (95%CI:1.71, 3.63); p < 0.001].ConclusionIn patients who underwent gastrectomy, PBT was associated with negative survival effects (OS, DFS, DSS) and a higher incidence of perioperative complications. However, more research was expected to further explore the impact of PBT. Meanwhile, strict blood transfusion management should be implemented to minimize the use of PBT