A Regulatory Module Controlling Homeostasis of a Plant Immune Kinase

Plant pattern recognition receptors (PRRs) perceive microbial and endogenous molecular patterns to activate immune signaling. The cytoplasmic kinase BIK1 acts downstream of multiple PRRs as a rate-limiting component, whose phosphorylation and accumulation are central to immune signal propagation. Previous work identified the calcium-dependent protein kinase CPK28 and heterotrimeric G proteins as negative and positive regulators of BIK1 accumulation, respectively. However, mechanisms underlying this regulation remain unknown. Here we show that the plant U-box proteins PUB25 and PUB26 are homologous E3 ligases that mark BIK1 for degradation to negatively regulate immunity. We demonstrate that the heterotrimeric G proteins inhibit PUB25/26 activity to stabilize BIK1, whereas CPK28 specifically phosphorylates conserved residues in PUB25/26 to enhance their activity and promote BIK1 degradation. Interestingly, PUB25/26 specifically target non-activated BIK1, suggesting that activated BIK1 is maintained for immune signaling. Our findings reveal a multi-protein regulatory module that enables robust yet tightly regulated immune responses

Co-occurrence Pattern of Posttraumatic Stress Disorder and Depression in People Living With HIV: A Latent Profile Analysis

Background: The comorbidity of posttraumatic stress disorder (PTSD) and depression is common among people living with the HIV (PLWH). Given the high prevalence and serious clinical consequences of the comorbidity of these two disorders, we conducted a latent profile analysis to examine the co-occurrence pattern of PTSD and depression in PLWH.Methods: The data for this cross-sectional study of PLWH were collected from 602 patients with HIV in China. A secondary analysis using latent profile analysis was conducted to examine HIV-related PTSD and depression symptoms.Results: A four-class solution fits the data best, with the four classes characterized as asymptomatic (42.9%), mild symptoms (33.9%), low to moderate symptoms (19.8%), and high to moderate symptoms (3.4%). The severity of PTSD and depression symptoms was comparable in this solution, and no group was dominated by PTSD or depression.Conclusion: The absence of a distinct subcluster of PLWH with only PTSD or depression symptoms supports that PTSD and depression in PLWH are psychopathological manifestations after traumatic exposures. Health care staff should pay more attention to the existence of comorbid symptoms of individuals, develop integrated interventions for the symptoms cluster, and evaluate their effectiveness in clinical practice

Graphene/silicon heterojunction for reconfigurable phase-relevant activation function in coherent optical neural networks

Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network performances and on-chip AF devices are still in development. Here, we first demonstrate on-chip reconfigurable AF devices with phase activation fulfilled by dual-functional graphene/silicon (Gra/Si) heterojunctions. With optical modulation and detection in one device, time delays are shorter, energy consumption is lower, reconfigurability is higher and the device footprint is smaller than other on-chip AF strategies. The experimental modulation voltage (power) of our Gra/Si heterojunction achieves as low as 1 V (0.5 mW), superior to many pure silicon counterparts. In the photodetection aspect, a high responsivity of over 200 mA/W is realized. Special nonlinear functions generated are fed into a complex-valued ONN to challenge handwritten letters and image recognition tasks, showing improved accuracy and potential of high-efficient, all-component-integration on-chip ONN. Our results offer new insights for on-chip ONN devices and pave the way to high-performance integrated optoelectronic computing circuits

Protein functional module identification method combining topological features and gene expression data

Article conducting an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. The experimental results show that the ECTG algorithm can detect protein functional modules better

The relationship between expression level and gene polymorphism of inflammatory factors and sepsis risk

Abstract The biomarkers associated with sepsis have not yet been completely elucidated. The objective of the current article is to investigate whether inflammatory factors act as risk factors for sepsis. The study included 320 adult patients with sepsis, which were enrolled as experimental group. In addition, 560 healthy individuals from the same period were selected as the control group. Cytokine expressions were measured using flow cytometry with fluorescence, and gene polymorphisms were analyzed through the PCR-RFLP technique. Significantly higher expression levels of IL-1, IL-6, IL-10, and TNF-α, were detected (p < 0.05). This study also identified specific polymorphisms IL-1B -511 C/T, IL-10 -1082 G/A, IL-6 -174 G/C, and TNF-α -308 G/A, that were significantly associated with an increased risk of sepsis (p < 0.05). The expression levels of IL-1, IL-6, IL-10, and TNF-α are associated with an increased risk of sepsis. Additionally, the polymorphisms IL-1B -511 C/T, IL-6 -174 G/C, IL-10 -1082 G/A, IFN-γ + 874 A/T, and TNF-α -308 G/A are also linked to sepsis risk in the Chinese population

Comparative Efficacy and Acceptability of Non-pharmacological Interventions for Depression Among People Living With HIV: Protocol for a Systematic Review and Network-meta Analysis

Abstract Background: Improving depression is critical to successful HIV treatment. Due to the adverse reactions of pharmacotherapy, treatment for depression in PLWH has increasingly turned to non-pharmacological treatments. However, the comparative efficacy and acceptability of non-pharmacological treatments for depression among PLWH in different resource contexts remain inconclusive. This protocol for a systematic review and network meta-analysis aims at evaluating the efficacy and acceptability of non-pharmacological treatments for depression among PLWH to guide future research and practice for all research settings and for low-income and middle-income countries (LMIC) only. Methods: We will include all randomized controlled trials of any non-pharmacological interventions to reduce depression in PLWH. The primary outcomes will be the efficacy (the overall mean change scores in depression) and acceptability (the proportion of participants who withdrew for any reason). We will systematically search Published studies through the related databases (PubMed, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, and CINAHL) and the bibliographies. There is no restriction by language and publication year. At least two investigators will independently conduct all study selection, quality evaluation, and data extraction. We will employ a network meta-analysis to synthesize all available evidence for each outcome and obtain a comprehensive ranking of all interventions for the global network and for low-income and middle-income countries (LMICs) network only. We will employ validated local and global approaches to assess inconsistency. We will use OpenBUGS (version 3.2.3) to fit our model into the Bayesian framework. We will evaluate the strength of evidence with the GRADE system. Discussion: We will synthesize all available evidence and identify the most efficacious and acceptable non-pharmacological interventions for depression among PLWH for global network and for LMIC network only. The results of this study will be used to guide decision-making better in different resource settings.Systematic review registration: PROSPERO CRD42021244230.</jats:p