A disulfidptosis-related glucose metabolism and immune response prognostic model revealing the immune microenvironment in lung adenocarcinoma.

Background: Lung adenocarcinoma accounts for the majority of lung cancer cases and impact survival rate of patients severely. Immunotherapy is an effective treatment for lung adenocarcinoma but is restricted by many factors including immune checkpoint expression and the inhibitory immune microenvironment. This study aimed to explore the immune microenvironment in lung adenocarcinoma via disulfidptosis. Methods: Public datasets of lung adenocarcinoma from the TCGA and GEO was adopted as the training and validation cohort. Based on the differences in the expression of disulfidptosis -related genes, a glucose metabolism and immune response prognostic model was constructed. The prognostic value and clinical relationship of the model were further explored. Immune-related analyses were performed according to CIBERSORT, ssGSEA, TIDE, IPS. Results: We verified that the model could accurately predict the survival expectancy of lung adenocarcinoma patients. Patients with lung adenocarcinoma and a low-risk score had better survival outcomes according to the model. Moreover, the high-risk group tended to have an immunosuppressive effect, as reflected by the immune cell components, phenotypes and functions. We also found that the clinically relevant immune checkpoint CTLA-4 was significantly higher in low-risk group (P<0.05), indicating that the high-risk group may suffer worse tumor immunotherapy efficacy. Finally, we found that this model has accurate predictive value for the efficacy of immune checkpoint blockade in non-small cell lung cancer (P<0.05). Conclusion: The prognostic model demonstrated the feasibility of predicting survival and immunotherapy efficacy via disulfidptosis-related genes and will facilitate the development of personalized anticancer therapy.

Facial length and angle feature recognition for digital libraries.

With the continuous progress of technology, facial recognition technology is widely used in various scenarios as a mature biometric technology. However, the accuracy of facial feature recognition has become a major challenge. This study proposes a face length feature and angle feature recognition method for digital libraries, targeting the recognition of different facial features. Firstly, an in-depth study is conducted on the architecture of facial action networks based on attention mechanisms to provide more accurate and comprehensive facial features. Secondly, a network architecture based on length and angle features of facial expressions, the expression recognition network is explored to improve the recognition rate of different expressions. Finally, an end-to-end network framework based on attention mechanism for facial feature points is constructed to improve the accuracy and stability of facial feature recognition network. To verify the effectiveness of the proposed method, experiments were conducted using the facial expression dataset FER-2013. The experimental results showed that the average recognition rate for the seven common expressions was 97.28% to 99.97%. The highest recognition rate for happiness and surprise was 99.97%, while the relatively low recognition rate for anger, fear, and neutrality was 97.18%. The data has verified that the research method can effectively recognize and distinguish different facial expressions, with high accuracy and robustness. The recognition method based on attention mechanism for facial feature points has effectively optimized the recognition process of facial length and angle features, significantly improving the stability of facial expression recognition, especially in complex environments, providing reliable technical support for digital libraries and other fields. This study aims to promote the development of facial recognition technology in digital libraries, improve the service quality and user experience of digital libraries.

Is cognitive behavioral therapy for insomnia (CBTI) more cost-effective? New-perspective on economic evaluations: a systematic review and meta-analysis.

STUDY OBJECTIVES: To investigate the cost-effectiveness of cognitive behavioral therapy for insomnia (CBTI), with an additional focus on digital cognitive behavioral therapy for insomnia (dCBTI) in adults with insomnia. METHODS: We searched eight electronic databases for economic evaluations of CBTI: PubMed, Scopus, Web of Science, psycINFO, Cochrane, Library, CINAHL, ProQuest and National Health Service Economic Evaluation Database. Meta-analyses were performed to investigate the effects and costs between CBTI and control groups (no treatment, other treatments included hygiene education and treatment as usual). Subgroup analyses for dCBTI were conducted. RESULTS: Twelve randomized controlled trails studies between 2004 and 2023 were included in our systematic review and meta-analyses. The incremental cost-utility ratios and incremental cost-effectiveness ratios showed that the CBTI and dCBTI groups were more cost-effective than controls, from healthcare perspective and societal perspective, respectively. Compared to controls, CBTI demonstrated significantly better efficacy within 12 months. Healthcare costs were significantly higher in the CBTI groups compared to the controls within 6 months but there was no difference at 12 months. Additionally, dCBTI was associated with significantly lower presenteeism costs compared to controls at 6 months. CONCLUSIONS: Our findings suggest that CBTI is more cost-effective than other treatments or no treatment for adults with insomnia. It may bring more economic benefits in the long-term, especially in long-lasting efficacy and costs reduction. In addition, dCBTI is one of the cost-effective options for insomnia.

Establishing the role of BRCA1 in the diagnosis, prognosis and immune infiltrates of breast invasive cancer by bioinformatics analysis and experimental validation.

BACKGROUND: Breast cancer susceptibility gene 1 (BRCA1) is a well-known gene that acts a vital role in suppressing the growth of tumors. Previous studies have primarily focused on the genetic mutations of BRCA1 and its association with hereditary breast invasive carcinoma (BRCA). However, little research has been done to investigate the relationship between BRCA1 and immune infiltrates and prognosis in BRCA. METHODS: We obtained the expression profiles and clinical information of patients with BRCA from the Cancer Genome Atlas (TCGA) database. The levels of the BRCA1 gene between BRCA tissues and normal breast tissues were compared through the Wilcoxon rank-sum test. Additionally, we performed WB and RT-qPCR techniques to detect the expression of BRCA1. We conducted functional enrichment analyses. Furthermore, we assessed immune cell infiltration using a single-sample gene set enrichment analysis. The methylation status of the BRCA1 gene was analyzed using the UALCAN and MethSurv databases. The Cox regression analysis and (KM) Kaplan-Meier method were employed to determine the prognostic value of BRCA1. In order to provide a practical tool for predicting the overall survival rates at different time points, we also constructed a nomogram. RESULTS: Our analysis revealed that the expression of BRCA1 was significantly higher in BRCA tissues compared to normal tissues. Furthermore, this increased level of BRCA1 was found to be associated with specific BRCA subtypes, including T2, stage II, ER positive, ect. Importantly, the overexpression of BRCA1 was shown to be a negative prognostic marker for the overall survival rates of BRCA patients. Moreover, low methylation status of the BRCA1 gene was related to a poorer prognosis. Furthermore, our results indicated that high levels of BRCA1 are related to a decrease in level of killer immune cells, such as natural killer (NK) cells, macrophages, CD8+ T cells, and plasma-like dendritic cells (pDCs) within the tumor microenvironment. CONCLUSIONS: Our study is the first to provide evidence indicating that the presence of BRCA1 can serve as a reliable marker for both diagnosing and determining the prognosis of BRCA. Moreover, BRCA1 acts as a crucial indicator of the cancer's potential to infiltrate and invade the immune system, which has important implications for developing targeted therapies in BRCA.

[Study on effects of 40 Hz light flicker stimulation on spatial working memory in rats and its neural mechanism].

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive impairment, with the predominant clinical diagnosis of spatial working memory (SWM) deficiency, which seriously affects the physical and mental health of patients. However, the current pharmacological therapies have unsatisfactory cure rates and other problems, so non-pharmacological physical therapies have gradually received widespread attention. Recently, a novel treatment using 40 Hz light flicker stimulation (40 Hz-LFS) to rescue the cognitive function of model animals with AD has made initial progress, but the neurophysiological mechanism remains unclear. Therefore, this paper will explore the potential neural mechanisms underlying the modulation of SWM by 40 Hz-LFS based on cross-frequency coupling (CFC). Ten adult Wistar rats were first subjected to acute LFS at frequencies of 20, 40, and 60 Hz. The entrainment effect of LFS with different frequency on neural oscillations in the hippocampus (HPC) and medial prefrontal cortex (mPFC) was analyzed. The results showed that acute 40 Hz-LFS was able to develop strong entrainment and significantly modulate the oscillation power of the low-frequency gamma (lγ) rhythms. The rats were then randomly divided into experimental and control groups of 5 rats each for a long-term 40 Hz-LFS (7 d). Their SWM function was assessed by a T-maze task, and the CFC changes in the HPC-mPFC circuit were analyzed by phase-amplitude coupling (PAC). The results showed that the behavioral performance of the experimental group was improved and the PAC of θ-lγ rhythm was enhanced, and the difference was statistically significant. The results of this paper suggested that the long-term 40 Hz-LFS effectively improved SWM function in rats, which may be attributed to its enhanced communication of different rhythmic oscillations in the relevant neural circuits. It is expected that the study in this paper will build a foundation for further research on the mechanism of 40 Hz-LFS to improve cognitive function and promote its clinical application in the future.

[Effects of 50 Hz electromagnetic field on rat working memory and investigation of neural mechanisms].

With the widespread use of electrical equipment, cognitive functions such as working memory (WM) could be severely affected when people are exposed to 50 Hz electromagnetic fields (EMF) for long term. However, the effects of EMF exposure on WM and its neural mechanism remain unclear. In the present paper, 15 rats were randomly assigned to three groups, and exposed to an EMF environment at 50 Hz and 2 mT for a different duration: 0 days (control group), 24 days (experimental group I), and 48 days (experimental group II). Then, their WM function was assessed by the T-maze task. Besides, their local field potential (LFP) in the media prefrontal cortex (mPFC) was recorded by the in vivo multichannel electrophysiological recording system to study the power spectral density (PSD) of θ and γ oscillations and the phase-amplitude coupling (PAC) intensity of θ-γ oscillations during the T-maze task. The results showed that the PSD of θ and γ oscillations decreased in experimental groups I and II, and the PAC intensity between θ and high-frequency γ (hγ) decreased significantly compared to the control group. The number of days needed to meet the task criterion was more in experimental groups I and II than that of control group. The results indicate that long-term exposure to EMF could impair WM function. The possible reason may be the impaired communication between different rhythmic oscillations caused by a decrease in θ-hγ PAC intensity. This paper demonstrates the negative effects of EMF on WM and reveals the potential neural mechanisms from the changes of PAC intensity, which provides important support for further investigation of the biological effects of EMF and its mechanisms.

Integrated Analysis of Non-Coding RNA and mRNA Expression Profiles in Exosomes from Lung Tissue with Sepsis-Induced Acute Lung Injury.

Background: Acute lung injury (ALI) is associated with a high mortality rate; however, the underlying molecular mechanisms are poorly understood. The purpose of this study was to investigate the expression profile and related networks of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in lung tissue exosomes obtained from sepsis-induced ALI. Methods: A mouse model of sepsis was established using the cecal ligation and puncture method. RNA sequencing was performed using lung tissue exosomes obtained from mice in the sham and CLP groups. Hematoxylin-eosin staining, Western blotting, immunofluorescence, quantitative real-time polymerase chain reaction, and nanoparticle tracking analysis were performed to identify relevant phenotypes, and bioinformatic algorithms were used to evaluate competitive endogenous RNA (ceRNA) networks. Results: Thirty lncRNA-miRNA-mRNA interactions were identified, including two upregulated lncRNAs, 30 upregulated miRNAs, and two downregulated miRNAs. Based on the expression levels of differentially expressed mRNAs(DEmRNAs), differentially expressed LncRNAs(DELncRNAs), and differentially expressed miRNAs(DEmiRNAs), 30 ceRNA networks were constructed. Conclusion: Our study revealed, for the first time, the expression profiles of lncRNA, miRNA, and mRNA in exosomes isolated from the lungs of mice with sepsis-induced ALI, and the exosome co-expression network and ceRNA network related to ALI in sepsis.

Neutrophil Extracellular Traps Induce Alveolar Macrophage Pyroptosis by Regulating NLRP3 Deubiquitination, Aggravating the Development of Septic Lung Injury.

Background: Uncontrolled inflammation is a typical feature of sepsis-related lung injury. The key event in the progression of lung injury is Caspase-1-dependent alveolar macrophage (AM) pyroptosis. Similarly, neutrophils are stimulated to release neutrophil extracellular traps (NETs) to participate in the innate immune response. This study aims to illustrate the specific mechanisms by which NETs activate AM at the post-translational level and maintain lung inflammation. Methods: We established a septic lung injury model by caecal ligation and puncture. We found elevated NETs and interleukin-1b (IL-1ß) levels in the lung tissues of septic mice. Western blot and immunofluorescence analyses was utilized to determine whether NETs promote AM pyroptosis and whether degrading NETs or targeting the NLRP3 inflammasome had protective effects on AM pyroptosis and lung injury. Flow cytometric and co-immunoprecipitation analyses verified intracellular reactive oxygen species (ROS) levels and the binding of NLRP3 and ubiquitin (UB) molecules, respectively. Results: Increased NETs production and IL-1ß release in septic mice were correlated with the degree of lung injury. NETs upregulated the level of NLRP3, followed by NLRP3 inflammasome assembly and caspase-1 activation, leading to AM pyroptosis executed by the activated fragment of full-length gasdermin D (FH-GSDMD). However, the opposite effect was observed in the context of NETs degradation. Furthermore, NETs markedly elicited an increase in ROS, which facilitated the activation of NLRP3 deubiquitination and the subsequent pyroptosis pathway in AM. Removal of ROS could promote the binding of NLRP3 and ubiquitin, inhibit NLRP3 binding to apoptosis-associated spotted proteins (ASC) and further alleviate the inflammatory changes in the lungs. Conclusion: In summary, these findings indicate that NETs prime ROS generation, which promotes NLRP3 inflammasome activation at the post-translational level to mediate AM pyroptosis and sustain lung injury in septic mice.

Two-Stage Multi-Objective Stochastic Model on Patient Transfer and Relief Distribution in Lockdown Area of COVID-19.

The outbreak of an epidemic disease may cause a large number of infections and a slightly higher death rate. In response to epidemic disease, both patient transfer and relief distribution are significant to reduce corresponding damage. This study proposes a two-stage multi-objective stochastic model (TMS-PTRD) considering pre-pandemic preparedness measures and post-pandemic relief operations. The proposed model considers the following four objectives: the total number of untreated infected patients, the total transfer time, the overall cost, and the equity distribution of relief supplies. Before an outbreak, the locations of temporary relief distribution centers (TRDCs) and the inventory levels of established TRDCs should be determined. After an outbreak, the locations of temporary hospitals (THs), the locations of designated hospitals (DHs), the transfer plans for patients, and the relief distribution should be determined. To solve the TMS-PTRD model, we address an improved preference-inspired co-evolutionary algorithm named the PICEA-g-AKNN algorithm, which is embedded with a novel similarity distance and three different tailored evolutionary strategies. A real-world case study of Hunan of China and 18 test instances are randomly generated to evaluate the TMS-PTRD model. The finding shows that the PICEA-g-AKNN algorithm is better than some most widely used multi-objective algorithms.

Suicidal ideation in the general population in China after the COVID-19 pandemic was initially controlled.

BACKGROUND: The COVID-19 pandemic increases the risk of psychological problems including suicidal ideation (SI) in the general population. In this study, we investigated the risk factors of SI after the COVID-19 pandemic was initially controlled in China. METHODS: We conducted an online questionnaire via JD Health APP in China in June 2020. Demographic data, feelings and experiences related to the COVID-19 pandemic and psychological problems were collected. The participants (n = 14,690) were divided into the non-SI and SI groups. A binary logistic regression analysis was used to examine the correlates of SI. RESULTS: Nine percent of the participants (1328/14690) reported SI. The regression analysis showed that SI was positively associated with ethnic minority (OR = 1.42 [1.08-1.85]), age (e.g. 18-30 years: OR = 2.31 [1.67-3.20]), having history of mental disorders (OR = 2.75 [2.27-3.35]), daily life disturbance due to health problems (OR = 1.67 [1.38-2.01]), being around someone with the COVID-19 (OR = 1.58 [1.30-1.91]), being uncertain about effective disease control (OR = 1.23 [1.03-1.46]), and having depressive symptoms (OR = 4.40 [3.59-5.39]), insomnia symptoms (OR = 2.49 [2.13-2.90]) or psychological distress (OR = 1.87 [1.59-2.18]). LIMITATIONS: The main limitation is that the cross-sectional design of this study could not allow us to further explore the causality of SI. CONCLUSIONS: The prevalence of SI was relatively high in general population after the COVID-19 pandemic was initially controlled in China. SI should be monitored continually after the COVID-19 pandemic.

[Research progress and application of transfer entropy algorithm].

In recent years, exploring the physiological and pathological mechanisms of brain functional integration from the neural network level has become one of the focuses of neuroscience research. Due to the non-stationary and nonlinear characteristics of neural signals, its linear characteristics are not sufficient to fully explain the potential neurophysiological activity mechanism in the implementation of complex brain functions. In order to overcome the limitation that the linear algorithm cannot effectively analyze the nonlinear characteristics of signals, researchers proposed the transfer entropy (TE) algorithm. In recent years, with the introduction of the concept of brain functional network, TE has been continuously optimized as a powerful tool for nonlinear time series multivariate analysis. This paper first introduces the principle of TE algorithm and the research progress of related improved algorithms, discusses and compares their respective characteristics, and then summarizes the application of TE algorithm in the field of electrophysiological signal analysis. Finally, combined with the research progress in recent years, the existing problems of TE are discussed, and the future development direction is prospected.

Neutrophil Extracellular Traps (NETs) Promote Non-Small Cell Lung Cancer Metastasis by Suppressing lncRNA MIR503HG to Activate the NF-κB/NLRP3 Inflammasome Pathway.

Neutrophil extracellular traps (NETs) that are produced in the tumour microenvironment (TME) have been suggested to play an essential role in the dissemination of metastatic cancer under multiple infectious and inflammatory conditions. However, the functions of NETs in promoting non-small cell lung cancer (NSCLC) metastasis and the underlying mechanisms remain incompletely understood. Here, we found that NETs promoted NSCLC cell invasion and migration by inducing epithelial to mesenchymal transition (EMT). To explore how NETs contribute to NSCLC metastasis, microarrays were performed to identify substantial numbers of long noncoding RNAs (lncRNAs) and mRNAs that were differentially expressed in NSCLC cells after stimulation with NETs. Interestingly, we observed that the expression of lncRNA MIR503HG was downregulated after NETs stimulation, and ectopic MIR503HG expression reversed the metastasis-promoting effect of NETs in vitro and in vivo. Notably, bioinformatics analysis revealed that differentially expressed genes were involved in the NOD-like receptor and NF-κB signalling pathways that are associated with inflammation. NETs facilitated EMT and thereby contributed to NSCLC metastasis by activating the NF-κB/NOD-like receptor protein 3 (NLRP3) signalling pathway. Further studies revealed that MIR503HG inhibited NETs-triggered NSCLC cell metastasis in an NF-κB/NLRP3-dependent manner, as overexpression of NF-κB or NLRP3 impaired the suppressive effect of MIR503HG on NETs-induced cancer cell metastasis. Together, these results show that NETs activate the NF-κB/NLRP3 pathway by downregulating MIR503HG expression to promote EMT and NSCLC metastasis. Targeting the formation of NETs may be a novel therapeutic strategy for treating NSCLC metastasis.

DJ-1 governs airway progenitor cell/eosinophil interactions to promote allergic inflammation.

BACKGROUND: DJ-1 is an antioxidant protein known to regulate mast cell-mediated allergic response, but its role in airway eosinophilic interactions and allergic inflammation is not known. OBJECTIVE: The aim of this study was to investigate the role of DJ-1 in airway eosinophilic inflammation in vitro and in vivo. METHODS: Ovalbumin-induced airway allergic inflammation was established in mice. ELISA was adopted to analyze DJ-1 and cytokine levels in mouse bronchoalveolar lavage fluid. Transcriptional profiling of mouse lung tissues was conducted by single-cell RNA-sequencing technology. The role of DJ-1 in the differentiation of airway progenitor cells into goblet cells was examined by organoid cultures, immunofluorescence staining, quantitative PCR, and cell transplantation in normal, DJ-1 knockout (KO), or conditional DJ-1 KO mice. RESULTS: This study observed that DJ-1 was increased in the lung tissues of ovalbumin-sensitized and challenged mice. DJ-1 KO mice exhibited reduced airway eosinophil infiltration and goblet cell differentiation. Mechanistically, we discovered that eosinophil-club cell interactions are reduced in the absence of DJ-1. Organoid cultures indicated that eosinophils impair the proliferative potential of club cells. Intratracheal transplantation of DJ-1-deficient eosinophils suppresses airway goblet cell differentiation. Loss of DJ-1 inhibits the metabolism of arachidonic acid into cysteinyl leukotrienes in eosinophils while these secreted metabolites promote airway goblet cell fate in organoid cultures and in vivo. CONCLUSIONS: DJ-1-mediated interactions between airway epithelial progenitor cells and immune cells are essential in controlling airway goblet cell metaplasia and eosinophilia. Blockade of the DJ-1 pathway is protective against airway allergic inflammation.

Thiosulfate as external electron donor accelerating denitrification at low temperature condition in S0-based autotrophic denitrification biofilter.

This study was carried out to determine the inhibition of low temperature on the performance of S0-based autotrophic denitrification (S0-SAD) biofilter, and proposed to enhance the nitrate removal efficiency with thiosulfate as external electron donor. With the decline of temperature from 30 °C to 10 °C at 0.25 h of empty bed contact time (EBCT), the nitrate removal rate presented a logarithmical drop, and the effluent nitrate dramatically increased from 9.19 mg L-1 to 15.13 mg L-1. EBCT was prolonged until 0.33 h for 20 °C, 0.66 h for 15 °C and 1.5 h for 10 °C, respectively, to maintain the effluent nitrate below 10 mg L-1. Such excessive variation of EBCT for different temperature is undoubtedly incredible for practical engineering. Thiosulfate, as the external electron donor, was adopted to compensate the efficiency loss during temperature decrease, which significantly prompted nitrate removal rate to 0.59, 0.53 and 0.31 kg N m-3 d-1 at 20 °C, 15 °C and 10 °C conditions, respectively, even at a short EBCT of 0.25 h. It not only acted as compensatory electron donor for nitrate removal, but also promoted the contribution of elemental sulfur via accelerating the DO consumption and extended larger effective volume of S0-layer for denitrification. Meanwhile, the significant enrichment of Sulfurimonas and Ferritrophicum provided biological evidences to the enhancement process. However, the incomplete consumption of thiosulfate was observed especially at EBCT of 0.25 h and 10 °C, and the thiosulfate runoff needs to be concerned in case of contaminating the effluent. Herein, approximately extending EBCT to 0.66 h and decreasing thiosulfate dosage were conducted simultaneously, thereby achieving 100% thiosulfate utilization efficiency and expected nitrate removal. This study provided a fundamental guidance to design and operate S0-SAD biofilter in response to seasonal temperature variation for practical engineering.

Cellular metabolic basis of altered immunity in the lungs of patients with COVID-19.

Metabolic pathways drive cellular behavior. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes lung tissue damage directly by targeting cells or indirectly by producing inflammatory cytokines. However, whether functional alterations are related to metabolic changes in lung cells after SARS-CoV-2 infection remains unknown. Here, we analyzed the lung single-nucleus RNA-sequencing (snRNA-seq) data of several deceased COVID-19 patients and focused on changes in transcripts associated with cellular metabolism. We observed upregulated glycolysis and oxidative phosphorylation in alveolar type 2 progenitor cells, which may block alveolar epithelial differentiation and surfactant secretion. Elevated inositol phosphate metabolism in airway progenitor cells may promote neutrophil infiltration and damage the lung barrier. Further, multiple metabolic alterations in the airway goblet cells are associated with impaired muco-ciliary clearance. Increased glycolysis, oxidative phosphorylation, and inositol phosphate metabolism not only enhance macrophage activation but also contribute to SARS-CoV-2 induced lung injury. The cytotoxicity of natural killer cells and CD8+ T cells may be enhanced by glycerolipid and inositol phosphate metabolism. Glycolytic activation in fibroblasts is related to myofibroblast differentiation and fibrogenesis. Glycolysis, oxidative phosphorylation, and glutathione metabolism may also boost the aging, apoptosis and proliferation of vascular smooth muscle cells, resulting in pulmonary arterial hypertension. In conclusion, this preliminary study revealed a possible cellular metabolic basis for the altered innate immunity, adaptive immunity, and niche cell function in the lung after SARS-CoV-2 infection. Therefore, patients with COVID-19 may benefit from therapeutic strategies targeting cellular metabolism in future.

Relationships between the changes in sleep patterns and sleep quality among Chinese people during the 2019 coronavirus disease outbreak.

OBJECTIVE: Rapidly increasing numbers of confirmed cases and deaths during the 2019 coronavirus disease outbreak (COVID-19) resulted in widespread psychological problems in the Chinese population. The purpose of this study was to investigate the sleep quality and changes in sleep patterns before and during the outbreak in the general population in China and to determine factors related to sleep quality. METHODS: This cross-sectional study was conducted using an online questionnaire from 20 February to 29 February 2020 in China. Socio-demographic data, self-designed COVID-19-related characteristics, sleep patterns, and Pittsburgh Sleep Quality Index (PSQI) scores were obtained. Single factor analysis and multivariate binary logistic regression analysis were used. RESULTS: A total of 1897 individuals were included in our study, and 30.0% of participants reported suffering poor sleep quality (PSQI≥8). Logistic regression analysis found that the factors related to sleep quality included poor physical health (OR = 3.382, p < 0.001), respiratory disease (OR = 1.629, p = 0.008), other diseases (OR = 2.504, p = 0.012), suspected case of COVID-19 in the same community (OR = 1.928, p = 0.002), confirmed case of COVID-19 in the same community (OR = 2.183, p = 0.007), worry about being infected (OR = 2.336, p < 0.001), ≥1 h/day spent hearing COVID-19 information (OR = 1.960, p < 0.001), time difference in midpoint time in bed (OR = 1.230, p < 0.001), and time difference in time in bed (OR = 0.711, p < 0.001). CONCLUSIONS: Our study revealed that more than one-fourth of the participants suffered poor sleep quality during the COVID-19 outbreak. In addition to the poor health status and COVID-19-related anxiety, delayed sleep phase and reduced time in bed impacted sleep quality in the general population in China.

Novel insights into the inhibitory mechanism of (+)-catechin against trimethylamine-N-oxide demethylase.

Trimethylamine-N-oxide demethylase (TMAOase) is a key enzyme for the decomposition of trimethylamine oxide into formaldehyde. The study investigated the inhibitory effects of (+)-catechin on TMAOase and involved mechanism to minimize the formaldehyde (FA) content of seafood during storage. TMAOase was purified by DEAE-52 cellulose and Sephacryl S-300 chromatography and the inhibitory mechanism of TMAOase was studied by Lineweaver-Burk plots, fluorescence spectroscopy, and circular dichroism. Specific activity of 37 ± 0.7 U/mg was obtained with 205 -fold purification and 15% yield, and molecular mass was 25 kDa. (+)-Catechin was a reversible inhibitor of TMAOase and its induced mechanism was the non-competitive inhibition type. (+)-Catechin binding to TMAOase formed a complex with the binding constant (Ksv) of 0.72 × 103 at 298 K. The formation of complex induced the static fluorescence quenching and changes in the conformation of TMAOase, leading to a reduction in the rate of catalysis.

Systematic discovery of signaling pathways linking immune activation to schizophrenia.

Immune activation has been shown to play a critical role in the development of schizophrenia; however its underlying mechanism remains unknown. Our report demonstrates a high-quality protein interaction network for schizophrenia (SCZ Network), constructed using our "neighborhood walk" approach in combination with "random walk with restart". The spatiotemporal expression pattern of the genes in this disease network revealed two developmental stages sensitive to perturbation by immune activation: mid-to late gestation, and adolescence. Furthermore, we induced immune activation at these stages in mice, carried out transcriptome sequencing on the mouse brains, and illustrated clear potential molecular pathways and key regulators correlating maternal immune activation during gestation and an increased risk for schizophrenia after a second immune activation at puberty. This work provides not only valuable resources for the study on molecular mechanisms underlying schizophrenia, but also a systematic strategy for the discovery of molecular pathways of complex mental disorders.

Generating artificial sensations with spinal cord stimulation in primates and rodents.

For patients who have lost sensory function due to a neurological injury such as spinal cord injury (SCI), stroke, or amputation, spinal cord stimulation (SCS) may provide a mechanism for restoring somatic sensations via an intuitive, non-visual pathway. Inspired by this vision, here we trained rhesus monkeys and rats to detect and discriminate patterns of epidural SCS. Thereafter, we constructed psychometric curves describing the relationship between different SCS parameters and the animal's ability to detect SCS and/or changes in its characteristics. We found that the stimulus detection threshold decreased with higher frequency, longer pulse-width, and increasing duration of SCS. Moreover, we found that monkeys were able to discriminate temporally- and spatially-varying patterns (i.e. variations in frequency and location) of SCS delivered through multiple electrodes. Additionally, sensory discrimination of SCS-induced sensations in rats obeyed Weber's law of just-noticeable differences. These findings suggest that by varying SCS intensity, temporal pattern, and location different sensory experiences can be evoked. As such, we posit that SCS can provide intuitive sensory feedback in neuroprosthetic devices.

Macrophages in Lung Injury, Repair, and Fibrosis.

Fibrosis progression in the lung commonly results in impaired functional gas exchange, respiratory failure, or even death. In addition to the aberrant activation and differentiation of lung fibroblasts, persistent alveolar injury and incomplete repair are the driving factors of lung fibrotic response. Macrophages are activated and polarized in response to lipopolysaccharide- or bleomycin-induced lung injury. The classically activated macrophage (M1) and alternatively activated macrophage (M2) have been extensively investigated in lung injury, repair, and fibrosis. In the present review, we summarized the current data on monocyte-derived macrophages that are recruited to the lung, as well as alveolar resident macrophages and their polarization, pyroptosis, and phagocytosis in acute lung injury (ALI). Additionally, we described how macrophages interact with lung epithelial cells during lung repair. Finally, we emphasized the role of macrophage polarization in the pulmonary fibrotic response, and elucidated the potential benefits of targeting macrophage in alleviating pulmonary fibrosis.