Acetylation-mediated proteasomal degradation of core histones during DNA repair and spermatogenesis.

Histone acetylation plays critical roles in chromatin remodeling, DNA repair, and epigenetic regulation of gene expression, but the underlying mechanisms are unclear. Proteasomes usually catalyze ATP- and polyubiquitin-dependent proteolysis. Here, we show that the proteasomes containing the activator PA200 catalyze the polyubiquitin-independent degradation of histones. Most proteasomes in mammalian testes ("spermatoproteasomes") contain a spermatid/sperm-specific α subunit α4 s/PSMA8 and/or the catalytic ß subunits of immunoproteasomes in addition to PA200. Deletion of PA200 in mice abolishes acetylation-dependent degradation of somatic core histones during DNA double-strand breaks and delays core histone disappearance in elongated spermatids. Purified PA200 greatly promotes ATP-independent proteasomal degradation of the acetylated core histones, but not polyubiquitinated proteins. Furthermore, acetylation on histones is required for their binding to the bromodomain-like regions in PA200 and its yeast ortholog, Blm10. Thus, PA200/Blm10 specifically targets the core histones for acetylation-mediated degradation by proteasomes, providing mechanisms by which acetylation regulates histone degradation, DNA repair, and spermatogenesis.

MKMR: a multi-kernel machine regression model to predict health outcomes using human microbiome data.

Studies have found that human microbiome is associated with and predictive of human health and diseases. Many statistical methods developed for microbiome data focus on different distance metrics that can capture various information in microbiomes. Prediction models were also developed for microbiome data, including deep learning methods with convolutional neural networks that consider both taxa abundance profiles and taxonomic relationships among microbial taxa from a phylogenetic tree. Studies have also suggested that a health outcome could associate with multiple forms of microbiome profiles. In addition to the abundance of some taxa that are associated with a health outcome, the presence/absence of some taxa is also associated with and predictive of the same health outcome. Moreover, associated taxa may be close to each other on a phylogenetic tree or spread apart on a phylogenetic tree. No prediction models currently exist that use multiple forms of microbiome-outcome associations. To address this, we propose a multi-kernel machine regression (MKMR) method that is able to capture various types of microbiome signals when doing predictions. MKMR utilizes multiple forms of microbiome signals through multiple kernels being transformed from multiple distance metrics for microbiomes and learn an optimal conic combination of these kernels, with kernel weights helping us understand contributions of individual microbiome signal types. Simulation studies suggest a much-improved prediction performance over competing methods with mixture of microbiome signals. Real data applicants to predict multiple health outcomes using throat and gut microbiome data also suggest a better prediction of MKMR than that of competing methods.

MK-BMC: a Multi-Kernel framework with Boosted distance metrics for Microbiome data for Classification.

MOTIVATION: Research on human microbiome has suggested associations with human health, opening opportunities to predict health outcomes using microbiome. Studies have also suggested that diverse forms of taxa such as rare taxa that are evolutionally related and abundant taxa that are evolutionally unrelated could be associated with or predictive of a health outcome. Although prediction models were developed for microbiome data, no prediction models currently exist that use multiple forms of microbiome-outcome associations. RESULTS: We developed MK-BMC, a Multi-Kernel framework with Boosted distance Metrics for Classification using microbiome data. We propose to first boost widely used distance metrics for microbiome data using taxon-level association signal strengths to up-weight taxa that are potentially associated with an outcome of interest. We then propose a multi-kernel prediction model with one kernel capturing one form of association between taxa and the outcome, where a kernel measures similarities of microbiome compositions between pairs of samples being transformed from a proposed boosted distance metric. We demonstrated superior prediction performance of (i) boosted distance metrics for microbiome data over original ones and (ii) MK-BMC over competing methods through extensive simulations. We applied MK-BMC to predict thyroid, obesity, and inflammatory bowel disease status using gut microbiome data from the American Gut Project and observed much-improved prediction performance over that of competing methods. The learned kernel weights help us understand contributions of individual microbiome signal forms nicely. AVAILABILITY AND IMPLEMENTATION: Source code together with a sample input dataset is available at https://github.com/HXu06/MK-BMC.

A Biodegradable Nanosuspension Locally Used for Inhibiting Postoperative Recurrence and Brain Metastasis of Breast Cancer.

Addressing the urgent need to prevent breast cancer postoperative recurrence and brain metastasis, Fe-metal organic framework (MOF)-coated hollow mesoporous organosilica nanoparticles (HMON) with tumor microenvironment dual-responsive degradability were prepared to encapsulate doxorubicin (DOX), formulating a tissue-adhesive nanosuspension for perioperative topical medication. This nanosuspension can not only retain the sustainably released drug in the postoperative residual tumor sites but also enhance the intracellular oxidative stress of tumors for remarkable tumor ferroptosis. Interestingly, the nanosuspension can act as an immune amplifier, which could not only stimulate DC cells to secrete chemokines for T cell recruitment but also elevate antigen exposure to facilitate the antigen presentation in lymph nodes. Thus, this nanosuspension could significantly activate antitumor immune responses in both in situ tumors and metastatic encephaloma for enhanced immunotherapy. In conjunction with the clinical PD-1 antibody, the locally administered nanosuspension could achieve an advanced therapeutic outcome for inhibiting postoperative recurrence and metastasis.

Identification and validation of anoikis-related genes to clarify the prognosis and immune mechanisms of patients with low-grade glioma.

BACKGROUND: Low-grade glioma (LGG) has an extremely poor prognosis, and the mechanism leading to malignant development has not been determined. The aim of our study was to clarify the function and mechanism of anoikis and TIMP1 in the malignant progression of LGG. METHODS: We screened 7 anoikis-related genes from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to construct a prognostic-predicting model. The study assessed the clinical prognosis, pathological characteristics, and immune cell infiltration in both high- and low-risk groups. Additionally, the potential modulatory effects of TIMP1 on proliferation, migration, and anoikis in LGG were investigated both in vivo and in vitro. RESULTS: In this study, we identified seven critical genes, namely, PTGS2, CCND1, TIMP1, PDK4, LGALS3, CDKN1A, and CDKN2A. Kaplan‒Meier (K‒M) curves demonstrated a significant correlation between clinical features and overall survival (OS), and single-cell analysis and mutation examination emphasized the heterogeneity and pivotal role of hub gene expression imbalances in LGG development. Immune cell infiltration and microenvironment analysis further elucidated the relationships between key genes and immune cells. In addition, TIMP1 promoted the malignant progression of LGG in both in vitro and in vivo models. CONCLUSIONS: This study confirmed that TIMP1 promoted the malignant progression of LGG by inhibiting anoikis, providing insights into LGG pathogenesis and potential therapeutic targets.

Educational status affects prognosis of patients with heart failure with reduced ejection fraction: A post-hoc analysis from the WARCEF trial.

AIMS: The influence of social determinants of health (SDOH) on the prognosis of Heart Failure and reduced Ejection Fraction (HFrEF) is increasingly reported. We aim to evaluate the contribution of educational status on outcomes in patients with HFrEF. METHODS: We used data from the WARCEF trial, which randomized HFrEF patients with sinus rhythm to receive Warfarin or Aspirin; educational status of patients enrolled was collected at baseline. We defined three levels of education: low, medium and high level, according to the highest qualification achieved or highest school grade attended. We analysed the impact of the educational status on the risk of the primary composite outcome of all-cause death, ischemic stroke (IS) and intracerebral haemorrhage (ICH); components of the primary outcome were also analysed as secondary outcomes. RESULTS: 2295 patients were included in this analysis; of these, 992 (43.2%) had a low educational level, 947 (41.3%) had a medium education level and the remaining 356 (15.5%) showed a high educational level. Compared to patients with high educational level, those with low educational status showed a high risk of the primary composite outcome (adjusted hazard ratio [aHR]: 1.31, 95% confidence intervals [CI] 1.02-1.69); a non-statistically significant association was observed in those with medium educational level (aHR: 1.20, 95%CI: .93-1.55). Similar results were observed for all-cause death, while no statistically significant differences were observed for IS or ICH. CONCLUSION: Compared to patients with high educational levels, those with low educational status had worse prognosis. SDOH should be considered in patients with HFrEF. CLINICAL TRIAL REGISTRATION: NCT00041938.

Assessing social cognition in patients with schizophrenia and healthy controls using the reading the mind in the eyes test (RMET): a systematic review and meta-regression.

The reading the mind in the eyes test (RMET) - which assesses the theory of mind component of social cognition - is often used to compare social cognition between patients with schizophrenia and healthy controls. There is, however, no systematic review integrating the results of these studies. We identified 198 studies published before July 2020 that administered RMET to patients with schizophrenia or healthy controls from three English-language and two Chinese-language databases. These studies included 41 separate samples of patients with schizophrenia (total n = 1836) and 197 separate samples of healthy controls (total n = 23 675). The pooled RMET score was 19.76 (95% CI 18.91-20.60) in patients and 25.53 (95% CI 25.19-25.87) in controls (z = 12.41, p < 0.001). After excluding small-sample outlier studies, this difference in RMET performance was greater in studies using non-English v. English versions of RMET (Chi [Q] = 8.54, p < 0.001). Meta-regression analyses found a negative association of age with RMET score and a positive association of years of schooling with RMET score in both patients and controls. A secondary meta-analysis using a spline construction of 180 healthy control samples identified a non-monotonic relationship between age and RMET score - RMET scores increased with age before 31 and decreased with age after 31. These results indicate that patients with schizophrenia have substantial deficits in theory of mind compared with healthy controls, supporting the construct validity of RMET as a measure of social cognition. The different results for English versus non-English versions of RMET and the non-monotonic relationship between age and RMET score highlight the importance of the language of administration of RMET and the possibility that the relationship of aging with theory of mind is different from the relationship of aging with other types of cognitive functioning.

Desloratadine ameliorates paclitaxel-induced peripheral neuropathy and hypersensitivity reactions in mice.

Paclitaxel (PTX) serves as a primary chemotherapy agent against diverse solid tumors including breast cancer, lung cancer, head and neck cancer and ovarian cancer, having severe adverse effects including PTX-induced peripheral neuropathy (PIPN) and hypersensitivity reactions (HSR). A recommended anti-allergic agent diphenhydramine (DIP) has been used to alleviate PTX-induced HSR. Desloratadine (DLT) is a third generation of histamine H1 receptor antagonist, but also acted as a selective antagonist of 5HTR2A. In this study we investigated whether DLT ameliorated PIPN-like symptoms in mice and the underlying mechanisms. PIPN was induced in male mice by injection of PTX (4 mg/kg, i.p.) every other day for 4 times. The mice exhibited 50% reduction in mechanical threshold, paw thermal response latency and paw cold response latency compared with control mice. PIPN mice were treated with DLT (10, 20 mg/kg, i.p.) 30 min before each PTX administration in the phase of establishing PIPN mice model and then administered daily for 4 weeks after the model was established. We showed that DLT administration dose-dependently elevated the mechanical, thermal and cold pain thresholds in PIPN mice, whereas administration of DIP (10 mg/kg, i.p.) had no ameliorative effects on PIPN-like symptoms. We found that the expression of 5HTR2A was selectively elevated in the activated spinal astrocytes of PIPN mice. Spinal cord-specific 5HTR2A knockdown by intrathecal injection of AAV9-5Htr2a-shRNA significantly alleviated the mechanical hyperalgesia, thermal and cold hypersensitivity in PIPN mice, while administration of DLT (20 mg/kg) did not further ameliorate PIPN-like symptoms. We demonstrated that DLT administration alleviated dorsal root ganglion neuronal damage and suppressed sciatic nerve destruction, spinal neuron apoptosis and neuroinflammation in the spinal cord of PIPN mice. Furthermore, we revealed that DLT administration suppressed astrocytic neuroinflammation via the 5HTR2A/c-Fos/NLRP3 pathway and blocked astrocyte-neuron crosstalk by targeting 5HTR2A. We conclude that spinal 5HTR2A inhibition holds promise as a therapeutic approach for PIPN and we emphasize the potential of DLT as a dual-functional agent in ameliorating PTX-induced both PIPN and HSR in chemotherapy. In summary, we determined that spinal 5HTR2A was selectively activated in PIPN mice and DLT could ameliorate the PTX-induced both PIPN- and HSR-like pathologies in mice. DLT alleviated the damages of DRG neurons and sciatic nerves, while restrained spinal neuronal apoptosis and CGRP release in PIPN mice. The underlying mechanisms were intensively investigated by assay against the PIPN mice with 5HTR2A-specific knockdown in the spinal cord by injection of adeno-associated virus 9 (AAV9)-5Htr2a-shRNA. DLT inhibited astrocytic NLRP3 inflammasome activation-mediated spinal neuronal damage through 5HTR2A/c-FOS pathway. Our findings have supported that spinal 5HTR2A inhibition shows promise as a therapeutic strategy for PIPN and highlighted the potential advantage of DLT as a dual-functional agent in preventing against PTX-induced both PIPN and HSR effects in anticancer chemotherapy.

Nitrophenols in the environment: An update on pretreatment and analysis techniques since 2017.

Nitrophenols, a versatile intermediate, have been widely used in leather, medicine, chemical synthesis, and other fields. Because these components are widely applied, they can enter the environment through various routes, leading to many hazards and toxicities. There has been a recent surge in the development of simple, rapid, environmentally friendly, and effective techniques for determining these environmental pollutants. This review provides a comprehensive overview of the latest research progress on the pretreatment and analysis methods of nitrophenols since 2017, with a focus on environmental samples. Pretreatment methods include liquid-liquid extraction, solid-phase extraction, dispersive extraction, and microextraction methods. Analysis methods mainly include liquid chromatography-based methods, gas chromatography-based methods, supercritical fluid chromatography. In addition, this review also discusses and compares the advantages/disadvantages and development prospects of different pretreatment and analysis methods to provide a reference for further research.

Mentoring as a complex adaptive system - a systematic scoping review of prevailing mentoring theories in medical education.

BACKGROUND: Effective mentorship is an important component of medical education with benefits to all stakeholders. In recent years, conceptualization of mentorship has gone beyond the traditional dyadic experienced mentor-novice mentee relationship to include group and peer mentoring. Existing theories of mentorship do not recognize mentoring's personalized, evolving, goal-driven, and context-specific nature. Evidencing the limitations of traditional cause-and-effect concepts, the purpose of this review was to systematically search the literature to determine if mentoring can be viewed as a complex adaptive system (CAS). METHODS: A systematic scoping review using Krishna's Systematic Evidence-Based Approach was employed to study medical student and resident accounts of mentoring and CAS in general internal medicine and related subspecialties in articles published between 1 January 2000 and 31 December 2023 in PubMed, Embase, PsycINFO, ERIC, Google Scholar, and Scopus databases. The included articles underwent thematic and content analysis, with the themes identified and combined to create domains, which framed the discussion. RESULTS: Of 5,704 abstracts reviewed, 134 full-text articles were evaluated, and 216 articles were included. The domains described how mentoring relationships and mentoring approaches embody characteristics of CAS and that mentorship often behaves as a community of practice (CoP). Mentoring's CAS-like features are displayed through CoPs, with distinct boundaries, a spiral mentoring trajectory, and longitudinal mentoring support and assessment processes. CONCLUSION: Recognizing mentorship as a CAS demands the rethinking of the design, support, assessment, and oversight of mentorship and the role of mentors. Further study is required to better assess the mentoring process and to provide optimal training and support to mentors.

Screening and identification of cyprinid herpesvirus 2 (CyHV-2) ORF55-interacting proteins by phage display.

BACKGROUND: Cyprinid herpesvirus 2 (CyHV-2) is a pathogenic fish virus belonging to family Alloherpesviridae. The CyHV-2 gene encoding thymidine kinase (TK) is an important virulence-associated factor. Therefore, we aimed to investigate the biological function of open reading frame 55 (ORF55) in viral replication. METHODS: Purified CyHV-2 ORF55 protein was obtained by prokaryotic expression, and the interacting peptide was screened out using phage display. Host interacting proteins were then predicted and validated. RESULTS: ORF55 was efficiently expressed in the prokaryotic expression system. Protein and peptide interaction prediction and dot-blot overlay assay confirmed that peptides identified by phage display could interact with the ORF55 protein. Comparing the peptides to the National Center for Biotechnology Information database revealed four potential interacting proteins. Reverse transcription quantitative PCR results demonstrated high expression of an actin-binding Rho-activating protein in the latter stages of virus-infected cells, and molecular docking, cell transfection and coimmunoprecipitation experiments confirmed that it interacted with the ORF55 protein. CONCLUSION: During viral infection, the ORF55 protein exerts its biological function through interactions with host proteins. The specific mechanisms remain to be further explored.

Dietary sinensetin and polymethoxyflavonoids: Bioavailability and potential metabolic syndrome-related bioactivity.

Sinensetin is among the most ubiquitous polyphenols in citrus fruit and recently has been extensively studied for its ability to prevent or treat diseases. The current literature on the bioavailability of sinensetin and its derivatives was reviewed and the potential ameliorative effects of metabolic syndrome in humans were evaluated. Sinensetin and its derivatives mainly aggregated in the large intestine and extensively metabolized through gut microbiota (GM) and the liver. So intestinal microorganisms had a significant influence on the absorption and metabolism of sinensetin. Interestingly, not only GM acted on sinensetin to metabolize them, but sinensetin also regulated the composition of GM. Thus, sinensetin was metabolized as methyl, glucuronide and sulfate metabolites in the blood and urine. Furthermore, sinensetin was reported to have the beneficial effect of ameliorating metabolic syndromes, including disorders of lipid metabolism (obesity, NAFLD, atherosclerosis), glucose metabolism disorder (insulin resistant) and inflammation, in terms of improving the composition of intestinal flora and modulating metabolic pathway factors in relevant tissues. The present work strongly elucidated the potential mechanism of sinensetin in improving metabolic disorders and supported the contribution of sinensetin to health benefits, thus offering a better perspective in understanding the role played by sinensetin in human health.

Analysis of N-of-1 trials using Bayesian distributed lag model with autocorrelated errors.

An N-of-1 trial is a multi-period crossover trial performed in a single individual, with a primary goal to estimate treatment effect on the individual instead of population-level mean responses. As in a conventional crossover trial, it is critical to understand carryover effects of the treatment in an N-of-1 trial, especially when no washout periods between treatment periods are instituted to reduce trial duration. To deal with this issue in situations where a high volume of measurements are made during the study, we introduce a novel Bayesian distributed lag model that facilitates the estimation of carryover effects, while accounting for temporal correlations using an autoregressive model. Specifically, we propose a prior variance-covariance structure on the lag coefficients to address collinearity caused by the fact that treatment exposures are typically identical on successive days. A connection between the proposed Bayesian model and penalized regression is noted. Simulation results demonstrate that the proposed model substantially reduces the root mean squared error in the estimation of carryover effects and immediate effects when compared to other existing methods, while being comparable in the estimation of the total effects. We also apply the proposed method to assess the extent of carryover effects of light therapies in relieving depressive symptoms in cancer survivors.

Association of Clinical Factors and Degree of Early Background Parenchymal Enhancement on Contrast-Enhanced Mammography.

BACKGROUND. Background parenchymal enhancement (BPE) may impact contrast-enhanced mammography (CEM) interpretation, although factors influencing the degree of BPE on CEM are poorly understood. OBJECTIVE. The purpose of our study was to evaluate relationships between clinical factors and the degree of early BPE on CEM. METHODS. This retrospective study included 207 patients (median age, 46 years) who underwent CEM between April 2020 and September 2021. Two radiologists independently assessed the degree of BPE on CEM as minimal, mild, moderate, or marked on the basis of two criteria (criterion 1, using the first of four obtained views; criterion 2, using the first two of four obtained views). The radiologists reached consensus for breast density on CEM. The EMR was reviewed for clinical factors. Radiologists' agreement for degree of BPE was assessed using weighted kappa coefficients. Univariable and multivariable analyses were performed to assess relationships between clinical factors and degree of BPE, treating readers' independent assessments as repeated measurements. RESULTS. Interreader agreement for degree of BPE, expressed as kappa, was 0.80 for both criteria. For both criteria, univariable analyses found degree of BPE to be negatively associated with age (both OR = 0.94), personal history of breast cancer (OR = 0.22-0.30), history of chemotherapy (OR = 0.18-0.21), history of radiation therapy (OR = 0.20-0.21), perimenopausal status (OR = 0.22-0.34), and postmenopausal status (OR = 0.10-0.11) and to be positively associated with dense breasts (OR = 4.13-4.26) and premenopausal status with irregular menstrual cycles (OR = 7.94-14.02). Among premenopausal patients with regular menstrual cycles, degree of BPE was lowest (using postmenopausal patients as reference) for patients in menstrual cycle days 8-14 (OR = 2.56-3.30). In multivariable analysis for both criteria, the only independent predictors of degree of BPE related to menstrual status and time of menstrual cycle (e.g., using premenopausal patients in days 1-7 as reference: OR = 0.21 for both criteria for premenopausal patients in days 8-14 and OR = 0.03-0.04 for postmenopausal patients). CONCLUSION. Clinical factors, including history of breast cancer or breast cancer treatment, breast density, menstrual status, and time of menstrual cycle, are associated with degree of early BPE on CEM. In premenopausal patients, the degree of BPE is lowest on days 8-14 of the menstrual cycle. CLINICAL IMPACT. Given the potential impact of BPE on diagnostic performance, the findings have implications for CEM scheduling and interpretation.

Effect of sandwiched YbCl3layer thickness on exciton dynamics of Yb3+doped CsPbCl3perovskite photodetectors.

Yb3+doped CsPbCl3metal halide perovskite photodetectors (PDs) in the structure of CsPbCl3(50 nm)/YbCl3(xnm)/CsPbCl3(50 nm), in whichxranges from 10 to 40 nm corresponding to the molar ratio from 6.3% to 25.2%, are fabricated by thermal evaporation on Si/SiO2substrate. Photoresponse from 350 to 980 nm have been achieved with the optimal responsivity (R) of 3959, 5425, 955 A W-1for the case of 20 nm YbCl3at the wavelength (λ) of 420, 680 and 980 nm, respectively. A series of photophysical and electrical characterization has been performed and it is found that the remarkably improved photoresponse originates from the combining effects of upconversion and defects passivation from Yb3+. Moreover, the optimal YbCl3thickness of 20 nm can be ascribed to the balance between upconversion and concentration quenching of Yb3+. The influence of the YbCl3doping on the CsPbCl3electronic structure is investigated and downshifting and stabilization of valence band maximum (VBM) can be attributed to the p-type doping and counteracting effect of Yb3+and Cl-, respectively.

Rosiglitazone inhibits acyl-CoA synthetase long-chain family number 4 and improves secondary brain injury in a rat model of surgical brain injury.

Ferroptosis is a recently discovered non-apoptotic form of cellular death. Acyl-CoA synthetase long-chain family number 4 (ACSL4) is necessary for iron-dependent cellular death, and reactive oxygen species (ROS) produced by ACSL4 are the executioners of ferroptosis. Rosiglitazone improves ferroptosis by inhibiting ACSL4. There is no research indicating whether ACSL4 plays a role in cell death after surgical brain injury (SBI). This study aimed to investigate the role of ACSL4 in SBI via the ferroptosis pathway. Ninety male Sprague-Dawley rats were examined using a model of SBI. Subsequently, the inhibitory effect of rosiglitazone on ACSL4 was assessed via western blot, real-time polymerase chain reaction (PCR), immunofluorescence, fluoro-jade C staining, Perl's staining, ROS assay, and neurological scoring. The results showed that compared with the Sham group, the protein levels of ACSL4 and transferrin were significantly increased after SBI. Administration of rosiglitazone significantly reduced neuronal necrosis, iron deposition, brain water content and ROS in brain tissue and ameliorated neurological deficits at 48 h after SBI, which was concomitant with decreased transferrin expression. These findings demonstrate that SBI-induced upregulation of ACSL4 may be partly mediated by the ferroptosis pathway, which can be reversed by rosiglitazone administration.

A multicenter, randomized controlled study on the efficacy of agomelatine in ameliorating anhedonia, reduced motivation, and circadian rhythm disruptions in patients with major depressive disorder (MDD).

OBJECTIVE: To evaluate the clinical efficacy and safety of Agomelatine in improving symptoms in patients with major depressive disorder (MDD), providing more scientific evidence for the treatment of depression, and offering more effective therapeutic options for patients. METHODS: A total of 180 MDD patients in acute phase from 10 psychiatric hospitals of Grade three in Zhejiang Province were enrolled in this 12-week study with the competitive and consecutive pattern, and they were randomized into two different groups treated with flexible-dosage antidepressants of selective serotonin reuptake inhibitors (SSRI) or agomelatine, respectively. The subjects were evaluated with psychological scales of HAMD-17, HAMA, SHAPS for anhedonia, MFI-20 for fatigue, PQSI for sleep quality and MEQ for disturbances in chronobiologic rhythms at baseline, 2, 4, 8 and 12-weekend points, and TESS was used for side-effect. The results were analyzed with repeated measurement analysis of variance. RESULTS: The two groups each had 90 participants, and there were no significant differences at baseline. The scores of various assessment scales showed statistically significant time main effects during the visits (P < 0.01). The Agomelatine group demonstrated faster efficacy within 2 weeks, with better improvement in SHAPS, MEQ, and PSQI compared to the SSRIs group. However, the remission rate at 12 weeks was lower in the Agomelatine group than in the SSRIs group (63.3% and 72.2%), but the difference between the groups was not statistically significant. The Agomelatine group had fewer adverse reactions (14.4% and 16.7%), but there was a slightly higher incidence of liver function impairment (6.7% and 4.4%), with no statistically significant difference between the groups. CONCLUSION: Agomelatine, as a novel antidepressant, shows certain advantages in improving depression and anxiety symptoms and is comparable to SSRIs in terms of safety. However, its long-term efficacy and safety on MDD or other depressive subtypes still require further observation and research.

Enabling Quick Response to Nitrogen Dioxide at Room Temperature and Limit of Detection to Ppb Level by Heavily n-Doped Graphene Hybrid Transistor.

Sensitive detection of nitrogen dioxide (NO2) is of significance in many areas for health and environmental protections. In this work, we developed an efficient NO2 sensor that can respond within seconds at room temperature, and the limit of detection (LOD) is as low as 100 ppb. Coating cyano-substituted poly(p-phenylene vinylene) (CN-PPV) films on graphene (G) layers can dope G sheets effectively to a heavy n state. The influences of solution concentrations and annealing temperatures on the n-doping effect were investigated in detail. The CN-PPV-G transistors fabricated with the optimized parameters demonstrate active sensing abilities toward NO2. The n-doping state of CN-PPV-G is reduced dramatically by NO2, which is a strong p-doping compound. Upon exposure to 25 ppm of NO2, our CN-PPV-G sensors react in 10 s, indicating it is almost an immediate response. LOD is determined as low as 100 ppb. The ultrahigh responding speed and low LOD are not affected in dry air. Furthermore, cycling use of our sensors can be realized through simple annealing. The superior features shown by our CN-PPV-G sensors are highly desired in the applications of monitoring the level of NO2 in situ and setting immediate alarms. Our results also suggest that transfer curves of transistors can react very promptly to the stimulus of target gas and, thus, are very promising in the development of fast-response sensing devices although the response values may not reach maximum as a tradeoff.

The role of frailty, social networks, and depression in self-neglect in an older Chinese population: A cross-sectional descriptive study.

OBJECTIVES: To identify the role of frailty, social networks, and depression in self-neglect in an older Chinese population. METHODS: The study was conducted in 521 older adults recruited from four community healthcare centers in a district in Beijing, China. Participants were investigated by a set of questionnaires. RESULTS: Frailty (ß=0.150, p=0.759) was not associated with self-neglect of older adults. Social isolation (ß=1.980, p<0.001) and depression (ß=3.606, p<0.001) were both factors associated with self-neglect in older adults. CONCLUSION: Management of depression and improvement of social networks of older adults should be incorporated into interventional strategies to effectively control self-neglect. Understanding self-neglect and its associated factors will ultimately contribute to the intervention development and well-being of older adults.

The association between loneliness and sleep quality among older adults: A systematic review and meta-analysis.

OBJECTIVE: To systematically review studies and explore the association between loneliness and sleep quality among older adults. METHODS: A comprehensive literature search was conducted in 8 databases from their inception to February 28, 2022. Studies that investigated the association between loneliness and sleep quality among older people were obtained. Comprehensive Meta-analysis was used to meta-analyze data in the included studies. RESULTS: In total, 16 studies with 23,485 participants were included in this review, and 6 of these studies were included in the meta-analysis. The meta-analysis showed that older adults who were lonely were significantly more likely to suffer from low sleep quality than their counterparts without loneliness (pooled OR = 1.750, 95% CI: 1.511-2.026, p < 0.01). CONCLUSIONS: Loneliness is associated with poor sleep quality among older adults. Loneliness reduction measures should be considered as one of the essential elements in sleep management programs for older people with low sleep quality.