Fertility history and intentions of married women, China.

Objective: To estimate the proportion of married women in China who intend to become pregnant given the country's pronatalist population policy and to investigate fecundity, with an emphasis on the influence of socioeconomic factors. Methods: A nationally representative survey of 12 815 married women aged 20 to 49 years (mean: 36.8 years) was conducted during 2019 and 2020. All completed questionnaires, 10 115 gave blood samples and 11 710 underwent pelvic ultrasound examination. Fertility intention was the desire or intent to become pregnant combined with engagement in unprotected sexual intercourse. We defined infertility as the failure to achieve pregnancy after 12 months or more of unprotected intercourse. We considered an anti-Müllerian hormone level < 1.1 ng/mL and an antral follicular count < 7 as indicating an abnormal ovarian reserve. Findings: Fertility intentions were reported by 11.9% of women overall but by only 6.1% of current mothers (weighted percentages). Fertility intention was significantly less likely among women in metropolises (odds ratio, OR: 0.38; 95% confidence interval, CI: 0.31-0.45) and those with a higher educational level (OR: 0.74; 95% CI: 0.62-0.88). Overall, 18.0% had experienced infertility at any time and almost 30% had an abnormal ovarian reserve on assessment. An abnormal ovarian reserve and infertility were less likely in women in metropolises (P < 0.05) but more likely in obese women (P < 0.05). Conclusion: The willingness of Chinese married women to give birth remained low, even with relaxation of the one-child policy.

Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging.

The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.

Latent profiles of academic resilience in undergraduate nursing students and their association with resilience and self-efficacy.

AIM: This study aimed to investigate the heterogeneity of academic resilience among nursing students using latent profile analysis and its associated influencing factors. BACKGROUND: Nursing students experience higher levels of stress compared to their peers in other professions, and the cultivation of academic resilience plays a pivotal role in their ability to effectively cope with this stress. Academic resilience not only facilitates success in the face of academic adversity but also contributes to the promotion of mental well-being among nursing students. However, the current research on the academic resilience of nursing students has predominantly focused on a scale-centered total score approach, disregarding individual variability, and hindering the development to inform personalized interventions for enhancing academic resilience. DESIGN: A cross-sectional study. METHODS: A convenience sampling method was used to collect a total of 644 nursing students from two medical schools in Guangzhou City. The participants were recruited through an online survey conducted from January to March 2023. The questionnaires consisted of a general information form, the Chinese version of the Academic Resilience Scale-30 (C-ARS-30), the 10-item Connor Davidson Resilience Scale (CD-RISC-10), and the General Self-Efficacy Scale (GSES). Latent profile analysis was used to identify distinct categories of academic resilience among nursing students, and influencing factors were examined through ordinal logistic regression analysis. RESULTS: The academic resilience levels of nursing students can be divided into three potential categories: 'low academic resilience' (13.0%), 'moderate academic resilience' (70.0%), and 'high academic resilience' (17.0%). Level of grade, GPA, self-reported physical health level, resilience and self-efficacy were significantly influenced the different categories of academic resilience of nursing students (P<0.05). CONCLUSIONS: The majority of undergraduate nursing students were placed in the moderate academic resilience group, however, educational institutions should pay special attention to nursing students demonstrating low levels. Regular assessments of academic resilience are recommended, and personalized interventions should be tailored to address specific academic resilience characteristics across different grades of nursing students. Strategies aimed at enhancing academic resilience among nursing students may include improvements in GPA performance, attention to physical health, and the reinforcement of resilience and self-efficacy.

Empagliflozin and liraglutide ameliorate HFpEF in mice via augmenting the Erbb4 signaling pathway.

Heart failure with preserved ejection fraction (HFpEF) is closely associated with metabolic derangement. Sodium glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) exert anti-HFpEF effects, but the underlying mechanisms remain unclear. In this study, we explored the anti-HFpEF effects of empagliflozin and liraglutide and the underlying molecular mechanisms in a mouse model of HFpEF. This model was established by high-fat diet (HFD) feeding plus Nω-nitro-L-arginine methyl ester (L-NAME) treatment. The mice were treated with empagliflozin (20 mg·kg-1·d-1, i.g.) or liraglutide (0.3 mg·kg-1·d-1, i.p.) or their combination for 4 weeks. At the end of the experimental protocol, cardiac function was measured using ultrasound, then mice were euthanized and heart, liver, and kidney tissues were collected. Nuclei were isolated from frozen mouse ventricular tissue for single-nucleus RNA-sequencing (snRNA-seq). We showed that administration of empagliflozin or liraglutide alone or in combination significantly improved diastolic function, ameliorated cardiomyocyte hypertrophy and cardiac fibrosis, as well as exercise tolerance but no synergism was observed in the combination group. Furthermore, empagliflozin and/or liraglutide lowered body weight, improved glucose metabolism, lowered blood pressure, and improved liver and kidney function. After the withdrawal of empagliflozin or liraglutide for 1 week, these beneficial effects tended to diminish. The snRNA-seq analysis revealed a subcluster of myocytes, in which Erbb4 expression was down-regulated under HFpEF conditions, and restored by empagliflozin or liraglutide. Pseudo-time trajectory analysis and cell-to-cell communication studies confirmed that the Erbb4 pathway was a prominent pathway essential for both drug actions. In the HFpEF mouse model, both empagliflozin and liraglutide reversed Erbb4 down-regulation. In rat h9c2 cells, we showed that palmitic acid- or high glucose-induced changes in PKCα and/or ERK1/2 phosphorylation at least in part through Erbb4. Collectively, the single-cell atlas reveals the anti-HFpEF mechanism of empagliflozin and liraglutide, suggesting that Erbb4 pathway represents a new therapeutic target for HFpEF. Effects and mechanisms of action of empagliflozin and liraglutide in HFpEF mice. HFpEF was induced with a high-fat diet and L-NAME for 15 weeks, and treatment with empagliflozin and liraglutide improved the HFpEF phenotype. Single nucleus RNA sequencing (snRNA-seq) was used to reveal the underlying mechanism of action of empagliflozin and liraglutide.

Prediction of vascular complications in free flap reconstruction with machine learning.

OBJECTIVE: This study aims to explore the risk factors of vascular complications following free flap reconstruction and to develop a clinical auxiliary assessment tool for predicting vascular complications in patients undergoing free flap reconstruction leveraging machine learning methods. METHODS: We reviewed the medical data of patients who underwent free flap reconstruction at the Affiliated Hospital of Zunyi Medical University retrospectively from January 1, 2019, to December 31, 2021. Statistical analysis was used to screen risk factors. A training data set was generated and augmented using the synthetic minority oversampling technique. Logistic regression, random forest and neural network, models were trained, using this dataset. The performance of these three predictive models was then evaluated and compared using a test set, with four metrics, area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTS: A total of 570 patients who underwent free flap reconstruction were included in this study, 46 of whom developed postoperative vascular complications. Among the models tested, the neural network model exhibited superior performance on the test set, achieving an AUC of 0.828. Multivariate logistic regression analysis identified that preoperative hemoglobin levels, preoperative fibrinogen levels, operation duration, smoking history, the number of anastomoses, and peripheral vascular injury as statistically significant independent risk factors for vascular complications post-free flap reconstruction. The top five predictive factors in the neural network were fibrinogen content, operation duration, donor site, body mass index (BMI), and platelet count. CONCLUSION: Hemoglobin levels, fibrinogen levels, operation duration, smoking history, and anastomotic veins are independent risk factors for vascular complications following free flap reconstruction. These risk factors enhance the ability of machine learning models to predict the occurrence of vascular complications and identify high-risk patients. The neural network model outperformed the logistic regression and random forest models, suggesting its potential to aid clinicians in early identification of high-risk patients thereby mitigating patient suffering and improving prognosis.

Ergosterols with rare peroxide, oxetane ring moiety, and a lactone ring from Aspergillus spectabilis and their immunosuppressive activities.

Ten ergostane-type steroids, including seven undescribed ones named spectasteroids A-G, were obtained from Aspergillus spectabilis. Their structures and absolute configurations were determined based on HRESIMS, NMR, ECD calculations, and single-crystal X-ray diffraction analyses. Structurally, spectasteroid A was a unique example of aromatic ergostane-type steroid that featured a rare peroxide ring moiety; spectasteroid B contained a rare oxetane ring system formed between C-9 and C-14; and spectasteroid C was an unusual 3,4-seco-ergostane steroid with an extra lactone ring between C-3 and C-9. Spectasteroids F and G specifically showed inhibitory effects against concanavalin A-induced T lymphocyte proliferation and lipopolysaccharide-induced B lymphocyte proliferation, with IC50 values ranging from 2.33 to 4.22 µM. Spectasteroid F also showed excellent antimultidrug resistance activity, which remarkable enhanced the inhibitory activity of PTX on the colony formation of SW620/Ad300 cells.

Can irisin be developed as the molecular evolutionary clock based on the origin and functions?

Irisin, a myokine identified in 2012, has garnered research interest for its capacity to induce browning of adipocytes and improve metabolic parameters. As such, the potential therapeutic applications of this exercise-induced peptide continue to be explored. Though present across diverse animal species, sequence analysis has revealed subtle variation in the irisin protein. In this review, we consider the effects of irisin on disease states in light of its molecular evolution. We summarize current evidence for irisin's influence on pathologies and discuss how sequence changes may inform development of irisin-based therapies. Furthermore, we propose that the phylogenetic variations in irisin could potentially be leveraged as a molecular clock to elucidate evolutionary relationships.

Tumor Size Is Not Everything: Advancing Radiomics as a Precision Medicine Biomarker in Oncology Drug Development and Clinical Care. A Report of a Multidisciplinary Workshop Coordinated by the RECIST Working Group.

Radiomics, the science of extracting quantifiable data from routine medical images, is a powerful tool that has many potential applications in oncology. The Response Evaluation Criteria in Solid Tumors Working Group (RWG) held a workshop in May 2022, which brought together various stakeholders to discuss the potential role of radiomics in oncology drug development and clinical trials, particularly with respect to response assessment. This article summarizes the results of that workshop, reviewing radiomics for the practicing oncologist and highlighting the work that needs to be done to move forward the incorporation of radiomics into clinical trials.

Physiologically based modeling of LNP-mediated delivery of mRNA in the vascular system.

RNA therapeutics are an emerging, powerful class of drugs with potential applications in a wide range of disorders. A central challenge in their development is the lack of clear pharmacokinetic (PK)-pharmacodynamic relationship, in part due to the significant delay between the kinetics of RNA delivery and the onset of pharmacologic response. To bridge this gap, we have developed a physiologically based PK/pharmacodynamic model for systemically administered mRNA-containing lipid nanoparticles (LNPs) in mice. This model accounts for the physiologic determinants of mRNA delivery, active targeting in the vasculature, and differential transgene expression based on nanoparticle coating. The model was able to well-characterize the blood and tissue PKs of LNPs, as well as the kinetics of tissue luciferase expression measured by ex vivo activity in organ homogenates and bioluminescence imaging in intact organs. The predictive capabilities of the model were validated using a formulation targeted to intercellular adhesion molecule-1 and the model predicted nanoparticle delivery and luciferase expression within a 2-fold error for all organs. This modeling platform represents an initial strategy that can be expanded upon and utilized to predict the in vivo behavior of RNA-containing LNPs developed for an array of conditions and across species.

Visual Cognitive Assessment Test: Utility of the brief cognitive battery for early screening of cognitive impairment in Chongqing, China.

OBJECTIVES: Early detection of cognitive impairment is essential for timely intervention. Currently, most widely used cognitive screening tests are influenced by language and cultural differences; therefore, there is a need for the development of a language-neutral, visual-based cognitive assessment tool. The Visual Cognitive Assessment Test (VCAT), a 30-point test that assesses memory, executive function, visuospatial function, attention, and language, has demonstrated its utility in a multilingual population. In this study, we evaluated the reliability, validity, and diagnostic performance of the VCAT for screening early cognitive impairment in Chongqing, China METHODS: A total of 134 individuals (49 healthy controls (HCs), 52 with mild cognitive impairment (MCI), and 33 with mild dementia) completed the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), VCAT, and domain-specific neuropsychological assessments. The diagnostic performances of MMSE, MoCA, and VCAT were evaluated using the area under the curve (AUC), sensitivity, and specificity. Construct validity of the VCAT was assessed with well-established domain-specific cognitive assessments. Reliability was measured using Cronbach's alpha. RESULTS: The VCAT and its subdomains demonstrated both good construct validity and internal consistency (α = 0.577). The performance of VCAT was comparable to that of MoCA and MMSE in differentiating mild dementia from nondemented groups (AUC: 0.940 vs. 0.902 and 0.977, respectively; p = .098 and .053) and in distinguishing cognitive impairment (CI) from HC (AUC: 0.929 vs. 0.899 and 0.891, respectively; p = .239 and .161), adjusted for education level. The optimal score range for VCAT in determining dementia, MCI, and HC was 0-14, 15-19, and 20-30, respectively. CONCLUSION: The VCAT proves to be a reliable screening test for early cognitive impairment within our cohort. Being both language and cultural neutral, the VCAT has the potential to be utilized among a wider population within China.

Multiscale calculations reveal new insights into the reaction mechanism between KRASG12C and α, ß-unsaturated carbonyl of covalent inhibitors.

Utilizing α,ß-unsaturated carbonyl group as Michael acceptors to react with thiols represents a successful strategy for developing KRASG12C inhibitors. Despite this, the precise reaction mechanism between KRASG12C and covalent inhibitors remains a subject of debate, primarily due to the absence of an appropriate residue capable of deprotonating the cysteine thiol as a base. To uncover this reaction mechanism, we first discussed the chemical reaction mechanism in solvent conditions via density functional theory (DFT) calculation. Based on this, we then proposed and validated the enzymatic reaction mechanism by employing quantum mechanics/molecular mechanics (QM/MM) calculation. Our QM/MM analysis suggests that, in biological conditions, proton transfer and nucleophilic addition may proceed through a concerted process to form an enolate intermediate, bypassing the need for a base catalyst. This proposed mechanism differs from previous findings. Following the formation of the enolate intermediate, solvent-assisted tautomerization results in the final product. Our calculations indicate that solvent-assisted tautomerization is the rate-limiting step in the catalytic cycle under biological conditions. On the basis of this reaction mechanism, the calculated kinact/ki for two inhibitors is consistent well with the experimental results. Our findings provide new insights into the reaction mechanism between the cysteine of KRASG12C and the covalent inhibitors and may provide valuable information for designing effective covalent inhibitors targeting KRASG12C and other similar targets.

Exposure to heavy metallic and trace essential elements and risk of diminished ovarian reserve in reproductive age women: A case-control study.

The associations between metallic elements and ovarian reserve function have remained uncertain yet. In this case-control study, we involved 149 women with diminished ovarian reserve (DOR) and 151 women with normal ovarian reserve, and assessed the levels of six heavy metallic (Cr, Cd, As, Hg, Pb, and Mn) and seven trace essential (Se, Fe, Zn, Co, Mo, Cu, I) elements in their follicular fluid with inductively coupled plasma mass spectrometry. Associations were examined with logistic regressions and Bayesian kernel machine regression (BKMR). As a result, we found that the medium and the highest tertiles of Pb were significantly associated with an increased likelihood of DOR compared to the lowest tertile, while the medium or/an the highest tertiles of Cu, I, and Fe showed significantly lower likelihoods of DOR compared to the lowest tertiles. Cu and Pb showed significantly non-linear associations with ovarian reserve markers such as follicle-stimulating, anti-mullerian hormone levels, and antral follicle count. With the rising overall concentrations of heavy metals, the likelihood of DOR increased although not significant. There was a trend of a "U-shaped" association across the whole concentration range of trace essential elements and the likelihood of DOR. Our study revealed that avoiding heavy metallic elements and properly supplementing trace essential elements are conducive to ovarian function.

Unveiling the Potential of Two-Terminal Perovskite/Organic Tandem Solar Cells: Mechanisms, Status, and Challenges.

Perovskite/organic tandem solar cells (PO-TSCs) demonstrate exceptional suitability for emerging applications such as building-integrated photovoltaics, wearable devices, and greenhouse farming. By leveraging the distinctive attributes of perovskite and organic materials, which encompass expanded solar spectrum utilization, chemically benign solubility, and soft nature, PO-TSCs position themselves as ideal candidates for high-performance semi-transparent photovoltaics (ST-PVs). Despite these advantages, their development significantly lags behind other perovskite-based counterparts, such as perovskite/perovskite, perovskite/silicon, and perovskite/Cu(In, Ga)Se2. To address existing challenges and unlock the full potential of PO-TSCs, an exploration of the fundamental mechanisms governing tandem photovoltaic devices is embarked. Delving into critical aspects such as charge generation/separation, energy level alignment, and material choices becomes pivotal for optimizing PO-TSC performance. The investigation of monolithic two-terminal PO-TSCs offers insights into achievements and barriers, recognizing the competitive landscape with other TSC counterparts. Further scrutiny of perovskite absorbers and organic absorbers in TSCs reveals strategies aimed at enhancing stability and efficiency. The discussion extends to interconnection layers, elucidating their role in optimizing light transmission and balancing carrier recombination. In conclusion, a compelling outlook on the dynamic landscape of PO-TSCs is presented, highlighting the remarkable efficiency progression and signaling their potential to revolutionize solar energy harvesting technologies.

Dual-Aptamer Recognition of DNA Logic Gate Sensor-Based Specific Exosomal Proteins for Ovarian Cancer Diagnosis.

Clinical diagnosis of ovarian cancer lacks high accuracy due to the weak selection of specific biomarkers along with the circumstance biomarkers localization. Clustering analysis of proteins transported on exosomes enables a more precise screening of effective biomarkers. Herein, through bioinformatics analysis of ovarian cancer and exosome proteomes, two coexpressed proteins, EpCAM and CD24, specifically enriched, were identified, together with the development of an as-derived dual-aptamer targeted exosome-based strategy for ovarian cancer screening. In brief, a DNA ternary polymer with aptamers targeting EpCAM and CD24 was designed to present a logic gate reaction upon recognizing ovarian cancer exosomes, triggering a rolling circle amplification chemiluminescent signal. A dynamic detection range of 6 orders of magnitude was achieved by quantifying exosomes. Moreover, for clinical samples, this strategy could accurately differentiate exosomes from healthy persons, other cancer patients, and ovarian cancer patients, enabling promising in situ detection. By accurately selecting biomarkers and constructing a dual-targeted exosomal protein detection strategy, the limitation of insufficient specificity of traditional protein markers was circumvented. This work contributed to the development of exosome-based prognosis monitoring in ovarian cancer through the identification of disease-specific exosome protein markers.

Transmembrane Determinants of Voltage Gating Differences Between BK (Slo1) and Slo3 Channels.

Voltage-gated potassium channels are critical in modulating cellular excitability, with Slo (slowpoke) channels forming a unique family characterized by their large conductance and dual regulation by electrical signals and intracellular messengers. Despite their structural and evolutionary similarities, Slo1 and Slo3 channels exhibit significant differences in their voltage-gating properties. This study investigates the molecular determinants that differentiate the voltage-gating properties of human Slo1 and mouse Slo3 channels. Utilizing Slo1/Slo3 chimeras, we pinpointed the selectivity filter region as a key factor in the Slo3 channel's reduced conductance at negative voltages. The S6 transmembrane (TM) segment was identified as pivotal for the Slo3 channel's biphasic deactivation kinetics at these voltages. Additionally, the S4 and S6 TM segments were found to be responsible for the gradual slope in the Slo3 channel's conductance-voltage (G-V) relationship, while multiple TM regions appear to be involved in the Slo3 channel's requirement of strong depolarization for activation. Mutations in the Slo1's S5 and S6 TM segments revealed three residues (I233, L302, and M304) that likely play a crucial role in the allosteric coupling between the voltage sensors and the pore gate.

Whole-genome sequencing of Sphingobium baderi SC-1 and identification of a crucial 3-phenoxybenzoic acid-degrading gene.

As an efficient degradation strain, Sphingobium baderi SC-1 can breakdown 3-phenoxybenzoic acid (3-PBA) with high proficiency. To investigate the internal factors that regulate this process, we conducted whole-genome sequencing and successfully identified the pivotal 3-PBA-degrading gene sca (1,230 bp). After sca was expressed in engineered bacteria, a remarkable degradation efficiency was observed, as 20 mg/L 3-PBA was almost completely decomposed within 24 h. The phenol was formed as one of the degradation products. Notably, in addition to their ability to degrade 3-PBA, the resting cells proficiently degraded 4'-HO-3-PBA and 3'-HO-4-PBA. In conclusion, we successfully identified and validated sca as the pivotal enzyme responsible for the efficient degradation of 3-PBA from Sphingomonas baderi, providing a crucial theoretical foundation for further explorations on the degradation potential of SC-1.

Occurrence of ochratoxin A in Sichuan bacon from different geographical regions and characterization and biocontrol of ochratoxigenic Aspergillus westerdijkiae strain 21G2-1A.

Sichuan bacon represents the most prevalent dry-cured meat product across Southwest China, but it is vulnerable to fungal spoilage. In the present study, a total of 47 Sichuan bacons were obtained from different regions of the Sichuan Province and analyzed for the presence of ochratoxin A (OTA), yielding a positive rate of 23.4 % (11/47). All the observed OTA concentrations exceeded the maximum admissible dose in meat products (1 µg/kg) established by some EU countries, with the highest OTA concentration being 250.75 µg/kg, which raises a food safety concern and reveals the need for a standardized scientific processing protocol. Then, an OTA-producing fungus named 21G2-1A was isolated from positive samples and found to be Aspergillus westerdijkiae. Further characterization suggested a positive correlation between fungal growth and OTA production. The optimal temperature for the former was 25 °C, while it was 20 °C for the latter. Although the A. westerdijkiae strain 21G2-1A demonstrated greater mycelium growth in the presence of NaCl, OTA production was significantly dismissed when the salinity was greater than 5 %. Four lactic acid bacteria (LAB) were screened out as antagonists against the ochratoxigenic fungus. In vitro evaluation of the antagonists revealed that live cells inhibited fungal growth, and adsorption also contributed to OTA removal at different levels. This study sheds some light on OTA control in Sichuan bacon through a biological approach.

[Spatial and Temporal Distribution Characteristics of Ozone Concentration and Health Benefit Assessment in the Beijing-Tianjin-Hebei Region from 2015 to 2020].

To evaluate the spatial and temporal distribution characteristics of ambient ozone (O3) in the Beijing-Tianjin-Hebei (BTH) Region, the land use regression (LUR) model and random forest (RF) model were used to simulate the ambient O3 concentration from 2015 to 2020. Meanwhile, all-cause, cardiovascular, and respiratory mortalities as well as economic losses attributed to O3 were also estimated. The results showed that upward trends with fluctuation were observed for ambient O3 concentration, mortalities, and economic losses attributable to O3 exposure in the BTH Region from 2015 to 2020. The areas with high O3 concentration and great changes were concentrated in the central and southwestern regions, whereas the concentration in the northern region was low, and the change degree was small. The spatial distribution of the mortalities was also consistent with the spatial distribution of O3 concentration. From 2015 to 2020, the economic losses regarding all-cause mortality and cardiovascular mortality increased in 13 cities of the BTH Region, whereas the economic losses of respiratory mortality decreased in 4 cities in the BTH Region. The results indicated that the priority areas for O3 control were not uniform. Specifically, Beijing, Tianjin, Hengshui, and Xingtai were vital areas for O3 pollution control in the BTH Region. Differentiated control measures should be adopted based on the characteristics of these target areas to decline O3 concentration and reduce health impacts and economic losses associated with O3 exposure.

Deciphering microglial activation and neuronal apoptosis post­traumatic brain injury: The role of TYROBP in inflammation regulation networks.

Traumatic Brain Injury (TBI) represents a significant public health challenge. Recovery from brain injury necessitates the collaborative efforts of various resident neural cells, predominantly microglia. The present study analyzed rat and mouse RNA expression micro­arrays, high­throughput RNA sequencing and single­cell sequencing data sourced from public databases. To construct an inflammation regulation network around TYRO protein tyrosine kinase­binding protein (TYROBP), to evaluate the role of TYROBP in cell death after TBI. These findings indicate that following TBI, neurons predominantly communicate with one another through the CXC chemokine ligand (CXCL) and CC chemokine ligand (CCL) signaling pathways, employing a paracrine mechanism to activate microglia. These activated microglia intensify the pathological progression of brain injury by releasing factors such as tumor necrosis factor α (TNF­α), vascular endothelial growth factor and transforming growth factor ß via the NF­κB pathway. Cells co­culture experiments demonstrated that neurons, impaired by mechanical injury, interact with microglia through non­contact mechanisms. Activated microglia secrete cytokines, including TNF­α, CXCL­8 and CCL2, which trigger an inflammatory response and facilitate neuronal apoptosis. TYROBP gene knockout in microglia was demonstrated to reduce this interaction and reduce neuronal cell apoptosis rates.

Construction and validation of machine learning algorithm for predicting depression among home-quarantined individuals during the large-scale COVID-19 outbreak: based on Adaboost model.

OBJECTIVES: COVID-19 epidemics often lead to elevated levels of depression. To accurately identify and predict depression levels in home-quarantined individuals during a COVID-19 epidemic, this study constructed a depression prediction model based on multiple machine learning algorithms and validated its effectiveness. METHODS: A cross-sectional method was used to examine the depression status of individuals quarantined at home during the epidemic via the network. Characteristics included variables on sociodemographics, COVID-19 and its prevention and control measures, impact on life, work, health and economy after the city was sealed off, and PHQ-9 scale scores. The home-quarantined subjects were randomly divided into training set and validation set according to the ratio of 7:3, and the performance of different machine learning models were compared by 10-fold cross-validation, and the model algorithm with the best performance was selected from 15 models to construct and validate the depression prediction model for home-quarantined subjects. The validity of different models was compared based on accuracy, precision, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC), and the best model suitable for the data framework of this study was identified. RESULTS: The prevalence of depression among home-quarantined individuals during the epidemic was 31.66% (202/638), and the constructed Adaboost depression prediction model had an ACC of 0.7917, an accuracy of 0.7180, and an AUC of 0.7803, which was better than the other 15 models on the combination of various performance measures. In the validation sets, the AUC was greater than 0.83. CONCLUSIONS: The Adaboost machine learning algorithm developed in this study can be used to construct a depression prediction model for home-quarantined individuals that has better machine learning performance, as well as high effectiveness, robustness, and generalizability.