3D reconstruction of a gastrulating human embryo.

Progress in understanding early human development has been impeded by the scarcity of reference datasets from natural embryos, particularly those with spatial information during crucial stages like gastrulation. We conducted high-resolution spatial transcriptomics profiling on 38,562 spots from 62 transverse sections of an intact Carnegie stage (CS) 8 human embryo. From this spatial transcriptomic dataset, we constructed a 3D model of the CS8 embryo, in which a range of cell subtypes are identified, based on gene expression patterns and positional register, along the anterior-posterior, medial-lateral, and dorsal-ventral axis in the embryo. We further characterized the lineage trajectories of embryonic and extra-embryonic tissues and associated regulons and the regionalization of signaling centers and signaling activities that underpin lineage progression and tissue patterning during gastrulation. Collectively, the findings of this study provide insights into gastrulation and post-gastrulation development of the human embryo.

Plasma Proteomics Identify Biomarkers and Pathogenesis of COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic is a global public health crisis. However, little is known about the pathogenesis and biomarkers of COVID-19. Here, we profiled host responses to COVID-19 by performing plasma proteomics of a cohort of COVID-19 patients, including non-survivors and survivors recovered from mild or severe symptoms, and uncovered numerous COVID-19-associated alterations of plasma proteins. We developed a machine-learning-based pipeline to identify 11 proteins as biomarkers and a set of biomarker combinations, which were validated by an independent cohort and accurately distinguished and predicted COVID-19 outcomes. Some of the biomarkers were further validated by enzyme-linked immunosorbent assay (ELISA) using a larger cohort. These markedly altered proteins, including the biomarkers, mediate pathophysiological pathways, such as immune or inflammatory responses, platelet degranulation and coagulation, and metabolism, that likely contribute to the pathogenesis. Our findings provide valuable knowledge about COVID-19 biomarkers and shed light on the pathogenesis and potential therapeutic targets of COVID-19.

Photobiocatalytic Platform for the Efficient Enantio-Divergent Synthesis of ß-Fluoromethylated Ketones.

ß-Fluoromethyl (CH2F, CHF2, and CF3)-substituted chiral ketones are essential moieties and are vital building blocks in pharmaceutical and agrochemistry. However, general and convenient methods for enantio-diverse access to diverse ß-fluoromethylated ketones are lacking, hindering the further development of these functional moieties. In this study, we developed an ene-reductase-based photobiocatalytic platform for efficient synthesis of enantio-divergent ß-fluoromethylated chiral ketones. Our method highlights substrate-type diversity, excellent enantioselectivity, enzymatic enantio-divergent synthesis, as well as a dicyanopyrazine (DPZ)-type photosensitizer for biocompatible olefin E/Z isomerization in enzymatic stereoconvergent olefin asymmetric reduction, thereby providing a general photobiocatalytic solution to diverse ß-fluoromethylated chiral ketones.

Prolonged Early Exposure to a High-Fat Diet Augments the Adverse Effects on Neurobehavior and Hippocampal Neuroplasticity: Involvement of Microglial Insulin Signaling.

High-fat diet (HFD) consumption may contribute to the high prevalence of cognitive-emotional issues in modern society. Mice fed a HFD for a prolonged period develop more severe neurobehavioral disturbances when first exposed to a HFD in the juvenile period than in adulthood, suggesting an initial age-related difference in the detrimental effects of long-term HFD feeding. However, the mechanism underlying this difference remains unclear. Here, male C57BL/6J mice initially aged 4 (IA4W) or 8 (IA8W) weeks were fed a control diet (CD) or HFD for 6 months and then subjected to metabolic, neurobehavioral, and histomorphological examinations. Although the detrimental effects of long-term HFD feeding on metabolism and neurobehavior were observed in mice of both ages, IA4W-HFD mice showed significant cognitive inflexibility accompanied by significantly greater levels of anxiety-like behavior than age-matched controls. Hippocampal neuroplasticity and microglial phenotype were altered by HFD feeding, whereas significant morphological alterations were more frequently observed in IA4W-HFD mice than in IA8W-HFD mice. Additionally, significantly increased hippocampal microglial engulfment of postsynaptic proteins and elevated phospho-insulin-receptor levels were observed in IA4W-HFD, but not in IA8W-HFD, mice. These findings suggest that aberrant microglia-related histomorphological changes in the hippocampus underlie the exacerbated detrimental neurobehavioral effects of prolonged early HFD exposure and indicate that enhanced insulin signaling might drive microglial dysfunction after prolonged early HFD exposure.

Isovanillin decreases the virulence regulated by the quorum sensing system of Pseudomonas aeruginosa.

The quorum-sensing (QS) system of Pseudomonas aeruginosa dominates the pathogenicity of the acute or chronic infection process. Hence, curbing the pathogenicity of P. aeruginosa by targeting QS system is an ideal strategy. This study aims to identify potential anti-virulence compounds that can effectively disrupt the QS system of P. aeruginosa using a combination of virtual screening and experimental validation techniques. We explored inhibitory effect of isovanillin obtained by virtual screening on P. aeruginosa QS regulated virulence factors extracellular protease, biofilm, and pyocyanin. Results displayed that isovanillin could inhibit the virulence phenotypes regulated by the las- and pqs-QS systems of P. aeruginosa. The synthesis of extracellular proteases, pyocyanin, and biofilm formation by P. aeruginosa were dramatically inhibited by sub-MICs doses of isovanillin. The results of RNA sequencing and quantitative PCR revealed that the QS-activated genes down-regulated by subinhibitory isovanillin in the transcriptional evels. Furthermore, the presence of isovanillin increased the susceptibility of drug-resistant P. aeruginosa to kanamycin, meropenem, and polymyxin B. Treatment of isovanillin as a monotherapy significantly decreased the mortality of C. elegans in P. aeruginosa PAO1 or UCBPP-PA14 (PA14) infection. Our study reported the anti-virulence activity of isovanillin against P. aeruginosa, and provided a structural foundation for developing anti-virulence drugs targeting the QS system of P. aeruginosa.

Phage cocktail inhibits inflammation and protects the integrity of the intestinal barrier in dextran sulfate sodium-induced colitis mice model.

Ulcerative colitis (UC) is an inflammatory bowel disease characterized by abdominal pain, diarrhea, and rectal bleeding. This study aims to explore the protective effects of a phage cocktail (108 PFU/mL of Clostridium perfringens phage, 108 PFU/mL of Escherichia coli phage, and 108 PFU/mL of Salmonella phage) on a mouse colitis model induced by dextran sulfate sodium (DSS) and its potential toxic effects on normal mice. The results demonstrate that the phage cocktail significantly alleviates clinical symptoms in mice, reduces colon shortening, weight loss, and colonic pathological damage. Furthermore, the phage cocktail markedly suppresses the inflammatory response and safeguards intestinal barrier integrity in the colonic tissues of the mouse colitis model. Preliminary investigation of the toxic effects of the phage cocktail in mice indicates that continuous administration for 14 days does not yield statistically significant differences in hematological and blood biochemical parameters, and specific pathological changes are absent in histopathological examination results. The aforementioned findings suggest that the phage cocktail exhibits anti-inflammatory and intestinal barrier protective effects in the mouse colitis model, and it does not exert significant toxic side effects on mice.

Microglial SCAP deficiency protects against diabetes-associated cognitive impairment through inhibiting NLRP3 inflammasome-mediated neuroinflammation.

Hyperglycemia-induced pathological microglial responses and subsequent neuronal damage are notable characteristics of diabetes-associated cognitive impairment (DACI). Cholesterol accumulation in the brain is a prevalent consequence of diabetes mellitus (DM), exacerbating pathological microglial responses. Regarding disordered glucose and lipid metabolism, the Sterol Regulatory Element-Binding Protein (SREBP) cleavage-activating protein (SCAP), a cholesterol sensor, exhibits increased expression and abnormal translocation from the endoplasmic reticulum to the Golgi, amplifying the inflammatory response. Therefore, we hypothesized that overexpression of microglia-SCAP and cholesterol accumulation in DM mice could induce pathological microglial responses associated with DACI. Our type 2 DM mice model presented an abnormal increase in microglial SCAP expression. The functional loss of microglia-specific SCAP in DM mice improved cognitive impairment, neuronal synaptic plasticity deficits, and abnormal microglial responses. Mechanistically, the accumulated SCAP directly bound to and enhanced the activation of the microglial-specific inflammatory amplifier, NLRP3 inflammasome, in Golgi, thereby increasing pathological microglial responses and promoting neuronal damage. These findings indicate an important regulatory axis of microglial responses from SCAP to the NLRP3 inflammasome pathway in microglia. These underscore the crosstalk between cholesterol disorders and pathological microglial responses, offering a promising avenue for pharmaceutical interventions in DACI.

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing ischemic changes in acute ischemic stroke using non-contrast computed tomography (NCCT), is often interpreted relying on expert experience and can vary between readers. This study aimed to develop a clinically applicable automatic ASPECTS system employing deep learning (DL). METHODS: This study enrolled 1987 NCCT scans that were retrospectively collected from four centers between January 2017 and October 2021. A DL-based system for automated ASPECTS assessment was trained on a development cohort (N = 1767) and validated on an independent test cohort (N = 220). The consensus of experienced physicians was regarded as a reference standard. The validity and reliability of the proposed system were assessed against physicians' readings. A real-world prospective application study with 13,399 patients was used for system validation in clinical contexts. RESULTS: The DL-based system achieved an area under the receiver operating characteristic curve (AUC) of 84.97% and an intraclass correlation coefficient (ICC) of 0.84 for overall-level analysis on the test cohort. The system's diagnostic sensitivity was 94.61% for patients with dichotomized ASPECTS at a threshold of ≥ 6, with substantial agreement (ICC = 0.65) with expert ratings. Combining the system with physicians improved AUC from 67.43 to 89.76%, reducing diagnosis time from 130.6 ± 66.3 s to 33.3 ± 8.3 s (p < 0.001). During the application in clinical contexts, 94.0% (12,591) of scans successfully processed by the system were utilized by clinicians, and 96% of physicians acknowledged significant improvement in work efficiency. CONCLUSION: The proposed DL-based system could accurately and rapidly determine ASPECTS, which might facilitate clinical workflow for early intervention. CLINICAL RELEVANCE STATEMENT: The deep learning-based automated ASPECTS evaluation system can accurately and rapidly determine ASPECTS for early intervention in clinical workflows, reducing processing time for physicians by 74.8%, but still requires validation by physicians when in clinical applications. KEY POINTS: The deep learning-based system for ASPECTS quantification has been shown to be non-inferior to expert-rated ASPECTS. This system improved the consistency of ASPECTS evaluation and reduced processing time to 33.3 seconds per scan. 94.0% of scans successfully processed by the system were utilized by clinicians during the prospective clinical application.

Integrated Knowledge Graph and Drug Molecular Graph Fusion via Adversarial Networks for Drug-Drug Interaction Prediction.

The Co-administration of multiple drugs can enhance the efficacy of disease treatment by reducing drug resistance and side effects. However, it also raises the risk of adverse drug interactions, presenting a challenging problem in healthcare. Various approaches have been developed to predict drug-drug interactions (DDIs) by leveraging both knowledge graphs and drug attribute information. While these methods have shown promise, they often fail to effectively capture correlations between biomedical information in the knowledge graph and drug properties. This work introduces a novel end-to-end DDI predictor framework based on generative adversarial networks. This framework utilizes a message-passing neural network to capture molecular structure information while employing the knowledge-aware graph attention network to capture the representation of drugs in the knowledge graph through considering the importance of different multihop neighbor nodes and relationships. The dual generative adversarial networks employ two generators and two discriminators in knowledge graph embedding and molecular topology embedding for adversarial training to capture the interrelations and complementary knowledge between molecular structure information and semantic information from the knowledge graph. comprehensive experiments have demonstrated that the proposed method outperforms state-of-the-art algorithms in binary classification, with improvements of 1.0% in accuracy, 0.45% in area under the receiver operating characteristic curve (AUC), 0.24% in area under the precision-recall curve (AUPR), and 0.98% in F1 score. Furthermore, for multiclass classification tasks, improvements were observed across various evaluation metrics, including 0.9% in accuracy, 0.25% in macro precision, 0.2% in macro recall, and 0.28% in macro F1. Additionally, ablation studies were conducted to showcase the effectiveness and robustness of our method in DDI prediction tasks.

Prevalence and Risk Factors of Intensive Care Unit-acquired Weakness in Patients With COVID-19: A Systematic Review and Meta-analysis.

BACKGROUND: Intensive care unit acquired weakness (ICUAW) is a common neuromuscular complication of critical illness, impacting patients' recovery and long-term outcomes. However, limited evidence is available on pooled prevalence and risk factors of ICUAW specifically in the COVID-19-infected population. METHODS: We searched on PubMed, Embase, Cochrane Library, Web of Science, PEDro, and EBSCOhost/CINAHL up to January 31, 2024. Data synthesis was conducted using the Freeman-Tukey double-arcsine transformation model for the pooled prevalence rate and odds ratios with corresponding 95% confidence intervals was used to identify risk factors. RESULTS: The pooled prevalence of ICUAW in COVID-19 patients was 55% in eight studies on 868 patients. Risk factors for developing ICUAW in these patients were: old age (WMD 4.78, 95% CI, 1.06-8.49), pre-existing hypertension (OR = 1.63, 95% CI, 1.02-2.61), medical intervention of prone position (OR = 5.21, 95% CI, 2.72-9.98), use of neuromuscular blocking agents (NMBA) (OR = 12.04, 95% CI, 6.20-23.39), needed tracheostomy (OR = 18.07, 95% CI, 5.64-57.92) and renal replacement therapy (RRT) (OR = 5.24, 95% CI = 2.36-11.63). CONCLUSIONS: The prevalence of ICUAW in patients with COVID-19 was considered relatively high. Older age, pre-existing hypertension, medical intervention of prone position, NMBA use, needed tracheostomy and RRT were likely risk factors. In the future, interdisciplinary medical team should pay attention to high-risk groups for ICUAW prevention and early treatments.

FXR activation remodels hepatic and intestinal transcriptional landscapes in metabolic dysfunction-associated steatohepatitis.

The escalating obesity epidemic and aging population have propelled metabolic dysfunction-associated steatohepatitis (MASH) to the forefront of public health concerns. The activation of FXR shows promise to combat MASH and its detrimental consequences. However, the specific alterations within the MASH-related transcriptional network remain elusive, hindering the development of more precise and effective therapeutic strategies. Through a comprehensive analysis of liver RNA-seq data from human and mouse MASH samples, we identified central perturbations within the MASH-associated transcriptional network, including disrupted cellular metabolism and mitochondrial function, decreased tissue repair capability, and increased inflammation and fibrosis. By employing integrated transcriptome profiling of diverse FXR agonists-treated mice, FXR liver-specific knockout mice, and open-source human datasets, we determined that hepatic FXR activation effectively ameliorated MASH by reversing the dysregulated metabolic and inflammatory networks implicated in MASH pathogenesis. This mitigation encompassed resolving fibrosis and reducing immune infiltration. By understanding the core regulatory network of FXR, which is directly correlated with disease severity and treatment response, we identified approximately one-third of the patients who could potentially benefit from FXR agonist therapy. A similar analysis involving intestinal RNA-seq data from FXR agonists-treated mice and FXR intestine-specific knockout mice revealed that intestinal FXR activation attenuates intestinal inflammation, and has promise in attenuating hepatic inflammation and fibrosis. Collectively, our study uncovers the intricate pathophysiological features of MASH at a transcriptional level and highlights the complex interplay between FXR activation and both MASH progression and regression. These findings contribute to precise drug development, utilization, and efficacy evaluation, ultimately aiming to improve patient outcomes.

Discovery of psoralen as a quorum sensing inhibitor suppresses Pseudomonas aeruginosa virulence.

Pseudomonas aeruginosa is a common opportunistic pathogen with growing resistance and presents heightened treatment challenges. Quorum sensing (QS) is a cell-to-cell communication system that contributes to the production of a variety of virulence factors and is also related to biofilm formation of P. aeruginosa. Compared to traditional antibiotics which kill bacteria directly, the anti-virulence strategy by targeting QS is a promising strategy for combating pseudomonal infections. In this study, the QS inhibition potential of the compounds derived from the Traditional Chinese Medicines was evaluated by using in silico, in vitro, and in vivo analyses. The results showed that psoralen, a natural furocoumarin compound derived from Psoralea corylifolia L., was capable of simultaneously inhibiting the three main QS regulators, LasR, RhlR, and PqsR of P. aeruginosa. Psoralen had no bactericidal activity but could widely inhibit the production of extracellular proteases, pyocyanin, and biofilm, and the cell motilities of the model and clinical P. aeruginosa strains. RNA-sequencing and quantitative PCR analyses further demonstrated that a majority of QS-activated genes in P. aeruginosa were suppressed by psoralen. The supplementation of psoralen could protect Caenorhabditis elegans from P. aeruginosa challenge, especially for the hypervirulent strain PA14. Moreover, psoralen showed synergistic antibacterial effects with polymyxin B, levofloxacin, and kanamycin. In conclusions, this study identifies the anti-QS and antibiofilm effects of psoralen against P. aeruginosa strains and sheds light on the discovery of anti-pseudomonal drugs among Traditional Chinese Medicines. KEY POINTS: • Psoralen derived from Psoralea corylifolia L. inhibits the virulence-related phenotypes of P. aeruginosa. • Psoralen simultaneously targets the three core regulators of P. aeruginosa QS system and inhibits the expression of a large part of downstream genes. • Psoralen protects C. elegans from P. aeruginosa challenge and enhances the susceptibility of P. aeruginosa to antibiotics.

Thalassospira aquimaris sp. nov. and Winogradskyella marincola sp. nov. two marine bacteria isolated from an agar-degrading co-culture.

Two novel Gram-stain-negative, aerobic, and non-motile strains, designated FZY0004T and YYF002T, were isolated from an agar-degrading co-culture, which was obtained from seawater of the intertidal zone of Yancheng City, the Yellow Sea of China. Strain FZY0004T optimally grew at 28 °C, pH 7.0, and 2-6% NaCl, while strain YYF002T optimally grew at 28 °C, pH 7.5, and 2-4% NaCl. Strain FZY0004T possessed Q-9 as the major respiratory quinone, and its major fatty acids (> 10%) were summed feature 8 (C18:1 ω7c), C16:0, and summed feature 3 (C16:1 ω7c/C16:1 ω6c). The polar lipids identified in strain FZY0004T were phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and several unidentified phospholipids (PL) and lipids (L). On the other hand, strain YYF002T had MK-6 as the predominant respiratory quinone and its major fatty acids consisted of iso-C15:0, iso-C15:1 G, and iso-C15:0 3-OH. The polar lipids identified in strain YYF002T were aminolipid (AL), PE, and several unidentified lipids. Strain FZY0004T shared 99.5% 16S rRNA gene sequence similarity and 90.1% average nucleotide identity (ANI) with T. povalilytica Zumi 95T, and strain YYF002T shared 99.2% 16S rRNA gene sequence similarity and 88.2% ANI with W. poriferorum JCM 12885T. The genomic DNA G + C contents of strains FZY0004T and YYF002T were 54.5% and 33.5%, respectively. The phylogenetic, phenotypic, and physiological characteristics permitted the distinction of the two strains from their neighbors, and we thus propose the names Thalassospira aquimaris sp. nov. (type strain FZY0004T = JCM 35895T = MCCC 1K08380T) and Winogradskyella marincola sp. nov. (type strain YYF002T = JCM 35950T = MCCC 1K08382T).

Isokinetic training of lower extremity during the early stage promote functional restoration in elder patients with disability after Total knee replacement (TKR) - a randomized control trial.

BACKGROUND: Transient progressive weakness and disability of lower limb during the early stage after TKR will increase the risk of fall, but the superior postoperative strength training mode have not been elucidated for functional restoration. This study aimed to compare whether the isokinetic lower limb training is superior to either isotonic or home isometric exercise during early stage after TKR in older people. METHODS: A total of 43 recruited old participants (mean age, 68.40 years old) receiving TKR were divided randomly based on the different four-week training modes into three groups including isokinetic, isotonic, and home isometric exercise (control group). The primary outcome was set as functional performance in terms of Timed Up and Go (TUG) test and the secondary outcomes include the peak torque of knee at 60 and 120 degree/ second, Short-Form 36 Health Survey (SF-36), and Western Ontario and McMaster Universities Arthritis index (WOMAC). RESULTS: All of the peak torque measurements of the knee improved significantly in both the isokinetic and the isotonic group, but not in the control group. Although isotonic training resulted in more strength gains, a significant enhancement in TUG test was observed in the isokinetic group only (p = 0.003). However, there were no significantly improvement of TUG test after training in other two groups. SF-36 and WOMAC improved after training in all three groups, with no significant difference in the degree of improvement between groups. CONCLUSION: Isokinetic training for 4 weeks following TKR effectively improved all the outcome parameters in this study, including the TUG test, lower limb strength, and functional scores. However, both isokinetic and isotonic training modes could be recommended after TKR because of no significant difference in the degree of improvement between these two groups. TRIAL REGISTRATION: Clinical trial registration number: NCT02938416. LEVEL OF EVIDENCE: I.

Effects of remimazolam tosilate on gastrointestinal hormones and gastrointestinal motility in patients undergoing gastrointestinal endoscopy with sedation: a randomized control trial.

PURPOSE: To investigate the impacts of remimazolam tosilate on gastrointestinal hormones and motility in patients undergoing gastrointestinal endoscopy with sedation. METHODS: A total of 262 American Society of Anesthesiologists Physical Status I or II patients, aged 18-65 years, scheduled for gastrointestinal endoscopy with sedation, were randomly allocated into two groups (n = 131 each): the remimazolam tosilate group (Group R) and the propofol group (Group P). Patients in Group R received 0.2-0.25 mg/Kg remimazolam tosilate intravenously, while those in Group P received 1.5-2.0 mg/kg propofol intravenously. The gastrointestinal endoscopy was performed when the Modified Observer's Assessment of Alertness/Sedation scores were ≤3. The primary endpoints included the endoscopic intestinal peristalsis rating by the endoscopist; serum motilin and gastrin levels at fasting without gastrointestinal preparation (T0), before gastrointestinal endoscopy (T1), and before leaving the Post Anesthesia Care Unit (T2); and the incidences of abdominal distension during Post Anesthesia Care Unit. RESULTS: Compared with Group P, intestinal peristalsis rating was higher in Group R (P < .001); Group R showed increased motilin and gastrin levels at T2 compared with Group P (P < .01). There was a rise in motilin and gastrin levels at T1 and T2 compared with T0 and at T2 compared with T1 in both groups (P < .01). The incidence of abdominal distension was lower in Group R (P < .05). CONCLUSION: Compared with propofol used during gastrointestinal endoscopy with sedation, remimazolam tosilate mildly inhibits the serum motilin and gastrin levels, potentially facilitating the recovery of gastrointestinal motility.

Maternal ozone exposure lowers infant's birthweight: A nationwide cohort of over 4 million livebirths in Iran.

BACKGROUND: Nationwide evidence linking maternal ozone exposure with fetal growth restriction (FGR) was extensively scarce, especially in the Middle East with dry climate and distinct religious culture. METHODS: We carried out a national retrospective birth cohort study using registry-based records from 749 hospitals across 31 provinces in Iran from 2013 to 2018. Monthly concentrations of maximum daily average 8-hour (MDA8) ozone at 0.125° × 0.125° resolution were extracted from well-validated spatiotemporal grid dataset. Linear and logistic regression models were employed to evaluate associations of maternal MDA8 ozone exposure with birthweight outcomes. Assuming causality, the comparative risk assessment framework was utilized to estimate the burden of low birthweight (LBW), small for gestational age (SGA), and birthweight loss per livebirth (BLL) attributable to ambient ozone pollution. RESULTS: Of 4030383 livebirths included in the study, 264304 (6.6%) were LBW and 484405 (12.0%) were SGA. Each 10-ppb increase in MDA8 ozone exposure was associated with an odds ratio of 1.123 (95% confidence interval [CI]: 1.104 to 1.142) for LBW and 1.210 (95% CI: 1.197 to 1.223) for SGA, and a 30.5-g (95% CI: 29.0 to 32.0) reduction in birthweight. We observed approximately linear exposure-response relationships of maternal MDA8 ozone exposure with LBW (Pnonlinear= 0.786), SGA (Pnonlinear= 0.156), and birthweight reduction (Pnonlinear= 0.104). Under the premise of causal association, we estimated 6.6% (95% CI: 5.7 to 7.5) of LBW, 10.1% (95% CI: 9.6 to 10.6) of SGA, and 18.8 g (95% CI: 17.9 to 19.7) of BLL could be attributable to maternal ozone exposure in Iran. Considerably greater risk and burden of ozone-related FGR were observed among younger, less-educated, and rural-dwelling mothers. CONCLUSIONS: Our study provided compelling evidence that maternal ozone exposure was associated with heightened FGR risk and burden, particularly among socioeconomically disadvantaged mothers. These findings underscored the urgent need for government to incorporate socioeconomic factors into future ozone-related health policies, not only to mitigate pollution, but also minimize inequality.

Long-term ozone exposure and all-cause mortality: Cohort evidence in China and global heterogeneity by region.

BACKGROUND: Cohort evidence linking long-term ozone (O3) exposure to mortality remained largely mixed worldwide and was extensively deficient in densely-populated Asia. This study aimed to assess the long-term effects of O3 exposure on all-cause mortality among Chinese adults, as well as to examine potential regional heterogeneity across the globe. METHODS: A national dynamic cohort of 42153 adults aged 16+ years were recruited from 25 provinces across Chinese mainland and followed up during 2010-2018. Annual warm-season (April-September) O3 and year-round co-pollutants (i.e., nitrogen dioxide [NO2] and fine particulate matter [PM2.5]) were simulated through validated spatial-temporal prediction models and were assigned to each enrollee in each calendar year. Cox proportional hazards models with time-varying exposures were employed to assess the O3-mortality association. Concentration-response (C-R) curves were fitted by natural cubic spline function to investigate the potential nonlinear association. Both single-pollutant model and co-pollutant models additionally adjusting for PM2.5 and/or NO2 were employed to examine the robustness of the estimated association. The random-effect meta-analysis was adopted to pool effect estimates from the current and prior population-based cohorts (n = 29), and pooled C-R curves were fitted through the meta-smoothing approach by regions. RESULTS: The study population comprised of 42153 participants who contributed 258921.5 person-years at risk (median 6.4 years), of whom 2382 death events occurred during study period. Participants were exposed to an annual average of 51.4 ppb (range: 22.7-74.4 ppb) of warm-season O3 concentration. In the single-pollutant model, a significantly increased hazard ratio (HR) of 1.098 (95% confidence interval [CI]: 1.023-1.179) was associated with a 10-ppb rise in O3 exposure. Associations remained robust to additional adjustments of co-pollutants, with HRs of 1.099 (95% CI: 1.023-1.180) in bi-pollutant model (+PM2.5) and 1.093 (95% CI: 1.018-1.174) in tri-pollutant model (+PM2.5+NO2), respectively. A J-shaped C-R relationship was identified among Chinese general population, suggesting significant excess mortality risk at high ozone exposure only. The combined C-R curves from Asia (n = 4) and North America (n = 17) demonstrated an overall increased risk of all-cause mortality with O3 exposure, with pooled HRs of 1.124 (95% CI: 0.966-1.307) and 1.023 (95% CI: 1.007-1.039) per 10-ppb rise, respectively. Conversely, an opposite association was observed in Europe (n = 8, HR: 0.914 [95% CI: 0.860-0.972]), suggesting significant heterogeneity across regions (P < 0.01). CONCLUSIONS: This study provided national evidence that high O3 exposure may curtail long-term survival of Chinese general population. Great between-region heterogeneity of pooled O3-mortality was identified across North America, Europe, and Asia.

Time synchronization between parietal-frontocentral connectivity with MRCP and gait in post-stroke bipedal tasks.

BACKGROUND: In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical potential (MRCP), and gait activities are common measures related to recovery outcomes. However, the interrelationship between FC, MRCP, gait activities, and bipedal distinguishability have yet to be investigated. METHODS: Ten participants were equipped with EEG devices and inertial measurement units (IMUs) while performing lower limb motor preparation (MP) and motor execution (ME) tasks. MRCP, FCs, and bipedal distinguishability were extracted from the EEG signals, while the change in knee degree during the ME phase was calculated from the gait data. FCs were analyzed with pairwise Pearson's correlation, and the brain-wide FC was fed into support vector machine (SVM) for bipedal classification. RESULTS: Parietal-frontocentral connectivity (PFCC) dysconnection and MRCP desynchronization were related to the MP and ME phases, respectively. Hemiplegic limb movement exhibited higher PFCC strength than nonhemiplegic limb movement. Bipedal classification had a short-lived peak of 75.1% in the pre-movement phase. These results contribute to a better understanding of the neurophysiological functions during motor tasks, with respect to localized MRCP and nonlocalized FC activities. The difference in PFCCs between both limbs could be a marker to understand the motor function of the brain of post-stroke patients. CONCLUSIONS: In this study, we discovered that PFCCs are temporally dependent on lower limb gait movement and MRCP. The PFCCs are also related to the lower limb motor performance of post-stroke patients. The detection of motor intentions allows the development of bipedal brain-controlled exoskeletons for lower limb active rehabilitation.

YOLOv7-TS: A Traffic Sign Detection Model Based on Sub-Pixel Convolution and Feature Fusion.

In recent years, significant progress has been witnessed in the field of deep learning-based object detection. As a subtask in the field of object detection, traffic sign detection has great potential for development. However, the existing object detection methods for traffic sign detection in real-world scenes are plagued by issues such as the omission of small objects and low detection accuracies. To address these issues, a traffic sign detection model named YOLOv7-Traffic Sign (YOLOv7-TS) is proposed based on sub-pixel convolution and feature fusion. Firstly, the up-sampling capability of the sub-pixel convolution integrating channel dimension is harnessed and a Feature Map Extraction Module (FMEM) is devised to mitigate the channel information loss. Furthermore, a Multi-feature Interactive Fusion Network (MIFNet) is constructed to facilitate enhanced information interaction among all feature layers, improving the feature fusion effectiveness and strengthening the perception ability of small objects. Moreover, a Deep Feature Enhancement Module (DFEM) is established to accelerate the pooling process while enriching the highest-layer feature. YOLOv7-TS is evaluated on two traffic sign datasets, namely CCTSDB2021 and TT100K. Compared with YOLOv7, YOLOv7-TS, with a smaller number of parameters, achieves a significant enhancement of 3.63% and 2.68% in the mean Average Precision (mAP) for each respective dataset, proving the effectiveness of the proposed model.

Development of Wearable Devices for Collecting Digital Rehabilitation/Fitness Data from Lower Limbs.

Lower extremity exercises are considered a standard and necessary treatment for rehabilitation and a well-rounded fitness routine, which builds strength, flexibility, and balance. The efficacy of rehabilitation programs hinges on meticulous monitoring of both adherence to home exercise routines and the quality of performance. However, in a home environment, patients often tend to inaccurately report the number of exercises performed and overlook the correctness of their rehabilitation motions, lacking quantifiable and systematic standards, thus impeding the recovery process. To address these challenges, there is a crucial need for a lightweight, unbiased, cost-effective, and objective wearable motion capture (Mocap) system designed for monitoring and evaluating home-based rehabilitation/fitness programs. This paper focuses on the development of such a system to gather exercise data into usable metrics. Five radio frequency (RF) inertial measurement unit (IMU) devices (RF-IMUs) were developed and strategically placed on calves, thighs, and abdomens. A two-layer long short-term memory (LSTM) model was used for fitness activity recognition (FAR) with an average accuracy of 97.4%. An intelligent smartphone algorithm was developed to track motion, recognize activity, and calculate key exercise variables in real time for squat, high knees, and lunge exercises. Additionally, a 3D avatar on the smartphone App allows users to observe and track their progress in real time or by replaying their exercise motions. A dynamic time warping (DTW) algorithm was also integrated into the system for scoring the similarity in two motions. The system's adaptability shows promise for applications in medical rehabilitation and sports.