Exploring the genetic and socioeconomic interplay between ADHD and anxiety disorders using Mendelian randomization.

Background: ADHD and anxiety disorders often co-occur, sharing symptoms and dysfunctions, yet the underlying mechanisms remain elusive. Methods: To explore the shared and distinct genetic variations between ADHD and anxiety disorders, we applied Mendelian randomization (MR) analysis to ADHD, anxiety disorders, and three socioeconomic factors: income, educational attainment (EA), and intelligence. MR analysis utilized genome-wide association study summary datasets (anxiety disorder: 7,016 cases and 14,745 controls; ADHD: 38,691 cases and 275,986 controls; EA: 766,345 participants; intelligence: 146,808 participants; household income: 392,422 participants), with inverse-variance weighting as the primary method. Results: Our MR analysis revealed no discernible genetic-level causal effect between ADHD and anxiety disorders (p > 0.77). Additionally, the independent variables for ADHD (25 SNPs) and anxiety disorders (18 SNPs) did not overlap, highlighting the genetic distinction between the two conditions. Higher income (p < 0.002) and EA (p < 0.005) were found to serve as protective factors for both ADHD and anxiety disorders. Genetic predisposition to higher income (86 SNPs) and EA (457 SNPs) were identified as a potential common protective factors for both conditions. Lastly, genetic predisposition to higher intelligence was found to potentially guard against ADHD (p < 0.001) but not against anxiety disorders (p > 0.55). Conclusion: Our findings indicate that the shared symptoms observed between ADHD and anxiety disorders are more likely influenced by genetic predispositions related to socioeconomic factors rather than by the genetic predispositions specific to the disorders themselves.

Rate control or rhythm control in patients with atrial fibrillation and acute coronary syndrome or percutaneous coronary intervention.

Background: Restoring and maintaining sinus rhythm in patients with atrial fibrillation (AF) and acute coronary syndrome (ACS) or undergoing percutaneous coronary intervention (PCI) has been studied in clinical trials to reduce symptoms and improve quality of life. Limited data exist on the effectiveness of rate or rhythm control therapy in these patients. Methods: Consecutive patients with AF and ACS or referred for PCI were prospectively recruited in Fuwai Hospital during 2017-2020. The primary endpoints were all-cause death and major adverse cardiovascular and cerebrovascular events (MACCEs), including cardiovascular mortality, myocardial infarction, ischemic stroke, non-central nervous system embolism and ischemia-driven revascularization. Kaplan-Meier curves and Cox regressions were performed to evaluate the association between rhythm/rate control and subsequent outcomes. For the primary endpoints, we used the Benjamini-Hochberg correction for multiple comparisons. Results: A total of 1499 patients with AF and ACS or undergoing PCI were included, with a median follow-up of 34.7 months. Compared to non-rate control, rate control strategy reduced the risk of subsequent MACCEs (adjusted HR, 0.320; 95 % CI 0.220-0.466; p <0.001; *p <0.002) and all-cause death (adjusted HR, 0.148; 95 % CI 0.093-0.236; p <0.001; *p <0.002). Similar trends were observed across all predefined subgroups (p <0.001). In the final multivariate model, rhythm control was not associated with a lower subsequent MACCEs but significantly improved all-cause mortality compared to non-rhythm control (adjusted HR, 0.546; 95 % CI 0.313-0.951; p =0.033; *p =0.044). Conclusions: In this real-world study, rate control strategy was associated with lower risk of MACCEs and all-cause death in AF and ACS or undergoing PCI. Besides, management with rhythm control strategy may improve all-cause mortality.

The Application of Artificial Intelligence in Atrial Fibrillation Patients: From Detection to Treatment.

Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although the guidelines for AF have been updated in recent years, its gradual onset and associated risk of stroke pose challenges for both patients and cardiologists in real-world practice. Artificial intelligence (AI) is a powerful tool in image analysis, data processing, and for establishing models. It has been widely applied in various medical fields, including AF. In this review, we focus on the progress and knowledge gap regarding the use of AI in AF patients and highlight its potential throughout the entire cycle of AF management, from detection to drug treatment. More evidence is needed to demonstrate its ability to improve prognosis through high-quality randomized controlled trials.

Accurate Prediction of Rat Acute Oral Toxicity and Reference Dose for Thousands of Polycyclic Aromatic Hydrocarbon Derivatives Based on Chemometric QSAR and Machine Learning.

Acute oral toxicity is currently not available for most polycyclic aromatic hydrocarbons (PAHs), especially their derivatives, because it is cost-prohibitive to experimentally determine all of them. Here, quantitative structure-activity relationship (QSAR) models using machine learning (ML) for predicting the toxicity of PAH derivatives were developed, based on oral toxicity data points of 788 individual substances of rats. Both the individual ML algorithm gradient boosting regression trees (GBRT) and the stacking ML algorithm (extreme gradient boosting + GBRT + random forest regression) provided the best prediction results with satisfactory determination coefficients for both cross-validation and the test set. It was found that those PAH derivatives with fewer polar hydrogens, more large-sized atoms, more branches, and lower polarizability have higher toxicity. Software based on the optimal ML-QSAR model was successfully developed to expand the application potential of the developed model, obtaining reliable prediction of pLD50 values and reference doses for 6893 external PAH derivatives. Among these chemicals, 472 were identified as moderately or highly toxic; 10 out of them had clear environment detection or use records. The findings provide valuable insights into the toxicity of PAHs and their derivatives, offering a standard platform for effectively evaluating chemical toxicity using ML-QSAR models.

Encapsulated stretchable amphibious strain sensors.

Soft and stretchable strain sensors have found wide applications in health monitoring, motion tracking, and robotic sensing. There is a growing demand for strain sensors in amphibious environments, such as implantable sensors, wearable sensors for swimmers/divers, and underwater robotic sensors. However, developing a sensitive, stretchable, and robust amphibious strain sensor remains challenging. This work presents an encapsulated stretchable amphibious strain sensor. The conductive layer, made of silver nanowires embedded below the surface of polydimethylsiloxane, was sandwiched by two layers of thermoplastic polyurethane. Periodic sharp cuts were introduced to change the direction of flow from across the sensor to along the conductive path defined by the opening cracks. The crack advancing and opening is controlled by a unique combination of weak/strong interfaces within the sandwich structure. The cut design and the interfacial interactions between the layers were investigated. The strain sensor exhibited a high gauge factor up to 289, a linear sensing response, a fast response time (53 ms), excellent robustness against over-strain, and stability after 16 000 loading cycles and 20 days in an aqueous saline solution. The functionality of this amphibious strain sensor was demonstrated by tracking the motion of a robotic fish, undertaking language recognition underwater, and monitoring the blood pressure of a porcine aorta. This illustrates the promising potential for this strain sensor for both underwater use and surgically implantable applications.

Shuang Wu.

Interview with Shuang Wu, who studies plant organ formation and tissue patterning at Fujian Agriculture and Forestry University in Fuzhou.

Hypoxia-related signature to risk stratify patients for the benefit of immune checkpoint inhibitors therapy in head and neck squamous cell carcinoma: An experimental study.

BACKGROUND: Increasing evidence has shown that hypoxia is a biomarker of tumor proliferation and metastasis. This research aimed to identify a hypoxia-associated gene prognostic index (HAGPI) in head and neck squamous cell carcinoma (HNSCC) and based on HAGPI-defined subgroups to predict prognosis and response to immune checkpoint inhibitors therapy. METHODS: RNA-sequencing transcriptomic data for patients with HNSCC were downloaded from The Cancer Genome Atlas (TCGA). Protein-protein interaction network analysis was performed to select hypoxia-related hub genes. Univariate and multivariate cox regression analyses were used to identify hub genes to develop the HAGPI. Afterward expression data were imported into CIBERSORT to evaluate the relative proportion of 22 immune cells and compared the relative proportions of immune cells between the 2 HAGPI subgroups. The relationship between immunopheno score (IPS) and HAGPI was validated for immune checkpoint inhibitors (ICIs) response in TCGA cohorts. RESULTS: The HAGPI was constructed based on HS3ST1, HK1, PGK1, STC2, SERPINE1, PKLR genes. In high-HAGPI patients, the primary and secondary endpoint events in TCGA and GEO cohorts were significantly lower than low-HAGPI groups (P < .05). HAGPI-high patients exhibited a poorer prognosis than HAGPI-low patients did. The abundance of M2 macrophages and NK cell were significantly enhanced in the high-HAGPI while T cells regulatory and T cells CD8, were markedly elevated in the low-HAGPI. Meanwhile, patients in the low-HAGPI patients had higher levels of immunosuppressant expression and less aggressive phenotypes. Furthermore, IPS analysis showed that the low-HAGPI group with higher IPS represented a more immunogenic phenotype. CONCLUSION: The current study developed and verified a HAPGI model that can be considered as an independent prognostic biomarker and elucidated the tumor immune microenvironment of HNSCC.

A nested reciprocal experimental design to map the genetic architecture of transgenerational phenotypic plasticity.

Extensive studies have revealed the ecological and evolutionary significance of phenotypic plasticity, but little is known about how it is inherited between generations and the genetic architecture of its transgenerational inheritance. To address these issues, we design a mapping study by growing Arabidopsis thaliana RILs in high- and low-light environments and further growing their offspring RILs from each maternal light environment in the same contrasting environments. This tree-like design of the controlled ecological experiment provides a framework for analysing the genetic regulation of phenotypic plasticity and its non-genetic inheritance. We implement the computational approach of functional mapping to identify specific QTLs for transgenerational phenotypic plasticity. By estimating and comparing the plastic response of leaf-number growth trajectories to light environment between generations, we find that the maternal environment affects phenotypic plasticity, whereas transgenerational plasticity is shaped by the offspring environment. The genetic architecture underlying the light-induced change of leaf number not only changes from parental to offspring generations, but also depends on the maternal environment the parental generation experienced and the offspring environment the offspring generation is experiencing. Most plasticity QTLs are annotated to the genomic regions of candidate genes for specific biological functions. Our computational-experimental design provides a unique insight into dissecting the non-genetic and genetic mechanisms of phenotypic plasticity shaping plant adaptation and evolution in various forms.

Hypnotic Use and the Risk of Cardiovascular Diseases in Insomnia Patients.

AIMS: We aimed to examine the association between hypnotic agents and cardiovascular outcomes in general individuals with insomnia. METHODS: In a propensity score matched cohort of UK Biobank (UKB) participants with insomnia, Cox proportional hazard model was used to estimate the association between regular use of hypnotic agents and predetermined cardiovascular outcomes including incident coronary heart diseases (CHD), heart failure (HF), stroke, and cardiovascular death. Inverse probability of treatment weighting, competing risk models, and shared frailty models were further performed during sensitivity analysis. Drug-target Mendelian randomization (MR) analyses were employed for further evaluation of the association between therapeutic targets of hypnotics and cardiovascular diseases. RESULTS: During a median follow-up of 14.3 years, the matched cohort documented a total of 929 CHD cases, 360 HF cases, 262 stroke cases, and 180 cardiovascular deaths. No significant association was detected between Z-meds and CHD, stroke, and cardiovascular mortality. Benzodiazepine use was significantly associated with the increased risk of CHD, HF, and cardiovascular mortality. The inverse probability of treatment weighting, competing risk models, and shared frailty models didn't alter the above associations. Moreover, drug-target MR analyses corroborated the safety of Z-meds in the general population regarding cardiovascular health. CONCLUSIONS: Our findings suggested the heterogeneous associations between different categories of hypnotics and incident cardiovascular events in individuals with insomnia. Both observational and genetic evidence raised safety concerns regarding the cardiovascular impact of benzodiazepines. No cardiovascular hazard of Z-meds was discovered in the UKB population with insomnia.

In the general population with insomnia, we uncovered the heterogeneous associations between different categories of hypnotics and incident cardiovascular events incorporating results from a propensity score matched cohort study of UK Biobank participants and drug-target Mendelian randomization analyses.Benzodiazepine was significantly associated with the increased risk of coronary heart disease, heart failure, and cardiovascular mortality.No adverse evidence regarding the cardiovascular safety of Z-meds was found in both observational and Mendelian randomization analyses.

Employing conductive porous hydrogen-bonded organic framework for ultrasensitive detection of peanut allergen Ara h1.

Peanut allergy has garnered worldwide attention due to its high incidence rate and severe symptoms, stimulating the demand for the ultrasensitive detection method of peanut allergen. Herein, we successfully developed a novel electrochemical aptasensor for ultrasensitive detection Ara h1, a major allergenic protein present in peanuts. A conductive nickel atoms Anchored Hydrogen-Bonded Organic Frameworks (PFC-73-Ni) were utilized as excellent electrocatalysts toward hydroquinone (HQ) oxidation to generate a readable current signal. The developed electrochemical aptasensor offers wide linear range (1-120 nM) and low detection limit (0.26 nM) for Ara h1. This method demonstrated a recovery rate ranging from 95.00% to 107.42% in standard addition detection of non-peanut food samples. Additionally, the developed electrochemical method was validated with actual samples and demonstrated good consistency with the results obtained from a commercial ELISA kit. This indicates that the established Ara h1 detection method is a promising tool for peanut allergy prevention.

Pulmonary neuroendocrine cells: crucial players in respiratory function and airway-nerve communication.

Pulmonary neuroendocrine cells (PNECs) are unique airway epithelial cells that blend neuronal and endocrine functions, acting as key sensors in the lung. They respond to environmental stimuli like allergens by releasing neuropeptides and neurotransmitters. PNECs stand out as the only lung epithelial cells innervated by neurons, suggesting a significant role in airway-nerve communication via direct neural pathways and hormone release. Pathological conditions such as asthma are linked to increased PNECs counts and elevated calcitonin gene-related peptide (CGRP) production, which may affect neuroprotection and brain function. CGRP is also associated with neurodegenerative diseases, including Parkinson's and Alzheimer's, potentially due to its influence on inflammation and cholinergic activity. Despite their low numbers, PNECs are crucial for a wide range of functions, highlighting the importance of further research. Advances in technology for producing and culturing human PNECs enable the exploration of new mechanisms and cell-specific responses to targeted therapies for PNEC-focused treatments.

Effect of LH level on HCG trigger day on clinical outcomes in patients with diminished ovarian reserve undergoing GnRH-antagonist protocol.

RESEARCH QUESTION: Does luteinizing hormone (LH) levels on human chorionic gonadotropin (HCG) trigger day (LHHCG) affect the clinical outcomes of patients with diminished ovarian reserve (DOR) undergoing gonadotropin-releasing hormone antagonist (GnRH-ant) protocol? METHODS: Retrospective analysis fresh embryo transfer cycles of DOR patients who underwent GnRH-ant protocol from August 2019 to June 2023. The participants were divided into different groups according to LHHCG level and age. The clinical data and outcomes were compared between groups. RESULTS: In patients with DOR, the HCG positive rate (59.3% versus 39.8%, P = 0.005), embryo implantation rate (34.5% versus 19.7%, P = 0.002), clinical pregnancy rate (49.2% versus 28.4%, P = 0.003), live birth rate (41.5% versus 22.7%, P = 0.005) in LHHCG < 2.58 IU/L group were significantly higher than LHHCG ≥ 2.58 IU/L group. There was no significant correlation between LHHCG level and clinical pregnancy in POSEIDON group 3. In POSEIDON group 4, the HCG positive rate (52.8% versus 27.0%, P = 0.015), embryo implantation rate (29.2% versus 13.3%, P = 0.023), clinical pregnancy rate (45.3% versus 18.9%, P = 0.010) in LHHCG < 3.14 IU/L group were significantly higher than LHHCG ≥ 3.14 IU/L group. Logistic regression analysis indicated that LHHCG level was an independent influencing factor for clinical pregnancy in POSEIDON group 4 patients (OR = 3.831, 95% CI: 1.379-10.643, P < 0.05). CONCLUSIONS: LHHCG level is an independent factor affecting pregnancy outcome of fresh embryo transfer in DOR patients undergoing GnRH-ant protocol, especially for advanced-aged women. LHHCG had a high predictive value for POSEIDON group 4 patients, and LHHCG ≥ 3.14 IU/L predicts poor pregnancy outcomes.

Topological change of soil microbiota networks for forest resilience under global warming.

Forest management by thinning can mitigate the detrimental impact of increasing drought caused by global warming. Growing evidence shows that the soil microbiota can coordinate the dynamic relationship between forest functions and drought intensity, but how they function as a cohesive whole remains elusive. We outline a statistical topology model to chart the roadmap of how each microbe acts and interacts with every other microbe to shape the dynamic changes of microbial communities under forest management. To demonstrate its utility, we analyze a soil microbiota data collected from a two-way longitudinal factorial experiment involving three stand densities and three levels of rainfall over a growing season in artificial plantations of a forest tree - larix (Larix kaempferi). We reconstruct the most sophisticated soil microbiota networks that code maximally informative microbial interactions and trace their dynamic trajectories across time, space, and environmental signals. By integrating GLMY homology theory, we dissect the topological architecture of these so-called omnidirectional networks and identify key microbial interaction pathways that play a pivotal role in mediating the structure and function of soil microbial communities. The statistical topological model described provides a systems tool for studying how microbial community assembly alters its structure, function and evolution under climate change.

[Correlation between Morphological Typing and Monoclonality of Bone Marrow Plasma Cells and Its Diagnostic Value for High-Risk Smoldering Multiple Myeloma].

OBJECTIVE: To investigate the correlation between morphological typing and monoclonality of bone marrow plasma cells, and explore the diagnostic value of plasma cell morphological typing for high-risk smoldering multiple myeloma(HR-SMM). METHODS: The correlation between the morphological characteristics and the monoclonality of bone marrow plasma cells was analyzed in 84 patients with HR-SMM who treated in our hospital. The consistency of morphologically abnormal bone marrow plasma cells with serum free light chain (sFLC) ratio, next-generation sequencing (NGS) detection results, and its correlation with monoclonal plasma cells detected by flow cytometry (FCM) were further verified. The immunoglobulin types and levels of non-involved immunoglobulins in serum of the patients were detected, and the distribution of plasma cell clusters in patients with different disease was observed. RESULTS: The mean percentage of mature plasma cells were decreased successively in the order of reactive plasmacytosis (RP) group, monoclonal gammopathy of undetermined significance (MGUS) group, smoldering multiple myeloma (SMM) group, HR-SMM group and multiple myeloma (MM) group; while the mean percentage of immature, primitive, reticular and flaming plasma cells were increased successively in the order of RP group, MGUS group, SMM group, and HR-SMM group, and the difference between any two groups was statistically significant (P < 0.05).The average proportion of abnormal plasma cells in the bone marrow of HR-SMM patients was 96.2% of the total plasma cells. The proportion of abnormal plasma cells were in good agreement with the sFLC ratio and the results of NGS detection in HR-SMM patients (kappa=0.879 and kappa=0.891, both >0.75)，and showed good correlation with the monoclonal plasma cells with immunophenotype of CD45-/CD38+/CD138+/CD56+/CD19-( γ=0.825). The levels of non-involved immunoglobulin in IgG, IgA and IgM type HR-SMM patients were all decreased by more than 25% compared with the normal reference range, and the differences were statistically significant (P < 0.05). There was no significant difference in the distribution ratio of plasma cell clusters among different disease groups (P >0.05). CONCLUSION: In HR-SMM patients, the immature, primitive, reticular and flaming plasma cells in bone marrow are considered as abnormal plasma cells, and they are correlated with monoclonal plasma cells. The proportion of abnormal plasma cells in total plasma cells of bone marrow and the reduction extent of non-involved immunoglobulin level in patients have certain reference value for the diagnosis of HR-SMM.

Comprehensive review of indicators and techniques for optical mapping of intracellular calcium ions.

Calcium ions (Ca2+) play crucial roles in almost every cellular process, making the detection of changes in intracellular Ca2+ essential to understanding cell function. The fluorescence indicator method has garnered widespread application due to its exceptional sensitivity, rapid analysis, cost-effectiveness, and user-friendly nature. It has successfully delineated the spatial and temporal dynamics of Ca2+ signaling across diverse cell types. However, it is vital to understand that different indicators have varying levels of accuracy, sensitivity, and stability, making choosing the right inspection method crucial. As optical detection technologies advance, they continually broaden the horizons of scientific inquiry. This primer offers a systematic synthesis of the current fluorescence indicators and optical imaging modalities utilized for the detection of intracellular Ca2+. It elucidates their practical applications and inherent limitations, serving as an essential reference for researchers seeking to identify the most suitable detection methodologies for their calcium-centric investigations.

Rapid and extensive SARS-CoV-2 Omicron variant infection wave revealed by wastewater surveillance in Shenzhen following the lifting of a strict COVID-19 strategy.

Wastewater-based epidemiology (WBE) has emerged as a promising tool for monitoring the spread of COVID-19, as SARS-CoV-2 can be shed in the faeces of infected individuals, even in the absence of symptoms. This study aimed to optimize a prediction model for estimating COVID-19 infection rates based on SARS-CoV-2 RNA concentrations in wastewater, and reveal the infection trends and variant diversification in Shenzhen, China following the lifting of a strict COVID-19 strategy. Faecal samples (n = 4337) from 1204 SARS-CoV-2 infected individuals hospitalized in a designated hospital were analysed to obtain Omicron variant-specific faecal shedding dynamics. Wastewater samples from 6 wastewater treatment plants (WWTPs) and 9 pump stations, covering 3.55 million people, were monitored for SARS-CoV-2 RNA concentrations and variant abundance. We found that the viral load in wastewater increased rapidly in December 2022 in the two districts, demonstrating a sharp peak in COVID-19 infections in late-December 2022, mainly caused by Omicron subvariants BA.5.2.48 and BF.7.14. The prediction model, based on the mass balance between total viral load in wastewater and individual faecal viral shedding, revealed a surge in the cumulative infection rate from <0.1 % to over 70 % within three weeks after the strict COVID-19 strategy was lifted. Additionally, 39 cryptic SARS-CoV-2 variants were identified in wastewater, in addition to those detected through clinical surveillance. These findings demonstrate the effectiveness of WBE in providing comprehensive and efficient assessments of COVID-19 infection rates and identifying cryptic variants, highlighting its potential for monitoring emerging pathogens with faecal shedding.

Copper mediated follicular atresia: Implications for granulosa cell death.

3-nitropropanoic acid is a potent oxidative stress inducer that is conventionally regarded as a regulator of follicular atresia by regulating granulosa cells (GCs) death through the apoptosis pathway. There has been no research investigating the impact of copper metal overload induced Cuproptosis in ovarian GCs as a factor contributing to hindered follicular development.To elucidate whether 3-NP-induced oxidative stress plays a contributory role in promoting Cuproptosis, and discuss the role of Cuproptosis in the development of ovarian follicles.We conducted an analysis of cuproptosis occurrence in murine GCs and C57BL/6 J mice under the influence of 3-NP and 3-NP with added exogenous copper.The results revealed that 3-NP serving as a robust facilitator of exogenous copper uptake by upregulating the expression of copper transporter 1 (CTR1). In turn, culminated in the accumulation of intracellular copper within mouse granulosa cells (mGCs). Furthermore, 3-NP promoted mitochondrial permeability transition pore opening and concurrently reduced the stability of lipoic acid proteins. These actions collectively induced the oligomerization of Dihydrolipoamide S-Acetyltransferase (DLAT), ultimately leading to cuproptosis in GCs and consequent follicular atresia. Heavy metal copper and fungal decomposition product 3-NP, induce ovarian atresia via cuproptosis, modulating the reproductive performance of female animals.

Association between adherence to life's simple 7 metrics and risk of obstructive sleep apnea among adults in the United States.

BACKGROUND: We aimed to explore the impact of adherence to Life's Simple 7 (LS7) metrics on risk of obstructive sleep apnea (OSA), and the impact of inflammation on the association, in adults in the United States. METHODS: Data from 13,825 community-dwelling adults aged ≥ 20 years recruited in the National Health and Nutrition Examination Surveys (NHANES) 2005-2008, 2015-2018 was analyzed. The LS7 score was calculated based on the AHA definition of LS7 metrics. The diagnosis of OSA was based on self-reported symptoms of sleep disturbance using a standard questionnaire. The Multivariable Apnea Prediction (MAP) Index score was also calculated to assess the risk of OSA. Log-binominal regression and negative binomial regression were performed to estimate the associations between LS7 and OSA and MAP index, with odds ratios (ORs) and prevalence ratios (PRs) and their 95% confidence intervals (CIs) calculated. Mediation analysis was performed to estimate the mediating effects of inflammatory indicators on the associations. RESULTS: A total of 4473 participants (32.4%) had OSA, and the mean MAP index was 0.39. In fully adjusted log-binominal regression models, with total score < 6 as the reference, the ORs (95% CIs) for risk of OSA were 0.90 (0.73, 1.10), 0.76 (0.65, 0.89), 0.78 (0.64, 0.95), and 0.45 (0.38, 0.54) for total score = 6, total score = 7, total score = 8, and total score > 8, respectively (P for trend < 0.001). When LS7 score was analyzed as a continuous variable, each 1-point increase in LS7 score was associated with a 15% decrease in OSA risk (P < 0.001). In negative binominal regression models, the adjusted PRs (95% CIs) for the MAP index were 0.93 (0.90, 0.97), 0.87 (0.84, 0.91), 0.80 (0.77, 0.84), and 0.55 (0.53, 0.57) for total score = 6, total score = 7, total score = 8, and total score > 8, respectively (P for trend < 0.001). For each 1-point increase in LS7 score, the risk of OSA decreased by 13% (P < 0.001). Consistent results were observed in subgroup analysis. Mediation analysis indicated that inflammatory factors, including blood cell count, neutrophil count, and C-reactive protein, positively mediated the association of LS7 with OSA, with a mediation proportion of 0.022 (P = 0.04), 0.02 (P = 0.04), and 0.02 (P = 0.02), respectively. CONCLUSIONS: In a nationally representative sample of US adults, adherence to LS7 metrics was independently associated with reduced OSA risk. Inflammation plays a mediating role in the association between LS7 and OSA.

High titer expression of antibodies using linear expression cassettes for early-stage functional screening.

Antibody discovery processes are continually advancing, with an ever-increasing number of potential binding sequences being identified out of in vivo, in vitro, and in silico sources. In this work we describe a rapid system for high yield recombinant antibody (IgG and Fab) expression using Gibson assembled linear DNA fragments (GLFs). The purified recombinant antibody yields from 1 ml expression for this process are approximately five to ten-fold higher than previous methods, largely due to novel usage of protecting flanking sequences on the 5' and 3' ends of the GLF. This method is adaptable for small scale (1 ml) expression and purification for rapid evaluation of binding and activity, in addition to larger scales (30 ml) for more sensitive assays requiring milligram quantities of antibody purified over two columns (Protein A and size exclusion chromatography). When compared to plasmid-based expression, these methods provide nearly equivalent yield of high-quality material across multiple applications, allowing for reduced costs and turnaround times to enhance the antibody discovery process.

A Fluorescent Lateral Flow Immunoassay for the Detection of Skeletal Muscle Troponin I in Serum for Muscle Injury Monitoring at the Point of Care.

Exercise-induced muscle injury is one of the most common types of sports injuries. Skeletal muscle troponin I (skTnI) serves as an ideal biomarker in assessing such injuries, facilitating timely detection and evaluation. In this study, we develop a fluorescent sandwich lateral flow immunoassay (LFIA) combined with a desktop analyzer for rapid detection of skTnI. Through optimizing the reaction system, the assay achieves a satisfying detection performance, reaching a limit of detection (LOD) of 0.5 ng/mL with a turnaround time of 15 min. The proposed detection platform offers portability, ease of use, and high sensitivity, which facilitates the monitoring of exercise-induced muscle injuries at the point of care. This feature is particularly advantageous for end users, enabling timely detection of sports-related injuries and ultimately enhancing prognosis and sports life.