The association between Weight-adjusted-Waist Index (WWI) and cognitive function in older adults: a cross-sectional NHANES 2011-2014 study.

BACKGROUND: The impact of obesity on cognitive function has engendered considerable interest. Weight-adjusted waist index (WWI) has emerged as a novel and innovative marker of obesity that reflects weight-independent abdominal obesity. However, the association between WWI and cognitive function remains unclear. To address this gap, the present study aims to explore the relationship between weight-adjusted waist index (WWI) and cognitive performance in older adults. METHODS: We conducted a cross-sectional investigation using datasets from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. The study included 3,472 participants (48.59% male, 51.41% female) of various races (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, and Other), with a mean age of 69.95 years (SD = 6.94). Multivariate regression and smoothing curve fitting were used to investigate the linear and nonlinear relationship between WWI and cognitive performance in the following domains: learning and memory, verbal fluency, and processing speed, as measured by Consortium to Establish a Registry for Alzheimer's Disease Word Learning subtest (CERAD-WL), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST), respectively. Subgroup analysis and interaction tests were conducted to examine the stability of this relationship across groups. Machine learning models based on random forests were used to analyze the predictive performance of WWI for cognitive function. RESULTS: A total of 3,472 participants were included in the analysis. The results revealed significant negative associations between WWI and low scores on the CERAD-WL [-0.96 (-1.30, -0.62)], AFT [-0.77 (-1.05, -0.49)], and DSST [-3.67 (-4.55, -2.79)]. This relationship remained stable after converting WWI to a categorical variable. In addition, this significant negative association was more pronounced in men than women and diminished with advancing age. Non-linear threshold effects were observed, with correlations intensifying between WWI and CERAD-WL when WWI surpassed 12.25, AFT when WWI surpassed 11.54, and DSST when WWI surpassed 11.66. CONCLUSIONS: A higher WWI, indicating increased abdominal obesity, was associated with deficits in learning, memory, verbal fluency, and processing speed among older adults. These findings suggest that abdominal obesity may play a crucial role in cognitive decline in this population. The stronger relationship observed between WWI and cognition in men highlights the need for gender-specific considerations in interventions targeting abdominal obesity. The results demonstrate the importance of interventions targeting abdominal obesity to preserve cognitive performance in older adults.

Methylation of EjNAC5 and its interactions with other transcription factors regulate loquat fruit chilling lignification.

Changes in both lignin biosynthesis and DNA methylation have been reported to be associated with chilling stress in plants. When stored at low temperatures, red-fleshed loquat is prone to lignification, with increased lignin content and fruit firmness, which has deleterious effects on taste and eating quality. Here, we found that 5°C storage mitigated the increasing firmness and lignin content of red-fleshed 'Dahongpao' ('DHP') loquat fruit that occurred during 0°C storage. EjNAC5 was identified by integrating RNA sequencing with whole-genome bisulfite sequencing analysis of 'DHP' loquat fruit. The transcript levels of EjNAC5 were positively correlated with changes in firmness and negatively correlated with changes in DNA methylation level of a differentially methylated region (DMR) in the EjNAC5 promoter. In white-fleshed 'Baisha' ('BS') loquat fruit, which do not undergo chilling-induced lignification at 0°C, the transcripts of EjNAC5 remained low and the methylation levels of the DMR in the EjNAC5 promoter was higher, compared to 'DHP' loquat fruit. Transient overexpression of EjNAC5 in loquat fruit and stable overexpression in Arabidopsis and liverwort led to an increase in lignin content. Furthermore, EjNAC5 interacts with EjERF39 and EjHB1 and activates the transcription of Ej4CL1 and EjPRX12 genes involved in lignin biosynthesis. This regulatory network involves different TFs to those involved in lignification pathway. Our study indicates that EjNAC5 promoter methylation modulates EjNAC5 transcript levels and identifies novel EjNAC5-EjERF39-Ej4CL1 and EjNAC5-EjHB1-EjPRX12 regulatory modules involved in chilling induced-lignification.

Protocol for a systematic review with prospective individual patient data meta-analysis in EGFR-mutant NSCLC with brain metastases to assess the effect of SRS+osimertinib compared to osimertinib alone: the STARLET Collaboration.

BACKGROUND: Patients with advanced non-small-cell lung cancer (NSCLC) with activating mutations in the epidermal growth factor receptor (EGFR) gene are a heterogeneous population who often develop brain metastases (BM). The optimal management of patients with asymptomatic brain metastases is unclear given the activity of newer-generation targeted therapies in the central nervous system. We present a protocol for an individual patient data (IPD) prospective meta-analysis to evaluate whether the addition of stereotactic radiosurgery (SRS) before osimertinib treatment will lead to better control of intracranial metastatic disease. This is a clinically relevant question that will inform practice. METHODS: Randomised controlled trials will be eligible if they include participants with BM arising from EGFR-mutant NSCLC and suitable to receive osimertinib both in the first-line and second-line settings (P); comparisons of SRS followed by osimertinib versus osimertinib alone (I, C) and intracranial disease control included as an endpoint (O). Systematic searches of Medline (Ovid), Embase (Ovid), Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL (EBSCO), PsychInfo, ClinicalTrials.gov and the WHO's International Clinical Trials Registry Platform's Search Portal will be undertaken. An IPD meta-analysis will be performed using methodologies recommended by the Cochrane Collaboration. The primary outcome is intracranial progression-free survival, as determined by response assessment in neuro-oncology-BM criteria. Secondary outcomes include overall survival, time to whole brain radiotherapy, quality of life, and adverse events of special interest. Effect differences will be explored among prespecified subgroups. ETHICS AND DISSEMINATION: Approved by each trial's ethics committee. Results will be relevant to clinicians, researchers, policymakers and patients, and will be disseminated via publications, presentations and media releases. PROSPERO REGISTRATION: CRD42022330532.

Modulating the gut microbiome in non-small cell lung cancer: Challenges and opportunities.

Despite the efficacy of immunotherapy in non-small cell lung cancer (NSCLC), the majority of the patients experience relapse with limited subsequent treatment options. Preclinical studies of various epithelial tumors, such as melanoma and NSCLC, have shown that harnessing the gut microbiome resulted in improvement of therapeutic responses to immunotherapy. Is this review, we summarize the role of microbiome, including lung and gut microbiome in the context of NSCLC, provide overview of the mechanisms of microbiome in efficacy and toxicity of chemotherapies and immunotherapies, and address current ongoing clinical trials for NSCLC including fecal microbiota transplantation (FMT) and live biotherapeutic products (LBPs).

Application of circular statistics in temporal distribution of adult mosquitoes in Qingdao, Shandong Province, China, 2021-2023.

BACKGROUND: Analyses of the temporal distribution of mosquitoes are presented in statistical charts, but it is difficult to prove in statistics whether differences in peak periods exist among different years or habitats. This study aimed to investigate the application of circular statistics in determining the peak period and a comparison of differences. METHODS: Surveillance of adult mosquitoes was conducted twice a month by light traps in five different habitats from March to November for 3 years (2021-2023) in Qingdao, Shandong Province, China. The Kruskal-Wallis test was performed to determine the differences in mosquito density among different years and habitats. Circular statistics and line charts were employed to determine the peak period and a comparison of differences. RESULTS: Among a total of 14,834 adult mosquitoes comprising five mosquito species from four genera, Culex pipiens pallens was dominant and accounted for 89.6% of the specimens identified. Aedes albopictus, Armigeres subalbatus, and Anopheles sinensis made up 5.7%, 4.2%, and 0.5%, respectively. Culex tritaeniorhynchus accounted for less than 0.1%. The mean mosquito density (females/trap night) for the trapping period was 10.3 in 2021, 5.6 in 2022, and 3.6 in 2023. Among five habitats, the highest mosquito density was 8.9 in livestock sheds, followed by 6.8 in parks, 5.9 in rural dwellings, 5.5 in urban dwellings, and 5.4 in hospitals. No statistically significant differences were found among different years (H = 1.96, d.f. 2, P = 0.376) and habitats (H = 0.45, d.f. 4, P = 0.978). Overall, the peak period of mosquito activity fell in the months from June to September. The peak period among 3 years differed significantly (F(2,7022) = 119.17, P < 0.01), but there were no statistically significant differences in peak period among different habitats (F(4,7020) = -159.09, P > 0.05). CONCLUSION: Circular statistics could be effectively combined with statistical charts to elucidate the peak period of mosquitoes and determine the differences in statistics among different years and habitats. These findings will provide valuable information for mosquito control and public health management.

A Modified Frailty Phenotype Used for Identifying Frailty in Health Care Practice: Validation Among Chinese Older Adults.

OBJECTIVES: The study aimed to evaluate a simplified and practical frailty detection tool derived from the Fried frailty phenotype (FFP). This tool was developed to facilitate the identification of frail individuals in constrained settings, addressing the challenges posed by uncertain cutoffs of FFP indicators in prompt frailty assessment. DESIGN: A longitudinal study and a cross-sectional study. SETTINGS AND PARTICIPANTS: A total of 1978 older adults aged 67.4 ± 6.16 years from the China Health and Retirement Longitudinal Study (CHARLS), and 972 older adults aged 72.8 ± 6.75 years from a pilot cross-sectional study conducted in Shanghai communities. METHODS: Frailty was assessed according to the FFP criterion. A Chinese modified frailty phenotype (CMFP) was developed, incorporating specific cutoffs for grip strength and an alternative test for walk speed. The internal consistency reliability, the criterion, and predictive validity of the CMFP were evaluated. RESULTS: The 5-time chair stand test (5t-CST) was significantly associated with the 2.5-m walk test (r = 0.373 in the CHARLS and 0.423 in the pilot study). Each element of the CMFP showed moderate to strong correlations with the total CMFP score and showed Cronbach's alpha of 0.303 and 0.358 in both populations. The Spearman's r and kappa values between the CMFP and the FFP were 0.795 and 0.663 in the CHARLS, and 0.676 and 0.537 in the pilot study. The areas under the curve (AUC) were 0.936 and 0.928 in the 2 studies, respectively. In addition, frailty assessed by the CMFP significantly predicted future incidence of outcomes, including all-cause mortality, activities of daily living (ADL)/instrumental ADL disability, hospitalization, and depression. CONCLUSIONS AND IMPLICATIONS: The study demonstrated the CMFP as a valid tool, particularly highlighting its excellent predictive ability on outcomes. The 5t-CST may act as a viable alternative test for assessing slowness. The CMFP can be systematically integrated into preclinical practice to identify frail individuals, especially within constrained spaces.

International Cost-Effectiveness Analysis of Durvalumab in Stage III Non-Small Cell Lung Cancer.

Importance: Standard of care for unresectable locally advanced non-small cell lung cancer (NSCLC) involves definitive chemoradiotherapy followed by maintenance therapy with durvalumab. However, the cost of durvalumab has been cited as a barrier to its use in various health systems. Objective: To evaluate the cost-effectiveness of durvalumab vs placebo as maintenance therapy in patients with unresectable stage III NSCLC from 4 international payer perspectives (US, Brazil, Singapore, and Spain). Design, Setting, and Participants: In this economic evaluation, a Markov model was designed to compare the lifetime cost-effectiveness of maintenance durvalumab for unresectable stage III NSCLC with that of placebo, using 5-year outcomes data from the PACIFIC randomized placebo-controlled trial. Individual patient data were extracted from the PACIFIC, KEYNOTE-189, ADAURA, ALEX, and REVEL randomized clinical trials to develop a decision-analytic model to determine the cost-effectiveness of durvalumab compared with placebo maintenance therapy over a 10-year time horizon. Direct costs, adverse events, and patient characteristics were based on country-specific payer perspectives and demographic characteristics. The study was conducted from June 1, 2022, through December 27, 2023. Main Outcomes and Measures: Life-years, quality-adjusted life years (QALYs), lifetime costs, and incremental cost-effectiveness ratios (ICERs) were estimated at country-specific willingness-to-pay thresholds ([data reported in US$] US: $150 000 per QALY; Brazil: $22 251 per QALY; Singapore: $55 288 per QALY, and Spain: $107 069 per QALY). One-way and probabilistic sensitivity analyses were performed to account for parameters of uncertainty. A cost-threshold analysis was also performed. Results: The US base-case model found that treatment with durvalumab was associated with an increased cost of $114 394 and improved effectiveness of 0.50 QALYs compared with placebo, leading to an ICER of $228 788 per QALY. Incremental cost-effectiveness ratios, according to base-case models, were $141 146 for Brazil, $153 461 for Singapore, and $125 193 for Spain. Durvalumab price adjustments to the PACIFIC data improved cost-effectiveness in Singapore, with an ICER of $45 164. The model was most sensitive to the utility of durvalumab. Conclusions and Relevance: In this cost-effectiveness analysis of durvalumab as maintenance therapy for unresectable stage III NSCLC, the therapy was found to be cost-prohibitive from the perspective of various international payers according to country-specific willingness-to-pay thresholds per QALY. The findings of the study suggest that discounted durvalumab acquisition costs, as possible in Singapore, might improve cost-effectiveness globally.

Predictors of quitting support from nonsmoking mothers for smoking fathers: a cross-sectional study from Chinese pupils' families.

BACKGROUND: Quitting support from smokers' partners can predict quit attempts and smoking abstinence but research on factors that predict such support has been limited. To add more evidence for partner support and the improved interventions for smoking cessation, we analyzed some new potential predictors of quitting support from smokers' spouses. METHOD: This cross-sectional study was conducted in in 2022 and 2023, selecting the students' families in which fathers smoked and mothers didn't smoke from grade 1-5 of 13 primary schools in Qingdao, China. Parents who met the criteria completed the online questionnaires and 1018 families were included in the analysis. We measured personal information related to smokers and their spouses such as age, education and nicotine dependence, and variables related to family and marital relationship such as family functioning, perceived responsiveness and power in decision-making of quitting smoking. Quitting support from smokers' spouses was measured by Partner Interaction Questionnaire and generalized linear model was used to explore the potential predictors of partner support. RESULTS: In this study, the mean age of smokers was 39.97(SD = 5.57) and the mean age of smokers' spouses was 38.24(SD = 4.59). The regression analysis showed that for smokers and their spouses, the older age groups showed the lower ratio of positive/negative support(P < 0.05) and smokers with high education showed the less positive and negative partner support(P < 0.05). Nicotine dependence was positively associated with negative support (ß = 0.120, P < 0.01), and perceived responsiveness (ß = 0.124, P < 0.05) as well as family functioning (ß = 0.059, P < 0.05) was positively associated with positive support. These three factors were associated with ratio of positive/negative support(P < 0.05). In addition, power of smoker's spouse in decision-making of quitting smoking was positively associated with the positive (ß = 0.087, P < 0.001) and negative support (ß = 0.084, P < 0.001). CONCLUSIONS: Nicotine dependence, family functioning, power in decision-making of quitting smoking and perceived responsiveness were found to be the predictors of quitting support from smokers' spouses. By incorporating predictors of partner support and integrating some established theories that can improve family functioning and marital relationships, smoking cessation interventions can be further improved.

Construction and Application of a Traditional Chinese Medicine Syndrome Differentiation Model for Dysmenorrhea Based on Machine Learning.

BACKGROUND: Dysmenorrhea is one of the most common ailments affecting young and middle-aged women, significantly impacting their quality of life. Traditional Chinese Medicine (TCM) offers unique advantages in treating dysmenorrhea. However, an accurate diagnosis is essential to ensure correct treatment. This research integrates the age-old wisdom of TCM with modern Machine Learning (ML) techniques to enhance the precision and efficiency of dysmenorrhea syndrome differentiation, a pivotal process in TCM diagnostics and treatment planning. METHODS: A total of 853 effective cases of dysmenorrhea were retrieved from the CNKI database, including patients' syndrome types, symptoms, and features, to establish the TCM information database of dysmenorrhea. Subsequently, 42 critical features were isolated from a potential set of 86 using a selection procedure augmented by Python's Scikit-Learn Library. Various machine learning models were employed, including Logistic Regression, Random Forest Classifier, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Artificial Neural Networks (ANN), each chosen for their potential to unearth complex patterns within the data. RESULTS: Based on accuracy, precision, recall, and F1-score metrics, SVM emerged as the most effective model, showcasing an impressive precision of 98.29% and an accuracy of 98.24%. This model's analytical prowess not only highlighted the critical features pivotal to the syndrome differentiation process but also stands to significantly aid clinicians in formulating personalized treatment strategies by pinpointing nuanced symptoms with high precision. CONCLUSION: The study paves the way for a synergistic approach in TCM diagnostics, merging ancient wisdom with computational acuity, potentially innovating the diagnosis and treatment mode of TCM. Despite the promising outcomes, further research is needed to validate these models in real-world settings and extend this approach to other diseases addressed by TCM.