Association of vitamins B1 and B2 intake with early-onset sarcopenia in the general adult population of the US: a cross-sectional study of NHANES data from 2011 to 2018.

Background: Early-onset sarcopenia refers to the progressive loss of muscle mass and function that occurs at an early age. This condition perpetuates the vicious cycle of muscle loss and is associated with adverse outcomes. It is important to identify the contributing factors for early intervention and prevention. While diet is known to impact muscle mass, the association of B vitamins with early-onset sarcopenia remains unexplored. Objectives: To investigate the association of B vitamins intake with early-onset sarcopenia risk in a cross-sectional study. Methods: We conducted data analysis on a total of 8,711 participants aged between 20 and 59 years who took part in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. Early-onset sarcopenia was defined as a SMI measured by DXA that was one standard deviation below the sex-specific mean of the reference population. B vitamins intake (B1, B2, B3, B6, B9, and B12) was assessed by 24-h dietary recall. We used weighted multiple logistic regression and RCS models to estimate the OR and 95% CI of sarcopenia by B vitamins intake, adjusting for demographic, physical, lifestyle, comorbidities, and nutritional covariates. Results: Higher intake of vitamin B1 was associated with a 22% lower sarcopenia risk (OR = 0.78, CI = 0.63-0.97, p = 0.022), and higher intake of vitamin B2 with a 16% lower risk (OR = 0.84, CI = 0.74-0.97, p = 0.012) in both genders. Gender-specific analyses showed a 28% reduction in sarcopenia risk among males with each additional mg of vitamin B1 intake (OR = 0.72, CI = 0.52-0.97, p = 0.038), and a 26% decrease among females with each additional mg of vitamin B2 intake (OR = 0.74, CI = 0.57-0.96, p = 0.021). No significant differences were found between vitamin B2 and males, or between vitamin B1 and females. The RCS model suggested a nonlinear relationship between vitamin B2 intake and sarcopenia risk (POverall = 0.001, PNonlinear = 0.033), with a plateau effect above 3 mg/d. Conclusion: Higher intake of vitamin B1 and B2 may lower the risk of early-onset sarcopenia, with gender differences. This suggests the potential of nutritional intervention by increasing these vitamins intake through diet and supplements. Further research is warranted to elucidate the mechanisms and design targeted interventions.

Exploring the Influence of Social Class and Sex on Self-Reported Health: Insights from a Representative Population-Based Study.

This study investigates the intricate interplay between social class, sex, and self-reported health (SRH) using data from the European Health Survey of Spain 2020 (EESE2020). Employing a cross-sectional design and a representative sample of 22,072 individuals, the analysis explores the persistence of disparities after adjusting for covariates, focusing on health-related variables. The study employs logistic regression models and directed acyclic graphs (DAGs) to delineate the direct effects of social class and sex on SRH, identifying a minimum adjustment set to control for confounding variables. Results reveal a gradient effect of social class on SRH, emphasizing the enduring impact of socioeconomic factors. Sex-based disparities in SRH diminish after considering additional health-related variables, highlighting the importance of a holistic approach. DAGs serve as transparent tools in disentangling complex relationships, guiding the identification of essential covariates. The study concludes that addressing health inequalities requires comprehensive strategies considering both individual health behaviours and socio-economic contexts. While recognizing limitations, such as the cross-sectional design, the findings contribute to a nuanced understanding of health disparities, informing evidence-based interventions and policies for a more equitable healthcare system.

Association of blood metals with anxiety among adults: A nationally representative cross-sectional study.

BACKGROUND: Previous evidence demonstrated the inconsistent associations between metals and anxiety. The purpose of this study was to evaluate the individual and joint effects of blood lead (Pb), cadmium (Cd), mercury (Hg), selenium (Se) and manganese (Mn) on anxiety in the general population. METHODS: Data of 4000 participants (aged≥20 years) in the study were retrieved from the National Health and Nutrition Examination Survey (NHANES) 2011-2012. Multiple logistic regression, restricted cubic splines (RCS) logistic analysis, and weighted quantile sum (WQS) regression were fitted to explore the possible effects of single and mixed metal exposures on anxiety. Moreover, this association was assessed by smoking group. RESULTS: In the study, 24.60 % of participants were in an anxiety state. In logistic regression, blood Pb, Cd, Hg, Se and Mn were not significantly associated with anxiety in all participants. After stratified by smoking group, blood Cd was positively associated with anxiety in the current smoking group [P = 0.029, OR (95 %): 1.708(1.063, 3.040)], whereas not in other groups. In RCS regression, we observed a linear dose-response effect of blood Cd on anxiety stratified by smoking group. In WQS analysis, mixed metal exposures were positively associated with anxiety [P = 0.033, OR (95 %): 1.437(1.031, 2.003)], with Cd (33.69 %) contributing the largest weight to the index. CONCLUSIONS: Our study showed that excessive exposure to Cd is a significant risk factor for anxiety, and the co-exposures to Pb, Cd, Hg, Se and Mn were positively related with the risk of anxiety in current smokers.

Impact of the pulmonary ventilation function on the prognosis of suspected asthma patients: a retrospective observational study.

OBJECTIVE: Asthma is a common chronic respiratory diseases, and the relationship between pulmonary ventilation function and the prognosis of patients with suspected asthma is not well understood. This study aims to explore the impact of pulmonary ventilation functions on the prognosis of patients with suspected asthma. METHODS: This retrospective observational study included patients with suspected asthma who were diagnosed and treated at the Guangdong Provincial Hospital of Traditional Chinese Medicine between August 2015 and January 2020. The primary outcome of interest was improvement in asthma symptoms, as measured by bronchial provocation test (BPT) results within one year after diagnosis. The impact of pulmonary ventilation functions on prognosis was explored by multivariable logistic regression analysis. RESULTS: Seventy-two patients were included in the study. Patients with normal (OR = 0.123, p = .004) or generally normal (OR = 0.075, p = .039) pulmonary ventilation function were more likely to achieve improvement in asthma symptoms compared with patients with mild obstruction. There were no significant differences between the improvement and non-improvement groups in baseline characteristics. CONCLUSION: These results suggest that suspected asthma patients with normal or generally normal pulmonary ventilation function are more likely to achieve improvement in asthma symptoms within one year compared to patients with mild obstruction.

Vitamin D Status among Patients Admitted to a Geriatric Ward-Are Recommendations for Preventing Its Deficiency Effective Enough?

Despite a decade of available recommendations aimed at preventing vitamin D (VD) deficiency in Poland, the efficacy of these measures among community-dwelling older individuals remains inconsistent. The PolSenior2 study provided valuable insights into VD status among community-dwelling older individuals in Poland. However, it is important to note that this research did not include the elderly living in care institutions. Therefore, our study concentrates on evaluating VD status in older patients admitted to a geriatrics ward to indirectly assess their adherence to existing recommendations and preventive actions in this particular setting (whether they translate into health-promoting behaviors (i.e., taking vitamin D supplements) and whether the recommended, optimal 25(OH)D concentration values are achieved). This approach offers a comprehensive understanding of VD status in a previously understudied population. We aimed to evaluate VD status in patients aged 70 and above within the geriatrics ward, exploring its association with age, sex, BMI, and the use of VD supplements. The study involved the measurement of serum VD concentration in 240 individuals. Of these participants, 177 (73.8%) were women, and 193 (80.4%) were over 75 years old. The median 25(OH)D concentration was found to be 22.95 (IQR, 13.7-33.0) ng/mL. Notably, profound deficiency (<10 ng/mL) was noted in 15% of the participants, while 67.5% exhibited VD inadequacy (<30 ng/mL). It is worth mentioning that only 18.3% of individuals took VD supplements preadmission. Insufficiency was more prevalent in nonsupplemented individuals (70.9% vs. 52.3%, p = 0.02) and those with a BMI ≥30 kg/m2 (76.2% vs. 59.2%, p = 0.007). The logistic regression model demonstrated that obese patients had over two times higher odds of VD inadequacy (OR = 2.21, p = 0.0074), as did nonsupplemented individuals (OR = 2.23, p = 0.0187). The high prevalence of VD deficiency and inadequacy in geriatric ward admissions emphasizes the urgent need for targeted interventions and enhanced education for older adults, caregivers, and physicians to improve adherence to preventive supplementation practices.

Disease-Related Factors Associated with Acupuncture Response in Patients with Chronic Tension-Type Headache: A Secondary Analysis of A Randomized Controlled Trial.

OBJECTIVE: To explore the demographic and disease-related factors associated with acupuncture response in patients with chronic tension-type headache (CTTH). METHODS: Using data from a randomized clinical trial (218 cases) consisting of 4 weeks of baseline assessment, 8 weeks of treatment, and 24 weeks of follow-up, participants were regrouped into responders (at least a 50% reduction in monthly headache days at week 16 compared with baseline) and non-responders. Twenty-three demographic and disease-related factors associated with acupuncture response in 183 participants were analyzed by multivariable logistic regression. RESULTS: One hundred and nineteen (65.0%) participants were classified as responders. Four factors were significantly independently associated with acupuncture response, including treatment assignment, headache intensity at baseline, and 2 domains [general health (GH) and social functioning (SF)] from the 36-Item Short Form Health Survey quality of life questionnaire. Treatment assignment was associated with non-response: participants receiving true acupuncture were 3-time more likely to achieve a CTTH response than those receiving superficial acupuncture [odds ratio (OR) 0.322, 95% confidence interval (CI) 0.162 to 0.625, P=0.001]. Compared with patients with mild-intensity headache, patients with moderate-intensity headache were twice as likely to respond to acupuncture (OR 2.001, 95% CI 1.020 to 4.011, P=0.046). The likelihood of non-response increased by 4.5% with each unit increase in the GH grade (OR 0.955, 95% CI 0.917 to 0.993, P=0.024) while decreased by 3.8% with each unit increase in the SF grade (OR 1.038, 95% CI 1.009 to 1.069, P=0.011). CONCLUSIONS: Greater headache intensity, lower GH score, and higher SF score were associated with better acupuncture responses in CTTH patients. These 3 factors require independent validation as predictors of acupuncture effectiveness in CTTH.

Setting nutrient boundaries to protect aquatic communities: The importance of comparing observed and predicted classifications using measures derived from a confusion matrix.

Defining nutrient thresholds that protect and support the ecological integrity of aquatic ecosystems is a fundamental step in maintaining their natural biodiversity and preserving their resilience. With increasing catchment pressures and climate change, it is more important than ever to develop clear methods to establish thresholds for status classification and management of waters. This must often be achieved using complex data and should be robust to interference from additional pressures as well as ameliorating or confounding conditions. We use both artificial and real data to examine challenges in setting nutrient thresholds in unbalanced and skewed data. We found significant advantages to using binary logistic regression over other techniques. However, one of the key challenges is objectively selecting a probability from which to derive the nutrient threshold. For this purpose, the examination of the proportions of matching and mismatching status classifications of nutrients and a biological quality element using a confusion matrix is a key step that should be more widely adopted in threshold selection. We examined a large array of statistical measures of classification accuracy and their performance over combinations of skewness and imbalance in the data. The most appropriate threshold probability is a compromise between maximising overall classification accuracy and reducing mismatches expressed as commission (false positives) without excessive omission (false negatives). An application to a lake type indicated total phosphorus thresholds that would be around 50 µg l-1 lower than the threshold achieved by an 'unguided' approach, indicating that this approach is a very significant development meriting attention from national authorities responsible for water management.

From fuzzy-TOPSIS to machine learning: A holistic approach to understanding groundwater fluoride contamination.

Fluoride (F-) contamination of groundwater is a prevalent environmental issue threatening public health worldwide and in India. This study targets an investigation into spatial distribution and contamination sources of fluoride in Dhanbad, India, to help develop tailored mitigation strategies. A triad of Multi Criteria Decision Making (MCDM) models (Fuzzy-TOPSIS), machine learning algorithms {logistic regression (LR), classification and regression tree (CART), Random Forest (RF)}, and classical methods has been undertaken here. Groundwater samples (n = 283) were collected for the purpose. Based on permissible limit (1.5 ppm) of fluoride in drinking water as set by the World Health Organization, samples were categorized as Unsafe (n = 67) and Safe (n = 216) groups. Mean fluoride concentration in Safe (0.63 ± 0.02 ppm) and Unsafe (3.69 ± 0.3 ppm) groups differed significantly (t-value = -10.04, p < 0.05). Physicochemical parameters (pH, electrical conductivity, total dissolved solids, total hardness, NO3-, HCO3-, SO42-, Cl-, Ca2+, Mg2+, K+, Na+ and F-) were recorded from samples of each group. The samples from 'Unsafe group' showed alkaline pH, the abundance of Na+ and HCO3- ions, prolonged rock water interaction in the aquifer, silicate weathering, carbonate dissolution, lack of Ca2+ and calcite precipitation which together facilitated the F- abundance. Aspatial distribution map of F- contamination was created, pinpointing the "contaminated pockets." Fuzzy- TOPSIS identified that samples from group Safe were closer to the ideal solution. Among these models, the LR proved superior, achieving the highest AUC score of 95.6 % compared to RF (91.3 %) followed by CART (69.4 %). This study successfully identified the primary contributors to F- contamination in groundwater and the developed models can help predicting fluoride contamination in other areas. The combination of different methodologies (Fuzzy-TOPSIS, machine learning algorithms, and classical methods) results in a synergistic effect where the strengths of each approach compensate for the limitations of the other.

The Association Between Vitamin B1 Deficiency and Anemia Among Elderly Patients at a Rural Hospital in Japan: A Cross-Sectional Study.

Background and objective Vitamin B1 deficiency can cause a variety of abnormalities in the neuropsychiatric, cardiovascular, and other systems. This condition can be rapidly corrected and prevented from progressing to irreversible sequelae through vitamin B1 supplementation. Therefore, early detection of and intervention in vitamin B1 deficiency are essential. We have previously demonstrated an association between vitamin B1 deficiency and appetite loss in hospitalized older adult patients in rural Japan. This study aimed to examine the additional predictors of vitamin B1 deficiency in patients with appetite loss and other symptoms suggestive of vitamin B1 deficiency. Material and methods This cross-sectional study involved 519 patients admitted to a rural hospital between April 2020 and March 2022. Data on vitamin B1 levels, age, sex, BMI, albumin levels, functional independence measure (FIM), hemoglobin levels, Charlson Comorbidity Index (CCI), and medications were collected from electronic medical records. Vitamin B1 deficiency was defined as serum vitamin B1 level <20 µg/dL. Data were analyzed using the Mann-Whitney U test, Student's t-test, and chi-square test, followed by multivariate logistic regression to examine the predictors of vitamin B1 deficiency. Results A total of 113 patients (21.5%) were found to be vitamin B1-deficient. Multivariate logistic regression showed that anemia was significantly associated with vitamin B1 deficiency [adjusted odds ratio (AOR): 1.71, 95% confidence interval (CI): 1.07-2.73, p<0.05]. Conclusion Based on our findings, anemia is significantly associated with vitamin B1 deficiency in hospitalized Japanese patients living in rural areas. Therefore, physicians should be mindful of the possibility of vitamin B1 deficiency in hospitalized patients with anemia.

Use of Cancer Survivorship Care Guidelines by Primary Care Providers in the United States.

BACKGROUND: National organizations have issued comprehensive cancer survivorship care guidelines to improve care of cancer survivors, many of whom receive care from primary care providers (PCPs). METHODS: We analyzed Porter Novelli's 2019 fall DocStyles survey to assess use of cancer survivorship care guidelines, receipt of survivorship training, types of survivorship services provided, and confidence providing care among PCPs in the United States. We grouped PCPs by use of any guideline ("users") versus no guideline use ("nonusers"). We calculated descriptive statistics and conducted multivariable logistic regression analyses to examine guideline use, having received training on providing survivorship care services, and confidence in providing care. Within the panel, sampling quotas were set so that 1000 primary care physicians, 250 OB/GYNs, 250 pediatricians, and 250 nurse practitioners/physician assistants were recruited. RESULTS: To reach selected quotas, 2696 health professionals were initially contacted to participate, resulting in a response rate of 64.9%. Sixty-two percent of PCPs reported using guidelines and 17% reported receiving survivorship care training. Use of any guidelines or receiving training was associated with reporting providing a range of survivorship services and confidence in providing care. After adjusting for demographic characteristics, guideline users were more likely than nonusers to report assessing genetic cancer risk (OR = 2.65 95% confidence interval (CI) (1.68, 4.17)), screening for cancer recurrence (OR = 2.32 95% CI (1.70, 3.18)) or a new cancer (OR = 1.63, 95% CI (1.20, 2.22)), and treating depression (OR = 1.64, 95% CI (1.20, 2.25)). Receipt of training was also positively associated with providing genetic risk assessment, surveillance for recurrence, as well as assessing late/long-term effects, and treating pain, fatigue, and sexual side effects. CONCLUSION: Survivorship care guidelines and training support PCPs in providing a range of survivorship care services.

A case-control study for exploring the association of Prakriti with Rheumatoid Arthritis.

BACKGROUND: Deha-Prakriti (DP) is a unique contribution of Ayurveda, which distinguishes the population into three main groups viz., Vata, Pitta, and Kapha predominant individuals. Its assessment helps physicians to prescribe a suitable diet, daily regimen, and lifestyle that prevents non-communicable diseases. Amavata (Rheumatoid Arthritis) is a disease that needs personalized management approach. AIM: To evaluate the association of DP with Amavata (∼Rheumatoid Arthritis). OBJECTIVE: To evaluate DP-based susceptibility in the manifestation of Amavata vis-à-vis Rheumatoid Arthritis. METHODOLOGY: A case-control study was conducted from 18.04.2018 to 09.01.2020, involving 150 cases (patients of Amavata), and 150 controls (healthy volunteers), matching in age (between 18 to 50 years), and sex, selected from Jamnagar. CCRAS-PAS for both the groups, Health Assessment proforma of TRISUTRA project CSIR-AYURGENOMICS, were used. Logistic regression analyses were conducted to determine the relationship between DP and Amavata. RESULTS: The proportion of people with Vata dosha in the case group (53.79%) was substantially higher (P < 0.0001) than in the control group (24.91%). Pitta (39.35%) and Kapha (36.27%) doshas were found to be more prevalent in the control group (P < 0.0001). There was a six-percent rise in the likelihood of developing Amavata with every unit increase in Vata percentage, according to logistic regression analysis. CONCLUSION: Vata predominant DP has a significant association with Amavata. Vata predominant DP individuals are more susceptible to Amavata than Pitta and Kapha predominant DP individuals.

Mortality Prediction in Severe Traumatic Brain Injury Using Traditional and Machine Learning Algorithms.

Abstract Prognostic prediction of traumatic brain injury (TBI) in patients is crucial in clinical decision and health care policy making. This study aimed to develop and validate prediction models for in-hospital mortality after severe traumatic brain injury (sTBI). We developed and validated logistic regression (LR), LASSO regression, and machine learning (ML) algorithms including support vector machines (SVM) and XGBoost models. Fifty-four candidate predictors were included. Model performance was expressed in terms of discrimination (C-statistic) and calibration (intercept and slope). For model development, 2804 patients with sTBI in the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) China Registry study were included. External validation was performed in 1113 patients with sTBI in the CENTER-TBI European Registry study. XGBoost achieved high discrimination in mortality prediction, and it outperformed logistic and LASSO regression. The XGBoost model established in this study also outperformed prediction models currently available, including the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) core and International Mission for Prognosis and Analysis of Clinical Trials (CRASH) basic models. When including 54 variables, XGBoost and SVM reached C-statistics of 0.87 (95% confidence interval [CI]: 0.81-0.92) and 0.85 (95% CI: 0.79-0.90) at internal validation, and 0.88 (95% CI: 0.87-0.88) and 0.86 (95% CI: 0.85-0.87) at external validation, respectively. A simplified version of XGBoost and SVM using 26 variables selected by recursive feature elimination (RFE) reached C-statistics of 0.87 (95% CI: 0.82-0.92) and 0.86 (95% CI: 0.80-0.91) at internal validation, and 0.87 (95% CI: 0.87-0.88) and 0.87 (95% CI: 0.86-0.87) at external validation, respectively. However, when the number of variables included decreased, the difference between ML and LR diminished. All the prediction models can be accessed via a web-based calculator. Glasgow Coma Scale (GCS) score, age, pupillary light reflex, Injury Severity Score (ISS) for brain region, and the presence of acute subdural hematoma were the five strongest predictors for mortality prediction. The study showed that ML techniques such as XGBoost may capture information hidden in demographic and clinical predictors of patients with sTBI and yield more precise predictions compared with LR approaches.

SPUR: A Patient-Reported Medication Adherence Model as a Predictor of Admission and Early Readmission in Patients Living with Type 2 Diabetes.

Purpose: Poor medication adherence (MA) is linked to an increased likelihood of hospital admission. Early interventions to address MA may reduce this risk and associated health-care costs. This study aimed to evaluate a holistic Patient Reported Outcome Measure (PROM) of MA, known as SPUR, as a predictor of general admission and early readmission in patients living with Type 2 Diabetes. Patients and Methods: An observational study design was used to assess data collected over a 12-month period including 6-month retrospective and 6-month prospective monitoring of the number of admissions and early readmissions (admissions occurring within 30 days of discharge) across the cohort. Patients (n = 200) were recruited from a large South London NHS Trust. Covariates of interest included: age, ethnicity, gender, level of education, income, the number of medicines and medical conditions, and a Covid-19 diagnosis. A Poisson or negative binomial model was employed for count outcomes, with the exponentiated coefficient indicating incident ratios (IR) [95% CI]. For binary outcomes (Coefficient, [95% CI]), a logistic regression model was developed. Results: Higher SPUR scores (increased adherence) were significantly associated with a lower number of admissions (IR = 0.98, [0.96, 1.00]). The number of medical conditions (IR = 1.07, [1.01, 1.13]), age ≥80 years (IR = 5.18, [1.01, 26.55]), a positive Covid-19 diagnosis during follow-up (IR = 1.83, [1.11, 3.02]) and GCSE education (IR = 2.11, [1.15,3.87]) were factors associated with a greater risk of admission. When modelled as a binary variable, only the SPUR score (-0.051, [-0.094, -0.007]) was significantly predictive of an early readmission, with patients reporting higher SPUR scores being less likely to experience an early readmission. Conclusion: Higher levels of MA, as determined by SPUR, were significantly associated with a lower risk of general admissions and early readmissions among patients living with Type 2 Diabetes.

Factors associated with falls in older adults: A secondary analysis of a 12-month randomized controlled trial.

PURPOSE: While identifying older adults at risk for falls is important, fall prediction models have had limited success, in part because of a poor understanding of which physical function measures to include. The purpose of this secondary analysis was to determine physical function measures that are associated with future falls in older adults. METHODS: In a 12-month trial comparing Vitamin D3 supplementation versus placebo on neuromuscular function, 124 older adults completed physical function measures at baseline, including the Short Physical Performance Battery (SPPB), Timed Up and Go, tests of leg strength and power, standing balance on a force plate with firm and foam surfaces, and walking over an instrumented walkway. Falls were recorded with monthly diaries over 12 months and categorized as no falls vs. one or more falls. Univariate and multivariable logistic regression adjusting for demographics, treatment assignment, depression, and prescription medications were conducted to examine the association between each physical function measure and future falls. Models were additionally adjusted for fall history. RESULTS: 61 participants sustained one or more falls. In univariate analysis, white race, depression, fall history, SPPB, and postural stability on foam were significantly associated with future falls. In multivariable analysis, fall history (OR (95% CI): 3.20 (1.42-7.43)), SPPB (0.80 (0.62-1.01)), and postural stability on foam (3.01 (1.18, 8.45)) were each significantly associated with future falls. After adjusting for fall history, only postural stability on foam was significantly associated with falls. CONCLUSIONS: When developing fall prediction models, fall history, the SPPB, and postural stability when standing on foam should be considered.

Lasso-Logistic regression model for the identification of serum biomarkers of neurotoxicity induced by strychnos alkaloids.

As a traditional Chinese medicine, strychnos alkaloids have wide effects including antitumor, analgesic, and anti-inflammatory. However, the therapeutic window of strychnos alkaloids is quite narrow due to potential neurotoxicity. Therefore, it is necessary to explore some efficient biomarkers to identify and predict the neurotoxicity induced by strychnos alkaloids and find a therapy to prevent the neurotoxicity of strychnos alkaloids. Based on the previous studies of our research team, 21 endogenous substances related to neurotoxicity were monitored in rats' serum with HPLC-MS/MS and ELISA. Starting from these fundamentals, a Lasso-Logistic regression model was used to select efficient biomarkers from 21 endogenous substances to predict brain injury and verify the neuroprotective effect of peonies. Under the processing of the Lasso-Logistic regression model, 12 biomarkers were identified from 21 endogenous substances to predict the neurotoxicity induced by strychnos alkaloids. At the same time, the neuroprotective effect of peonies was further confirmed by evaluating the level of 12 biomarkers. The results indicated that the development of the Lasso-Logistic regression model would provide a new, simple and efficient method for the prediction and diagnosis of the neurotoxicity induced by strychnos alkaloids.

BMI Modifies the Association Between Depression Symptoms and Serum Copper Levels.

Depression is one of the most common mental disorders which dramatically threatens public health and wellness. Copper has been known to be involved in many biological processes that could help explaining the occurrence of depression. However, studies focusing on its effect have yielded mixed results. The present study aims to evaluate the association between serum copper levels and depression symptoms. It also investigates the effect of modification of BMI (body mass index) on depression symptoms. A total of 5419 US adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) 2011-2016 participated in the cross-sectional study. Logistic regression models were applied using depression levels as the outcome and serum cooper/selenium/zinc categories as the main predictor, with the adjustments of gender, age, marital status, race, education, family income level, alcohol drinking, cigarette smoking, diabetes, pressure, stroke, and BMI. The interaction terms for copper levels and other covariates were further incorporated into the model to assess their roles in predicting depression symptoms. The prevalence of depression symptoms was significantly higher in samples with a high copper level. Among the levels of serum copper, selenium, and zinc, only the association between depression symptoms and serum copper levels was observed to be significant in the unadjusted model (P = 0.002). Individuals with a high copper level (114-134 µg/dL) and a very high copper level (≥ 134 µg/dL) had 1.85 (95% CI 1.24, 2.77)- and 1.72 (95% CI 1.21, 2.44)-fold higher odds ratio of depression symptoms, respectively, compared to those with a normal serum copper level. Although the association was not significant in the adjusted models, in which confounders were added, the interaction of copper level, including high and very high copper levels, and obesity (BMI ≥ 30 kg/m2) exhibited significantly higher odds ratio (4.12 (95% CI 1.38, 12.27) and 4.53 (95% CI 1.87, 10.96)) of having depression symptoms. The concentration of serum copper was positively associated with the prevalence of depression symptoms. Obesity exacerbated the risk of having depression symptoms in people with high serum copper levels.

Using radish (Raphanus lativus L.) germination to establish a benchmark dose for the toxicity of ozonated-petroleum byproducts in soil.

The concentration-response relationship between the germination outcome of radish (Raphanus lativus L.) and ozonated petroleum residuals was determined experimentally. The outcomes were used to produce an ecological risk assessment model to predict the extra risk of adverse outcomes based on the concentration of ozonated residuals. A test soil with low organic matter (0.5% w/w) was mixed with raw crude oil, artificially weathered, and treated at three doses of ozone (O3) gas (5 g, 10 g, and 40 g O3 per 600 g of soil). Total petroleum hydrocarbons (TPH) and produced dissolved organic carbon (DOC) were measured. TREATMENT categories (control, petroleum, petroleum + 5 g O3, petroleum + 10 g O3, and petroleum + 40 g O3) were then used to create a dilution series using different proportions of the test soil and a commercially available potting mix (∼75% w/w organic matter) to evaluate the effects of background organic matter (b-ORGANIC) in conjunction with TPH and DOC. Multivariable logistic regression was performed on the adverse germination outcome as a function of TPH, DOC, TREATMENT, and b-ORGANIC. The parameters controlling germination were the continuous variable DOC and the categorical variables TREATMENT and b-ORGANIC. Radish germination was strongly harmed by DOC from ozonation, but DOC's ecotoxicity decreased with increasing O3 dose and the presence of b-ORGANIC beyond 10% (w/w). We used the germination outcome of radish to produce a logistic regression model that computes margins of DOC (± std. error) that create 10%, 25%, and 50% extra risk of adverse germination effects.

Establishment and evaluation of predictive models of platelet transfusion effect in multi-center tumor patients / 中国输血杂志

【Objective】 To study the platelet transfusion predictive models in tumor patients and evaluate its application effect. 【Methods】 A retrospective study was conducted on 944 tumor patients, including 533 males and 411 females who received platelet transfusion in the Affiliated Hospital of Traditional Chinese Medicine of Xinjiang Medical University, the Affiliated Cancer Hospital of Xinjiang Medical University and Kailuan General Hospital from August 2022 to January 2023. Multivariate Logistic regression analysis was used to establish the platelet transfusion predictive models, and Medcalc15.8 software was used to draw the receiver operating curve (ROC) to evaluate the application effect of the prediction model. The actual application effect of models was verified through 162 female clinical cases and 172 male clinical cases. 【Results】 The incidence of platelet transfusion refractoriness in tumor patients was 28.9% (273/944), with 33.2% (177/533) in males, significantly higher than that in females [23.4% (96/411)] (P<0.05). Platelet transfusion predictive models: Y1 (female) =-8.546+ (0.581×number of pregnancies) + (0.964×number of inpatient transfusion bags) + number of previous platelet transfusion bags (5-9 bags: 1.259, ≥20 bags: 1.959) + clinical diagnosis (lymphoma: 2.562, leukemia: 3.214); Y2 (male) =-7.600+ (1.150×inpatient transfusion bags) + previous platelet transfusion bags (10-19 bags: 1.015, ≥20 bags: 0.979) + clinical diagnosis (lymphoma: 1.81, leukemia: 3.208, liver cancer: 1.714). Application effect evaluation: The AUC (area under the curve), cut-off point, corresponding sensitivity and specificity of female and male platelet transfusion effect prediction models were 0.868, -0.354, 68.75%, 89.84% and 0.854, -0.942, 81.36%, 77.53%, respectively. Actual application results showed that the sensitivity, specificity, and accuracy of female and male model were 89.47%, 92.74%, 91.98% and 83.72%, 91.47%, 89.53%, respectively. 【Conclusion】 There is high incidence of platelet transfusion refractoriness in tumor patients, and the predictive model has good prediction effect on platelet transfusion refractoriness in tumor patients, which can provide reliable basis for accurate platelet transfusion in tumor patients.

The association of trace elements with arthritis in US adults: NHANES 2013-2016.

BACKGROUND: Arthritis is a common chronic disease, and is a major cause of disability and chronic pain in adults. Considering inflammatory responses is closely related with trace elements (TEs), the role of TEs in arthritis has attracted much attention. This study aimed to assess the association between TEs and arthritis. METHODS: Concentrations of TEs in whole blood [cadmium (Cd), lead (Pb), mercury (Hg), selenium (Se), and manganese (Mn)] and serum [copper (Cu) and zinc (Zn)] were measured in adults who participated in the US National Health and Nutrition Examination Survey. Logistic regression model and Bayesian kernel machine regression model were used to explore the association between TEs and arthritis. RESULTS: The levels of five TEs (Pb, Hg, Cd, Se, and Cu) in the arthritis group changed significantly. Three TEs were found to be associated with an increased risk of arthritis: Pb [OR (95% CI): 2.96 (2.18, 4.03), p-value for trend (P-t) < 0.001], Cd [OR (95% CI): 2.28 (1.68, 3.11), P-t < 0.001], Cu [OR (95% CI): 2.05 (1.53, 2.76), P-t < 0.001]. The Relative Excess Risk of Interaction was 0.35 (95% CI: 0.06-0.65) and 0.38 (95% CI: 0.11-0.64), respectively, suggesting that Hg ions and Se ions have positive additional interactions with alcohol consumption, which reduced the risk of arthritis. Subgroup analysis showed that Pb ions and Cd ions were significantly correlated with osteoarthritis and rheumatoid arthritis. CONCLUSION: Elevated concentrations of Pb, Cd, and Cu were associated with increased risk of arthritis. Drinking with high levels of Hg or Se may be a protective factor for arthritis. Future studies are warranted to validate these findings in prospective studies.

Parameter study on characteristic pulse diagram of polycystic ovary syndrome based on logistic regression analysis.

This study aimed to explore the parameters of the independent predictive characteristic pulse diagram of polycystic ovary syndrome (PCOS) by analysing the pulse characteristics between healthy women and the PCOS group. A total of 278 women were recruited for this study. Pulse wave parameters were collected by the pulse spectrum analyser. The single-factor analysis of the pulse diagram parameters was used to identify significant indicators, and the logistic regression analysis was carried out on the above indicators with statistical differences to obtain independent predictors. According to the single-factor and multi-factor analyses, h1, h5, h3/h1, t, t1 and t5 were independent predictors of PCOS diagnosis. The results showed that PCOS patients had a faster heart rate, decreased left ventricular systolic function and decreased aortic compliance compared to healthy individuals. These findings suggested that the characteristic pulse parameters screened out are valuable for the diagnosis of PCOS.IMPACT STATEMENTWhat is already known on this subject? Polycystic ovary syndrome (PCOS) is a common gynecological reproductive endocrine and metabolic disease, which is significant for screening and early intervention in the disease. However, due to the lack of pulse's diagnostic evidence of PCOS, there is still an unknown area in the research on the correlation between PCOS and pulse diagram parameters.What do the results of this study add? This study fills the gap between the research on PCOS and pulse wave. The study also shows that the pulse characteristic parameters h1, h5, h3/h1, t, t1, and t5 are independent predictors of PCOS, suggesting that the patients have a higher heart rate, lower ventricular systolic function, and aortic compliance than healthy individuals.What are the implications of these findings for clinical practice and/or further research? Prominent risk factors for pulse parameters associated with the occurrence of PCOS facilitate early screening and diagnosis of the disease. The objectification of pulse diagnosis helps to establish a health management model, which can be used for the accurate assessment and treatment of PCOS by traditional Chinese medicine (TCM). It provides a clinical reference for the study of pulse diagnosis objectification.