Obesity Disparities Among Adult Single-Race and Multiracial Asian and Pacific Islander Populations.

Importance: Despite increasing numbers of multiracial individuals, they are often excluded in studies or aggregated within larger race and ethnicity groups due to small sample sizes. Objective: To examine disparities in the prevalence of obesity among single-race and multiracial Asian and Pacific Islander individuals compared with non-Hispanic White (hereafter, White) individuals. Design, Setting, and Participants: This cross-sectional study used electronic health record (EHR) data linked to social determinants of health and health behavior data for adult (age ≥18 years) members of 2 large health care systems in California and Hawai'i who had at least 1 ambulatory visit to a primary care practitioner between January 1, 2006, and December 31, 2018. Data were analyzed from October 31, 2022, to July 31, 2023. Exposure: Self-identified race and ethnicity provided in the EHR as a single-race category (Asian Indian, Chinese, Filipino, Japanese, Native Hawaiian only, Other Pacific Islander, or White) or a multiracial category (Asian and Pacific Islander; Asian, Pacific Islander, and White; Asian and White; or Pacific Islander and White). Main Outcomes and Measures: The main outcome was obesity (body mass index [BMI] ≥30.0), based on last measured height and weight from the EHR. Logistic regression was used to examine the association between race and ethnicity and odds of obesity. Results: A total of 5229 individuals (3055 [58.4%] male; mean [SD] age, 70.73 [11.51] years) were examined, of whom 444 (8.5%) were Asian Indian; 1091 (20.9%), Chinese; 483 (9.2%), Filipino; 666 (12.7%), Japanese; 91 (1.7%), Native Hawaiian; 95 (1.8%), Other Pacific Islander; and 888 (17.0%), White. The percentages of individuals who identified as multiracial were as follows: 417 (8.0%) were Asian and Pacific Islander; 392 (7.5%), Asian, Pacific Islander, and White; 248 (4.7%), Asian and White; and 414 (7.9%), Pacific Islander and White. A total of 1333 participants (25.5%) were classified as having obesity based on standard BMI criteria. Obesity was highest among people who identified as Asian, Pacific Islander, and White (204 of 392 [52.0%]) followed by those who identified as Other Pacific Islander (47 of 95 [49.5%]), Native Hawaiian (44 of 91 [48.4%]), and Pacific Islander and White (186 of 414 [44.9%]). After accounting for demographic, socioeconomic, and health behavior factors, people who identified as Asian, Pacific Islander, and White (odds ratio [OR], 1.80; 95% CI, 1.37-2.38) or Pacific Islander and White (OR, 1.55; 95% CI, 1.18-2.04) had increased odds of obesity compared with White individuals. All single-race Asian groups had lower odds of obesity compared with White individuals: Asian Indian (OR, 0.29; 95% CI, 0.20-0.40), Chinese (OR, 0.22; 95% CI, 0.17-0.29), Filipino (OR, 0.46; 95% CI, 0.35-0.62), and Japanese (OR, 0.38, 95% CI, 0.29-0.50). Conclusions and Relevance: In this study, multiracial Asian and Pacific Islander individuals had an increased prevalence of obesity compared with many of their single-race counterparts. As the number of multiracial individuals increases, it will be important for clinical and public health systems to track disparities in these populations.

Combining fecal immunochemical testing and questionnaire-based risk assessment in selecting participants for colonoscopy screening in the Chinese National Colorectal Cancer Screening Programs: A population-based cohort study.

BACKGROUND: Screening reduces colorectal cancer (CRC) burden by allowing early resection of precancerous and cancerous lesions. An adequate selection of high-risk individuals and a high uptake rate for colonoscopy screening are critical to identifying people more likely to benefit from screening and allocating healthcare resources properly. We evaluated whether combining a questionnaire-based interview for risk factors with fecal immunochemical test (FIT) outcomes for high-risk assessment is more efficient and economical than a questionnaire-based interview-only strategy. METHODS AND FINDINGS: In this multicenter, population-based, prospective cohort study, we enrolled community residents aged 40 to 74 years in 29 provinces across China. From 2016 to 2020, a total of 1,526,824 eligible participants were consecutively enrolled in the Cancer Screening Program in Urban China (CanSPUC) cohort, and 940,605 were enrolled in the Whole Life Cycle of Cancer Screening Program (WHOLE) cohort, with follow-up to December 31, 2022. The mean ages were 56.89 and 58.61 years in CanSPUC and WHOLE, respectively. In the WHOLE cohort, high-risk individuals were identified by combining questionnaire-based interviews to collect data on risk factors (demographics, diet history, family history of CRC, etc.) with FIT outcomes (RF-FIT strategy), whereas in the CanSPUC cohort, high-risk individuals were identified using only interview-based data on risk factors (RF strategy). The primary outcomes were participation rate and yield (detection rate of advanced neoplasm, early-stage detection rate of CRCs [stage I/II], screening yield per 10,000 invitees), which were reported for the entire population and for different gender and age groups. The secondary outcome was the cost per case detected. In total, 71,967 (7.65%) and 281,985 (18.47%) individuals were identified as high-risk and were invited to undergo colonoscopy in the RF-FIT group and RF group, respectively. The colonoscopy participation rate in the RF-FIT group was 26.50% (19,071 of 71,967) and in the RF group was 19.54% (55,106 of 281,985; chi-squared test, p < 0.001). A total of 102 (0.53%) CRCs and 2,074 (10.88%) advanced adenomas were detected by the RF-FIT, versus 90 (0.16%) and 3,593 (6.52%) by the RF strategy (chi-squared test, both p < 0.001). The early-stage detection rate using the RF-FIT strategy was significantly higher than that by the RF strategy (67.05% versus 47.95%, Fisher's exact test, p = 0.016). The cost per CRC detected was $24,849 by the RF-FIT strategy versus $55,846 by the RF strategy. A limitation of the study was lack of balance between groups with regard to family history of CRC (3.5% versus 0.7%). CONCLUSIONS: Colonoscopy participation and screening yield were better with the RF-FIT strategy. The association with CRC incidence and mortality reduction should be evaluated after long-term follow-up.

Low-dose decitabine for previously untreated acute myeloid leukemia ineligible for intensive chemotherapy aged 65 years or older: a prospective study based on comprehensive geriatric assessment.

Background: The outcome of patients with acute myeloid leukemia (AML) aged ⩾65 years is poor. Effective treatment options are limited for patients with AML who cannot tolerate intensive chemotherapy. Objectives: We aimed to evaluate the efficacy of low-dose decitabine in previously untreated patients with AML aged ⩾65 years who were ineligible for intensive chemotherapy based on a comprehensive geriatric assessment. Design: We performed a prospective, multicenter, open-label, and non-randomized study. Methods: Patients were enrolled at four centers in Beijing between 1 January 2017 and 31 December 2020. They were treated with decitabine at a dose of 6 mg/m2 for 10 days. The treatment was repeated every 28 days for one cycle for a total of six cycles. The primary endpoint of our study was overall survival (OS) at the end of the first year after enrolment. The secondary endpoints included overall response rate, leukemia-free survival, relapse rate, treatment-related mortality (TRM), quality of life, safety, and transfusion dependence. Patients were continuously monitored for toxicity. Results: Overall, 47 patients (30 males and 17 females) participated in this study. The median age of the enrolled patients was 78 (range, 65-90) years. The median follow-up time was 22.2 (range, 4.6-38.8) months. Fifteen (31.9%) patients achieved complete remission (CR), 11 (23.4%) patients achieved partial remission, 3 (6.4%) patients achieved hematological improvement only, and 18 (38.3%) patients did not achieve remission. The median time to obtain CR was 2 months. The median CR was 8.5 months. Of the patients, 36 (76.6%) patients completed six cycles of treatment with low-dose decitabine, and the 1-year OS was 36.1%. According to instrumental activities of daily living scales, age, comorbidities, and albumin (IACA) scores, the median survival was 11.2 months in the unfit group and 6 months in the frail group. The 1-year OS rates in the unfit and frail groups were 49.2% and 23.4%, respectively. Grade ⩾3 non-hematological toxicity was observed in 70.2% (33/47) of the patients. TRM occurred in three patients. No early deaths occurred after treatment. Conclusion: In newly diagnosed older patients with AML whose IACA assessment was unfit or frail for standard chemotherapy, treatment with low-dose decitabine demonstrated clinical activity and good security in our study.

A protocol of Chinese expert consensuses for the management of health risk in the general public.

Introduction: Non-communicable diseases (NCDs) represent the leading cause of mortality and disability worldwide. Robust evidence has demonstrated that modifiable lifestyle factors such as unhealthy diet, smoking, alcohol consumption and physical inactivity are the primary causes of NCDs. Although a series of guidelines for the management of NCDs have been published in China, these guidelines mainly focus on clinical practice targeting clinicians rather than the general population, and the evidence for NCD prevention based on modifiable lifestyle factors has been disorganized. Therefore, comprehensive and evidence-based guidance for the risk management of major NCDs for the general Chinese population is urgently needed. To achieve this overarching aim, we plan to develop a series of expert consensuses covering 15 major NCDs on health risk management for the general Chinese population. The objectives of these consensuses are (1) to identify and recommend suitable risk assessment methods for the Chinese population; and (2) to make recommendations for the prevention of major NCDs by integrating the current best evidence and experts' opinions. Methods and analysis: For each expert consensus, we will establish a consensus working group comprising 40-50 members. Consensus questions will be formulated by integrating literature reviews, expert opinions, and an online survey. Systematic reviews will be considered as the primary evidence sources. We will conduct new systematic reviews if there are no eligible systematic reviews, the methodological quality is low, or the existing systematic reviews have been published for more than 3 years. We will evaluate the quality of evidence and make recommendations according to the GRADE approach. The consensuses will be reported according to the Reporting Items for Practice Guidelines in Healthcare (RIGHT).

The roles of liquidity and delay in financial markets based on an optimal forecasting model.

We investigate the roles of liquidity and delay in financial markets through our proposed optimal forecasting model. The efficiency and liquidity of the financial market are examined using stochastic models that incorporate information delay. Based on machine learning, we estimate the in-sample and out-of-sample forecasting price performances of the six proposed methods using the likelihood function and Bayesian methods, and the out-of-sample prediction performance is compared with the benchmark model ARIMA-GARCH. We discover that the forecasting price performance of the proposed simplified delay stochastic model is superior to that of the benchmark methods by the test methods of a variety of loss function, superior predictive ability test (SPA), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Using data from the Chinese stock market, the best forecasting model assesses the efficiency and liquidity of the financial market while accounting for information delay and trade probability. The rise in trade probability and delay time affects the stability of the return distribution and raises the risk, according to stochastic simulation. The empirical findings show that empirical and best forecasting approaches are compatible, that company size and liquidity (delay time) have an inverse relationship, and that delay time and liquidity have a nonlinear relationship. The most efficient have optimal liquidity.

Factors associated with adherence to provider referrals for lung cancer screening with low dose computed tomography before and during COVID-19 pandemic.

BACKGROUND: Lung cancer has been the leading cause of American deaths from cancer. Although Medicare started covering lung cancer screening (LCS) with low-dose computed tomography (LDCT) in 2015, the uptake of LDCT-LCS remains low. This study examines the changes in adherence to provider referrals for LDCT-LCS and the factors at patient, provider, and health system levels that influence the completion rate of LDCT-LCS orders before and during the COVID-19 pandemic. METHODS: Our study examined electronic health record data (December 2013 - December 2020) from a large, community-based clinical healthcare delivery system in California. We plotted monthly trends in the frequency of LDCT-LCS orders and completion rate and compared the annual LDCT-LCS completion rate between LCS-eligible, LCS-ineligible, and unknown eligibility groups. We then explored multilevel factors associated with the completion of LDCT-LCS orders using hierarchical generalized linear models. RESULTS: There was an increase in LDCT-LCS orders (N = 12,469) from 2013 to 2019, followed by a sharp decline in March 2020 due to the onset of the COVID-19 pandemic. Thereafter, LDCT-LCS orders slowly increased again in June 2020. The completion rate of LDCT-LCS increased from 0% in December 2013 to approximately 70% in 2018-2019 but declined to 50-60% in 2020 during the pandemic. Ineligible patients had lower completion rates of LDCT-LCS. Patients who were new to the healthcare system, Black, received the LDCT-LCS order in the first few years after Medicare coverage (2016 or 2017), during the pandemic, had major comorbidities, and smoked less than 30 pack-years were less likely to complete an order. Patients were more likely to complete LDCT-LCS orders if they were younger, received the LDCT-LCS order from a physician (vs. nonphysician provider), from family medicine or other specialties (vs. internal medicine), or saw a provider with more experience in LDCT-LCS. CONCLUSIONS: The beginning of the COVID-19 pandemic largely decreased the volume of LDCT-LCS orders, but rates have since been slowing recovering. Future interventions to improve lung cancer screening should consider doing more targeted outreach to new patients and Black patients as well as providing additional education to nonphysician practitioners and those providers with lower rates of LDCT-LCS referral orders.

Recent development of nanotechnology-empowered antigen assay methods for the control of infectious diseases.

The global spread of air-borne diseases, such as Covid-19 caused by the new coronavirus (SARS-CoV-2), has significantly impacted public health and economic development worldwide. Accurate and rapid detection of pathogens is the key to controlling the spread of infection and reducing severe illness and death. Compared to nucleic acid testing, rapid antigen testing for pathogen proteins shows unique advantages such as convenience, speed, and cost-effectiveness, but its sensitivity is limited. Here, we review the latest progress in the development of immunological assay methods for infectious diseases. We summarize the principles, performance, advantages and limitations of several representative methods. We highlight recent efforts in utilizing nanotechnology to engineer biosensing interfaces, offering enhanced sensitivity while maintaining convenience for on-site diagnosis. Finally, we provide an outlook on the development of this field.

Assessment of neoadjuvant chemotherapy with docetaxel, cisplatin, and fluorouracil in patients with oral cavity cancer.

BACKGROUND: Chemotherapy with docetaxel, cisplatin, and fluorouracil (TPF) has been studied in patients with head and neck cancer. Its impact on patients with oral cavity cancer was not specified. METHODS: We consecutively reviewed medical files of patients with untreated oral cavity cancer who received neoadjuvant TPF chemotherapy in our department from January 2017 to April 2020. Outcomes included the objective response to TPF chemotherapy, factors associated with the response, and progression and survival in different response groups. RESULTS: A total of 167 patients were included, with half of stage IV disease. Complete or partial response was observed in 51 patients. A total of 91 patients had stable disease, and 25 patients had progressive disease. The response was not associated with age, sex, anatomic subsite, and the tumor's T stage. It was related with N stage (p < 0.001) and clinical stage (p = 0.004). Most patients with bulky nodes or nodes with obvious necrosis showed low response or even progressed after neoadjuvant TPF chemotherapy. The planned surgery was conducted in 159 patients. Disease relapse mostly occurred in 2 years after treatment. The 2-year overall survival and the progression-free survival were 89.0% and 85.2% for patients with complete or partial response, 62.4% and 55.6% for patients with stable disease, and 12.5% and 4.2% for patients with progressive disease, respectively. CONCLUSIONS: The response of neoadjuvant TPF chemotherapy in patients with oral cavity cancer is related to disease stage, especially the nodal stage. Patients with complete or partial response developed less progression events and better survival.

Supporting routine cognitive reactivity assessment during the perinatal period: psychometric testing of the Chinese version of the Leiden Index of Depression Sensitivity.

BACKGROUND: It is critical to find optimal forms to identify perinatal depression (PND) and its vulnerable factors and make them more applicable to depression screening. This study aims to evaluate the reliability and validity of the Chinese version of the Leiden Index of Depression Sensitivity (LEIDS-RR-CV) among perinatal women in China and determine the cut-off values for screening for high-risk depression. METHODS: Women in their third trimester of pregnancy and six weeks postpartum completed the LEIDS-RR-CV and a diagnostic reference standard online. We assessed the LEIDS-RR-CV using classical test theory (CTT) and item response theory (IRT). We also assessed the test performance for cut-off scores using receiver operator characteristic analysis to further screen for high-risk depression at each time point. RESULTS: In total, 396 (third trimester) and 321 (six weeks postpartum) women participated. Cronbach's alpha, two-week test-retest reliability, and marginal reliability for the scale were all greater than 0.8. It showed a five-factor model; the cut-off values were 58 (third trimester) and 60 (six weeks postpartum). The areas under the curve were acceptable (≥ 0.7), and the LEIDS-RR-CV was positively correlated with the total Edinburgh Postnatal Depression Scale (EPDS) score (r = 0.52 and 0.56, p = 0.00), indicating its predictive validity. An IRT analysis further confirmed its discriminative validity. CONCLUSIONS: The LEIDS-RR-CV was found to be reliable, valid, and can be used to quantify cognitive reactivity among perinatal Chinese women and for screening for high-risk depression during this period.

Provider and patient perspectives to improve lung cancer screening with low-dose computed tomography 5 years after Medicare coverage: a qualitative study.

Lung cancer remains the leading cause of cancer-related deaths for both men and women in the U.S., yet uptake of preventive cancer screening for people with a heavy smoking history remains low. This qualitative interview study of patients and providers from a large ambulatory healthcare system in northern and central California reevaluated perceptions of lung cancer screening with low-dose computed tomography (LCS-LDCT) 5 years after Medicare coverage. We hypothesized that initial attitudes and barriers within the LCS-LDCT discussion and process have likely persisted with little change since Medicare coverage and we sought to understand how these attitudes continue to impact effective implementation and uptake of screening with the goal of identifying opportunities for improvement. Between 2019 and 2020, interviews were conducted with 10 primary care physicians and 30 patients using semi-structured interview guides. Providers and patients expressed that they were both aware and supportive of LCS-LDCT, a change from earlier studies, but continued to report little to no shared decision making nor use of a decision aid despite being Medicare requirements. Creation and incorporation of a single-page, graphic heavy decision aid may help address many of the persistent barriers around implementation for both providers and patients. Given recently expanded guidelines from the U.S. Preventive Services Task Force for LCS-LDCT screening and their coverage by Medicare, it is important for healthcare systems to understand provider and patient perceptions to further improve the implementation of LCS-LDCT to ultimately reduce lung cancer mortality.

Explainable Deep-Learning-Assisted Sweat Assessment via a Programmable Colorimetric Chip.

Multianalytes and individual differences of biofluids (such as blood, urine, or sweat) pose enormous complexity and challenges to rapid, facile, high-throughput, and accurate clinical analysis or health assessment. Deep-learning (DL)-assisted image analysis has been demonstrated to be an efficient big data process which shows accurate individual identification. However, the data-driven "black boxes" of current DL algorithms are suffering from the nontransparent inner working mechanism. In this work, we designed a programmable colorimetric chip with explainable DL to approach accurate classification and quantification analysis of sweat samples. Gel (sodium alginate) capsules with different indicators were adopted to combinate as designed programmable colorimetric chips. We collected 4600 colorimetric response images as the data set and assessed two DL algorithms and seven machine learning (ML) algorithms. Glucose, pH, and lactate in human sweat could be facilely and 100% accurately classified and quantified by the convolutional neural network (CNN) DL algorithm, and the testing results of actual sweat via the DL-assisted colorimetric approach match 91.0-99.7% with the laboratory measurements. Class activation mapping (CAM) was processed to visualize the inner working mechanism of CNN operation, which could help to verify and explicate the design rationality of colorimetric chips. The explainable DL-assisted programmable colorimetric chip provided an "end-to-end" strategy to ascertain the black box of the DL algorithm, promoted software design or principium optimization, and contributed facile indicators for clinical monitoring, disease prevention, and even new scientific discoveries.

Effects of Smoking on SARS-CoV-2 Positivity: A Study of a Large Health System in Northern and Central California.

Introduction: COVID-19 continues to impact vulnerable populations disproportionally. Identifying modifiable risk factors could lead to targeted interventions to reduce infections. The purpose of this study is to identify risk factors for testing positive for SARS-CoV-2. Methods: Using electronic health records collected from a large ambulatory care system in northern and central California, the study identified patients who had a test for SARS-CoV-2 between 2/20/2020 and 3/31/2021. The adjusted effect of active and passive smoking and other risk factors on the probability of testing positive for SARS-CoV-2 were estimated using multivariable logistic regression. Analyses were conducted in 2021. Results: Of 556 690 eligible patients in our sample, 70 564 (12.7%) patients tested positive for SARS-CoV-2. Younger age, being male, racial/ethnic minorities, and having mild major comorbidities were significantly associated with a positive SARS-CoV-2 test. Current smokers (adjusted OR: 0.69, 95% CI: 0.66-0.73) and former smokers (adjusted OR: 0.92, 95% CI: 0.89-0.95) were less likely than nonsmokers to be lab-confirmed positive, but no statistically significant differences were found when comparing passive smokers with non-smokers. The patients with missing smoking status (25.7%) were more likely to be members of vulnerable populations with major comorbidities (adjusted OR ranges from severe: 2.52, 95% CI = 2.36-2.69 to mild: 3.28, 95% CI = 3.09-3.48), lower income (adjusted OR: 0.85, 95% CI: 0.85-0.86), aged 80 years or older (adjusted OR: 1.11, 95% CI: 1.07-1.16), have less access to primary care (adjusted OR: 0.07, 95% CI: 0.07-0.07), and identify as racial ethnic minorities (adjusted OR ranges from Hispanic: 1.61, 95% CI = 1.56-1.65 to Non-Hispanic Black: 2.60, 95% CI = 2.5-2.69). Conclusions: Our findings suggest that the odds of testing positive for SARS-CoV-2 were significantly lower in smokers compared to nonsmokers. Other risk factors include missing data on smoking status, being under 18, being male, being a racial/ethnic minority, and having mild major comorbidities. Since those with missing data on smoking status were more likely to be members of vulnerable populations with higher smoking rates, the risk of testing positive for SARS-CoV-2 among smokers may have been underestimated due to missing data on smoking status. Future studies should investigate the risk of severe outcomes among active and passive smokers, the role that exposure to tobacco smoke constitutes among nonsmokers, the role of comorbidities in COVID-19 disease course, and health disparities experienced by disadvantaged groups.

Social Determinants of Stroke Hospitalization and Mortality in United States' Counties.

(1) Background: Stroke incidence and outcomes are influenced by socioeconomic status. There is a paucity of reported population-level studies regarding these determinants. The goal of this ecological analysis was to determine the county-level associations of social determinants of stroke hospitalization and death rates in the United States. (2) Methods: Publicly available data as of 9 April 2021, for the socioeconomic factors and outcomes, was extracted from the Centers for Disease Control and Prevention. The outcomes of interest were "all stroke hospitalization rates per 1000 Medicare beneficiaries" (SHR) and "all stroke death rates per 100,000 population" (SDR). We used a multivariate binomial generalized linear mixed model after converting the outcomes to binary based on their median values. (3) Results: A total of 3226 counties/county-equivalents of the states and territories in the US were analyzed. Heart disease prevalence (odds ratio, OR = 2.03, p < 0.001), blood pressure medication nonadherence (OR = 2.02, p < 0.001), age-adjusted obesity (OR = 1.24, p = 0.006), presence of hospitals with neurological services (OR = 1.9, p < 0.001), and female head of household (OR = 1.32, p = 0.021) were associated with high SHR while cost of care per capita for Medicare patients with heart disease (OR = 0.5, p < 0.01) and presence of hospitals (OR = 0.69, p < 0.025) were associated with low SHR. Median household income (OR = 0.6, p < 0.001) and park access (OR = 0.84, p = 0.016) were associated with low SDR while no college degree (OR = 1.21, p = 0.049) was associated with high SDR. (4) Conclusions: Several socioeconomic factors (e.g., education, income, female head of household) were found to be associated with stroke outcomes. Additional research is needed to investigate intermediate and potentially modifiable factors that can serve as targeted interventions.

A Case Study of Community-Academic Partnership in Improving the Quality of Life for Asthmatic Urban Minority Children in Low-Income Households.

Community-academic partnerships (CAPs) are being increasingly used to study and address health disparity issues. CAPs help to create new bodies of knowledge and innovative solutions to community problems, which benefits the community and academia. Supported by a grant, a partnership was formed between an academic research team and a community health organization to analyze and interpret data collected from the caregivers of asthmatic African American children living in urban low-income households. Using a case study approach, we discuss how we built a healthy CAP and the lessons learned from the process. Our analysis was guided by the six main factors that facilitate success in developing collaborative relationships, including (1) environment; (2) membership; (3) process and structure; (4) communication; (5) purpose; and (6) resources. Based on these six factors, we describe our collaboration process, challenges, and areas for improvement. We aimed to provide a "points-to-consider" roadmap for academic and community partners to establish and maintain a mutually beneficial and satisfactory relationship. Collaborating with community members and organizations provides unique opportunities for researchers and students to apply their skills and knowledge from textbooks and the classroom, engage with community members, and improve real-life community needs. Building a constructive CAP involves efforts, energy, and resources from both parties. The six major themes derived from our project offer suggestions for building a healthy, collaborative, and productive relationship that best serves communities in the future.

Serum creatinine/cystatin C ratio as a screening tool for sarcopenia and prognostic indicator for patients with esophageal cancer.

BACKGROUND & AIMS: Sarcopenia is associated with poor clinical outcomes of patients who underwent esophagectomy. The current diagnostic criteria for sarcopenia are complex and laborious. We aimed to employ the simple and economic indicator sarcopenia index (SI = creatinine/cystatin C ×100) to screen for sarcopenia and to evaluate its prognostic value in patients with esophageal cancer (EC). METHODS: Older participants in the National health and nutrition examination survey (NHANES) database (1999-2002) were divided into three groups according to tertiles of the SI value to explore the feasibility of SI in the diagnosis of sarcopenia. Restricted cubic spline (RCS) was utilized to show the non-linear relationship between all-cause mortality and SI. Patients with EC admitted to Jinling Hospital were enrolled to validate the efficacy and prognostic value of SI. Cut-off values of SI were determined using receiver operating characteristic curves. Multivariable logistic analyses and Cox analyses were used to identify the independent factors of postoperative complications and long-term survival, respectively. RESULTS: A total of 989 participants were identified from the NHANES database. SI showed the diagnostic value of sarcopenia (tertile 1 vs. tertile 3: odds ratio [OR]=3.67, 95% confidence interval [CI]: 1.52-8.87, p=0.004; tertile 2 vs. tertile 3: OR=1.79, 95% CI: 0.75-4.28, p=0.191) adjusted for race, gender, and body mass index (BMI). Individuals with SI ≤ 68 had a poorer overall survival (OS) (hazard ratio [HR]=2.14, 95% CI: 1.71-2.68, p<0.001), and the RCS plot showed that the all-cause mortality risk gradually decreased with the increase in SI. Then, 203 patients with EC were enrolled, of which 76 patients were diagnosed with sarcopenia. There was a linear correlation between SI and skeletal muscle index and prealbumin, indicating that SI was reliable for diagnosing sarcopenia. Patients in the high sarcopenia risk group (Male: SI < 62; Female: SI < 55) showed a higher incidence of complications (OR=3.50, 95% CI: 1.85-6.61, p<0.001) and poorer long-term survival (HR=2.62, 95% CI: 1.02-6.77, p=0.046). CONCLUSION: SI could be used to identify sarcopenia in patients with EC, and it is a useful prognostic factor of postoperative complications and long-term survival.

A Low Cost Fe3O4-Activated Biochar Electrode Sensor by Resource Utilization of Excess Sludge for Detecting Tetrabromobisphenol A.

Owing to its ubiquity in natural water systems and the high toxicity of its accumulation in the human body, it is essential to develop simple and low-cost electrochemical sensors for the determination of 3,3',5,5'-tetrabromobisphenol A (TBBPA). In this work, Fe3O4-activated biochar, which is based on excess sludge, was prepared and characterized using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FTIR) and BET analysis to analyze its basic features. Subsequently, it was used to fabricate an electrochemical sensor for the detection of TBBPA. The electrochemical test results revealed that the Fe3O4-activated biochar film exhibited a larger active surface area, a lower charge transfer resistance and a higher accumulation efficiency toward TBBPA. Consequently, the peak current of TBBPA was significantly enhanced on the surface of the Fe3O4-activated biochar. The TBBPA sensing platform developed using the Fe3O4-activated biochar composite film, with relatively a lower detection limit (3.2 nM) and a wider linear range (5-1000 nM), was successfully utilized to determine TBBPA levels in water samples. In summary, the effective application of Fe3O4-activated biochar provided eco-friendly and sustainable materials for the development of a desirable high-sensitivity sensor for TBBPA detection.

[Characteristics and Risk Assessment of Antibiotic Contamination in Chishui River Basin, Guizhou Province, China].

To preliminarily explore the antibiotic concentration distribution characteristics of Guizhou Chishui River basin surface water and potential ecological risks, we used solid phase extraction liquid chromatography tandem mass spectrometry (SPE-HPLC- MS) to analyze 21 types of antibiotics in surface water samples. Twelve types of antibiotics were detected in the Chishui River basin surface water, and the total concentrations of ofloxacin, sulfadiazine, and trimethoprim ranged from ND-1166.97 ng·L-1, with a detection rate of 100%. On average, the highest concentration of the three types of antibiotics detected were ofloxacin (221.59 ng·L-1), tetracycline (13.18 ng·L-1), and sulfadiazine (4.11 ng·L-1), and the antibiotic concentration distribution showed the following order of characteristics:downstream (359.41 ng·L-1) > midstream(224.59 ng·L-1) > upstream (179.72 ng·L-1). The ecological environment risk assessment results indicated the largest risk for downstream W21, tetracycline, doxycycline, enrofloxacin, norfloxacin, and erythromycin. The risk quotient revealed that lincomycin had a medium-risk level, and ofloxacin had a high-risk level. This shows that antibiotics in the waters of the Chishui River basin may cause certain ecological risks.

Disaggregating Asian American Cigarette and Alternative Tobacco Product Use: Results from the National Health Interview Survey (NHIS) 2006-2018.

INTRODUCTION: Asian Americans suffer high rates of smoking and tobacco-related deaths, varying by ethnic group. Trends of cigarette and alternative tobacco product use among Asian Americans, specifically considering ethnic group, sex, and nativity, are infrequently reported. METHODS: Using National Health Interview Survey (NHIS) data from 2006-2018 and the 2016-2018 alternative tobacco supplement (e-cigarettes, cigars, smokeless tobacco, pipes), we explored cigarette and alternative tobacco product use by Asian ethnic group (Asian Indian (n = 4373), Chinese (n = 4736), Filipino (n = 4912)) in comparison to non-Hispanic Whites (NHWs (n = 275,025)), adjusting for socioeconomic and demographic factors. RESULTS: Among 289,046 adults, 12% of Filipinos were current smokers, twice the prevalence in Asian Indians and Chinese (p < 0.001). The male-female gender difference was fivefold for Chinese (10.3% vs. 2.2%; p < 0.001), eightfold for Asian Indians (8.7% vs. 1.1%; p < 0.001), and twofold for Filipinos (16.8% vs. 9.0%). Moreover, 16.3% of US-born and 10.3% of foreign-born Filipinos were current smokers. Odds of ever using e-cigarettes, cigars, smokeless tobacco, and pipes in comparison to NHWs were lowest for Chinese (ORs 0.6, 0.5, 0.2, and 0.5). DISCUSSION: Filipinos had the highest current smoking rates of Asian ethnic groups. Though more Asian men were current smokers, the high rate of current smoking among Filipinas is concerning. More US-born Filipinos were current smokers than foreign-born, despite rates typically decreasing for US-born Asians. Investigating cultural factors contributing to less frequent use of tobacco products, such as alternative tobacco products among Chinese, may aid campaigns in curbing tobacco usage.

Lack of Sex Disparity in Oral Anticoagulation in Atrial Fibrillation Patients Presenting with Ischemic Stroke in a Rural Population.

Various studies on oral anticoagulants (OAC) use among atrial fibrillation (AF) patients have shown high rates of undertreatment and the presence of sex disparity. This study used the 'Geisinger Neuroscience Ischemic Stroke' (GNSIS) database to examine sex differences in OAC treatment among ischemic stroke patients with the pre-event diagnosis of AF in rural Pennsylvania between 2004 and 2019. We examined sex disparities in OAC undertreatment and associated risks based on age group and ischemic stroke year. A total of 1062 patients were included in the study and 1015 patients (96%) had CHA2DS2-VASc score ≥ 2, of which 549 (54.1%) were women. Undertreatment rates were not statistically significant between men and women in the overall cohort (50.0% vs. 54.5%, p = 0.18), and male sex was not found to be a significant factor in undertreatment (OR 0.82, 95% CI 0.62-1.09, p = 0.17). The result persisted even when patients were divided into four age groups and two groups based on the study time period. The undertreatment rates in both sex groups remained consistent following the introduction of novel oral anticoagulants. In conclusion, there was no evidence of sex disparity with respect to OAC treatment, even after stratifying the cohort by age and ischemic stroke year.

Ensemble Learning Based on Policy Optimization Neural Networks for Capability Assessment.

Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability assessment and index sensitivity. Aiming at the problem of overfitting and parameter optimization in neural network learning, the paper proposes an improved machine learning algorithm-the Ensemble Learning Based on Policy Optimization Neural Networks (ELPONN) with the policy optimization and ensemble learning. This algorithm presents an optimized neural network learning algorithm through different strategies evolution, and builds an ensemble learning model of multi-intelligent algorithms to assess the capability and analyze the sensitivity of the indexes. Through the assessment of capabilities, the algorithm effectively avoids parameter optimization from entering the minimum point in performance to improve the accuracy of equipment capability assessment, which is significantly better than previous neural network assessment methods. The experimental results show that the mean relative error is 4.10%, which is better than BP, GABP, and early stopping. The ELPONN algorithm has better accuracy and stability performance, and meets the requirements of capability assessment.