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PurposesTo evaluate the capability of PET/CT images for differentiating the histologic subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from radiomics-based machine learning/deep learning algorithms.MethodsIn this study, 867 patients with adenocarcinoma (ADC) and 552 patients with squamous cell carcinoma (SCC) were retrospectively analysed. A stratified random sample of 283 patients (20%) was used as the testing set (173 ADC and 110 SCC); the remaining data were used as the training set. A total of 688 features were extracted from each outlined tumour region. Ten feature selection techniques, ten machine learning (ML) models and the VGG16 deep learning (DL) algorithm were evaluated to construct an optimal classification model for the differential diagnosis of ADC and SCC. Tenfold cross-validation and grid search technique were employed to evaluate and optimize the model hyperparameters on the training dataset. The area under the receiver operating characteristic curve (AUROC), accuracy, precision, sensitivity and specificity was used to evaluate the performance of the models on the test dataset.ResultsFifty top-ranked subset features were selected by each feature selection technique for classification. The linear discriminant analysis (LDA) (AUROC, 0.863; accuracy, 0.794) and support vector machine (SVM) (AUROC, 0.863; accuracy, 0.792) classifiers, both of which coupled with the ℓ2,1NR feature selection method, achieved optimal performance. The random forest (RF) classifier (AUROC, 0.824; accuracy, 0.775) and ℓ2,1NR feature selection method (AUROC, 0.815; accuracy, 0.764) showed excellent average performance among the classifiers and feature selection methods employed in our study, respectively. Furthermore, the VGG16 DL algorithm (AUROC, 0.903; accuracy, 0.841) outperformed all conventional machine learning methods in combination with radiomics.ConclusionEmploying radiomic machine learning/deep learning algorithms could help radiologists to differentiate the histologic subtypes of NSCLC via PET/CT images.

Background Recent studies have suggested that triglyceride-glucose (TyG) index is an independent predictor of cardiovascular disease (CVD). However, the impact of long-term visit-to-visit variability in TyG index on the risk of CVD is not known. We aimed to investigate the longitudinal association between baseline and mean TyG index as well as TyG index variability and incident CVD in a Chinese population. Methods We included 49,579 participants without previous history of CVD in the Kailuan study who underwent three health examinations (2006, 2008, and 2010) and were followed up for clinical events until 2019. TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. We measured TyG index variability as the SD of the residuals obtained from a linear regression on the three TyG index measurements for each individual. Multivariate-adjusted Cox models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) with incident CVD. Results During a median follow-up time of 9.0 years, 2404 developed CVD. The highest tertile (T3) of baseline and mean TyG index were each associated with higher CVD incidence as compared with the lowest tertile (T1): aHR, 1.25; 95% CI 1.11–1.42; and aHR 1.40; 95% CI 1.24–1.58, respectively. Tertile 3 of TyG index variability was associated with increased CVD incidence compared to T1 group (aHR, 1.12; 95% CI 1.01–1.24). Similar findings were observed in a series of sensitivity analyses. Conclusion Higher TyG index level and greater TyGindex variability were each independently associated with a higher incidence of CVD.

Heavy fine particulate matter (PM2.5) air pollution occurs frequently in China. However, epidemiological research on the association between short-term exposure to PM2.5 pollution and respiratory disease morbidity is still limited. This study aimed to explore the association between PM2.5 pollution and hospital emergency room visits (ERV) for total and cause-specific respiratory diseases in urban areas in Beijing. Daily counts of respiratory ERV from Jan 1 to Dec 31, 2013, were obtained from ten general hospitals located in urban areas in Beijing. Concurrently, data on PM2.5 were collected from the Beijing Environmental Protection Bureau, including 17 ambient air quality monitoring stations. A generalized-additive model was used to explore the respiratory effects of PM2.5, after controlling for confounding variables. Subgroup analyses were also conducted by age and gender. A total of 92,464 respiratory emergency visits were recorded during the study period. The mean daily PM2.5 concentration was 102.1±73.6 μg/m3. Every 10 μg/m3 increase in PM2.5 concentration at lag0 was associated with an increase in ERV, as follows: 0.23% for total respiratory disease (95% confidence interval [CI]: 0.11%-0.34%), 0.19% for upper respiratory tract infection (URTI) (95%CI: 0.04%-0.35%), 0.34% for lower respiratory tract infection (LRTI) (95%CI: 0.14%-0.53%) and 1.46% for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) (95%CI: 0.13%-2.79%). The strongest association was identified between AECOPD and PM2.5 concentration at lag0-3 (3.15%, 95%CI: 1.39%-4.91%). The estimated effects were robust after adjusting for SO2, O3, CO and NO2. Females and people 60 years of age and older demonstrated a higher risk of respiratory disease after PM2.5 exposure. PM2.5 was significantly associated with respiratory ERV, particularly for URTI, LRTI and AECOPD in Beijing. The susceptibility to PM2.5 pollution varied by gender and age.

Background Impaired sensitivity to thyroid hormones is a newly proposed clinical entity associated with hyperuricemia in the subclinical hypothyroid population. However, it is unknown whether the association exists in the euthyroid population. This study aimed to explore the association of impaired sensitivity to thyroid hormones (assessed by the thyroid feedback quantile-based index [TFQI], parametric thyroid feedback quantile-based index [PTFQI], thyrotrophic thyroxine resistance index [TT4RI] and thyroid-stimulating hormone index [TSHI]) with hyperuricemia and quantify the mediating effect of body mass index BMI in the euthyroid population. Methods This cross-sectional study enrolled Chinese adults aged ≥ 20 years who participated in the Beijing Health Management Cohort (2008–2019). Adjusted logistic regression models were used to explore the association between indices of sensitivity to thyroid hormones and hyperuricemia. Odds ratios [OR] and absolute risk differences [ARD] were calculated. Mediation analyses were performed to estimate direct and indirect effects through BMI. Results Of 30,857 participants, 19,031 (61.7%) were male; the mean (SD) age was 47.3 (13.3) years; and 6,515 (21.1%) had hyperuricemia. After adjusting for confounders, individuals in the highest group of thyroid hormone sensitivity indices were associated with an increased prevalence of hyperuricemia compared with the lowest group (TFQI: OR = 1.18, 95% CI 1.04–1.35; PTFQI: OR = 1.20, 95% CI 1.05–1.36; TT4RI: OR = 1.17, 95% CI 1.08–1.27; TSHI: OR = 1.12, 95% CI 1.04–1.21). BMI significantly mediated 32.35%, 32.29%, 39.63%, and 37.68% of the associations of TFQI, PTFQI, TT4RI and TSHI with hyperuricemia, respectively. Conclusions Our research revealed that BMI mediated the association between impaired sensitivity to thyroid hormones and hyperuricemia in the euthyroid population. These findings could provide useful evidence for understanding the interaction between impaired sensitivity to thyroid hormone and hyperuricemia in euthyroid individuals and suggest the clinical implications of weight control in terms of impaired thyroid hormones sensitivity. Keypoints Quetions To what extent is impaired sensitivity to thyroid hormones associated with hyperuricemia through body mass index (BMI) in the euthyroid population? Findings In this cross-sectional study of 30,857 euthyroid adults, impaired sensitivity to thyroid hormones was independently associated with an increased prevalence of hyperuricemia. BMI mediated 32.3–39.6% of the association between impaired sensitivity to thyroid hormones and hyperuricemia. Meaning This study revealed that BMI mediated the association between impaired sensitivity to thyroid hormones and hyperuricemia in the euthyroid population, suggesting the potential clinical benefit of weight control in maintaining metabolic health among individuals with impaired thyroid hormones sensitivity.

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person.This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19.

Background Cross-sectional studies have reported that insulin resistance (IR) is associated with arterial stiffness. However, the relationship between IR and arterial stiffness progression remains unclear. This study aims to evaluate the association of triglyceride glucose (TyG) index and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio with arterial stiffness progression in a non-normotensive population. Methods A total of 1895 prehypertensive (systolic pressure 120–139 mmHg or diastolic pressure 80–90 mmHg) or hypertensive (systolic pressure ≥ 140 mmHg or diastolic pressure ≥ 90 mmHg or using antihypertensive medication) participants were enrolled in 2013 and 2014, and followed until December 31, 2019. Arterial stiffness progression was measured by brachial-ankle pulse wave velocity (baPWV) change (absolute difference between baseline and last follow-up), baPWV change rate (change divided by following years), and baPWV slope (regression slope between examination year and baPWV). Results During a median follow-up of 4.71 years, we observed an increasing trend of baPWV in the population. There were linear and positive associations of the TyG index and TG/HDL-C ratio with the three baPWV parameters. The difference (95% CI) in baPWV change (cm/s) comparing participants in the highest quartile versus the lowest of TyG index and TG/HDL-C ratio were 129.5 (58.7–200.0) and 133.4 (52.0–214.9), respectively. Similarly, the evaluated baPWV change rates (cm/s/year) were 37.6 (15.3–60.0) and 43.5 (17.8–69.2), while the slopes of baPWV were 30.6 (9.3–51.8) and 33.5 (9.0–58.0). The observed association was stronger in the hypertensive population. Conclusion Our study indicates that the TyG index and TG/HDL-C ratio are significantly associated with arterial stiffness progression in hypertensive population, not in prehypertensive population.

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM2.5 and meteorological factors. Daily and hourly PM2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM). Annual mean and median of PM2.5 concentrations were 88.07 μg/m3 and 71.00 μg/m3, respectively, from August 2013 to July 2014. PM2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM2.5 showed a long-term trend of fluctuations, with 2-6 peaks each month. PM2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM2.5 concentration using the GAMM model (R2 = 0.59, AIC = 7373.84). PM2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM2.5.

Background Concerns exist over a possible worsening of disparities in health status and health care access across racial/ethnic and income groups during the COVID-19 pandemic. We aimed to characterize trends in racial/ethnic and income differences in self-reported measures of health status and health care access among US adults. Methods This serial cross-sectional nationally representative study included adults (age ≥ 18 years) participating in the National Health Interview Survey (NHIS) from 2019 to 2022. Self-reported health status (poor or fair health status, functional limitation, clinician-diagnosed depression or anxiety disorders) and health care access and affordability were collected. Results Our analysis included 107,230 adults (mean [SE] age, 48.1 [0.1] years, 51.6% women), of whom 6.1% were Asian, 12.1% were Black, 17.3% were Latino/Hispanic, and 64.5% were White. Black individuals with low income had the highest prevalence of poor or fair health status (30.9% [95% CI, 27.8%–34.3%] in 2019 and 28.4% [95% CI, 25.1% to 32.0%] in 2022), and these racial/ethnic gaps did not change significantly, irrespective of income levels. The prevalence of clinician-diagnosed depression or anxiety disorders increased from 2019 to 2022 for all racial/ethnic groups, especially for Whites (from 32.6% [95% CI, 30.8%–34.4%] to 38.2% [95% CI, 36.4% to 40.1%], P  < 0.001). There was no significant change in functional limitations during the pandemic. Latino/Hispanic individuals with low income had the highest estimated prevalence of limited health care access from 2019 to 2022. Health insurance access and affordability significantly improved for White individuals with low income from 2019 to 2022 ( P  < 0.001), but not for other racial/ethnic groups. Racial/ethnic gaps in health care access and affordability did not change significantly, irrespective of income levels. Conclusions In a serial cross-sectional survey study of US adults during the COVID-19 pandemic, prevalence of clinician-diagnosed depression or anxiety disorders significantly increased. Racial and ethnic differences in health status and health care access either persisted or widened over time.

Background Associations between the frequency of social and intellectual activities and cognitive trajectories are understudied in Chinese middle-aged and older adults. We aimed to examine this association in a nationally representative longitudinal study. Methods The China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative sample of Chinese middle-aged and older participants. The frequency of social and intellectual activities was measured at baseline. Interview-based cognitive assessments of orientation and attention, episodic memory, and visuospatial skills and the calculation of combined global scores were assessed every 2 years from 2011 to 2016. Cognitive aging trajectories over time were analyzed using group-based trajectory modeling, and the associations of the trajectory memberships with social and intellectual activities were analyzed using multinomial logistic regression. Odds ratios (OR) and 95% confidence intervals (CI) were reported. Results Among 8204 participants aged 50–75 years at baseline, trajectory analysis identified three longitudinal patterns of cognitive function based on the global cognitive scores: “persistently low trajectory” ( n  = 1550, 18.9%), “persistently moderate trajectory” ( n  = 3194, 38.9%), and “persistently high trajectory” ( n  = 3460, 42.2%). After adjustment for sociodemographic variables, lifestyles, geriatric symptoms, and health conditions, more frequent intellectual activities (OR 0.54, 95% CI 0.38–0.77) and social activities (OR 0.79, 95% CI 0.65–0.95) were both associated with a lower likelihood of being in the “persistently low trajectory” for global cognitive function. Conclusions These findings suggested that more frequent social and intellectual activities were associated with more favorable cognitive aging trajectories.

Due to advances in telemedicine, mobile medical care, wearable health monitoring, and electronic skin, great efforts have been directed to non-invasive monitoring and treatment of disease. These processes generally involve disease detection from interstitial fluid (ISF) instead of blood, and transdermal drug delivery. However, the quantitative extraction of ISF and the level of drug absorption are greatly affected by the individual’s skin permeability, which is closely related to the properties of the stratum corneum (SC). Therefore, measurement of SC impedance has been proposed as an appropriate way for assessing individual skin differences. In order to figure out the current status and research direction of human SC impedance detection, investigations regarding skin impedance measurement have been reviewed in this paper. Future directions are concluded after a review of impedance models, electrodes, measurement methods and systems, and their applications in treatment. It is believed that a well-matched skin impedance model and measurement method will be established for clinical and point-of care applications in the near future.