Preparation of molecularly imprinted polymer for the specific adsorption and selective extraction of alkylresorcinols from whole wheat flour.

Alkylresorcinols are important biomarkers for evaluating whole wheat foods. However, their structures encompass a broad spectrum of homologs, making isolating and analyzing individual alkylresorcinol notably challenging. Herein, we synthesized highly selective molecularly imprinted polymers (MIPs) utilizing a facile and cost-effective precipitation polymerization method and 5-heneicosylresorcinol (ARC21:0) as the template molecule. Various crucial preparation parameters were systematically optimized, such as different porogens, functional monomers, imprinting ratios, and polymerization time. The polymers were characterized through scanning electron microscopy and Fourier transform infrared spectroscopy, and their adsorption performances were thoroughly evaluated. MIPs exhibited a notably enhanced adsorption capacity compared with that of non-imprinted polymers, reaching an optimal adsorption amount of 71.75 mg·mL-1 and imprinting factor of 2.02. Altogether, the synthesized MIPs showed superior affinity and selectivity for ARC21:0, as confirmed by their selective extraction, suggesting their potential applications in the analysis, separation, and monitoring of ARC21:0 in whole wheat foods.

Molecularly Imprinted Electrochemical Sensor Based on α-Cyclodextrin Inclusion Complex and MXene Modification for Highly Sensitive and Selective Detection of Alkylresorcinols in Whole Wheat Foods.

Authenticating whole wheat foods poses a significant challenge for both the grain industry and consumers. Alkylresorcinols (ARs), serving as biomarkers of whole wheat, play a crucial role in assessing the authenticity of whole wheat foods. Herein, we introduce a novel molecularly imprinted electrochemical sensor with modifications involving a molecularly imprinted polymer (MIP) and MXene nanosheets, enabling highly sensitive and selective detection of ARs. Notably, we specifically chose 5-heneicosylresorcinol (AR21), the predominant homologue in whole wheat, as the template molecule. α-Cyclodextrin and acrylamide served as dual functional monomers, establishing a robust multiple interaction between the MIP and AR21. As a result, the sensor exhibited a wide linear range of 0.005 to 100 µg·mL-1 and a low detection limit of 2.52 ng·mL-1, demonstrating exceptional selectivity and stability. When applied to commercial whole wheat foods, the assay achieved satisfactory recoveries and accuracy, strongly validating the practicality and effectiveness of this analytical technique.

Association between metabolic syndrome severity score and cardiovascular disease: results from a longitudinal cohort study on Chinese adults.

Objective: This study aimed to quantify the severity of metabolic syndrome(MetS) and investigate its association with cardiovascular disease(CVD) risk on Chinese adults. Methods: 13,500 participants from the Zhejiang Adult Chronic Disease Study were followed up between 2010 and 2021. A continuous MetS severity score derived from the five components of MetS was used to quantify MetS severity, and the association between MetS severity and the risk of incident CVD was assessed using Cox proportional hazard and restricted cubic spline regression. Results: Both the presence and severity of MetS were strongly associated with CVD risk. MetS was related to an increased risk of CVD (hazard ratio(HR):1.700, 95% confidence interval(CI): 1.380-2.094). Compared with the hazard ratio for CVD in the lowest quartile of the MetS severity score, that in the second, third, and highest quartiles were 1.812 (1.329-2.470), 1.746 (1.265-2.410), and 2.817 (2.015-3.938), respectively. A linear and positive dose-response relationship was observed between the MetS severity and CVD risk (P for non-linearity = 0.437). Similar results were found in various sensitivity analyses. Conclusion: The MetS severity score was significantly associated with CVD risk. Assessing MetS severity and further ensuring intervention measures according to the different severities of MetS may be more useful in preventing CVD.

A Review of deep learning methods for denoising of medical low-dose CT images.

To prevent patients from being exposed to excess of radiation in CT imaging, the most common solution is to decrease the radiation dose by reducing the X-ray, and thus the quality of the resulting low-dose CT images (LDCT) is degraded, as evidenced by more noise and streaking artifacts. Therefore, it is important to maintain high quality CT image while effectively reducing radiation dose. In recent years, with the rapid development of deep learning technology, deep learning-based LDCT denoising methods have become quite popular because of their data-driven and high-performance features to achieve excellent denoising results. However, to our knowledge, no relevant article has so far comprehensively introduced and reviewed advanced deep learning denoising methods such as Transformer structures in LDCT denoising tasks. Therefore, based on the literatures related to LDCT image denoising published from year 2016-2023, and in particular from 2020 to 2023, this study presents a systematic survey of current situation, and challenges and future research directions in LDCT image denoising field. Four types of denoising networks are classified according to the network structure: CNN-based, Encoder-Decoder-based, GAN-based, and Transformer-based denoising networks, and each type of denoising network is described and summarized from the perspectives of structural features and denoising performances. Representative deep-learning denoising methods for LDCT are experimentally compared and analyzed. The study results show that CNN-based denoising methods capture image details efficiently through multi-level convolution operation, demonstrating superior denoising effects and adaptivity. Encoder-decoder networks with MSE loss, achieve outstanding results in objective metrics. GANs based methods, employing innovative generators and discriminators, obtain denoised images that exhibit perceptually a closeness to NDCT. Transformer-based methods have potential for improving denoising performances due to their powerful capability in capturing global information. Challenges and opportunities for deep learning based LDCT denoising are analyzed, and future directions are also presented.

Ambient PM2.5 and cardiopulmonary mortality in the oldest-old people in China: A national time-stratified case-crossover study.

BACKGROUND: Evidence on the associations of fine particulate matter (PM2.5) with cardiopulmonary mortality in the oldest-old (aged 80+ years) people remains limited. METHODS: We conducted a time-stratified case-crossover study of 1,475,459 deaths from cardiopulmonary diseases in China to estimate the associations between short-term exposure to ambient PM2.5 and cardiopulmonary mortality among the oldest-old people. FINDINGS: Each 10 µg/m3 increase in PM2.5 concentration (6-day moving average [lag05]) was associated with higher mortality from cardiopulmonary diseases (excess risks [ERs] = 1.69%, 95% confidence interval [CI]: 1.54%, 1.84%), cardiovascular diseases (ER = 1.72%, 95% CI: 1.54%, 1.90%), and respiratory diseases (ER = 1.62%, 95% CI: 1.33%, 1.91%). Compared to the other groups, females (ER = 1.94%, 95% CI: 1.73%, 2.15%) (p for difference test = 0.043) and those aged 95-99 years (ER = 2.31%, 95% CI: 1.61%, 3.02%) (aged 80-85 years old was the reference, p for difference test = 0.770) presented greater mortality risks. We found 14 specific cardiopulmonary causes associated with PM2.5, out of which emphysema (ER = 3.20%, 95% CI: 1.57%, 4.86%) had the largest association. Out of the total deaths, 6.27% (attributable fraction [AF], 95% CI: 5.72%, 6.82%) were ascribed to short-term PM2.5 exposure. CONCLUSIONS: This study provides evidence of PM2.5-induced cardiopulmonary mortality and calls for targeted prevention actions for the oldest-old people. FUNDING: This work was supported by the National Key Research and Development Program of China, the National Natural Science Foundation of China, the Foreign Expert Program of the Ministry of Science and Technology, the Natural Science Foundation of Guangdong, China, and the Science and Technology Program of Guangzhou.

Development and evaluation of a risk assessment tool for the personalized screening of breast cancer in Chinese populations: A prospective cohort study.

INTRODUCTION: Breast cancer is a significant contributor to female mortality, exerting a public health burden worldwide, especially in China, where risk-prediction models with good discriminating accuracy for breast cancer are still scarce. METHODS: A multicenter screening cohort study was conducted as part of the Cancer Screening Program in Urban China. Dwellers aged 40-74 years were recruited between 2014 and 2019 and prospectively followed up until June 30, 2021. The entire data set was divided by year of enrollment to develop a prediction model and validate it internally. Multivariate Cox regression was used to ascertain predictors and develop a risk-prediction model. Model performance at 1, 3, and 5 years was evaluated using the area under the curve, nomogram, and calibration curves and subsequently validated internally. The prediction model incorporates selected factors that are assigned appropriate weights to establish a risk-scoring algorithm. Guided by the risk score, participants were categorized into low-, medium-, and high-risk groups for breast cancer. The cutoff values were chosen using X-tile plots. Sensitivity analysis was conducted by categorizing breast cancer risk into the low- and high-risk groups. A decision curve analysis was used to assess the clinical utility of the model. RESULTS: Of the 70,520 women enrolled, 447 were diagnosed with breast cancer (median follow-up, 6.43 [interquartile range, 3.99-7.12] years). The final prediction model included age and education level (high, hazard ratio [HR], 2.01 [95% CI, 1.31-3.09]), menopausal age (≥50 years, 1.34 [1.03-1.75]), previous benign breast disease (1.42 [1.09-1.83]), and reproductive surgery (1.28 [0.97-1.69]). The 1-year area under the curve was 0.607 in the development set and 0.643 in the validation set. Moderate predictive discrimination and satisfactory calibration were observed for the validation set. The risk predictions demonstrated statistically significant differences between the low-, medium-, and high-risk groups (p < .001). Compared with the low-risk group, women in the high- and medium-risk groups posed a 2.17-fold and 1.62-fold elevated risk of breast cancer, respectively. Similar results were obtained in the sensitivity analyses. A web-based calculator was developed to estimate risk stratification for women. CONCLUSIONS: This study developed and internally validated a risk-adapted and user-friendly risk-prediction model by incorporating easily accessible variables and female factors. The personalized model demonstrated reliable calibration and moderate discriminative ability. Risk-stratified screening strategies contribute to precisely distinguishing high-risk individuals from asymptomatic individuals and prioritizing breast cancer screening. PLAIN LANGUAGE SUMMARY: Breast cancer remains a burden in China. To enhance breast cancer screening, we need to incorporate population stratification in screening. Accurate risk-prediction models for breast cancer remain scarce in China. We established and validated a risk-adapted and user-friendly risk-prediction model by incorporating routinely available variables along with female factors. Using this risk-stratified model helps accurately identify high-risk individuals, which is of significant importance when considering integrating individual risk assessments into mass screening programs for breast cancer. Current clinical breast cancer screening lacks a constructive clinical pathway and guiding recommendations. Our findings can better guide clinicians and health care providers.

Associations between experience of stressful life events and cancer prevalence in China: results from the China Kadoorie Biobank study.

BACKGROUND: Studies examining the relationships of stressful life events and cancer yielded inconsistent findings, while relevant evidence in mainland China is scarce. The current study sought to determine whether experience of stressful life events was associated with cancer prevalence in Chinese population. METHODS: We used cross-sectional data from the China Kadoorie Biobank study which that recruited 0.5 million Chinese adults aged 30 to 79 from 2004 to 2008. Logistic regression models were used to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for cancer associated with stressful life events reported at baseline. RESULTS: Among the 461,696 participants included in this analysis, 2,122 (0.46%) had self-reported cancer with the mean (SD) age was 57.12 (9.71) years. Compared to those without any stressful life event, participants who experienced 1 and 2 or more events had significantly higher odds of cancer, with the ORs of 1.80 (95% CI: 1.58-2.05) and 3.05 (2.18-4.28). For categories of work-, family-, and personal-related events, the OR of cancer was 1.48 (1.07-2.05), 2.06 (1.80-2.35), and 1.65 (1.17-2.33), respectively. Regarding the specific stressful life events, loss of income/living on debt, major conflict within family, death/major illness of other close family member, and major injury/traffic accident were significantly associated with increased odds of cancer, with the ORs of 2.64 (1.81-3.86), 1.73 (1.20-2.50), 2.36 (2.05-2.72), and 2.11 (1.43-3.13). CONCLUSION: Our findings suggested that experiences of cumulative and specific stressful life events were significantly associated with increased cancer prevalence in Chinese population.

Analysis of the Risk Factors for Mechanical Allodynia in Herpetic Neuralgia: A Retrospective Cross-Sectional Study.

Purpose: Mechanical allodynia is reportedly common during herpetic neuralgia. The purpose of this study was to establish a risk prediction model to predict the individual risk of allodynia in herpetic neuralgia. Methods: Three hundred and eighty-six patients with trunk herpetic neuralgia were divided into two regions, T2-5 and T6-11. The causality between allodynia and other factors was analyzed by a binary logistic regression model. Results: 42.2% of subjects had allodynia, 137 suffered from dynamic allodynia, and 110 with dynamic allodynia experienced local sweating. The following 5 items as predictors determined this model: local sweating (Odd Ratio = 27.57, P<0.001), lesion location (Odd Ratio=2.46, P =0.017), pain intensity (Odd Ratio=1.38, P =0.020), pain duration (Odd Ratio=0.94, P =0.006), and local scars (Odd Ratio=0.07, P<0.001). The presence and development of allodynia are associated with local sweating. The positive proportion of the Iodine-starch test between the T2-5 (50.0%) with the T6-11 (23.7%) had a statistically significant difference (χ2=5.36, P=0.021). 29.5% of patients at the T2-6 had obvious sweating, which was different from only sticky feelings at the T6-11 (70.5%, χ2=10.88, P=0.001). 19.2% of patients with residual scars and allodynia was significantly lower than 48.5% of patients without allodynia (χ2=15.28, P<0.001). Conclusion: This analysis suggests that local sweating is a concomitant symptom in dynamic allodynia, which imply the sympathetic nerves innervating the sweat glands of the skin were also involved during herpetic neuralgia. This may assist in the evaluation of dynamic allodynia and prove the role of sympathetic nerve intervention for herpetic neuralgia.

Health and wellbeing among the empty nest and non-empty nest elderly in China-Results from a national cross-sectional study.

BACKGROUND: The number of empty nest elderly in China has gradually increased in recent years. There is growing concern about the physical and mental health of this population as empty nest elderly are commonly at the risk of compromising health, home safety and quality of life. This study reported the health and well-being of empty nest elderly with regards to their health status, depression and satisfaction, lifestyle as compared to non-empty nest elderly in China. METHODS: Data was collected from the 2018 follow-up interviews of China Health and Retirement Longitudinal Survey. We included 4,630 empty nest elderly and 6,188 non-empty nest elderly. Chi-square Test and Logistic Regression were used to compare the differences between these two groups. RESULTS: As compared to the non-empty nest elderly, there was higher proportion of empty nest elderly who suffered from dyslipidemia, diabetes, chronic lung diseases, heart attack (27.0% vs. 25.0%; 16.6% vs. 15.1%; 19.4% vs. 16.4%; 26.3% vs. 23.4%, P < 0.05). The empty nest elderly had higher proportion of participants who drank more than once a month (25.3% vs. 23.9%, P < 0.05), who felt satisfied with their marriage (71.6% vs. 66.2%, P < 0.001), who were satisfied with their children's relationship (85.2% vs. 83.2%, P < 0.001). However, these significances disappeared in the Logistic Regression analysis (P > 0.05). CONCLUSION: Our study showed that significant between-group difference was found between empty nest elderly and non-empty nest elderly in their health and wellbeing. However, disappearance of such difference in the multivariable analysis may indicate improved health and wellbeing among the empty nest elderly. Even though our study still suggested the importance of improving the health, lifestyles and family dynamics of the elderly and promoting the integration of health and social care for the elderly, especially among the empty nest elderly.

High-throughput sequencing reveals Jatrorrhizine inhibits colorectal cancer growth by ferroptosis-related genes.

BACKGROUND: Colorectal cancer is a malignant tumor that poses a serious threat to human health. The main objective of this study is to investigate the mechanism by which Jatrorrhizine (JAT), a root extract from Stephania Epigaea Lo, exerts its anticancer effects in colorectal cancer. METHODS: We initially assessed the inhibitory properties of JAT on SW480 cells using MTT and cell scratch assays. Flow cytometry was employed to detect cell apoptosis. Differentially expressed genes were identified through high-throughput sequencing, and they were subjected to functional enrichment and signaling pathway analysis and PPI network construction. RT-qPCR was used to evaluate gene expression and identify critical differentially expressed genes. Finally, the function and role of differentially expressed genes produced by JAT-treated SW480 cells in colorectal cancer will be further analyzed using the TCGA database. RESULTS: Our study demonstrated that JAT exhibits inhibitory effects on SW480 cells at concentrations of 12.5µM, 25µM, 50µM, and 75µM without inducing cell apoptosis. Through high-throughput sequencing, we identified 244 differentially expressed genes. KEGG and GO analysis of high-throughput sequencing results showed that differentially expressed genes were significantly enriched in MAPK, Wnt, and P53 signaling pathways. Notably, JAT significantly altered the expression of genes associated with ferroptosis. Subsequent RT-qPCR showed that the expression of ferroptosis genes SLC2A3 and ASNS was significantly lower in JAT-treated SW480 cells than in the control group. Analysis by TCGA data also showed that ferroptosis genes SLC2A3 and ASNS were significantly highly expressed in COAD. The prognosis of SLC2A3 was significantly worse in COAD compared to the normal group. SLC2A3 may be a core target of JAT for the treatment of COAD. CONCLUSIONS: JAT can inhibit COAD growth by ferroptosis-related genes. And it is a potential natural substance for the treatment of COAD.

The association of heatwave with drowning mortality in five provinces of China.

Drowning is a serious public health problem in the world. Several studies have found that ambient temperature is associated with drowning, but few have investigated the effect of heatwave on drowning. This study aimed to explore the associations between heatwave and drowning mortality, and further estimate the mortality burden of drowning attributed to heatwave in China. Drowning mortality data were collected in 71 prefectures in China during 2013-2018 from provincial vital register system. Meteorological data at the same period were collected from European Centre for Medium-Range Weather Forecasts (ECMWF). A distributed lag non-linear model (DLNM) was first to explore the association between heatwave and drowning mortality in each prefecture. Secondly, the prefecture-specific associations were pooled using meta-analysis. Finally, attributable fractions (AFs) of drowning deaths caused by heatwave were estimated. Compared to normal day, the mortality risk of drowning significantly increased during heatwave (RR = 1.20, 95%CI: 1.18-1.23). Higher risks were observed in males (RR = 1.23, 95%CI: 1.20-1.27) than females (RR = 1.18, 95%CI: 1.13-1.23), in children aged 5-14 years old (RR = 1.24, 95%CI: 1.15-1.33) than other age groups, in urban city (RR = 1.32, 95%CI: 1.28-1.36) than rural area (RR = 1.09, 95%CI: 1.07-1.12) and in Jilin province (RR = 2.85, 95%CI: 1.61-5.06) than other provinces. The AF of drowning deaths due to heatwave was 11.4 % (95%CI: 10.0 %-12.9 %) during heatwave and 1.0 % (95%CI: 0.9 %-1.1 %) during study period, respectively. Moreover, the AFs during study period were higher for male (1.2 %, 95%CI: 1.0 %-1.3 %), children 5-14 years (1.1 %, 95%CI: 0.7 %-1.6 %), urban city (1.6 %, 95%CI: 1.4 %-1.8 %) than their correspondents. These differences were also observed in AFs during heatwave. We found that heatwave may significantly increase the mortality risk of drowning mortality, and its mortality burden attributable to heatwave was noteworthy. Targeted intervention should be carried out to decrease drowning mortality during heatwave.

Association of high miR-27a, miR-206, and miR-214 expression with poor patient prognosis and increased chemoresistance in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype, associated with early metastasis and recurrence as well as poor patient outcome. TNBC does not or weakly respond to hormonal or HER2-targeted therapies. Therefore, there is a strong need to identify other potential molecular targets for TNBC therapy. Micro-RNAs play important roles in the post-transcriptional regulation of gene expression. Thus, micro-RNAs, displaying an association between elevated expression and poor patient prognosis, may represent candidates for such novel tumor targets. In the present study, we evaluated the prognostic impact of miR-27a, miR-206, and miR-214 in TNBC via qPCR in tumor tissue (n=146). In univariate Cox regression analysis, elevated expression of all three analyzed micro-RNAs was significantly associated with shortened disease-free survival (hazard ratio [HR] for miR-27a: 1.85, P=0.038; miR-206: 1.83, P=0.041; miR-214: 2.06, P=0.012). In multivariable analysis, the micro-RNAs remained independent biomarkers for disease-free survival (HR for miR-27a: 1.99, P=0.033; miR-206: 2.14, P=0.018; miR-214: 2.01, P=0.026). Furthermore, our results suggest that elevated levels of these micro-RNAs are linked to enhanced resistance to chemotherapy. Based on the association of high expression levels with shortened patient survival and increased chemoresistance, miR-27a, miR-206, and miR-214 may represent novel molecular targets for TNBC.

The Combined Effects of Short-Term Exposure to Multiple Meteorological Factors on Unintentional Drowning Mortality: Large Case-Crossover Study.

BACKGROUND: Drowning is a serious public health problem worldwide. Previous epidemiological studies on the association between meteorological factors and drowning mainly focused on individual weather factors, and the combined effect of mixed exposure to multiple meteorological factors on drowning is unclear. OBJECTIVE: We aimed to investigate the combined effects of multiple meteorological factors on unintentional drowning mortality in China and to identify the important meteorological factors contributing to drowning mortality. METHODS: Unintentional drowning death data (based on International Classification of Diseases, 10th Edition, codes W65-74) from January 1, 2013, to December 31, 2018, were collected from the Disease Surveillance Points System for Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces, China. Daily meteorological data, including daily mean temperature, relative humidity, sunlight duration, and rainfall in the same period were obtained from the Chinese Academy of Meteorological Science Data Center. We constructed a time-stratified case-crossover design and applied a generalized additive model to examine the effect of individual weather factors on drowning mortality, and then used quantile g-computation to estimate the joint effect of the mixed exposure to meteorological factors. RESULTS: A total of 46,179 drowning deaths were reported in the 5 provinces in China from 2013 to 2018. In an effect analysis of individual exposure, we observed a positive effect for sunlight duration, a negative effect for relative humidity, and U-shaped associations for temperature and rainfall with drowning mortality. In a joint effect analysis of the above 4 meteorological factors, a 2.99% (95% CI 0.26%-5.80%) increase in drowning mortality was observed per quartile rise in exposure mixture. For the total population, sunlight duration was the most important weather factor for drowning mortality, with a 93.1% positive contribution to the overall effects, while rainfall was mainly a negative factor for drowning deaths (90.5%) and temperature and relative humidity contributed 6.9% and -9.5% to the overall effects, respectively. CONCLUSIONS: This study found that mixed exposure to temperature, relative humidity, sunlight duration, and rainfall was positively associated with drowning mortality and that sunlight duration, rather than temperature, may be the most important meteorological factor for drowning mortality. These findings imply that it is necessary to incorporate sunshine hours and temperature into early warning systems for drowning prevention in the future.

A novel denoising method for low-dose CT images based on transformer and CNN.

Computed Tomography (CT) has become a mainstream imaging tool in medical diagnosis. However, the issue of increased cancer risk due to radiation exposure has raised public concern. Low-dose computed tomography (LDCT) technique is a CT scan with lower radiation dose than conventional scans. LDCT is used to make a diagnosis of lesions with the smallest dose of x-rays, and is currently mainly used for early lung cancer screening. However, LDCT has severe image noise, and these noises affect adversely the quality of medical images and thus the diagnosis of lesions. In this paper, we propose a novel LDCT image denoising method based on transformer combined with convolutional neural network (CNN). The encoder part of the network is based on CNN, which is mainly used to extract the image detail information. In the decoder part, we propose a dual-path transformer block (DPTB), which extracts the features of input of the skip connection and the features of input of the previous level through two paths respectively. DPTB can better restore the detail and structure information of the denoised image. In order to pay more attention to the key regions of the feature images extracted at the shallow level of the network, we also propose a multi-feature spatial attention block (MSAB) in the skip connection part. Experimental studies are conducted, and comparisons with the state-of-the-art networks are made, and the results demonstrate that the developed method can effectively remove the noise in CT images and improve the image quality in the evaluation metrics of peak signal to noise ratio (PSNR), structural similarity (SSIM), and root mean square error (RMSE) and is superior to the state-of-the-art models. Our method achieved 28.9720 of PSNR, 0.8595 of SSIM and 14.8657 of RMSE on the Mayo Clinic LDCT Grand Challenge dataset. For different noise level σ (15, 35, and 55) on the QIN_LUNG_CT dataset, our proposed also achieved better performances.

Risk factors of osteoporosis in elderly inpatients: A cross-sectional single-centre study.

Objective: This study aimed to identify factors significantly associated with the occurrence of osteoporosis in elderly and very elderly patients. Methods: Elderly hospitalized patients who were older than 60 years old, from the Rehabilitation Hospital from December 2019 to December 2020 were selected. Barthel index (BI), nutritional assessment, the causes of bone mineral density (BMD) reductions in elderly and elderly patients were analysed. Results: A total of 94 patients (83.56 ± 8.37 years old) were enrolled. With increasing age, the BMD of the lumbar spine, femoral neck, and femoral shaft of elderly patients significantly decreased, and the incidence of osteoporosis (OP) significantly increased. The BMD of the lumbar spine was negatively correlated with female and positively correlated with serum 25-hydroxyvitamin D levels, the difference between actual body weight and ideal body weight, and blood uric acid levels; The BMD of the femoral neck was negatively correlated with age and female, and positively correlated with height and geriatric nutrition risk index score. The BMD of the femoral shaft was negatively correlated with female and positively correlated with BI. Conclusion: With increasing age, the BMD of the lumbar spine and the femoral shaft significantly decreased, and the incidence of OP significantly increased in elderly and very elderly patients. Aric acid may protect bone health in elderly patients. Early attention to the nutritional status, exercise capacity, 25-hydroxyvitamin D level, and blood uric acid level in the elderly population can help identify high-risk elderly patients with OP.

Mortality burden based on the associations of ambient PM2.5 with cause-specific mortality in China: Evidence from a death-spectrum wide association study (DWAS).

Although studies have estimated the associations of PM2.5 with total mortality or cardiopulmonary mortality, few have comprehensively examined cause-specific mortality risk and burden caused by ambient PM2.5. Thus, this study investigated the association of short-term exposure to PM2.5 with cause-specific mortality using a death-spectrum wide association study (DWAS). Individual information of 5,450,764 deaths during 2013-2018 were collected from six provinces in China. Daily PM2.5 concentration in the case and control days were estimated by a random forest model. A time-stratified case-crossover study design was applied to estimate the associations (access risk, ER) of PM2.5 with cause-specific mortality, which was then used to calculate the population-attributable fraction (PAF) of mortality and the corresponding mortality burden caused by PM2.5. Each 10 µg/m3 increase in PM2.5 concentration (lag03) was associated with a 0.80 % [95 % confidence interval (CI): 0.73 %, 0.86 %] rise in total mortality. We found greater mortality effect at PM2.5 concentrations < 50 µg/m3. Stratified analyses showed greater ERs in females (1.01 %, 95 %CI: 0.91 %, 1.11 %), children ≤ 5 years (2.17 %, 95 %CI: 0.85 %, 3.51 %), and old people ≥ 70 years. We identified 33 specific causes (level 2) of death which had significant associations with PM2.5, including 16 circulatory diseases, 9 respiratory diseases, and 8 other causes. The PAF estimated based on the overall association between PM2.5 and total mortality was 3.16 % (95 %CI: 2.89 %, 3.40 %). However, the PAF was reduced to 2.88 % (95 %CI: 1.88 %, 3.81 %) using the associations of PM2.5 with 33 level 2 causes of death, based on which 250.15 (95 %CI: 163.29, 330.93) thousand deaths were attributable to short-term PM2.5 exposure across China in 2019. Overall, this study provided a comprehensive picture on the death-spectrum wide association between PM2.5 and morality in China. We observed robust positive cause-specific associations of PM2.5 with mortality risk, which may provide more precise basis in assessing the mortality burden of air pollution.

Low Trend for VZV-Associated Disease Patients to Visit Neurologists.

Background: Herpes zoster (HZ) is a skin disease that can also cause virus-infectious peripheral neuropathies. Despite this, there is limited information on patient preferences for seeking medical attention for HZ and zoster-associated pain (ZAP). Our study aimed to evaluate how frequently patients with ZAP choose to visit neurologists for their symptoms. Methods: This study conducted a retrospective review of electronic health records in three general hospitals from January 2017 to June 2022. Using association rule mining, the study analyzed referral behaviors. Results: We identified 33,633 patients with 111,488 outpatient visits over 5.5 years. The study found that the majority of patients (74.77-91.22%) visited dermatologists during their first outpatient visit, while only a small percentage (0.86-1.47%) preferred to consult a neurologist. The proportion of patients referred to a specialist during their medical visit varied significantly between different specialties within the same hospital (p <0.05) and even within the same specialty (p<0.05). There was a weak association (Lift:1.00-1.17) of referral behaviors between dermatology and neurology. Across the three hospitals, the average number of visits to a neurologist for ZAP was 1.42-2.49, with an average electronic health record duration of 11-15 days per patient. After consulting with a neurologist, some patients were referred to other specialists. Conclusion: It was observed that patients with HZ and ZAP tended to visit a variety of specialists, with only a small number seeking the assistance of neurologists. However, from the perspective of neuroprotection, it is the duty of neurologists to provide more means.

Pain Fluctuations of Women with Subacute Herpetic Neuralgia During Local Methylcobalamin in Combination with Lidocaine Treatment: A Single-Blinded Randomized Controlled Trial.

Purpose: To evaluate the efficacy and pain fluctuations of methylcobalamin in combination with lidocaine local injection treatment for subacute herpetic neuralgia (SHN). Methods: Seventy-nine women (60.4 ± 2.7 years) with thoracic SHN were enrolled and randomized to receive a combination of methylcobalamin and lidocaine local injection (MI, N=40), or a combination of lidocaine patch 5% and oral methylcobalamin (PO, N=39) for four weeks. Repeated-measures analyses of variance were used to evaluate the effect on pain levels. Generalized estimation equations were used to analyze the cause-effect relationship between pain fluctuations and influencing factors. Results: At the treatment endpoint, the group, treatment time, and group interacted with treatment time effects of the pain scores and area were statistically significant (P<0.001), The pain scores were 2.9 ±0.9 (MI) and 4.3 ± 1.5 (PO). 80.00% (MI) or 28.21% (PO) of patients had pain scores ≤ 3, the odds ratio was 2.84 (95% CI: 1.68 to 4.79). The incidence of postherpetic neuralgia was 5.0% (2/40) at 3 months. Pain fluctuated repeatedly during treatment. The pain fluctuation increased from 8.75 log folds in the afternoon, to 79.85 log folds at night. With the ADLs level increasing from 1 to 3, the pain fluctuated from 4.28 to 17.70 log folds. Allodynia, itching, sleep quality, and ADLs were the significant influencing factors (P<0.05). Conclusion: This study validated the efficacy of methylcobalamin combined with lidocaine for SHN, and confirmed that pain levels in patients with SHN had an obvious circadian rhythm. ADLs were an important cause of pain fluctuations.

Effect analysis of multi-department cooperation in improving etiological submission rates before antibiotic treatment.

Increased bacterial drug resistance has become a serious global public health problem. The application of antibiotics involves various clinical departments, and the rational application of antibiotics is the key to improving their efficacy. To provide a basis for further improving the etiological submission rate and standardizing the rational use of antibiotics, this article discusses the intervention effect of multi-department cooperation in improving the etiological submission rate before antibiotic treatment. A total of 87 607 patients were divided into a control group (n = 45 890) and an intervention group (n = 41 717) according to whether multi-department cooperation management was implemented. The intervention group involved the patients hospitalized from August to December 2021, while the control group involved the patients hospitalized from August to December 2020. The submission rates of the two groups; the rates before antibiotic treatment at the unrestricted use level, the restricted use level, and the special use level in departments; and the timing of submission were compared and analysed. The overall differences in the etiological submission rates before antibiotic treatment at the unrestricted use level (20.70% vs 55.98%), the restricted use level (38.23% vs 66.58%), and the special use level (84.92% vs 93.14%) were statistically significant before and after intervention (P < .05). At a more specific level, the etiological submission rates of different departments before antibiotic treatment at the unrestricted use level, the restricted use level, and the special use level were improved, but the special activities of multi-department cooperation management did not improve the submission timing significantly. Multi-department cooperation can effectively improve the etiological submission rates before antimicrobial treatment, but it is necessary to improve measures for specific departments to improve long-term management and incentive and restraint mechanisms.

The impact of mortality underreporting on the association of ambient temperature and PM10 with mortality risk in time series study.

Properly analyzing and reporting data remains a challenging task in epidemiologic research, as underreporting of data is often overlooked. The evaluation on the effect of underreporting remains understudied. In this study, we examined the effect of different scenarios of mortality underreporting on the relationship between PM10, temperature, and mortality. Mortality data, PM10, and temperature data in seven cities were obtained from Provincial Center for Disease Control and Prevention (CDC), China Meteorological Data Sharing Service System, and China National Environmental Monitoring Center, respectively. A time-series design with a distributed lag nonlinear model (DLNM) was used to examine the effects of five mortality underreporting scenarios: 1) Random underreporting of mortality; 2) Underreporting is monotonically increasing (MI) or monotonically decreasing (MD); 3) Underreporting due to holiday and weekends; 4) Underreporting occurs before the 20th day of each month, and these underreporting will be added after the 20th day of the month; and 5) Underreporting due to holiday, weekends, MI, and MD. We observed that underreporting at random (UAR) scenario had little effect on the association between PM10, temperature, and daily mortality. However, other four underreporting not at random (UNAR) scenarios mentioned above had varying degrees of influence on the association between PM10, temperature, and daily mortality. Additionally, in addition to imputation under UAR, the variation of minimum mortality temperature (MMT) and attributable fraction (AF) of mortality attributed to temperature in the same imputation scenarios is inconsistent in different cities. Finally, we observed that the pooled excess risk (ER) below MMT was negatively associated with mortality and the pooled ER above MMT was positively associated with mortality. This study showed that UNAR impacted the association between PM10, temperature, and mortality, and potential underreporting should be dealt with before analyzing data to avoid drawing invalid conclusions.