Objective: To understand the hydration status and related factors of rural boarding primary school students, so as to provide a scientific basis for drinking water health intervention for primary school students. Methods: In November 2023, a convenience sampling approach was employed to conduct a hydration status survey among 144 boarding students in grades 5 and 6 of a rural primary school in Guangxi. The Duplicate meal method and weighing method were utilized to measure the food derived water intake over three consecutive days. Urine osmolarity of students was measured on site for three days, and a simple physical examination was also carried out. A self administered questionnaire was used to investigate students drinking water literacy, daily water intake, and physical activity levels. Meanwhile, a drinking water literacy survey was conducted among 21 substitute teachers and 144 parents of the boarding students in grades 5 and 6. Logistic regression was used to identify factors associated with students hydration status. Results: The median daily total water intake of students was 2 043.55 mL, and 54.86% of the students did not reach the recommended Adequate Intake (AI). The median food derived water intake was 1 149.24 mL, accounting for 53.94% of the total water intake. Univariate analysis revealed that the daily drinking frequency, daily water intake, and food derived water intake of students were related factors of hydration status ( β =-1.60, -1.01, -0.00, all P <0.05). Multivariate Logistic regression analysis showed that primary school students with a daily drinking frequency of ≥7 times were more likely to maintain an adequate hydration status ( OR =0.28, 95% CI =0.09-0.93, P ＜0.05). Conclusions The water intake from food is the main source of water in the body for boarding primary school students in a certain rural school in Guangxi. Primary school students should increase their water intake frequency appropriately to maintain an adequate hydration status.

ObjectiveTo investigate the status of overlapping hepatitis B virus （HBV） infection in patients with chronic hepatitis C virus （HCV） infection and the serological characteristics of such patients. MethodsA total of 8 637 patients with HCV infection who were hospitalized from January 1， 2010 to December 31， 2020 and had complete data of HBV serological markers were enrolled， and the composition ratio of patients with overlapping HBV serological markers was analyzed among the patients with HCV infection. The patients were divided into groups based on age and year of birth， and serological characteristics were analyzed， and the distribution of HBV-related serological characteristics were analyzed across different HCV genotypes. ResultsThe patients with HCV/HBV overlapping infection accounted for 5.85%， and the patients with previous HBV infection accounted for 48.10%； the patients with protective immunity against HBV accounted for 14.67%， while the patients with a lack of protective immunity against HBV accounted for 31.39%. The patients were divided into groups based on age： in the 0 — 17 years group， the patients with protective immunity against HBV accounted for 61.41% （304 patients）； the 18 — 44 years group was mainly composed of patients with previous HBV infection （698 patients， 37.31%）， the 45 — 59 years group was predominantly composed of patients with previous HBV infection （1 945 patients， 50.38%）， and the ≥60 years group was also predominantly composed of patients with previous HBV infection （1 486 patients， 61.66%）. The patients were divided into groups based on the year of birth： in the pre-1992 group， the patients with previous HBV infection accounted for 51.63% （4 112 patients）； in the 1992 — 2005 group， the patients with protective immunity against HBV accounted for 54.72% （168 patients）； in the post-2005 group， the patients with protective immunity against HBV accounted for 64.38% （235 patients）. In this study， 6 301 patients underwent HCV genotype testing： the patients with genotype 1b accounted for the highest proportion of 51.71% （3 258 patients）， followed by those with genotype 2a （1 769 patients， 28.07%）， genotype 3b （63 patients， 1.00%）， genotype 3a （10 patients， 0.16%）， genotype 4 （21 patients， 0.33%）， and genotype 6a （5 patients， 0.08%）. ConclusionWith the implementation of hepatitis B planned vaccination program in China， there has been a significant reduction in the proportion of patients with previous HBV infection among the patients with HCV/HBV overlapping infection， but there is still a relatively high proportion of patients with a lack of protective immunity against HBV.

Ferroptosis is a key driver of the onset and progression of chronic obstructive pulmonary disease （COPD）. By exploring the role of ferroptosis in COPD from the perspective of "qi deficiency with retention and stagnation"， it is considered that mitochondrial dysfunction and imbalanced antioxidant defenses are the microscopic manifestations of "qi deficiency"， whereas iron accumulation and lipid peroxide deposition constitute the pathological basis of "retention and stagnation". In traditional Chinese medicine （TCM）， the treatment principle is tonifying deficiency and benefiting qi， scattering retention and unblocking stagnation. Its mechanism involves improving the antioxidant system and mitochondrial function to enhance cellular resistance to ferroptosis， as well as relieving pulmonary iron overload， excessive lipid peroxidation， and inflammatory factor release to reduce the accumulation of pathological products， thereby exerting therapeutic effects on COPD.

Objective To explore the relationship between nutritional status and sarcopenia in patients with chronic kidney disease. Methods This study included 310 patients with chronic kidney disease (assigned to the kidney disease group) and 150 healthy volunteers who underwent physical examinations during the same period (assigned to the healthy group) between May 2022 and October 2024.The clinical data and related nutritional indicators were compared between the two groups, and the correlation between nutritional status indicators and clinical parameters was analyzed. According to the presence or absence of sarcopenia in the kidney disease group, the patients were divided into a sarcopenia group (n=107) and a non-sarcopenia group (n=203). The nutritional indicators were compared between the two subgroups, the correlation between patients' nutritional status and sarcopenia was analyzed, and the value of nutritional status indicators in diagnosing sarcopenia was evaluated. Results BMI, 25(OH)D3, total body water, muscle mass, and adipose mass in the kidney disease group were significantly lower than those in the healthy group (P<0.05), while the UA, SCr, TC, TG, LDL-C, BUN, CRP, and UACR were significantly higher than those in the healthy group (P<0.05). BMI, 25(OH)D3, total body water, and muscle mass in the kidney disease group were significantly negatively correlated with UA, SCr, CRP, TC, TG, and LDL-C (P<0.05), while UACR was significantly positively correlated with UA, SCr, CRP, TC, TG, and LDL-C (P<0.05). BMI, 25(OH)D3, total body water, and total muscle volume in the sarcopenia group were significantly lower than in the non-sarcopenia group (P<0.05), whereas UACR was significantly higher (P<0.05). BMI, 25(OH)D3, total body water, and muscle mass were protective factors against sarcopenia (OR < 1, P < 0.05), whereas UACR was a risk factor associated with sarcopenia (OR > 1, P < 0.05). The AUCs of BMI, 25 (OH) D3, UACR, total body water, and muscle mass for predicting sarcopenia were 0.614, 0.786, 0.881, 0.675, and 0.734, respectively. The combined diagnostic AUC was 0.951, indicating higher diagnostic value. Conclusion In patients with chronic kidney disease, decreases in BMI, 25(OH)D3, total body water, and muscle mass, and an increase in UACR, can all indicate the occurrence of sarcopenia. Among these, BMI, 25(OH)D3, total body water, and muscle mass serve as nutritional status indicators, and their combination with UACR has auxiliary diagnostic value for sarcopenia.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Objective: To detect the different proteomic characteristics of microvesicles (MVs) and exosomes (EXOs) released from apheresis platelets during storage, and to explore their role in mediating platelet storage damage lesion (PSL). Methods: Apheresis platelets were collected from the retention bag on the third day of storage. MVs and EXOs were isolated using differential centrifugation. Platelet, MVs and EXOs protein samples were extracted respectively, and the differentially expressed proteins were detected by quantitative proteomics technology. Further, the co-incubation model of MVs, EXOs and fresh platelets was adopted to evaluate the effect of extracellular vesicles on PSL. The aggregation response of platelets to collagen agonizers and the changes in ATP release rate were evaluated by optical turbidimetry. Flow cytometry was used to evaluate the changes of platelet early activation indicators (P-selectin and PAC-1) and mitochondrial membrane potentia. Western blot was used to detect the changes in the expression of key proteins for platelet activation and apoptosis (P-selectin, Integrin β3 and Bcl-xl). Results: Proteomic analysis revealed a significantly separation in protein expression profiles of platelet, MVs and EXOs samples within the latent variable space. Energy metabolization-related proteins such as mitochondrial respiratory chain complex and oxidative phosphorylation were enriched specifically, in MVs while EXOs were enriched with inflammation-related proteins. Co-incubation experiments confirmed that extracellular vesicles could significantly induce platelet responses to agonists (the maximum aggregation rate in the MVs group increased by 187.36%, P<0.001; 71.26%, in the EXOs group P=0.002). The maximum ATP release rate of platelets also increased (275.44% in the MVs group, P<0.001; 70.18% in the EXOs group, P=0.015). The expression of P-selectin increased (119.33% in the MVs group, P<0.001; 25.61% in the EXOs group, P=0.013), as detected by flow cytometry. The binding rate of PAC-1 increased (132.18% in MVs group, P<0.001; 21.41% in EXOs group, P=0.043), and the mitochondrial membrane potential decreased (20.49% in MVs group, P<0.001; 9.73% in EXOs group, P=0.044). In the MVs group, platelet P-selectin and Integrin β3 expression were significantly increased (100.83% and 395.64%, P<0.001), while Bcl-xl expression was lower than that in the control group (83.94%, P<0.001). Compared with the control group, P-selectin and Integrin β3 expression were also increased (27.89% and 181.91%, P=0.007和P=0.002), while Bcl-xl was decreased in the EXOs group (36.52%, P<0.001). Conclusion: MVs and EXOs derived from stored platelets show different proteomic characteristics. Compared with EXOs, MVs exhibits a stronger effect in inducing mitochondrial dysfunction. Mvs also promots PSL responses including platelet activation and apoptosis.

ObjectiveTo investigate the role of serum HBV RNA in assessing antiviral therapy for patients with chronic hepatitis B， as well as its potential as a biomarker in clinical therapy， and to provide a scientific basis for the clinical treatment of chronic hepatitis B. MethodsA total of 134 patients who were diagnosed with chronic HBV infection in The Second Affiliated Hospital of Kunming Medical University from April 2023 to May 2024 were enrolled as subjects， and related examinations were performed， including HBV DNA， serum HBV RNA， liver function， HBsAg， anti-HBs， HBeAg， anti-HBe， anti-HBc， and transient elastography of the liver. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between multiple groups； the chi-square test or the continuity-adjusted chi-square test was used for comparison of categorical data between two groups. Pearson correlation analysis or Spearman correlation analysis was performed. ResultsThe 134 patients with chronic HBV infection were divided into HBeAg-positive group with 45 patients and HBeAg-negative group with 89 patients， and there were significant differences between the two groups in age， the positive rate and quantitative value of HBV DNA， the positive rate and quantitative value of serum HBV RNA， HBsAg， anti-HBe， and ALT （all P<0.05）. In the cohort study of the HBeAg negative group， there were significant differences in the levels of HBV DNA， HBsAg， and GGT between the serum HBV RNA-negative group with 14 patients and the serum HBV RNA-positive group with 75 patients （all P<0.05）. There were 28 patients in the HBeAg-positive group and 62 in the HBeAg-positive group who used antiviral drugs for ≥1 month， and the 28 HBeAg-positive patients had an HBV RNA positive rate of 100%， while for the 62 HBeAg-negative patients， there were significant differences in the positive rate and level of serum HBV RNA between the patients with different durations of medication （both P<0.05）. Among the 89 HBeAg-negative patients， there were 62 treatment-experienced patients and 27 treatment-naïve patients， and there was a significant difference between the two groups in HBV RNA level ［2.07 （1.52 — 2.82） log₁₀ copies/mL vs 2.69 （1.80 — 3.55） log₁₀ copies/mL， Z=2.034， P=0.042］. For HBeAg-negative patients， serum HBV RNA was positively correlated with HBV DNA and HBsAg （both P<0.05）， and for HBeAg-positive patients， serum HBV RNA was significantly positively correlated with HBV DNA， HBsAg， and HBeAg （all P<0.05）. ConclusionAntiviral therapy can reduce viral load， and for HBeAg-negative patients with high-sensitivity HBV DNA below the lower limit of detection， serum HBV RNA can fill the “gap” in the detection of viral replication.

Objective:To establish a nomogram prediction model for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections.Methods:A retrospective analysis was performed for the clinical and imaging data of 395 pregnant and par-turient women with multiple cesarean section who were hospitalized for delivery from January 2021 to December 2023.Univariate analysis and multivariate logistic regression analysis were used to investigate the risk factors for severe postpartum hemorrhage in sub-sequent pregnancies after multiple cesarean sections.A nomogram prediction model was established and validated in terms of specific-ity,accuracy,and clinical decision-making utility.Results:Among the 395 patients,131 experienced severe postpartum hemorrhage,accounting for 33.16%.The univariate analysis showed that times of pregnancy,times of vaginal delivery,grade of hospitals for previ-ous surgeries,number of prenatal checkups during this time of pregnancy,pregnancy-induced hypertension,gestational diabetes,pla-centa previa,location of placenta,association between placenta and uterus,and whether emergency cesarean section was performed were risk factors for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections(P<0.05).The multivari-ate logistic regression analysis showed that times of pregnancy,number of prenatal checkups,gestational diabetes,position of placenta,and whether emergency cesarean section was performed were independent risk factors for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections(P<0.05).A nomogram prediction model was established based on these independent risk factors,which had an area under the ROC curve of 0.783(95%CI=0.732-0.834),and there was a good consistency between the pre-dicted probability curve and the observed frequency curve.When the probability of severe postpartum hemorrhage predicted by the nomogram model was within the range of 0.15-1.0,the model has a good value of clinical decision-making.Conclusion:The incidence rate of severe postpartum hemorrhage in this population can be re-duced by attending regular prenatal checkups,controlling preg-nancy complications,and reducing the rate of emergency cesarean section and the number of deliveries.The nomogram prediction model established in this study has certain clinical application prospects.