ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveTo construct a scale for the diagnosis of chronic atrophic gastritis （CAG） with turbid toxin accumulating in the stomach. MethodsFirst， a research group was established to construct the scale framework. Relevant literature of CAG with syndrome of turbid toxin accumulating in the stomach was searched in CNKI， Wanfang Database （WF）， and VIP Database （CQVIP） from April 1， 2003 to April 1， 2023， and items were preliminarily selected after standardization of terms. Through clinical investigation， the discrete trend method， correlation coefficient method， Cronbach's coefficient method， and factor analysis method were used to screen symptom items， and the frequency method was used to screen signs， tongue coating， and pulse conditions. Three rounds of Delphi expert consultation were conducted to determine the items of the scale. The weight of each item was obtained by the analytic hierarchy process. ResultsA total of 49 articles were included， and 45 items were obtained after primary screening， including 28 symptoms， 2 signs， 10 tongue coatings， and 5 pulse conditions. After clinical investigation， 15 symptoms were retained， and 8 signs and pulse conditions of tongue coating were retained. The positive coefficients of experts in three rounds of Delphi expert consultation were 100%， 96.67%， and 100%， respectively. The expert authority coefficients were 0.86， 0.87， and 0.87， respectively， and the coordination coefficients were 0.18， 0.25， and 0.30. After core group discussion， Delphi method investigation， and AHP weight assignment， the diagnostic scale items of CAG with turbid toxin accumulating in stomach syndrome were finally established， namely， dark red or purplish tongue proper with yellow greasy （or dry） coating （30 points）， epigastric stuffiness and fullness or pain （15 points）， sticky and unsmooth defecation （10 points）， taste disturbance （sticky mouth， fetid breath， bitter taste， 7 points）， heartburn or acid regurgitation （6 points）， dizziness and clouding （5 points）， general heaviness and fatigue （5 points）， slippery， string‑slippery， or slippery‑rapid pulse （5 points）， dysuria （or yellow or deep yellow urine， 4 points）， poor appetite （4 points）， dull complexion （3 points）， sticky， greasy， and fetid secretions （3 points）， and poor sleep （3 points）. ConclusionBased on the establishment， screening， confirmation， and weighting of an item pool， combined with subjective and objective approaches as well as qualitative and quantitative methods， a diagnostic scale for CAG with the syndrome of turbid toxin accumulating in the stomach was successfully constructed.

Contemporary Chinese medical ethics culture is a brand-new cultural field gradually formed with the development of Chinese society and the progress of medical science and technology. This type of culture， with its own characteristics， needs to be examined and understood from the perspective of the historical roots and origins of its evolution. The ancient Chinese medical ethics thought has a foundational significance for modern and contemporary medical ethics thought. The thought that “medicine is the art of benevolence” is the core concept of Chinese medical ethics culture， from which the ancient medical moral thoughts and cultural systems were derived. With the introduction of Western medicine and its development in China， the penetration of modern Western medical ethics thought into the moral thought system of traditional Chinese medicine became the beginning of the collision and integration of Chinese and Western medical ethics wisdom. The “spirit of red medicine” formed during the revolutionary process in modern China， reflects the characteristics of medical ethics culture forged in the practice of China’s great revolution. Contemporary Chinese medical ethics culture is gradually blending into the mainstream of Chinese society and has become a constituent element of the socialist culture system with Chinese characteristics.

eIF3a is a N ⁶-methyladenosine (m⁶A) reader that regulates mRNA translation by recognizing m⁶A modifications of these mRNAs. It has been suggested that eIF3a may play an important role in regulating translation initiation via m⁶A during infection when canonical cap-dependent initiation is inhibited. However, the death of animal model studies impedes our understanding of the functional significance of eIF3a in immunity and regulation in vivo. In this study, we investigated the in vivo function of eIF3a using eIF3a knockout and knockdown mouse models and found that eIF3a deficiency resulted in splenic tissue structural disruption and multi-organ damage, which contributed to severe sepsis induced by Lipopolysaccharide (LPS). Ectopic eIF3a overexpression in the eIF3a knockdown mice rescued mice from LPS-induced severe sepsis. We further showed that eIF3a maintains a functional and healthy immune system by regulating B cell function and quantity through m⁶A modification of mRNAs. These findings unveil a novel mechanism underlying sepsis, implicating the pivotal role of B cells in this complex disease process regulated by eIF3a. Furthermore, eIF3a may be used to develop a potential strategy for treating sepsis.

With the aging of the population and changes in lifestyle in China, the number of patients with diabetic infra-popliteal artery occlusion has been growing. Revascularization is of great significance for improving the limb salvage rate and survival rate of patients. By comparing open surgery and endovascular revascularization techniques, although open surgery can improve lower limb ischemia, it has significant trauma and numerous complications. Endovascular treatment, which includes procedures such as lumen recanalization, lumen preparation, and lumen maintenance, has become the preferred option due to its advantages such as minimal trauma. The lumen recanalization technique has continuously advanced with the helping of new devices and the accumulation of experience. Lumen preparation encompasses various methods such as balloon dilation and debulking techniques to address different lesions. In lumen maintenance, drug-coated balloon (DCB) have a certain effect in inhibiting smooth muscle proliferation and improving long-term patency rates. However, the safety of paclitaxel on DCB remains controversial. Stent implantation is not currently recommended due to the characteristics of the infra-popliteal arteries such as small lumen, long lesions, and severe calcification. At present, revascularization for diabetic infra-popliteal artery occlusion still faces challenges. Research on angiogenesis therapy is expected to bring new breakthroughs, and the future development of this field requires the integration of multiple disciplines. This article reviews the development history of revascularization for diabetic infra-popliteal artery lesions, and expounds the transformation of its treatment concept from early arbitrary recanalization to the precise Angiographsome concept.

Objective:To analyze the clinical and genetic characteristics of children diagnosed with Noonan-syndrome associated with loose anagen hair (NS-LAH).Methods:A retrospective analysis was conducted on the clinical data of 5 children diagnosed with NS-LAH by the Endocrinology Department of the Capital Institute of Pediatrics from January 2018 to June 2024. This analysis encompassed the patients′ demographic information, clinical manifestations, distinguishing features, treatment regimens, and prognostic outcomes to elucidate their clinical characteristics. Additionally, whole-exome sequencing and Sanger sequencing were utilized to investigate the genetic etiology within the families, and the identified variations were interpreted according to the guidelines of the American College of Medical Genetics and Genomics.Results:Among the 5 NS-LAH patients, there were 3 boys and 2 girls, with ages at diagnosis ranging from 2.3 to 7.7 years old. All patients presented with short stature as a primary complaint. Birth histories were generally unremarkable, though case 2 and 5 of macrosomia were noted. In addition to the characteristic facial features of Noonan syndrome, short stature, and varying degrees of intellectual and motor developmental delay, all 5 patients exhibited sparse hair that was easily shed, as well as enlarged head circumferences. Four patients showed structural cardiac abnormalities, which included a case of hypertrophic cardiomyopathy, 2 cases of atrial septal defect, and 1 case of patent foramen ovale. Genetic analysis revealed heterozygous missense variantion in SHOC2 gene in 4 patients, comprising 3 cases with c.4A>G (p.S2G) and one case with c.519G>C (p.M173I). Additionally, one patient was found to have a heterozygous missense variantion c.146C>G (p.P49R) in PPP1CB gene. Three children were diagnosed with growth hormone deficiency and treated with growth hormone for 1.7, 2.7 and 0.5 years. This resulted in significant improvements in height, with annual increases of 11.8, 8.4 and 13.0 cm, respectively. Among the 4 patients with SHOC2 variantions, 2 developed systemic lupus erythematosus and 1 exhibited symptoms of arthritis.Conclusions:Growth failure is the primary complaint in patients with NS-LAH. Key characteristic findings include enlarged head circumference and sparse, loose hair. Growth hormone deficiency is commonly associated with NS-LAH, and growth hormone therapy is generally effective. Furthermore, patients carrying the classic variantion in SHOC2 (c.4A>G) may have an increased risk of developing autoimmune diseases.

Objective:To develop and validate a deep learning-based multimodal model integrating clinical and radiomic features for predicting acute kidney injury（AKI）risk after partial nephrectomy.Methods:A retrospective analysis was conducted on 416 patients who underwent partial nephrectomy at Zhongshan Hospital，Fudan University from January 2023 to January 2025. The cohort included 100 AKI patients［defined by a ≥ 25% reduction in postoperative evaluated glomerular filtration rate（eGFR）within 48 hours sustained for >24 hours］and 316 non-AKI patients（1∶3 ratio，randomly matched with 16 additional cases for redundancy）. Clinical and radiomic features were extracted from preoperative contrast-enhanced CT scans using PyRadiomics. Demographics included 259 males and 158 females，with a median age of 57（49，65）years，body mass index of（24.1 ± 3.3）kg/m2，preoperative eGFR of（88.5 ± 18.3）ml/（min·1.73 m2），postoperative eGFR（48-hour）of（76.0 ± 21.9）ml/（min·1.73 m2），Zhongshan Score（ZSscore）of 7.34 ± 2.01，and R.E.N.A.L. score of 7.50 ± 1.71. All tumors were T 1a stage. Patients were divided into training（n = 312）and test（n = 104）sets（3∶1 ratio）. A clinical model was constructed via multivariate logistic regression，while radiomic and combined（clinical + radiomic）models utilized an artificial neural network（ANN）with 1 input layer，5 hidden layers，1 output layer，and 10 5 training epochs. Model performance was evaluated by using receiver operating characteristic（ROC）curves and area under the curve（AUC），and was compared to the Martini model. Feature contributions were interpreted via SHapley Additive exPlanations（SHAP）. Results:In the test set，the results of multivariate logistic regression showed that patient’s weight，preoperative eGFR，R.E.N.A.L. score，surgical approach，and operation time were risk factors for AKI（ P < 0.05）. The AUC of the clinical feature prediction model constructed based on the above factors was 0.852（95% CI 0.775?0.929）. In the test set，the AUC of the Martini model was 0.725（95% CI 0.565?0.791）. The radiomic model，trained on 1 315 imaging features，achieved an AUC of 0.898（95% CI 0.804?0.993）with 94.2%（98/104）accuracy. The combined clinical and radiomic model，integrating 1 315 radiomic features and clinical features，demonstrated superior performance with an AUC of 0.946（95% CI 0.887?1.000）and 96.2%（100/104）accuracy，outperforming both the clinical model（ P = 0.03）and the Martini model（ P < 0.01）. SHAP analysis identified the top five predictors in the combined model：ZSscore（SHAP value：0.78），long-run low gray-level emphasis（SHAP value：0.61），run-length non-uniformity（SHAP value：0.58），size-zone non-uniformity（SHAP value：0.46），and gray-level co-occurrence matrix joint energy（SHAP value：0.36）. Conclusions:The deep learning-based multimodal model integrating clinical and radiomic features accurately predicts AKI risk after partial nephrectomy，offering a novel strategy for preoperative risk stratification and personalized intervention.

Objective To investigate disparities in health levels among populations across different regions of China and analyze the relationship between these disparities and regional, social, and economic factors, and to provide recommendations to promote health equity. Methods Based on the data from the Seventh National Population Census, this study employed spatial autocorrelation analysis and the spatial Durbin model to conduct spatial and temporal analyses of the health status of the national population from 2012 to 2021, focusing on the regional distribution of health levels and related influencing factors. Results 1. Regional disparities: The mortality rate in Gansu Province rose from 6.05‰ in 2012 to 8.26‰ in 2021, whereas the mortality rate in eastern provinces such as Hainan Province was relatively low in 2021 (5.39‰). 2. Spatial clustering: The spatial correlation of mortality rates was weak (Moran's I: 0.134-0.245), and the high mortality clusters showed a shift from southwest to northeast region. 3. Influencing factors: Economic conditions, education quality, urbanization levels, and healthcare resources significantly impacted population mortality rates. Conclusion The present study identifies pronounced regional disparities in population health, providing a scientific basis for formulating targeted healthcare policies. Additionally, this study highlights the critical importance of spatial analysis in understanding and addressing public health issues to advance health equity.