Objective To analyze the influencing factors of malaria infection of labor service exported to overseas in Langfang City, in order to establish a visualization tool to assist clinicians in predicting the risk of malaria. Methods A total of 4 774 expatriate employees of the Nibei Pipeline Project of the Pipeline Bureau from October 2021 to August 2023 were taken as the subjects, and the gender, age, overseas residence area and Knowledge of malaria controlscores of the study subjects were investigated by questionnaire survey, and the possible risk factors of malaria were screened by logistic regression model. At the same time, the nomogram prediction model was established, and the subjects were divided into the training group and the validation group at a ratio of 2:1, and the area under the curve (ROC) and the decision curve were plotted to evaluate the prediction ability and practicability of the prediction model in this study. Results Among the 4 774 study subjects, 96 cases of malaria occurred, and the detection rate was 2.01%. Junior school （OR=1.723，95% CI:1.361-2.173）， and residence in rural areas（OR=2.091，95%CI:1.760 -3.100）were risk factors (OR>1), while protective measures（OR=0.826，95% CI : 0.781 - 0.901） and high malaria education scores （OR=0.872，95% CI : 0.621 - 0.899）were protective factors.The nomogram prediction model results showed that the area under the curve of the nomogram prediction model in the training group was 0.94 (95% CI : 0.85 - 1.00), while the validation group was 0.93 (95% CI : 0.80 - 1.00). The results of the decision curve showed that when the threshold probability of the population was 0-0.9, the nomogram model was used to predict the risk of malaria occurrence with the highest net income. Conclusion The nomogram prediction model (including gender, education, region, protection and malaria education score) established and validated in this study is of great value for clinicians to screen high-risk patients with malaria.

Objective:To investigate the correlation between plasma Dickkopf-1 (DKK1) and post-stroke cognitive impairment (PSCI) in patients with acute ischemic stroke.Methods:Consecutive patients with first-ever acute ischemic stroke admitted to the Department of Neurology, Nanjing Jiangbei Hospital from March 2023 to February 2024 were included prospectively. Enzyme-linked immunosorbent assay was used to detect plasma DKK1 within 24 hours of onset. The Montreal Cognitive Assessment Scale was used to evaluate cognitive function at 3 months after onset. A score ≤22 was defined as PSCI. Multivariate logistic regression analysis was used to determine the correlation between DKK1 and PSCI. The relationship between DKK1 and PSCI risks was evaluated through restrictive cubic spline analysis. Results:A total of 205 patients with acute ischemic stroke were enrolled, including 106 males (51.7%), aged 67.0±9.4 years; 61 patients (29.8%) experienced PSCI. Multivariate logistic regression analysis showed that after adjusting for age, gender, education level, and other confounding factors, there was a significant independent correlation between higher plasma DKK1 and PSCI (odds ratio 1.778, 95% confidence interval 1.313-2.408; P=0.001). Subgroup analysis showed that age, gender, etiological classification of stroke, and education level had no significant effect on the above correlation. Restrictive cubic spline analysis showed plasma DKK1 had a linear relationship with the risk of PSCI ( P=0.003). Conclusion:Higher plasma DKK1 level is significantly correlated with PSCI in patients with acute ischemic stroke at 90 days after onset.

Objectives:To investigate the predictive factors of stroke associated-pneumonia (SAP) in patients with acute stroke, develop nomogram and neural network prediction models and verify their predictive performance.Methods:Patients with acute stroke admitted to the First Affiliated Hospital of Kunming Medical University and Zhenxiong County People's Hospital were included retrospectively. Multivariate logistic regression analysis was used to determine the independent predictive factors of SAP, and develop nomogram and neural network prediction models. Receiver operating characteristic curve (ROC) curves were used to validate and compare the predictive performances. Results:A total of 450 patients with acute stroke were enrolled, including 286 males (63.6%), aged 64.28±13.24 years; 344 patientss (76.4%) had ischemic stroke and 106 (23.6%) had hemorrhagic stroke; 128 patients (28.4%) experienced SAP. According to the random number method, they were divided into a modeling cohort ( n=300) and a validation cohort ( n=150). Multivariate logistic regression analysis in the modeling cohort showed that a higher baseline National Institutes of Health Stroke Scale (NIHSS) score, gastric tube placement, use of proton pump inhibitors, heart failure, and higher neutrophil/lymphocyte ratio (NLR) were the independent predictive factors of SAP. ROC curve analysis showed that the area under the ROC curve of the nomogram model for predicting SAP in the modeling cohort and validation cohort was 0.841 (95% confidence interval [ CI] 0.795-0.880) and 0.863 (95% CI 0.798-0.914), respectively. The sensitivity for predicting SAP were 75.00% and 70.45%, respectively, and the specificity was 81.94% and 92.45%, respectively. The area under the ROC curve of the neural network model for predicting SAP in the modeling cohort and validation cohort was 0.847 (95% CI 0.802-0.866) and 0.862 (95% CI 0.796-0.913), respectively. The sensitivity for predicting SAP were 76.19% and 72.73%, and the specificity was 79.17% and 89.62%, respectively. Conclusions:Higher NIHSS score, gastric tube placement, use of proton pump inhibitors, heart failure, and higher NLR are the independent risk factors for SAP in patients with acute stroke. The nomogram and neural network prediction model developed using the above risk factors have higher predictive value for SAP.

Traumatic aortic injury (TAI) is an acute, critical, and severe disease, and then combined with multiple organ damage, it is even more dangerous. TAI progresses very rapidly, with a pre-hospital mortality rate of 57%-80%, and even when arriving at the hospital, more than one-third of the patients die within 4 h, and it is the 2nd leading cause of death in individuals aged 4-34 years. In addition, the incidence of TAI combined with injury was 81.4%. Therefore, early diagnosis, expeditious surgery, and timely and effective multidisciplinary cooperation are essential for successful rescue. The authors report 2 patients with acute traumatic aortic dissection combined with multiple organ injuries and treated with emergency endovascular surgery to discuss their clinical characteristics and treatment experience, and to provide experience in the diagnosis and treatment of such patients.
Humans ; Aortic Dissection/surgery* ; Endovascular Procedures ; Multiple Trauma/surgery*

Peptide receptor radionuclide therapy (PRRT) with radiolabeled SSTR2 agonists is a treatment option that is highly effective in controlling metastatic and progressive neuroendocrine tumors (NETs). Previous studies have shown that an SSTR2 agonist combined with albumin binding moiety Evans blue (denoted as ¹⁷⁷Lu-EB-TATE) is characterized by a higher tumor uptake and residence time in preclinical models and in patients with metastatic NETs. This study aimed to enhance the in vivo stability, pharmacokinetics, and pharmacodynamics of ¹⁷⁷Lu-EB-TATE by replacing the maleimide-thiol group with a polyethylene glycol chain, resulting in a novel EB conjugated SSTR2-targeting radiopharmaceutical, ¹⁷⁷Lu-LNC1010, for PRRT. In preclinical studies, ¹⁷⁷Lu-LNC1010 exhibited good stability and SSTR2-binding affinity in AR42J tumor cells and enhanced uptake and prolonged retention in AR42J tumor xenografts. Thereafter, we presented the first-in-human dose escalation study of ¹⁷⁷Lu-LNC1010 in patients with advanced/metastatic NETs. ¹⁷⁷Lu-LNC1010 was well-tolerated by all patients, with minor adverse effects, and exhibited significant uptake and prolonged retention in tumor lesions, with higher tumor radiation doses than those of ¹⁷⁷Lu-EB-TATE. Preliminary PRRT efficacy results showed an 83% disease control rate and a 42% overall response rate after two ¹⁷⁷Lu-LNC1010 treatment cycles. These encouraging findings warrant further investigations through multicenter, prospective, and randomized controlled trials.

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

Objective Depression,a most common psychiatric disease,is defined in Traditional Chinese Medicine(TCM)as Yu Syndrome,i.e.,depression disorder,or Baihe Disease,i.e.,lily bulb disease,a category of emotional disorders treated with lily-based TCM preparations.In TCM,depression is managed through syndrome differentiation and treatment,which is characterized by high efficacy and safety.However,there is no unified standard for the classification of depression syndromes,which leads to a disconnection between the analysis of patients'medication patterns and their actual syndromes and hinders the study of medication patterns specific to particular syndromes.Therefore,this study is focused on investigating the medication patterns of different sub-types of depression patients based on an objective classification system of depression.Methods We searched for and retrieved clinical literature on TCM formulas for depression from relevant databases,including China National Knowledge Infrastructure(CNKI),Wanfang Data,VIP Database,Sinomed,Web of Science,and PubMed.Information on patient symptoms and medication was standardized.Then,the symptoms and the medication frequency of depression patients were statistically analyzed.We used the K-means clustering method combined with implicit structural analysis to objectively categorize depression patients into sub-types.In addition,the main symptoms and core TCM formulas of each sub-type of depression patients were identified.On the basis of objective classification system,we also statistically analyzed the characteristics of herbs used on depression patients,including the 4 basic properties,the 5 flavors,the attributes,the therapeutic efficacy,and the co-occurrence patterns,which may help reveal the medication patterns.Results A total of 3 537 publications and 4 434 prescriptions were included in the analysis.By using the K-means algorithm and latent structure analysis methods,patients with depression were categorized into 9 sub-types,with Cluster 6 accounting for the largest proportion.The most common symptoms among depression patients were insomnia and a depressed mood.Medication frequency analysis showed that Radix Bupleuri(Chai Hu),Radix Paeoniae Alba(Bai Shao),Poria(Fu Ling),Rhizoma Chuanxiong(Chuan Xiong),and Radix Curcumae(Yu Jin)were the most commonly used TCM herbs.For the depression sub-types of Clusters 1,2,and 6,blood-activating and stasis-dissolving herbs were used most often.The depression sub-types of Clusters 3,4,5,8,and 9 were mainly treated with qi-regulating herbs,while the depression sub-type of Cluster 7 was treated with qi-supplementing herbs.Depression patients were mostly treated with herbs that were cold or warm in nature and had sweet,bitter,and pungent flavors.Moreover,treatments for Cluster 1 and Cluster 6 mainly targeted the spleen meridian,while those for Cluster 2,Cluster 3,Cluster 4 and Cluster 5 mainly targeted the heart meridian.The treatments for the other sub-types mainly targeted the liver meridian.The core TCM formulas for the 9 depression sub-types included Zishui Qinggan Decoction,Danzhi Xiaoyao Powder,Huanglian Wendan Tang,Chaihu Guizhi Tang,Modified Xiaoyao Powder,Qinggan Jieyu Tang,Xiaoyao Powder,Xuefu Zhuyu Decoction,and Bazhen Decoction.The most commonly used Chinese herbal medicinal formulas were Gan Cao-Chai Hu,Bai Shao-Chai Hu,and Chen Pi-Chai Hu.Conclusion Based on machine learning,this study reveals the scientific aspects of TCM typing and syndrome-based treatment.It clarifies the rationale for targeting different symptoms in depression treatment and provides theoretical support for clinicians to make medication prescriptions.It also presents a new perspective for investigating TCM medication patterns.

Objective To characterize the clinical features of the group of gout patients to facilitate earlier identifi-cation,and optimize the diagnosis and treatment of the condition.Methods The retrospective study analyzed 24 gout patients with shoulder joint(s)involved and consulted by physicians of Peking Union Medical College Hospital from March 2021 to April 2025,while 70 outpatient gout patients matched by clinical course duration and sex were enrolled as control group.Clinical data including medical history,laboratory tests,therapeutic interventions.Prog-nosis was systematically collected to delineate the distinctive clinical manifestations of the patients.Results All 24 gout patients with shoulder joints involved were male,aged(43.16±13.13)years and had an average BMI of 27.70±4.63.The duration of gout was 8(5,12)years while of those patients had an early onset before 30 years old.The maximal serum uric acid concentration was(754.15±175.79)μmol/L.It was shown by case review that 16.67％of the patients were asymptomatic,and 79.17％suffered from shoulder pain.A quarter of the patients developed subcutaneous tophi.All the patients affected(P＜0.05).The affected joints ascended from lower extremities to the upper averagely took 4.72±2.80 years and had heavier burden of hyperuricemia(P＜0.05),while no significant difference was found in renal function and inflammation level.Conclusions Gout patients with shoulder joints involvement are older and have atypical manifestation.The diagnosis needs support of imaging or ar-throcentesis.