Objective To investigate the epidemiological characteristics of malaria and provide a basis for developing improved prevention and control measures. Methods Data were obtained from the Chinese Disease Prevention and Control Information System. Malaria surveillance data for Nanning City from January 1,2023, to December 31,2024, were exported from the Infectious Disease Reporting Information Management Subsystem. The characteristics of the two groups of malaria cases were compared. Results A total of 103 imported malaria cases were reported in Nanning City in 2024, representing a 38.32% decrease compared with the same period of the previous year. No statistically significant difference were observed between cases reported in 2023 and 2024 in terms of average age, gender ratio, proportion of parasite species, and monthly reporting distribution;however, statistically significant differences were found in the proportion of reporting areas and current residence areas(χ2= 13.572 and 10.355, respectively; P = 0.001 and 0.035, respectively). The proportion of cases reported in Shanglin County and the proportion of cases residing in Shanglin County were both lower than those during the same period of the previous year. Conclusions The high aggregation of imported malaria cases in Nanning City has decreased. Medical institutions in areas other than Shanglin County should strengthen their vigilance against malaria.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

One of its primary surgical treatments of tricuspid regurgitation is tricuspid valve biological valve replacement. Catheter tricuspid valve-in-valve implantation is a novel interventional alternative for biological valve failure. The non-invasive lung fluid measuring device remote dielectric sensing (ReDSTM) has been increasingly incorporated into clinical practice as a means of monitoring chronic heart failure in recent years. This report describes the process and outcomes of the first instance of perioperative lung fluid volume evaluation following transcatheter tricuspid valve implantation utilizing ReDSTM technology. The patient has a short-term, substantial increase in postoperative lung fluid volume as compared to baseline.

Pancreatic cancers (PCs) is a common malignant tumor with poor prognosis in the digestive system. Its main treatment methods include surgery, radiotherapy, chemotherapy, and targeted therapy. The early diagnosis rate of hidden onset of PCs is low, and most patients have already lost the opportunity to undergo surgery when diagnosed with PCs. Chemotherapy is still the main treatment for advanced PCs, but the use of chemotherapy drugs in PCs can easily lead to drug resistance. The most significant feature that distinguishes PCs from other tumors is its rich and dense matrix, which not only hinders drug penetration but also impedes the infiltration of immune cells. The above reasons have led to a very low survival rate of PCs patients. Therefore, drug delivery systems are very important in the diagnosis and treatment of PCs. They can improve drug delivery, enhance biological barrier penetration, reduce side effects, and combine multiple treatment methods. Therefore, the treatment prospects of PCs are very broad. Currently, drug delivery systems widely applied in PCs primarily include nanodrug delivery systems, tumor microenvironment-targeted drug delivery system, immunotherapy drug delivery system, gene therapy drug delivery system, and combination therapy drug delivery system that synergize multiple therapeutic modalities. Emerging drug delivery systems (DDSs) have revolutionized PCs treatment by addressing these challenges through multiple mechanisms. Nanoformulations improve drug solubility, prolong circulation time, and reduce systemic toxicity via passive/active targeting. Smart DDSs responsive to PCs-specific stimuli enable extracellular matrix degradation, tumor-associated fibroblasts reprogramming, and vascular normalization to enhance drug accessibility. Last but not least, carrier systems loaded with myeloid-derived suppressor cell inhibitors or T cell activators can reverse immunosuppression and potentiate immunotherapy efficacy. Advanced platforms co-deliver chemotherapeutics with immunomodulators, gene-editing tools, or sonodynamic agents to achieve synergistic antitumor effects. These platforms aim to address critical challenges in PCs treatment, such as enhancing drug bioavailability, overcoming stromal barriers, reprogramming immunosuppressive niches, and achieving multi-mechanistic antitumor effects. This article provides a systematic summary and prospective analysis of the current development status, latest cutting-edge advances, opportunities, and challenges of the above-mentioned drug delivery systems in the field of PCs therapy.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

Salvia miltiorrhiza is a perennial herb of the genus Salvia(Lamiaceae). As one of the earliest medicinal plants to undergo molecular biology research, it has gradually become a model plant for molecular biology of medicinal plants. With the gradual analysis of the genome of S. miltiorrhiza and the biosynthetic pathways of its main active components tanshinone and salvianolic acids, the transcriptional regulation mediated by transcription factors and related regulatory proteins has gradually become a new research focus. Due to the lack of scientific and unified naming of transcription factors and different research indexes in different literature, this paper systematically sorted out the transcription factors in different literature with the genomes of DSS3 from selfing for three generations and bh2-7 from selfing for six generations as reference. In total, 73 transcription factors and related regulatory proteins belonging to 13 gene families were identified. The effects of overexpression or gene silencing experiments on tanshinone and salvianolic acids were also analyzed. This study unified the identified transcription factors, which laid a foundation for further constructing the regulatory networks of secondary metabolites and insect or stress resistance and improving the quality of medicinal materials by using global transcriptional regulation engineering.
Salvia miltiorrhiza/chemistry* ; Plant Proteins/metabolism* ; Gene Expression Regulation, Plant ; Transcription Factors/metabolism* ; Abietanes/metabolism*

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.