Objective: To evaluate the efficacy and safety of ruxolitinib combined with low-dose hormone for patients with acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: Thirty patients with aGVHD after allo-HSCT admitted to the Department of Hematology of the General Hospital of Western Theater Command from November 2021 to November 2024 were retrospectively analyzed. All patients were treated with low-dose hormone (methylprednisolone 0.3-1 mg kg -d ) combined with ruxolitinib 5-10 mg d . The efficacy and adverse reactions were observed during the follow-up period to analyze the survival outcomes of the patients. Results: A total of 30 patients with aGVHD after allo-HSCT were included in this study, consisting of 15 (50%) males and 15 (50%) females with a median age of 34 year-old (ranging from 14 to 62). Classification by disease type: there were 18 cases of acute myeloid leukemia, 4 cases of acute lymphoblastic leukemia, 4 cases of aplastic anemia, and 4 cases of myelodysplastic syndrome. Classification by aGVHD severity: there were 27 cases (90%) of Ⅱ-Ⅳ degree aGVHD and 11 cases (36.7%) of Ⅲ-Ⅳ degree aGVHD. Ruxolitinib in combination with low-dose glucocorticoid treatment yield responses in 28 (93.3%) patients, of which 27 (90%) achieved complete remission (CR), while 1 (3.3%) showed partial remission (PR). One patient (3.3%) had no response (NR), and 1 patient (3.3%) exhibited progressed disease (PD). Overall survival (OS) at 1 year of transplantation was 73.9% (95%CI 49.5% to 87.7%), progression-free survival (PFS) was 93.3% (95%CI 75.9% to 98.3%), non-relapse mortality (NRM) was 20.6% (95%CI 7.9% to 47.4%), and median survival time was 27.6 months. Conclusion: Ruxolitinib combined with low-dose hormones is safe and effective in the treatment of aGVHD after allo-HSCT.

Surface plasmon resonance （SPR） sensor is an optical detection technique enables real-time and dynamic monitoring of biological samples. SPR-based biosensors have remarkable characteristics such as label-free detection and high sensitivity, making them important tools for studying molecular interactions. The recognition element, which plays a critical role in SPR sensors,which could specifically identify and capture of target analytes, closely influencing the selectivity performance of the sensor. The progress on SPR sensors in pharmaceutical research were reviewed, which focused on the application of recognition elements such as antibodies, aptamers, molecularly imprinted polymers, and metal nanoparticles.

AIM To investigate the variations in mercury dissolution from HgS-containing traditional medicines in three kinds of simulated gastrointestinal dissolution media.METHODS 39 batches of 15 types of HgS-containing traditional medicines were collected,total mercury content and dissolved mercury concentrations in simulated gastric fluid,simulated intestinal fluid,and L-cysteine-containing simulated intestinal fluid were measured.The maximum daily intake of total mercury and soluble mercury was calculated based on the maximum daily clinical dosage.RESULTS Among the 15 types of medicines,the maximum daily intake of total mercury varied by 156 times,the daily intake of soluble mercury varied by 3 502 times in simulated gastric fluid,313 times in simulated intestinal fluid,and 10 663 times in L-cysteine-containing simulated intestinal fluid,approximately.CONCLUSION For the 15 types of HgS-containing traditional medicines,the daily maximum intake of soluble mercury showed greater variations than that of total mercury.Soluble mercury concentration is more closely correlated with intestinal absorption of mercury and thus represents a more rational quality control indicator for HgS-containing traditional medicines.

AIM To study the chemical constituents from the water fraction of rhizoma of Smilax trinervula Miq.and their biological activities.METHODS Polyamide,silica gel,Sephadex LH-20,ODS and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT mothod,and the inhibitory activities on α-glucosidase were determined by PNPG method.RESULTS Eleven compounds were isolated and identified as tyrosine(1),uridine(2),2-(2',3',4'-trihydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(3),2-(1',2',3',4'-tetrahydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(4),2-(1',2',3',4'-tetrahydroxybutyl)-5-(2",3",4"-trihydroxybutyl)-pyrazine(5),uracil(6),2-(1',2',3',4'-tetrahydroxybutyl)-5-(1",2",3",4"-tetrahydroxybutyl)-pyrazine(7),dioscin(8),shikimic acid(9),pyrazine(10),3,4-dihydroxyphenyethyl alcohol 8-O-β-D-glycopyranoside(11).The IC50 values of compounds 8 to human breast cancer cell MCF-7 was(2.36±0.26)μg/mL,and the IC50 values of compounds 3-5 and 7 to α-glucosidase were(1.54±0.15)-(10.53±0.38)μg/mL.CONCLUSION Compounds 1-7,10 are isolated from Smilax genus for the first time,and compound 9,11 are first isolated from this plant.Compound 8 has anti-tumor activity,and compounds 3-5,7 have α-glucosidase inhibitory activities.

Myocardial fibrosis(MF)is the leading cause of car-diac insufficiency.Its complex pathogenesis and lack of effective treatment are key issues to be addressed in the cardiovascular field.Mitochondrial quality control system(MQC)is an impor-tant mechanism for eukaryotic cells to maintain the stability of mitochondrial form,quantity and quality.MQC disorders,which are characterized by low level of mitochondrial biogenesis,exces-sive mitochondrial oxidative stress,mitochondrial autophagy de-fect and mitochondrial dynamics disorder,play a crucial role in mediating the pathophysiological process of MF.Consequently,this article reviews the role of MQC in MF pathogenesis and the latest research,in order to better understand the molecular mech-anism of MF and provide reference for the development of more natural drugs in the future.

Objective To investigate the expression of arginase Ⅱ(ArgⅡ)in kidney tissue of rats with diabetic nephropathy(DN)and its significance in the development of DN.Methods A total of 10 male SD rats were randomly divided into the control group and the model group,with 5 rats in each group.An rat model of DN was developed by feeding with high-sugar and high-fat diet combined with intra-peritoneal injection of low-dose streptozotocin(45 mg/kg),and they were sacrificed after 11 weeks of continued feeding.The body weight,and biochemical indexes of blood and urine of rats were determined.The right kidney was weighed and histopathological examination was performed.The pathological changes of kidney tissues and protein expression of ArgⅡ and CD68+were observed,and the immunofluores-cence double staining was used to observe the distribution and expression of ArgⅡand a marker of renal macrophage activation CD68+;the protein expression of ArgⅡ,NF-κB,TNF-α and IL-6 in kidney tissues was determined by Western blot.Results Compared with the control group,the ratio of kidney weight to body weight,24-hour urine volume,24-hour urine protein,fasting blood glucose,urea nitrogen and insulin level in the model group were significantly increased(P<0.05).The renal histopathology showed that the mesangial cells of the renal glomerular were necrotic with vascular dilatation,and the renal tubular epithelial cells were steatosis and congestion.Compared with the control group,the protein expression of ArgⅡ,CD68+,NF-κB,TNF-α and IL-6 in the kidney tissues of the model group were significantly increased(P<0.05).Immunofluorescence double staining demonstrated the co-expression of ArgⅡ and CD68+in renal tissue,and the fluorescence intensities of both ArgⅡ and CD68+in the model group were significantly stronger than those in the control group(P<0.01).Conclusion The expression of ArgⅡ is increased in DN,which may be participated in the occurrence of inflammatory lesions in DN.

Objective To investigate the feasibility and accuracy of an ultrasound-based transfer learning artificial intelligence model in predicting the malignancy probability of partially cystic thyroid nodules(PCTN).Methods A retrospective analysis was conducted on 246 patients with PCTN who had definitive pathological results and were admitted to Weihai Municipal Hospital,Cheeloo College of Medicine,Shandong University from January 2021 to December 2023.Patients were randomly divided into training and test cohorts at a ratio of 7:3.Ultrasonic image features of PCTN were evaluated,and independent risk factors were identified using multivariate logistic regression analysis,with the area under the curve(AUC)subsequently calculated.Additionally,five different pre-trained models-Inception_v3,EfficientNet,VGG19,ResNet50,and DenseNet121-were selected for transfer learning after data preprocessing using the PyTorch framework in Python.The AUC values of these models were calculated and compared.Results Solid portion greater than 50%,eccentric acute angle,ill-defined margin,spiculated or microlobulated margin,rim calcification,and microcalcification exhibited statistically significant differences(P<0.05)in distinguishing between benign and malignant PCTN.The AUC value derived from these independent risk factors was 0.843.Furthermore,among the five transfer learning models evaluated,the ResNet50 model demonstrated the highest diagnostic efficiency,achieving an AUC value of 0.903 2.Conclusion The ultrasound-based transfer learning artificial intelligence model demonstrated superior performance compared to traditional ultrasound image evaluation methods,enabling accurate prediction of the nature of PCTN and thereby reducing unnecessary ultrasound-guided fine needle biopsies.

This study was aimed at providing basic data for the control and prevention of Yersinia enterocolitica(Ye)infections.Ye isolates from stool samples collected from patients with diarrhea in a Beijing district between January 2019 and June 2024 were studied.Basic patient information and stool samples were collected,and quantitative polymerase chain reaction(qPCR)was applied to enriched cultures.Further analyses included virulence gene detection,whole-genome sequencing,and drug resistance detection.The detection rate of Ye was 0.76%(11/1 439),according to culture methods,thus yielding 12 Ye strains from distinct patients:11 isolated during the study period and 1 from 2017.The 12 Ye positive patients were 6-41 years of age,and their clinical presentations predominantly featured watery stools(66.67%,8/12)and loose stools(33.33%,4/12).The frequencies of nausea,vomiting,and fever were 41.67%(5/12),41.67%(5/12),and 8.33%(1/12),respectively.The drug resistance rates of Ye to TET,AMP,and NAL were 50.00%(6/12),33.33%(4/12),and 25.00%(3/12),respectively.One Ye strain exhibited multidrug resistance to ETP,MEM,TET,CIP,NAL,and AMP.According to qPCR detection of five common virulence genes,two Ye strains were identified as ystA+/ystB-type(ystA+/ystB-/ail+/yadA+/virF+),whereas ten strains were identified as ystA-/ystB+type(ystA-/ystB+/ail-/yadA-/virF-).VFDB database analysis based on genome sequences indicated that 12 Ye strains carried an average of 11 key virulence genes associated with adhesion,invasion,protease activity,and flagellar movement,and predicted 106 virulence genes and 12 virulence gene profiles.Only the two ystA+/ystB-Ye strains contained elements related to the TTSS and ABC transporter function.Detection of ystA-/ystB+Ye in stool isolation and culture of diarrhea cases might potentially have been missed in some cases,thus highlighting the importance of fluorescence PCR screening of fecal growth solutions to enhance isolation efficiency.Moreover,our findings revealed the genetic diversity of Ye isolated from diarrhea cases,thereby indicating the presence of multiple types of virulence genes within this pathogen.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective:To analyze the clinical value of delayed solidification of cement at freezing point combined with establishment of cement channels in the treatment of further leakage of cement in percutaneous kyphoplasty (PKP).Methods:A retrospective analysis was performed for the medical records of 261 patients with osteoporotic vertebral fracture in the thoracolumbar segment who underwent PKP treatment in Beijing Puren Hospital from April 2019 to April 2023. According to the method of dealing with PKP cement leakage, it was divided into freezing point group (using bone cement combined with cement channel reconstruction treatment at freezing point temperature) and temperature gradient group (using temperature gradient method). There were 128 cases in the freezing point group, including 37 males and 91 females, aged 75.57±4.60 years (range, 65-85 years), and fracture locations were 18 cases in T 10, 30 cases in T 11, 44 cases in T 12, 23 cases in L 1 and 13 cases in L 2. There were 133 cases in the temperature gradient group, including 36 males and 97 females, aged 75.66±4.51 years (range, 65-85 years), and fracture locations were 17 cases in T 10, 32 cases in T 11, 51 cases in T 12, 22 cases in L 1, and 11 cases in L 2. The intraoperative blood loss, operation time, intravertebral cement area, cement leakage area, cement leakage area increase, cement bolus time and incidence of injection difficulty, as well as the pain visual analogue scale (VAS), Oswestry disability index (ODI), kyphosis angle, the height of the anterior edge of the injured vertebral body and the difference between it before and after surgery were compared. Results:All patients were followed up for 3 consecutive months. The intraoperative blood loss and initial cement leakage area were 9.48±2.64 ml and 32.56±7.05 mm 2 in the freezing point group and 9.04±2.25 ml and 32.86±7.00 mm 2 in the temperature gradient group, respectively, and the difference was not statistically significant ( P>0.05) ; The operation time, the area of bone cement in the vertebral body, the final leakage area of bone cement, and the increase of bone cement leakage in the freezing point group were 55.08±4.13 min, 1 175.45±117.11 mm 2, 35.84±8.67 mm 2, and 0.00(0.00, 13.32) mm 2, respectively, and the temperature gradient group were 53.02±3.96 min, 823.70±144.79 mm 2, and 73.38±29.16 mm 2 and 44.39(20.13, 56.61) mm 2, the differences were statistically significant ( P<0.05). The height of the anterior edge of the vertebral body was 21.54±2.06 mm and 21.24±2.33 mm immediately after surgery and 3 months after surgery in the freezing point group, which were higher than those in the temperature gradient group 21.10±1.60 mm and 18.92±1.51 mm, respectively, and the difference was statistically significant ( P<0.05). The VAS scores of the freezing point group were 2.29±0.62 and 1.03±0.66 points, ODI were 23.20%±3.97%, 10.43%±4.33%, and the kyphosis angles were 9.09°±2.80° and 9.44°±2.93°, respectively, which were lower than those of the temperature gradient group (4.11±0.79 and 2.79±0.65 points), ODI (35.97%±6.42%, and 23.73%±5.72%), and the kyphosis angles (10.24°±2.33° and 13.22°±2.56°), the differences were statistically significant ( P<0.05). The operating time of bone cement in the freezing point group was 10.89±2.35 min, which was longer than that in the temperature gradient group 5.77±0.52 min, and the difference was statistically significant ( t=24.021, P<0.001). The incidence of cement injection difficulty was 0 in the freezing point group and 27.1% (36/133) in the temperature gradient group. Conclusion:The establishment of bone cement combined with bone cement channel at freezing point temperature can effectively prolong the bolus time of bone cement and reduce the re-leakage of bone cement, which is conducive to increasing the injection volume and distribution area of bone cement in the vertebral body, effectively reducing the amount of bone cement leakage and obtaining better clinical efficacy.