OBJECTIVE: To investigate the clinical characteristics, treatment and prognosis of adult AML patients with NUP98::HOXA9 fusion gene. METHODS: From May 2017 to October 2023， among 2 113 AML patients who visited the Hematology Department of our hospital, patients with NUP98 rearrangements were screened. The clinical characteristics, chromosome karyotypes, immunophenotypes, gene mutations, treatment efficacy and prognosis of the patients with NUP98::HOXA9 positive were analyzed. RESULTS: Among the 2 113 AML patients, there were 18 cases with NUP98 rearrangement, including 14 NUP98::HOXA9 positive cases, with a detection rate of 0.66% (14/2 113). The median age of the NUP98::HOXA9 positive patients was 42.5 (23-64) years old. The most common chromosome karyotype was t(7; 11)(p15; p15). The immunophenotypes of all patients expressed CD13, CD33, CD117 and CD38, and most patients expressed CD34 and cMPO, while only a few expressed HLA-DR. Second-generation sequencing (NGS) was performed to detect genetic mutations associated with leukemia in all 14 patients, and the genes exhibiting a high frequency of mutation were WT1 (10/14), TET2 (7/14), and FLT3-ITD (6/14). Additionally, mutations were also observed in KRAS/NRAS, IDH1, and KIT. Of the 13 patients who received treatment, 9 achieved complete remission (CR), and all 3 patients who received azacytidine(AZA)+ venetoclax (VEN) regimen achieved CR after the first course of treatment. Within this cohort, 6 patients were classified as relapsed/refractory (6/13). 4 patients underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT), of which two achieved long-term survival. The median follow-up time was 12 (2.1-65.0) months, while the median overall survival (OS) and relapse-free survival (RFS) were recorded as 11.4 months and 9.6 months, respectively. CONCLUSION The most common type of NUP98 rearrangement in adults AML patients is NUP98::HOXA9 , which is often accompanied by somatic mutations in WT1, TET2, and FLT3-ITD. These patients are prone to relapse, have short survival time, and generally face poor prognoses. Hopefully, utilization of the AZA+VEN regimen is anticipated to enhance the rate of induced remission in the patients, and some patients may prolong their survival through allo-HSCT. However, more effective treatment methods are still needed to improve the overall prognosis of these patients.
Humans ; Adult ; Leukemia, Myeloid, Acute/genetics* ; Middle Aged ; Prognosis ; Nuclear Pore Complex Proteins/genetics* ; Oncogene Proteins, Fusion/genetics* ; Mutation ; Male ; Female ; Young Adult ; Homeodomain Proteins/genetics*

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To evaluate the role of hippocampal activating transcription factor 5 (ATF5) in cognitive impairment induced by neuropathic pain and the relationship with mitochondrial unfolded protein response(mtUPR) in mice.Methods:This study was conducted in 2 parts. Experiment Ⅰ Twenty-four SPF healthy male C57BL/6 mice, aged 6-8 weeks, weighing 20-25 g, were divided into 2 groups ( n=12 each) using a random number table method: sham operation group (S1 group) and neuropathic pain group (NP group). Neuropathic pain was induced by chronic constriction injury to the sciatic nerve. The mechanical paw withdrawal threshold (MWT) and thermal paw withdrawal latency (TWL) were measured before developing the model and at 7, 14, 21 and 28 days after developing the model. Mouse cognitive function was assessed using the novel object recognition test from 30-31 days after developing the model. After the end of the novel object recognition test, mice were sacrificed and the hippocampal CA1 region was harvested for determination of the expression of ATF5 (by Western blot) and the expression of ATF5 in neurons, microglia and astrocytes (by immunofluorescence double staining). Experiment Ⅱ Thirty-six SPF healthy male C57BL/6 mice, aged 6-8 weeks, weighing 20-25 g, were divided into 3 groups ( n=12 each) using a random number table method: sham operation group (S2 group), neuropathic pain + ATF5 up-regulation group (NA group), and neuropathic pain + empty virus group (NE group). On day 14 after developing the model, a virus that specifically up-regulated ATF5 expression in neurons and empty virus were injected into the hippocampal CA1 region. The MWT and TWL were measured at days 28 and 35 after developing the model. The novel object recognition test was performed on day 36 after developing the model to evaluate the cognitive function. After the end of the behavioral test, mice were sacrificed and the hippocampal CA1 region was harvested for detection of the expression of ATF5 and mtUPR marker proteins (Lon protease [LONP1] and heat shock protein 60 [HSP60]) by Western blot. Results:Experiment Ⅰ Compared with S1 group, no statistically significant change was found in the MWT and TWL before developing the model ( P>0.05), the MWT and TWL were significantly decreased on days 7, 14, 21 and 28 after developing the model, the discrimination index (DI) was decreased at day 31 after developing the model, the expression of ATF5 was down-regulated, the expression of ATF5 in neurons was down-regulated ( P<0.05), and no statistically significant change was found in the expression of ATF5 in mircrolia and astrocytes in NP group ( P>0.05). Experiment Ⅱ Compared with S2 group, the MWT and TWL were significantly decreased on days 28 and 35 after developing the model in NE group and NA group, DI was decreased, and the expression of ATF5, LONP1 and HSP60 was down-regulated in NE group ( P<0.05), and no significant change was found in NA group ( P>0.05). Compared with NE group, no significant change was found in the MWT and TWL in NA group ( P>0.05), DI was significantly increased, and the expression of ATF5, LONP1 and HSP60 was up-regulated in NA group ( P<0.05). Conclusions:Down-regulated ATF5 in the hippocampus is involved in the process of cognitive impairment caused by neuropathic pain, and the mechanism may be related to the inhibition of mtUPR.

Objective:To assess the clinical utility of vector flow mapping（VFM）for evaluating left ventricular wall shear stress（WSS）in individuals with non-obstructive hypertrophic cardiomyopathy（nHCM）.Methods:Forty patients with non-obstructive HCM（nHCM）and 46 healthy volunteers in Tangdu Hospital of Air Force Medical University from May 2020 to September 2023 were enrolled prospectively in this study. The left ventricular WSS of each of 18 segments was measured and analyzed by VFM during rapid filling phase（T1），slow filling phase（T2），isovolumetric contraction phase（T3）and rapid ejection phase（T4）.Results:① WSS decreased gradually from basal to apical segments in control group，while there was no such change pattern in nHCM group. ② Diastolic phase：When compared to the control group，the nHCM group demonstrated significantly increased WSS across all segments of the inferoseptal regions，the basal anteroseptal segment，and the middle and apical inferior segments during the T1 stage. Additionally，at the T2 stage，the WSS was significantly higher in the nHCM group across all segments of the inferoseptal and anteroseptal regions，the basal anterolateral segment，and the apical inferolateral and anterior segments（all P<0.05）. Conversely，during the T1 stage，the basal anterolateral segment，basal inferolateral segment，and the middle and apical anteroseptal segments，as well as during the T2 stage，the basal and middle inferior segments，exhibited lower WSS values compared to the control group，with these differences being statistically significant（all P<0.05）. ③Systolic Phase：During the T3 stage，the WSS values in all segments of the anteroseptal and anterolateral regions，as well as the apical inferior and anterior segments，were significantly elevated in the nHCM group compared to the control group（all P<0.05）.At the T4 stage，WSS in each segment of the inferolateral and inferior regions，as well as the basal and middle anterior segments，was significantly elevated in the nHCM group compared to the control group（all P<0.01）. Conversely，during the same stage，the WSS values in the basal inferolateral segment，the basal and middle anterolateral segments，and the basal and middle anteroseptal segments were significantly lower in the nHCM group than in the control group，with all differences reaching statistical significance（all P<0.01）.Regarding global WSS，the left ventricular global WSS in the nHCM group was significantly higher than that in the control group at both the T2 and T3 stages（all P<0.001）. Furthermore，the global WSS at the T3 stage was negatively correlated with left ventricular end-systolic volume，end-diastolic volume，and left ventricular stroke volume（ r=-0.226， P=0.036； r=-0.345， P=0.001； r=-0.303， P=0.005）. Conclusions:Significant differences in WSS are observed between patients with nHCM and control groups at various phases. WSS may serve as an early indicator of changes in cardiac function in nHCM patients.

AIM To optimize the cellulase-assisted ultrasound extraction process for total flavonoids from Plumbago zeylanica L.,and to evaluate their anti-oxidant activity.METHODS With extraction time,liquid-solid ratio,cellulase addition amount,extraction temperature and ultrasonic power as influencing factors,extraction rate of total flavonoids as an evaluation index,the extraction process was optimized by response surface method on the basis of single factor test.Subsequently,The scavenging rates of extract on DPPH,ABTS and OH free radicals were determined.RESULTS The optimal conditions were determined to be 34∶1 for liquid-solid ratio,3％for cellulase addition amount,51 ℃ for extraction temperature,38 min for extraction time,and 400 W for ultrasonic power,the extraction rate of total flavonoids was(33.411±0.97)％.The IC50 values of three free radicals were 0.13,0.042,3.29 mg/mL,respectively.CONCLUSION This reasonable and reliable method can be used for the cellulase-assisted ultrasound extraction of total flavonoids from P.zeylanica with strong anti-oxidant activity.

Osteoporotic distal radius fracture (ODRF), a common fragility fracture in elderly patients, poses a significant threat to patients′ life and health due to its high incidence and disability rate. Both traditional Chinese medicine and Western medicine have accumulated extensive clinical experience in the diagnosis, treatment and rehabilitation of ODRF. However, there is currently a lack of specific guideline on how to effectively integrate the strengths of the two medical systems. To standardize the collaborative diagnosis and treatment of ODRF using integrated traditional Chinese and Western medicine, the Clinical Practice Guideline Working Group for the clinical practice guideline for the diagnosis and treatment of osteoporotic distal radius fracture through integrated traditional Chinese medicine and Western medicine was established in September 2024, led by the Third Affiliated Hospital of Yunnan University of Chinese medicine (Kunming Hospital of Chinese Medicine) with the participation of many medical institutions across China. Protocol for the guideline was then formulated to detail each key aspect in the development of the guideline and explain the related procedures, aiming to ensure a standardized, orderly and transparent development.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.