ObjectiveTo construct a risk prediction model for frequent acute exacerbations of chronic obstructive pulmonary disease （COPD） under disease-syndrome combination， thus providing decision support for precise clinical intervention. MethodsA total of 2 029 patients with acute exacerbations of COPD admitted to the First Affiliated Hospital of Anhui University of Chinese Medicine from January 2020 to August 2024 were retrospectively included. These patients were classified into groups of frequent acute exacerbations （≥2 times/year） and infrequent acute exacerbations （<2 times/year） according to the hospitalization times per year. Risk factors were screened by LASSO regression combined with logistic regression， and a nomogram model was constructed. The model performance was assessed based on the area under the curve （AUC）， calibration curves， and decision curve analysis （DCA）. ResultsThe differences in baseline characteristics between the frequent acute exacerbations group （1 196 cases） and infrequent acute exacerbations group （833 cases） were not statistically significant. LASSO regression combined with multivariate logistic regression screened the following independent risk factors： body mass index （BMI）， hospitalization days， number of smoking years， place of residence， use of noninvasive ventilators， oxygen-demanding therapy， liver cirrhosis， use of systemic glucocorticosteroids， and traditional Chinese medicine syndrome （phlegm and stasis obstructing the lung）. The nomogram model showed good discrimination and calibration in both the training set （AUC=0.748） and validation set （AUC=0.774）. ConclusionThe risk prediction model for frequent acute exacerbations of COPD， integrating traditional Chinese medicine syndrome， constructed in this study has high accuracy. It can provide a scientific basis for early clinical identification of high-risk patients and individualized intervention.

Objective: To assess the awareness and associated factors of wild mushroom poisoning among students in Guizhou Province, so as to provide a scientific foundation for wild mushroom poisoning prevention and control among students. Methods: By a multi stage stratified cluster random sampling method, 1 162 students from Guizhou Province were selected in May 2024. The questionnaire survey was administered to evaluate knowledge regarding wild mushroom poisoning. Data were analyzed employing the χ 2 test and Logistic regression model. Results: Among the nine questions assessing awareness of wild mushroom poisoning, only three had the awareness rate exceeding 70%. Binary Logistic regression analysis revealed that students who "actively learn about the prevention of wild mushroom poisoning" ( OR=0.48, 95%CI =0.26-0.92) and "spread knowledge about wild mushroom poisoning to others" ( OR=0.47, 95%CI =0.33-0.69) scored higher on the wild mushroom poisoning knowledge questions ( P <0.05). Conversely, students with a habit of consuming wild mushrooms ( OR=1.52, 95%CI =1.15-2.02) scored lower ( P < 0.05 ). 42.3% of the students suggested that scientific dissemination and publicity about wild mushrooms should be intensified. Conclusions The awareness rate of wild mushroom poisoning knowledge among students in Guizhou Province requires further attention. Comprehensive knowledge should be disseminated systematically through various channels to further improve students awareness of the prevention and control of wild mushroom poisoning.

AIM: To explore the efficacy of 0.05% cyclosporine A combined with olopatadine eye drops in treating allergic conjunctivitis-related dry eye disease.METHODS: A total of 63 patients(63 eyes)with allergic conjunctivitis-related dry eye disease in the People's Hospital of Guangxi Zhuang Autonomous Region from August 2022 to April 2023 were enrolled and randomly divided into control group(n=33)and observation group(n=30). The patients of the control group were administrated with 0.1% olopatadine eye drops and 0.3% sodium hyaluronate eye drops, while the observation group was administrated with 0.1% olopatadine eye drops and 0.05% cyclosporine A eye drops. The ocular surface disease index(OSDI), total ocular symptom score(TOSS), conjunctival congestion score, conjunctival papillae and follicle score, Schirmer I test(SⅠt), tear meniscus height(TMH), meibomian gland secretion ability and property score, meibomian gland loss area score, corneal fluorescein staining(CFS), tear film break-up time(BUT), noninvasive first tear film break-up time(NIBUTf), noninvasive average tear film break-up time(NIBUTav)before and after treatment and the drug safety during the treatment period of both groups of patients were evaluated.RESULTS: After treatment, OSDI, TOSS, conjunctival congestion score, conjunctival papillae and follicle score, SⅠt, TMH, meibomian gland secretion ability score and property score, CFS, BUT, NIBUTf, and NIBUTav of the observation group showed improvements compared with those before treatment(all P<0.017). Among these, OSDI, TOSS, conjunctival congestion score, conjunctival papillae and follicle score, BUT, NIBUTf, and NIBUTav demonstrated significant improvement compared with the control group(all P<0.05). There was no statistically significant difference in meibomian gland loss area score between the two groups before and after treatment(P>0.05). During the treatment period, there were no local or systemic adverse reactions.CONCLUSION: The combined use of 0.05% cyclosporine A and olopatadine eye drops can significantly improve ocular discomfort symptoms of patients with dry eye disease associated with allergic conjunctivitis, such as red eyes, itchy eyes and foreign body sensation, promote tear film stability and have high safety.

Objective To investigate the effect and mechanism of dabrafenib （DAB） combined with tremelimumab （TREM） on melanoma. Methods The effects of DAB combined with TREM on cell viability, cytotoxicity and cell migration of A375 cells were evaluated by Cell Counting Kit-8 （CCK-8） method, lactate dehydrogenase （LDH） method and scratch assay. The levels of reactive oxygen species （ROS）, adenosine triphosphate （ATP）, malondialdehyde （MDA）, and superoxide dismutase （SOD） were detected to evaluate the effects of combined drugs on oxidative stress and energy metabolism. In addition, A375 tumor-bearing nude mice model was used to evaluate the inhibitory effect of the combined treatment on tumor growth in vivo, and the degree of cell apoptosis and cell proliferation in tumor tissues were analyzed by terminal deoxynucleotidyl transferase-mediated dutP Nick end labeling （TUNEL） and proliferating cell nuclear antigen （PCNA） immunohistochemical staining. Results The combined treatment significantly inhibited the survival rate and migration ability of A375 cells and enhanced the cytotoxicity. The combined intervention also significantly increased ROS level, decreased ATP, SOD and MDA levels. It effectively inhibited tumor growth in tumor-bearing nude mice, increased the apoptosis rate of tumor cells and inhibited cell proliferation. Conclusion DAB combined with TREM may improve the therapeutic effect of melanoma by enhancing oxidative stress, inhibiting energy metabolism, and promoting cell apoptosis. This combination therapy may provide a new therapeutic strategy to overcome the limitations of singledrug therapy.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

The p21-activated kinase 4 (PAK4), a key regulator of malignancy, is negatively correlated with immune infiltration and has become an emergent drug target of cancer therapy. Given the lack of high efficacy PAK4 inhibitors, we herein reported the identification of a novel inhibitor 13 bearing a tetrahydrobenzofuro[2,3-c]pyridine tricyclic core and possessing high potency against MIA PaCa-2 and Pan02 cell lines with IC₅₀ values of 0.38 and 0.50 μmol/L, respectively. This compound directly binds to PAK4 in a non-ATP competitive manner. In the mouse Pan02 model, compound 13 exhibited significant tumor growth inhibition at a dose of 100 mg/kg, accompanied by reduced levels of PAK4 and its phosphorylation together with immune infiltration in mice tumor tissue. Overall, compound 13 is a novel allosteric PAK4 inhibitor with a unique tricyclic structural feature and high potency both in vitro and in vivo, thus making it worthy of further exploration.

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.

Objective To observe and analyze the influence of the improved ultra-low temperature storage box on the quality of fresh frozen plasma(FFP).Methods A total of 80 qualified whole blood samples(400 mL,O type not includ-ed)collected from July to November in 2023 were selected,and were divided into 4 groups,with 20 samples in each group.Group A:quick-frozen in a traditional low temperature box for 1 hour and then stored in a-30℃cold storage;Group B:quick-frozen in the flat freezer for 1 hour and then stored in a-30℃cold storage;Group C:quick-frozen in a newly im-proved ultra-low temperature storage box for 1 hour and stored in a-30℃cold storage;Group D:quick-frozen in a new im-proved ultra-low temperature storage box for 12 hours and stored in a-30℃cold storage.The contents of FⅧand fibrinogen(Fg)in four groups were detected.Results The contents of FⅧin group B,C and D were significantly higher than those in group A,with statistical difference(P＜0.05),but with no statistical difference among gourp B,C and D(P＞0.05),and no statistical difference in the contents of Fg was found among the four groups(P＞0.05).Conclusion The improved ultra-low temperature storage box is superior to the traditional low temperature box in preparing FFP,and there is no obvious difference between the improved ultra-low temperature storage box and the flat-plate quick freezer.However,the improved ultra-low temperature storage box can make the process of preparing FFP more flexible and improve the efficiency of compo-nent preparation.

OBJECTIVE To establish the fingerprint of Lianhua Qingwen capsule(LHQW) with the HPLC method, and to evaluate the quality by combining with chemical pattern recognition method. METHODS The chromatographic separation was performed on an Agilent Zorbax SB-C18(250 mm×4.6 mm, 5 μm) column with 0.1% phosphoric acid(A)-acetonitrile(B) as the mobile phase for the gradient elution. The detection wavelength was set at 207 nm. The flow rate was set at 1.0 mL·min–1 and the column temperature was 30 ℃. Similarity evaluation, hierarchical clustering analysis(HCA), radar plot analysis, principal component analysis(PCA), and orthogonal partial least-squares discrimination analysis(OPLS-DA) were used for the further assessment of 13 batches of LHQW samples. RESULTS The fingerprint of LHQW was established with 40 common peaks, in which 10 common peaks were identified, and the similarities of 13 batches of LHQW samples were 0.947–1.000. By applying chemical pattern recognition methods such as HCA, and OPLS-DA, 13 batches of samples were classified into three clusters, and the results of classification were correlated with the production date. And 8 major chemical markers causing quality differences were screened. CONCLUSION With good reproducibility and stability, this method could provide the reference for the quality evaluation of LHQW．

Both morbidity and mortality of gastric cancer are in the front rank among malignant tumors.At present,enhanced CT is served as an important imaging method for preoperative diagnosis and assessment of gastric cancer,but it is mostly based on morphological evaluation and unable to perform quantitative analysis.The functional imaging technology represented by energy spectral CT and CT perfusion imaging has a variety of quantitative parameters,which is expected to make up for the shortcomings of conventional CT.The review introduces the basic principles of energy spectral CT and CT perfusion imaging,and summarizes their applications in the diagnosis,pathological classification,grading,staging and efficacy prediction of gastric cancer,aiming to improve the understanding of functional CT imaging for the pretreatment assessment in gastric cancer.