A 51-year-old male presented with nasal obstruction, followed by progressive hearing loss and blurred vision. Imaging identified space-occupying lesions in the paranasal sinuses, orbits, and paraspinal regions, while laboratory tests confirmed positive anti-proteinase 3 anti-neutrophil cytoplasmic antibody(PR3- ANCA) immunoglobulin G (IgG)and markedly elevated serum IgG4. Despite treatment with corticosteroids, immunosuppressants, and radiotherapy, the patient exhibited steroid dependency with relentless disease progression. Following multidisciplinary consultation, a diagnosis of inflammatory myofibroblastic tumor (IMT) coexisting with ANCA- associated vasculitis (AAV) was favored, though IgG4-related disease remained a critical differential. Ultimately, profound immunosuppression precipitated a severe herpesvirus infection, leading to disseminated intravascular coagulation and multiple organ dysfunction syndrome. This case underscores the rarity and diagnostic complexity of concurrent IMT and AAV, highlights the therapeutic dilemma of balancing primary disease control against fatal opportunistic infections, and emphasizes the critical role of multidisciplinary collaboration in the diagnosis and treatment of complex diseases.

Current experimental and computational methods have limitations in accurately and efficiently classifying ion channels within vast protein spaces. Here we have developed a deep learning algorithm, GPT2 Ion Channel Classifier (GPT2-ICC), which effectively distinguishing ion channels from a test set containing approximately 239 times more non-ion-channel proteins. GPT2-ICC integrates representation learning with a large language model (LLM)-based classifier, enabling highly accurate identification of potential ion channels. Several potential ion channels were predicated from the unannotated human proteome, further demonstrating GPT2-ICC's generalization ability. This study marks a significant advancement in artificial-intelligence-driven ion channel research, highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data. Moreover, it provides a valuable computational tool for uncovering previously uncharacterized ion channels.

Current experimental and computational methods have limitations in accurately and efficiently classi-fying ion channels within vast protein spaces.Here we have developed a deep learning algorithm,GPT2 Ion Channel Classifier(GPT2-ICC),which effectively distinguishing ion channels from a test set con-taining approximately 239 times more non-ion-channel proteins.GPT2-ICC integrates representation learning with a large language model(LLM)-based classifier,enabling highly accurate identification of potential ion channels.Several potential ion channels were predicated from the unannotated human proteome,further demonstrating GPT2-ICC's generalization ability.This study marks a significant advancement in artificial-intelligence-driven ion channel research,highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data.Moreover,it provides a valuable computational tool for uncovering previously uncharacterized ion channels.

Objective:To analyze the depressive symptoms of physical and mental workers and the impact of their behavior and lifestyle on their depressive symptoms.Methods:In August 2022, a cross-sectional study design was adopted to select 553 workers as research subjects using cluster sampling. General demographic information, health-related behaviors and lifestyles were collected, and their depressive symptoms were evaluated using the Chinese version of the Patient Health Questionnaire 9 (PHQ-9). The differences in general demographic information, health-related behaviors and lifestyles between physical and mental workers were analyzed, and logistic regression was used to analyze the influencing factors of depressive symptoms in occupational populations.Results:Among the 553 subjects, 317 were physical workers (57.32%) and 236 were mental workers (42.68%). Statistically significant differences were observed between the two groups in terms of education level, monthly income, smoking rate, regular physical exercise rate and appropriate sleep time rate ( P<0.05). The score and the detection rate of depression symptoms among physical workers were (9.67±2.75) points and 20.82% (66/317), respectively, which were higher than those of mental workers [(8.34±2.18) points, 12.71% (30/236) ] ( t=6.13, χ 2=6.20, P<0.05). The results of logistic regression analysis showed that smoking, regular physical exercise, appropriate sleep time and mental work were influencing factors of depressive symptoms among the occupational population ( OR=1.592, 95% CI: 1.316-1.825; OR=0.659, 95% CI: 0.416-0.830; OR=0.502, 95% CI: 0.257-0.717; OR=0.839, 95% CI: 0.522-0.967; P<0.05) . Conclusion:The depressive symptoms of physical workers are more serious than those of mental workers. Low education level, not frequently participating in physical exercise, smoking and sleep disorder are potential risk factors that affect the depressive symptoms of the occupational population.

Objective:To analyze the depressive symptoms of physical and mental workers and the impact of their behavior and lifestyle on their depressive symptoms.Methods:In August 2022, a cross-sectional study design was adopted to select 553 workers as research subjects using cluster sampling. General demographic information, health-related behaviors and lifestyles were collected, and their depressive symptoms were evaluated using the Chinese version of the Patient Health Questionnaire 9 (PHQ-9). The differences in general demographic information, health-related behaviors and lifestyles between physical and mental workers were analyzed, and logistic regression was used to analyze the influencing factors of depressive symptoms in occupational populations.Results:Among the 553 subjects, 317 were physical workers (57.32%) and 236 were mental workers (42.68%). Statistically significant differences were observed between the two groups in terms of education level, monthly income, smoking rate, regular physical exercise rate and appropriate sleep time rate ( P<0.05). The score and the detection rate of depression symptoms among physical workers were (9.67±2.75) points and 20.82% (66/317), respectively, which were higher than those of mental workers [(8.34±2.18) points, 12.71% (30/236) ] ( t=6.13, χ 2=6.20, P<0.05). The results of logistic regression analysis showed that smoking, regular physical exercise, appropriate sleep time and mental work were influencing factors of depressive symptoms among the occupational population ( OR=1.592, 95% CI: 1.316-1.825; OR=0.659, 95% CI: 0.416-0.830; OR=0.502, 95% CI: 0.257-0.717; OR=0.839, 95% CI: 0.522-0.967; P<0.05) . Conclusion:The depressive symptoms of physical workers are more serious than those of mental workers. Low education level, not frequently participating in physical exercise, smoking and sleep disorder are potential risk factors that affect the depressive symptoms of the occupational population.

Objective:To analyze the characteristics of smoking network among smokers in Kunming smoking cessation outpatient service.Methods:A multicenter, cross-sectional study was carried out, and smoking cessation outpatients from 8 tertiary hospitals (the Second Affiliated Hospital of Kunming Medical University, the First Affiliated Hospital of Kunming Medical University, Yan′an Hospital, Ganmei Hospital, the 920 Hospital of the Chinese People′s Liberation Army Joint Logistic Support Force, Kunming First People′s Hospital, the First People′s Hospital of Yunnan Province and the Second People′s Hospital of Yunnan Province) in Kunming, Yunnan Province were included to receive a questionnaire survey. The questionnaire mainly consisted of four parts: (1) demographic characteristics of smokers; (2) the specific situation of smoking; (3) social support network; (4) smoking network. A total of 360 questionnaires were distributed in this survey, 351 were recovered, and 351 were valid, the collected data from valid questionnaire were statistically analyzed to analyze the social demographic characteristics, smoking status and smoking network characteristics of smokers.Results:In this survey, the demographic characteristics of the 351 patients in the smoking cessation clinic were as follows: there were 342 male cases (97.4%), 249 cases (70.9%) were Han, 233 patients (66.4%) were non-religious, there were 236 cases (67.2%) with college degree or above, and 51 cases (14.5%) were unemployed. The analysis of smoking status showed that 167 patients (47.6%) maintained daily smoking, 247 patients (70.4%) had plans to quit smoking, at least one parent of 258 patients (73.5%) had a history of smoking, 188 patients (53.6 %) smoked at home. In the smoking network of the surveyed patients, there were 304 patients (86.6%) who smoked together with two or more people, and more than 90 percent of the patients smoked with the same sex.Conclusions:The smoking network of patients in Kunming smoking cessation clinic is small, and a third of smokers are friends. It is suggested to use the characteristics of smoking network to carry out smoking cessation intervention activities, so as to improve the success rate of smoking cessation.

Enterotoxigenic Escherichia coli（ETEC）infection can induce watery diarrhea，leading to dehydration，electrolyte disturbance，and even death in severe cases. Recombinant B subunit/inactivated whole-cell cholera（rBS/WC）vaccine is effective in preventing ETEC infectious diarrhea. On the basis of the latest evidence on etiology and epidemiology of ETEC，as well as the effectiveness，safety，and health economics of rBS/WC vaccine，National Clinical Research Center for Child Health（The Children’s Hospital，Zhejiang University School of Medicine）and Zhejiang Provincial Center for Disease Control and Prevention invited experts to develop expert consensus on rBS/WC vaccine in prevention of ETEC infectious diarrhea. It aims to provide the clinicians and vaccination professionals with guidelines on using rBS/WC vaccine to reduce the incidence of ETEC infectious diarrhea.

AIM:To explore the effect of HbA1c level in the patients with type 2 diabetes mellitus (T2DM) on the rheological properties of erythrocytes and the structure of hemoglobin (Hb).METHODS:The patients with T2DM were classified into 3 groups:the patients with good glycaemic control (group A, HbA1c<7.0%), the patients with poor glycaemic control (group B, 7.0%≤HbA1c<9.0%) and the patients with persistent hyperglycemia (group C, HbA1c≥9.0%) .The rheological properties of a single living erythrocyte were analyzed by the techniques of static imaging and anal -ysis.Ultraviolet-visible spectroscopy was used to study the structure of Hb .RESULTS: Compared with group H , the roundness effect factor (REF) of erythrocytes, which was positively related with HbA1c level, was significantly increased in groups A, B and C (P<0.05).The contact area of erythrocytes in group B and all the morphological parameters of erythrocytes in group C were significantly higher than those in group H ( P <0.05 ) .There were significant differences among groups A , B and C in deformation capacity and elastic parameters of the cell membrane ( P<0.05 ) , but with no difference in the long axis and short axis between group A and group B .Compared with group H , no obvious change in the spectral pattern and spectrum peak of Hb in groups A , B and C was observed.However, the absorbance of Hb, which showed a trend of gradual decline with the increase in HbA 1c level, in group B and group C was significantly decreased as compared with group H (P<0.01), and the Hb absorbance in group C were also lower than that in group A (P<0.05). CONCLUSION:With the increase in HbA1c level, the morphology along with the deformation function of erythrocytes in T2DM changes and declines gradually , and the structure of Hb may also change .

Objective To measure the dynamic and static frictional resistances between different self-ligating orthodontic brackets and different combination of tandem archwires.Methods On standard model the upper right quadrant Damon Q self-ligating brackets was pasted as team A,3M Smart clip self-ligating brackets as team B and Forestadent Quick 3.0 self-ligating brackets as team C respectively.Nickel-titanium archwires of 0.012 inch and 0.016 inch and two nickel-titanium archwires of 0.014 inch were applied to simulate sliding in the brackets and measure the friction changes in brackets and archwires,so as to explore the frictional resistance between different combination of the tandem archwires and different self-ligating brackets.Results When using the combination of two 0.014-inch nickel-titanium tandem archwires,the static frictional resistances was significantly different (P＜ 0.05):team A ＜team B ＜team C while the kinetic frictional resistance was also significantly different (P＜0.05):team A ＜team B ＜team C,When using the combination of 0.012-inch and 0.016-inch nickel-titanium tandem archwires,the static frictional resistances was significantly different (P＜0.05):team A＜team B＜team C,while the kinetic frictional resistance was also significantly different (P＜0.05):team A＜team B＜team C.Gonclusion There are different frictional resistance in different kind of self-ligating brackets and different combination of the tandem archwires.The combination of two 0.014-inch nickel-titanium tandem archwire applied to Forestadent Quick 3.0 self-ligating brackets has the biggest frictional resistance while the combination of 0.012-inch and 0.016-inch nickel-titanium tandem archwire applied to the Damon Q self-ligating brackets has the lowest frictional resistance,which enables the teeth to move at the fastest speed and facilitates the following use of the edgewires.

Objective: To study the effects of CTGF on the periodontal tissue remolding during orthodontic tooth movement. Methods: A mouse model of orthodontic tooth movement was established. The CTGF and NS were injected into the periodontal tissue of the first molar. HE staining, immunohistochemical staining and automatic image analysis system were used to detect the changes of periodontal tissue and the expression of VEGF. Results: The periodontal tissue remolding accompanied the over expression of VEGF during the orthodontic tooth movement. At day 7, the remolding was most active and the expression of VEGF was the highest. CTGF injection induced acceleration of periodontal remolding and up-regulating the expression of VEGF during orthodontic tooth movement, especially at day 7 and day 15 after the orthodontic force were applied. Conclusion: In the mouse model of orthodontic tooth movement, periodontal CTGF injection induces over expression of VEGF and accelerates the periodontal remodeling during orthodontic tooth movement.