Objective: To investigate the trends in mortality and life loss of gastric cancer in Wenzhou City, Zhejiang Province from 2014 to 2023, so as to provide the evidence for formulating the prevention and control strategy for gastric cancer. Methods: The surveillance on causes of death data of permanent residents in Wenzhou City were collected through the Wenzhou Chronic Disease Monitoring and Management Information System from 2014 to 2023. The crude mortality of gastric cancer was calculated, and standardized by the data from the Sixth Chinese National Population Census in 2010. The life loss were measured using potential years of life lost (PYLL) and rate of potential years of life lost (PYLLR). The characteristics of mortality and life loss of gastric cancer in different genders and age groups were described. The trends in mortality and PYLLR of gastric cancer were analyzed using the average annual percent change (AAPC). Results: Totally 17 080 deaths were reported due to gastric cancer in Wenzhou City from 2014 to 2023, accounting for 12.58% and ranking third in the order of malignant tumor deaths. The crude mortality of gastric cancer was 20.73/105, and the standardized mortality was 15.22/105, showing decreasing trends (AAPC=-3.311%, -6.470%, both P<0.05). The crude mortality of gastric cancer was 29.22/105 in men and 11.61/105 in women, with standardized mortality rates of 20.81/105 and 8.74/105 (both P<0.05). The crude mortality of gastric cancer appeared a tendency towards a rise with increasing age (P<0.05), reaching the highest rate of 225.88/105 in the group aged 80 to <85 years. The PYLL and PYLLR of gastric cancer were 107 607.50 person-years and 1.37‰. The PYLLR appeared a tendency towards a decline from 2014 to 2023, with AAPC of -6.667% (P<0.05). Conclusions The mortality and PYLLR of gastric cancer in Wenzhou City appeared a tendency towards a decline from 2014 to 2023. Men and the elderly populations were the key groups for the prevention and treatment of gastric cancer.

Background Job burnout and depressive symptoms are prevalent among occupational populations, with a close relationship between them. Sleep quality, as a potential mediating factor, significantly affects the mental health of workers. Objective To explore the relationship between job burnout, sleep quality, and depressive symptoms, and determine whether sleep quality mediates the relationship between job burnout and depressive symptoms. Methods From April 25 to May 1, 2024, this study employed cluster sampling to conduct a questionnaire survey among individuals engaged in various occupations across five cities in the Ningxia Hui Autonomous Region. The questionnaires included socio-demographic information, as well as the Chinese Maslach Burnout Inventory (CMBI), the Pittsburgh Sleep Quality Index (PSQI), and the Patient Health Questionnaire-9 (PHQ-9) for assessing burnout, sleep quality, and depressive symptoms, respectively. Out of the 4106 questionnaires distributed, a total of 3837 questionnaires were valid, and the valid recovery rate was 93.45%. The distribution among demographic variables in burnout, sleep quality and depressive symptoms were statistically analyzed. A binary logistic regression model was used for multifactor correlation analysis; Pearson correlation was used to test the correlation between burnout, sleep quality, and depressed mood. Modelling and mediated effect path mapping were performed using Amos 24.0 software. Results The postive rate of occupational burnout in the workers was 97.49% (3741/3837), the positive rate of poor sleep quality was 66.77% (2526/3837), and the positive rate of depressive symptoms was 75.68% (2904/3837). There were statistically significant differences in depressive symptoms by ages, shift types, working years, marital status, smoking habits, drinking habits, and exercising frequency (P < 0.05). The logistic model indicated that working years, drinking habits, job burnout, and overall sleep quality were significant factors influencing the occurrence of depressive symptoms (P < 0.05). The correlation analysis revealed positive correlations between depressive symptom scores and job burnout scores (r=0.045, P < 0.01), between depressive symptom scores and sleep quality scores (r=0.480, P < 0.01), and between job burnout scores and sleep quality scores (r=0.054, P < 0.01). Furthermore, the indirect effect of job burnout on depressive symptoms through sleep quality was 0.100 (95%CI: 0.204, 0.252; P < 0.01). Conclusion Job burnout and sleep quality are significant factors associated with the occurrence of depressive symptoms among occupational populations, and sleep quality plays a partial mediating role in depressive symptoms associated with job burnout. This finding may provide a scientific basis for developing intervention strategies to control depressive symptoms among workers.

Abdominal aortic aneurysm (AAA) is a deadly condition of the aorta, carrying a significant risk of death upon rupture. Currently, there is a dearth of efficacious pharmaceutical interventions to impede the advancement of AAA and avert it from rupturing. Here, we investigated dihydromyricetin (DHM), one of the predominant bioactive flavonoids in Ampelopsis grossedentata (A. grossedentata), as a potential agent for inhibiting AAA. DHM effectively blocked the formation of AAA in angiotensin II-infused apolipoprotein E-deficient (ApoE^-/-) mice. A combination of network pharmacology and whole transcriptome sequencing analysis revealed that DHM's anti-AAA action is linked to heme oxygenase (HO)-1 (Hmox-1 for the rodent gene) and hypoxia-inducible factor (HIF)-1α in vascular smooth muscle cells (VSMCs). Remarkably, DHM caused a robust rise (∼10-fold) of HO-1 protein expression in VSMCs, thereby suppressing VSMC inflammation and oxidative stress and preserving the VSMC contractile phenotype. Intriguingly, the therapeutic effect of DHM on AAA was largely abrogated by VSMC-specific Hmox1 knockdown in mice. Mechanistically, on one hand, DHM increased the transcription of Hmox-1 by triggering the nuclear translocation and activation of HIF-1α, but not nuclear factor erythroid 2-related factor 2 (NRF2). On the other hand, molecular docking, combined with cellular thermal shift assay (CETSA), isothermal titration calorimetry (ITC), drug affinity responsive target stability (DARTS), co-immunoprecipitation (Co-IP), and site mutant experiments revealed that DHM bonded to HO-1 at Lys243 and prevented its degradation, thereby resulting in considerable HO-1 buildup. In summary, our findings suggest that naturally derived DHM has the capacity to markedly enhance HO-1 expression in VSMCs, which may hold promise as a therapeutic strategy for AAA.

The ambiguity of etiology makes temporomandibular joint osteoarthritis (TMJOA) "difficult-to-treat". Emerging evidence underscores the therapeutic promise of exosomes in osteoarthritis management. Nonetheless, challenges such as low yields and insignificant efficacy of current exosome therapies necessitate significant advances. Addressing lower strontium (Sr) levels in arthritic synovial microenvironment, we studied the effect of Sr element on exosomes and miRNA selectively loading in synovial mesenchymal stem cells (SMSCs). Here, we developed an optimized system that boosts the yield of SMSC-derived exosomes (SMSC-EXOs) and improves their miRNA profiles with an elevated proportion of beneficial miRNAs, while reducing harmful ones by pretreating SMSCs with Sr. Compared to untreated SMSC-EXOs, Sr-pretreated SMSC-derived exosomes (Sr-SMSC-EXOs) demonstrated superior therapeutic efficacy by mitigating chondrocyte ferroptosis and reducing osteoclast-mediated joint pain in TMJOA. Our results illustrate Alix's crucial role in Sr-triggered miRNA loading, identifying miR-143-3p as a key anti-TMJOA exosomal component. Interestingly, this system is specifically oriented towards synovium-derived stem cells. The insight into trace element-driven, site-specific miRNA selectively loading in SMSC-EXOs proposes a promising therapeutic enhancement strategy for TMJOA.
MicroRNAs/metabolism* ; Mesenchymal Stem Cells/drug effects* ; Osteoarthritis/drug therapy* ; Exosomes/drug effects* ; Strontium/pharmacology* ; Synovial Membrane/cytology* ; Humans ; Animals ; Temporomandibular Joint Disorders/therapy* ; Temporomandibular Joint

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

ObjectiveTo investigate the expression level of lysophosphatidyllecithin acyltransferase 4 （LPCAT4） in pancreatic cancer and its effect on the proliferation of pancreatic cancer cells. MethodsIn this study， the differentially expressed genes of patients with KRAS mutant and wild-type pancreatic cancer were analyzed by online database LinkedOmics. The LPCAT4 expression in pancreatic cancer tissues was analyzed online by the University of Alabama at Birmingham Cancer Data Analysis （UALCAN）， Sangerbox and gene expression profile interaction analysis 2 （GEPIA2）. Kaplan-Meier Plotter database was used to explore the correlation between LPCAT4 and the prognosis of patients with pancreatic cancer. The expression of LPCAT4 in human pancreatic cancer cells were detected by quantitative real-time PCR and Western blot analysis. LPCAT4 was knocked down in the high-expressing SW1990 cell line and overexpressed in the low-expressing MIA PaCa-2 cell line. The effects of LPCAT4 expression on cell proliferation were assessed using CCK-8 and EdU assays. STRING and GEPIA2 databases were used to obtain LPCAT4 binding and coexpressed genes in tumors， which were then analyzed by GO and KEGG. ResultsAnalysis of the LinkedOmics online database revealed a significant upregulation of LPCAT4 in patients with KRAS mutant pancreatic cancer compared to patients with KRAS wild-type pancreatic cancer. The online analysis of GEPIA2， UALCAN and Sangerbox 3.0 showed that the expression of LPCAT4 was higher in pancreatic cancer than in normal tissues. Analysis of the Kaplan-Meier Plotter database revealed that high LPCAT4 expression was associated with poorer prognosis in pancreatic cancer patients.Western blot and qPCR results showed that expression of LPCAT4 in pancreatic cancer cell lines was significantly higher than in normal pancreatic ductal epithelial cells. Knockdown of LPCAT4 in SW1990 cells inhibited proliferation， while overexpression in MIA PaCa-2 cells promoted proliferation. Enrichment analysis indicated that LPCAT4 was closely related to sulfur metabolism. ConclusionsLPCAT4 is highly expressed in pancreatic cancer and is associated with poor prognosis of patients. It plays a significant regulatory role in the proliferation of pancreatic cancer cells， with its expression level closely correlated with cell proliferation capacity. These findings reveal the critical role of LPCAT4 in the malignant progression of pancreatic cancer and provide important evidence for its potential as a therapeutic target.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Objective To evaluate the application value of prone-position ultrasound in assessing retrorenal colon among patients scheduled for percutaneous nephrolithotomy(PCNL).Methods A total of 651 patients scheduled for PCNL were enrolled.All patients underwent preoperative supine-position computed tomography(CT)and prone-position ultrasound to assess retrorenal colon.Retro-renal colon was defined as segment of the colon located posterior to the kidney,with its inferior mar-gin extending beyond the lower pole of the kidney.The degree of coverage was classified as mild(≤3.0 cm),moderate(＞3.0 cm without extending beyond the renal hilum)and severe(extending be-yond the renal hilum).Patients diagnosed with retrorenal colon by ultrasound underwent further eval-uation using prone-position CT.Concordance between ultrasound and supine-position or prone-posi-tion CT in diagnosing and classifying retrorenal colon was compared,and the impact on puncture pathway selection and surgical approach was analyzed.Results Among 651 patients,prone-position ultrasound identified retrorenal colon in 57 patients,including 43 mild cases,11 moderate cases,and 3 severe cases.Prone-position CT identified retrorenal colon in 55 patients,including 42 mild cases,10 moderate cases,and 3 severe cases.Supine CT identified retrorenal colon in 26 patients,inclu-ding 23 mild cases,2 moderate cases,and 1 severe case.The detection rate of retrorenal colon by supine CT was significantly lower than that by prone-position ultrasound(P＜0.05).In 12 patients(4 mild cases,7 moderate cases,1 severe case),the puncture pathway was modified based on ultra-sound diagnosis,and 2 patients with severe involvement underwent a change in surgical approach.Conclusion Prone-position ultrasound demonstrates good agreement with prone-position CT in the assessment of retrorenal colon.

Objective To investigate the potential role of estrogen in the formation of granulation tissue hyperplasia-induced tracheal stenosis in rats.Methods Twenty-four female SD rats were ran-domly divided into three groups(n=8)using a random number table method:sham group(n=8),ovariectomized(OVX)group(bilateral ovariectomy,n=8),and ovariectomized+estrogen(OVX+E2)group(bilateral ovariectomy followed by exogenous estrogen intervention,n=8).Four weeks af-ter establishment of the Sham and OVX rat models,a granulation tissue hyperplasia-induced tracheal stenosis model was constructed in all rats using the oral nylon brush scraping method.On the first day of modeling,rats in the OVX+E2 group were administered 17β-E2 at a dose of 300 μg/kg via intrap-eritonealinjection daily,while rats in the other two groups were given the same volume of normal saline.After 7 consecutive days of administration,tracheal specimens were obtained.Hematoxylin and eosin(HE)staining was used to observe the pathological changes of tracheal granulation tissue hyperplasia in each group and calculate the tracheal stenosis rate.Masson staining was employed to analyze the collagen fibers in the tracheal granulation tissue and calculate the relative collagen deposition area.Immunohistochemical(IHC)staining was used to detect the protein expression levels of transforming growth factor-beta 1(TGF-β 1),vascular endothelial growth factor(VEGF),alpha-smooth muscle actin(α-SMA),and collagen type Ⅰ(COL-Ⅰ)in the tracheal granulation tissue,and the average optical density(AOD)was calculated.Results HE staining revealed granulation tissue hyperplasi-a and tracheal lumen stenosis in the tracheal walls of all three groups.The stenosis rate was the highest in the OVX+E2 group,followed by the sham group,and the lowest in the OVX group,with statistically significant differences(P＜0.05).Masson staining showed that the collagen fibers in the sham group were thicker and denser with more collagen deposition compared to the OVX group.In contrast,the OVX+E2 group had even thicker and denser collagen fibers with more collagen dep-osition than the sham group.IHC staining demonstrated that the protein expression levels of COL-Ⅰ,TGF-β1,VEGF,and α-SMA in the tracheal granulation tissue were the lowest in the OVX group,fol-lowed by the sham group,and the highest in the OVX+E2 group.Conclusion Estrogen can acceler-ate tracheal granulation tissue hyperplasia by upregulating the protein expression levels of COL-Ⅰ,TGF-β1,and VEGF,as well as promoting fibroblast activation,leading to aggravated tracheal stenosis.

Artificial intelligence (AI), particularly deep learning, has demonstrated remarkable performance in medical imaging across a variety of modalities, including X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET), and pathological imaging. However, most existing state-of-the-art AI techniques are task-specific and focus on a limited range of imaging modalities. Compared to these task-specific models, emerging foundation models represent a significant milestone in AI development. These models can learn generalized representations of medical images and apply them to downstream tasks through zero-shot or few-shot fine-tuning. Foundation models have the potential to address the comprehensive and multifactorial challenges encountered in clinical practice. This article reviews the clinical applications of both task-specific and foundation models, highlighting their differences, complementarities, and clinical relevance. We also examine their future research directions and potential challenges. Unlike the replacement relationship seen between deep learning and traditional machine learning, task-specific and foundation models are complementary, despite inherent differences. While foundation models primarily focus on segmentation and classification, task-specific models are integrated into nearly all medical image analyses. However, with further advancements, foundation models could be applied to other clinical scenarios. In conclusion, all indications suggest that task-specific and foundation models, especially the latter, have the potential to drive breakthroughs in medical imaging, from image processing to clinical workflows.
Humans ; Artificial Intelligence ; Deep Learning ; Diagnostic Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed ; Positron-Emission Tomography