Circadian rhythm is a biological endogenous process regulated by the suprachiasmatic nucleus of the hypothalamus, which transmits light signals to peripheral clocks and synchronizes the body with the external environment through balanced expression of circadian rhythm genes. Working the night shift, sleep disorders, and exposure to artificial light can lead to disturbances in circadian rhythm and genetic imbalances. A substantial body of research has demonstrated that circadian rhythm plays a significant role in the treatment of autoimmune diseases and neurodegenerative disorders, with increasing attention being directed toward their impact on oral health. Disturbances in circadian rhythm primarily affect psycho-neuro-immune mechanisms, oxidative stress responses, and oral microflora through pathways such as the hypothalamic-pituitary-adrenal axis (HPA axis), brain and muscle ARNT-like 1 (BMAL1)-brain-derived neurotrophic factor (BDNF) signaling, and BMAL1-nuclear factor kappa-B (NF-κB) interactions. These disruptions may influence the progression of oral diseases. Certain pharmacological agents (e.g., melatonin, vitamin D, nobiletin, and propofol) have been shown to regulate mood disorders, immune function, and sleep-wake cycles by upregulating BMAL1 expression, thus alleviating disturbances in circadian rhythm. In addition, non-pharmacological interventions, such as sleep management strategies, psychotherapy approaches, and light therapy, also modulate these processes through HPA axis regulation. Currently, the specific mechanisms by which circadian rhythm regulates BDNF levels, T cell subsets, and inflammatory signals—thereby influencing both pathogenesis and treatment outcomes for oral diseases—remain unclear. Future research should focus on elucidating these molecular mechanisms as well as identifying therapeutic targets related to circadian rhythm within the oral health context. Further, multidisciplinary collaboration encompassing pharmacy, sleep behavior studies, and psychology will be instrumental in advancing prevention strategies and treatments for oral diseases.

Objective:To investigate the differences in clinical and imaging characteristics of patients with recent small subcortical infarct (RSSI) stratified by different etiological subtypes.Methods:A retrospective, consecutive analysis was conducted on 696 RSSI patients admitted to the West China Hospital, Sichuan University, from January 2019 to May 2024. Based on clinical and imaging data, patients were stratified into 3 etiological subgroups: presumed cerebral small vessel disease (CSVD)-related RSSI, coexisting carrier large artery stenosis, and coexisting proximal extracranial/intracranial large artery stenosis. The clinical characteristics, vascular risk factors, infarct imaging features, and CSVD markers were compared across the 3 groups. Additionally, the differences in clinical and imaging features based on the location of infarcts (anterior vs posterior circulation) and infarct size (<15 mm vs ≥15 mm) were examined. Results:Among the 696 patients, 557 (80.0%) had presumed CSVD-related RSSI, 68 (9.8%) had coexisting carrier large artery stenosis, and 71 (10.2%) had coexisting proximal extracranial/intracranial large artery stenosis. The patients with presumed CSVD-related RSSI were the youngest [60 (53, 69) years], followed by those with coexisting carrier large artery stenosis [64 (55, 69) years] and those with coexisting proximal extracranial/intracranial large artery stenosis [69 (55, 75) years; H=9.523, P=0.013]. Among RSSI patients with coexisting proximal extracranial/intracranial large artery stenosis, the proportion of those with diabetes (38/71, 53.5%) was the highest, whereas the proportion was 210/557 (37.7%) in the presumed CSVD-related group and 31/68 (45.6%) in the group with coexisting carrier large artery stenosis (χ 2=8.027, P=0.023). Patients with RSSI combined with proximal extracranial/intracranial large artery stenosis had more infarction sites in the pons and a higher proportion of proximal infarction. However, there were no significant differences among the 3 groups in terms of infarct size, or CSVD imaging markers. In the anterior versus posterior circulation comparison, patients with posterior circulation RSSI ( n=360) had a significantly higher age of onset [63(55, 72) years vs 60(52, 59) years, U=51 335.500, P<0.001], had higher prevalence of hypertension and diabetes, and showed higher NIHSS scores [3(2, 6) vs 3(1, 5), U=57 840.500, P=0.028]. The anterior circulation group ( n=366) showed a higher proportion of lacunas [152/336 (45.2%) vs 118/360 (32.8%), χ2=11.364, P<0.001], while the posterior circulation group had a greater prevalence of severe perivascular spaces in the basal ganglia [254/360 (70.6%) vs 203/336 (60.4%), χ2=7.879, P=0.005] and deep white matter hyperintensities grading≥2 [124/360 (34.4%) vs 90/336 (26.8%), χ2=4.787, P=0.029]. There were no statistically significant differences in the distribution of infarcts between anterior and posterior circulations or in CSVD imaging markers between RSSI patients with infarction lesions ≥15 mm ( n=290) and <15 mm ( n=406). Conclusions:Approximately 20% of RSSI cases are related to large artery stenosis. These patients tend to be older at onset and have a higher prevalence of diabetes. Compared to presumed CSVD-related RSSI cases, RSSI cases related to large artery stenosis show no significant differences in infarct imaging features and CSVD imaging markers, suggesting that large artery stenosis in RSSI may be an epiphenomenon rather than a direct causative factor.

Objective:To explore the quantitative indexes of dual energy spectrum CT and related clinical data to establish a predictive model for predicting pneumoconiosis.Methods:In April 2024, the information of 203 pneumoconiosis patients diagnosed by the occupational disease appraisal expert group in the Third People's Hospital of Xinjiang Uygur Autonomous Region (Occupational Disease Hospital of Xinjiang Autonomous Region) from January 2022 to December 2023 was retrospectively analyzed. Another 207 non-pneumoconiosis patients with dust exposure history were selected as control group. The measurement data between the two groups were compared using T test or Wilcoxon in dependent quality test, count date asing chi-square or Fishers test, the energy spectrum related indicators and clinical indicators of the patients were compared between groups, and potential factors for diagnosis of pneumoconiosis were screened through univariate analysis, and independent risk factors were further determined by multivariate logistic regression. Based on the results of regression analysis, the machine learning model was constructed, and the reciver operating characteristic curve (ROC) was drawn to evaluate the efficiency of the model, and the Area under cruve (AUC) value, sensitivity and specificity were calculated.Results:Smoking, lung tissue mass, silicon dioxide (SiO 2) equivalent total mass and SiO 2 equivalent concentration were the risk factors for pneumoconiosis ( P<0.05) . Multivariate logistic regression analysis showed that smoking, lung tissue mass, total lung SiO 2 equivalent total volume and total lung SiO 2 equivalent total mass were independent predicators of the diagnosis of pneumoconiosis ( OR=0.53, 0.99, 1.13, 0.85, P<0.05) . Logistic regression machine learning was used to establish a predictive model, and the training set AUC was 0.74, and the verification set AUC was 0.72, indicating that the model had good accuracy and certain ability to diagnose pneumoconiosis. Conclusion:The machine learning prediction model established by the quantitative analysis index of dual energy spectrum CT and clinical related indexes has a good diagnostic performance for the diagnosis of pneumoconiosis.

Objective To explore the influencing factors of coronary artery lesion severity in patients with acute coronary syndrome (ACS). Methods Clinical data of ACS patients admitted to Zhongshan Hospital, Fudan University from December 2017 to December 2019 were consecutively collected. The modified Gensini score was used to assess the severity of coronary artery lesions. Univariate and multivariate linear regression analyses were performed to identify independent factors associated with coronary artery lesion severity. Results A total of 1 689 ACS patients were included, with an average age of (64.04±11.45) years; 1 353 (80.11%) were male, and the mean modified Gensini score was (8.12±4.03). Multivariate linear regression analysis revealed that sex (β＝0.97, P＝0.001), age (β＝0.03, P＝0.021), estimated glomerular filtration rate (eGFR; β＝－0.03, P＜0.001), low-density lipoprotein cholesterol (LDL-C; β＝0.58, P＜0.001), apolipoprotein A1 (Apo A1; β＝－1.28, P＝0.012), lipoprotein(a) [Lp(a); β＝0.001, P＝0.033], and glycated hemoglobin A_1C (HbA_1C; β＝0.45, P＜0.001) were independent influencing factors of the modified Gensini score. Conclusions Metabolic indicators, including Apo A1, LDL-C, HbA_1C, and Lp(a), may serve as risk factors for coronary artery lesion severity in ACS patients, with Apo A1 demonstrating the strongest impact.

Noise-induced hearing loss is a worldwide public health issue that is characterized by temporary or permanent changes in hearing sensitivity. This condition is closely linked to inflammatory responses, and interventions targeting the inflammatory gene tumor necrosis factor-alpha (TNFα) are known to mitigate cochlear noise damage. TNFα-induced proteins (TNFAIPs) are a family of translucent acidic proteins, and TNFAIP6 has a notable association with inflammatory responses. To date, there have been few reports on TNFAIP6 levels in the inner ear. To elucidate the precise mechanism, we generated transgenic mouse models with conditional knockout of Tnfaip6 (Tnfaip6 cKO). Evaluation of hair cell morphology and function revealed no significant differences in hair cell numbers or ribbon synapses between Tnfaip6 cKO and wild-type mice. Moreover, there were no notable variations in hair cell numbers or hearing function in noisy environments. Our results indicate that Tnfaip6 does not have a substantial impact on the auditory system.
Animals ; Mice, Knockout ; Hair Cells, Auditory, Inner/pathology* ; Mice ; Mice, Transgenic ; Hearing Loss, Noise-Induced ; Evoked Potentials, Auditory, Brain Stem/physiology*

Objective To determine the expression of glucose transporter 1(GLUT1)in lung adenocarcinoma tissues and its effects on cancer cell proliferation,migration,invasion,and cell cycle progression.Methods Prognostic signature genes related to butyrate metabolism in lung adenocarcinoma were screened based on the TCGA-LUAD and GEO databases.Western blot,qPCR,and immunohistochemistry(IHC)were used to detect GLUT1 expression levels.After transfecting A549 and H1299 lung adenocarcinoma cell lines with GLUT1-specific siRNA,CCK-8 assay,colony formation assay,scratch assay,and Transwell assay were performed to investigate the effects of GLUT1 silencing on cell proliferation,clonogenic potential,migration,and invasion,respectively.Flow cytometry was used to analyze cell cycle changes.Results GLUT1 expression was significantly higher in lung adenocarcinoma tissues than normal tissues(P＜0.05).Inhibition of GLUT1 significantly reduced the proliferation,clono-genicity,migration,and invasion abilities of A549 and H1299 cells(P＜0.05).Knockdown of GLUT1 significantly suppressed the expression of CyclinD1 and CDK6,and increased the proportion of cells in the G1 phase(P＜0.05).Conclusion GLUT1 is highly expressed in lung adenocarcinoma tissues and influences patient prognosis by regulating cell cycle progression and pro-liferation,suggesting its potential as a novel therapeutic target for lung adenocarcinoma.

Objective:To explore the quantitative indexes of dual energy spectrum CT and related clinical data to establish a predictive model for predicting pneumoconiosis.Methods:In April 2024, the information of 203 pneumoconiosis patients diagnosed by the occupational disease appraisal expert group in the Third People's Hospital of Xinjiang Uygur Autonomous Region (Occupational Disease Hospital of Xinjiang Autonomous Region) from January 2022 to December 2023 was retrospectively analyzed. Another 207 non-pneumoconiosis patients with dust exposure history were selected as control group. The measurement data between the two groups were compared using T test or Wilcoxon in dependent quality test, count date asing chi-square or Fishers test, the energy spectrum related indicators and clinical indicators of the patients were compared between groups, and potential factors for diagnosis of pneumoconiosis were screened through univariate analysis, and independent risk factors were further determined by multivariate logistic regression. Based on the results of regression analysis, the machine learning model was constructed, and the reciver operating characteristic curve (ROC) was drawn to evaluate the efficiency of the model, and the Area under cruve (AUC) value, sensitivity and specificity were calculated.Results:Smoking, lung tissue mass, silicon dioxide (SiO 2) equivalent total mass and SiO 2 equivalent concentration were the risk factors for pneumoconiosis ( P<0.05) . Multivariate logistic regression analysis showed that smoking, lung tissue mass, total lung SiO 2 equivalent total volume and total lung SiO 2 equivalent total mass were independent predicators of the diagnosis of pneumoconiosis ( OR=0.53, 0.99, 1.13, 0.85, P<0.05) . Logistic regression machine learning was used to establish a predictive model, and the training set AUC was 0.74, and the verification set AUC was 0.72, indicating that the model had good accuracy and certain ability to diagnose pneumoconiosis. Conclusion:The machine learning prediction model established by the quantitative analysis index of dual energy spectrum CT and clinical related indexes has a good diagnostic performance for the diagnosis of pneumoconiosis.

Objective To determine the expression of glucose transporter 1(GLUT1)in lung adenocarcinoma tissues and its effects on cancer cell proliferation,migration,invasion,and cell cycle progression.Methods Prognostic signature genes related to butyrate metabolism in lung adenocarcinoma were screened based on the TCGA-LUAD and GEO databases.Western blot,qPCR,and immunohistochemistry(IHC)were used to detect GLUT1 expression levels.After transfecting A549 and H1299 lung adenocarcinoma cell lines with GLUT1-specific siRNA,CCK-8 assay,colony formation assay,scratch assay,and Transwell assay were performed to investigate the effects of GLUT1 silencing on cell proliferation,clonogenic potential,migration,and invasion,respectively.Flow cytometry was used to analyze cell cycle changes.Results GLUT1 expression was significantly higher in lung adenocarcinoma tissues than normal tissues(P＜0.05).Inhibition of GLUT1 significantly reduced the proliferation,clono-genicity,migration,and invasion abilities of A549 and H1299 cells(P＜0.05).Knockdown of GLUT1 significantly suppressed the expression of CyclinD1 and CDK6,and increased the proportion of cells in the G1 phase(P＜0.05).Conclusion GLUT1 is highly expressed in lung adenocarcinoma tissues and influences patient prognosis by regulating cell cycle progression and pro-liferation,suggesting its potential as a novel therapeutic target for lung adenocarcinoma.

Objective:To investigate the differences in clinical and imaging characteristics of patients with recent small subcortical infarct (RSSI) stratified by different etiological subtypes.Methods:A retrospective, consecutive analysis was conducted on 696 RSSI patients admitted to the West China Hospital, Sichuan University, from January 2019 to May 2024. Based on clinical and imaging data, patients were stratified into 3 etiological subgroups: presumed cerebral small vessel disease (CSVD)-related RSSI, coexisting carrier large artery stenosis, and coexisting proximal extracranial/intracranial large artery stenosis. The clinical characteristics, vascular risk factors, infarct imaging features, and CSVD markers were compared across the 3 groups. Additionally, the differences in clinical and imaging features based on the location of infarcts (anterior vs posterior circulation) and infarct size (<15 mm vs ≥15 mm) were examined. Results:Among the 696 patients, 557 (80.0%) had presumed CSVD-related RSSI, 68 (9.8%) had coexisting carrier large artery stenosis, and 71 (10.2%) had coexisting proximal extracranial/intracranial large artery stenosis. The patients with presumed CSVD-related RSSI were the youngest [60 (53, 69) years], followed by those with coexisting carrier large artery stenosis [64 (55, 69) years] and those with coexisting proximal extracranial/intracranial large artery stenosis [69 (55, 75) years; H=9.523, P=0.013]. Among RSSI patients with coexisting proximal extracranial/intracranial large artery stenosis, the proportion of those with diabetes (38/71, 53.5%) was the highest, whereas the proportion was 210/557 (37.7%) in the presumed CSVD-related group and 31/68 (45.6%) in the group with coexisting carrier large artery stenosis (χ 2=8.027, P=0.023). Patients with RSSI combined with proximal extracranial/intracranial large artery stenosis had more infarction sites in the pons and a higher proportion of proximal infarction. However, there were no significant differences among the 3 groups in terms of infarct size, or CSVD imaging markers. In the anterior versus posterior circulation comparison, patients with posterior circulation RSSI ( n=360) had a significantly higher age of onset [63(55, 72) years vs 60(52, 59) years, U=51 335.500, P<0.001], had higher prevalence of hypertension and diabetes, and showed higher NIHSS scores [3(2, 6) vs 3(1, 5), U=57 840.500, P=0.028]. The anterior circulation group ( n=366) showed a higher proportion of lacunas [152/336 (45.2%) vs 118/360 (32.8%), χ2=11.364, P<0.001], while the posterior circulation group had a greater prevalence of severe perivascular spaces in the basal ganglia [254/360 (70.6%) vs 203/336 (60.4%), χ2=7.879, P=0.005] and deep white matter hyperintensities grading≥2 [124/360 (34.4%) vs 90/336 (26.8%), χ2=4.787, P=0.029]. There were no statistically significant differences in the distribution of infarcts between anterior and posterior circulations or in CSVD imaging markers between RSSI patients with infarction lesions ≥15 mm ( n=290) and <15 mm ( n=406). Conclusions:Approximately 20% of RSSI cases are related to large artery stenosis. These patients tend to be older at onset and have a higher prevalence of diabetes. Compared to presumed CSVD-related RSSI cases, RSSI cases related to large artery stenosis show no significant differences in infarct imaging features and CSVD imaging markers, suggesting that large artery stenosis in RSSI may be an epiphenomenon rather than a direct causative factor.

Low-intensity pulsed ultrasound(LIPUS)is a low-cost,non-invasive and safe treatment method mainly used for musculoskeletal diseases,especially for fractures and nonunion.This article reviews the therapeutic effects of LIPUS on various musculoskeletal and nervous system diseases and analyzes its mechanism and potential targets.It is found that besides fracture and nonunion,LIPUS also has clinical application prospect in treating osteoporosis,muscle injury,and motor nervous system diseases.