Beijing Obstetrics and Gynecology Hospital

The early diagnosis of malignant transformation in oral leukoplakia (OLK) assumes paramount importance in the preventive and timely intervention strategies for oral cancer. Nevertheless, the existing diagnostic modalities exhibit complexity, invasiveness, or inherent limitations. The therapeutic efficacy and mechanism of miR-185 in extracellular vesicles (EVs) in oral cancer have been previously demonstrated. Thus, this study aims to establish a diagnostic model using miR-185 from salivary EVs to identify the malignant transformation of OLK and facilitate the prevention and treatment of oral cancer. miR-185 in salivary EVs was characterized in a discovery cohort comprising healthy controls (n = 8) and patients with hyperplasia (n = 13), mild to moderate dysplasia (n = 15), severe dysplasia (n = 10), and squamous cell carcinoma (OSCC, n = 23). A training set from a validation cohort (n = 164) underwent analysis using receiver operating characteristic curve (ROC) and logistic regression analysis to distinguish malignant forms (MT; i.e., severe dysplasia and OSCC) from non-malignant forms (N-MT; i.e., hyperplasia, mild to moderate dysplasia). The validation set was then utilized to validate the model. miR-185 in salivary EVs demonstrated accurate identification of MT [area under ROC (AUC) = 0.9349, specificity = 90.32%, sensitivity = 80.77%], and its feasibility and accuracy were successfully confirmed in the validation set (specificity = 93.55%, sensitivity = 84.21%). miR-185 in salivary EVs can serve as a non-invasive biomarker for the detection of OLK malignant transformation.

Gestational weight gain (GWG) is a modifiable factor associated with maternal and neonatal outcomes. However, whether recommended weight gain ranges are appropriate across different pre-pregnancy body mass index (BMI) categories remains uncertain, particularly in Asian populations. This study examined the associations between GWG and maternal and neonatal outcomes across pre-pregnancy BMI categories using gestational weight management recommendations developed for the Chinese population. A retrospective cohort study was conducted in a public general hospital in Beijing, China. Pregnant women with singleton pregnancies who attended routine antenatal care and delivered between January 2021, and December 2024 were included. Women with incomplete data were excluded. GWG was calculated as the difference between self-reported pre-pregnancy weight and weight recorded before delivery. Weight gain was classified as inadequate, adequate, or excessive within each pre-pregnancy BMI category according to Chinese gestational weight management guidelines. Maternal outcomes included Caesarean section, non-elective caesarean, mode of birth, gestational diabetes, and gestational hypertension. Neonatal outcomes included preterm birth, low birthweight, and macrosomia, neonatal asphyxia. Multivariable logistic regression analyses stratified by pre-pregnancy BMI category were performed. A total of 3,734 women were included, of whom 66.1% had normal pre-pregnancy BMI. Among women with normal BMI, excessive GWG was associated with higher odds of caesarean section (adjusted odds ratio 1.38, 95% confidence interval 1.15–1.66) and non-elective caesarean Sect. (1.56, 1.16–2.11). Inadequate weight gain in this group was associated with increased odds of preterm birth (2.60, 1.46–4.49) and low birthweight (2.48, 1.37–4.32). Excessive GWG was also associated with higher odds of macrosomia among women with normal BMI (3.08, 1.98–4.92) and those who were overweight (2.96, 1.31–7.96). Among women with obesity, inadequate weight gain was associated with increased odds of preterm birth (6.28, 1.70–26.30). Other associations were limited or outcome-specific. Associations between GWG and maternal and neonatal outcomes varied across pre-pregnancy BMI categories. Women with normal pre-pregnancy BMI demonstrated the most consistent associations with adverse outcomes when gestational weight gain fell outside recommended ranges. These findings suggest that gestational weight management should not focus solely on women at the extremes of BMI, and support BMI-stratified approaches to antenatal weight monitoring and counselling using population-specific guidelines.

Precision medicine is increasingly applied in stomatology by enabling personalized diagnosis and treatment tailored to individual patient needs, and fulfilling this promise involves a convergence of medicine and engineering. Laser is a coherent light that functions as a diagnostic tool and provides tailored energy that can be precisely modulated spatially and temporally for direct treatment of diseases and for the production of delicate dental devices. However, reproducible outcomes depend not only on clinical technique but also on system-level factors central to optomechatronics how energy is delivered, sensed, and regulated in the presence of intraoral variability. Stomatology’s complexity and requirement for customized treatment make laser applications attractive across domains such as photobiomodulation, caries removal, and fabrication of dental implants and invisible braces, where accuracy, efficiency, and minimally invasive workflows are often reported. This review synthesizes laser success in oral medicine from both tissue removal and reconstruction perspectives, mapping common modalities to delivery architectures, controllable parameters including spot size, fluence or irradiance, pulse structure, repetition rate, scan speed, and dwell time, and candidate feedback signals. In addition, we highlight the intertwinement of lasers and digitalization, including artificial intelligence–enabled planning, robotic or digitally guided laser treatments, and three-dimensional laser printing of customized devices, with emphasis on integration challenges such as dosimetry reporting consistency, feedback reliability, motion compensation, latency, and safety interlocks.

IntroductionThe contribution of a family history of hypertension (HH) to diabetic kidney disease (DKD) pathogenesis remains unclear. Investigating this association is crucial for refining risk stratification and enabling early intervention in patients with type 2 diabetes (T2D). This study examined whether a HH is associated with higher odds of DKD among individuals with T2DMethodsParticipants with T2D were grouped according to the presence or absence of a family history of hypertension. Propensity score matching (PSM) was used to mitigate potential confounding factors from baseline clinical features across the comparative groups. To evaluate robustness against confounding and missingness, we applied multivariable logistic regression and E-value analysis and then performed PSM on the dataset after multiple imputation.ResultsThe final analytical data comprised 1,612 individuals fulfilling the diagnostic criteria for T2D, comprising 1,419 without HH and 193 with HH. After PSM, 386 patients (193 patients per group) were included. PSM analysis yielded an odds ratio (OR) of 2.57 (95% CI: 1.48–4.46, P = 0.001). Similar estimates were obtained using inverse probability of treatment weighting (OR = 2.18, 95% CI: 1.52–3.13, P < 0.001) and other weighting approaches. The key findings maintained statistical significance throughout sensitivity testing.DiscussionIn this cross-sectional study, a history of familial hypertension was significantly associated with higher odds of DKD in individuals with T2D. Given the cross-sectional design, causality and temporal direction cannot be established; prospective studies are needed to determine whether familial hypertension contributes to DKD development and progression.