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AIM: To analyze the correlation between ocular surface status and serum lipids in patients with meibomian gland dysfunction(MGD)during pregnancy, and to provide new ideas for the management and treatment of MGD during pregnancy.METHODS: Totally 120 pregnant women(240 eyes)treated in our hospital from May 2021 to May 2022 were selected and they were divided into MGD group(60 cases, 120 eyes)and control group(60 cases, 120 eyes)according to the presence or absence of MGD. All subjects received the ocular surface disease index scores(OSDI)and underwent examinations of meibomian gland morphology and function, tear film and blood lipid.RESULTS: The scores of OSDI, the related indexes of meibomian gland, corneal fluorescein staining(FL)scores, total cholesterol(TC), triglyceride(TG)and low density lipoprotein-cholesterol(LDL-C)in the MGD group were significantly higher than those in the control group(P

Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous driving. Due to the interference from trees and other ground objects in street scenes caused by mobile laser scanning, there may be a small number of missing points in the roadside tree point cloud, which makes it familiar for under-segmentation and over-segmentation phenomena to occur in the roadside tree segmentation process. In addition, existing methods have difficulties in meeting measurement requirements for segmentation accuracy in the individual tree segmentation process. In response to the above issues, this paper proposes a roadside tree segmentation algorithm, which first completes the scene pre-segmentation through unsupervised clustering. Then, the over-segmentation and under-segmentation situations that occur during the segmentation process are processed and optimized through projection topology checking and tree adaptive voxel bound analysis. Finally, the overall high-precision segmentation of roadside trees is completed, and relevant parameters such as tree height, diameter at breast height, and crown area are extracted. At the same time, the proposed method was tested using roadside tree scenes. The experimental results show that our methods can effectively recognize all trees in the scene, with an average individual tree segmentation accuracy of 99.07%, and parameter extraction accuracy greater than 90%. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to investigate the prevalence and associated factors of hypokalemia in patients with acute ischemic stroke. Methods: A cohort of 996 patients was assessed using a general data questionnaire, laboratory indicators, the NIH Stroke Scale (NIHSS), the Barthel Index (BI), the Frail scale, Nutritional Risk Screening (NRS-2002), and the Kubota drinking water test. Results: Among the 996 patients, 205 (20.6%) were found to have hypokalemia. Logistic regression analysis identified several independent predictors of hypokalemia: age (OR 1.020, 95% CI 1.001– 1.039, P=0.041), hypertension (OR 2.691, 95% CI 1.190– 6.089, P=0.017), Frail score (OR 1.756, 95% CI 1.034– 2.981, P=0.037), Kubota drinking water test grade 3 (OR 2.124, 95% CI 1.055– 4.276, P=0.035), Kubota drinking water test grade 4 (OR 3.016, 95% CI 1.113– 8.174, P=0.037), NIHSS score (OR 1.135, 95% CI 1.018– 1.264, P=0.022), platelet count (OR 0.997, 95% CI 0.994– 0.999, P=0.021), and urea nitrogen levels (OR 0.833, 95% CI 0.750– 0.926, P=0.001). Conclusion: The prevalence of hypokalemia is high in patients with acute ischemic stroke. Independent risk factors included age, hypertension, frailty, neurological function, swallowing function, platelet count and blood urea level. [ABSTRACT FROM AUTHOR]

Aims/Background The prevalence of pressure injuries (PIs) is a widely used clinical indicator of patient safety and quality of care. Nurses' understanding of pressure injury (PI) can significantly impact the treatment outcomes for patients. This study, based on latent profile analysis (LPA), reveals the characteristics associated with PI knowledge levels among clinical nurses in district and county tertiary medical institutions. We aim to help nursing managers formulate training plans accurately so that clinical nurses can provide high-level skin care services for patients. Method In June 2023, 1482 nurse staff from 4 tertiary general hospitals at the district and county level in Chengdu were chosen as research subjects using the convenience sampling method. Responses to the general information questionnaire, the Chinese Version of Pressure Ulcer Knowledge Assessment Tool (C-PUKAT), and the Chinese Version of Attitude towards Pressure ulcer Prevention (C-APuP) were used to compare the population's characteristics based on LPA. Results Three latent profiles of nurses' PI knowledge were identified: weak foundation type (46.3%), strengthening foundation type (42.7%), and special improvement type (11.0%). Subjects' departments, administrative positions, highest degrees and PI prevention attitude scores, as well as whether they have participated in the training, all differed significantly between latent profile groups (p < 0.05). Conclusion The PI knowledge level of nursing staff at the district and county tertiary general hospitals requires urgent improvement. Nursing managers should prioritize the management level and quality of PI training among clinical nursing staff. Precise training programs can be developed based on different categories of nursing staff to enhance their PI knowledge, thereby effectively improving the quality of healthcare for inpatients. [ABSTRACT FROM AUTHOR]

Introduction The prevalence of waterpipe tobacco smoking is increasing globally. Biomarkers of waterpipe tobacco smoke (WTS) exposure are less studied. Aims and Methods To identify the types of biomarkers of WTS exposure and estimate changes in biomarker concentrations pre- to post-WTS exposure. PubMed, Embase, Web of Science, CINAHL Plus, PsycINFO, and Cochrane Library were searched for studies up to April 24, 2023. The types of biomarkers were identified. Random-effects models were used to estimate changes in biomarker concentrations pre- to post-WTS exposure. Results Seventy-three studies involving 3755 participants exposed to WTS (49% male, mean age: 24.8 years) and 11 types of biomarkers of WTS exposure were identified. The biomarkers included tobacco alkaloids, expired carbon monoxide (eCO), carboxyhemoglobin (COHb), tobacco-specific nitrosamines, volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), heavy metals, unmetabolized VOCs, unmetabolized PAHs, furan metabolites, and heterocyclic aromatic amines. Compared with pre-WTS exposure, eCO (breath; mean difference [MD] 27.00 ppm; 95% confidence interval [CI]: 20.91 to 33.08), COHb (blood; MD 4.30%; 95%CI: 2.57 to 6.03), COHb (breath; MD 7.14%; 95%CI: 4.96 to 9.31), nicotine (blood; MD 8.23 ng/mL; 95%CI: 6.27 to 10.19), and cotinine (urine; MD 110.40 ng/mL; 95%CI: 46.26 to 174.54) significantly increased post-WTS exposure. Conclusions Biomarkers of WTS exposure were systematically identified. The similarity between the biomarkers of WTS exposure and those of cigarette smoke and higher concentrations of some biomarkers post-WTS exposure underscore the need for further research on applying biomarkers in surveillance, interventions, and regulations to mitigate the harms of waterpipe tobacco smoking. Implications This study provides the first comprehensive overview of biomarkers investigated and available for assessing WTS exposure and their concentration changes in the human body. Researchers can use biomarkers such as eCO, COHb, nicotine, and cotinine to measure the health risks associated with WTS exposure and objectively evaluate the effectiveness of public health interventions aimed at reducing waterpipe tobacco smoking. Public health policymaking can also be informed through increased biomarker concentrations following WTS exposure, to implement regulations and public health education campaigns on limiting or preventing waterpipe tobacco smoking. [ABSTRACT FROM AUTHOR]

Background/Aims: Long noncoding RNAs (lncRNAs) have recently emerged as novel and potentially promising therapeutic targets in various cancers. However, the expression pattern and biological function of lncRNAs in glioma remain largely elusive. In the present study, we investigated the functional role of an lncRNA, small nucleolar RNA host gene 16 (SNHG16), in glioma. Methods: The expression levels of SNHG16 and miR-4518 were measured using qRT-PCR. The relationship between the levels of SNHG16 and clinicopathologic features were statically analyzed. The levels of proteins were detected using western blot. Bioinformatics analysis and luciferase reporter assays were applied to the analysis of the relationship between SNHG16, miR-4518 and PRMT5. Cell viability and apoptosis were measured using MTT and apoptosis ELISA assay, respectively. Results: SNHG16 was highly expressed in glioma tissues and cell lines, which was related to poorer clinicopathologic features and shorter survival time. Knockdown of SNHG16 inhibits the viability and induces apoptosis of glioma cells. Further investigation revealed that SNHG16 could up-regulate the expression of miR-4518 targeted gene PRMT5 via acting as an endogenous sponge of miR-4518. Moreover, SNHG16 also affects the expression of Bcl-2 family proteins and the activation of PI3K/Akt signaling pathway. Conclusion: Our study revealed a novel SNHG16-miR-4518-PRMT5 pathway regulatory axis in glioma pathogenesis. SNHG16 could be used as a potential therapeutic target in the treatment of glioma.