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There are numerous prognostic predictive models for evaluating mortality risk, but current scoring models might not fully cater to sepsis patients’ needs. This study developed and validated a new model for sepsis patients that is suitable for any care setting and accurately forecasts 28-day mortality. The derivation dataset, gathered from 20 hospitals between September 2019 and December 2021, contrasted with the validation dataset, collected from 15 hospitals from January 2022 to December 2022. In this study, 7436 patients were classified as members of the derivation dataset, and 2284 patients were classified as members of the validation dataset. The point system model emerged as the optimal model among the tested predictive models for foreseeing sepsis mortality. For community-acquired sepsis, the model’s performance was satisfactory (derivation dataset AUC: 0.779, 95% CI 0.765–0.792; validation dataset AUC: 0.787, 95% CI 0.765–0.810). Similarly, for hospital-acquired sepsis, it performed well (derivation dataset AUC: 0.768, 95% CI 0.748–0.788; validation dataset AUC: 0.729, 95% CI 0.687–0.770). The calculator, accessible at , is user-friendly and compatible. The new predictive model of sepsis mortality is user-friendly and satisfactorily forecasts 28-day mortality. Its versatility lies in its applicability to all patients, encompassing both community-acquired and hospital-acquired sepsis. [ABSTRACT FROM AUTHOR]

Tree detection and fuel amount and distribution estimation are crucial for the investigation and risk assessment of wildfires. The demand for risk assessment is increasing due to the escalating severity of wildfires. A quick and cost-effective method is required to mitigate foreseeable disasters. In this study, a method for tree detection and fuel amount and distribution prediction using aerial images was proposed for a low-cost and efficient acquisition of fuel information. Three-dimensional (3D) fuel information (height) from light detection and ranging (LiDAR) was matched to two-dimensional (2D) fuel information (crown width) from aerial photographs to establish a statistical prediction model in northeastern South Korea. Quantile regression for 0.05, 0.5, and 0.95 quantiles was performed. Subsequently, an allometric tree model was used to predict the diameter at the breast height. The performance of the prediction model was validated using physically measured data by laser distance meter triangulation and direct measurement from a field survey. The predicted quantile, 0.5, was adequately matched to the measured quantile, 0.5, and most of the measured values lied within the predicted quantiles, 0.05 and 0.95. Therefore, in the developed prediction model, only 2D images were required to predict a few of the 3D fuel details. The proposed method can significantly reduce the cost and duration of data acquisition for the investigation and risk assessment of wildfires. [ABSTRACT FROM AUTHOR]

Background: Studies on facial hyperpigmentation across different facial units are limiting. We aimed to analyze melanin pigmentation images to observe facial pigmentary demarcation lines (FPDLs) and suggest facial hyperpigmentation types for normal individuals. Materials and methods: 3D facial melanin pigmentation images of 173 volunteers were obtained and analyzed for the presence of FPDLs. Pigmentation severity was assessed for each of the thirteen facial pigment units. The images were then grouped according to a pattern of hyperpigmentation to suggest three facial hyperpigmentation types—dark spot, photoaging and post‐inflammatory hyperpigmentation. Results: Four groups of FPDLs including a novel group I were observed. Nasal, frontal, auricular were the darkest pigmented facial pigment unit, and the anterior neck was the least pigmented. The dark spot type was the most common facial hyperpigmentation type. The photoaging type and the PIH type showed age‐dependent distribution, as the photoaging type was more common among the subjects over 40s, and the PIH type was more common in younger subjects. Conclusion: Facial hyperpigmentation among healthy individuals with Fitzpatrick skin types II‐IV is often accompanied by FPDLs and categorized into three types. Each type is modeled after the pattern of pigmentation associated with certain dermatological disorders. The practical implications of facial hyperpigmentation types can be resourceful in various fields including prevention and treatment of pigmentary disorders. [ABSTRACT FROM AUTHOR]

Background: Rheum tanguticum root, cataloged as " Daehwang " in the Korean Pharmacopeia, is rich in various anthraquinones known for their anti-inflammatory and antioxidant properties. Formulations containing Daehwang are traditionally employed for treating neurological conditions. This study aimed to substantiate the antiepileptic and neuroprotective efficacy of R. tanguticum root extract (RTE) against trimethyltin (TMT)-induced epileptic seizures and hippocampal neurodegeneration., Methods: The constituents of RTE were identified by ultra-performance liquid chromatography (UPLC). Experimental animals were grouped into the following five categories: control, TMT, and three TMT+RTE groups with dosages of 10, 30, and 100 mg/kg. Seizure severity was assessed daily for comparison between the groups. Brain tissue samples were examined to determine the extent of neurodegeneration and neuroinflammation using histological and molecular biology techniques. Network pharmacology analysis involved extracting herbal targets for Daehwang and disease targets for epilepsy from multiple databases. A protein-protein interaction network was built using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and pivotal targets were determined by topological analysis. Enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool to elucidate the underlying mechanisms., Results: The RTE formulation was found to contain sennoside A, sennoside B, chrysophanol, emodin, physcion, (+)-catechin, and quercetin-3-O-glucuronoid. RTE effectively inhibited TMT-induced seizures at 10, 30, and 100 mg/kg dosages and attenuated hippocampal neuronal decay and neuroinflammation at 30 and 100 mg/kg dosages. Furthermore, RTE significantly reduced mRNA levels of tumor necrosis factor ( TNF-α ), glial fibrillary acidic protein ( GFAP ), and c-fos in hippocampal tissues. Network analysis revealed TNF, Interleukin-1 beta (IL-1β), Interleukin-6 (IL-6), Protein c-fos (FOS), RAC-alpha serine/threonine-protein kinase (AKT1), and Mammalian target of rapamycin (mTOR) as the core targets. Enrichment analysis demonstrated significant involvement of R. tanguticum components in neurodegeneration ( p = 4.35 × 10-5) and TNF signaling pathway ( p = 9.94 × 10-5)., Conclusions: The in vivo and in silico analyses performed in this study suggests that RTE can potentially modulate TMT-induced epileptic seizures and neurodegeneration. Therefore, R. tanguticum root is a promising herbal treatment option for antiepileptic and neuroprotective applications., Competing Interests: The authors declare no conflict of interest. Changjong Moon is serving as one of the Editorial Board members/Guest editors of this journal. We declare that Changjong Moon had no involvement in the peer review of this article and has no access to information regarding its peer review. Full responsibility for the editorial process for this article was delegated to Jesús Pastor and Gernot Riedel., (© 2024 The Author(s). Published by IMR Press.)