RESUMO
A 17-year-old female patient presented to us with complaints of diffuse swelling in her left upper eyelid with preauricular lymphadenopathy for three days. She was diagnosed with a case of hordeolum externum and was treated on the same line. However, during follow-up, she developed a mild- to moderate-grade fever, which did not subside with treatment. On further investigation, her IgM rapid ELISA for Scrub typhus was positive, which was further confirmed by the Weil-Fellix test (OXK=1:360). She was treated with systemic doxycycline. Within a week, her fever returned to normal baseline, with resolution of local eye lid swelling, and her black scab was also gone. We have reported a case of scrub typhus as a rare manifestation with lid swelling and subsequently eschar formation on the upper eye lid. The patient was promptly treated with oral antibiotics without any morbidity.
RESUMO
Gamma secretase (GS) is an important therapeutic target in anticancer drug discovery. Increased GS activity activates notch signaling pathway which is associated with cancer stemness and drug resistance in cancer cells. A total of 69,075 natural and their derivative compounds were screened to identify the lead compound on the basis of in silico GS catalytic domain binding potential and in vitro selective anticancer efficacy. STOCK1N-23234 showed higher dock score (-11.82) compared to DAPT (-9.2) in molecular docking experiment and formed hydrogen bond with the key amino acid (Asp385) involve in catalysis process. Molecular dynamics (MD) simulation parameters (RMSD, RMSF, Rg, SASA and hydrogen bond formation) revealed that the STOTCK1N-23234 formed structurally and energetically stable complex with the GS catalytic domain with lower binding energy (-22.79 kcal/mol) compared to DAPT (-16.22 kcal/mol). STOCK1N-23234 showed better toxicity (up to 60%) against colon and breast cancer cells (HCT-116 and MDA-MB-453) at 1-70 µM concentration. Interestingly, STOCK1N-23234 did not showed cytotoxicity against human normal breast cells (MCF-10A). STOCK1N-23234 treatment significantly decreased sphere formation, notch promoter activity, and transcription of notch target genes (Hes-1 and Hey-1) in HCT-116 cells derived colonosphere. Confocal microscopy revealed that STOTCK1N-23234 treatment at test concentration induced apoptosis related morphological changes, reduced mitochondria membrane potential and increased reactive oxygen species production in HCT-116 cells compared to non-treated cells. In conclusion, STOCK1N-23234 is a novel lead natural anticancer compound which requires in depth validation in cancer preclinical models.Communicated by Ramaswamy H. Sarma.
RESUMO
Sleep deprivation is a critical issue that affects workers in numerous industries, including construction. It adversely affects workers and can lead to significant concerns regarding their health, safety, and overall job performance. Several studies have investigated the effects of sleep deprivation on safety and productivity. Although the impact of sleep deprivation on safety and productivity through cognitive impairment has been investigated, research on the association of sleep deprivation and contributing factors that lead to workplace hazards and injuries remains limited. To fill this gap in the literature, this study utilized machine learning algorithms to predict hazardous situations. Furthermore, this study demonstrates the applicability of machine learning algorithms, including support vector machine and random forest, by predicting sleep deprivation in construction workers based on responses from 240 construction workers, identifying seven primary indices as predictive factors. The findings indicate that the support vector machine algorithm produced superior sleep deprivation prediction outcomes during the validation process. The study findings offer significant benefits to stakeholders in the construction industry, particularly project and safety managers. By enabling the implementation of targeted interventions, these insights can help reduce accidents and improve workplace safety through the timely and accurate prediction of sleep deprivation.