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Fe3O4 nanoparticles and IAA auxin affect secondary metabolism over time without altering genetic stability in chrysanthemum
Author Correction: Genetic fusions favor tumorigenesis through degron loss in oncogenes
Preoperative neutrophil percentage-to-albumin ratio as a postoperative AKI predictor in non-cardiac surgery: a retrospective cohort secondary analysis
Abstract Acute kidney injury (AKI) is a critical postoperative complication in non-cardiac surgery patients, significantly impacting patient outcomes. The neutrophil percentage-to-albumin ratio (NPAR) is a promising inflammatory biomarker for predicting AKI. However, it is still unclear whether NPAR could be used as a predictor of postoperative AKI in Non-Cardiac Surgical Patients. Univariate and multivariable logistic regression analyses were conducted to assess the predictive value of NPAR for postoperative AKI, controlling for potential confounders. A total of 3041 patients were considered for the analysis after excluding those with preoperative infections and chronic kidney disease. The area under the receiver operating characteristic (ROC) curve for NPAR was 0.723, indicating moderate predictive capability for postoperative AKI. The optimal threshold for NPAR was 5.310, with a specificity of 0.640 and a sensitivity of 0.729. Multivariable regression analysis revealed that NPAR was significantly associated with postoperative AKI risk (adjusted odds ratio 1.093, 95% CI 1.072–1.116, P < 0.001), independent of other clinical factors. Preoperative NPAR is a significant predictor of postoperative AKI in non-cardiac surgical patients under general anesthesia and could be a valuable biomarker for identifying non-cardiac surgical patients at high-risk of AKI.
Mogat1 drives metabolic adaptations to evade immune surveillance
Pediatric adenoidectomy is safe surgery with a low complication rate: a population-based study
Abstract Population-based data on incidence of complications after pediatric adenoidectomy are sparse. Therefore, a retrospective population-based study of all 2105 pediatric adenoidectomies (59.9% male, median age: 4 years) in the year 2019 in all otolaryngology departments in one federal state, Thuringia, in Germany, was performed. Patients’ and treatment characteristics, and complications were analyzed. The highest surgery rate was seen at the age of 3 years (2747.4 per 100,000 children). Adenoidectomy was combined with tonsillotomy or tonsillectomy in 29.2% and 1.5% of the cases. Postoperative bleeding needing re-surgery occurred in 1.1% of all cases. The revision surgery for bleeding rate after solitary adenoidectomy was 0.7%. A wound infection was seen in 1.0%. Complications classified according to the Clavien-Dindo classification (CDC) occurred in 2.6% of cases. The overall complication rate was 20.3/100,000 population. Additional tonsillectomy was independently associated to bleeding > 24 h after surgery (Odds ratio [OR] = 52.141; confidence interval [CI] = 7.772-349.818; p < 0.0001). There was no independent associative factor to enhanced risk of wound infection. CDC complications occurred more frequently in comorbid patients (OR = 4.175; CI = 1.222–14.271; p = 0.023), underweight children (OR = 2.430; CI = 1.198–6.571; p = 0.040), when additional tonsillectomy was performed (OR = 11.177; CI = 2.098–59.548; p < 0.0001), and when perioperative antibiotics were applied (OR = 13.251; CI = 5.695–30.834; p < 0.001). Adenoidectomy is very safe surgery. Main risk factor for bleeding complications is additional tonsillectomy, not adenoidectomy itself.
SP140–RESIST pathway regulates interferon mRNA stability and antiviral immunity
Abstract Type I interferons are essential for antiviral immunity 1 but must be tightly regulated 2 . The conserved transcriptional repressor SP140 inhibits interferon-β ( Ifnb1 ) expression through an unknown mechanism 3,4 . Here we report that SP140 does not directly repress Ifnb1 transcription. Instead, SP140 negatively regulates Ifnb1 mRNA stability by directly repressing the expression of a previously uncharacterized regulator that we call RESIST (regulated stimulator of interferon via stabilization of transcript; previously annotated as annexin 2 receptor). RESIST promotes Ifnb1 mRNA stability by counteracting Ifnb1 mRNA destabilization mediated by the tristetraprolin (TTP) family of RNA-binding proteins and the CCR4–NOT deadenylase complex. SP140 localizes within punctate structures called nuclear bodies that have important roles in silencing DNA-virus gene expression in the nucleus 3 . Consistent with this observation, we find that SP140 inhibits replication of the gammaherpesvirus MHV68. The antiviral activity of SP140 is independent of its ability to regulate Ifnb1 . Our results establish dual antiviral and interferon regulatory functions for SP140. We propose that SP140 and RESIST participate in antiviral effector-triggered immunity 5,6 .
A role for the thalamus in danger evoked awakening during sleep
Development of a novel deep learning method that transforms tabular input variables into images for the prediction of SLD
‘Immortal’ stars have an elixir of youth: dark matter
Artificial intelligence-integrated video analysis of vessel area changes and instrument motion for microsurgical skill assessment
Abstract Mastering microsurgical skills is essential for neurosurgical trainees. Video-based analysis of target tissue changes and surgical instrument motion provides an objective, quantitative method for assessing microsurgical proficiency, potentially enhancing training and patient safety. This study evaluates the effectiveness of an artificial intelligence (AI)-based video analysis model in assessing microsurgical performance and examines the correlation between AI-derived parameters and specific surgical skill components. A dual AI framework was developed, integrating a semantic segmentation model for artificial blood vessel analysis with an instrument tip-tracking algorithm. These models quantified dynamic vessel area fluctuation, tissue deformation error count, instrument path distance, and normalized jerk index during a single-stitch end-to-side anastomosis task performed by 14 surgeons with varying experience levels. The AI-derived parameters were validated against traditional criteria-based rating scales assessing instrument handling, tissue respect, efficiency, suture handling, suturing technique, operation flow, and overall performance. Rating scale scores correlated with microsurgical experience, exhibiting a bimodal distribution that classified performance into good and poor groups. Video-based parameters showed strong correlations with various skill categories. Receiver operating characteristic analysis demonstrated that combining these parameters improved the discrimination of microsurgical performance. The proposed method effectively captures technical microsurgical skills and can assess performance.