Search

The expanding presence of red foxes (Vulpes vulpes) in urban and suburban regions could potentially lead to increased instances of human aggression towards this species. We studied 10 deceased red foxes that were submitted by law enforcement agencies in the metropolitan area of Madrid in 2014–2022 because of suspected abuse. Forensic autopsies were performed to establish the cause and manner of death. In 4 of the 10 cases, the cause of death was deemed unnatural, involving blunt-force trauma (n = 2), asphyxia resulting from hanging (n = 1), and firearm injury (n = 1). Among the remaining cases, most had succumbed to natural causes (n = 4), often marked by severe emaciation and a high burden of parasites, primarily Sarcoptes scabiei. In 2 cases, death was undetermined given the poor preservation of the carcass. The growing prevalence of wildlife species in urban areas, particularly red foxes, may require forensic veterinary investigation of deaths potentially related to abuse. [ABSTRACT FROM AUTHOR]

In this study, the application of low-level fusion (LLF) and high-level fusion (HLF) strategies using a combination of Fourier transform infrared spectroscopy (FT-IR) and Raman spectroscopy in the identification of antemortem and postmortem fracture at different postmortem intervals (PMIs) was investigated. On a technical level, the same hard tissue sample can be detected using a mix of FT-IR and Raman techniques. At the method level, two cutting-edge chemometrics approaches (LLF and HLF) combining FT-IR and Raman spectroscopic data are explored. The models were ranked in accordance with their parametric quality as follows: HLF and LLF + HLF models > LLF single model > Raman single model > FT-IR single model. The LLF model performed marginally better than the Raman model, however, when compared to other models, the HLF model performed considerably better. The HLF model achieved the best performance, with both cross-validation accuracy and test data set accuracy of 0.88. The importance of the feature wavelengths in the model construction process was subsequently evaluated by intersection fusion, and it was found that the absorbance bands of amide I, PO43– ν1 ν3, and CH2 in FT-IR and phenylalanine, CO32– ν1– PO43– ν3, and amide III in Raman have outstanding contributions to the construction of antemortem and postmortem fractures identification models. Overall, the combination of FT-IR and Raman with the HLF strategy is a novel and promising approach for developing antemortem and postmortem fracture identification models at different PMIs. [ABSTRACT FROM AUTHOR]

Background. Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. It utilizes virtual microscopy wherein glass slides are converted into digital slides and are viewed by pathologists by automated image analysis. Its impact on pathology workflow, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and institutional collaboration exemplifies a significant innovative movement. The recent US Food and Drug Administration approval to WSI for its use in primary surgical pathology diagnosis has opened opportunities for wider application of this technology in routine practice. Main Text. The ongoing technological advances in digital scanners, image visualization methods, and the integration of artificial intelligence-derived algorithms with these systems provide avenues to exploit its applications. Its benefits are innumerable such as ease of access through the internet, avoidance of physical storage space, and no risk of deterioration of staining quality or breakage of slides to name a few. Although the benefits of WSI to pathology practices are many, the complexities of implementation remain an obstacle to widespread adoption. Some barriers including the high cost, technical glitches, and most importantly professional hesitation to adopt a new technology have hindered its use in routine pathology. Conclusions. In this review, we summarize the technical aspects of WSI, its applications in diagnostic pathology, training, and research along with future perspectives. It also highlights improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology. WSI provides a golden opportunity for pathologists to guide its evolution, standardization, and implementation to better acquaint them with the key aspects of this technology and its judicial use. Also, implementation of routine digital pathology is an extra step requiring resources which (currently) does not usually result increased efficiency or payment. [ABSTRACT FROM AUTHOR]

Background: ChatGPT has substantial potential to revolutionize medical education. We aim to assess how medical students and laypeople evaluate information produced by ChatGPT compared to an evidence-based resource on the diagnosis and management of 5 common surgical conditions. Methods: A 60-question anonymous online survey was distributed to third- and fourth-year U.S. medical students and laypeople to evaluate articles produced by ChatGPT and an evidence-based source on clarity, relevance, reliability, validity, organization, and comprehensiveness. Participants received 2 blinded articles, 1 from each source, for each surgical condition. Paired-sample t-tests were used to compare ratings between the 2 sources. Results: Of 56 survey participants, 50.9% (n = 28) were U.S. medical students and 49.1% (n = 27) were from the general population. Medical students reported that ChatGPT articles displayed significantly more clarity (appendicitis: 4.39 vs 3.89, P =.020; diverticulitis: 4.54 vs 3.68, P <.001; SBO 4.43 vs 3.79, P =.003; GI bleed: 4.36 vs 3.93, P =.020) and better organization (diverticulitis: 4.36 vs 3.68, P =.021; SBO: 4.39 vs 3.82, P =.033) than the evidence-based source. However, for all 5 conditions, medical students found evidence-based passages to be more comprehensive than ChatGPT articles (cholecystitis: 4.04 vs 3.36, P =.009; appendicitis: 4.07 vs 3.36, P =.015; diverticulitis: 4.07 vs 3.36, P =.015; small bowel obstruction: 4.11 vs 3.54, P =.030; upper GI bleed: 4.11 vs 3.29, P =.003). Conclusion: Medical students perceived ChatGPT articles to be clearer and better organized than evidence-based sources on the pathogenesis, diagnosis, and management of 5 common surgical pathologies. However, evidence-based articles were rated as significantly more comprehensive. [ABSTRACT FROM AUTHOR]