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Physician detection of heart sound abnormality is complicated by the inherent difficulty of detecting critical abnormalities in the presence of noise. Computer-aided heart auscultation provides a promising alternative for more accurate detection, with recent deep learning approaches exceeding expert accuracy. Although combining phonocardiogram (PCG) data with electrocardiogram (ECG) data provides more information to an abnormal heart sound classifier, the scarce presence of labelled datasets with this combination impedes training. This paper explores fine-tuning deep convolutional neural networks such as ResNet, VGG, and inceptionv3, on images of spectrograms, mel-spectrograms, and scalograms. By fine-tuning deep pre-trained models on image representations of ECG and PCG, we achieve 91.25% accuracy on the training-a dataset of the PhysioNet Computing in Cardiology Challenge 2016, compared to a previous result of 81.48%. Interpretation of the model’s learned features is also provided, with the results indicative of clinical significance.

The presence of Salmonella spp. in dairy cattle farms poses a major risk to animal health and welfare. This study focused on Salmonella detection in dairy farms located in the Cremona and Mantua provinces (northern Italy) in samples collected and submitted to laboratories in 2021–2022. A total of 2710 samples from different sources, including calf carcasses/organs (n = 128), rectal swabs (n = 1937), feces (n = 390), bulk milk (n = 93), and overshoes/swabs (n = 127) for environmental sampling, were analyzed for the presence of Salmonella spp. and were included in the present study. Our results indicate that Salmonella was most commonly firstly identified from calf carcasses and organs (61.67%) and that the serotypes most frequently detected in dairies were S. Dublin (38.33%), S. Typhimurium (23.33%), and S. Typhimurium monophasic variant (14.17%). The most common pathological findings in calf carcasses were enteritis, hepatosplenomegaly, and pneumonia. The antimicrobial resistance pattern analyzed using the MIC assay of 51 Salmonella isolates revealed the presence of multi-resistant strains, which pose a major risk to public and animal health.

Abstract Background Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis Results Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg. Conclusion This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.

The management of advanced-stage melanoma is clinically challenging, mainly because of its resistance to the currently available therapies. Therefore, it is important to develop alternative therapeutic strategies. The sigma-2 receptor (S2R) is overexpressed in proliferating tumor cells and represents a promising vulnerability to target. Indeed, we have recently identified a potent S2R modulator (BS148) that is effective in melanoma. To elucidate its mechanism of action, we designed and synthesized a BS148 fluorescent probe that enters SK-MEL-2 melanoma cells as assessed using confocal microscopy analysis. We show that S2R knockdown significantly reduces the anti-proliferative effect induced by BS148 administration, indicating the engagement of S2R in BS148-mediated cytotoxicity. Interestingly, BS148 treatment showed similar molecular effects to S2R RNA interference-mediated knockdown. We demonstrate that BS148 administration activates the endoplasmic reticulum stress response through the upregulation of protein kinase R-like ER kinase (PERK), activating transcription factor 4 (ATF4) genes, and C/EBP homologous protein (CHOP). Furthermore, we show that BS148 treatment downregulates genes related to the cholesterol pathway and activates the MAPK signaling pathway. Finally, we translate our results into patient-derived xenograft (PDX) cells, proving that BS148 treatment reduces melanoma cell viability and migration. These results demonstrate that BS148 is able to inhibit metastatic melanoma cell proliferation and migration through its interaction with the S2R and confirm its role as a promising target to treat cancer.

Simple Summary: Salmonellosis represents a considerable public and animal health concern. Cattle and particularly calves can be affected by this infection, which can cause a variety of clinical problems. At present, data about the diffusion of Salmonella spp. in dairy cattle farms of northern Italy are scarce. In this context, this study aims to conduct a retrospective survey on the presence of Salmonella serotypes in dairy cattle farms in the Cremona and Mantua provinces of the Lombardy Region (northern Italy). The results highlight that in most cases, Salmonella spp. was detected in the carcasses or organs of calves and that its presence was widely distributed on the farm. Finally, the analyses of antimicrobial resistance patterns place the attention on the spread of multi-drug resistant Salmonella strains. The presence of Salmonella spp. in dairy cattle farms poses a major risk to animal health and welfare. This study focused on Salmonella detection in dairy farms located in the Cremona and Mantua provinces (northern Italy) in samples collected and submitted to laboratories in 2021–2022. A total of 2710 samples from different sources, including calf carcasses/organs (n = 128), rectal swabs (n = 1937), feces (n = 390), bulk milk (n = 93), and overshoes/swabs (n = 127) for environmental sampling, were analyzed for the presence of Salmonella spp. and were included in the present study. Our results indicate that Salmonella was most commonly firstly identified from calf carcasses and organs (61.67%) and that the serotypes most frequently detected in dairies were S. Dublin (38.33%), S. Typhimurium (23.33%), and S. Typhimurium monophasic variant (14.17%). The most common pathological findings in calf carcasses were enteritis, hepatosplenomegaly, and pneumonia. The antimicrobial resistance pattern analyzed using the MIC assay of 51 Salmonella isolates revealed the presence of multi-resistant strains, which pose a major risk to public and animal health. [ABSTRACT FROM AUTHOR]

Background/Aims: Endoscopic ultrasound (EUS)-guided tissue acquisition is widely utilized as a diagnostic modality for intra-abdominal masses, but there remains debate regarding which suction technique, slow pull (SP) or conventional suction (CS), is better. A meta-analysis of reported studies was conducted to compare the diagnostic yields of SP and CS during EUS-guided tissue acquisition. Methods: We conducted a systematic electronic search using MEDLINE/PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials to identify clinical studies comparing SP and CS. We meta-analyzed accuracy, sensitivity, blood contamination and cellularity using the random-effects model. Results: A total of 17 studies (seven randomized controlled trials, four prospective studies, and six retrospective studies) with 1,616 cases were included in the analysis. Compared to CS, there was a trend toward better accuracy (odds ratio [OR], 1.48; 95% confidence interval [CI], 0.97 to 2.27; p=0.07) and sensitivity (OR, 1.67; 95% CI, 0.95 to 2.93; p=0.08) with SP and a significantly lower rate of blood contamination (OR, 0.48; 95% CI, 0.33 to 0.69; p

Le misure restrittive a seguito dell’emergenza sanitaria hanno messo in evidenza la necessità di sperimentare nuovi strumenti e ambienti di apprendimento, in particolare per quelle discipline che prevedono attività laboratoriali. Per rispondere a questa esigenza è nata una collaborazione tra il Dipartimento di Fisica dell’Università di Torino e l’Équipe Formativa Territoriale del Piemonte che ha focalizzato la sua azione sulla formazione dei docenti. È stato svolto un tirocinio formativo per la progettazione, la realizzazione e la documentazione di attività di Didattica Digitale Integrata con le schede programmabili. Sono stati organizzati incontri di formazione, a cui è seguita un’attività di accompagnamento per seguirne la ricaduta all’interno delle scuole. La proposta è replicabile in altri contesti e con altre tecnologie.