Georadar investigations to detect cavities in a historical town damaged by an earthquake of the past

This paper aims to highlight the use of the georadar as a useful prospecting technique to identify the areal density and the geometrical features of the grottoes placed in a historical town characterised by high seismic hazard. <br><br> The town considered here is Rionero in Vulture (Southern Italy) that was hit by several historical earthquakes, among which the 1930 Irpinia earthquake (Me=6.7, Is=VIII MCS). <br><br> For this event a damage map was already available from a previous study (Gizzi and Masini, 2006). This map shows that some sectors of the town suffered higher damage. One factor causing the uneven distribution of the effects is considered to be the presence of grottoes. <br><br> To strengthen this work hypothesis it was necessary to in-depth investigate the subsoil of Rionero in Vulture. Therefore, geophysical data were correlated and integrated with data obtained from field surveys and historical documentary sources. All these investigations allowed to obtain more insights about the influences of the man-made caves on seismic damage

Fatty acid composition of Mediterranean buffalo milk fat

The purpose of this research was to investigate the variation in fatty acid composition of milk fat from four buffalo (Bubalus bubalis) herds under different feeding management and ration composition. Changes in milk fatty acid composition were monitored on a weekly basis. Saturated fatty acids (65.5%) predominated in buffalo milk fat; monounsaturated and polyunsaturated fatty acids were 27.0% and 4.5%, respectively. Of saturated fatty acids, the content of palmitic acid was the highest (30.6%) followed by stearic acid (12.0%) and myristic acid (10.7%). Of the unsaturated fatty acids the content of oleic acid was the highest (26.6%). The average content of conjugated linoleic acid (0.76±0.33) was higher than the maximal values generally reported for dairy cow

Plasma activated water as resistance inducer against bacterial leaf spot of tomato

Plant bacterial diseases are routinely managed with scheduled treatments based on heavy metal compounds or on antibiotics; to reduce the negative environmental impact due to the use of such chemical compounds, as pollution or selection of antibiotic resistant pathogens, the integrated control management is required. In the frame of a sustainable agriculture the use of bacterial antagonists, biological agents, plant defence response elicitors or resistant host plant genotypes are the most effective approaches. In this work, cold atmospheric pressure plasma (CAP) was applied to sterile distilled water, inducing the production of a hydrogen peroxide, nitrite and nitrate, and a pH reduction. In particular, an atmospheric pressure dielectric barrier discharge (DBD) has been used to produce plasma activated water (PAW), that was firstly assayed in in vitro experiments and then in planta through application at the root apparatus of tomato plants, against Xanthomonas vesicatoria (Xv), the etiological agent of bacterial leaf spot. Moreover, the transcription abundance of five genes related to the plant defense was investigated in response to PAW treatment. PAW did not show direct antimicrobial activity against Xv in in vitro experiments, but it enhanced the tomato plants defenses. It was effective in reducing the disease severity by giving relative protections of ca. 61, 51 and 38% when applied 1 h, 24 h and 6 days before the experimental inoculation, respectively. In addition, the experiments highlighted the pal gene involvement in response to the PAW treatments and against the pathogen; its transcription levels resulted significantly high from 1 to 48 h until their decrease 192 h after PAW application

Choosing wisely first line immunotherapy in non-small cell lung cancer (NSCLC): what to add and what to leave out

Immunotherapy has dramatically changed the therapeutic scenario in treatment na\uefve advanced non-small celllung cancer (NSCLC). While single agent pembrolizumab has become the standard therapy in patients with PD-L1 expression on tumor cells 65 50%, the combination of pembrolizumab or atezolizumab and platinum-basedchemotherapy has emerged as an effective first line treatment regardless of PD-L1 expression both in squamousand non-squamous NSCLC without oncogenic drivers. Furthermore, double immune checkpoint inhibition hasshown promising results in treatment na\uefve patients with high tumor mutational burden (TMB). Of note, thepresence of both negative PD-L1 expression and low TMB may identify a subgroup of patients who has littlebenefit from immunotherapy combinations and for whom the best treatment option may still be platinum-basedchemotherapy. To date, first-line single agent immune checkpoint blockade has demonstrated limited activity inEGFR mutated NSCLC and the combination of immunotherapy and targeted agents has raised safety concerns inboth EGFR and ALK positive NSCLC patients. Finally, in EGFR mutated or ALK rearranged NSCLC, atezolizumabin combination with platinum-based chemotherapy and bevacizumab is emerging as a potential treatment optionupon progression to first line tyrosine kinase inhibitors

Supporting Clinical Decision-Making during the SARS-CoV-2 Pandemic through a Global Research Commitment: The TERAVOLT Experience.

To understand the real impact of COVID-19 on cancer patients, an entirely new data collection effort was initiated within the Thoracic Cancers International COVID-19 Collaboration (TERAVOLT). TERAVOLT reported high mortality related to COVID-19 infection in thoracic cancer patients and identified several negative prognostic factors. In this commentary, we discuss the importance and limits of patient registries to support decision-making in thoracic cancer during the SARS-CoV-2 pandemic

ForePass endoscopic bypass device for obesity and insulin resistance-metabolic treatment in a swine model

N/

Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

Background: The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology. Materials and methods: We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data. Results: A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data. Conclusion: AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice