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Abstract Introduction Aging populations necessitate home care, but Italy's plan to increase coverage lacks implementation specifics alongside regional variability. Furthermore, there is no data on Italian GP's HC delivery. This study examines home care delivery by General Practitioners in Modena province. Methods A cross-sectional study was conducted involving 85 volunteer GPs (19% of the province's total GPs) from all seven districts of Modena province. Data were collected through a knowledge questionnaire on home care attitudes and analyzed alongside administrative data from December 2022, including active HC contracts, hospitalization rates, and emergency department access. Results 75% of respondent GPs were female, with an average age of 50 years. The average patient load per GP was 1362, with significant variability in age distribution. Most GPs worked in group practices (67%) and utilized support staff, including nurses (66%) and secretaries (86%). 44% of GPs reported conducting 3-5 home visits weekly, 58% activated HC contracts for less than half of their non-transportable patients. The main barriers in activating these contracts were a preference for need-based visits, time constraints, and bureaucratic hurdles. Contracts were mainly for Integrated HC (56%) and Planned HC (41%). GPs managed an average of 15 contracts each (range 2-44), with significant variability in contract types. Hospitalization rates for enrolled GPs (62.3 medical, 41.7 surgical per 1,000 patients) were lower than the provincial average (66.4 and 42.7, respectively). Conclusions The findings highlight the need for Local Health authorities to streamline processes to support HC services, addressing identified barriers and optimizing patient care. The study underscores the importance of providing a comprehensive description of home care services to inform healthcare reforms and improve evidence-based decision-making. Key messages • The study shows variations in home care delivery among GPs in the province of Modena, highlighting challenges and the impact of local healthcare organization. • Findings emphasize the need for streamlined processes and support to improve home care services, addressing barriers and optimizing patient care.

IntroductionPain is a multidimensional experience that varies among individuals and has a significant impact on their health. A biopsychosocial approach is recommended for effective pain management; however, health professionals’ education is weak on this issue. Patient involvement is a promising didactic methodology in developing a more holistic perspective, however there is a lack of reliable evidence on this topic. The aim of the present study is to evaluate the effectiveness of patient involvement in pain education in undergraduate medicine and nursing students.Methods and analysisAn open-label randomised controlled trial including qualitative data will be conducted. After an introductory lesson, each student will be randomly assigned to the intervention group, which includes an educational session conducted by a patient–partner along with an educator, or to the control group in which the session is exclusively conducted by an educator. Both sessions will be carried out according to the Case-Based Learning approach. Primary outcomes will be students’ knowledge, attitudes, opinions and beliefs about pain management, whereas the secondary outcome will be students’ satisfaction. The Pain Knowledge and Attitudes (PAK) and Chronic Pain Myth Scale (CPMS) will be administered preintervention and postintervention to measure primary outcomes. Students’ satisfaction will be measured by a questionnaire at the end of the session. Two focus groups will be conducted to evaluate non-quantifiable aspects of learning.Ethics and disseminationThe protocol of this study was approved by the independent Area Vasta Emilia Nord ethics committee.Adherence to The Declaration of Helsinki and Good Clinical Practice will ensure that the rights, safety and well-being of the participants in the study are safeguarded, as well as data reliability. The results will be disseminated through scientific publications and used to improve the educational offer. A version of the anonymised data set will be released for public access.Trial registrationTrial was not registered on ClinicalTrials.gov as the interventions being compared only concern educational programmes and the outcomes considered do not refer to any clinical dimension.

Non-celiac gluten sensitivity (NCGS) is characterized by the onset of symptoms after eating gluten-containing food. We aimed to single out NCGS subjects among subjects with functional gastrointestinal symptoms. Patients were enrolled in a multicenter double-blind placebo-controlled trial with crossover. Symptoms and quality of life were evaluated by means of 10-cm VAS and SF36. Iron parameters, transaminases and C reactive protein (CRP) were evaluated. After a three-week-long gluten-free diet (GFD), responsive patients were randomly assigned to gluten intake (5.6 g/day) or placebo for seven days, followed by crossover. The primary endpoint was the worsening of symptoms (VAS increase ≥3 cm) during gluten ingestion compared to placebo. One hundred and forty patients were enrolled and 134 (17 males, mean age 39.1 ± 11.7 years, BMI 22.4 ± 3.8) completed the first period. A total of 101 subjects (10 males, mean age 39.3 ± 11.0 years, BMI 22.3 ± 4.0) reported a symptomatic improvement (VAS score 2.3 ± 1.2 vs. 6.5 ± 2.2 before and after GFD, p = 0.001). 98 patients underwent the gluten challenge and 28 (all females, mean age 38.9 ± 12.7 years, BMI 22.0 ± 2.9) reported a symptomatic relapse and deterioration of quality of life. No parameters were found to be statistically associated with positivity to the challenge. However, 14 patients responded to the placebo ingestion. Taking into account this finding, about 14% of patients responding to gluten withdrawal showed a symptomatic relapse during the gluten challenge. This group is suspected to have NCGS.

Randomized controlled clinical trials require management effort, involving huge organizational, economic and informatics investments. Information technology offers opportunities to approach clinical trial methodology in new ways. However, there are only a few reports of computerized data and drug management systems. This paper describes a novel software created specifically for the management of a randomized trial of diet and metformin in people with metabolic syndrome (the Me.Me.Me. trial). Me.Me.Me. is an ongoing phase III randomized controlled trial in healthy people with metabolic syndrome to test the hypothesis that comprehensive lifestyle changes and/or metformin can prevent age-related chronic non-communicable diseases. To manage all the phases of the trial, we created a software which is a state pattern machine, user friendly, web-based, able to maintain the correct balance between randomization groups, and structured in various levels of security in order to guarantee the participant's privacy and compliance with the study protocol. The software achieves budget savings: drug management is not based on patients' packs, but on the actual need for drugs according to each participant's \"state\", with strict guidelines for the handling and supply of medication. The trial is ongoing and recruitment will close on August 31, 2018. To date, 11737 bottles of metformin/placebo have been dispensed to 1054 randomized participants, with drug savings of 29.5%. A software which takes into account the \"state\" of participant might be a powerful resource for developing and managing clinical trials, helping avoid poor treatment allocation, and wastage of drugs and money. EUDRACT no. 2012-005427-32. ClinicalTrials.gov Identifier: NCT02960711.

Background Glioblastoma is the most aggressive type of brain cancer with high-levels of intra- and inter-tumour heterogeneity that contribute to its rapid growth and invasion within the brain. However, a spatial characterisation of gene signatures and the cell types expressing these in different tumour locations is still lacking. Methods We have used a deep convolutional neural network (DCNN) as a semantic segmentation model to segment seven different tumour regions including leading edge (LE), infiltrating tumour (IT), cellular tumour (CT), cellular tumour microvascular proliferation (CTmvp), cellular tumour pseudopalisading region around necrosis (CTpan), cellular tumour perinecrotic zones (CTpnz) and cellular tumour necrosis (CTne) in digitised glioblastoma histopathological slides from The Cancer Genome Atlas (TCGA). Correlation analysis between segmentation results from tumour images together with matched RNA expression data was performed to identify genetic signatures that are specific to different tumour regions. Results We found that spatially resolved gene signatures were strongly correlated with survival in patients with defined genetic mutations. Further in silico cell ontology analysis along with single-cell RNA sequencing data from resected glioblastoma tissue samples showed that these tumour regions had different gene signatures, whose expression was driven by different cell types in the regional tumour microenvironment. Our results further pointed to a key role for interactions between microglia/pericytes/monocytes and tumour cells that occur in the IT and CTmvp regions, which may contribute to poor patient survival. Conclusions This work identified key histopathological features that correlate with patient survival and detected spatially associated genetic signatures that contribute to tumour-stroma interactions and which should be investigated as new targets in glioblastoma. The source codes and datasets used are available in GitHub: https://github.com/amin20/GBM_WSSM .

We present trace metal geochemistry and stable isotope records for the middle Eocene Alano di Piave section, NE Italy, deposited during magnetochron C18n in the marginal Tethys Ocean. We identify a ~500 kyr long carbon isotope perturbation event we infer to be the middle Eocene climatic optimum (MECO) confirming the Northern Hemisphere expression and global occurrence of MECO. Interpreted peak climatic conditions are followed by the rapid deposition of two organic rich intervals (3% TOC) and contemporaneous positive 13C excursions. These two intervals are associated with increases in the concentration of sulphur and redox-sensitive trace metals and low concentrations of Mn, as well as coupled with the occurrence of pyrite. Together these changes imply low, possibly dysoxic, bottom water O2 conditions promoting increased organic carbon burial. We hypothesize that this rapid burial of organic carbon lowered global pCO2 following the peak warming and returned the climate system to the general Eocene cooling trend.

In recent years, improved deep learning techniques have been applied to biomedical image processing for the classification and segmentation of different tumors based on magnetic resonance imaging (MRI) and histopathological imaging (H&E) clinical information. Deep Convolutional Neural Networks (DCNNs) architectures include tens to hundreds of processing layers that can extract multiple levels of features in image-based data, which would be otherwise very difficult and time-consuming to be recognized and extracted by experts for classification of tumors into different tumor types, as well as segmentation of tumor images. This article summarizes the latest studies of deep learning techniques applied to three different kinds of brain cancer medical images (histology, magnetic resonance, and computed tomography) and highlights current challenges in the field for the broader applicability of DCNN in personalized brain cancer care by focusing on two main applications of DCNNs: classification and segmentation of brain cancer tumors images.

Pregnancy complications are poorly represented in the archeological record, despite their importance in contemporary and ancient societies. While excavating a Byzantine cemetery in Troy, we discovered calcified abscesses among a woman’s remains. Scanning electron microscopy of the tissue revealed ‘ghost cells’, resulting from dystrophic calcification, which preserved ancient maternal, fetal and bacterial DNA of a severe infection, likely chorioamnionitis. Gardnerella vaginalis and Staphylococcus saprophyticus dominated the abscesses. Phylogenomic analyses of ancient, historical, and contemporary data showed that G. vaginalis Troy fell within contemporary genetic diversity, whereas S. saprophyticus Troy belongs to a lineage that does not appear to be commonly associated with human disease today. We speculate that the ecology of S. saprophyticus infection may have differed in the ancient world as a result of close contacts between humans and domesticated animals. These results highlight the complex and dynamic interactions with our microbial milieu that underlie severe maternal infections. Why and how have some bacteria evolved to cause illness in humans? One way to study bacterial evolution is to search for ancient samples of bacteria and use DNA sequencing technology to investigate how modern bacteria have changed from their ancestors. Understanding the evolution process may help researchers to understand how some bacteria become resistant to the antibiotics designed to kill them. Complications that occur during pregnancy, including bacterial infections, have long been a major cause of death for women. Now, Devault, Mortimer et al. have been able to sequence the DNA of bacteria found in tissue collected from a woman buried 800 years ago in a cemetery in Troy. Some of the woman’s tissues had been well preserved because they had calcified (probably as the result of infection), which preserved their structure in a mineralized layer. Two mineralized “nodules” in the body appear to be the remains of abscesses. Some of the human DNA in the nodules came from a male, suggesting that the woman was pregnant with a boy and that the abscesses formed in placental tissue. Sequencing the DNA of the bacteria in the abscess allowed Devault, Mortimer et al. to diagnose the woman’s infection, which was caused by two types of bacteria. One species, called Gardnerella vaginalis, is found in modern pregnancy-related infections. The DNA of the ancient samples was similar to that of modern bacteria. The other bacteria species was an ancient form of Staphylococcus saprophyticus, a type of bacteria that causes urinary tract infections. However, the DNA of the ancient S. saprophyticus bacteria is quite different to that of the bacteria found in modern humans. Instead, their DNA sequence appears more similar to forms of the bacteria that infect currently livestock. As humans lived closely with their livestock at the time the woman lived, her infection may be due to a type of bacteria that passed easily between humans and animals. Overall, the results suggest that the disease-causing properties of bacteria can arise from a wide range of sources. In addition, Devault, Mortimer et al. have demonstrated that certain types of tissue found in archeological remains are a potential gold mine of information about the evolution of bacteria and other microbes found in the human body.

IntroductionThe Distally Penetrating Embolic (DPE) is a purpose-built, solvent-free, shear-responsive, silicone-based biomaterial designed for embolization applications where complete casting and occlusion of fine vessel branches is desired (e.g., embolization of the middle meningeal artery for meningiomas and chronic subdural hematoma). The DPE is supplied as a three-part system in small-volume syringes that are mixed prior to use, forming an injectable, shear-thinning paste that preferentially drives into distal vessels where shear is highest; ultimately, the DPE cures in situ into an elastomeric solid. Here, we report on DPE usability and embolization performance in vivo.MethodsUsability: Six neurointerventional radiologists assessed device preparation and injection using a Likert scale (1-very difficult to 5-very easy). Embolization: A total of 57 injections in 20 swine at two sites were performed to acutely evaluate distal penetration and occlusion performance; injections were performed using a 0.017’ microcatheter (n=52) or with dual-lumen balloon occlusion (n=5). Seven and thirty-day studies were conducted against commercially-available controls to evaluate embolization and safety performance in kidney vasculature (n=8 per timepoint). Occlusion via angiography, distal penetration via micro-computed tomography (μCT), and biocompatibility via histopathology were assessed.ResultsAverage device preparation time by clinicians was 2.3 ± 0.4 minutes. Usability was acceptable, and all clinicians were able to hand-inject the material through a 150 cm long, 0.017’ microcatheter. When injected into vessels with blood flow, the DPE shear-thinned and was carried distally into small branches; thereafter, it proceeded proximally to fill larger vessels. After injection was stopped, proximal blood pressure continued to ‘pack’ the material further into the distal vasculature and capillary bed until the material completely cured (~10 minutes from initial mixing). With balloon occlusion, the pressure from injection progressively advanced the DPE proximally to distally, whereupon it shear-thinned and evenly penetrated into small vessel branches. At follow-up, angiography showed effective occlusion of target vasculature without evidence of recanalization. μCT radiographs indicated complete casting of millimeter to micron-sized vessels. Histological sections confirmed full luminal occlusion in vessels down to 30-micron diameter (material was not detected in the venous vasculature). Vessel injury and necrosis were both absent while inflammation was only minimal. No hemorrhage occurred when DPE-embolized kidney tissue was surgically incised.ConclusionThe solvent-free, shear-responsive DPE is an easily prepared, hand-injectable agent that penetrates deeply into distal vessels to provide complete casting and occlusion of target vasculature with favorable biocompatibility. These promising outcomes warrant further study in human subjects.Abstract O-041 Figure 1Disclosures D. Fiorella: 1; C; National Cancer Institute – R44CA257802, Penumbra, Stryker, Balt USA, Siemens. 2; C; Arsenal Medical, Medtronic, Microventoin, Stryker, Balt USA, Mentice, Neurogami, Marblehead, Rapid.AI, Rapid Medical, Phenox, Scientia Vascular. 4; C; Mentice, Neurogami, Marblehead, Scientia Vascular, NVMed. C. Sadasivan: 1; C; National Cancer Institute – R44CA257802. R. Brownlee: 1; C; National Cancer Institute – R44CA257802. A. Arthur: 1; C; Balt USA, Medtronic, Microvention, Penumbra, Siemens. 2; C; Arsenal Medical, Balt USA, Johnson and Johnson, Medtronic, Microvention, Penumbra, Scientia Vascular, Stryker. 4; C; Azimuth, Bendit, Cerebrotech, Endostream, Magneto, Mentice, Neurogami, Neuros, Scientia Vascular, Serenity, Synchron, Tulavi, Vastrax, Viz.ai. J. Groom II: 1; C; National Cancer Institute – R44CA257802. 4; C; Arsenal Medical. C. Guertin: 1; C; National Cancer Institute – R44CA257802. 5; C; Arsenal Medical. Q. Pham: 1; C; National Cancer Institute – R44CA257802. 4; C; Arsenal Medical. M. Fornaciari: 1; C; National Cancer Institute – R44CA257802. 4; C; Arsenal Medical. C. Wiltsey: 1; C; National Cancer Institute – R44CA257802. 4; C; Arsenal Medical. L. Core: 4; C; Arsenal Medical. U. Sharma: 4; C; Arsenal Medical.