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Nuclear fusion is a potential source of carbon-free electricity with many concepts in development. The Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science (PANDA-FES) suite has been deployed since 2021 to measure neutron yield, energy, and spatiotemporal source location at two different Z-pinch fusion devices. This diagnostic can be used at a variety of facilities pursuing fusion in the magnetic, inertial, and magneto-inertial regimes. These different regimes have a wide range of time scales from less than 100 ns to a few μ s, neutron yields from 106 to 1011, and noise environments. Neutron yield is measured through activation of 79Br and 89Y with calibrated detectors. Temporal, spatial, and energy dependence of neutrons is measured with scintillators coupled to photomultiplier tubes (PMTs). Experimental setups and data analysis methods have been developed for these conditions. Neutron yield, neutron energy anisotropy, and spatiotemporal evolution of the source have been measured.

Muhammad Amir,1,2 Zeeshan Feroz,2,3 Anwar Ejaz Beg2 1Pharmacy Services, Aga Khan University Hospital, Karachi, Pakistan; 2Faculty of Pharmacy, Ziauddin University, Karachi, Pakistan; 3Department of Basic Sciences, King Saud Bin Abdulaziz University, Riyadh, Saudi Arabia Abstract: This paper presents a practice-based conceptual (theoretical) model to address medication adherence. The study reviews literature for different rationales of medication adherence and its associated factors. It also reviews the interventions involved in improving medication adherence and its effect. It is known that many interventions applied have not received great success owing to the fact that they have not been employed in regular clinical practice. Furthermore, models or theories utilized for different interventions were based on patient perspective only. The model presented in the paper is based on health care professionals’ perspective, with an aim to be employed in clinical practice. The model framework is based on five premises on the basis of which the two dynamics, patient and health care professional, work. The model is presented with a graphical representation and exemplary procedural framework. It is also compared to other related procedural models. It is suggested that using such a model will allow medication adherence as an integral part of health care outcomes. Keywords: medication adherence, practice model, health care professional, theoretical concept, pharmacy practice

BACKGROUND: The early-generation ROS1 tyrosine kinase inhibitors (TKIs) that are approved for the treatment of ROS1 fusion-positive non-small-cell lung cancer (NSCLC) have antitumor activity, but resistance develops in tumors, and intracranial activity is suboptimal. Repotrectinib is a next-generation ROS1 TKI with preclinical activity against ROS1 fusion-positive cancers, including those with resistance mutations such as ROS1 G2032R. METHODS: In this registrational phase 1-2 trial, we assessed the efficacy and safety of repotrectinib in patients with advanced solid tumors, including ROS1 fusion-positive NSCLC. The primary efficacy end point in the phase 2 trial was confirmed objective response; efficacy analyses included patients from phase 1 and phase 2. Duration of response, progression-free survival, and safety were secondary end points in phase 2. RESULTS: On the basis of results from the phase 1 trial, the recommended phase 2 dose of repotrectinib was 160 mg daily for 14 days, followed by 160 mg twice daily. Response occurred in 56 of the 71 patients (79%; 95% confidence interval [CI], 68 to 88) with ROS1 fusion-positive NSCLC who had not previously received a ROS1 TKI; the median duration of response was 34.1 months (95% CI, 25.6 to could not be estimated), and median progression-free survival was 35.7 months (95% CI, 27.4 to could not be estimated). Response occurred in 21 of the 56 patients (38%; 95% CI, 25 to 52) with ROS1 fusion-positive NSCLC who had previously received one ROS1 TKI and had never received chemotherapy; the median duration of response was 14.8 months (95% CI, 7.6 to could not be estimated), and median progression-free survival was 9.0 months (95% CI, 6.8 to 19.6). Ten of the 17 patients (59%; 95% CI, 33 to 82) with the ROS1 G2032R mutation had a response. A total of 426 patients received the phase 2 dose; the most common treatment-related adverse events were dizziness (in 58% of the patients), dysgeusia (in 50%), and paresthesia (in 30%), and 3% discontinued repotrectinib owing to treatment-related adverse events. CONCLUSIONS: Repotrectinib had durable clinical activity in patients with ROS1 fusion-positive NSCLC, regardless of whether they had previously received a ROS1 TKI. Adverse events were mainly of low grade and compatible with long-term administration. (Funded by Turning Point Therapeutics, a wholly owned subsidiary of Bristol Myers Squibb; TRIDENT-1 ClinicalTrials.gov number, NCT03093116.).

BACKGROUND: Frontotemporal dementia (FTD) represents a collection of neurobehavioral and neurocognitive syndromes that are associated with a significant degree of clinical, pathological, and genetic heterogeneity. Such heterogeneity hinders the identification of effective biomarkers, preventing effective targeted recruitment of participants in clinical trials for developing potential interventions and treatments. In the present study, we aim to automatically differentiate patients with three clinical phenotypes of FTD, behavioral-variant FTD (bvFTD), semantic variant PPA (svPPA), and nonfluent variant PPA (nfvPPA), based on their structural MRI by training a deep neural network (DNN). METHODS: Data from 277 FTD patients (173 bvFTD, 63 nfvPPA, and 41 svPPA) recruited from two multi-site neuroimaging datasets: the Frontotemporal Lobar Degeneration Neuroimaging Initiative and the ARTFL-LEFFTDS Longitudinal Frontotemporal Lobar Degeneration databases. Raw T1-weighted MRI data were preprocessed and parcellated into patch-based ROIs, with cortical thickness and volume features extracted and harmonized to control the confounding effects of sex, age, total intracranial volume, cohort, and scanner difference. A multi-type parallel feature embedding framework was trained to classify three FTD subtypes with a weighted cross-entropy loss function used to account for unbalanced sample sizes. Feature visualization was achieved through post-hoc analysis using an integrated gradient approach. RESULTS: The proposed differential diagnosis framework achieved a mean balanced accuracy of 0.80 for bvFTD, 0.82 for nfvPPA, 0.89 for svPPA, and an overall balanced accuracy of 0.84. Feature importance maps showed more localized differential patterns among different FTD subtypes compared to groupwise statistical mapping. CONCLUSION: In this study, we demonstrated the efficiency and effectiveness of using explainable deep-learning-based parallel feature embedding and visualization framework on MRI-derived multi-type structural patterns to differentiate three clinically defined subphenotypes of FTD: bvFTD, nfvPPA, and svPPA, which could help with the identification of at-risk populations for early and precise diagnosis for intervention planning.

In this study, 3D printing filaments were produced from hemp hurd fibre-reinforced polylactide (PLA) composites. Hemp hurd microfibres were obtained through alkaline digestion followed by a bleaching treatment and were used to produce PLA-based composites with 20–40 wt% fibre content for fused deposition modelling. Tensile testing of 3D printed composites revealed a gradual increase of Young's modulus with the addition of fibres, reaching a maximum of 7.1 GPa for the 40 wt% composite - a two-fold increase to neat PLA. However, tensile strength was only improved for the 20 wt% formulation, with an increase of 8% in comparison with neat PLA. Nevertheless, the thermo-mechanical properties of the composites were significantly enhanced with the addition of fibres. In addition, physical objects were printed from the recycled filaments to assess their recyclability and printability. It was found that the recycled filaments maintained comparable mechanical properties and printability after three recycling cycles.

Abstract Clinically, the body mass index remains the most frequently used metric of overall obesity, although it is flawed by its inability to account for different adipose (i.e., visceral, subcutaneous, and inter/intramuscular) compartments, as well as muscle mass. Numerous prior studies have demonstrated linkages between specific adipose or muscle compartments to outcomes of multiple diseases. Although there are no universally accepted standards for body composition measurement, many studies use a single slice at the L3 vertebral level. In this study, we use computed tomography (CT) studies from patients in The Cancer Genome Atlas (TCGA) to compare current L3-based techniques with volumetric techniques, demonstrating potential limitations with level-based approaches for assessing outcomes. In addition, we identify gene expression signatures in normal kidney that correlate with fat and muscle body composition traits that can be used to predict sex-specific outcomes in renal cell carcinoma.

Abstract Type-1 diabetes (T1D) is an autoimmune disorder characterized by impaired insulin release by islet β cells. It has been shown that proinflammatory cytokines released during the disease can exacerbate the condition, while anti-inflammatory cytokines offer protection. This study analyzed the clinical role of interleukin (IL)-6, -8, -10, and vitamin D levels in T1D patients compared to healthy controls. The levels of IL-6, IL-8, IL-10, and vitamin D in the participants’ serum samples were analyzed using ELISA. The findings showed that T1D patients had significantly increased levels (p

Cardiovascular disease (CVD) and diabetes mellitus (DM) are the pressing global health issue, with advanced glycation end products (AGEs) playing a crucial role in its development. AGEs are harmful compounds formed through chronic exposure to elevated blood glucose levels and oxidative stress, both of which are prevalent in diabetes mellitus. These molecules have detrimental effects on vascular function, inflammation, and oxidative stress, exacerbating CVD progression. Conventional strategies for managing AGEs are often limited by side effects and insufficient efficacy, driving the need for alternative approaches. This review investigates the intricate relationship between AGEs, diabetes mellitus, and CVD, with a focus on the therapeutic potential of natural products-particularly phenolic compounds. The review explores how AGEs contribute to the pathogenesis of diabetes-related complications and their impact on cardiovascular health. It examines the molecular mechanisms underlying AGE formation and the inhibitory effects of various natural compounds on this process. Additionally, the review assesses preclinical and clinical evidence supporting the efficacy of these natural agents in mitigating AGE-induced damage. By highlighting the significant role of AGEs in diabetes and CVD, the study underscores the potential of natural products to counteract AGE accumulation. It provides an in-depth analysis of AGE biochemistry, their sources, and the effects of different natural products on AGE formation. The review concludes by emphasizing the promise of natural compounds in reducing oxidative stress and inflammation, and thereby lowering the risk of cardiovascular complications associated with diabetes. This comprehensive overview advocates for the integration of natural products into therapeutic strategies for managing AGE-mediated cardiovascular and diabetic conditions.

The current study is concerned with Rusafa side of Baghdad city, which extends on 362 square kilometres and is inhabited by 3738371 people. It suffers from population growth, which led to decline in municipal services and rising of land surface temperature (LST) during the summer season. The current study aims to assess the spatial and temporal variation of LST using different dated satellite images of Landsat 4, 7 and 8 at path 168 and raw 037 during July 16, 1989, April 25, 2000, April 26, 2006, and May 31, 2016. Eight analysis models which were built using ERDAS 2014 software are used to calculate the LST parameters; while the land use/land cover (LULC) types are classified using ENVI v.5.3 software. The maximum surface temperature recorded at barren lands are between 26 and 41°C, while at vegetation cover ranging from 25 to 34°C and an inverse correlation are recorded between LST and NDVI ranging from -0.5 to -0.81. The built-up area was increased by 23%, whereas open spaces and vegetation cover are decreased by 16% and 6% respectively all that consequently will make the environment of the study area prone to be warmer.