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The U.S. Food and Drug Administration’s (FDA) recent authorization of DermaSensor, an AI-enabled device for skin cancer detection in primary care, marks a pivotal moment in digital health innovation. Clinically, the authorization of the first AI-enabled device for use by non-specialists for detecting skin cancer reinforces the feasibility of digital health technologies to bridge gaps in access and expertise in medical practice. The authorization also establishes a new regulatory precedent for FDA authorization of medical devices incorporating AI and machine learning (ML) technologies within dermatology. Together, this article uses the DermaSensor authorization to examine the clinical evidence and regulatory implications of emerging AI-enabled technologies in dermatology.

Integrated farming (IF) by temporal and spatial mixing of crops, livestock, fishery, and allied activities in a single farm, is considered a critical multifunctional option for smallholder farmers, who form the backbone of Indian agriculture, to ensure sustainable livelihoods, the productivity of agricultural enterprises, stability of farm income, food and nutritional security. However, the adoption of IF still remains low. To explore the critical factors of IF systems and prioritize them for stakeholders’ decision-making and development of strategies, the current research was undertaken to integrate SWOT (Strengths, Weaknesses, Opportunities, and Threats) - AHP (Analytic Hierarchy Process) analysis. We used a multi-stage sampling to select 60 practicing IF adopters in West Bengal state of eastern India for the collection of pair-wise comparison data on 32 SWOT factors using a close-ended questionnaire and subjected to AHP analysis to understand the quantitative importance of each factor of SWOT. Results of the multi- criteria analysis showed the total priority weight of the opportunity component (0.450) was the highest, followed by strength (0.341), weakness (0.114), and threat components (0.095). Based on the global priority weight of all 32 SWOT factors, sustainable livelihood security” was the key driving factor (0.081) followed by promotion of organic farming (0.072), better risk management (0.063) and incorporation of high-value crops (0.063) of opportunity component. Increased farm production and productivity (0.058) and enhancement in income (0.055) of strength component also played as vital driving factors. There was no factor of weakness and threat components within the first 10 important factors. The insights of this study may help improve extension services to smallholder farmers for prioritizing strategies in the adoption process of IF. Additionally, it can also help policymakers to design targeted policies, remove barriers, foster innovation, and promote sustainable practices, contributing to food security and environmental sustainability.

Generative AI is designed to create new content from trained parameters. Learning from large amounts of data, many of these models aim to simulate human conversation. Generative AI is being applied to many different sectors. Within healthcare there has been innovation specifically towards generative AI models trained on electronic medical record data. A recent review characterizes these models, their strengths, and weaknesses. Inspired by that work, we present our evaluation checklist for generative AI models applied to electronic medical records.

Abstract Nano zero-valent iron (nZVI), bimetallic nano zero-valent iron-copper (Fe0–Cu), and Raw algae (sargassum dentifolium) activated carbon-supported bimetallic nano zero-valent iron-copper (AC-Fe0–Cu) are synthesized and characterized using FT-IR, XRD, and SEM. The maximum removal capacity is demonstrated by bimetallic activated carbon AC-Fe0–Cu, which is estimated at 946.5 mg/g capacity at the condition pH = 7, 30 min contact time under shaking at 120 rpm at ambient temperature, 200 ppm of M.O, and 1 g/l dose of raw algae-Fe0–Cu adsorbent. The elimination capability of the H3PO4 chemical AC-Fe0–Cu adsorbent is 991.96 mg/g under the conditions of pH = 3, 120 min contact time under shaking at 120 rpm at room temperature, 200 ppm of M.O, and 2 g/l doses of H3PO4 chemical AC-Fe0–Cu adsorbent. The Bagasse activated carbon adsorbent sheet achieves a removal capacity of 71.6 mg/g MO dye solution. Kinetic and isothermal models are used to fit the results of time and concentration experiments. The intra-particle model yields the best fit for bimetallic Fe0–Cu, AC-Fe0–Cu, H3PO4 chemical AC-Fe0–Cu and bagasse activated carbon(CH), with corrected R-Squared values of 0.9656, 0.9926, 0.964, and 0.951respectively. The isothermal results emphasize the significance of physisorption and chemisorption in concentration outcomes. Response surface methodology (RSM) and artificial neural networks (ANN) are employed to optimize the removal efficiency. RSM models the efficiency and facilitates numerical optimization, while the ANN model is optimized using the moth search algorithm (MSA) for optimal results. Highlights 1. The Fe0–Cu composite, when combined with activated carbon from Bagasse Pulp (CH), exhibited the most effective decolorization effectiveness for anionic colours present in wastewater. 2. The utilization of composites presents a promising opportunity for efficient dye removal due to its cost-effectiveness and environmentally sustainable nature. 3. The utilization of response surface approach and artificial neural network modelling improves the efficacy of removal processes and treatment techniques.

Background: The aim of the study was to analyze the prevalence of Kell antigen and its correlation to major blood groups, ABO & Rh system in Eastern India. There was simultaneous retrospective analysis of Kell alloimmunization to find out the implication and recommendation of transfusion protocols in multi-transfused thalassemia and sickle cell patients. Methods: The study was a prospective observational conducted on 3000 donors for KELL and ABO grouping. Retrospective analysis was made to identify common alloantibodies in multi-transfused patients. Results: The overall prevalence of Kell antigen was 2.6% (80) in 3000 donors. Among male, it was highly prevalent i.e. 2.77% and in females 0.65%. Kell antigen was highly prevalent among AB donors, i.e. 5.1%. It was 2.5% in A, 2.9% in B, 1.9% in Blood Donors. Kell prevalence was high in Rh D positive donors, i.e. 2.72% and was 1.72% among Rh D negative donors. Anti-K was the 3rd most common alloantibody detected in 638 cases of multi-transfused thalassemia and sickle cell (SCD) patients (9.25%). Anti-E (42.6%)was most common entity followed by anti-c (24.0%). Conclusion: The higher incidence of Kell prevalence in AB & Rh D Positive Blood groups and also in male persons indicate that there should be a donor database and knowledge of red cell antigen prevalence in a population. This will help blood centers in providing antigen negative compatible blood units to patients with corresponding alloantibodies. Hemolytic transfusion reactions due to Kell alloimmunization are of a significant severity. Prevalence of Kell alloantibody is high among multi-transfused patients and is next to anti E & anti c. Kell sensitized mothers may also cause serious consequences like hemolytic disease of fetus and newborn. Therefore, it is suggested that extended phenotyping including Kell blood group antigen should be implemented in cases of multi-transfused patients. Keywords: Blood donors, Extended phenotyping, Kell, Multitransfused thalassemia patients, Multitransfused sickle cell disease patients

BackgroundWhile salt sensitivity of blood pressure (SSBP) is a risk factor for hypertension, end-organ damage and death, most studies are conducted in western countries and in White people. We previously found that the prevalence of SSBP in Blacks living in Sub-Saharan Africa is as high as 75–80% like what has been reported in the west. Erythrocyte glycocalyx sensitivity to sodium (eGCSS), a marker of sodium-induced damage to the erythrocyte and vascular endothelial glycocalyx is thought to be related to blood pressure perturbations associated with salt intake. We hypothesized that SSBP correlates with eGCSS differently in men and women in Black people.MethodsWe conducted a cross sectional study using data from our recent clinical trial from Livingstone University Teaching Hospital among 117 normotensive young adults. We used a “salt blood test” to determine eGCSS and an immediate pressor response to oral salt (IPROS) for the diagnosis of SSBP.ResultsThe proportion of males were equal to females and the median age (interquartile range) of the participants was 29 (22–45) years. The eGCSS scores were higher in salt-resistant females compared to salt-sensitive females and males. eGCSS correlated negatively with SSBP (AOR 0.98, 95% CI 0.97–0.99, p = 0.008), however, this relationship was driven by female sex and abrogated by male sex. Although blood pressure elevations exhibited a sustained bimodal pattern in both sexes, in males, systolic and diastolic blood pressure never returned to baseline during the time course as it did in females.ConclusionIn this study, eGCSS correlated negatively with SSBP in black women but not in black men and the pressor response to dietary salt was significantly higher in men compared to women. These results suggest that women tend to have a higher disruption of the vascular endothelial glycocalyx by an acute salt load, implying that acute changes in blood pressure may not be driven directly by the endothelial glycocalyx. Our findings suggest a novel mechanism linking eGCSS and SSBP with potential implications for sex differences in salt-induced cardiovascular disease.Clinical trial registration: https://clinicaltrials.gov/, identifier [NCT04844255].

During the rabi season of 2020, a trial was performed to estimate the efficacy of Cyantraniliprole 10.26 % OD at different doses (30, 60, 90, and 120 g a.i./ha respectively) together with Imidacloprid 17.8% SL (20 g a.i./ha) and Spinosad 45% SC (73 g a.i./ha) to evaluate their efficacy against the fruit borer and thrips infesting chilli (variety SHP-4884). The trial was performed in randomized block design containing three replications. The results showed that Cyantraniliprole 10.6% OD @ 120 g a.i./ha was the most efficient insecticide among the others and recorded the maximum reduction (84.13 % in larval population of fruit borer and 78.03 % in thrips population) in both the pest populations over the untreated check. However, Cyantraniliprole 10.6% OD @ 90 g a.i./ha was noted as the next best insecticide.

Vildagliptin, a dipeptidyl peptidase-4 (DPP-4) inhibitor is effective in reducing HbA1c levels in patients with type 2 diabetes (T2DM) when administered as monotherapy, dual or triple combination therapy. In India, Vildagliptin is commonly prescribed in T2DM patients because it reduces mean amplitude of glycemic excursion (MAGE), has lower risk of hypoglycemia and is weight neutral. Early combination therapy with vildagliptin and metformin is effective and well-tolerated in patients with T2DM, regardless of age or ethnicity. In view of already existing data on vildagliptin and the latest emerging clinical evidence, a group of endocrinologists, diabetologists and cardiologists convened for an expert group meeting to discuss the role and various combinations of vildagliptin in T2DM management. This practical document aims to guide Physicians and Specialists regarding the different available strengths and formulations of vildagliptin for the initiation and intensification of T2DM therapy.

IntroductionThis study was designed to measure the concentration and activity of urinary proteases that activate renal epithelial sodium channel (ENaC) mediated Na+ transport in infants with congenital heart disease, a potential mechanism for fluid retention.MethodsUrine samples from infants undergoing cardiac surgery were collected at three time points: T1) pre-operatively, T2) 6–8 h after surgery, and T3) 24 h after diuretics. Urine was collected from five heathy infant controls. The urine was tested for four proteases and whole-cell patch-clamp testing was conducted in renal collecting duct M-1 cells to test whether patient urine increased Na+ currents consistent with ENaC activation.ResultsHeavy chain of plasminogen, furin, and prostasin were significantly higher in cardiac patients prior to surgery compared to controls. There was no difference in most proteases before and after surgery. Urine from cardiac patients produced a significantly greater increase in Na+ inward currents compared to healthy controls.ConclusionUrine from infants with congenital heart disease is richer in proteases and has the potential to increase activation of ENaC in the nephron to enhance Na+ reabsorption, which may lead to fluid retention in this population.

Introduction: Leprosy is one of the leading causes of physical disabilities contributing to intense social stigmata resulting in human discrimination. This chronic infectious disease caused by Mycobacterium leprae principally affects skin. Histopathology study and bacillary index is important in understanding the disease progression, diagnosis, varied manifestation and complications. Aim: To study the histopathological features of leprosy in skin biopsies, categorize them into various types and correlate Bacillary Index with clinical presentation whenever possible. Materials & Methods: Skin biopsy specimen was obtained from clinically diagnosed 100 cases of Leprosy patients attending Skin OPD. Specimen stained with Hematoxylin & Eosin and 5% AFB. Results: The age of the patients ranged from 4 to 80 years. The male to female ratio was 3:1. Borderline Tuberculoid was the most common presentation. Clinco-histopathological agreement was seen in 76 (76%) cases. Conclusions: The clinical and histopathological features along with bacteriological index are useful than any single parameter in arriving definitive diagnosis and classification of the leprosy.

We explore the evolving landscape of diagnostic artificial intelligence (AI) in dermatology, particularly focusing on deep learning models for a wide array of skin diseases beyond skin cancer. We critically analyze the current state of AI in dermatology, its potential in enhancing diagnostic accuracy, and the challenges it faces in terms of bias, applicability, and therapeutic recommendations.

The utilization of artificial intelligence (AI) in diabetes care has focused on early intervention and treatment management. Notably, usage has expanded to predict an individual’s risk for developing type 2 diabetes. A scoping review of 40 studies by Mohsen et al. shows that while most studies used unimodal AI models, multimodal approaches were superior because they integrate multiple types of data. However, creating multimodal models and determining model performance are challenging tasks given the multi-factored nature of diabetes. For both unimodal and multimodal models, there are also concerns of bias with the lack of external validations and representation of race, age, and gender in training data. The barriers in data quality and evaluation standardization are ripe areas for developing new technologies, especially for entrepreneurs and innovators. Collaboration amongst providers, entrepreneurs, and researchers must be prioritized to ensure that AI in diabetes care is providing quality and equitable patient care.

Heart failure with preserved ejection fraction (HFpEF) is a heterogenous clinical syndrome characterized by diastolic dysfunction, concentric cardiac left ventricular (LV) hypertrophy, and myocardial fibrosis with preserved systolic function. However, the underlying mechanisms of HFpEF are not clear. We hypothesize that an enhanced central sympathetic drive is sufficient to induce LV dysfunction and HFpEF in rats. Male Sprague–Dawley rats were subjected to central infusion of either saline controls (saline) or angiotensin II (Ang II, 20 ng/min, i.c.v) via osmotic mini-pumps for 14 days to elicit enhanced sympathetic drive. Echocardiography and invasive cardiac catheterization were used to measure systolic and diastolic functions. Mean arterial pressure, heart rate, left ventricular end-diastolic pressure (LVEDP), and ± dP/dt changes in responses to isoproterenol (0.5 μg/kg, iv) were measured. Central infusion of Ang II resulted in increased sympatho-excitation with a consequent increase in blood pressure. Although the ejection fraction was comparable between the groups, there was a decrease in the E/A ratio (saline: 1.5 ± 0.2 vs Ang II: 1.2 ± 0.1). LVEDP was significantly increased in the Ang II-treated group (saline: 1.8 ± 0.2 vs Ang II: 4.6 ± 0.5). The increase in +dP/dt to isoproterenol was not significantly different between the groups, but the response in -dP/dt was significantly lower in Ang II-infused rats (saline: 11,765 ± 708 mmHg/s vs Ang II: 8,581 ± 661). Ang II-infused rats demonstrated an increased heart to body weight ratio, cardiomyocyte hypertrophy, and fibrosis. There were elevated levels of atrial natriuretic peptide and interleukin-6 in the Ang II-infused group. In conclusion, central infusion of Ang II in rats induces sympatho-excitation with concurrent diastolic dysfunction, pathological cardiac concentric hypertrophy, and cardiac fibrosis. This novel model of centrally mediated sympatho-excitation demonstrates characteristic diastolic dysfunction in rats, representing a potentially useful preclinical murine model of HFpEF to investigate various altered underlying mechanisms during HFpEF in future studies.

This research manuscript proposes an Improved Manta Ray Foraging Optimization (IMRFO) algorithm for the power system congestion cost problem. The goal of the proposed Congestion Management (CM) strategy is twofold: firstly, the Generator Sensitivity Factors (GSF) is determined to select and involve the most influential power system generators that will reschedule their real power to alleviate the excess power flow in congested transmission lines. Secondly, the IMRFO has been developed and applied to attain the minimum possible congestion cost. The IMRFO has been formulated with the inclusion of correction factors in the exploration and exploitation phases to improve the coordination between these phases. The effectiveness of IMRFO has been measured considering its effective performance on the 23 conventional benchmark functions. 39 bus New England and IEEE-118 bus test system has been utilized to authenticate the effectiveness of the CM approach with the application of IMRFO. The outcomes highlight that the congestion cost achieved with IMRFO has been reduced by, of 16.08%, 13.73%, 11.78%, and 4.48 % for the 39-bus system and 14.84%, 12.97%, 9.63%, and 6.85% for 118 bus system when compared to the Bacteria Forge Optimization (BFO), Grey Wolf Optimization (GWO), Sine-Cosine Algorithm (SCA), and Original MRFO. The results gained with the implementation of IMRFO on the CM problem portrays appreciable minimization in the congestion cost, enhancement in the system voltage and losses, generates better convergence profile and computational time when contrasted with the recent optimization methods.

Mercury (II) ions are considered the most harmful heavy metal ion and their accumulation in the human body causes several diseases so need to be detected at trace levels. The use of nanozyme-based colorimetric detection is an acknowledged and innovative method to detect heavy metal ions in water bodies. In this work, we report CuMOF nanoparticles (CuMOF NPs) synthesized using hand grinding technique. The MOF nanoparticles were characterized by FTIR, TGA, SCXRD, PXRD, FESEM and TEM. The SCXRD confirmed paddle wheel type structure and MOF exhibits interpenetrated pcu topology with point symbol {412.63}. BET analysis revealed a high surface area of 15.995 m2g-1 and pore diameter of 3.42 nm for CuMOF NPs. The MOF NPs were found to show peroxidase-like activity. The CuMOF NPs employed as the catalyst, where 3,3′,5,5′-tetramethylbenzidine (TMB) was oxidised by Hg2+ and a bluish solution of oxidised TMB was obtained and recorded by UV–vis spectroscopy. The activity was determined with a detection limit of 0.55 μM, Km of 0.0477 M, and Vmax of 0.3125 M s−1 for TMB, and Km of 2.646 M and Vmax of 0.126 M s−1 for H2O2. The selectivity of the method was excellent and the mechanism was supported by XPS analysis. So, we provide a low-cost, eco-friendly approach for the detection of Hg2+ using CuMOF NPs.

From 1990 to 2024, this study presents a groundbreaking bibliometric and sentiment analysis of nanocomposite literature, distinguishing itself from existing reviews through its unique computational methodology. Developed by our research group, this novel approach systematically investigates the evolution of nanocomposites, focusing on microstructural characterization, electrical properties, and mechanical behaviors. By deploying advanced Boolean search strategies within the Scopus database, we achieve a meticulous extraction and in-depth exploration of thematic content, a methodological advancement in the field. Our analysis uniquely identifies critical trends and insights concerning nanocomposite microstructure, electrical attributes, and mechanical performance. The paper goes beyond traditional textual analytics and bibliometric evaluation, offering new interpretations of data and highlighting significant collaborative efforts and influential studies within the nanocomposite domain. Our findings uncover the evolution of research language, thematic shifts, and global contributions, providing a distinct and comprehensive view of the dynamic evolution of nanocomposite research. A critical component of this study is the “State-of-the-Art and Gaps Extracted from Results and Discussions” section, which delves into the latest advancements in nanocomposite research. This section details various nanocomposite types and their properties and introduces novel interpretations of their applications, especially in nanocomposite films. By tracing historical progress and identifying emerging trends, this analysis emphasizes the significance of collaboration and influential studies in molding the field. Moreover, the “Literature Review Guided by Artificial Intelligence” section showcases an innovative AI-guided approach to nanocomposite research, a first in this domain. Focusing on articles from 2023, selected based on citation frequency, this method offers a new perspective on the interplay between nanocomposites and their electrical properties. It highlights the composition, structure, and functionality of various systems, integrating recent findings for a comprehensive overview of current knowledge. The sentiment analysis, with an average score of 0.638771, reflects a positive trend in academic discourse and an increasing recognition of the potential of nanocomposites. Our bibliometric analysis, another methodological novelty, maps the intellectual domain, emphasizing pivotal research themes and the influence of crosslinking time on nanocomposite attributes. While acknowledging its limitations, this study exemplifies the indispensable role of our innovative computational tools in synthesizing and understanding the extensive body of nanocomposite literature. This work not only elucidates prevailing trends but also contributes a unique perspective and novel insights, enhancing our understanding of the nanocomposite research field.

We consider the influence of different nanoparticles or micrometre-scale colloidal objects, which we commonly refer to as particles, on liquid crystalline (LC) orientational order in essentially spatially homogeneous particle–LC mixtures. We first illustrate the effects of coupling a single particle with the surrounding nematic molecular field. A particle could either act as a “dilution”, i.e., weakly distorting local effective orientational field, or as a source of strong distortions. In the strong anchoring limit, particles could effectively act as topological point defects, whose topological charge q depends on particle topology. The most common particles exhibit spherical topology and consequently act as q = 1 monopoles. Depending on the particle’s geometry, these effective monopoles could locally induce either point-like or line-like defects in the surrounding LC host so that the total topological charge of the system equals zero. The resulting system’s configuration is topologically equivalent to a crystal-like array of monopole defects with alternating topological charges. Such configurations could be trapped in metastable or stable configurations, where the history of the sample determines a configuration selection.

Congestion management is one of the most critical issues in the operation of deregulated power systems. This research work proposes a Congestion Management (CM) approach considering the optimal real power rescheduling of power system generators. The Generator Sensitivity Factors (GSF) have been considered to select the most sensitive generators that would participate in CM. An Improved Crow Search Algorithm (ICSA) has been formulated to minimize the congestion cost. The stages of exploration and exploitation of the Crow Search Algorithm (CSA) have been modified with the incorporation of the dynamic awareness probability and Lévy​ flight approach for the formulation of ICSA in CM. The CM cost optimization problem was validated using the standard 39-bus new England system and the IEEE-118 bus system. A comparison analysis with other optimization techniques has also been carried over to further assess the performance of the proposed ICSA approach. The obtained results showed that the congestion cost achieved with ICSA has been reduced by 1.84%, 4.01%, 6.25%, when compared to the Differential Evolution (DE) Algorithm, Grey Wolf Optimization (GWO), and Crow Search Algorithm (CSA), respectively, for the 39-bus system. For the IEEE 118-bus system, the application of ICSA has curtailed the congestion cost by 2.50%, 8.55%, and 12.50%, when compared to the congestion cost achieved with DE, GWO, and CSA, correspondingly. It is observed that the performance of ICSA for CM cost has superseded the other approaches adopted for CM.

Even as innovation occurs within digital medicine, challenges around equity and racial health disparities remain. Golden et al. evaluate structural racism in their recent paper focused on reproductive health. They recommend a framework to Remove, Repair, Restructure, and Remediate. We propose applying the framework to three areas within digital medicine: artificial intelligence (AI) applications, wearable devices, and telehealth. With this approach, we can continue to work towards an equitable future for digital medicine.

Improving piezoelectric strain and voltage constant generally compromises piezoelectric performance and mechanical softness. Here, the authors report a bond weakening strategy for organic-inorganic hybrid piezoelectrics and mitigated these issues.

Volume reflex produces sympatho-inhibition that is mediated by the hypothalamic paraventricular nucleus (PVN). However, the mechanisms for the sympatho-inhibitory role of the PVN and the neurochemical factors involved remain to be identified. In this study, we proposed C-type natriuretic peptide (CNP) as a potential mediator of this sympatho-inhibition within the PVN. Microinjection of CNP (1.0 μg) into the PVN significantly decreased renal sympathetic nerve activity (RSNA) (−25.8% ± 1.8% vs. −3.6% ± 1.5%), mean arterial pressure (−15.0 ± 1.9 vs. −0.1 ± 0.9 mmHg) and heart rate (−23.6 ± 3.5 vs. −0.3 ± 0.9 beats/min) compared with microinjection of vehicle. Picoinjection of CNP significantly decreased the basal discharge of extracellular single-unit recordings in 5/6 (83%) rostral ventrolateral medulla (RVLM)-projecting PVN neurons and in 6/13 (46%) of the neurons that were not antidromically activated from the RVLM. We also observed that natriuretic peptide receptor type C (NPR-C) was present on the RVLM projecting PVN neurons detected by dual-labeling with retrograde tracer. Prior NPR-C siRNA microinjection into the PVN significantly blunted the decrease in RSNA to CNP microinjections into the PVN. Volume expansion-mediated reduction in RSNA was significantly blunted by prior administration of NPR-C siRNA into the PVN. These results suggest a potential role for CNP within the PVN in regulating RSNA, specifically under physiological conditions of alterations in fluid balance.

Long-distance quantum communication will require the use of quantum repeaters to overcome the exponential attenuation of signal with distance. One class of such repeaters utilizes quantum error correction to overcome losses in the communication channel. Here we propose a strategy of using the bosonic Gottesman-Kitaev-Preskill (GKP) code in a two-way repeater architecture with multiplexing. The crucial feature of the GKP code that we make use of is the fact that GKP qubits easily admit deterministic two-qubit gates, hence allowing for multiplexing without the need for generating large cluster states as required in previous all-photonic architectures based on discrete-variable codes. Moreover, alleviating the need for such clique clusters entails that we are no longer limited to extraction of at most one end-to-end entangled pair from a single protocol run. In fact, thanks to the availability of the analog information generated during the measurements of the GKP qubits, we can design better entanglement swapping procedures in which we connect links based on their estimated quality. This enables us to use all the multiplexed links so that large number of links from a single protocol run can contribute to the generation of the end-to-end entanglement. We find that our architecture allows for high-rate end-to-end entanglement generation and is resilient to imperfections arising from finite squeezing in the GKP state preparation and homodyne detection inefficiency. In particular we show that long-distance quantum communication over more than 1000 km is possible even with less than 13 dB of GKP squeezing. We also quantify the number of GKP qubits needed for the implementation of our scheme and find that for good hardware parameters our scheme requires around 10^{3}−10^{4} GKP qubits per repeater per protocol run.

Oxidative stress is a deteriorating condition that arises due to an imbalance between the reactive oxygen species and the antioxidant system or defense of the body. The key reasons for the development of such conditions are malfunctioning of various cell organelles, such as mitochondria, endoplasmic reticulum, and Golgi complex, as well as physical and mental disturbances. The nervous system has a relatively high utilization of oxygen, thus making it particularly vulnerable to oxidative stress, which eventually leads to neuronal atrophy and death. This advances the development of neuroinflammation and neurodegeneration-associated disorders such as Alzheimer’s disease, Parkinson’s disease, epilepsy, dementia, and other memory disorders. It is imperative to treat such conditions as early as possible before they worsen and progress to irreversible damage. Oxidative damage can be negated by two mechanisms: improving the cellular defense system or providing exogenous antioxidants. Natural antioxidants can normally handle such oxidative stress, but they have limited efficacy. The valuable features of nanoparticles and/or nanomaterials, in combination with antioxidant features, offer innovative nanotheranostic tools as potential therapeutic modalities. Hence, this review aims to represent novel therapeutic approaches like utilizing nanoparticles with antioxidant properties and nanotheranostics as delivery systems for potential therapeutic applications in various neuroinflammation- and neurodegeneration-associated disease conditions.

Gregoor et al. evaluated the healthcare implications and costs of an AI-enabled mobile health app for skin cancer detection, involving 18,960 beneficiaries of a Netherlands insurer. They report a 32% increase in claims for premalignant and malignant skin lesions among app users, largely attributed to benign skin lesions and leading to higher annual costs for app users (€64.97) compared to controls (€43.09). Cost-effectiveness analysis showed a comparable cost to dermatologist-based diagnosis alone. This editorial emphasizes the balance in AI-based dermatology between increased access and increased false positives resulting in overutilization. We suggest refining the diagnostic schemas with new referral pathways to capitalize on potential savings. We also discuss the importance of econometric analysis to evaluate the adoption of new technologies, as well as adapting payment models to mitigate the risk of overutilization inherent in AI-based diagnostics such as skin cancer detection.

Abstract Telehealth use for primary care has skyrocketed since the onset of the COVID-19 pandemic. Enthusiasts have praised this new medium of delivery as a way to increase access to care while potentially reducing spending. Over two years into the pandemic, the question of whether telehealth will lead to an increase in primary care utilization and spending has been met with contradictory answers. Some evidence suggests that telehealth may be used as an addition to in-person visits. Others like Dixit et al. have found that telehealth can actually substitute for in-person care rather than contribute to overutilization. As telehealth continues to evolve, outcomes, utilization, and quality of care should be closely monitored.

Abstract The sorting of RNA transcripts dictates their ultimate post-transcriptional fates, such as translation, decay or degradation by RNA interference (RNAi). This sorting of RNAs into distinct fates is mediated by their interaction with RNA-binding proteins. While hundreds of RNA binding proteins have been identified, which act to sort RNAs into different pathways is largely unknown. Particularly in plants, this is due to the lack of reliable protein-RNA artificial tethering tools necessary to determine the mechanism of protein action on an RNA in vivo. Here we generated a protein-RNA tethering system which functions on an endogenous Arabidopsis RNA that is tracked by the quantitative flowering time phenotype. Unlike other protein-RNA tethering systems that have been attempted in plants, our system circumvents the inadvertent triggering of RNAi. We successfully in vivo tethered a protein epitope, deadenylase protein and translation factor to the target RNA, which function to tag, decay and boost protein production, respectively. We demonstrated that our tethering system (1) is sufficient to engineer the downstream fate of an RNA, (2) enables the determination of any protein’s function upon recruitment to an RNA, and (3) can be used to discover new interactions with RNA-binding proteins.

The field experiment was carried out on tomato in the Rabi season of 2019-20 at the Vegetable Research Farm, Institute of Agricultural Science, Banaras Hindu University, Varanasi, India. The crop variety, Arka Vikas (Selection 22) was selected to evaluate the bioefficacy of nine different insecticidal treatments against the sucking pest complex and the natural enemies in tomato under field conditions. Two sprays at 15 days intervals of ten treatments with three replications were applied. The treatments were Diafenthiuron 50% WP, Abamectin 1.8% EC, Buprofezin 25% SC, Indoxacarb 14.5% SC, Spinosad 45% SC, Chlorantraniliprole 18.5% SC, Pymetrozine 50% WG, Flonicamid 50% WG, and Lancer Gold (50 + 1.8) % SP and control (water spray). Observations were recorded one day before and 1st, 3rd, 5th, 7th, 10th, and 15th days after each spray. For controlling Whitefly (B. tabaci), Lancer gold was observed to be the best (76.98%), followed by Pymetrozine (69.03%) and Flonicamid (59.39%). At the same time, Flonicamid was excellent (70.62%) in controlling Aphids (A. gossypii), followed by Lancer gold (67.15%) and Pymetrozine (65.48%). In case of a reduction of damage by Thrips (T. tabaci), Lancer gold showed the best result (75.60%), followed by Buprofezin (68.45%) and Flonicamid (65.69%). However, all the treatments showed minute toxicity for the natural enemies; yet Flonicamid and Lancer gold were significantly safer among all of them.

The primary mission of the healthcare sector is to protect from various ailments with improved healthcare services and to use advanced diagnostic solutions to promote reliable treatments for complex diseases. However, healthcare is among the significant contributors to the current climate crisis. Therefore, research is underway to identify various measures to reduce the emissions from advanced healthcare systems. Modern healthcare facilities invest significantly in renewable energy, efficient energy solutions, and intelligent climate cooling and control technologies. Furthermore, innovative technologies like artificial intelligence (AI) are proposed to enable automation for patient health monitoring. With the advances in AI, there are green AI goals for potentially reducing emissions through data-driven and well-optimized models for healthcare. Furthermore, novel machine learning and deep learning techniques are continually proposed for improved efficiency to reduce emissions. Therefore, the scope of the research is to review the potential of AI in healthcare for lowering emission rates and its methodologies, current approaches, metrics, challenges, and future trends to attain a straightforward pathway.

Cancer is a life-threatening disease, resulting in nearly 10 million deaths worldwide. There are various causes of cancer, and the prognostic information varies in each patient because of unique molecular signatures in the human body. However, genetic heterogeneity occurs due to different cancer types and changes in the neoplasms, which complicates the diagnosis and treatment. Targeted drug delivery is considered a pivotal contributor to precision medicine for cancer treatments as this method helps deliver medication to patients by systematically increasing the drug concentration on the targeted body parts. In such cases, nanoparticle-mediated drug delivery and the integration of artificial intelligence (AI) can help bridge the gap and enhance localized drug delivery systems capable of biomarker sensing. Diagnostic assays using nanoparticles (NPs) enable biomarker identification by accumulating in the specific cancer sites and ensuring accurate drug delivery planning. Integrating NPs for cancer targeting and AI can help devise sophisticated systems that further classify cancer types and understand complex disease patterns. Advanced AI algorithms can also help in biomarker detection, predicting different NP interactions of the targeted drug, and evaluating drug efficacy. Considering the advantages of the convergence of NPs and AI for targeted drug delivery, there has been significantly limited research focusing on the specific research theme, with most of the research being proposed on AI and drug discovery. Thus, the study's primary objective is to highlight the recent advances in drug delivery using NPs, and their impact on personalized treatment plans for cancer patients. In addition, a focal point of the study is also to highlight how integrating AI, and NPs can help address some of the existing challenges in drug delivery by conducting a collective survey.

Abstract With the increasing number of FDA-approved artificial intelligence (AI) systems, the financing of these technologies has become a primary gatekeeper to mass clinical adoption. Reimbursement models adapted for current payment schemes, including per-use rates, are feasible for early AI products. Alternative and complementary models may offer future payment options for value-based AI. A successful reimbursement strategy will align interests across stakeholders to guide value-based and cost-effective improvements to care.

Abstract Genetic and epigenetic modifications of genes involved in the key regulatory pathways play a significant role in the pathophysiology and progression of multifactorial diseases. The present study is an attempt to identify single nucleotide variations (SNVs) at CpG sites of promoters of ACAT1, APOB, APOE, CYBA, FAS, FLT1, KSR2, LDLR, MMP9, PCSK9, PHOX2A, REST, SH2B3, SORT1 and TIMP1 genes influencing CpG island (CGI) existence and size associated with the pathophysiology of Diabetes mellitus, Coronary artery disease and Cancers. Promoter sequences located between −2000 to + 2000 bp were retrieved from the EPDnew database and predicted the CpG island using MethPrimer. Further, SNVs at CpG sites were accessed from NCBI, Ensembl while transcription factor (TF) binding sites were accessed using AliBaba2.1. CGI existence and size were determined for each SNV at CpG site with respect to wild type and variant allele by MethPrimer. A total of 200 SNVs at CpG sites were analyzed from the promoters of ACAT1, APOB, APOE, CYBA, FAS, FLT1, KSR2, LDLR, MMP9, PCSK9, PHOX2A, REST, SH2B3, SORT1 and TIMP1 genes. Of these, only 17 (8.5%) SNVs were found to influence the loss of CGI while 70 (35%) SNVs were found to reduce the size of CGI. It has also been found that 59% (10) of CGI abolishing SNVs are showing differences in binding of TFs. The findings of the study suggest that the candidate SNVs at CpG sites regulating CGI existence and size might influence the DNA methylation status and expression of genes involved in molecular pathways associated with several diseases. The insights of the present study may pave the way for new experimental studies to undertake challenges in DNA methylation, gene expression and protein assays.

Context: The changes in the volume and dimensions of the alveolar bone after tooth extraction often lead to challenges in prosthetic rehabilitation of the same necessitating ridge preservation procedures (RPP). Aim: The aim of this randomized clinical trial was to evaluate and compare the dimensional and histomorphometric changes of the sites preserved using the collagen membrane with and without demineralized bone matrix (DMBM). Settings and Design: Interventional, parallel-design, double blinded, randomized controlled trail. Materials and Methods: A randomized controlled trial was designed with 45 participants having at least 2 teeth indicated for were enrolled in this study. The sites were randomly assigned to the control group (RPP using collagen membrane) and the test group (RPP using collagen membrane with DMBM). The clinical parameters assessed were alveolar bone width and alveolar bone height. Histomorphometric analysis was carried out on tissue trephined from the preserved sites to evaluate the percentage of bone and connective tissue (CT %) formed 8 months postRPP. Statistical Analysis Used: Shapiro − Wilk test and paired and unpaired t-test. Results: Horizontal resorption was significantly less in the test group (7.375 ± 1.64). Histomorphometry of these sites revealed a complete absence of residual graft particles, presence of trabecular bone, and a more mineralized matrix (63.256%) as compared to the control sites (46.833%). Conclusions: The use of DMBM along with the collagen membrane for RPP yielded better results both clinically and histomorphometically.

Digital health technologies (DHTs) have brought several significant improvements to clinical trials, enabling real-world data collection outside of the traditional clinical context and more patient-centered approaches. DHTs, such as wearables, allow the collection of unique personal data at home over a long period. But DHTs also bring challenges, such as digital endpoint harmonization and disadvantaging populations already experiencing the digital divide. A recent study explored the growth trends and implications of established and novel DHTs in neurology trials over the past decade. Here, we discuss the benefits and future challenges of DHT usage in clinical trials.

In the present study, polyethylene Glycol passivated Graphene Quantum Dots (PEG-GQDs) were successfully synthesized via the hydrothermal method. Furthermore, for the synthesis of anticancer drug loaded GQD embedded microspheres, the anticancer drug was mixed with synthesized PEG-GQD. As prepared, Gefitinib-PEG-GQDs were incorporated into poly-lactic acid (PLA) microspheres using poly-vinyl-acetate (PVA) as surfactant via solvent evaporation technique and single emulsification method. The successful synthesis of anticancer drug loaded microspheres was confirmed by several characterization techniques, including Field-Emission Scanning Electron Microscopy (FE-SEM), which shows the morphology of microspheres, Fourier Transform Infrared Spectroscopy (FTIR) analysis gives an idea about functional group present in the microspheres. X-ray diffraction (XRD) provides information about the crystallinity of the samples respectively. The drug release characteristics were determined by UV-Vis spectrophotometric analysis. Moreover, the in-vitro cell-based cytotoxicity assay indicated almost insignificant cytotoxicity of the NCI–H522 cell line (Human, Lung, Non-small cell lung cancer).

BackgroundHypertension is common in people living with HIV (PLWH) on antiretroviral therapy (ART). In the general population and in experimental animal models, the incidence of hypertension is greater in males than in females, especially during the premenopausal period. However, it is not known whether there are sex differences in hypertension associated with HIV and ART, and the factors contributing to incident hypertension among PLWH have not been well characterized. In this study, we aimed to determine the time course, sex differences and factors associated with incident hypertension in PLWH initiating ART.Methods and resultsWe conducted a retrospective study in which we used programmatic data from the ART registry to identify sex differences in the determinants of incident hypertension among PLWH initiating the ART regimen from Livingstone University Teaching Hospital in Zambia and followed for 8 years. Males developed hypertension earlier, 2 years after initiating ART, compared to 6 years in females. In multivariable analysis, increasing age, baseline systolic blood pressure and baseline mean arterial pressure (MAP) were associated with increased risk for developing incident hypertension. Also, participants who switched to the integrase strand transfer inhibitor, dolutegravir (DTG) or the protease inhibitor, lopinavir boosted with ritonavir were 2 and 3 times more likely to develop hypertension when compared to those on non-nucleoside reverse transcriptase inhibitors (NNRTIs). However, these relationships were abrogated by sex, as self-reported male sex was the major contributor in predicting incident hypertension. While none of the factors remained significantly associated with incident hypertension upon multivariate analysis among females, body mass index (BMI), and use of protease inhibitors remained strongly associated with hypertension among males.ConclusionOur results indicate that the use of protease inhibitors and BMI are important predictors of incident hypertension among males. Thus, blood pressure and BMI should be closely monitored, particularly in males living with HIV on protease inhibitors. In addition, identifying specific factors that protect females from developing hypertension early is important but remains to be determined.

Non-communicable disease (NCD), including cancer, disproportionately affect Low- and Middle-Income Countries (LMICs). This inequity is in part due to limitations of pathology services, both human and infrastructural. While significant improvements have been made to address these gaps, creative approaches that are mindful of regional priorities, cultural differences, and unique local challenges are needed. In this perspective, we will describe the implementation of telepathology services in sub-Saharan Africa (SSA) that serve as cornerstones for direct patient care, multi-disciplinary care coordination, research programs, and building human capacity through training. Models and challenges of system implementation, sustainability, and pathologist engagement will be discussed. Using disease and site-specific examples, we will suggest metrics for quality control and improvement initiatives that are critical for providing high-quality cancer registry data and necessary for future implementation of therapeutic and interventional clinical trials.

BackgroundSystemic administration of marrow stromal cells (MSCs) leads to the release of a broad range of factors mediating recovery in rodent stroke models. The release of these factors could depend on the various cell types within the peripheral blood as they contact systemically administered MSCs. In this study, we assessed the immunomodulatory interactions of MSCs with peripheral blood derived monocytes (Mϕ) collected from acute stroke patients.MethodsPeripheral blood from stroke patients was collected at 5–7 days (N = 5) after symptom onset and from age-matched healthy controls (N = 5) using mononuclear cell preparation (CPT) tubes. After processing, plasma and other cellular fractions were removed, and Mϕ were isolated from the mononuclear fraction using CD14 microbeads. Mϕ were then either cultured alone or co-cultured with MSCs in a trans-well cell-culture system. Secretomes were analyzed after 24 h of co-cultures using a MAGPIX reader.ResultsOur results show that there is a higher release of IFN-γ and IL-10 from monocytes isolated from peripheral blood at day 5–7 after stroke compared with monocytes from healthy controls. In trans-well co-cultures of MSCs and monocytes isolated from stroke patients, we found statistically significant increased levels of IL-4 and MCP-1, and decreased levels of IL-6, IL-1β, and TNF-α. Addition of MSCs to monocytes increased the secretions of Fractalkine, IL-6, and MCP-1, while the secretions of TNF-α decreased, as compared to the secretions from monocytes alone. When MSCs were added to monocytes from stroke patients, they decreased the levels of IL-1β, and increased the levels of IL-10 significantly more as compared to when they were added to monocytes from control patients.ConclusionThe systemic circulation of stroke patients may differentially interact with MSCs to release soluble factors integral to their paracrine mechanisms of benefit. Our study finds that the effect of MSCs on Mϕ is different on those derived from stroke patients blood as compared to healthy controls. These findings suggest immunomodulation of peripheral immune cells as a therapeutic target for MSCs in patients with acute stroke.

The usage of digital devices in clinical and research settings has rapidly increased. Despite their promise, optimal use of these devices is often hampered by low adherence. The relevant factors predictive of long-term adherence have yet to be fully explored. A recent study investigated device usage over 12 months in a cohort of the electronic Framingham Heart Study. It identified sociodemographic and health-related factors associated with the long-term use of three digital health components: a smartphone app, a digital blood pressure cuff, and a smartwatch. The authors found that depressive symptoms and lower self-rated health were associated with lower smartwatch usage. Female sex and higher education levels were associated with higher app-based survey completion. Here, we discuss factors predictive for adherence and personalized strategies to promote adherence to digital tools.

Artificial intelligence (AI) and natural language processing (NLP) have found a highly promising application in automated clinical coding (ACC), an innovation that will have profound impacts on the clinical coding industry, billing and revenue management, and potentially clinical care itself. Dong et al. recently analyzed the technical challenges of ACC and proposed future directions. Primary challenges for ACC exist at the technological and implementation levels; clinical documents are redundant and complex, code sets like the ICD-10 are rapidly evolving, training sets are not comprehensive of codes, and ACC models have yet to fully capture the logic and rules of coding decisions. Next steps include interdisciplinary collaboration with clinical coders, accessibility and transparency of datasets, and tailoring models to specific use cases.

Background: Posttraumatic stress disorder (PTSD) is a devastating psychological disorder. Patients with PTSD canonically demonstrate an increased risk for inflammatory diseases as well as increased sympathetic tone and norepinephrine outflow. Yet, the exact etiology and causal nature of these physiologic changes remain unclear. Previously, we demonstrated that exogenous norepinephrine alters mitochondrial superoxide in T lymphocytes to produce a proinflammatory T helper 17 phenotype and observed similar T helper 17 polarization in a preclinical model of PTSD. Therefore, we hypothesized sympathetic-driven neuroimmune interactions could mediate psychological trauma–induced T lymphocyte inflammation. Methods: Repeated social defeat stress (RSDS) is a preclinical murine model that recapitulates the behavioral, autonomic, and inflammatory aspects of PTSD. Targeted splenic denervation was performed to deduce the contribution of splenic sympathetic nerves to RSDS-induced inflammation. Denervation or sham operation was performed in 85 C57BL/6J mice, followed by RSDS or control paradigms. Animals were assessed for behavioral, autonomic, inflammatory, and redox profiles. Results: Denervation did not alter the antisocial or anxiety-like behavior induced by RSDS. In circulation, denervation/RSDS animals exhibited diminished levels of T lymphocyte–specific cytokines (interleukin 2 [IL-2], IL-17A, and IL-22) compared with intact animals, whereas other nonspecific inflammatory cytokines (e.g., IL-6, tumor necrosis factor α, and IL-10) were unaffected by denervation. Importantly, denervation specifically ameliorated the increases in RSDS-induced T lymphocyte mitochondrial superoxide, T helper 17 polarization, and proinflammatory gene expression with minimal impact to non–T lymphocyte immune populations. Conclusions: Overall, our data suggest that sympathetic nerves regulate RSDS-induced splenic T lymphocyte inflammation but play less of a role in the behavioral and non–T lymphocyte inflammatory phenotypes induced by this psychological trauma paradigm.