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Aims: To compare the accuracy of marginal fit of CAD-CAM endocrown with two different preparation forms, i.e., endocrown with ferrule and endocrown without ferrule. Settings and Design: Various studies have opined on the impact of preparation form on the marginal fit of endocrown, but studies on the effect on the marginal fit of digitally milled endocrown with and without ferrule are sparse. Materials and Methods: Total of 30 typodont were sectioned 3 mm above the cemento-enamel junction, and central cavity was prepared to depict a severely destructed tooth. The typodonts were divided into two groups: Group 1 contained specimens for endocrown without ferrule (WoF); Group 2 contained specimens for endocrown with ferrule (WF). The typodonts were prepared based on standard preparation. The specimens were then scanned using intraoral scanner, and the stereolithography (STL) was generated. Endocrowns were designed in the Exocad software using a digital library. The STL file format is translated into millable data file format (CNC- Computer numerical control) in the inLAB MC X5 Milling machine. The marginal fit of endocrowns was then assessed in the stereomicroscope. Statistical Analysis: The data was analysed with a digital image analyser. The result was generated using a two-way ANOVA test. The significance level was set at P ≤ 0.05. Results: In the present study, the marginal fit of WoF showed a superior marginal fit than WF. A statistically significant difference was seen in the marginal fit of two endocrowns, with a higher marginal discrepancy observed in the endocrown with the ferrule. The P value for the difference in the means of the marginal gap without and with ferrule (-13.42) is zero. Maximum marginal gap of 96 micron is observed for with ferrule (WF) design at location B. Minimum marginal gap of 29 micron is observed for without ferrule (WoF) at location D. Conclusions: Endocrown without a ferrule can provide a better marginal fit and can contribute to the long-term survival of restoration.

Abstract Mitochondrial function is modulated by its interaction with the endoplasmic reticulum (ER). Recent research indicates that these contacts are disrupted in familial models of amyotrophic lateral sclerosis (ALS). We report here that this impairment in the crosstalk between mitochondria and the ER impedes the use of glucose-derived pyruvate as mitochondrial fuel, causing a shift to fatty acids to sustain energy production. Over time, this deficiency alters mitochondrial electron flow and the active/dormant status of complex I in spinal cord tissues, but not in the brain. These findings suggest mitochondria-associated ER membranes (MAM domains) play a crucial role in regulating cellular glucose metabolism and that MAM dysfunction may underlie the bioenergetic deficits observed in ALS.

Background: Inherited disorders of hemoglobin (hemoglobinopathies) are the most common genetic disorders in the world with 7% prevalence. Thalassemia and sickle cell anemia are the most prevalent hemoglobinopathies in India. Screening and diagnosis of hemoglobinopathies require a comprehensive evaluation combining clinical and family history, blood counts, red blood cell indices, and molecular analysis. Aims and Objective: (1) To differentiate the type of hemoglobinopathies on the basis of red cell parameters, (2) to assess the spectrum of hemoglobinopathies, and (3) to study the age at diagnosis and genderwise distribution of various hemoglobinopathies. Material and Methods: A prospective observational study over a period of 1 year (August 2020 to July 2021) at a tertiary care hospital, Rajkot, Gujarat. All indoor patients’ samples were sent for complete blood count (CBC), peripheral smear examination, reticulocyte count, sickling test, and high-performance liquid chromatography (HPLC). Result: A total of 140 subjects were included in the final analysis. The mean age at diagnosis was 24.7 ± 10.5 years; 48 participants were male, and the remaining 92 were female with an M:F ratio of 0.5:1. The most common hemoglobinopathy in this study was sickle cell trait (40 cases, 28.6%). Conclusion: To reduce the burden of various hemoglobinopathies, screening is recommended as a part of antenatal checkup and in infants after 6 months of age in high-prevalence districts for particular hemoglobinopathies via CBC including RBC indices and HPLC.

Fungi and their natural products, like secondary metabolites, have gained a huge demand in the last decade due to their increasing applications in healthcare, environmental cleanup, and biotechnology-based industries. The fungi produce these secondary metabolites (SMs) during the different phases of their growth, which are categorized into terpenoids, alkaloids, polyketides, and non-ribosomal peptides. These SMs exhibit significant biological activity, which contributes to the formulation of novel pharmaceuticals, biopesticides, and environmental bioremediation agents. Nowadays, these fungal-derived SMs are widely used in food and beverages, for fermentation, preservatives, protein sources, and in dairy industries. In healthcare, it is being used as an antimicrobial, anticancer, anti-inflammatory, and immunosuppressive drug. The usage of modern tools of biotechnology can achieve an increase in demand for these SMs and large-scale production. The present review comprehensively analyses the diversity of fungal SMs along with their emerging applications in healthcare, agriculture, environmental sustainability, and nutraceuticals. Here, the authors have reviewed the recent advancements in genetic engineering, metabolic pathway manipulation, and synthetic biology to improve the production and yield of these SMs. Advancement in fermentation techniques, bioprocessing, and co-cultivation approaches for large-scale production of SMs. Investigators further highlighted the importance of omics technologies in understanding the regulation and biosynthesis of SMs, which offers an understanding of novel applications in drug discovery and sustainable agriculture. Finally, the authors have addressed the potential for genetic manipulation and biotechnological innovations for further exploitation of fungal SMs for commercial and environmental benefits.

Abstract Background Injection drug use (IDU) may lead to negative health outcomes and increased healthcare utilization. In US Veterans (USV) with opioid use disorder (OUD), there is sparse information about healthcare utilization, harm reduction prescription, and outcomes associated with IDU, including severe injection-related infections (SIRI). We assessed psychosocial factors, clinical outcomes, and harm reduction receipt in a cohort of USV with OUD, specifically focusing on persons who inject drugs (PWID). Methods A retrospective cohort study was performed of USV aged ≥ 18 years with a diagnosis of OUD who presented to the Northport Veterans Affairs Medical Center (Long Island, NY) between 2012 and 2022. Demographics, psychosocial factors, history of human immunodeficiency virus (HIV), hepatitis C virus (HCV) infection, and healthcare utilization were compared by IDU status. Prescription of medications for opioid use disorder, naloxone and pre-exposure prophylaxis (PrEP) for HIV were also compared by IDU status. SIRI episodes and associated sequelae were characterized in USV with IDU. Results A total of 502 USV with OUD were included and 216 (43%) were PWID. Mean age was 52.6 years. PWID were more likely to use multiple stimulants (14.4% PWID vs. 7.3% non-PWID, p

Abstract The creation of new alloys with improved qualities has become essential in modern industries for high-performance materials. This work’s main objective is to use vacuum arc melting (VAM) to synthesize two different high-entropy alloys (HEAs): AlCrFeNiCu and AlCrFeNiCo. The mechanical properties, phase composition, grain boundaries, and alloy composition of the HEAs were studied. The predominant crystal structure, the Body-Centred Cubic (BCC) phase was obtained for both alloys. Significantly, the Co-containing HEA showed a smaller particle size than the Cu-containing HEA, which led to a 14.21% increase in microhardness. It indicates that the Co-based HEA will likely perform better than the Cu-based HEA in applications prone to abrasion, and indentation, and requiring high hardness levels based on the observed microstructure and hardness parameters. According to wear surface morphology studies, main effects analysis and ANOVA show that increasing loads and sliding distances increase wear rate, whereas sliding velocity has less effect. The best wear rate-reducing parameters are 10 N, 0.5 m/s, and 500 m for Cu-containing HEAs, and the same can be predicted using regression analysis. The study categorizes the intricate worn surface structure by describing different surface properties and wear mechanisms, such as grooves, delamination, adhesive wear, and pitting.

Abstract Background The use of machine learning (ML) in mental health (MH) research is increasing, especially as new, more complex data types become available to analyze. By examining the published literature, this review aims to explore the current applications of ML in MH research, with a particular focus on its use in studying diverse and vulnerable populations, including immigrants, refugees, migrants, and racial and ethnic minorities. Methods From October 2022 to March 2024, Google Scholar, EMBASE, and PubMed were queried. ML-related, MH-related, and population-of-focus search terms were strung together with Boolean operators. Backward reference searching was also conducted. Included peer-reviewed studies reported using a method or application of ML in an MH context and focused on the populations of interest. We did not have date cutoffs. Publications were excluded if they were narrative or did not exclusively focus on a minority population from the respective country. Data including study context, the focus of mental healthcare, sample, data type, type of ML algorithm used, and algorithm performance were extracted from each. Results Ultimately, 13 peer-reviewed publications were included. All the articles were published within the last 6 years, and over half of them studied populations within the US. Most reviewed studies used supervised learning to explain or predict MH outcomes. Some publications used up to 16 models to determine the best predictive power. Almost half of the included publications did not discuss their cross-validation method. Conclusions The included studies provide proof-of-concept for the potential use of ML algorithms to address MH concerns in these special populations, few as they may be. Our review finds that the clinical application of these models for classifying and predicting MH disorders is still under development.

Abstract Lecithin-cholesterol acyltransferase (LCAT) serves as a pivotal enzyme in preserving cholesterol homeostasis via reverse cholesterol transport, a process closely associated with the onset of atherosclerosis. Impaired LCAT function can lead to severe LCAT deficiency disorders for which no pharmacological treatment exists. LCAT-based therapies, such as small molecule positive allosteric modulators (PAMs), against LCAT deficiencies and atherosclerosis hold promise, although their efficacy against atherosclerosis remains challenging. Herein we utilized a quantitative in silico metric to predict the activity of novel PAMs and tested their potencies with in vitro enzymatic assays. As predicted, sodium-glucose cotransporter 2 (SGLT2) inhibitors (gliflozins), sucrose and flavonoids activate LCAT. This has intriguing implications for the mechanism of action of gliflozins, which are commonly used in the treatment of type 2 diabetes, and for the endogenous activation of LCAT. Our results underscore the potential of molecular dynamics simulations in rational drug design.

Introduction Primary healthcare is broadly acknowledged as the cornerstone of any strategy aimed at achieving Universal Health Coverage (UHC). This study aims to evaluate the costs, work patterns and efficiency of comprehensive primary healthcare (CPHC) in India.Methods and analysis We will use a top-down microcosting approach to estimate the economic cost of services delivered at the primary healthcare facilities in India. A multistage stratified random sampling approach will be applied to select the primary healthcare facilities—Ayushman Arogya Mandirs (AAMs), formerly Health and Wellness Centres (HWCs). First, states will be selected based on key supply-side and demand-side healthcare indicators. Second, two districts will be chosen in each state based on advanced functionality criteria of AAMs. Finally, AAM-subhealth centres (SHCs) and AAM-primary health centres (PHCs) will be randomly selected within each district, implying a total of 48 SHCs and 24 PHCs. Data on both quantity and prices of capital (such as space, building, equipment and furniture) and recurrent resources (including salaries, medicines, consumables, stationery and overheads) used for delivering primary healthcare services during the period from April 2022 to March 2023 will be collected. All costs will be reported in current India Rupees (₹) and US Dollar (USD) ($) at an exchange rate of $1 = ₹86. A time and motion study will be undertaken to collect data from a total of 48 Community Health Officers (CHOs) and 48 auxiliary nurse midwives (ANMs) over a period of 6 days. This will be complemented by interviews to ascertain time spent on various services and activities. The data will be analysed to derive the annual cost of delivering CPHC services at an AAM, unit cost of individual services as a part of the 12 CPHC packages, as well as time spent by the healthcare workers (CHO and ANM) on various activities and services. Finally, a data envelopment analysis will be used to assess the level of technical efficiency in delivering primary healthcare services. The evidence on cost generated through the study will be useful for decisions related to better planning of healthcare services by aligning the work pattern to desired goals, efficient resource allocation, as well as future research on cost-effectiveness and benefit incidence over health accounts of primary healthcare services.Ethics and dissemination The study has been approved by the Institute Ethics Committee of the Post Graduate Institute of Medical Education and Research, Chandigarh, India vide IEC no: PGI/IEC/2023/EIC000588. The study results will be published in peer-reviewed journals and presented to the policymakers at the national level. Furthermore, the cost estimates generated by the study will be integrated into the National Health System Cost Database for India, providing information to policymakers and researchers.

This research investigates the intricate flow behavior of hybrid nanofluids based on the non-Newtonian Eyring–Powell model over a stretched porous inclined cylinder or plate, with significant applications in biomedical and industrial fields. The study incorporates electromagnetic hydrodynamics, Darcy-Forchheimer effects, and advanced heating mechanisms such as Joule heating, non-linear thermal radiation, and non-uniform heat sources, with Cu-Fe₃O₄ nanoparticles dispersed in blood. These analyses aim to optimize cancer therapy through enhanced hyperthermia techniques and facilitate the development of biosensors for precise biomolecule detection in diagnostic applications. Furthermore, the effects of buoyancy forces, mass transfer, chemical reactions, and bioconvective flow involving gyrotactic microorganisms under multi-slip, conducting, and radiating boundary conditions are examined. The thermal conductivity of nanoparticles with different shapes is evaluated to tailor heat transfer efficiency for diverse biomedical and industrial processes, such as drug delivery systems and cooling mechanisms in microfluidics. With rise in conduction-radiation parameter the escalation in temperature of the system is obtained. For greater buoyancy ratio parameter, the velocity of the fluid gets reduced. Employing similarity transformations, the mathematical model reduces the governing equations to ordinary differential forms, which are solved using MATLAB's bvp4c solver. Graphical interpretations reveal the impact of various parameters.

Antibiotics are extensively used in layer flocks for the prevention of diseases and to enhance their growth and production. However, their nonprudent use is leading to the occurrence of residues in eggs. The present study aimed at the detection of tetracycline group residues in egg samples collected from layer farms located in Haryana, India, and human health risk assessment. A total of 100 pooled egg samples were analyzed using High-Performance Liquid Chromatography with Ultraviolet detector for the detection of tetracycline group residues. Out of 100 pooled samples, 13 (13%) were found to be contaminated with tetracycline residues (12 for chlortetracycline and one for tetracycline). Of these, five (38.5%) samples (one for tetracycline and four for chlortetracycline) exceeded the maximum residue limit (MRL) established by Food Safety and Standards Authority of India. The risk assessment based on the per capita availability of eggs in Haryana revealed that the current levels of residues in eggs pose no significant toxicological effects on the consumer’s health. The residues exceeding MRL indicate nonprudent use of antibiotics in veterinary practices, which could lead to the emergence of antibiotic resistance. There is a need to generate awareness among farmers toward judicious antibiotic usage in layer birds and adherence to withdrawal periods to prevent the escalating problem of antibiotic resistance.

Collagenofibrotic Glomerulopathy (CG) is a very rare glomerular disease characterised by the massive accumulation of atypical type III collagen fibrils within the mesangial matrix and subendothelial space, as well as a marked increase in serum type III procollagen peptide levels. Owing to its rarity, the cause and pathogenesis of CG remain uncertain. While initial reports of CG were primarily in patients of Asian descent, subsequent cases in patients of European descent have also been published. Clinically, patients present with oedema and hypertension, often progressing to end-stage renal disease. Proteinuria is a cardinal manifestation of this disease. A definitive diagnosis is contingent upon recognising this entity, maintaining a high index of suspicion, and confirming it through immunohistochemistry and Electron Microscopy (EM), due to its rarity, non specific presenting signs and symptoms, and various differential diagnoses on histology. Here, a case of a 44-year-old non diabetic, hypertensive female who presented with pedal oedema and nephrotic range proteinuria. The biopsy showed nodular expansion of the mesangium by homogeneous, congo red-negative, eosinophilic material, along with vascular changes indicative of acute thrombotic microangiopathy. Many conditions, such as amyloidosis, fibrillary glomerulonephritis, diabetic nephropathy, fibronectin glomerulopathy, light chain deposition disease, and thrombotic microangiopathy, can cause nodular or membranoproliferative glomerular changes. The biopsy was initially reported as nodular glomerulosclerosis, which, upon EM, showed mesangial and subendothelial space expansion by banded fibrillary material. Further immunohistochemistry for type III collagen was performed, which yielded positive results. Thus, the diagnosis of CG was confirmed.

The current study is based on a predator-prey model with infection that affects only predator species. Predators are divided into two categories such as the susceptible predator and the infected predator, which are feeding on prey species. The Takagi-Sugeno (T-S) based fuzzy impulsive control model was used to explore the stability of the Lotka-Volterra predator-prey system. Numerical simulation provides global stability and the fuzzy solution.

Rheumatoid arthritis (RA), a condition characterized by joint deterioration through the action of matrix metalloproteinases (MMPs), is prevalent worldwide. Bee venom (BV) has traditionally been used in Chinese medicine for pain, arthritis, rheumatism, skin diseases, etc. BV is enriched with active substances, notably melittin and phospholipase A2 (PLA2), offering significant therapeutic potential. Hence, the review summarizes current insights into BV’s composition, antiarthritic mechanism and pharmacological benefits, focusing on melittin. Constituting 50-60% of BV, melittin notably downregulates nuclear factor Kappa B (NF-κB) activity, inhibits MMP-1 and MMP-8, and diminishes tumor necrosis factor (TNF-α), all of which contribute to the mitigation of type 2 collagen degradation. Despite its potential, melittin exhibits hemolytic activity and can significantly affect cell membranes, limiting its application, which poses a challenge to its therapeutic use. To overcome these challenges, delivery techniques utilizing nanocarriers and modifications in amino acid sequencing have been developed. Recent advancements in delivery systems, including nanocarriers, transdermal patches, and nanoemulsions, aim to minimize toxicity, expanding its therapeutic utility for RA. This article explores these novel strategies, underlining the evolving role of melittin in RA management.

Aim: In the osteosynthesis of mandibular condylar fractures, the goal had been to assess the stability of a single trapezoidal-shaped 3-D condylar plate. Materials and Methods: We evaluated 15 individuals who had mandibular condylar fractures. Under general anesthesia, the chosen patients underwent open reduction and fixation using three-dimensional titanium miniplates called trapezoidal condylar plates (TCPs). The Mini Retro Mandibular Approach and the Trans Masseteric Antero Parotid Approach were used to treat each of these fractures. Results and Conclusion: The three-dimensional Trapezoidal Condylar Plate titanium miniplates were found to be an efficient osteosynthesis device for stabilising condylar fracture and hence, yielded acceptable results in terms of achieving anatomical and functional stability.

This research presents a novel approach to fabricating Yttrium Aluminum Garnet (YAG) nanofibers doped with Gadolinium (Gd3+) ions using the electrospinning technique. Rare earth-doped electrospun nanofibers, known for their exceptional performance, attract significant interest for applications in flexible display devices. While Gd3+-doped YAG materials have been studied, this is the first instance of their synthesis in nanofiber form, enhancing their optical and emission properties, particularly in the ultraviolet-B i.e. UV-B (280–315 nm) range. The study aims to develop and characterize these nanofibers with varying Gd3+ concentrations (x = 0.5, 1, 1.5, 2 mol%), employing techniques like X-Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-Ray Photoelectron Spectroscopy (XPS), and photoluminescence to analyze structural integrity, surface morphology, and luminescence. XRD confirmed the pure YAG phase after calcination at 950 °C for 2 hrs, and the nanofibers showed a strong emission peak at 313 nm under 274 nm excitation corresponding to the 6P7/2 → 8S7/2 transition, with optimal photoluminescence at 1 mol% Gd3+ doping. These results highlight the potential of Gd3+-doped YAG nanofibers for advanced applications in flexible electronics and UV-based display devices.

Tumour is a very serious and dangerous health risk, which is defined as a mass or lump of tissue formalized by the aggregation of abnormal cells. In this paper, we have presented a comparative and chaotic investigation of tumour and effector cells using non-integer order tumour immune dynamical model. Also, we have looked at the interactions between different tumour cell populations and immunological composition using a model of a real-world medical research problem. Additionally, stability analysis of the proposed model is established with the help of fixed-point iteration. Further bifurcation diagrams, as well as phase portraits, have been used to study the proposed system numerically and to analyse its behaviour. For numerical simulations, we have used the Hermite wavelet operational matrix and Taufik-Atangana methods using Caputo fractional derivatives. models. The main objective of the paper is to convert nonlinear fractional systems into algebraic equations. Our findings will be valuable to biologists in cancer treatment.

This paper presents wavelet and other numerical techniques for solving systems of tumour-immune-vitamin intervention (TIV) model with non-integer order and nonlinear. For the first time, fractional order TIV system has been solved by using Bernstein wavelet collocation method (BWCM). This process uses wavelet approximations depend on Bernstein wavelets and their non-integer integral to transform non-integer differential systems into algebraic equation. This fractional TIV model will represent the effects of memory on the system. Three elements make up this partial sequence TIV system: vitamin intervention, immune cells, and tumour cells. Boundedness and non-negativity, residual error and convergence analysis of solutions have been determined using the iterative approach and BWCM. This investigation shows that the technique is very much useful and efficient for TIV intervention. Also, we have discussed the existence and uniqueness of the non-integer order TIV model. According to the findings, the TIV system would benefit from the use of the BWCM and this numerical method will open more research. Our findings will be valuable to biologists and researcher in the treatment of TIV.

This paper presents a mathematical model to examine the effects of the coexistence of predators on single prey. Based on Caputo operators, we present a newly developed system of differential equations for the predator–prey system using wavelet method. It is well known that a system of nonlinear singular models cannot operate smoothly since they are singular and nonlinear. Therefore, with the help of this numerical approach, we have converted the system into a nonlinear system of algebraic equations by extending it through operational matrix of Legendre wavelets. Using the wavelet collocation scheme, we have calculated these unknown coefficients. It has been demonstrated in tables and graphs that the developed approach is consistent and proficient. Further bifurcation diagrams, as well as phase portraits, have been used to study the proposed system numerically and to analyse its behaviour. In addition, a nonlinear functional analysis have used to establish uniformly boundedness for the proposed model. Also we have discussed residual error analysis and Lyapunov exponent. The applicability and efficacy of this methodology have been demonstrated through this nonlinear system. Additionally, a comparison with existing results highlights the advantages of our numerical approach. All calculations have been done using MATLAB.

The research explored the critical examination of unsteady second-grade Tri-hybrid nanofluid flow between parallel disks within a Darcy-Forchheimer medium with porosity. The study focusses on a fluid comprised of Au, TiO2, and Ag solid nanoparticles within blood, encompassing various shapes such as brick, blade, and platelet. It thoroughly investigated the impacts of Soret and Dufour effects in conjunction with MHD, joule heating, and the presence of a heat source. Furthermore, it elucidated thermally radiative effects and considers slip and convective boundary conditions, as well as mass transfer with a chemical reaction. The research also encompassed the influence of suction/injection on the squeezing flow. As the second-grade fluid parameter increases, the velocity of the fluid rises, especially when the η < 0.4. However, when η > 0.4, the velocity decreases. Additionally, the Biot numbers exhibit different effects depending on their application to the lower and upper disks. Specifically, Bi1 enhances the system's temperature, while Bi2 reduces it. The comprehensive mathematical formulation incorporates all these effects, later transformed into ODEs using similarity transformation conditions. Employing the optimal homotopy analysis technique in Mathematica software, the study graphically characterized velocity, temperature, and concentration profiles. The research's credibility is ascertained through validation against previous work by other researchers.

Objective Arrhythmia detection and classification are challenging because of the imbalanced ratio of normal heartbeats to arrhythmia heartbeats and the complicated combinations of arrhythmia types. Arrhythmia classification on wearable electrocardiogram monitoring devices poses a further unique challenge: unlike clinically used electrocardiogram monitoring devices, the environments in which wearable devices are deployed are drastically different from the carefully controlled clinical environment, leading to significantly more noise, thus making arrhythmia classification more difficult. Methods We propose a novel hierarchical model based on CNN+BiLSTM with Attention to arrhythmia detection, consisting of a binary classification module between normal and arrhythmia heartbeats and a multi-label classification module for classifying arrhythmia events across combinations of beat and rhythm arrhythmia types. We evaluate our method on our proprietary dataset and compare it with various baselines, including CNN+BiGRU with Attention, ConViT, EfficientNet, and ResNet, as well as previous state-of-the-art frameworks. Results Our model outperforms existing baselines on the proprietary dataset, resulting in an average accuracy, F 1-score, and AUC score of 95%, 0.838, 0.906 for binary classification, and 88%, 0.736, 0.875 for multi-label classification. Conclusions Our results validate the ability of our model to detect and classify real-world arrhythmia. Our framework could revolutionize arrhythmia diagnosis by reducing the burden on cardiologists, providing more personalized treatment, and achieving emergency intervention of patients by allowing real-time monitoring of arrhythmia occurrence.

BackgroundSystemic Lupus Erythematosus (SLE) is characterized by dysregulated immune responses, with neutrophil extracellular traps (NETs) playing a significant role. NETs are recognized by autoantibodies in SLE patients, exacerbating pathology. Both excessive NET formation and impaired degradation contribute to SLE pathophysiology.ObjectiveTo investigate the immunomodulatory effects of Dexamethasone-primed Wharton’s jelly (WJ) derived MSCs CM (DW) and IFN-γ-primed WJ-MSCs-CM (IW) on NETosis and associated protein markers in SLE patients’ LPS or ribonucleoprotein immune complexes (RNP ICs) induced neutrophils and in pristane induced lupus (PIL) model. And to elucidate the mechanism involved therein.MethodsWe investigated the immunomodulatory effects of DW and IW on NETosis in SLE. Utilizing ex vivo and in vivo models, we assessed the impact of preconditioned media on NET formation and associated protein markers neutrophil elastase (NE), citrullinated histone (citH3), myeloperoxidase (MPO), cytoplasmic and mitochondrial ROS production. We also examined the involvement of key immunomodulatory factors present in DW and IW, including prostaglandin E2 (PGE2), indoleamine 2,3-dioxygenase (IDO), and transforming growth factor-beta (TGF-β).ResultsPreconditioned media effectively suppressed NETosis and reduced ROS generation in SLE neutrophils, indicating their immunomodulatory potential. Inhibition studies implicated IDO and PGE2 in mediating this effect. Combined treatment with DW or IW together with hydroxychloroquine (HCQ) demonstrated superior efficacy over HCQ alone, a standard SLE medication. In PIL mouse model, DW and IW treatments reduced NETosis, ROS generation, as evidenced by decreased NET-associated protein expression in vital organs.ConclusionOur study highlights the multifaceted impact of IW and DW on NETosis, ROS dynamics, and lupus severity in SLE. These findings underscore the potential of preconditioned media for the development of targeted, personalized approaches for SLE treatment.

Hepatitis C virus infection is one of the main causes of liver disease that can lead to liver cirrhosis and finally to the chronic development of Hepatocellular Carcinoma (HCC). With 8 different HCV genotypes circulating, it becomes necessary to characterize the pathogenesis caused by each one of the HCV genotypes infecting population of a particular setting. Present study aims to identify the circulating Hepatitis C virus (HCV) genotypes in the different areas of State of Uttar Pradesh, India and understand their clinical etiology and related co-morbidities. The patients reporting to Sharda Hospital, Uttar Pradesh, India who were diagnosed positive for HCV were included in the study. The informed consent was obtained and then blood was drawn. In-house primers, for all the 8 genotypes were prepared and RT-PCR was performed. The amplified product was subjected to Agarose gel electrophoresis to identify the genotypes present in individual samples. Total 30 serum samples were taken. Of these, 21 (70%) showed presence of multiple genotypes, while 7 (23.33%) showed positivity for single genotype and two did not show any bands. Presence of multiple genotypes in individual patient has been reported for the first time. The pathological consequences of multiple genotypes within one host need to be studied further in terms of increased risk of developing a chronic liver disease. Further studies are being undertaken to study association of specific HCV genotype and multiple genotypes, Core, NS3 and NS5 viral proteins with the disease progression to develop predictors of liver cirrhosis and HCC.

Abstract Genetic mutations causing primary mitochondrial disease (i.e those compromising oxidative phosphorylation [OxPhos]) resulting in reduced bioenergetic output display great variability in their clinical features, but the reason for this is unknown. We hypothesized that disruption of the communication between endoplasmic reticulum (ER) and mitochondria at mitochondria-associated ER membranes (MAM) might play a role in this variability. To test this, we assayed MAM function and ER-mitochondrial communication in OxPhos-deficient cells, including cybrids from patients with selected pathogenic mtDNA mutations. Our results show that each of the various mutations studied indeed altered MAM functions, but notably, each disorder presented with a different MAM “signature”. We also found that mitochondrial membrane potential is a key driver of ER-mitochondrial connectivity. Moreover, our findings demonstrate that disruption in ER-mitochondrial communication has consequences for cell survivability that go well beyond that of reduced ATP output. The findings of a “MAM-OxPhos” axis, the role of mitochondrial membrane potential in controlling this process, and the contribution of MAM dysfunction to cell death, reveal a new relationship between mitochondria and the rest of the cell, as well as providing new insights into the diagnosis and treatment of these devastating disorders.

Abstract Background In this work, we represent synthesis, in silico analysis and biological activity of 1,4 diazepine linked piperidine derivatives (6a–6o). All the derivatives were screened for their anti-microbial activity against gram-positive (Staphylococcus aureus, Bacillus Subtills, Bacillus megaterium) and gram-negative (Escherichia coli, Pseudonymous, Shigella sp.) bacteria. Compounds were synthesized from reaction of tert-butyl 1,4-diazepane-1-carboxylic, butyryl chloride and varied aromatic aldehyde, further characterized by 1H NMR and LCMS spectral techniques. Result Using ampicillin as a positive control, the synthetic compounds 6a–6o were tested for their in-silico study and experimental anti-microbial activity against gram-positive (Staphylococcus aureus, Bacillus Subtills, Bacillus megaterium) and gram-negative (Escherichia coli, Pseudonymous, Shigella sp.) bacteria. According to in vitro assay compound 6a, compound 6c, compound 6d, compound 6m and compound 6I showed higher activity against all the tested strains. Molecule 6i, compound 6j, compound 6k, compound 6f has good to moderate antibacterial activity. DFT computations were used to optimize the molecular geometry at the B3LYP/6-31G (d, p) theoretical level. The corresponding energy values of molecular orbitals were visualized using optimized geometries. Moreover, Auto Dock Vina 1.2.0 is used to assess molecular docking against two target proteins, Bacillus subtilis (PDB ID: 6UF6) and Protease Vulgaris (PDB ID: 5HXW). The target molecule 6b displayed the best binding energies for both. Additionally, we calculated the ADME for each molecule (6a–6o). Conclusion All fifteen synthesized compounds were screened for their in vitro and in silico analysis. In vitro analysis for anti-microbial activity was carried out against gram-positive (Staphylococcus aureus, Bacillus Subtills, Bacillus megaterium) and gram-negative (Escherichia coli, Pseudonymous, Shigella sp.) bacteria and compound 6a, compound 6c, compound 6d, compound 6m and compound 6I exhibits more potent activity towards all tested strains. Molecular docking is performed against target proteins, L-amino acid deaminase from Proteus Vulgaris and LcpA ligase from Bacillus subtilis, representing the Gram-negative bacterium and Gram-positive bacterium, respectively. Compound 6b showed the highest no. of interaction with protein according to molecular docking. With the advent of innovative techniques like ADME, we select their hit compounds early on and anticipate future pharmacokinetic and pharmacodynamic benefits and drawbacks of these promising therapeutic candidates. Graphical abstract

Paediatric Clinical Care Pathways (CCPs) are developed for specific health conditions or patient populations and are designed to standardise care across different healthcare settings, including hospitals, clinics, and outpatient settings. These care pathways outline the clinical guidelines for diagnosis, treatment, and follow-up of specific medical conditions. They provide a framework for the delivery of care based on the best available evidence and tailored to each patient's individual needs. This overview is aimed at identifying the available evidence for the effective use of CCPs in paediatric patients with Lower Respiratory Tract Infection (LRTI). It reviews the nature of CCPs of LRTI, their benefits, strategies to implement them, steps involved in development of CCPs and the disease condition in paediatric population for whom the CCPs are used so far. The article also gives an account of limitations of using CCPs.

The trihelix transcription factors (THX TFs) play a crucial role in light responses and are involved in plant growth, development, and stress responses. In this study, we have identified 35 trihelix TFs in pearl millet (Pennisetum glaucum), which is one of the most widely grown C4 cereal crops in tropical semi-arid regions. Identified PgTHXs (Trihelix members of P. glaucum) were classified into 5 subgroups (GT1, GT2, GTγ, SH4, and SIP1) based on phylogenetic analysis, and these subgroup members shared similar gene structure and motif distribution pattern. Collinearity analysis exhibited gene duplication events of trihelix family members in pearl millet across the genome. Gene ontology (GO) annotation and cis-regulatory elements (CREs) analysis of PgTHXs suggested their involvement in diverse biological and molecular functions associated with plant growth, development, and stress responses. RNA sequencing data and expression profile displayed differential expression patterns of PgTHXs under abiotic stress and phytohormone treatments. The induced expression pattern of the PgTHX4, PgTHX5, PgTHX24, and PgTHX30 suggested their potential involvement in abiotic stress responses through phytohormonal signalling pathways. Among these, PgTHX24, a GT-3b member, was localized in the nucleus with self-transactivation ability. Overexpression of PgTHX24 positively regulated expression of stress-related markers in transformed pearl millet calli under drought stress conditions. Promoter activity analysis also highlighted the stress-inducible nature of PgTHX24’s promoter. Overall, our findings provide a comprehensive understanding of PgTHXs with a framework for further functional characterization to understand their regulatory role in pearl millet’s growth, development, and stress responses. Key message: Thirty-five trihelix TFs were identified in pearl millet, and a comprehensive expression profile highlighted their functional diversity. Overexpression of PgTHX24 exhibited its potential involvement in abiotic stress responses.

Economic outputs are an attractive prospect in any field and hence agriculture also relies heavily on economic stability. The costs associated with cotton farming are increasing and profitability is taking a hit in cotton cultivation. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. Present study was carried out during 2022 to 2023 in Haryana to provide some insights into the possible future prices of cotton (Gossypium spp.) with the help of data collected from AGMARKNET and various major cotton markets (Adampur, Sirsa and Fatehabad) of Haryana. The Autoregressive Integrated Moving Average (ARIMA) models have been employed in order to forecast the prices of cotton crops for the years 2022–23 to 2027–28. Through a meticulous exploration of various combinations of lagged moving average and autoregressive components, the ARIMA (1,1,1) model was selected as the most suitable for the price forecasting in these districts. The results of this analysis demonstrate that the coefficient of determination (R2) for the forecasted cotton crop prices in comparison to the real-time prices falls within acceptable ranges. This finding underscores the efficacy of the ARIMA (1,1,1) model as a reliable tool for generating short-term price estimates. This model offers valuable insights and predictive accuracy, aiding decision-makers and stakeholders in the cotton industry of Adampur, Sirsa and Fatehabad markets to make informed choices and plan effectively for the coming years. Cotton prices vary according to the season and the region, hence a valuable insight on future price assumptions will help the agriculture community.

Background Smoking cessation is linked to improved mental health that encompasses the overall well-being and psychological functioning of an individual. Objective Examine relationships between smoking, mental health, and social connectedness among adults in Maryland, US in 2020. Methodology This cross-sectional study used data from the Maryland 2020 Behavioral Risk Factor Surveillance System Survey of adults during the onset of COVID-19. Primary outcomes measured include demographics, depression, and number of not good mental health days among individuals with current and former smoking statuses compared to those who have never smoked. Results Compared to those who never smoked, individuals who currently smoked had an increased relative risk of reporting 14 or more days of not good mental health (RRR = 1.63, 95% CI: 1.35-1.97, P < .001) and a history of depression (RRR = 1.99, 95% CI: 1.69-2.35, P < .001). Individuals with former smoking status also showed elevated risk, with RRR = 1.24 (95% CI: 1.06-1.45, P = .006) for 14 or more days of not good mental health and RRR = 1.46 (95% CI: 1.28-1.66, P < .001) for a history of depression. Widowed, separated, or divorced; unemployed or unable to work; without a high school diploma; or recent physical exam were inclined to have a current or former smoking status. Conclusion We identify critical subpopulations vulnerable to life-long smoking behaviors amid the COVID-19 pandemic including adults under 35 years old, and those suffering from depression, a lack of social connectedness due to unemployment, changes in marital status, and outdated physical exams. The US Surgeon General’s 2023 Advisory on the epidemic of loneliness and the 2021 Youth Mental Health Report emphasize the mental health crises among the young in which these findings serve as a compelling call to action for innovating targeted public health interventions.

In the research investigation exploring the effects of Advanced Yogasanas on psycho-biochemical parameters, a cohort of 67 adult yoga practitioners, spanning ages 20 to 54 (with a mean age of 28.94±6.95), actively engaged in an extensive one-month training program facilitated by certified yoga instructors. The sessions were conducted during evening hours, specifically from 4 to 7 pm, ensuring a consistent and structured learning environment. To evaluate the psychological impact, participants underwent assessments employing The Mindful Attention Awareness Scale (MAAS) for Attention and the Self-Efficacy Scale for Self-efficacy. The outcomes revealed remarkable improvements in Attention scores (p

Promoters are one of the most important components for many gene-based research as they can fine-tune precise gene expression. Many unique plant promoters have been characterized, but strong promoters with dual expression in both monocot and dicot systems are still lacking. In this study, we attempted to make such a promoter by combining specific domains from monocot-infecting pararetroviral-based promoters sugarcane bacilliform virus (SCBV) and banana streak virus (BSV) to a strong dicot-infecting pararetroviral-based promoter mirabilis mosaic virus (MMV). The generated chimeric promoters, MS, SM, MB, and BM, were tested in monocot and dicot systems and further validated in transgenic tobacco plants. We found that the developed chimeric promoters were species-specific (monocot or dicot), which depended on their respective core promoter (CP) region. Furthermore, with this knowledge, deletion-hybrid promoters were developed and evaluated, which led to the development of a unique dual-expressing promoter, MSD3, with high gene expression efficiency (GUS and GFP reporter genes) in rice, pearl millet, and tobacco plants. We conclude that the MSD3 promoter can be an important genetic tool and will be valuable in plant biology research and application.

Abstract In oxygen (O2)‐controlled cell culture, an indispensable tool in biological research, it is presumed that the incubator setpoint equals the O2 tension experienced by cells (i.e., pericellular O2). However, it is discovered that physioxic (5% O2) and hypoxic (1% O2) setpoints regularly induce anoxic (0% O2) pericellular tensions in both adherent and suspension cell cultures. Electron transport chain inhibition ablates this effect, indicating that cellular O2 consumption is the driving factor. RNA‐seq analysis revealed that primary human hepatocytes cultured in physioxia experience ischemia‐reperfusion injury due to cellular O2 consumption. A reaction‐diffusion model is developed to predict pericellular O2 tension a priori, demonstrating that the effect of cellular O2 consumption has the greatest impact in smaller volume culture vessels. By controlling pericellular O2 tension in cell culture, it is found that hypoxia vs. anoxia induce distinct breast cancer transcriptomic and translational responses, including modulation of the hypoxia‐inducible factor (HIF) pathway and metabolic reprogramming. Collectively, these findings indicate that breast cancer cells respond non‐monotonically to low O2, suggesting that anoxic cell culture is not suitable for modeling hypoxia. Furthermore, it is shown that controlling atmospheric O2 tension in cell culture incubators is insufficient to regulate O2 in cell culture, thus introducing the concept of pericellular O2‐controlled cell culture.

In the current scenario, where demand for food production is constantly increasing with the rise in population, the threat of plant pathogens has also increased. The destruction of crops due to diseases caused by plant pathogens has become difficult to control with conventional physical and chemical methods. Traditional agriculture often depends on use of chemical pesticides, which have had negative impacts on both living organisms and ecosystems. As a fundamental principle of sustainable agriculture, it is important to limit the use of chemical pesticides in order to safeguard the environment and preserve diverse species. Additionally, sustainable agriculture should operate as a low input system, characterised by reduced production costs and increased net returns. Here, nanotechnology stands as a new weapon against rising challenges in agriculture. Nanotechnology may greatly improve the effectiveness of agricultural inputs, making it a valuable tool for promoting sustainable growth in agroecosystems via the use of nanoparticles. Using magnetic nanoparticles for controlling plant pathogenic fungi can be developed as a potent method for disease management in plants. In the present study, the effect of plant (Carica papaya) -based Fe3O4 magnetic nanoparticles was synthesized and studied against Fusarium oxysporum f.sp. ciceris, a chickpea pathogen. The antifungal effect of these nanoparticles and their minimum inhibitory concentration were studied using a soft agar assay and broth assay. Plant-synthesized nanoparticles were able to inhibit Fusarium oxysporum f.sp. ciceris by up to 87 %. It’s in vivo effect was checked with pot trials on chickpeas. Fe3O4 magnetic nanoparticles have shown adequate inhibition of fungus both in vitro and in vivo.

Abstract Recently, microbial cellulose-based coatings and films have attracted substantial attention because of their promising uses in numerous fields, such as food packaging. The present work was designed to synthesize active microbial cellulose-based coatings and films with a comprehensive investigation of their antimicrobial and structural properties. Microbial cellulose was synthesized by using a gram-negative bacterium called Acetobacter aceti. The produced microbial cellulose was mixed with sodium alginate, chitosan and starch to obtain two different composite solutions, i.e., microbial cellulose + starch + chitosan (MSC) and microbial cellulose + starch + sodium alginate (MSS). The antimicrobial properties were achieved by incorporating four different concentrations of clove extract into the composite solutions. The resulting composite solutions were tested against S. aureus, Shigella, Salmonella, and E. coli through the agar diffusion assay method. The clove extract was found to be effective in inhibiting the growth of these pathogens, as a clear zone of inhibition was observed at all clove extract concentrations, with a maximum zone of inhibition of 4.0 ± 0.05 cm on E. coli for the MSC solution incorporated with 4% clove extract. The best antimicrobial solutions found were then casted into films by pouring the solutions into petri dishes and drying at 50 °C in a tray drier. The antimicrobial activity was again evaluated for the films. The results indicated that MSC 3% showed a greater zone of inhibition against all pathogens (1.7 ± 0.18 cm). Furthermore, structural and thermal analyses of the formed films were conducted. The results indicated distinctive antimicrobial and structural characteristics of the films. Graphical Abstract

To quantify the aqueous and methanolic extracts for primary and secondary metabolites, and the antioxidant potential of leaf extracts of the Thunbergia erecta plant and to adopt them in Ayurvedic medications for various illnesses. Primary metabolites like carbohydrates, proteins, and secondary metabolites such as flavonoids, alkaloids, total phenols, and tannins were estimated using standard procedures. The 2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing antioxidant power (FRAP), hydrogen peroxide, and phosphomolybdenum free radical scavenging activities were employed to evaluate the antioxidative potential. The phytochemical examination of T. erecta exhibited the presence of carbohydrates, proteins, amino acids, alkaloids, total polyphenolics, flavonoids, and tannins in significant quantity. The in vitro antioxidant potential of the species, clearly verifies that methanolic extract shows prominent antioxidant properties followed by the hydroalcoholic extract. From this study, it can be concluded that this species is effective in scavenging free radicals and may be a powerful antioxidant. The T. erecta leaf extract showed the existence of bioactive components which are known to exhibit medicinal activities. The findings of this study suggest that these plant leaves could be a potential source of natural antioxidants that could have great importance as therapeutic agents in preventing various diseases.

Background: Cesarean section rate is rising globally, now accounting for more than 1 in 5 (21%) of all childbirths. This number is set to continue increasing over the coming decade unless the factors which increase the rate of cesarean section are kept in check. Intrapartum cardiotocography (CTG) has shown a false-positive rate of cesarean section. This has been correlated with neonatal umbilical cord blood pH analysis. Aims and Objectives: (1) Correlation of non-reassuring CTG, resulting in cesarean section with umbilical cord arterial blood pH. (2) To find the false-positive indications of cesarean section due to CTG. Materials and Methods: This observational study was conducted in the Department of Obstetrics and Gynecology of SKIMS, Soura, from September 2020 to July 2022 over a period of 22 months. Women with a gestational age of more than 34 weeks with singleton pregnancy were included in the study. Those with CTG-documented fetal distress were subjected to umbilical cord arterial blood pH monitoring. Results: A total of 85 patients underwent cesarean sections in view of fetal distress documented by CTG, but only 45 neonates had actual distress as documented by umbilical cord blood sampling. Conclusion: Social and non-medical factors no doubt have caused an alarming rise in cesarean sections, but at the same time, there are some iatrogenic causes, namely CTG, which lead to the rise in the cesarean section rate due to false-positive indications. This has been further supported by the fact that the pH of the umbilical cord blood of neonates with intrapartum non-reassuring CTG does not correspond to fetal acidemia in all cases. Hence, a significant number of cesarean sections is being done for false-positive indications.

Abstract Early life stress (ELS) significantly increases susceptibility to alcohol use disorder (AUD) by affecting the interplay between the executive and the salience networks (SNs). The link between AUD and higher body-mass index (BMI) is known, but we lack understanding of how BMI impacts the relationship between ELS and brain connectivity in individuals with AUD. To bridge this gap, we investigated the main and interaction effects of ELS and BMI on brain connectivity in individuals with AUD compared to non-AUD participants (n = 77 sex-matched individuals per group). All participants underwent resting-state functional magnetic resonance imaging, revealing intriguing positive functional connectivity between SN seeds and brain regions involved in somatosensory processing, motor coordination and executive control. Examining the relationship of brain connectivity with ELS and BMI, we observed positive associations with the correlations of SN seeds, right anterior insula (RAIns) and supramarginal gyrus (SMG) with clusters in motor [occipital cortex, supplementary motor cortex]; anterior cingulate cortex (ACC) with clusters in frontal, or executive, control regions (middle frontal gyrus; MFG, precentral gyrus) that reportedly are involved in processing of emotionally salient stimuli (all |β | > 0.001, |p |

Onychomycosis (OM) is a difficult-to-treat condition, especially considering the limited armamentarium of antifungal drugs, need for prolonged treatment, and poor compliance. This problem is further confounded while treating OM in special populations such as children, elderly, immunosuppressed patients, pregnant or lactating women, and patients with chronic liver or kidney disease. In the absence of standardized treatment guidelines, the antifungal therapy is either withheld or compromised, as it is largely governed by personal preferences or based on anecdotal reports. Hence, an expert group of the Nail Society of India worked towards drafting guidelines based on established literature and inputs from experts, with practical recommendations for the treatment of onychomycosis in special population groups. An extensive analysis of available English language literature on onychomycosis in special populations, published during a 10-year period (2014–2023 until date) was done. The available studies and reports were evaluated, cross-references read, and evidence compiled, graded, and discussed by the expert group to derive consensus recommendations for practice. The evidence and recommendations based on it are presented in a narrative format to guide treatment choices when dealing with population groups with special considerations.

Artificial intelligence (AI) is fundamentally transforming the marketing landscape, enabling significant progress in customer engagement, personalization, and operational efficiency. The retail sector has been at the forefront of the AI revolution, adopting AI technologies extensively to transform consumer interactions, supply chain management, and business performance. Given its early adoption of AI, the retail industry serves as an essential case context for investigating the broader implications of AI for consumer behavior. Drawing on 404 articles published between 2000 and 2023, this study presents a comprehensive bibliometric and content analysis of AI applications in retail marketing. The analysis used VOSviewer (1.6.20.0 version) and Bibliometrix (version 4.3.1) to identify important contributors, top institutions, and key publication sources. Co-occurrence keyword and co-citation analyses were used to map intellectual networks and highlight emerging themes. Additionally, a focused content analysis of 50 recent articles was selected based on their relevance, timeliness, and citation influence. It revealed six primary research streams: (1) consumer behavior, (2) AI in retail marketing, (3) business performance, (4) sustainability, (5) supply chain management, and (6) trust. These streams were categorized through thematic relevance and theoretical significance, emphasizing AI’s impact on the retail sector. The contributions of this study are twofold. Theoretically, it integrates existing research on AI in retail marketing and outlines future research in areas such as AI’s role in the domain of consumer behavior. From an empirical standpoint, the study highlights how AI can be applied to enhance customer experiences and improve business operations.

Abstract While CT lung cancer screening reduces lung cancer-specific mortality, there are remaining challenges. Radiomic tools promiss to address these challenges, however, they are subject to interobserver variability if semi-automated segmentation techniques are used. Herein we report interobserver variability for two validated radiomic tools, BRODERS (Benign versus aggRessive nODule Evaluation using Radiomic Stratification) and CANARY (Computer-Aided Nodule Assessment and Risk Yield). We retrospectively analyzed the CT images of 95 malignant lung nodules of the adenocarcinoma spectrum using BRODERS and CANARY. Cases were identified at Mayo Clinic (n = 45) and Vanderbilt University Medical Center and Nashville/Veteran Administration Tennessee Valley Health Care System (n = 50). Three observers with different training levels (medical student, internal medicine resident and thoracic radiology fellow) each performed lung nodule segmentation. All methods were carried out in accordance with relevant guidelines and regulations. Interclass correlation coefficients (ICC) of 0.77, 0.98 and 0.97 for the average nodule volume, BRODERS cancer probability and Score Indicative of Lesion Aggression (SILA) which summarizes the distribution of the CANARY exemplars indicated good to excellent reliability, respectively. The dice similarity coefficient was 0.79 and 0.81 for the data sets from the two institutions. BRODERS and CANARY are robust radiomics tools with excellent interobserver variability. These tools are simple and reliable regardless the observer/operator’s level of training.

Hypoxia is a major factor shaping the immune landscape, and several cancer models have been developed to emulate hypoxic tumors. However, to date, they still have several limitations, such as the lack of reproducibility, inadequate biophysical cues, limited immune cell infiltration, and poor oxygen (O2) control, leading to non-pathophysiological tumor responses. Therefore, it is essential to develop better cancer models that mimic key features of the tumor extracellular matrix and recreate tumor-associated hypoxia while allowing cell infiltration and cancer-immune cell interactions. Herein, hypoxia-inducing cryogels (HICs) have been engineered using hyaluronic acid (HA) to fabricate three-dimensional microtissues and model a hypoxic tumor microenvironment. Specifically, tumor cell-laden HICs have been designed to deplete O2 locally and induce long-standing hypoxia. HICs promoted changes in hypoxia-responsive gene expression and phenotype, a metabolic adaptation to anaerobic glycolysis, and chemotherapy resistance. Additionally, HIC-supported tumor models induced dendritic cell (DC) inhibition, revealing a phenotypic change in the plasmacytoid DC (pDC) subset and an impaired conventional DC (cDC) response in hypoxia. Lastly, our HIC-based melanoma model induced CD8+ T cell inhibition, a condition associated with the downregulation of pro-inflammatory cytokine secretion, increased expression of immunomodulatory factors, and decreased degranulation and cytotoxic capacity of T cells. Overall, these data suggest that HICs can be used as a tool to model solid-like tumor microenvironments and has great potential to deepen our understanding of cancer-immune cell relationship in low O2 conditions and may pave the way for developing more effective therapies.

In the last few decades, academic research has focused more on financial problems and poverty levels. These are among the two major challenges of the modern world today. To understand the challenge of financial crisis and poverty in societies. This paper explains a deterministic financial system of non linear differential equations. Which aim to provide recommendations to address the twin challenges. In this fractional chaotic model, memory and chaos are portrayed as effects on a system. Financial systems of fractional order have three compartments: interest rate x(t), investment demand rate y(t) and price indexes rate z(t). For the first time, the Legendre wavelet approximation is applied to fractional order financial systems. A major objective of this process is to convert fractional differential equations (FDEs) into algebraic equations by using Legendre wavelets and their fractional integral operators. For residual analysis, convergence and stability analysis, we have used iteration methods and Legendre wavelets. This study indicates good results between the approximate and numerical solutions and that this method is efficient and accurate. Using the iteration method, we prove that the solution exists, while the contraction theory proves its uniqueness. The findings of this study will be extremely useful for future financial management. We have demonstrated the applicability and effectiveness of these methods by analysing numerical simulations for the fractional order financial model and the numerical simulation has been calculated by MATLAB programming.

Immune exhaustion is a state of immune cell dysfunction that occurs most commonly following chronic exposure to an antigen which persists after the immune response fails to remove it. Exhaustion has been studied most thoroughly with several cancers, but has also been observed in several chronic infectious diseases. The topic has mainly been studied with CD8+ T cells, but it can also occur with CD4+ T cells and other immune cell types too. Exhaustion is characterized by a hierarchical loss of effector cell functions, up-regulation of immuno-inhibitory receptors, disruption of metabolic activities, and altered chromatin landscapes. Exhaustion has received minimal attention so far in diseases of veterinary significance and this review's purpose is to describe examples where immune exhaustion is occurring in several bovine disease situations. We also describe methodology to evaluate immune exhaustion as well as the prospects of controlling exhaustion and achieving a more suitable outcome of therapy in some chronic disease scenarios.

Abstract INTRODUCTION We described patients’ and care partners’ experiences with Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarker testing and result disclosure in routine care. METHODS IMPACT‐AD BC is an observational study of clinic patients who underwent AD CSF biomarker testing as part of their routine medical care (n = 142). In the personal utility arm of the study, semi‐structured phone interviews were conducted with a subset of patients (n = 34), and separately with their care partners (n = 31). Post‐disclosure interviews were conducted ∼1 month and ∼6 months after biomarker result disclosure and investigated the patients’ decision‐making process around testing, impact of receiving results, wellness and lifestyle changes, and future planning. RESULTS A majority of patients (90%) rated their decision to undergo testing as “easy.” Post‐disclosure, the majority (82%) reported overall positive feelings from having greater certainty and the ability to plan ahead, and results spurred them to adopt/continue healthy behaviors such as exercise (84%) and cognitive activities (54%). Care partners expressed relief from having more diagnostic certainty, increased appreciation of future caregiving responsibilities, and a desire to connect with support resources. DISCUSSION Perspectives of persons with lived experience in dementia provide new insight into the value of biomarker testing and should be included as part of evidence‐guided considerations for pre‐test counseling and result disclosure. Moreover, study findings identify an interval when patients and care partners are highly receptive to positive lifestyle and medical interventions.

Abstract INTRODUCTION In the Investigating the Impact of Alzheimer's Disease Diagnostics in British Columbia (IMPACT‐AD BC) study, we aimed to understand how Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarker testing—used in medical care—impacted medical decision‐making (medical utility), personal decision‐making (personal utility), and health system economics. METHODS The study was designed as an observational, longitudinal cohort study. A total of 149 patients were enrolled between February 2019 and July 2021. Patients referred to memory clinics were approached to participate if their dementia specialist ordered AD CSF biomarker testing as part of their routine medical care, and the clinical scenario met the appropriate use criteria for lumbar puncture and AD CSF biomarker testing. For the medical utility pillar, detailed clinical management plans were collected via physician questionnaires pre‐ and post‐biomarker disclosure. RESULTS Patients with completed management questionnaires (n = 142) had a median age of 64 (interquartile range: 59–69) years, 48% were female, and 60% had CSF biomarker profiles on the AD continuum. Clinical management changed in 89.4% of cases. AD biomarker testing was associated with decreased need for other diagnostic procedures, including brain imaging (–52.0%) and detailed neuropsychological assessments (–63.2%), increased referrals and counseling (57.0%), and guided AD‐related drug prescriptions (+88.4% and –50.0% in biomarker‐positive and ‐negative cases, respectively). DISCUSSION AD biomarker testing was associated with significant and positive changes in clinical management, including decreased health care resource use, therapy optimization, and increased patient and family member counseling. While certain changes in management were linked to the AD biomarker profile (e.g., referral to clinical trials), the majority of changes were independent of baseline clinical presentation and level of cognitive impairment, demonstrating a broad value for AD biomarker testing in individuals meeting the appropriate use criteria for testing.

Congenital insensitivity to pain with anhidrosis (CIPA) is a rare autosomal disorder. It is characterized by systemic insensitivity to pain, unexplained fever, and psychiatric manifestations. Anesthetic management of these cases is a challenge to the anesthetist due to the various implications associated with it. In this case report, we describe the anesthetic management of a 3-year-old child with CIPA and report the implications and challenges faced.

Abstract Background A quality by design approach can potentially lead to a more robust/rugged method development due to emphasis on the risk assessment and management. By carefully understanding the step-by-step procedure for analytical QbD-based optimization parameters, such as analytical target profile and critical quality attributes (CQAs), was assessed. The present study describes the simple, rapid, sensitive and cost-effective RP-HPLC method development and validation for the estimation of evogliptin tartrate in pharmaceutical dosage form. Results The factor screening studies were performed using Box–Behnken design by three key components of the RP-HPLC method (mobile phase, pH and flow rate). The chromatographic conditions were optimized with the Design Expert software trial version 13.0. The optimal chromatographic separation was achieved having water C18 column (250 mm × 4.6 mm, 5 μ) and using mobile phase as a methanol and phosphate buffer (pH 4.5) 60:40% v/v with a flow rate 1.0 ml/min and UV detection at 267 nm. The Box–Behnken experimental design describes the interrelationship of mobile phase, pH and flow rate at three different levels, and responses of retention time and tailing factor were observed with response surface plot and statistical data. The developed method was validated as per recommended ICH guidelines which revealed the high degree of linear, precise, accurate, sensitive and robust method over the existing RP-HPLC method for evogliptin tartrate. Conclusion The developed QbD-based method helped in generating a design space and operating space with knowledge of all method performance characteristics, and RP-HPLC method takes less time and can be used in the industry for routine quality control of bulk and marketed formulation of evogliptin tartrate.

Abstract Background The growing power and ever decreasing cost of RNA sequencing (RNA-Seq) technologies have resulted in an explosion of RNA-Seq data production. Comparing gene expression values within RNA-Seq datasets is relatively easy for many interdisciplinary biomedical researchers; however, user-friendly software applications increase the ability of biologists to efficiently explore available datasets. Results Here, we describe ROGUE (RNA-Seq Ontology Graphic User Environment, https://marisshiny.research.chop.edu/ROGUE/ ), a user-friendly R Shiny application that allows a biologist to perform differentially expressed gene analysis, gene ontology and pathway enrichment analysis, potential biomarker identification, and advanced statistical analyses. We use ROGUE to identify potential biomarkers and show unique enriched pathways between various immune cells. Conclusions User-friendly tools for the analysis of next generation sequencing data, such as ROGUE, will allow biologists to efficiently explore their datasets, discover expression patterns, and advance their research by allowing them to develop and test hypotheses.

Metal nanoparticles have been tested for therapeutic and imaging applications in pre-clinical models of cancer, but fears of toxicity have limited their translation. An emerging concept in nanomedicine is to exploit the inherent drug-like properties of unmodified nanomaterials for cancer therapy. To be useful clinically, there must be a window between the toxicity of the nanomaterial to cancer and toxicity to normal cells. This necessitates identification of specific vulnerabilities in cancers that can be targeted using nanomaterials without inducing off-target toxicity. Previous studies point to proteotoxic stress as a driver of silver nanoparticle (AgNPs) toxicity. Two key cell stress responses involved in mitigating proteotoxicity are the heat shock response (HSR) and the integrated stress response (ISR). Here, we examine the role that these stress responses play in AgNP-induced cytotoxicity in triple-negative breast cancer (TNBC) and immortalized mammary epithelial cells. Furthermore, we investigate HSR and ISR inhibitors as potential drug partners to increase the anti-cancer efficacy of AgNPs without increasing off-target toxicity. We showed that AgNPs did not strongly induce the HSR at a transcriptional level, but instead decreased expression of heat shock proteins (HSPs) at the protein level, possibly due to degradation in AgNP-treated TNBC cells. We further showed that the HSR inhibitor, KRIBB11, synergized with AgNPs in TNBC cells, but also increased off-target toxicity in immortalized mammary epithelial cells. In contrast, we found that salubrinal, a drug that can sustain pro-death ISR signaling, enhanced AgNP-induced cell death in TNBC cells without increasing toxicity in immortalized mammary epithelial cells. Subsequent co-culture studies demonstrated that AgNPs in combination with salubrinal selectively eliminated TNBCs without affecting immortalized mammary epithelial cells grown in the same well. Our findings provide additional support for proteotoxic stress as a mechanism by which AgNPs selectively kill TNBCs and will help guide future efforts to identify drug partners that would be beneficial for use with AgNPs for cancer therapy.

The increase in global population has had a tremendous impact on sustainable agri-food practices. With the growth in world population, various modern technologies are being utilized that more often result in the opening of tremendous opportunities in the agriculture and food sectors. Nanotechnology is used in agri-food sectors for a variety of purposes, including enhancing flavor, pest/pathogen diagnosis, production, processing, storage, packaging, and transportation of agricultural products. Plant pathogenic microorganisms including bacteria, viruses, fungi, and nematodes have a significant impact on the global economy. In particular, advances in nanotechnology, including nanobiosensors, have been used in the detection of plant diseases and pathogens, the evaluation and examination of infections caused by microorganisms, the management of diseases and, thus, the promotion of food security. Apart from the management of plant diseases, nanobiosensors offer better opportunities for sustainable agri-food production by controlling physical, chemical, and biological processes, thus improving food safety and the agricultural economy. This review outlines the application of nano-integrated nanobiosensors for better agricultural and food practices.