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Purpose: To evaluate the anatomic and visual outcomes and safety profile of initial Indian eyes with neovascular age-related macular degeneration (nAMD) treated with intravitreal injection (IVI) of brolucizumab. Methods: This retrospective multicentric, real-world study enrolled consecutive eyes with nAMD that were treated with IVI brolucizumab after it was launched in India in October 2020. Data collected for each eye included best-corrected visual acuity (BCVA), central subfield thickness (CSFT), subretinal fluid (SRF), and intraretinal fluid (IRF) status at 6, 12, and 24 months follow-up. Also recorded were the lens status, treatment protocol, number of injections received before enrollment (in switch-over cases), total number of injections, and adverse effects noticed during the study period. Primary outcomes were change in BCVA, CSFT at follow-up visits, and incidence of intraocular inflammation (IOI). Secondary outcomes were profile of macular neovascularization, treatment protocols, mean number of injections, and maximum injection-free interval observed in eyes treated by pro-re-nata (PRN) protocol. Results: In total, 331 eyes received a mean of 3.55 ± 1.83 injections. Most frequent treatment protocol was PRN (53%). BCVA data was available for 100%, 96%, and 74% eyes at 6, 12, and 24 months follow-up. BCVA and CSFT improved significantly (P < 0.001) at all follow-ups. Two hundred and seventy-six (83.38%) out of 331 eyes received more than one injection; out of these, 241 (87.3%) eyes that were treated by PRN protocol could achieve mean “maximum injection-free interval” of 19.43 ± 8.82 weeks. IOI and retinal vasculitis were reported in 2.11% (7/331) and 0.60% (2/331) eyes, respectively. None of the eyes with IOI or vasculitis lost any vision at the final follow-up. Conclusion: This study demonstrated favorable visual and anatomic outcomes and safety profile for eyes with nAMD treated by IVI brolucizumab. Mean maximum injection-free interval in eyes treated with PRN was 19 weeks.

Frailty is an age-associated state of increased vulnerability due to declines in physiologic systems, leading to compromised ability to withstand stressors. Given India’s rapidly aging population, our study aims to estimate the pooled prevalence of frailty and its associated factors in hospital settings. An extensive search was conducted across four databases, up to January 2024. A random-effects model was utilized. To quantify heterogeneity, the I² statistic, prediction interval, and the Chi-square-based Q test were employed. Outliers were identified using a Baujat plot and influence analysis. Doi plot, luis furuya kanamori (LFK) index and funnel plot were used to assess publication bias. The current meta-analysis determined a pooled frailty prevalence of 42.3% (95%CI: 34.8%−50.1%) and prefrailty prevalence of 39.8% (95%CI: 30.4%−49.8%), both exhibiting high heterogeneity (I² values of 96.9% and 95.3%, respectively). A high degree of variability was indicated by a prediction interval ranging from 9% to 76%, while Egger’s test suggested no evidence of publication bias. Our systematic review and meta-analysis, encompassing 6,856 individuals, revealed a considerable prevalence of frailty at 42.3%, underscoring its ubiquity across health spectra and demographics in India.

In developing countries, coastal urban slums are acknowledged as highly susceptible areas to the consequences of climate extremes. With a limited capacity to absorb and prevent rising waters, coastal slums experience recurring floods. This challenge has led slum dwellers to develop local adaptation measures over the years. The public space embedded within the slum morphology provide for spatial interplay between the floods and measures of adaptation. Formerly perceived as a threat, the excess of water is evolving into an opportunity. In these contexts, streets provide for essential physical space in the slum fabric, also useful to address the effects of floods. The form of the street allows temporary cyclical occupations that relate to the activities of the slum dwellers, the daily or seasonal rhythms, in which water level plays a lead role. Thus, the character of the street is both defined by the fixed section and the cyclical adaptive measures and elements that compose the liveable space. Dharavi, in Mumbai, consists of a highly diverse informal settlement comprising streets that support the livelihoods of different communities, such as fishers in Koliwada, potters in Kumbharwada, and laundry workers in Dhobi Ghat, among others. In this paper, the diversity of street form and cycles is decoded and translated by interpretative drawings based on cartographic and collected images. This study seeks to showcase the crucial role of slum streets, as urban morphological elements, in addressing cyclical floods. It contributes to the wider research into the typification of flood adaptation measures and the systematisation of a lexicon of flood adaptation measures for coastal urban slums.

Abstract As energy demands continue to rise and concerns about the impact on the environment of fossil fuels, renewable energy sources have emerged as viable alternatives. Bio-fuels can replace non-renewable energy sources. Micro and macro-algae, animal fat, leftover cooking oil and vegetable oil can be utilised to make bio-diesel. Micro-algae is readily available and affordable, making it a viable alternative to these sources. A bio-diesel supply chain that supports large-scale production must be developed quickly. A multi-objective framework is used to construct a sustainable micro-algal bio-diesel supply chain. Bio-diesel supply chain economic objective and environmental impact is minimized in the proposed approach. Bio-diesel is advertised as a fossil fuel replacement. Bio-refineries, bio-diesel depositories, multi-harvesting centres and supply sites for micro-algae (Chlorella, chlamydomonas and Scenedesmus) are considered. The suggested multi-objective model is optimized by implementing the $$Genetic-Algorithm$$ G e n e t i c - A l g o r i t h m . The framework and solution technique are validated using numerical illustrations. Findings indicate that bio-diesel production facility starting expenses comprise 59% of overall costs, showing high installation costs in the supply chain. Additionally, their environmental impact accounts for 67% of total environmental installation impact. A sensitivity analysis is performed to determine the feasibility of this study. The suggested paradigm could potentially be beneficial for traders and governing bodies with an interest in bio-fuel industry.

Abstract We develop an automated high-throughput workflow for calculating lattice dynamical properties from first principles including those dictated by anharmonicity. The pipeline automatically computes interatomic force constants (IFCs) up to 4th order from perturbed training supercells, and uses the IFCs to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free energy and entropy. It performs phonon renormalization for dynamically unstable compounds to obtain real effective phonon spectra at finite temperatures and calculates the associated free energy corrections. The methods and parameters are chosen to balance computational efficiency and result accuracy, assessed through convergence testing and comparisons with experimental measurements. Deployment of this workflow at a large scale would facilitate materials discovery efforts toward functionalities including thermoelectrics, contact materials, ferroelectrics, aerospace components, as well as general phase diagram construction.

Abstract Whole genome sequencing (WGS) has become a gold standard for diagnosing genomic variation. Peripheral blood is a common sample source for the extraction of nucleic acids for Next-Generation Sequencing (NGS) applications. Here, we present an integrated and fully automated device design that uses new concepts of fluid mechanics, heat-mass transfer, and thermodynamics of enzymatic reactions to extract nucleic acids from the blood and perform DNA library preparation from a pre-filled plate. We demonstrate that the presented device effectively extracts dsDNA with an average of 25.03 µg/mL and 25.91 µg/mL yield from citrate-stabilized human peripheral blood stored in Fresh (4 °C) and Frozen (-20 °C) conditions, respectively. Furthermore, our method automatically extracts nucleic acids and creates a high-quality sequence-ready DNA library from blood stabilized with citrate and EDTA for 8 samples simultaneously in a single run with a total operation time of ~ 7 h. Our results show the required coverage and depth of the genome, highlighting an essential application of this device in processing blood samples for genome sequencing. Graphical Abstract

Background and Aim: Management of pain and anxiety associated with dental procedures in pediatric age group is a big challenge. In this part of the world, counselling has been the main modality for managing such patients. It is associated with mixed outcome. We share our experience of managing 23 patients using a combination of inhalational nitrous oxide- oxygen and intravenous midazolam with satisfactory outcomes. Material and Methods: Patients aged more than six years, American society of anaesthesiologists classification (ASA) I or II, procedure that could be finished within one hour like pulpectomies, root canal treatments, extraction and multiple restorations were accepted for conscious sedation. Complete blood count was done and pre-anaesthetic checkup (PAC) with written informed consent from the parent was taken for the dental procedure under conscious sedation. We placed the nasal mask of the Conscious sedation anesthesia machine and made the child inhale Oxygen/Nitrous oxide mixture. After inhaling variable concentration of nitrous oxide/ oxygen mixture in proportion increasing from 30:70 to 70:30, procedure was done. After completion of the procedure, the patient was administered hundred percent oxygen for five minutes. Results: We have done a total of twenty-three cases till now with ages between five to seventeen years. The duration of procedures ranged from 30 min to one and half hour. Two patients less than six years were found to be uncooperative for the procedure. Conclusion: Minimum age group that was suitable for conscious sedation was six years and above. Frequent meetings and counselling by the same team should be facilitated prior to taking up for the procedure.

Abstract The present study aimed to identify nutrients (UPLC-PDA-ESI-MS/MS, HPLC-RI method) and biological activities (antioxidant activity to reduce Fe3+ and ABTS·+, pancreatic lipase inhibitory effect, α-amylase, and α-glucosidase, anti-bacterial) of 14 highbush blueberries (Vaccinium corymbosum L.) cultivars (Northern type) as well as a principal component analysis (PCA) to assess the variation of these properties in the context of biodiversity. Most of the cultivars in this research have been first presented in this paper. Phytochemical profiling of the tested highbush blueberry fruit revealed 75 bioactive compounds, including 5 macroelements, 7 microelements, 7 monophosphate nucleotides, 15 anthocyanins, 1 phenolic acid, 14 flavonols, 11 essential amino acids, 8 non-essential amino acids, 2 sugars, 7 organic acids. The PCA showed that the profile and contents of the analyzed compounds as well as their anti-bacterial, antioxidant, anti-diabetic, and anti-obesity potentials depended significantly on the tested cultivars. Thus, the study provides comprehensive data on cultivar-specific biodiversity and correlations that can be used to design novel extracts rich in polyphenolic, amino acids, and/or minerals extracts from the selected cultivars of highbush blueberry as natural and alternative sources to fulfill the growing industry demand for supplements, pharmaceuticals, and nutraceutical products.

Abstract We explore the cosmic birefringence signal produced by an ultralight axion field with a small CP-violating coupling to bulk SM matter in addition to the usual CP-preserving photon coupling. The change in the vacuum expectation value of the field between recombination and today results in a frequency-independent rotation of the plane of CMB linear polarization across the entire sky. While many previous approaches rely on the axion rolling from a large initial expectation value, the couplings considered in this work robustly generate the birefringence signal regardless of initial conditions, by sourcing the field from the cosmological nucleon density. We place bounds on such monopole-dipole interactions using measurements of the birefringence angle from Planck and WMAP data, which improve upon existing constraints by up to three orders of magnitude. We also discuss UV completions of this model, and possible strategies to avoid fine-tuning the axion mass.

Hematologic cancers, notably leukemias and lymphomas, pose significant challenges to healthcare systems globally, due to rising incidence rates and increasing costs. This study aimed to estimate the phase and lifetime health system total costs (not net costs) of care for patients diagnosed with leukemia and lymphoma in Ontario, Canada. We conducted a population-based study of patients diagnosed between 2005 and 2019, using data from the Ontario Cancer Registry linked with health administrative databases. Costs were estimated using a phase-based approach and stratified by care phase and cancer subtype. Acute lymphocytic leukemia (ALL) patients had the highest mean monthly initial (CAD 19,519) and terminal (CAD 41,901) costs among all cancer subtypes, while acute myeloid leukemia (AML) patients had the highest mean monthly cost (CAD 7185) during the continuing phase. Overall lifetime costs were highest for ALL patients (CAD 778,795), followed by AML patients (CAD 478,516). Comparatively, patients diagnosed with Hodgkin lymphoma (CAD 268,184) and non-Hodgkin lymphoma (CAD 321,834) had lower lifetime costs. Major cost drivers included inpatient care, emergency department visits, same-day surgeries, ambulatory services, and specialized cancer drugs. Since 2005, the cost structure has evolved with rising proportions of interventional drug costs. Additionally, costs were higher among males and younger age groups. Understanding these costs can help guide initiatives to control healthcare spending and improve cancer care quality.

Breast cancer is a heterogeneous disease, with a subpopulation of tumor cells known as breast cancer stem cells (BCSCs) with self-renewal and differentiation abilities that play a critical role in tumor initiation, progression, and therapy resistance. The tumor microenvironment (TME) is a complex area where diverse cancer cells reside creating a highly interactive environment with secreted factors, and the extracellular matrix. Autophagy, a cellular self-digestion process, influences dynamic cellular processes in the tumor TME integrating diverse signals that regulate tumor development and heterogeneity. Autophagy acts as a double-edged sword in the breast TME, with both tumor-promoting and tumor-suppressing roles. Autophagy promotes breast tumorigenesis by regulating tumor cell survival, migration and invasion, metabolic reprogramming, and epithelial-mesenchymal transition (EMT). BCSCs harness autophagy to maintain stemness properties, evade immune surveillance, and resist therapeutic interventions. Conversely, excessive, or dysregulated autophagy may lead to BCSC differentiation or cell death, offering a potential avenue for therapeutic exploration. The molecular mechanisms that regulate autophagy in BCSCs including the mammalian target of rapamycin (mTOR), AMPK, and Beclin-1 signaling pathways may be potential targets for pharmacological intervention in breast cancer. This review provides a comprehensive overview of the relationship between autophagy and BCSCs, highlighting recent advancements in our understanding of their interplay. We also discuss the current state of autophagy-targeting agents and their preclinical and clinical development in BCSCs.

High-pressure processing (HPP) has been employed in the food and pharmaceutical industries for multiple applications, such as microbial inactivation, shelf life extension, homogenizing/stabilizing emulsions, suspensions, gels, and other colloidal systems, cold extraction of meat in crustaceans, the opening of mollusks, etc. However, high pressure is known to affect the stability and the quality of barosensitive (i.e., sensitivity because of the level of pressure) components of the bioproducts, such as proteins. In general, Le Chatelier's principle dictates the fate of high molecular weight polymeric compounds like proteins under high pressure, suggesting a tendency to degrade into simpler monomers. From a structural analysis point of view, this generally results in increased tendencies for the protein to denature from its native state and possibly affect its ability to renature. Protein crystallization is also affected favorably or unfavorably by pressure, depending on the effect of pressure on nucleation and crystal growth steps for the particular type of protein. Protein refolding is another effect whose kinetics can be optimized by pressure. This work discusses the mechanisms of the impact of pressure on protein structure, crystallization refolding, and unfolding, with examples of the application of these processes in recent literature.

AbstractDrought severely affects maize growth and productivity, making the identification of tolerant genotypes essential, especially in local maize. Therefore, a greenhouse pot experiment was conducted in Sundarbazar, Lamjung, from February to April using 30 local maize accessions under irrigated and drought conditions in a completely randomized block design to study nine vegetative traits and screen drought tolerance for upcoming breeding programs. Accession NGRC05570 showed relative tolerance to root length and number, NGRC05586 to shoot length, NGRC05589 to root-to-shoot ratio, NGRC05591 to moisture content in roots, NGRC05578 to moisture in shoot and relative water content (RWC), NGRC05561 to root volume and NGRC05573 to normalized difference vegetation index (NDVI). Accession NGRC05571, although lacking singular dominance in traits, exhibited an overall tolerance for NDVI, root-to-shoot ratio, root number, root length and RWC. Corelation analysis between shoot moisture content and shoot length showed a significant negative correlation under drought (−0.38) but a significant positive correlation under irrigation (0.38). Similarly, a significant negative correlation between the root-to-shoot ratio and shoot moisture content was observed under drought (−0.62) but not under irrigation. The possibility of accession NGRC05571, collected from Surkhet, being used in upcoming breeding studies has been seen, but a study on its ability to tolerate reproductive drought would be more insightful.

As a disruptive technology, blockchain has become a strategic priority for many businesses. A vast amount of research exists on blockchain's innovative nature and immense potential for multiple industries. This study aims to synthesize the existing research to classify the findings into various themes and propose avenues for further research. A total of 2,360 academic articles were analyzed using the text-mining method of structural topic modeling. The identified fifteen topics were mapped to the four quadrants of the Datatopia model, leading to the development of the Datatopia-blockchain (DBlock) framework. The results present future scenarios that provide an understanding of what is known about blockchain, its characteristics, and potential research areas. The contributions to the theory and implications to the practitioners are discussed in detail.

Dengue virus infection can cause a wide spectrum of clinical manifestations, ranging from mild fever to lethal dengue shock syndrome. Neurological manifestations include encephalitis, acute disseminated encephalomyelitis, Transverse myelitis, Guillain-Barre syndrome, and neuro-ophthalmic complications. We report a case of a 44-year-old male who was admitted to our hospital with high-grade fever, myalgia, retro-orbital pain, visual disturbances, and drowsiness. Hematological and serological parameters confirmed the diagnosis of dengue fever. Brain imaging demonstrated altered signal intensity in the splenium of the corpus callosum and eventually a diagnosis of a cytotoxic lesion of the corpus callosum (CLOCC) was made. The patient was managed conservatively and discharged 7 days after admission and imaging findings were resolved completely 3 weeks later.

Background: Development of obscured fingerprints on a diverse range of surfaces is a crucial aspect of forensic investigations. Aims and Objectives: In this particular study, the utilization of Syzygium cumini (L.) Skeels (Jamun) seed powder was examined for the purpose of revealing hidden fingerprints on a variety of surfaces, including both permeable and impermeable substrates. Materials and Methods: The seed powder was extracted using a simple process and was analysed using multiple analytical techniques. The efficacy of the jamun seed powder in developing latent fingerprints was evaluated. Results: The findings of this investigation demonstrate that the jamun seed powder was capable of producing fingerprint patterns of exceptional quality and clarity on numerous surfaces. Conclusion: This research highlights the potential use of jamun seed powder as a practical and effective alternative for the development of hidden fingerprints in forensic investigations, while also providing cost-effectiveness.

Abstract The selection of drought-tolerant genotypes from the existing gene pool is a preliminary step for breeding for drought tolerance. Research efforts aimed at exploring the ability of crops to withstand drought stress have not yet touched the realm of reproductive drought performance of local genotypes. To examine how local crop accessions demonstrate varying reproductive performance under drought conditions, twenty accessions of maize (Zea mays L.) were evaluated for six quantitative traits in a two-factor factorial completely randomized design with two replications between February to June of 2023. All the traits under study showed significant differences among the genotypes (p

Abstract The level of phosphorus must be carefully monitored for proper and effective utilization of coal and coal ash. The phosphorus content needs to be assessed to optimize combustion efficiency and maintenance costs of power plants, ensure quality, and minimize the environmental impact of coal and coal ash. The detection of low levels of phosphorus in coal and coal ash is a significant challenge due to its complex chemical composition and low concentration levels. Effective monitoring requires accurate and sensitive equipment for the detection of phosphorus in coal and coal ash. X-ray fluorescence (XRF) is a commonly used analytical technique for the determination of phosphorus content in coal and coal ash samples but proves challenging due to their comparatively weak fluorescence intensity. Fourier Transform Infrared spectroscopy (FTIR) emerges as a promising alternative that is simple, rapid, and cost-effective. However, research in this area has been limited. Until now, only a limited number of research studies have outlined the estimation of major elements in coal, predominantly relying on FTIR spectroscopy. In this article, we explore the potential of FTIR spectroscopy combined with machine learning models (piecewise linear regression—PLR, partial least square regression—PLSR, random forest—RF, and support vector regression—SVR) for quantifying the phosphorus content in coal and coal ash. For model development, the methodology employs the mid-infrared absorption peak intensity levels of phosphorus-specific functional groups and anionic groups of phosphate minerals at various working concentration ranges of coal and coal ash. This paper proposes a multi-model estimation (using PLR, PLSR, and RF) approach based on FTIR spectral data to detect and rapidly estimate low levels of phosphorus in coal and its ash (R $$^2$$ 2 of 0.836, RMSE of 0.735 ppm, RMSE (%) of 34.801, MBE of − 0.077 ppm, MBE (%) of 5.499, and MAE of 0.528 ppm in coal samples and R $$^2$$ 2 of 0.803, RMSE of 0.676 ppm, RMSE (%) of 38.050, MBE of − 0.118 ppm, MBE (%) of 4.501, and MAE of 0.474 ppm in coal ash samples). Our findings suggest that FTIR combined with the multi-model approach combining PLR, PLSR, and RF regression models is a reliable tool for rapid and near-real-time measurement of phosphorus in coal and coal ash and can be suitably modified to model phosphorus content in other natural samples such as soil, shale, etc.

The last decade has witnessed significant progress towards zero-emission electric aviation. Lithium-ion batteries are at the centre of this technological transformation. However, electric flight requires suitable considerations for safety concerns associated with Lithium-ion batteries. Fault diagnostic approaches aimed at validating the safety of batteries before every flight have emerged as an attractive prospect. In this pursuit, a three-paper series proposing a novel fault diagnosis algorithm is presented. The algorithm is capable of diagnosing faults in an aircraft battery using the data collected during charging and was previously validated for a particular cell type under steady charging conditions. In this paper, two extensional aspects of the algorithm are investigated: cell-to-cell transferability and disparate charging conditions. While crucial for practical implementation, these aspects were overlooked in previous literature. Through experiments conducted at module-level, it was revealed that the algorithm could diagnose faults for a different cell type with minimal preliminary cell-level characterisation, thus demonstrating its ease of transferability. Moreover, modifications introduced in the algorithm enabled it to perform fault diagnosis under unsteady charging conditions for an aerospace module despite significant internal temperature gradients. Thus, the successful working of the algorithm in the considered aspects, which are unprecedented in literature, prove its feasibility for real-life application.

Abstract Next-generation sequencing (NGS) is emerging as a powerful tool for molecular diagnostics but remains limited by cumbersome and inefficient sample preparation. We present an innovative automated NGS library preparation system with a simplified mechanical design that exploits both macro- and microfluidic properties for optimizing heat transfer, reaction kinetics, mass transfer, fluid mechanics, adsorption–desorption rates, and molecular thermodynamics. Our approach introduces a unique two-cannula cylindrical capillary system connected to a programmable syringe pump and a Peltier heating element able to execute all steps with high efficiency. Automatic reagent movement, mixing, and magnetic bead-based washing with capillary-based thermal cycling (capillary-PCR) are completely integrated into a single platform. The manual 3-h library preparation process is reduced to less than 15 min of hands-on time via optimally pre-plated reagent plates, followed by less than 6 h of instrument run time during which no user interaction is required. We applied this method to two library preparation assays with different DNA fragmentation requirements (mechanical vs. enzymatic fragmentation), sufficiently limiting consumable use to one cartridge and one 384 well-plate per run. Our platform successfully prepared eight libraries in parallel, generating sequencing data for both human and Escherichia coli DNA libraries with negligible coverage bias compared to positive controls. All sequencing data from our libraries attained Phred (Q) scores > 30, mapping to reference genomes at 99% confidence. The method achieved final library concentrations and size distributions comparable with the conventional manual approach, demonstrating compatibility with downstream sequencing and subsequent data analysis. Our engineering design offers repeatability and consistency in the quality of sequence-able libraries, asserting the importance of mechanical design considerations that employ and optimize fundamental fluid mechanics and heat transfer properties. Furthermore in this work, we provide unique insights into the mechanisms of sample loss within NGS library preparation assays compared with automated adaptations and pinpoint areas in which the principles of thermodynamics, fluid mechanics, and heat transfer can improve future mechanical design iterations.

Background: Epidermoid cysts (ECs) are rare, benign lesions which comprise less than 1 % of all spinal tumors. Calcification of spinal ECs is rare, and EC ossification within the lumbar spine has never been documented. We report the only known congenital lumbar epidermoid tumor with ossification and a literature review of intradural lumbar ECs. Methods: Studies meeting the following criteria were included: 1) EC as the primary tumor type, 2) intradural location, 3) involvement of the lumbar spinal level, and 4) primary presentation. Studies lacking individual patient data or published in a non-English language were excluded. Results: A total of 172 studies were reviewed and 43 were included in analysis. Of the 83 total patients, 37 (45.1 %) were male and 45 (54.9 %) female, at an average age of 26 years. The L3 and L4 spinal levels were most frequently involved. Acquired etiology was reported in 49 (59.0 %) patients, and 24 (28.9 %) cases were congenital. Multivariate analyses demonstrated trends between decreased age and improved outcome, decreased delay in diagnosis and improved outcome, and increased extent of resection with reduced recurrence. Nine calcified spinal ECs were identified, with no previous report of EC ossification in the lumbar spine. Conclusion: We present a case report of the only known ossified epidermoid tumor of the lumbar spine and a comprehensive literature review of 83 patients with intradural lumbar ECs. This review demonstrated trends between reduced age and improved outcome, reduced delay in diagnosis and improved outcome, and increased extent of resection with reduced recurrence.

Introduction: Cellular stress responses play a crucial role in maintaining cellular homeostasis and combating various pathological conditions. Understanding the stress response mechanisms triggered by R. coptidis is critical for harnessing its therapeutic potential. This herb is widely used, but the precise cellular mechanisms through which it exerts its therapeutic effects remain less explored. This review aims to elucidate how R. coptidis affects key cellular pathways and its potential as a therapeutic agent. Method: This review examines existing evidence on the cellular mechanisms and stress response pathways influenced by R. coptidis. The analysis focuses on the regulation of NF-κB, MAPK, PI3K-Akt, AMPK, ERS, and oxidative stress pathways. Sources include peer-reviewed articles, clinical studies, and traditional Chinese medicine (TCM) literature. Results: Evidence indicates that R. coptidis exerts beneficial effects on various diseases by modulating the NF-κB, MAPK, PI3K-Akt, AMPK, ERS, and oxidative stress pathways. By targeting these pivotal pathways, R. coptidis mitigates cellular damage and restores homeostasis under pathological conditions. Conclusion: Understanding the cellular stress response and molecular mechanisms of R. coptidis highlights its multifaceted therapeutic potential. These findings underscore the importance of integrating TCM approaches into modern therapeutic strategies for combating complex diseases. Further investigations into the molecular targets and clinical efficacy of R. coptidis are needed to fully realize its therapeutic potential.

Decentralized Point-of-Care (PoC) diagnostics hold momentous potential for rapid and accessible viral infection disease detection. Presented is a unique design application of an easy-to-use (plug-and-play) platform for viral detection. The platform leverages a simplified multiplex Reverse-Transcription Loop-mediated Isothermal Amplification (RT-LAMP) Lateral Flow Biosensor (LFB) assay with a lyophilized master mix, eliminating the need for RNA isolation or special reporting equipment. A user-friendly Saliva Measuring Tube (SMT) ensures accurate saliva volume self-collection, and a Syringe-based PoC (SPoC) platform automates sample treatment, reagent mixing, and temperature control using readily available components and consumables. The platform’s performance was evaluated by multiplexed detection of the SARS-CoV-2 N2 target gene and human ACTB gene from saliva samples. The SPoC platform achieved a detection limit of spiked 500 copies/mL for SARS-CoV-2 and consistent internal control readout. The presented PoC system offers a promising initial step for further development toward a decentralized solution for viral infection testing.

The failure of bridges, attributed to bridge pier scouring, poses a significant challenge in ensuring safe and cost-effective design. Numerous laboratory and field experiments have been conducted to comprehend the mechanisms and predict the maximum equilibrium scour depth around bridge piers. Over the last eight decades, various empirical methods have been developed, with different authors incorporating diverse influencing parameters that significantly impact the estimation of equilibrium scour depth around bridge piers. This paper aims to consolidate: (1) available experimental and field data sets on different types of bridge pier scouring, (2) the influence of flow and roughness parameters on both clear water scouring (CWS) and live bed scouring (LBS), and (3) existing empirical equations suitable for computing equilibrium scour depth around a bridge pier under CWS and LBS conditions. The presented research encompasses over 80 experimental/field data sets and more than 60 scour-predicting equations developed for CWS and LBS conditions in the past eight decades. Based on the performance of different empirical models in predicting scour depth ratio, suitable models are recommended for CWS and LBS conditions. HIGHLIGHTS To focus on the available experimental and field data sets on different types of bridge pier scouring such as clear water scouring and live bed scouring.; To study the effect of flow and roughness parameters on clear water and live bed scouring.; To select the suitable existing empirical equations to compute scour depth around a bridge pier for clear water and live bed scouring.;

Abstract Background Increased mitochondrial activities contributing to cancer cell proliferation, invasion, and metastasis have been reported in different cancers; however, studies on the therapeutic targeting of mitochondria in regulating cell proliferation and invasiveness are limited. Because mitochondria are believed to have evolved through bacterial invasion in mammalian cells, antibiotics could provide an alternative approach to target mitochondria, especially in cancers with increased mitochondrial activities. In this study, we investigated the therapeutic potential of bacteriostatic antibiotics in regulating the growth potential of colorectal cancer (CRC) cells, which differ in their metastatic potential and mitochondrial functions. Methods A combination of viability, cell migration, and spheroid formation assays was used to measure the effect on metastatic potential. The effect on mitochondrial mechanisms was investigated by measuring mitochondrial DNA copy number by qPCR, biogenesis (by qPCR and immunoblotting), and functions by measuring reactive oxygen species, membrane potential, and ATP using standard methods. In addition, the effect on assembly and activities of respiratory chain (RC) complexes was determined using blue native gel electrophoresis and in-gel assays, respectively). Changes in metastatic and cell death signaling were measured by immunoblotting with specific marker proteins and compared between CRC cells. Results Both tigecycline and tetracycline effectively reduced the viability, migration, and spheroid-forming capacity of highly metastatic CRC cells. This increased sensitivity was attributed to reduced mtDNA content, mitochondrial biogenesis, ATP content, membrane potential, and increased oxidative stress. Specifically, complex I assembly and activity were significantly inhibited by these antibiotics in high-metastatic cells. Significant down-regulation in the expression of mitochondrial-mediated survival pathways, such as phospho-AKT, cMYC, phospho-SRC, and phospho-FAK, and upregulation in cell death (apoptosis and autophagy) were observed, which contributed to the enhanced sensitivity of highly metastatic CRC cells toward these antibiotics. In addition, the combined treatment of the CRC chemotherapeutic agent oxaliplatin with tigecycline/tetracycline at physiological concentrations effectively sensitized these cells at early time points. Conclusion Altogether, our study reports that bacterial antibiotics, such as tigecycline and tetracycline, target mitochondrial functions specifically mitochondrial complex I architecture and activity and would be useful in combination with cancer chemotherapeutics for high metastatic conditions.

Abstract Objective Biopharmaceutics Classification System says that simvastatin (SMV) is a Class II drug with low bioavailability (5%). This is because it dissolves slowly and is broken down a lot in the first pass. Simvastatin transdermal patches were produced as part of this study's aim to treat hyperlipidemia. The Box–Behnken design (three-factor, three-level) was selected for optimization of patches. Methodology The optimization design involved 15 runs with independent factors hydroxypropyl methylcellulose K100, Eudragit L100, and polyethylene glycol 400 percentage, and dependent factors including folding endurance and in-vitro drug release. Results The results showed that the concentration of hydroxypropyl methylcellulose K-100 positively impacted the patch’s folding endurance. The fact that factor C was the only scenario where the p-value was less than 0.05 and the coefficient value was higher in the in vitro drug release model means that it has a greater influence on the release of medicines. The patches were also evaluated for drug content, swelling, moisture uptake, moisture content, etc. The optimized patch shows an in vitro drug release of 55.3% in up to 24 h. In vivo antihyperlipidemic activity was evaluated in albino Wistar rats. In the standard treatment (simvastatin oral) groups, there is a decrease in cholesterol (132.76 ± 0.35) and triglyceride level (139.80 ± 76) whereas in the test formulation group or test group, there is also a decrease in cholesterol (169.65 ± 0.21 mg/dL) and triglyceride level (151.20 ± 31 mg/dL) level. Conclusion Based on in-vitro and in-vivo results it can be concluded that simvastatin patches can be an alternative to traditional therapy.

Abstract Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers.

Background: Prostate cancer (PCa) is the second most common malignancy in men and the sixth leading cause of death. Clinical course of PCa is highly variable and current clinico pathological parameters are unable to predict accurately the course of the disease because of genetic heterogeneity seen in this tumor. Aims and Objectives: The aim of the study was to study the prevalence of E26 transformation-specific-related gene (ERG) expression in benign and malignant lesions of prostate in Northern Indian patients. Whether ERG expression using immunohistochemical (IHC) methods can also be used for differentiating various lesions of the prostate gland is also evaluated. Materials and Methods: This is an observational study conducted on 50 biopsy specimens encompassing different lesions of prostate. The study was carried out in the Department of Pathology at Integral Institute of Medical Sciences and Research, Lucknow, India, during the period January 2020–September 2022. Results: Amongst 50 cases of prostatic lesions included in the study, there were 20 cases of benign prostatic hyperplasia (BPH), 17 cases of benign mimicker lesions and 13 cases of PCa. ERG expression was absent in all cases of BPH and benign mimicker lesions. ERG expression was seen in 38.5% of cases of PCa. Conclusion: In our study, none of the patients of BPH or benign mimicker lesion expressed ERG on IHC, while 38.5% of patients of PCa showed positive staining. This figure differs from reports from other parts of the world. ERG expressions can be a potential therapeutic target for personalized treatment in a subset of patients of PCa. However, it was not found to be a sensitive marker for the diagnosis of PCa.

Segmentation of lesions is crucial for the detection and treatment of ischemic stroke. The aim of this work is to develop a robust and highly accurate framework for lesion stroke detection in brain Magnetic Resonance Imaging (MRI). The paper propose a novel deep learning model, named EnigmaNet, for the segmentation of ischemic stroke lesions in Fluid-Attenuated Inversion Recovery (FLAIR) and Diffusion Weighted Imaging (DWI) images. EnigmaNet use novel Genesis-k blocks and dual attention mechanism in the encoder and decoder blocks of the architecture. A modified Weighted Focal-Tversky-Dice (wFTD) Loss is used for improved performance. The model is validated on the ISLES-2015 public dataset. EnigmaNet showed a Dice score of 0.8965, sensitivity of 0.8776 and specificity of 0.9866 for the FLAIR test images. Dice score of 0.8423, sensitivity of 0.8452 and specificity of 0.9754 were obtained for DWI images. The segmentation results of EnigmaNet shows an improvement in Dice score of about 32% over U-Net-sharp, 41% over FCN-8 and 10% over Attention U-Net. A region-based comparison of segmentation results of EnigmaNet highlighted its ability to detect fine lesions accurately in multiple vascular territories in brain, thereby signifying its robustness to segment lesions of diverse size, shape and location. The proposed model showed improved results as compared to the state-of-the-art techniques. EnigmaNet model is thus a promising approach for accurate and robust segmentation of ischemic stroke lesions.

Introduction: Vitamin B12 (vit B12) deficiency is a preventable disorder and has dire consequences on the neurological development of the infant. The only source of vit B12 for exclusively breastfed newborns is their mother’s milk. So, determining the status of maternal vit B12 levels during early lactation is vital. In India, very few studies have documented vit B12 deficiency among lactating mothers, especially eastern region remains unexplored. Aim: To estimate the prevalence of vit B12 deficiency among healthy lactating mothers attending the postpartum clinic at six weeks at a Tertiary Care Hospital of West Bengal, India and also to compare the haematological values between vit B12 deficient and sufficient groups among the lactating mothers. Materials and Methods: An observational cross-sectional study was conducted in the Department of Biochemistry in collaboration with postpartum clinic of Calcutta National Medical College, West Bengal, India. The study was carried out over a period of two months, from July 2022 to August 2022. Serum vit B12, serum ferritin and haematological parameters {Haemoglobin (Hb), Mean Corpuscular Haemoglobin (MCH), Mean Corpuscular Volume (MCV), Mean Corpuscular Haemoglobin Concentration (MCHC)} were measured in 121 apparently healthy lactating women attending the postpartum clinic for a regular check-up at six weeks. Detailed socioclinical history and dietary history was taken from each participant and these variables were compared between vit B12 deficient and sufficient groups. Pearson’s Chi-square test, Fisher’s-exact test, Mann-Whitney U test were applied to analyse the data. Results: The total study population comprised of 121 mothers with an average age of 25.65±3.71 years and 75% of them consumed non vegetarian diet. A prevalence of 19 (15.7%) deficiency of vit B12 was found among the lactating mothers at six weeks postpartum. Mothers who were vegetarian, multigravida and with complaints of paraesthesia were more associated to cobalamin deficiency. The vit B12 deficient mothers had significantly higher erythrocyte indices than the sufficient group but none of the values were in the megaloblastic range. Conclusion: The vit B12 deficiency was prevalent during early lactation in 19 (15.7%) lactating mothers. The first postnatal visit at six weeks might be the most feasible period to screen and supplement these women to prevent long term sequelae in both mother and child. Haematological parameters were of limited use in identifying vit B12 deficiency during lactation.

Background: Resistance to most of the antitubercular drugs has been on rising trends due to the misuse of existing drugs. This has encouraged us to explore a novel scaffold that has the potential for quick antimicrobial action with minimum side effects. Nitrofurans have attracted us due to their extensive biological activities, such as antibacterial and antifungal activities. Objective: The antitubercular activities of 126 nitrofuran derivatives have been investigated by using indicator parameters and topological and structural fragment descriptors. Methods: The different quantitative structure activity relationship (QSAR) models have been created and validated by using two different methodologies: combinatorial protocol in multiple linear regression (CP-MLR) and partial least-squares (PLS) analysis. Results: The 16 descriptors identified in CP-MLR are from six different classes: Constitutional, Functional, Atom Centered Fragments, Topological, Galvez, and 2D autocorrelation. Indicator parameters and Dragon descriptors suggested that the presence of a furan ring substituted by nitro group is essential for antitubercular activity. Further descriptors from constitutional, and functional classes suggest that the number of double bonds, number of sulphur atoms and number of fragments like thiazole, morpholine and thiophene should be minimum, along with the positive influence of Kier-Hall electrotopological states (Ss) for improved activity. The ACF class descriptors, GALVEZ class descriptors, and 2D-AUTO descriptor GATS4p have also shown positive influence on the antitubercular activity. The TOPO class descriptor T(O…S) suggests that the minimum gap between sulphur and oxygen is favorable for activity. Conclusions: The models acknowledged in the study have explained the variance between 72 to 76% in the training set and in the prediction of the test set compounds. Also, compounds 122:, 123: and 82: were found to possess good binding affinity towards nitroreductase.

Abstract Quantum theory allows spatially separated observers to share nonlocal correlations, which enable them to accomplish classically inconceivable information processing and cryptographic feats. However, the distances over which nonlocal correlations can be realized remain severely limited due to their high fragility to noise and high threshold detection efficiencies. To enable loophole-free nonlocality across large distances, we introduce Bell experiments wherein the spatially separated parties randomly choose the location of their measurement devices. We demonstrate that when devices close to the source are perfect and witness extremal nonlocal correlations, such correlations can be extended to devices placed arbitrarily far from the source. To accommodate imperfections close to the source, we demonstrate an analytic trade-off: the higher the loophole-free nonlocality close to the source, the lower the threshold requirements away from the source. We utilize this trade-off and formulate numerical methods to estimate the critical requirements of individual measurement devices in such experiments.

The study examined the antimicrobial and antioxidant potential of pure Acetyl-11-keto-β-boswellic acid (AKBA), boswellic acid (70%) and AKBA loaded nanoparticles as topical polymeric films. The optimized concentration (0.05 % w/v) of pure AKBA, boswellic acid (BA), and AKBA loaded silver nanoparticles were used to study its impact on film characteristics. Carboxymethyl cellulose (CMC), sodium alginate (SA), and gelatin (Ge) composite films were prepared in this study. The polymeric films were evaluated for their biological (antioxidant and antimicrobial activities) and mechanical characteristics such as tensile strength (TS) and elongation (%). Moreover, other parameters including water barrier properties and color attributes of the film were also evaluated. Furthermore, assessments were conducted using analytical techniques like FTIR, XRD, and SEM. Surface analysis revealed that AgNP precipitation led to a few particles in the film structure. Overall, the results indicate a relatively consistent microstructure. Moreover, due to the addition of AKBA, BA, and AgNPs, a significant decrease in TS, moisture content, water solubility, and water vapor permeation was observed. The films transparency also showed a decreasing trend, and the color analysis revealed decreasing yellowness (b*) of the films. Importantly, a significant increase in antioxidant activity against DPPH free radicals and ABTS cations was observed in the CSG films. Additionally, the AgNP-AKBA loaded films displayed significant antifungal activity against C. albicans. Moreover, the molecular docking analysis revealed the inter-molecular interactions between the AKBA, AgNPs, and composite films. The docking results indicate good binding of AKBA and silver nanoparticles with gelatin and carboxymethyl cellulosemolecules. In conclusion, these polymeric films have potential as novel materials with significant antioxidant and antifungal activities.

Despite being a minimally invasive sample source, dried blood spots (DBS) generally pose the challenge of efficient sample extraction for broad metabolomics applications. This is particularly true for the quantification of steroids using non-derivatized liquid chromatography tandem mass spectrometry assays. To address these limitations, we have demonstrated the use of electric field as a driver for sample preparation from DBS samples to simultaneously quantify testosterone (T), 17α-hydroxyprogesterone (17-OHP), progesterone (P), and cortisol (C), using both standard electroporation cuvettes, as well as a novel custom vertical electric field setup. Our findings, backed by computational modeling, show that a 10V DC application for 180 s can draw out twice the amount of the aforementioned steroids from both Whatman-903 and DMPK-C sample collection cards using our novel device when compared to standard solvent-based collection methods. This study not only introduces the use of electric field for sample preparation for metabolomics, but additionally introduces a novel device that eliminates the electric double layer effect in the process.

Acinar cystic transformation (ACT) is a rare benign cystic lesion of the pancreas reported in elderly women. ACT can be easily confused with other cystic lesions of the pancreas, such as intraductal papillary neoplasm and serous and mucinous neoplasms, on imaging, especially when detected radiologically in a male patient as the index case. A preoperative histological examination can establish a diagnosis and avoid extensive surgical resection. We hereby report a case of ACT in a 69-year-old male patient that affected the body and tail region of the pancreas.

Abstract Activation-induced cytidine deaminase (AID) is the key mediator of antibody diversification in activated B-cells by the process of somatic hypermutation (SHM) and class switch recombination (CSR). Targeting AID to the Ig genes requires transcription (initiation and elongation), enhancers, and its interaction with numerous factors. Furthermore, the HIRA chaperon complex, a regulator of chromatin architecture, is indispensable for SHM. The HIRA chaperon complex consists of UBN1, ASF1a, HIRA, and CABIN1 that deposit H3.3 onto the DNA, the SHM hallmark. We explored whether UBN1 interacts with AID using computational and in-vitro experiments. Interestingly, our in-silico studies, such as molecular docking and molecular dynamics simulation results, predict that AID interacts with UBN1. Subsequently, co-immunoprecipitation and pull-down experiments established interactions between UBN1 and AID inside B-cells. Additionally, a double immunofluorescence assay confirmed that AID and UBN1 were co-localized in the human and chicken B-cell lines. Moreover, proximity ligation assay studies validated that AID interacts with UBN1. Ours is the first report on the interaction of genome mutator enzyme AID with UBN1. Nevertheless, the fate of interaction between UBN1 and AID is yet to be explored in the context of SHM or CSR.

The successful integration of Li-ion batteries in the automotive industry paved the way for their integration into a new generation of aircraft with zero emission. However, potential hazards associated with Li-on batteries are a major concern for the safety-critical aerospace sector. Removing or reducing the hazards from Li-ion batteries while preferable, requires fundamental changes to the battery chemistry. Another way to address this is the implementation of fault diagnostics and prognostics for forecasting or detecting the presence of faults before an aircraft is airborne. This article, part of a three-part series, presents a novel algorithm exploiting the data collected while charging a battery pack for diagnosing faults. The algorithm works off-board, thus not adding any computational burden or weight to the aircraft while minimising aircraft turn-around time, which is crucial for commercial flight operation. This paper presents the underlying method of the algorithm involving the computation of resistance, charge energy and incremental capacity curve using the charging data followed by a combined horizontal and vertical comparative scheme for diagnosis of faults. The performance of the proposed algorithm was validated via module-level experiments considering three cell inactivation faults. Results indicated that the algorithm successfully segregated faulty and unfaulty cells in multiple test scenarios with different number of faults in a laboratory-assembled module. Upon testing the algorithm in experiments conducted using a real-life aerospace battery module, there was a slight reduction in the performance, attributed to greater thermal variation. Nevertheless, the results indicated promising prospects for practical implementation in eVTOL batteries.

Abstract Recent advances in peptide delivery and nanotechnology has resulted in emergence of several non-parenteral administration routes that replace subcutaneous injections associated with patient discomfort. Thiolated biopolymers are relatively new materials being explored to enhance mucoadhesivity and permeability in these efforts, yet their pH dependent reactivity remains an obstacle. This work focussed on improving the mucoadhesivity of thiolated chitosans by activating them with mercaptonicotinic acid, in a bid to create a novel thiomerized chitosan that can open cell tight junctions for application in oral delivery. The synthesized mercaptonicotinic acid activated thiolated chistoan (MNA-TG-chitosan), along with thiolated chitosan (TG-chitosan) and unmodified chitosan were then used to create insulin nanoparticles (insNPs) using spray drying encapsulation process. Use of MNA-TG-chitosan in place of chitosan resulted in reduction of particle size of insNPs from 318 to 277 nm with no significant changes in polydispersity index (~ 0.2), encapsulation efficiency (~ 99%), insulin loading content (~ 25%) and morphology. Results from in-vitro cytotoxicity on TR146, CaCo2 and HepG2 cell lines revealed no significant effects on cell viability at 50–1000 μg/mL concentration. insNPs encapsulated with the new material, MNA-TG-chitosan, resulted in a 1.5-fold and 4.4-fold higher cellular uptake by HepG2 liver cells where insulin is metabolized, approximately 40% and 600% greater insulin transport through TR146 buccal cell monolayers, and 40% and 150% greater apparent permeability than insNPs encapsulated with unmodified chitosan and TG-chitosan respectively. The higher permeation achieved on using MNA-TG chitosan was attributed to the greater opening of the cell tight junction evidenced by reduction of transepithelial electrical resistance of TR146 buccal cell monolayers. This study demonstrates MNA-TG-chitosan as a promising material for improved peptide oral delivery.

Abstract Background Tuberculosis (TB) is a global public health issue, particularly in resource-constrained countries like Nepal. This case report highlights the consequences of prolonged self-treatment and non-compliance with TB management protocols, emphasizing the need for increased awareness and intervention. Case Presentation A 50-year-old male from Nepal self-medicated with anti-tubercular drugs for 13 years after completing the recommended course of treatment. He experienced worsening symptoms, including respiratory distress and visual impairment. Upon evaluation, he was diagnosed with chronic cavitary pulmonary aspergillosis. The patient received comprehensive treatment, including antifungal therapy, steroids, antibiotics, and respiratory support, resulting in significant improvement. Conclusions This case highlights the dangers of self-treatment and non-compliance with TB management protocols. It emphasizes the importance of patient education, awareness programs, and regular follow-up to ensure treatment adherence and detect complications. The case also reveals gaps in the DOTS (Directly Observed Treatment, Short Course) program, including the need for improved surveillance, and a multidisciplinary approach. The ease of over-the-counter purchase of anti-tubercular drugs in Nepal contributed to the patient’s prolonged self-medication, highlighting a concerning. The complications arising from prolonged self-medication underscore the need for increased awareness, intervention, and patient education in TB management. Improving patient education, raising awareness about the risks of self-medication, and integrating ophthalmologic evaluations into standard management are essential for better TB control in Nepal.

In this paper, we propose a method for denoising experimental density matrices that combines standard quantum state tomography with an attention-based neural network architecture. The algorithm learns the noise from the data itself, without a priori knowledge of its sources. Firstly, we show how the proposed protocol can improve the averaged fidelity of reconstruction over linear inversion and maximum likelihood estimation in the finite-statistics regime, reducing at least by an order of magnitude the amount of necessary training data. Next, we demonstrate its use for out-of-distribution data in realistic scenarios. In particular, we consider squeezed states of few spins in the presence of depolarizing noise and measurement/calibration errors and certify its metrologically useful entanglement content. The protocol introduced here targets experiments involving few degrees of freedom and afflicted by a significant amount of unspecified noise. These include NISQ devices and platforms such as trapped ions or photonic qudits.

Medical datasets may be imbalanced and contain errors due to subjective test results and clinical variability. The poor quality of original data affects classification accuracy and reliability. Hence, detecting abnormal samples in the dataset can help clinicians make better decisions. In this study, we propose an unsupervised error detection method using patterns discovered by the Pattern Discovery and Disentanglement (PDD) model, developed in our earlier work. Applied to the large data, the eICU Collaborative Research Database for sepsis risk assessment, the proposed algorithm can effectively discover statistically significant association patterns, generate an interpretable knowledge base for interpretability, cluster samples in an unsupervised learning manner, and detect abnormal samples from the dataset. As shown in the experimental result, our method outperformed K-Means by 38% on the full dataset and 47% on the reduced dataset for unsupervised clustering. Multiple supervised classifiers improve accuracy by an average of 4% after removing abnormal samples by the proposed error detection approach. Therefore, the proposed algorithm provides a robust and practical solution for unsupervised clustering and error detection in healthcare data.

Climatic changes and global warming affect the growth, development, and productivity of crops. In this review, we highlight the possible benefits of using innovative breeding techniques like clustered regularly interspaced short palindromic repeats (CRISPRs), exogenous phytohormone-like strigolactones (SLs), nanomaterials (NMs), and beneficial microbial endophytes to address the challenges in sustainable cultivation of horticultural crops. These applications are evaluated by examining how they affect different metabolic, morphological, and biochemical parameters in diverse crops. Endophytes are symbiotic microorganisms and can be used as nematicides for improving crop yield. With an emphasis on quality control, we examined the impacts of applying NMs, a novel family of phytohormones called SLs, and microbial endophytes on horticultural commodities. Furthermore, we reviewed the benefits of CRISPR for the editing of plant genomes, as well as how it affects gene expression and transcription factors to increase crop tolerance and yield. These innovations hold the potential to improve crop yield, quality, and resilience by acting as safe, natural components in biofertilizers and plant protection solutions. Gradually adopting these methods could decrease reliance on agrochemicals, thereby reducing their negative effects on biodiversity, soil fertility, and human health.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies in the world, for which the mortality is almost as high as the disease incidence and is predicted to be the second‐highest cause of cancer‐related deaths by 2030. These cancerous tumors consist of diversified gene expressions within the different cellular subpopulations that include neoplastic ductal cells, cancer‐associated fibroblasts, and immune cells, all of which collectively facilitate cellular heterogeneity in the PDAC tumor microenvironment (TME). Active intratumoral interaction within the cell populations in TME induces the proliferation of cancerous cells, accounting for tumorigenesis and rapid metastasis. Methods This review will focus on novel findings uncovering PDAC heterogeneity in different cellular subpopulations using single‐cell RNA‐sequencing (scRNA‐seq) and other single‐cell analysis technologies. It will further explore the emerging role of single‐cell technologies in assessing the role of different subpopulations of neoplastic ductal cells, cancer‐associated fibroblasts, and immune cells in PDAC progression. Results and Conclusion The application of scRNA‐seq in PDAC has started to unveil associations between disease progression and heterogeneity in pancreatic TME and could influence future PDAC treatment. Recent advances in scRNA‐seq have uncovered comprehensive analyses of heterogeneous ecosystems present within the TME. These emerging findings underpins further need for a more in‐depth understanding of intratumoral heterogeneity in the PDAC microenvironment.

Abstract Aim Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate of all major cancers. Chemotherapy is the mainstay systemic therapy for PDAC, and chemoresistance is a major clinical problem leading to therapeutic failure. This study aimed to identify key differences in gene expression profile in tumors from chemoresponsive and chemoresistant patients. Methods Archived formalin‐fixed paraffin‐embedded tumor tissue samples from patients treated with neoadjuvant chemotherapy were obtained during surgical resection. Specimens were macrodissected and gene expression analysis was performed. Multi‐ and univariate statistical analysis was performed to identify differential gene expression profile of tumors from good (0%–30% residual viable tumor [RVT]) and poor (>30% RVT) chemotherapy‐responders. Results Initially, unsupervised multivariate modeling was performed by principal component analysis, which demonstrated a distinct gene expression profile between good‐ and poor‐chemotherapy responders. There were 396 genes that were significantly (p

Abstract Background Transferrable mechanisms of quinolone resistance (TMQR) can lead to fluoroquinolone non-susceptibility in addition to chromosomal mechanisms. Some evidence suggests that fluoroquinolone resistance is increasing among the pediatric population. We sought to determine the occurrence of TMQR genes among quinolone-resistant E. coli and K. pneumoniae causing urinary tract infections among Nepalese outpatient children (

The paper proposes a hierarchical reliability modelling and assessment approach for a life support system (LSS) that provides oxygen to the pilot and is employed in a combat aircraft. The system has the primary function of generating oxygen onboard, and it has a backup gaseous oxygen tank as redundancy. An emergency oxygen bottle is also part of the ejection seat for emergency use. Both backup oxygen and emergency oxygen have a fixed capacity and a fixed duration of oxygen supply. Therefore, it is crucial to assess the reliability of the LSS to ensure its safety and effectiveness of this LSS during a mission by the combat aircraft. The proposed reliability model of LSS is developed as a two-level hierarchical model, that captures the inherent randomness in the operation of the system. At the lowest level of the hierarchy, Markov chains are used to model the events that may lead to the failure of the LSS. The events include the failure of individual components, the depletion of backup oxygen, and the depletion of emergency oxygen. The Markov chains consider the interactions between individual components and events during the mission profile. At the top level of the hierarchy, a fault tree is used to model the interactions between various events during the mission profile. The fault tree considers the interactions between individual events and the effects of redundancy on the reliability of the LSS. The results of the Markov chains at the lower level are exported to the higher level modelled via fault tree to find the overall system reliability. The reliability model is further extended to incorporate the deterministic nature of the LSS due to the fixed capacity of the backup tank and emergency bottle. The work addresses the modelling of six different scenarios of LSS operations. The modelling of these scenarios is achieved using Semi-Markov Processes (SMP), which allow the state holding time to be a general distribution.

Scouring refers to the process by which bed sediment in a river is eroded around the periphery of a bridge abutment or pier. Many empirical models are available to estimate the scour depth for different flow, geometry, and bed roughness condition. However, none of them provide a better estimation of scour depth for a wide range of input parameters. Thus, in this paper, the scour depth around bridge piers has been modelled using M5 tree and hybrid artificial neural network (ANN)-particle swarm optimisation (PSO) techniques by considering the wide range of datasets. The clear-water scouring (CWS) datasets are collected from the literature and five different non-dimensional influencing parameters are selected as input parameters to model the scour depth. A Gamma test (GT) was performed to choose the best input parameter combinations. Based on the lowest gamma value and V-ratio, 4 out of 26 distinct input combinations for CWS depth modelling were chosen in the GT. According to statistical measures, the proposed M5 tree model predicts scour depth better than empirical approaches. Additionally, the developed ANN-PSO model is suitable for determining scour depth in both rectangular and circular shapes of piers. The results of both developed models are compared with other existing models and found to be satisfactory. HIGHLIGHTS A wide dataset range is considered in developing a model for scour depth around the bridge pier.; Influencing parameters affecting the scour depth are identified using the Gamma test.; Separate models have been proposed for clear-water scouring around bridge piers using the M5 tree and ANN-PSO.;

Abstract Background Ondansetron is a selective 5-hydroxytryptamine type 3 serotonin-receptor antagonist with antiemetic properties used inadvertently in the emergency department for controlling nausea. However, ondansetron is linked with a number of adverse effects, including prolongation of the QT interval. Therefore, the purpose of this meta-analysis was to assess the occurrence of QT prolongation in pediatric, adult, and elderly patients receiving oral or intravenously administered ondansetron. Methods A thorough electronic search was conducted on PubMed (Medline) and Cochrane Library from the databases' inception to August 10, 2022. Only those studies were considered in which ondansetron was administered orally or intravenously to participants for the treatment of nausea and vomiting. The prevalence of QT prolongation in multiple predefined age groups was the outcome variable. Analyses were conducted using Review manager 5.4 (Cochrane collaboration, 2020). Results A total of 10 studies involving 687 ondansetron group participants were statistically analyzed. The administration of ondansetron was associated with a statistically significant prevalence of QT prolongation in all age groups. An age-wise subgroup analysis was conducted which revealed that the prevalence of QT prolongation among participants younger than 18 years was not statistically significant, whereas it was statistically significant among participants aged 18–50 years and among patients older than 50 years. Conclusions The present meta-analysis provides further evidence that oral or intravenous administration of Ondansetron may lead to QT prolongation, particularly among patients older than 18 years of age.