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Alzheimer’s disease (AD) is a multifactorial, rapidly progressing neurodegenerative disorder. As the exact cause of the disease is still unclear, the drug development is very challenging. This review encompasses the commonly used AD models involving various chemicals, heavy metals and endogenous substances induced models and the transgenic models. It also provides insight into the reliable emerging models of AD that may overcome the shortcomings associated with available models. Chemicals like streptozotocin, scopolamine, colchicine and okadaic acid render the animal susceptible to neuroinflammation and oxidative stress induced neurodegeneration along with amyloid-β deposition and tau hyperphosphorylation. Similarly, endogenous substances like acrolein and amyloid-β 1–42 are efficient in inducing the major pathologies of AD. Heavy metals like aluminum and fluoride and mixture of these have been reported to induce neurotoxicity therefore are used as animal models for AD. Transgenic models developed as a result of knock-in or knock-out of certain genes associated with AD including PDAPP, APP23, Tg2576, APP/PS1, 3 × Tg and 5 × FAD have also been incorporated in this study. Further, emerging and advanced pathomimetic models of AD are provided particular interest here which will add on to the current knowledge of animal models and may aid in the drug development process and deepen our understanding related to AD pathogenesis. These newly discovered models include oAβ25-35 model, transgenic model expressing 82-kDa ChAT, oDGal mouse and APP knock-in rat. This study may aid in the selection of suitable model for development of novel potent therapeutics and for exploring detailed pathogenic mechanism of AD. Graphical abstract

The current generation is witnessing a huge interest in optical waveguides due to their salient features: they are of low cost, immune to electromagnetic interference, easy to multiplex, have a compact size, etc. These features of optical fibers make them a useful tool for various sensing applications including in medicine, automotives, biotechnology, food quality control, aerospace, physical and chemical monitoring. Among all the reported applications, optical waveguides have been widely exploited to measure the physical and chemical variations in the surrounding environment. Optical fiber-based temperature sensors have played a crucial role in this decade to detect high fever and tackle COVID-19-like pandemics. Recognizing the major developments in the field of optical fibers, this article provides recent progress in temperature sensors utilizing several sensing configurations including conventional fiber, photonic crystal fiber, and Bragg grating fibers. Additionally, this article also highlights the advantages, limitations, and future possibilities in this area.

Benzodiazepines such as diazepam, lorazepam and midazolam remained the mainstay of treatment for acute repetitive seizures (ARS). The immediate care for ARS should often begin at home by a caregiver. This prevents the progression of ARS to prolonged seizures or status epilepticus. For a long time and despite social objections rectal diazepam gel remained only FDA-approved rescue medication. Intranasal administration of benzodiazepines is considered attractive and safe compared with rectal, buccal and sublingual routes. Intranasal delivery offers numerous advantages such as large absorptive surface area, bypass the first-pass metabolism and good patient acceptance as it is needle free and painless. Recent clinical studies have demonstrated that diazepam nasal spray (NRL-1; Valtoco®, Neurelis Inc.,San Diego, CA, USA) showed less pharmacokinetic variability and reliable bioavailability compared with the diazepam rectal gel. Diazepam nasal spray could be considered as a suitable alternative for treating seizure emergencies outside the hospital. This review summarizes the treatment options for ARS and findings from clinical studies involving intranasal diazepam for treating seizure emergencies.

Medical termination of pregnancy (MTP) has been legalized in India since 1971 considering the huge burden of unsafe abortions. Even after about 50 years, Indian women continued to have unsafe abortions and face adverse and fatal consequences. At this point, only legislative amendments may not be sufficient but along with that, many other aspects need to be considered like awareness, availability, accessibility, affordability of quality MTP services, and contraceptives. People should know the adverse effects of taking unsupervised medical termination pills. Comprehensive abortion care should be provided at every level of health care to ensure the good reproductive health of the women.

PurposeAgriculture value chains (AVCs) have experienced unprecedented disruption during the COVID-19 pandemic, with lockdowns and stringent social distancing restrictions making buying and selling behaviours complex and uncertain. This study aims provide a theoretical framework describing the stakeholder behaviours that arise in severely disrupted value chains, which give rise to inter-organisational initiatives that impact industry sustainability.Design/methodology/approachA mixed-methods approach is adopted, in which uncertainty theory and relational governance theory and structured interviews with 15 AVC stakeholders underpin the initial conceptual model. The framework is empirically validated via partial least squares structural equation modelling using data from an online survey of 185 AVC stakeholders based in India.FindingsThe findings reveal that buyer and supplier uncertainty created by the COVID-19 lockdowns gives rise to behaviours that encourage stakeholders to engage in relational governance initiatives. Progressive farmers and other AVC stakeholders welcome this improved information sharing, which encourages self-reliance that positively impacts agricultural productivity and sustainability.Practical implicationsThe new framework offers farmers and other stakeholders in developing nations possibilities to sustain their AVCs even in dire circumstances. In India, this also requires an enabling ecosystem to enhance smallholders' marketing power and help them take advantage of recent agricultural reforms.Originality/valueResearch is scarce into the impact of buyer and seller behaviour during extreme supply chain disruptions. This study applies relational governance and uncertainty theories, leading to a proposed risk aversion theory.

Exploration of secondary resources for isolation of valuable constituents, such as rare earth elements (REEs) and trace elements (TEs), is of importance owing to the need to identify new domestic sources and reduce reliance on imports. The present study systematically discusses the distribution of REEs and TEs in core samples from the coal block of Bhalukasba Surni {(B1(125 m)-B9 (409 m)} located in Rajmahal coalfield, Jharkhand, India, which has not been investigated previously for its geochemistry. The studied coal samples were found to be enriched in TEs whose abundances were in the order of Mn > Mo > Zr > Ni > Cr > V > Cu > Zn > Pb, and REEs (La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Er, Tm, Yb, Lu) along with Sc and Y. The average concentration of REEs with yttrium (ΣREY) on an ash basis was 528 ppm, which is significantly higher than the world average for coal ash (435 ppm). Of the samples investigated, B3 (182–184 m) and B8 (396–399 m) demonstrated relatively higher concentrations of potentially economic elements, with B3 containing a higher proportion of middle to heavy REEs Gd, Dy, Ho and Er, and B8 showing relative enrichment in Nd and Y. On dry whole coal basis, B6 (275–278 m) showed a considerably higher concentration of Ge (55 ppm) than other samples, whereas the concentration of Zr varied in the range of 90–160 ppm in the whole coal block. X-ray diffraction studies revealed the presence of quartz, keatite, hematite, zircon, anatase and orthoclase in the coal ash samples prepared at 815 °C. REEs exhibited prominent positive correlation with Al 2 O 3 (0.4 <  r > 0.9) which is supportive of their residence in primary clay minerals such as kaolinite and illite-smectite. Additionally, a positive correlation of REEs with P 2 O 5 (0.4 <  r > 0.9) suggests their association with phosphate minerals (such as monazite, xenotime, apatite). Positive correlation with TiO 2 ( r  > 0.7) corroborates the possible association of REEs with anatase. The morphology of the coal ash samples viewed in SEM showed the presence of Al 2 O 3 and SiO 2 enriched irregular-sponge particles likely derived from partly-fused clay minerals, which accounted for the lower extent of REE encapsulation. The Bhalukasba Surni coal block is potentially of economic importance due to its enrichment in Ge, Zr, and the REEs. Highlights A systematic study on the distribution of REEs and TEs in the coal block of Bhalukasba Surni in Rajmahal coalfield, Jharkhand, India was performed. The average concentration of ΣREY on an ash basis was 528 ppm as compared to the world average of 435 ppm. Enrichment of trace elements followed the order of Mn > Mo > Zr > Ni > Cr > V > Cu > Zn > Pb. X-ray diffraction studies revealed the presence of quartz, keatite, hematite, zircon, anatase and orthoclase in the coal ash samples prepared at 815 °C.

Evidence supports the integration of prevention and management for tuberculosis (TB) with non-communicable diseases (NCDs). Bi-directional screening for TB and diabetes mellitus (DM) is already implemented in India, a country with a dual burden of TB and NCDs. However, very limited programmatic data are available on the feasibility of adding other NCDs and their risk factors in such screening programme. To assess the yield, feasibility, and acceptability of a two-stage integrated screening for NCDs and risk factors for NCDs among patients with TB ≥20 years and treated in DOTS centres of two medical colleges in Delhi, between October 2016 and March 2017. It was a mixed-methods, triangulation study with a quantitative component (cross-sectional study using questionnaires, anthropometric measurements and records review) and a qualitative component (descriptive study using interview data). Amongst 403 patients screened, the prevalence of hypertension was 7% (n = 28) with 20 new cases detected and 8% for DM (n = 32) with 6 new cases diagnosed. The number needed to screen to find a new case was 20 and 63 for hypertension and DM respectively. The most frequent NCD-risk factors were inadequate vegetable (80%) and fruits (72%) intake, alcohol use (34%), use of smokeless tobacco (33%) and smoking (32%). Clustering of four or more risk factors was associated with increasing age and male sex (p<0.05). Both patients and health providers considered the screening relevant and acceptable. However, waiting time and costs involved in blood tests were considered as bothersome by the patients, while health providers perceived increased workload, inadequate medical supplies and inadequate skills and knowledge as key challenges in implementation of the screening. Integrating screening for NCDs and their risk factors in the existing TB programme produces high yield and it is feasible and acceptable by patients and health providers provided the challenges are overcome.

The purpose of this study was to develop a model to predict whether or not glaucoma will progress to the point of requiring surgery within the following year, using data from electronic health records (EHRs), including both structured data and free-text progress notes. A cohort of adult glaucoma patients was identified from the EHR at Stanford University between 2008 and 2020, with data including free-text clinical notes, demographics, diagnosis codes, prior surgeries, and clinical information, including intraocular pressure, visual acuity, and central corneal thickness. Words from patients' notes were mapped to ophthalmology domain-specific neural word embeddings. Word embeddings and structured clinical data were combined as inputs to deep learning models to predict whether a patient would undergo glaucoma surgery in the following 12 months using the previous 4-12 months of clinical data. We also evaluated models using only structured data inputs (regression-, tree-, and deep-learning-based models) and models using only text inputs. Of the 3,469 glaucoma patients included in our cohort, 26% underwent surgery. The baseline penalized logistic regression model achieved an area under the receiver operating curve (AUC) of 0.873 and F1 score of 0.750, compared with the best tree-based model (random forest, AUC 0.876; F1 0.746), the deep learning structured features model (AUC 0.885; F1 0.757), the deep learning clinical free-text features model (AUC 0.767; F1 0.536), and the deep learning model with both the structured clinical features and free-text features (AUC 0.899; F1 0.745). Fusion models combining text and EHR structured data successfully and accurately predicted glaucoma progression to surgery. Future research incorporating imaging data could further optimize this predictive approach and be translated into clinical decision support tools.

Festivals are significant markers of cultural heritage and community traditions. Nevertheless, every year, significant increases in pollution levels are recorded during celebratory events, due to the overuse of firecrackers. This study evaluated gaseous and particulate matter (PM) concentrations using a gas and particulate sampler, alongside noise levels measured by a sound level meter, during the pre-to-post-Diwali period of 2023 and 2024 in Malda, India, and PM concentrations in Warsaw, Poland in 2024, using a DustAir dust meter. The results indicated that during Diwali, the concentrations of PM2.5 and PM1 exceeded the standard set by the World Health Organization, while gaseous pollutants remained within acceptable limits. Since no standards set for PM1 exist, PM2.5 criteria were utilized as a benchmark. Additionally, on New Year’s Eve in Warsaw, concentrations of PM10, PM2.5, and PM1 surpassed the standard around midnight, while gaseous pollutants remained within the standard range. An elemental analysis revealed 13 elements in Diwali PM samples, with toxic metals like arsenic and cadmium more prevalent in PM1. The risk of carcinogenic and non-carcinogenic effects through ingestion was higher for children compared to adults. The findings of this study could potentially raise awareness among researchers and policymakers, prompting them to develop sustainable substitutes for firecrackers and sparklers.

In this study, we demonstrate the influence of operating temperature variation and stress-induced effects on a silicon-on-insulator (SOI)-based multi-mode interference coupler (MMI). Here, SiGe is introduced as the cladding layer to analyze its effect on the optical performance of the MMI coupler. SiGe cladding thickness is varied from 5 nm to 40 nm. Characterization of the MMI coupler for ridge waveguides with both rectangular and trapezoidal sidewall slope angle cross-sections is reviewed in terms of power splitting ratio and birefringence. Stress-induced birefringence as a function of operating temperature and cladding thickness for fundamental mode have been calculated. A trapezoidal waveguide with 40 nm of cladding thickness induces more stress and, therefore, affects birefringence more than a rectangular waveguide of any thickness. Simulation results using the finite element method (FEM) confirmed that operating temperature variation, upper cladding thickness, and its stress effect are significant parameters that drastically modify the performance of an MMI coupler.