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The paper reviews the entire spectrum of Artificial Intelligence (AI) in mental health and its positive role in mental health. AI has a huge number of promises to offer mental health care and this paper looks at multiple facets of the same. The paper first defines AI and its scope in the area of mental health. It then looks at various facets of AI like machine learning, supervised machine learning and unsupervised machine learning and other facets of AI. The role of AI in various psychiatric disorders like neurodegenerative disorders, intellectual disability and seizures are discussed along with the role of AI in awareness, diagnosis and intervention in mental health disorders. The role of AI in positive emotional regulation and its impact in schizophrenia, autism spectrum disorders and mood disorders is also highlighted. The article also discusses the limitations of AI based approaches and the need for AI based approaches in mental health to be culturally aware, with structured flexible algorithms and an awareness of biases that can arise in AI. The ethical issues that may arise with the use of AI in mental health are also visited.

Nepal’s community forestry initiatives have significantly enhanced forest restoration outcomes; however, nearly two-thirds of rural households continue to depend on forest resources, exerting sustained socio-ecological pressure on conservation. In Khaptad National Park (KNP), a mountainous and emerging tourism destination, this study analyzed land use and land cover (LULC) dynamics from 1991 to 2020 using multi-temporal Landsat imagery combined with household survey data. We employed intensive mountain-specific pre-processing—including topographic illumination normalization and DEM-based terrain shadow masking—followed by random forest classification to assess spatial changes in both core and buffer zones. Results show that agricultural land and grassland increased by 8.17 km 2 and 17.60 km 2 , respectively, while forest and shrubland decreased by 18.63 km 2 and 10.48 km 2 . In the buffer zone, agricultural land expanded from 79.00 km 2 in 1991 to 87.09 km 2 in 2020 (~ 0.28 km 2 yr⁻ 1 ). These transitions coincided with rising mean temperature and precipitation trends. Survey findings indicate that although over half of households perceived a decline in agricultural productivity, many simultaneously reported greater dependence on agriculture and livestock, reflecting adaptive livelihood strategies amid environmental constraints. The combination of demographic pressures, tourism-related demand, and limited alternatives to biomass energy continues to drive forest conversion and resource extraction in the buffer zone. Collectively, these results underscore the urgent need for integrated land-use planning, adaptive forest management, and context-appropriate sustainable tourism strategies to balance local livelihood needs with long-term conservation goals and enhance socio-ecological resilience in mountain protected areas.

The workflow of this research is based on numerous hypotheses involving the usage of pre-processing methods, wheat canopy segmentation methods, and whether the existing models from the past research can be adapted to classify wheat crop water stress. Hence, to construct an automation model for water stress detection, it was found that pre-processing operations known as total variation with L1 data fidelity term (TV-L1) denoising with a Primal-Dual algorithm and min-max contrast stretching are most useful. For wheat canopy segmentation curve fit based K-means algorithm (Cfit-kmeans) was also validated for the most accurate segmentation using intersection over union metric. For automated water stress detection, rapid prototyping of machine learning models revealed that there is a need only to explore nine models. After extensive grid search-based hyper-parameter tuning of machine learning algorithms and 10 K fold cross validation it was found that out of nine different machine algorithms tested, the random forest algorithm has the highest global diagnostic accuracy of 91.164% and is the most suitable for constructing water stress detection models.

Immunoglobulin light chain amyloidosis (AL amyloidosis) is among the most common forms of systemic amyloidosis. Using electronic health records (EHR) data from the United States, we aimed to estimate the incidence and prevalence of AL amyloidosis over time, to evaluate the distribution of different disease stages, and to assess patients’ demographic characteristics. We conducted a retrospective cohort study using Optum EHR data from 2016 to 2022. AL amyloidosis was defined by ≥ 2 ICD-10-CM codes or positive mentions in the EHR that were ≥ 30 days apart. Incident and prevalent patients were included. Staging was assessed using cardiac biomarkers (whenever available) according to the European modification of the 2004 Mayo staging system. A total of 1976 AL amyloidosis patients were identified. In 2021, the estimated AL amyloidosis incidence was 16.7 per million person-years in adults, and the prevalence was 69.0 per million adult population. Among patients with staging available near the time of diagnosis (41.7% of incident patients), the following distribution was observed: 16.1% Stage I, 44.5% Stage II, 20.6% Stage IIIa, and 18.8% Stage IIIb. At the most recently available staging assessment, combined Stage IIIa and IIIb was more common among males (38.6% vs. 27.1%) and was more common with increasing age (25.7% for 40–49 years vs. 38.5% for 80+ years). We observed the highest prevalence of AL amyloidosis published to date. This may be due to true increased prevalence, consistent with reports of improved survival in AL amyloidosis.

There are significant variations in discharge post-diabetes-related ketoacidosis (DKA) hospitalisation, yet there is a paucity of research to understand or minimise the reasons. This quality improvement project (QIP) aimed to identify reasons for post-DKA discharge delays and assess intervention efficacy. Utilising the Digital Evaluation of Ketosis and Other Diabetes-related Emergencies (DEKODE) model, data from 177 DKA episodes from January 2021 to September 2023 across three hospitals were analysed. Factors affecting discharge were investigated through a plan, do, study, act (PDSA) methodology. While interventions focused on optimising data collection and refining discharge guidelines, no significant reduction in DKA duration or length of stay was observed. Findings highlight post-DKA hospitalisation's multifaceted nature and the limited impact of simple interventions. Collaborative efforts and further research are necessary to develop effective strategies for expedited discharge and improved patient care. This study's comprehensive tracking and analysis tool offers valuable insights for future interventions in managing DKA-related hospitalisations.

Maternally inherited endosymbionts of arthropods are one of the most abundant and diverse group of bacteria. These bacterial endosymbionts also show extensive horizontal transfer to taxonomically unrelated hosts and widespread recombination in their genomes. Such horizontal transfers can be enhanced when different arthropod hosts come in contact like in an ecological community. Higher rates of horizontal transfer can also increase the probability of recombination between endosymbionts, as they now share the same host cytoplasm. However, reports of community‐wide endosymbiont data are rare as most studies choose few host taxa and specific ecological interactions among the hosts. To better understand endosymbiont spread within host populations, we investigated the incidence, diversity, extent of horizontal transfer, and recombination of three endosymbionts (Wolbachia, Cardinium, and Arsenophonus) in a specific soil arthropod community. Wolbachia strains were characterized with MLST genes whereas 16S rRNA gene was used for Cardinium and Arsenophonus. Among 3,509 individual host arthropods, belonging to 390 morphospecies, 12.05% were infected with Wolbachia, 2.82% with Cardinium and 2.05% with Arsenophonus. Phylogenetic incongruence between host and endosymbiont indicated extensive horizontal transfer of endosymbionts within this community. Three cases of recombination between Wolbachia supergroups and eight incidences of within‐supergroup recombination were also found. Statistical tests of similarity indicated supergroup A Wolbachia and Cardinium show a pattern consistent with extensive horizontal transfer within the community but not for supergroup B Wolbachia and Arsenophonus. We highlight the importance of extensive community‐wide studies for a better understanding of the spread of endosymbionts across global arthropod communities. This manuscript characterizes incidence, diversity, extent of horizontal transfer, and recombination of three different endosymbionts (Wolbachia, Cardinium, and Arsenophonus) in a soil arthropod community. We utilized multilocus strain typing system (MLST) for Wolbachia and 16S rRNA gene for Cardinium and Arsenophonus to answer whether endosymbionts are being transferred within an ecological community first and then spreading through different arthropod communities across the world.

The COVID-19 pandemic has deeply disrupted cancer care, both during and after lockdowns. In this study, we analysed the treatment delay in patients with breast cancer due to COVID-19 pandemic in India. From March 2, 2020, to March 31, 2021, patients with breast cancer who presented to the breast clinic in the department of Radiotherapy & Oncology, Regional Cancer Centre, Postgraduate Institute of Medical Education and Research, Chandigarh, India were included in this analysis. Delays to the start of chemotherapy, surgery, and radiotherapy faced by patients with breast cancer were recorded. Delays to the patient treatment due to the COVID-19 pandemic were calculated and its impact on disease outcomes was analysed. 405 women were registered in the breast clinic. Diagnosis was delayed for up to 3 months for 144 (36%) patients, 4–6 months for 70 (17%) patients, 7–9 months for 43 (11%) patients, 10–11 months for 37 (9%) patients, and 12 or more months for 111 (27%) patients. Localised disease at presentation was observed in 360 (89%) patients, and metastatic disease in 45 (11%) patients. A total of 161 (40%) patients had delays to their treatment: chemotherapy was delayed for 45 (11%) patients, surgery for 56 (14%) patients, and radiotherapy for 90 (22%) patients. 19 (5%) patients were lost to follow-up. Disease progression occurred in 33 (20%) of 161 patients who had delays to start of treatment. Significantly more patients (64 [40%] of 161) who faced delays to treatment presented with T4 disease than patients who did not face delays (58 [26%] of 225; p=0·010). A significantly greater number of patients required neoadjuvant chemotherapy because of the delay at the start of treatment (90 [56%] vs 59 (26%) patients who did not face delays; p<0·0001). 142 (88%) of 161 patients who faced treatment delays and in 193 (86%) of 225 patients who did not face delays underwent surgery (either lumpectomy or mastectomy). More patients who faced treatment delays (107 [75%] of 142) had to undergo mastectomy than did patients who did not face delays (131 [68%] of 193). In patients with disease progression, median delay to start of chemotherapy was 3 months (IQR 2–8), median delay to start of surgery was 3 months (2–6), and median delay to start of radiotherapy was 2 months (2–4). Due to delays in diagnosis and start of treatment, more patients presented with advanced tumours, which resulted in a greater number of patients needing neoadjuvant chemotherapy. Presentation in advanced stage translated to more mastectomies in these patients. Smaller delays to the start of radiotherapy could be because radiotherapy facilities were still operational during the COVID-19 pandemic. Delays to the start of treatment of breast cancer led to disease progression in one-fifth of affected patients, which can negatively affect their survival. Patients affected by delays to diagnosis or start of treatment need to be followed-up on for monitoring of effects of these delays on survival. None.

Quantifying landslide volumes in earthquake affected areas is critical to understand the orogenic processes and their surface effects at different spatio-temporal scales. Here, we build an accurate scaling relationship to estimate the volume of shallow soil landslides based on 1 m pre- and post-event LiDAR elevation models. On compiling an inventory of 1719 landslides for 2018 M w 6.6 Hokkaido-Iburi earthquake epicentral region, we find that the volume of soil landslides can be estimated by γ = 1.15. The total volume of eroded debris from Hokkaido-Iburi catchments based on this new scaling relationship is estimated as 64–72 million m 3 . Based on the GNSS data approximation, we noticed that the co-seismic uplift volume is smaller than the eroded volume, suggesting that frequent large earthquakes (and rainfall extremes) may be counterbalancing the topographic uplift through erosion by landslides, especially in humid landscapes such as Japan, where soil properties are rather weak.

IntroductionThe revision of International Federation of Gynaecology and Obstetrics staging in 2018 with recommendations to include cross-sectional imaging and a separate stage for node positive disease have opened a lot of uncertainties in implementing the correct treatment approach in these patients. While studies have suggested higher chances of occult para-aortic lymph node (PALN) even with advanced imaging, especially in pelvic node positive disease which tend to recur after pelvic radiation therapy. This study intends to study these patients and isolate the subset who will benefit most from elective PALN irradiation.Methods and analysisThis is an ongoing multicentric phase III randomised controlled trial with a sample size of 274 subjects in two arms (137 in each arm) to determine the superiority of limited elective para-aortic irradiation compared with no irradiation. Arm one includes radiation to the lower PALN and pelvis; Arm two includes radiation to the pelvis. Concurrent chemotherapy followed by brachytherapy is standard in both arms. Patients with cervical cancer and radiologically positive pelvic LNs aged>18 years and<70 years are screened for the study. The primary endpoint of this study is 3-year disease-free survival. The secondary endpoints include 3-year para-aortic recurrence-free survival, 3-year distant metastasis-free survival, 3-year overall survival, acute and late toxicity, quality of life. Translational study to evaluate systemic immune response by FAPI-PETCT (fibroblast activator protein inhibitor positron emission tomography) and assessment of p16, L1 cell adhesion molecule (L1CAM) and protein death ligand-1 (PDL-1) expression by immunohistochemistry.Ethics and disseminationThe study has been approved by the institutional ethics committee and will be routinely monitored according to standard guidelines. The results of the study will be published in peer-reviewed scientific journals, presented at conferences and submitted to regulatory authorities.Trial registration numberThe study was registered on 17 January 2022 under CTRI/2022/01/039495 (http://ctri.nic.in).

Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) has significantly affected maize crop yields, production efficiency, and farmers’ incomes in the Indian Eastern Gangetic Plains region since it was first observed in India in 2018. A lack of awareness by maize growers of the appropriate selection, method, and timing of insecticide application not only creates a barrier to sustainable FAW control but also contributes to increased environmental pollution, reduced human health and increased production costs. We demonstrated that FAW inflicted the most damage in early whorl growth stage of maize, regardless of whether chemical insecticides were applied. FAW egg masses and larvae collected from maize fields in which no insecticides had been sprayed showed high parasitism rates by parasitoid wasps; in contrast fields that had been sprayed had much lower rates of parasitism on FAW. Ten hymenopteran parasitoids were observed in maize fields across the study region, suggesting a diversity of natural methods to suppress FAW in maize at different growth stages. These included two FAW egg parasitoids and eight FAW larval parasitoids. Microplitis manilae Ashmead was the most abundant FAW larval parasitoid species, and Telenomus cf. remus was the dominant FAW egg parasitoid species. Endemic FAW parasitoids such as those observed in this study have great potential as part of a sustainable, cost-effective agroecological management strategy, which can be integrated with other methods to achieve effective control of FAW.