Search

Developed countries have substantial investments in renewable energy currently, particularly Photovoltaics (PV), for achieving net-zero emissions. But PV generation is highly volatile and hence achieving supply-demand balance is challenging. Robust forecasting models will help PV integration and penetration into the grid, making sure that there is an adequate supply to match the demand, ensuring reliability and stability of power systems. In this paper, a deep learning model is developed for PV generation multistep forecasting using a small subset of weather variables with a 15-minute resolution, with very low computation time. The forecasts very closely align with the actual generation, with a Normalized Mean Absolute Error (nMAE) of 0.04, much less than 1 kWh in terms of error in forecast generation. Direct and multioutput forecasting are combined here. Comparisons with Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) show performance improvement, by ∼15% compared to LSTM and ∼17% compared to GRU in terms of average nMAE. The model can be used in urban environments for short term forecasting. Also, if an accurate forecast is available, PV asset owners can plan their generation better when they export power back into the grid, make better bids in the energy markets, increase their revenues and eventually increase the share of renewables in the energy market.

Background: A staggering 85% of the global population resides in low- and middle-income countries (LAMICs). India stands as an exemplary pioneer in the realm of mental health initiatives among LAMICs, having launched its National Mental Health Program in 1982. It is imperative to effectively evaluate mental health systems periodically to cultivate a dynamic learning model sustained through continuous feedback from mental healthcare structures and processes. Materials and Methods: The National Mental Health Survey (NMHS) embarked on the Mental Health Systems Assessment (MHSA) in 12 representative Indian states, following a pilot program that contextually adapted the World Health Organization's Assessment Instrument for Mental Health Systems. The methodology involved data collection from various sources and interviews with key stakeholders, yielding a set of 15 quantitative, 5 morbidity, and 10 qualitative indicators, which were employed to encapsulate the functional status of mental health systems within the surveyed states by using a scorecard framework. Results: The NMHS MHSA for the year 2015–16 unveiled an array of indices, and the resultant scorecard succinctly encapsulated the outcomes of the systems' evaluation across the 12 surveyed states in India. Significantly, the findings revealed considerable interstate disparities, with some states such as Gujarat and Kerala emerging as frontrunners in the evaluation among the surveyed states. Nevertheless, notable gaps were identified in several domains within the assessed mental health systems. Conclusion: MHSA, as conducted within the framework of NMHS, emerges as a dependable, valid, and holistic mechanism for documenting mental health systems in India. However, this process necessitates periodic iterations to serve as critical indicators guiding the national mental health agenda, including policies, programs, and their impact evaluation.

Background: Common mental disorders (CMDs) have a higher prevalence among women in their reproductive age (WRA) compared to the general population. Large Indian epidemiological studies focusing on the prevalence and socioeconomic correlates of CMDs among WRA are lacking. The associated disability and treatment gap particularly in the women population is unknown. Aim: To estimate the current prevalence, correlates, disability, socioeconomic impact, and treatment gap of CMDs among WRA from a nationally representative sample from India. Materials and Methods: The National Mental Health Survey of India 2016 is a multisite nationwide household survey conducted across India using a uniform methodology. Overall, 39,532 adults were surveyed with a response rate of 88%. The diagnosis was based on Mini International Neuropsychiatric Interview 6.0.0. CMDs among WRA (18-49 years) for this secondary analysis included depression and anxiety disorders. Results: The prevalence of CMDs among WRA in India was 5.83%. Two important risk factors for CMDs included being divorced and living in the urban metro. Nearly 70% of women reported disabilities of varying severity. The overall treatment gap was around 82% (urban nonmetro > metro > rural population). On average, the cost of treatment of CMDs was ₹ 2,000 per month. Conclusion: CMDs are prevalent among WRA groups with significant disabilities and treatment gaps in India. The disability and treatment gap associated with CMDs among WRA can be handled by integrating mental health into general medical/obstetric care.

Introduction: Schizophrenia spectrum disorders represent a significant global health concern, contributing significantly to the global burden of disease. The National Mental Health Survey (NMHS) of India, conducted between 2015 and 2016, investigated the prevalence and epidemiological correlates of schizophrenia spectrum disorders in India. Materials and Methods: The NMHS conducted a population-based cross-sectional study in 12 Indian states from 2015 to 2016, encompassing 34,802 adults. The overall study design of the NMHS was a multistage, stratified, random cluster sampling technique, incorporating random selection based on probability proportion to size at each stage. The Mini-International Neuropsychiatric Interview 6.0 was used for psychiatric diagnoses, disability was assessed using Sheehan's disability scale, and the illness-related socioeconomic impact was assessed using a questionnaire based on the World Health Organization Disability Assessment Schedule 2.0. Firth penalized logistic regression was employed to understand the correlates of current schizophrenia spectrum disorder. Results: The study found a lifetime prevalence of schizophrenia spectrum disorders at 1.41%, with a current prevalence of 0.42%. A substantial treatment gap of 72% existed for current cases, rising to 83.3% in urban non-metro areas. The penalized logistic regression revealed that the age group category of 30–49 years, unemployed status, and lower education level had higher odds of association with schizophrenia spectrum disorders. Conclusion: The primary finding of this study is a lifetime prevalence of 1.41%, a current prevalence of 0.42%, and a substantial treatment gap of 72%. Addressing this treatment gap and holistic intervention is crucial for reducing the socioeconomic impact of this disorder. Strengthening the National Mental Health Program and implementing community-based rehabilitation are essential first steps in this direction.

Introduction: Generalized anxiety disorder (GAD) is one of the common anxiety disorders leading to impairment and burden. However, GAD remains the least studied anxiety disorder. There is a need for nationally representative epidemiological data of GAD to understand the current burden and plan the mental health policies and programs to attain their unmet needs. Hence, this study focuses on epidemiology, socio-demographic correlates, disability, and treatment gap of GAD from India's National Mental Health Survey (NMHS) 2016. Materials and Methods: NMHS 2016 was a nationally representative epidemiological survey of adult respondents from 12 states of India. NMHS is a multi-stage, stratified, random cluster sampling with random selection based on probability proportional to size at each stage. The Mini-International Neuropsychiatric Interview 6.0.0 used to diagnose psychiatric disorders. Sheehan disability scale was used to assess the disability. The current weighted prevalence of GAD was estimated. Association between GAD and socio-demographic factors was done using Firth's penalized logistic regression. The treatment gap and disability in GAD also calculated. Results: The current weighted prevalence of GAD is 0.57%. The male gender and higher education groups have significantly lesser odds with current GAD. Urban metro and the married group have significantly higher odds with current GAD. The most common comorbid psychiatric disorders are depression (15.8%) followed by agoraphobia (9.4%). Among respondents with current GAD in the past 6 months across three domains, around 2/5th has mild and moderate disability, 1/10th has a severe disability, and 1/20th has an extreme disability. The overall treatment gap of current GAD is 75.7%. Conclusion: NMHS 2016 has provided valuable insights into the epidemiology and burden of GAD among the general population. The available findings provide a glimpse of the current scenario in GAD to aid policymakers in targeting interventions.

Background. Metabolic dysfunction-associated steatohepatitis (MASH) has become the leading cause of chronic liver disease, but there has been no approved pharmacotherapy to date. Methods. We used a network analysis approach to delineate protein-protein interactions that contribute to the transition from steatosis to MASH, in order to identify and target this transition as a potential pharmacotherapeutic strategy. Acyl-CoA thioesterase 1 (ACOT1) was identified as a critical node in the protein-protein interaction (PPI) network of the transition from steatosis to MASH in patient samples. ACOT1 overexpression and silencing effects were tested in vivo on C57BL/6 mice exposed to high-fat diet (HFD) and inoculated with an adenoviral system to modulate ACOT1 expression. Transcriptomic and untargeted lipidomic profiles were performed on the mouse livers. Results. ACOT1 expression was 3-fold higher in MASH as compared to steatosis. In patient samples, ACOT1 was significantly correlated with the severity of MASH as reflected by the nonalcoholic fatty liver disease score. Experimental validation showed that downregulation of ACOT1 resulted in decreased lipid accumulation and prevention of MASH in vivo. Conversely, upregulation of ACOT1 via an adenoviral vector resulted in development of MASH, whereas control mice only developed steatosis. Lipidomic analysis revealed glycerophospholipids to be especially abundant in MASH accelerated by ACOT1 upregulation. Conclusion. These results suggest that ACOT1 contributes to the transition from steatosis to MASH through modulation of glycerophospholipid accumulation and its potential as a novel therapeutic target in MASH. This trial is registered with NCT02148471.

Background One of the most prevalent mental illnesses that chronic kidney disease CKD patients undergoing haemodialysis tend to encounter is depression. Patients receiving haemodialysis have frequently experienced underdiagnosed and undertreated depression.Objectives To assess the mental health of chronic kidney disease patients mainly depression and to analyze reasons for depression among dialysis patients in Gadag district Karnataka.Methods A cross-sectional study was conducted at Government and Private hospitals of Gadag Karnataka between December 2023 to January 2024. Beck Depression Inventory-2 scale was used to assess depression and reasons for depression among CKD patients. Subsequently the statistical analysis of the gathered data was executed using SPSS version 20.0. The predetermined level of statistical significance was established at 5.Results The study included one hundred patients from a district hospital two private hospitals and four subdistrict hospitals. With a mean age of 49.94 years standard deviation 12.85 most of the patients were male 75 with the majority in the age range of 60-69 years 25. Concerningly all the haemodialysis patients suffered from depression in varying severity and as high as 62 patients reported having severe depression. Some of the factors that were found to be associated with depression included religion employment status family income f inancial difficulties fluid intake chronic pain illness that conflicts with living renal diet and sleep disturbance.Conclusion Patients with CKD are more prone to depression and this study also indicates an increased incidence of severe depression among them. The socio-demographic characteristics and factors related to the disease and treatment were associated with the prevalence of depression among the study sample. In order to improve the patientrsquos quality of life depressive symptoms need to be regularly assessed and promptly treated with psychological counselling. The socio-economic causes predisposing to mental health issues need to be addressed as a priority.

Abstract Background Chronic rhinosinusitis (CRS) is a complex inflammatory disease of the sinonasal tract. To understand this disease entity and develop targeted treatments, a reproducible animal model is paramount. Aims/objectives To optimize a murine model of eosinophilic CRS by establishing benchmark histological markers and validate its fidelity in evaluating intranasal treatments. Material and methods Forty-five Balb/c mice were included in the 7-week protocol. Experimental animals (n = 20) were induced a CRS disease state upon receiving intraperitoneal sensitization with ovalbumin (OVA), followed by intranasal OVA with Aspergillus oryzae protease. Analysis of complete blood count with differential, peripheral blood smear, and histological markers from the nasal cavity mucosa were performed. CRS mice were additionally treated with intranasal saline (n = 5) or mometasone (n = 10) and compared with control groups of untreated CRS (n = 5) and healthy (n = 5) mice after week 7. Results Histological analysis of experimental animal nasal mucosa revealed significantly higher levels of eosinophilic tissue infiltration/degranulation, hyaline droplets, Charcot–Leyden crystals, and respiratory epithelial thickness compared to healthy controls. Treatment with mometasone significantly reversed the histopathological changes observed in CRS mice. Conclusion and significance This murine model induced substantial local eosinophilic inflammation within sinonasal mucosa, that was reversible with mometasone. This model may be used to evaluate the efficacy of therapeutics designed to target CRS.

Introduction: The clinical interview (CI) based diagnosis has more validity than the structured interview schedules based diagnosis. Hence, the epidemiological studies by clinician’s evaluation would be more valuable. To date, there is no clinical epidemiological studies by psychiatrists’ CIs of the primary care patients in India, especially for substance use and psychotic disorders. Objectives: To understand the prevalence of selected psychiatric disorders among patients of primary health centers (PHCs) based on the psychiatrist’s CI. Materials and Methods: Data collected from a file review of Telepsychiatric On-Consultation Training program (2016–2018) in which 73 in-service primary care doctors are trained in live general consultation of rural PHCs of Mandya district, Karnataka, India. Results: Prevalence of the psychiatric disorders among adult primary care patients was 47.5%. The common mental disorders (CMDs) (35.2%) were most common among them, followed by substance use (9.5%) and psychotic disorders (2.6%). Discussion: This is the first clinical epidemiological study from Indian rural primary health care based on a psychiatrist’s CI. Nearly half of the primary care patients were diagnosed with psychiatric disorders. This study demonstrated the feasibility of conducting such epidemiological studies with available time and resources. This study reported a higher prevalence of psychiatric disorders in rural PHCs.

Hypogonadotropic hypogonadism is a common finding in patients who are diagnosed with a prolactinoma. It can be accompanied by the presence of other pituitary hormone deficits, including secondary adrenal insufficiency and central hypothyroidism. While the proportion of improvement in endocrine deficits over the short term is well characterized, there is not enough literature about the recovery of pituitary function over the longer term. We present the case of a 23-year-old man with a giant prolactinoma who initially presented with pituitary hemorrhage and panhypopituitarism. He underwent decompression of the pituitary tumor followed by treatment with cabergoline. Over a 9-year follow-up period, we noted that the hypogonadotropic hypogonadism resolved after 4 years and the secondary adrenal insufficiency resolved after 8 years. This case suggests that partial or complete recovery of the pituitary function is possible over the long-term even in patients with a giant prolactinoma.

The upcoming India-based Neutrino Observatory (INO) will host a 50 kton magnetized Iron Calorimeter (ICAL) to study atmospheric neutrinos. As part of its proposal, small-scale prototype detectors have been built and are in operation. The primary focus in these prototypes has been on detector characterization studies. At the same time, few physics analyses were also carried out with the cosmic muon data collected. However, due to the small size of the detectors, such analyses always relied on the assumption that the tracks were of single muons only. Consequently, multi-muon events were discarded as noisy events, reducing the physics potential. In this work, we report the development of a machine learning model to predict multi-muon events, study its efficiency and report the muon multiplicity distribution observed using cosmic muon events from the prototype detector.

Abstract Carangids are abundant and commercially important marine fish that contribute to a significant portion of the fisheries in many parts of the world. In the present study, we characterized the complete mitogenome of the Indian scad, Decapterus russelli and performed a comprehensive comparative mitogenomic analysis of the family Carangidae. The comparative mitogenomics provided valuable insights into the structure, variability, and features of the coding and non-coding regions that evolved across species over millions of years. The structural features of tRNAs revealed changes in the frequency of mismatched and wobble base pairs, which is reflected in the base composition of H and L strands. The highly conserved sequence motif of the mTERF binding site in carangids over the ~ 400 MYA of their divergence demonstrated the functional importance of these sites. The control region of carangids was characterized by the presence of discontinuous repeat units with a high rate of sequence divergence in the form of base substitutions, insertions, and deletions. The maintenance of secondary structures in the control region independent of the rapid evolution of primary structure suggested the effect of selective constraints on their maintenance. Maximum likelihood (ML) and Bayesian inference (BI) phylogeny revealed a similar topology consistent with previous taxonomic studies. The extant carangids diverged through the evolutionary events experienced during the Cretaceous, Paleogene, and Neogene periods.

Kinetic stability, defined as the rate of protein unfolding, is central to determining the functional lifetime of proteins, both in nature and in wide-ranging medical and biotechnological applications. Further, high kinetic stability is generally correlated with high resistance against chemical and thermal denaturation, as well as proteolytic degradation. Despite its significance, specific mechanisms governing kinetic stability remain largely unknown, and few studies address the rational design of kinetic stability. Here, we describe a method for designing protein kinetic stability that uses protein long-range order, absolute contact order, and simulated free energy barriers of unfolding to quantitatively analyze and predict unfolding kinetics. We analyze two β-trefoil proteins: hisactophilin, a quasi-three-fold symmetric natural protein with moderate stability, and ThreeFoil, a designed three-fold symmetric protein with extremely high kinetic stability. The quantitative analysis identifies marked differences in long-range interactions across the protein hydrophobic cores that partially account for the differences in kinetic stability. Swapping the core interactions of ThreeFoil into hisactophilin increases kinetic stability with close agreement between predicted and experimentally measured unfolding rates. These results demonstrate the predictive power of readily applied measures of protein topology for altering kinetic stability and recommend core engineering as a tractable target for rationally designing kinetic stability that may be widely applicable.

For ages, humankind was unsuccessful in accomplishing their aspirations practically, though sometimes they were able to achieve the same theoretically. However, this gap was bridged by many groundbreaking inventions. One such invention is the World Wide Web. The web, which is often described as an evolving network of networks, has constantly been moving forward since its discovery and thereby giving rise to improved applications. This review paper aims to elucidate the reader on the same. It provides a comprehensive understanding of each iteration of the web and talks about the technological advancements made considering that specific version of the web. The outcome of this review is to present the reader with a comparative analysis of all the iterations of the web based on certain chosen parameters. Furthermore, the findings of this review have been discussed from various aspects to help the reader gain a better understanding of the comparative analysis.

Despite the widely recognised impact of both digital and physical spaces as active contributors to teaching and learning processes, relatively little is known about the learning environment. Furthermore, it is time to explore the interplay between these two spaces. Therefore, we proposed employing a holistic approach to develop a new conceptual model for Designing Teaching and Learning Environments (DTALE). To do this, the paper presents first a critical review of the research literature underpinning learning environments, with a particular interest in the integration of the physical and digital spaces, to develop the DTALE model. In the second step, the DTALE model has been developed and validated by applying the model to existing cases from different contexts. Based on the study's findings, we outline the implications for theory and practice. Limitations and suggestions for future research are also included.

Understanding inclusive education challenges in India involves acknowledging the complex linguistic, cultural, religious, and caste-based diversity affecting marginalized groups. Ambiguity surrounds implementing the "inclusion" concept, necessitating critical evaluation and adaptation to align with India's unique dynamics. Despite increased enrollment (61%), concerns persist about omitting some children from inclusive education benefits, suggesting exclusivity. The 2020 National Education Policy aims for equitable opportunities, but challenges remain in implementation and access. Interchangeable terms (e.g., "inclusion" vs. "integration") and a lack of differentiation hinder progress. Robust research on classroom practices is vital to establish effective strategies, support families, and address diverse student needs. This multifaceted issue requires consideration of India-specific contexts. India's interpretation of inclusive education varies based on disability severity, and solutions should account for political, historical, and cultural contexts and the beliefs and experiences of disabled individuals.

Background: Serum prostate-specific antigen (PSA), used in prostate cancer screening, is nonspecific for cancer and is affected by age and prostate volume. More specific biomarkers could be more accurate for early detection of prostate cancer and reduce unnecessary prostate biopsies. Objective: To evaluate the association of age and prostate volume with urinary MyProstateScore (MPS) in a screened, longitudinal cohort without evidence of prostate cancer. Design, setting, and participants: The Olmsted County Study included men aged 40–79 yr who underwent biennial prostate cancer screening. PSA ≥4.0 ng/ml or abnormal rectal examination triggered prostate biopsy, and patients with cancer were excluded. The remaining men submitted urinary specimens for PCA3 and TMPRSS2:ERG testing. Outcome measurements and statistical analysis: MPS was calculated using the validated, locked model for grade group ≥2 cancer that includes serum PSA, urinary PCA3, and urinary TMPRSS2:ERG. The associations of age and volume with biomarkers were assessed in multivariable regression models. The t statistic was used to quantify the strength of associations independent of the unit of measurement, and R2 values were used to estimate the proportion of biomarker variance explained by each factor. Results and limitations: The study included 314 screened men without evidence of cancer. In multivariable models including age and volume, PCA3 score was significantly associated with age (t = 7.51; p

Many single-domain proteins are not only stable and water-soluble, but they also populate few to no intermediates during folding. This reduces interactions between partially folded proteins, misfolding, and aggregation, and makes the proteins tractable in biotechnological applications. Natural proteins fold thus, not necessarily only because their structures are well-suited for folding, but because their sequences optimize packing and fit their structures well. In contrast, folding experiments on the de novo designed Top7 suggest that it populates several intermediates. Additionally, in de novo protein design, where sequences are designed for natural and new non-natural structures, tens of sequences still need to be tested before success is achieved. Both these issues may be caused by the specific scaffolds used in design, i.e., some protein scaffolds may be more tolerant to packing perturbations and varied sequences. Here, we report a computational method for assessing the response of protein structures to packing perturbations. We then benchmark this method using designed proteins and find that it can identify scaffolds whose folding gets disrupted upon perturbing packing, leading to the population of intermediates. The method can also isolate regions of both natural and designed scaffolds that are sensitive to such perturbations and identify contacts which when present can rescue folding. Overall, this method can be used to identify protein scaffolds that are more amenable to whole protein design as well as to identify protein regions which are sensitive to perturbations and where further mutations should be avoided during protein engineering.

The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging >106 cells/day and screening >104 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.

Gender norms have been posited to impact intimate partner violence (IPV), but there is scant evidence of the longitudinal association between community-level gender norms and IPV. Using longitudinal data on 3,965 married girls surveyed in India, we fitted mixed-effects ordinal and binary logistic regression models for physical IPV intensity and occurrence of sexual IPV. We found a 26% increase in the odds that women experience frequent physical IPV per one unit increase in greater community-level equitable gender norms. We did not find an association between community-level equitable gender norms and sexual IPV. Findings suggest that the relationship between gender norms and physical and sexual IPV differs, indicating the need for tailored interventions for different types of IPV.

Glioblastoma is immunologically cold and resistant to single-agent immune-checkpoint inhibitors (ICI). Our previous study of neoadjuvant pembrolizumab in surgically-accessible recurrent glioblastoma identified a molecular signature of response to ICI and suggested that neoadjuvant pembrolizumab may improve survival. To increase the power of this observation, we enrolled an additional 25 patients with a primary endpoint of evaluating the cell cycle gene signature associated with neoadjuvant pembrolizumab and performed bulk-RNA seq on resected tumor tissue (NCT02852655). Neoadjuvant pembrolizumab was associated with suppression of cell cycle/cancer proliferation genes and upregulation of T-cell/interferon-related gene expression. This signature was unique to patients treated with neoadjuvant pembrolizumab and was an independent positive risk factor for survival. Our results demonstrate a clear pharmacodynamic effect of anti-PD1 therapy in glioblastoma and identify pathways that may mediate resistance. However, we did not confirm a survival benefit to neoadjuvant pembrolizumab in recurrent glioblastoma and our secondary endpoint of PFS-6 was 19.5% (95% CI: 9.29-41.2%) for the pooled neoadjuvant cohorts. Our new data suggests some patients may exhibit innate resistance to pre-surgical ICI and require other concomitant therapies to sensitize effectively.

The models of E-learning Readiness (ELR) are basically designed to understand the process of obtaining the basic information necessary for measuring ELR among participants. They help organizations to identify the requirements for designing, developing and implementing E-learning. These models not only help the organizations to identify the degree of ELR but also to identify the factors or areas where the organization is weak. The present study reviews the models of E-learning Readiness (ELR) with the help of a small-scale literature review on Models of ELR. The purpose of the current study was to make an analysis of the existing ELR models in the literature. The researcher visited various online databases to collect studies. In addition to that, the researcher also did a manual search in the reference list of various studies in the related field for the addition of additional studies. By following an appropriate strategy, the researchers selected 07 ELR models for the current study. The current study reveals that Technology, Skills, Attitude, resources and human resources, Infrastructure, Flexibility, Support, Pedagogy, Management, Evaluation, Continual Improvement, Culture, Budgeting, Curriculum, Awareness, Law and Regulation, Content and Policy have been used on a larger scale for the development of the ELR models. Further, majority of reviewed studies have used various statistical techniques like regression analysis, Confirmatory Factor Analysis (CFA) and Exploratory Factor Analysis (EFA) for developing the models.

Fusobacterium nucleatum is an anaerobe that is commensal to the human oral cavity. It is usually a component of periodontal plaque that is emerging as a pathogen and quickly attracting attention of the medical and research communities. It has been even discovered in bronchoalveolar lavage of some patients with lung cancer. Lemierre's syndrome (LS) is characterized as septic thrombophlebitis of the internal jugular vein, which usually begins with oropharyngeal infection that worsens and leads to inflammation of the wall of the jugular vein. This is the hallmark of the disease. However, in this case, there was no thrombophlebitis of the internal jugular vein. There is one other case presentation where it was diagnosed without the internal jugular vein involvement. Most sequelae involve infected thrombus of the vein, soft tissue inflammation, persistent bacteremia, and septic emboli, often leading to metastatic infections. Interestingly enough, in the age of SARS-COV-2, LS has also been mistaken for multisystem inflammatory syndrome in children (MIS-C).We present a previously healthy 20-year-old female college student who was transferred from her local hospital to Bristol-Myers Squibb Children's Hospital (BMSCH) at Robert Wood Johnson University Hospital for suspected LS with loculated pleural effusions and necrotizing pneumonia with lung abscess secondary to Fusobacterium nucleatum, systemic and emphysematous osteomyelitis possibly secondary to septic emboli, thrombocytopenia, and palatine tonsil and thyroid abscesses.

Background The Joint United Nations Programme on AIDS (UNAIDS) has emphasized on the incidence-prevalence ratio (IPR) and incidence-mortality ratio (IMR) to measure the progress in HIV epidemic control. In this paper, we describe the status of epidemic control in India and in various states in terms of UNAIDS’s recommended metrices. Method The National AIDS Control Programme (NACP) of India spearheads work on mathematical modelling to estimate HIV burden based on periodically conducted sentinel surveillance for providing guidance to program implementation and policymaking. Using the results of the latest round of HIV Estimations in 2019, IPR and IMR were calculated. Results National level IPR was 0.029 [0.022–0.037] in 2019 and ranged from 0.01 to 0.15 in various States and Union Territories (UTs). Corresponding Incidence-Mortality Ratio was at 0.881 [0.754–1.014] nationally and ranged between 0.20 and 12.90 across the States/UTs. Conclusions Based on UNAIDS recommended indicators for HIV epidemic control, namely IPR and IMR; national AIDS response in India appears on track. However, the program success is not uniform and significant heterogeneity as well as expanding epidemic was observed at the level of States or UTs. Reinforcing States/UTs specific and focused HIV prevention, testing and treatment initiatives may help in the attainment of 2030 Sustainable Development Goals of ending AIDS as a public health threat by 2030.