Search

Vipul Vilas Wagh,1 Tanvi Kottat,1 Suchita Agrawal,2 Shruti Purohit,2 Tejaswini Arun Pachpor,3,4 Leelavati Narlikar,5 Vasudeo Paralikar,2 Satyajeet Pramod Khare1 1Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, MH, India; 2Psychiatry Unit, KEM Hospital Research Centre, Pune, MH, India; 3Department of Biosciences and Technology, School of Science and Environment Studies, Dr. Vishwanath Karad MIT World Peace University, Pune, MH, India; 4Department of Biotechnology, MES Abasaheb Garware College, Pune, MH, India; 5Department of Data Science, Indian Institute of Science Education and Research, Pune, MH, IndiaCorrespondence: Vasudeo Paralikar; Satyajeet Pramod Khare, Email paralikarv2010@gmail.com; satyajeetkhare@gmail.comIntroduction: Stigma contributes to a significant part of the burden of schizophrenia (SCZ), therefore reducing false positives from the diagnosis would be liberating for the individuals with SCZ and desirable for the clinicians. The stigmatization associated with schizophrenia advocates the need for high-precision diagnosis. In this study, we present an ensemble learning-based approach for high-precision diagnosis of SCZ using peripheral blood gene expression profiles.Methodology: The machine learning (ML) models, support vector machines (SVM), and prediction analysis for microarrays (PAM) were developed using differentially expressed genes (DEGs) as features. The SCZ samples were classified based on a voting ensemble classifier of SVM and PAM. Further, microarray-based learning was used to classify RNA sequencing (RNA-Seq) samples from our case-control study (Pune-SCZ) to assess cross-platform compatibility.Results: Ensemble learning using ML models resulted in a significantly higher precision of 80.41% (SD: 0.04) when compared to the individual models (SVM-radial: 71.69%, SD: 0.04 and PAM 77.20%, SD: 0.02). The RNA sequencing samples from our case-control study (Pune-SCZ) resulted in a moderate precision (59.92%, SD: 0.05). The feature genes used for model building were enriched for biological processes such as response to stress, regulation of the immune system, and metabolism of organic nitrogen compounds. The network analysis identified RBX1, CUL4B, DDB1, PRPF19, and COPS4 as hub genes.Conclusion: In summary, this study developed robust models for higher diagnostic precision in psychiatric disorders. Future efforts will be directed towards multi-omic integration and developing “explainable” diagnostic models. Keywords: Schizophrenia, peripheral blood, gene expression, machine learning, ensemble learning

Introduction: SARS-COV-2 infection (COVID-19) may be associated with wide range of bacterial and fungal infections. Mucormycosis is a common and potentially life threatening opportunistic fungal infection responsible for morbidity and mortality. Many factors like diabetes mellitus, hypertension and corticosteroid therapy might have been a role in the immunocompromised state of the patients. The aim of present study was to know the predisposing factors and role of histopathology in diagnosis and assessing the prognosis of post COVID-19 mucormycosis cases. Material and methods: It is a prospective observational study conducted in tertiary care hospital over a period of 6 months from April 2021 to September 2021. Functional endoscopic sinus surgery (FESS) and maxillectomy samples from 157 post COVID-19 mucormycosis suspected cases were studied and details regarding history of diabetes mellitus, hypertension and corticosteroid therapy were retrieved. All tissue samples were examined under H&E stain and special fungal stain (PAS). Results: On histopathological examination, out of total 157 cases, 94 cases were found to be positive for mucormycosis. Of these 94 cases, 63 were males and 31 were females. Age range was from 23 to 75 years. 5 cases showed mixed mucormycosis and aspergillosis infection. Also out of 94 post COVID mucormycosis cases, 72 were diabetic, 21 were hypertensive and 68 had a history of corticosteroid intake for treatment of COVID-19 infection. Conclusion: Histopathology plays a pivotal role in accurate diagnosis and assessing the severity and invasiveness of mucormycosis. Diabetes mellitus and corticosteroid use are the important associated factors.

Background: The present study was undertaken to study the histopathological features of leprosy in skin punch biopsies and to categories them in to various type based on microscopy and bacterial index. The aim of study was to know the role of histopathology in diagnosis of Hansen’s disease and to study the clinicohistopathological correlations of suspected cases of Hansen’s disease. Materials and methods: A retrospective hospital-based study of clinically diagnosed leprosy cases was conducted over a period of one year (April 2021 to March 2022). Lesional skin biopsies obtained were fixed, processed and stained with Haematoxylin and Eosin (H&E) followed by Fite-Faraco staining. The lesions were classified on microscopy as per Ridley-Jopling classification. Results: 63 Skin biopsies were obtained from patients with age range of 14-72 years. Highest incidence was in age group of 31 – 50 years. There was male predominance with male to female ratio of 2:1. Clinically borderline Hansen’s (BB) (25.40%) was the most frequent subtype observed followed by borderline lepromatous (BLH) (19.04%) and lepromatous Hansen’s (LL) (19.04%). On histopathology we found tuberculoid Hansen’s (TT) (28.57%) was the most frequently observed subtype followed by borderline tuberculoid Hansen’s (BT) (19.04%). Fite stain revealed lepromatous bacilli in all cases of LL, BL, histoid and indeterminate Hansen’s; whereas bacilli could be demonstrated in six cases of BB, eight cases of BT and two cases of TT. Conclusion: Early diagnosis of leprosy is clinically difficult as patient present in different clinicopathological form, depending on host immune status. Therefore combined clinical, histopathological and bacteriological features are required for accurate diagnosis and classification.

Ranju Pokharel,1 Sudha Agrawal,1 Prajwal Pandey,1 Madhab Lamsal2 1Department of Dermatology and Venereology, B.P Koirala Institute of Health Sciences, Dharan, Nepal; 2Department of Biochemistry, B.P Koirala Institute of Health Sciences, Dharan, NepalCorrespondence: Ranju Pokharel, Junior Resident, Department of Dermatology and Venereology, B.P. Koirala Institute of Health Sciences, Dharan, Nepal, Tel +9779860660852, Email ranjupokharel.rp@gmail.comBackground: Chronic plaque psoriasis is a chronic inflammatory skin disorder. Vitamin D has been shown to have effects on keratinocyte differentiation as well as immune regulation in the skin.Objective: The main objective of this study was to assess the 25hydroxyvitamin D [25 (OH) D] level in patients with psoriasis in comparison with healthy control subjects.Materials and Methods: This case–control study included 180 persons (120 cases and 60 age- and sex-matched control subjects) from outpatient department of BPKIHS, a tertiary care hospital in eastern Nepal. Severity of psoriatic skin lesions was assessed using psoriasis area severity index (PASI) scoring. Serum vitamin D level was assessed by chemiluminescent immunoassay.Results: The mean serum 25(OH) D levels in psoriatic patients and controls were 19.57 ± 6.85 ng/mL and 23.63 ± 6.40 ng/mL, respectively. The difference was statistically significant even after adjusting for confounding factors in a multivariate analysis (aOR 2.929, 95% CI 1.376– 6.230). Low serum 25(OH) D levels were negatively associated with the severity of disease (r= − 0.628, P= 0.01).Conclusion: Serum 25(OH) D levels are significantly lower in psoriatic patients than in healthy control subjects. Deficiency of serum 25(OH) D was associated with severity of disease with an inverse relationship with PASI score.Keywords: psoriasis, psoriasis area severity index, 25hydroxyvitamin vitamin D

Dendritic cells (DCs) are critical antigen-presenting cells which are the initiators and regulators of the immune response. Numerous studies support the idea that dietary sugars influence DC functions. Increased consumption of fructose has been thought to be the leading cause of metabolic disorders. Although evidence supports their association with immune dysfunction, the specific mechanisms are not well understood. Fructose is one of the main dietary sugars in our diet. Therefore, here we compared the effect of fructose and glucose on the functions of human DCs. High levels of D-fructose compared to D-glucose led to activation of DCs in vitro by promoting interleukin (IL)-6 and IL-1β production. Moreover, fructose exposed DCs also induced interferon (IFN)-γ secretion from T cells. Proinflammatory response of DCs in high fructose environment was found to be independent of the major known metabolic regulators or glycolytic control. Instead, DC activation on acute exposure to fructose was via activation of receptor for advanced glycation end product (RAGE) in response to increased accumulation of advanced glycation end products (AGE). However, chronic exposure of DCs to high fructose environment induced a shift towards glycolysis compared to glucose cultured DCs. Further investigations revealed that the AGEs formed by fructose induced increased levels of inflammatory cytokines in DCs compared to AGEs from glucose. In summary, understanding the link between metabolic changes and fructose-induced DC activation compared to glucose has broad implications for immune dysfunction associated with metabolic disorders.