To the Editor, WHO recently listed out the top 10 threats to global health 1. The new five year strategic plan to triple billion target ensures split of 1 billion each in category of access to cover universal health, from health emergency protection and for the better enjoyment of health and well-being respectively. Among the top five or the fifth threat is the antimicrobial resistance 1 .

The patients’ vocal Parkinson’s disease (PD) changes could be identified early on, allowing for management before physically incapacitating symptoms appear. In this work, static as well as dynamic speech characteristics that are relevant to PD identification are examined. Speech changes or communication issues are among the challenges that Parkinson’s individuals may encounter. As a result, avoiding the potential consequences of speech difficulties brought on by the condition depends on getting the appropriate diagnosis early. PD patients’ speech signals change significantly from those of healthy individuals. This research presents a hybrid model utilizing improved speech signals with dynamic feature breakdown using CNN and LSTM. The proposed hybrid model employs a new, pre-trained CNN with LSTM to recognize PD in linguistic features utilizing Mel-spectrograms derived from normalized voice signal and dynamic mode decomposition. The proposed Hybrid model works in various phases, which include Noise removal, extraction of Mel-spectrograms, feature extraction using pre-trained CNN model ResNet-50, and the final stage is applied for classification. An experimental analysis was performed using the PC-GITA disease dataset. The proposed hybrid model is compared with traditional NN and well-known machine learning-based CART and SVM & XGBoost models. The accuracy level achieved in Neural Network, CART, SVM, and XGBoost models is 72.69%, 84.21%, 73.51%, and 90.81%. The results show that under these four machine approaches of tenfold cross-validation and dataset splitting without samples overlapping one individual, the proposed hybrid model achieves an accuracy of 93.51%, significantly outperforming traditional ML models utilizing static features in detecting Parkinson’s disease.

Background Monoclonal antibodies are explored for their therapeutic potential in Psoriasis. Objectives To evaluate Risankizumab in the moderate to severe psoriasis with regard to efficacy, tolerability and safety Data sources PubMed, Cochrane Central Register of Controlled Trials (CENTRAL) and clinicaltrials.gov, databases were searched for relevant RCTs. The reference lists of relevant publications were also scanned manually to identify any further studies not indexed in the searched databases. Study eligibility criteria Only RCT aiming to evaluate the role of Risankizumab in the treatment of moderate to severe psoriasis were considered eligible for this systematic review. Interventions Intervention group was patients taking Risankizumab and placebo or other monoclonal antibody was considered as control group. Study appraisal and synthesis methods Cochrane review manager 5 (RevMan) version 5.3 was used for data synthesis and meta‐analysis. Quality assessment of included randomized controlled trials was done with Cochrane Collaboration risk of bias assessment tool, version 2.0 (ROB‐2). Overall Grading of evidence for study objectives was performed with GRADE Pro GDT software. Results A total of seven studies were included in analysis with total of 1533 and 710 patients in Risankizumab and standard care groups, respectively. Statistically significant increase in percentage of individual achieving PASI90 (OR= 11.01 (95% CI = 8.67‐13.99), DLQI‐01 (OR= 6.95 (95% CI = 5.53‐8.75), sPGA‐01 (OR= 14.22 (95% CI = 11.10‐18.22); sPGA‐0 (OR= 6.39 (95% CI = 4.79‐8.54) in risankizumab group as compared to control, with high quality of evidence. Increased risk of infections with risankizumab as compared to placebo ((OR= 1.44 (95% CI = 1.13‐1.83), high quality evidence), while no difference in SAE among two groups. Strengths Analysis of all outcome data from RCTs. Conclusions In the light of evidence from systematic review on effectiveness of Risankizumab, we propose treatment with risankizumab for psoriasis patients not responding to available treatment.

Background: Diabetes mellitus is a real pandemic of the modern world and the incidence of the disease is increasing at a tremendous rate with a number of complications involving major systems of the human body. The renin angiotensin system (RAS) is considered to be involved in most of the pathological processes that result in diabetic nephropathy and retinopathy. Aim: The study was designed to evaluate and compare effects of ramipril (angiotensin-converting enzyme inhibitor-ACEI) and telmisartan (angiotensin II receptor blocker - ARBs) combinations on the progression of retinopathy and nephropathy in the streptozotocin (STZ) induced diabetic model. Materials and Methods: Diabetic state in rats was induced by chemical method using STZ 55 mg/kg intraperitoneally. Diabetic renal tubulopathy and interstitial inflammatory changes were done. Diabetic retinopathy manifested in the form of vacuolar changes in the inner plexiform and the ganglionic layers of the retina was observed. Results: Treatments with ACEI and ARBs reduced the incidence of the occurrence of cataract. The effect of combinational drugs of ACEI (ramipril) and AT1 receptor blocker (Telmisartan) was evaluated. The drugs used in combinations showed improvement in the histopathological and biochemical changes of the diabetic animals, both for the retina and kidney. Conclusion: The efficacy of the drugs suggests a pivotal role of the local RAS system in the pathogenesis of tubulopathy in the kidney and neuronal damage in the retina of the diabetic animals.

Indian Journal of Community Medicine, the official organ of the Indian Association of Preventive and Social Medicine (IAPSM), India