Development of a machine learning-based Parkinson's disease prediction system through Ayurvedic dosha analysis

The development of a machine learning (ML) based prediction model for Parkinson's disease (PD) using Ayurvedic literature is very rare in practice. In modern era of digitization and artificial intelligence this lack leads us for developing a significant and useful predictive model for PD in light of Ayurveda. As in contemporary Ayurvedic literature, PD has not been fully classified according to all of its motor and non-motor symptoms, with the exception of Kampavata or tremor, one of the cardinal motor symptoms of PD, we have taken the help of MDS-UPDRS-II and MDS-NMSQ scaling system as an initial input for this purpose. Based on the available literature, we determined our tridosha score using these scales, which become our main inputs to the ML algorithm, along with other general health attributes such as age, sex, and BMI. We applied various ML algorithms and ranked our best ML model based on their performance. For training and testing purposes, we used the Fox Insight dataset with n = 80,916 records including PD and control. Finally, we found that Kernel-SVM, SVM, Logistics Regression (LR), and XGBoost are our four most accurate algorithms, with an accuracy more than 92.5% with no dimensionality reduction applied. Here we chose the LR model as our best ML model, depending on the lower false positive rate of 0.045 with an accuracy of 92.6%. The designed LR model is statistically significant with χ2(6) = 70703.137, p =0.000. The LR coefficient was also calculated for probability analysis and future implementation of digital Ayurveda-based PD prediction applications

Diarylidene-N-Methyl-4-Piperidone and Spirobibenzopyran Curcumin Analogues as Antioxidant and Anti-Inflammatory Pharmacophores

There is a significant need for new small molecule anti-inflammatory compounds. Curcumin, a small molecule natural product from the Turmeric (Curcuma longa) plant, has well-known anti-oxidant properties, resulting from its radical scavenging ability and inhibition of inflammation-associated factors. However, its lack of solubility, instability, and poor bioavailability and biodistribution characteristics are an impediment to its use. To circumvent these issues while retaining curcumin’s biological activity, we synthesized twenty-one diarylidene-N-methyl-4-piperidones (DANMPs), four diheteroarylidene-N-methyl-4-piperidones (DHANMPs), and five spirobibenzopyran (SBP) derivatives. All were screened in terms of anti-oxidant activity via a cell-free 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay and for drug-like properties in silico. In the former, some compounds possessed improved radical scavenging behavior versus ascorbic acid, which was used as a benchmark. Conformity to simulated Lipinski’s parameters and Absorption, Distribution, Metabolism, and Excretion (ADME) studies indicated the DANMPs, DHANMPs, and SBPs to be potentially useful compounds. A subset of molecules was investigated in terms of their aqueous solubilities, which were significantly improved compared to that of curcumin. In vitro assessments of the cellular and anti-inflammatory effects of these compounds were conducted using RAW264.7 macrophages. RT-PCR and Griess assays were used to evaluate the presence of inflammatory/activated (M1) markers and production of nitric oxide (NO) species, which are associated with inflammation, respectively. While the compounds did not affect non-stimulated (naïve) macrophages, they did reduce levels of markers and NO to extents similar to or better than curcumin in inflamed cells. Our results indicate that these pharmacophores possess anti-inflammatory properties and can be used as curcumin-substitutes with improved characteristics. Further investigation into their mechanisms of action and potential use in the treatment of inflammatory diseases is merited

Evaluation of a self-help intervention to promote the health and wellbeing of marginalised people including those living with leprosy in Nepal : a prospective, observational, cluster-based, cohort study with controls

People affected by leprosy are at increased risk of ulcers from peripheral nerve damage. This in turn can lead to visible impairments, stigmatisation and economic marginalisation. Health care providers suggest that patients should be empowered to self-manage their condition to improve outcomes and reduce reliance on services. Self-care involves carrying out personal care tasks with the aim of preventing disabilities or preventing further deterioration. Self-help, on the other hand, addresses the wider psychological, social and economic implications of leprosy and incorporates, for example, skills training and microfinance schemes. The aim of this study, known as SHERPA (Self-Help Evaluation for lepRosy and other conditions in NePAl) is to evaluate a service intervention called Integrated Mobilization of People for Active Community Transformation (IMPACT) designed to encourage both self-care and self-help in marginalised people including those affected by leprosy. A mixed-method evaluation study in Province 5, Nepal comprising two parts. First, a prospective, cluster-based, non-randomised controlled study to evaluate the effectiveness of self-help groups on ulcer metrics (people affected by leprosy only) and on four generic outcome measures (all participants) - generic health status, wellbeing, social integration and household economic performance. Second, a qualitative study to examine the implementation and fidelity of the intervention. This research will provide information on the effectiveness of combined self-help and self-care groups, on quality of life, social integration and economic wellbeing for people living with leprosy, disability or who are socially and economically marginalised in low- and middle- income countries

Self-Exfoliated Guanidinium-Based Ionic Covalent Organic Nanosheets (iCONs)

Covalent organic nanosheets (CONs) have emerged as functional two-dimensional materials for versatile applications. Although π–π stacking between layers, hydrolytic instability, possible restacking prevents their exfoliation on to few thin layered CONs from crystalline porous polymers. We anticipated rational designing of a structure by intrinsic ionic linker could be the solution to produce self-exfoliated CONs without external stimuli. In an attempt to address this issue, we have synthesized three self-exfoliated guanidinium halide based ionic covalent organic nanosheets (iCONs) with antimicrobial property. Self-exfoliation phenomenon has been supported by molecular dynamics (MD) simulation as well. Intrinsic ionic guanidinium unit plays the pivotal role for both self-exfoliation and antibacterial property against both Gram-positive and Gram-negative bacteria. Using such iCONs, we have devised a mixed matrix membrane which could be useful for antimicrobial coatings with plausible medical benefits

Self-Exfoliated Guanidinium-Based Ionic Covalent Organic Nanosheets (iCONs)

Covalent organic nanosheets (CONs) have emerged as functional two-dimensional materials for versatile applications. Although π–π stacking between layers, hydrolytic instability, possible restacking prevents their exfoliation on to few thin layered CONs from crystalline porous polymers. We anticipated rational designing of a structure by intrinsic ionic linker could be the solution to produce self-exfoliated CONs without external stimuli. In an attempt to address this issue, we have synthesized three self-exfoliated guanidinium halide based ionic covalent organic nanosheets (iCONs) with antimicrobial property. Self-exfoliation phenomenon has been supported by molecular dynamics (MD) simulation as well. Intrinsic ionic guanidinium unit plays the pivotal role for both self-exfoliation and antibacterial property against both Gram-positive and Gram-negative bacteria. Using such iCONs, we have devised a mixed matrix membrane which could be useful for antimicrobial coatings with plausible medical benefits

Self-Exfoliated Guanidinium-Based Ionic Covalent Organic Nanosheets (iCONs)

Covalent organic nanosheets (CONs) have emerged as functional two-dimensional materials for versatile applications. Although π–π stacking between layers, hydrolytic instability, possible restacking prevents their exfoliation on to few thin layered CONs from crystalline porous polymers. We anticipated rational designing of a structure by intrinsic ionic linker could be the solution to produce self-exfoliated CONs without external stimuli. In an attempt to address this issue, we have synthesized three self-exfoliated guanidinium halide based ionic covalent organic nanosheets (iCONs) with antimicrobial property. Self-exfoliation phenomenon has been supported by molecular dynamics (MD) simulation as well. Intrinsic ionic guanidinium unit plays the pivotal role for both self-exfoliation and antibacterial property against both Gram-positive and Gram-negative bacteria. Using such iCONs, we have devised a mixed matrix membrane which could be useful for antimicrobial coatings with plausible medical benefits

Self-Exfoliated Guanidinium-Based Ionic Covalent Organic Nanosheets (iCONs)

Covalent organic nanosheets (CONs) have emerged as functional two-dimensional materials for versatile applications. Although π–π stacking between layers, hydrolytic instability, possible restacking prevents their exfoliation on to few thin layered CONs from crystalline porous polymers. We anticipated rational designing of a structure by intrinsic ionic linker could be the solution to produce self-exfoliated CONs without external stimuli. In an attempt to address this issue, we have synthesized three self-exfoliated guanidinium halide based ionic covalent organic nanosheets (iCONs) with antimicrobial property. Self-exfoliation phenomenon has been supported by molecular dynamics (MD) simulation as well. Intrinsic ionic guanidinium unit plays the pivotal role for both self-exfoliation and antibacterial property against both Gram-positive and Gram-negative bacteria. Using such iCONs, we have devised a mixed matrix membrane which could be useful for antimicrobial coatings with plausible medical benefits

Estimation of tuberculosis incidence at subnational level using three methods to monitor progress towards ending TB in India, 2015–2020

Objectives We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India.Design A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data.Setting National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status.Participants Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district.Outcome measures We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015.Results The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra.Conclusion TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020