Ethno-medicinal use of monitor lizard Varanus bengalensis (Daudin, 1802) by the ‘Adi’ tribe at East Siang, Arunachal Pradesh

749-753A recent visit to the remote villages of East Siang District, Arunachal Pradesh, revealed a unique medicinal approach practiced by the Adi tribe (earlier Abor tribe) using monitor lizard tails. Following reports of being a traditional medicine for humans, this case study emphasizes on the administration pattern to treat their livestock, veterinary purposes by the indigenous tribe of Arunachal Pradesh. The use of animal parts in traditional medicines negatively impacts and contributes to the overexploitation of wild animals for meat and remedial purposes. We raise our concerns of wildlife being harvested by the local communities for such unscientific use as a traditional medicine which harms species survival and a challenge for wildlife law enforcement

Ethno-medicinal use of monitor lizard Varanus bengalensis (Daudin, 1802) by the ‘Adi’ tribe at East Siang, Arunachal Pradesh

A recent visit to the remote villages of East Siang District, Arunachal Pradesh, revealed a unique medicinal approach practiced by the Adi tribe (earlier Abor tribe) using monitor lizard tails. Following reports of being a traditional medicine for humans, this case study emphasizes on the administration pattern to treat their livestock, veterinary purposes by the indigenous tribe of Arunachal Pradesh. The use of animal parts in traditional medicines negatively impacts and contributes to the overexploitation of wild animals for meat and remedial purposes. We raise our concerns of wildlife being harvested by the local communities for such unscientific use as a traditional medicine which harms species survival and a challenge for wildlife law enforcement

Treatment of W. bancrofti (Wb) in HIV/Wb Coinfections in South India

Background: The disease course of human immunodeficiency virus (HIV) is often altered by existing or newly acquired coincident infections. Methodology/Principal Findings: To assess the influence of pre-existing Wuchereria bancrofti infection on HIV progression, we performed a case-controlled treatment study of HIV positive individuals with (FIL+) or without (FIL-) W. bancrofti infection. Twenty-eight HIV+/FIL+ and 51 matched HIV+/FIL- subjects were treated with a single dose of diethylcarbamazine and albendazole (DEC/Alb) and followed for a year at regular intervals. Sixteen of the HIV+/FIL+ subjects (54%) and 28 of the HIV+/FIL- controls (57%) were on antiretroviral therapy (ART) during the study. Following treatment, no differences were noted in clinical outcomes between the 2 groups. There also was no significant difference between the groups in the HIV viral load at 12 months as a percentage of baseline viral load (HIV+/FIL+ group had on average 0.97 times the response of the HIV+/FIL- group, 95% CI 0.88, 1.07) between the groups. Furthermore, there were no significant differences found in either the change in viral load at 1, 3, or 6 months or in the change in CD4 count at 3, 6, or 12 months between the 2 groups. Conclusions/Significance: We were unable to find a significant effect of W. bancrofti infection or its treatment on HIV clinical course or surrogate markers of HIV disease progression though we recognized that our study was limited by the smaller than predicted sample size and by the use of ART in half of the patients. Treatment of W. bancrofti coinfection in HIV positive subjects (as is usual in mass drug administration campaigns) did not represent an increased risk to the subjects, and should therefore be considered for PLWHA living in W. bancrofti endemic areas

Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors

Wheat dominates the Australian grain production market and accounts for 10–15% of the world’s 100 million tonnes annual global wheat trade. Accurate wheat yield prediction is critical to satisfying local consumption and increasing exports regionally and globally to meet human food security. This paper incorporates remote satellite-based information in a wheat-growing region in South Australia to estimate the yield by integrating the kernel ridge regression (KRR) method coupled with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the grey wolf optimisation (GWO). The hybrid model, ‘GWO-CEEMDAN-KRR,’ employing an initial pool of 23 different satellite-based predictors, is seen to outperform all the benchmark models and all the feature selection (ant colony, atom search, and particle swarm optimisation) methods that are implemented using a set of carefully screened satellite variables and a feature decomposition or CEEMDAN approach. A suite of statistical metrics and infographics comparing the predicted and measured yield shows a model prediction error that can be reduced by ~20% by employing the proposed GWO-CEEMDAN-KRR model. With the metrics verifying the accuracy of simulations, we also show that it is possible to optimise the wheat yield to achieve agricultural profits by quantifying and including the effects of satellite variables on potential yield. With further improvements in the proposed methodology, the GWO-CEEMDAN-KRR model can be adopted in agricultural yield simulation that requires remote sensing data to establish the relationships between crop health, yield, and other productivity features to support precision agriculture

DNA barcodes and ethnomedicinal use of Sharpnose guitarfish Glaucostegus granulatus by the locals at Keylong, Lahaul and Spiti, Himachal Pradesh

Illegal trade of fishes is common and has been in practice since ages for the support of livelihood and as dietary supplements. However, several species are protected in the Wildlife (Protection) Act, 1972 of India and their trade is restricted under CITES. In this article, we report trade of Sharpnose guitarfish (Glaucostegus granulatus) for the ethnomedicinal remedy, identified using DNA barcoding in the Keylong district of Lahaul and Spiti, Himachal Pradesh. This study provides the first DNA barcode of Sharpnose guitarfish. In order to handle wildlife offense cases we emphasize that a large reference database for other fishes in trade is needed

Correlates of HIV and malaria co-infection in Southern India

Abstract Background Malaria and HIV co-infection adversely impact the outcome of both diseases and previous studies have mostly focused on falciparum malaria. Plasmodium vivax contributes to almost half of the malaria cases in India, but the disease burden of HIV and P. vivax co-infection is unclear. Methods HIV-infected subjects (n=460) were randomly selected from the 4,611 individuals seen at a Voluntary Counseling and Testing Center in Chennai, India between Jan 2 to Dec 31 2008. Malaria testing was performed on stored plasma samples by nested PCR using both genus-specific and species-specific primers and immunochromatography-based rapid diagnostic test for detecting antibodies against Plasmodium falciparum and P. vivax. Results Recent malaria co-infection, defined by the presence of antibodies, was detected in 9.8% (45/460) participants. Plasmodium vivax accounted for majority of the infections (60%) followed by P. falciparum (27%) and mixed infections (13%). Individuals with HIV and malaria co-infection were more likely to be men (p=0.01). Between those with and without malaria, there was no difference in age (p=0.14), CD4+ T-cell counts (p=0.19) or proportion CD4+ T-cell below 200/mL (p=0.51). Conclusions Retrospective testing of stored plasma samples for malaria antibodies can facilitate identification of populations with high rates of co-infection, and in this southern India HIV-infected cohort there was a considerable burden of malaria co-infection, predominantly due to P. vivax. However, the rate of P. falciparum infection was more than 6-fold higher among HIV-infected individuals than what would be expected in the general population in the region. Interestingly, individuals co-infected with malaria and HIV were not more likely to be immunosuppressed than individuals with HIV infection alone

Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables

Crop yield forecasting is critical for enhancing food security and ensuring an appropriate food supply. It is critical to complete this activity with high precision at the regional and national levels to facilitate speedy decision-making. Tea is a big cash crop that contributes significantly to economic development, with a market of USD 200 billion in 2020 that is expected to reach over USD 318 billion by 2025. As a developing country, Bangladesh can be a greater part of this industry and increase its exports through its tea yield and production with favorable climatic features and land quality. Regrettably, the tea yield in Bangladesh has not increased significantly since 2008 like many other countries, despite having suitable climatic and land conditions, which is why quantifying the yield is imperative. This study developed a novel spatiotemporal hybrid DRS-RF model with a dragonfly optimization (DR) algorithm and support vector regression (S) as a feature selection approach. This study used satellite-derived hydro-meteorological variables between 1981 and 2020 from twenty stations across Bangladesh to address the spatiotemporal dependency of the predictor variables for the tea yield (Y). The results illustrated that the proposed DRS-RF hybrid model improved tea yield forecasting over other standalone machine learning approaches, with the least relative error value (11%). This study indicates that integrating the random forest model with the dragonfly algorithm and SVR-based feature selection improves prediction performance. This hybrid approach can help combat food risk and management for other countries

Consort diagram.

<p>Consort diagram.</p

HIV viral load by over time by individual.

<p>HIV VL at baseline and 1 year in HIV+ /FIL+ individuals (<b>A</b>) and HIV+/FIL- individuals (<b>B</b>).</p

CD4 count and viral load comparisons at baseline and 1 year.

<p>Comparison of CD4 and viral load (VL) at baseline (<b>A</b> CD4 [count/dL]), <b>B</b> log VL [log₁₀ RNA Copies]) and at 1 year (<b>C</b> CD4 count, <b>D</b> log VL) between HIV+/FIL+ cases and HIV+/FIL- controls.</p