An atypical presentation of human monkeypox infection with clinicopathologic correlation.

There is growing evidence to support new modes of transmission for human monkeypox infection. As these methods are being explored, this report delineates the day-to-day clinical sequelae following the initial exposure in an HIV-positive man who had sexual intercourse with another man days preceding his infection. We describe atypical cutaneous manifestations involving widespread erythematous pustules with preceding anogenital ulcerations and concomitant bilateral inguinal lymphadenopathy. Clinicopathologic correlation is used to assist in the workup and establishing the diagnosis. Our case supports others reported in the literature that suggest sexual contact as a means of transmission. More research is needed that investigates the presence of infection in both men and women, including those who could act as carriers, to elucidate other pathways in this evolving yet evasive viral disease.

A study of neural artistic style transfer models and architectures for Indian art styles.

Neural Style Transfer (NST) has been a widely researched topic as of late enabling new forms of image manipulation. Here we perform an extensive study on NST algorithms and extend the existing methods with custom modifications for application to Indian art styles. In this paper, we aim to provide a comprehensive analysis of various methods ranging from the seminal work of Gatys et al which demonstrated the power of Convolutional Neural Networks (CNNs) in creating artistic imagery by separating and recombining image content and style, to the state of the art image-to-image translation models which use Generative Adversarial Networks (GANs) to learn the mapping between two domain of images. We observe and infer based on the results produced by the models on which one could be a more suitable approach for Indian art styles, especially Tanjore paintings which are unique compared to the Western art styles. We then propose the method which is more suitable for the domain of Indian Art style along with custom architecture which includes an enhancement and evaluation module. We then present evaluation methods, both qualitative and quantitative which includes our proposed metric, to evaluate the results produced by the model.

Positive identity development through community engagement among youth with intellectual and developmental disabilities.

BACKGROUND: Identity development in individuals with disabilities is often negatively impacted by exclusion, marginalisation, and stigma. However, meaningful opportunities for community engagement can serve as one pathway towards establishing positive identity. This pathway is further examined in the present study. METHODS: Researchers used a tiered, multi-method, qualitative methodology consisting of audio diaries, group interviews, and individual interviews with seven youth (ages 16-20) with intellectual and developmental disabilities, recruited through the Special Olympics U.S. Youth Ambassador Program. RESULTS: Participants' identities incorporated disability while simultaneously transcending the social limits of disability. Participants viewed disability as one aspect of their broader identity, shaped by leadership and engagement experiences such as those offered by the Youth Ambassador Program. CONCLUSIONS: Findings have implications for understanding identity development in youth with disabilities, the importance of community engagement and structured leadership opportunities, and the value of tailoring qualitative methodologies to the subject of the research.

Mechanistic Insights of Plant Growth Promoting Bacteria Mediated Drought and Salt Stress Tolerance in Plants for Sustainable Agriculture.

Climate change has devastating effects on plant growth and yield. During ontogenesis, plants are subjected to a variety of abiotic stresses, including drought and salinity, affecting the crop loss (20-50%) and making them vulnerable in terms of survival. These stresses lead to the excessive production of reactive oxygen species (ROS) that damage nucleic acid, proteins, and lipids. Plant growth-promoting bacteria (PGPB) have remarkable capabilities in combating drought and salinity stress and improving plant growth, which enhances the crop productivity and contributes to food security. PGPB inoculation under abiotic stresses promotes plant growth through several modes of actions, such as the production of phytohormones, 1-aminocyclopropane-1-carboxylic acid deaminase, exopolysaccharide, siderophore, hydrogen cyanide, extracellular polymeric substances, volatile organic compounds, modulate antioxidants defense machinery, and abscisic acid, thereby preventing oxidative stress. These bacteria also provide osmotic balance; maintain ion homeostasis; and induce drought and salt-responsive genes, metabolic reprogramming, provide transcriptional changes in ion transporter genes, etc. Therefore, in this review, we summarize the effects of PGPB on drought and salinity stress to mitigate its detrimental effects. Furthermore, we also discuss the mechanistic insights of PGPB towards drought and salinity stress tolerance for sustainable agriculture.

Subject-Specific Cognitive Workload Classification Using EEG-Based Functional Connectivity and Deep Learning.

Cognitive workload is a crucial factor in tasks involving dynamic decision-making and other real-time and high-risk situations. Neuroimaging techniques have long been used for estimating cognitive workload. Given the portability, cost-effectiveness and high time-resolution of EEG as compared to fMRI and other neuroimaging modalities, an efficient method of estimating an individual's workload using EEG is of paramount importance. Multiple cognitive, psychiatric and behavioral phenotypes have already been known to be linked with "functional connectivity", i.e., correlations between different brain regions. In this work, we explored the possibility of using different model-free functional connectivity metrics along with deep learning in order to efficiently classify the cognitive workload of the participants. To this end, 64-channel EEG data of 19 participants were collected while they were doing the traditional n-back task. These data (after pre-processing) were used to extract the functional connectivity features, namely Phase Transfer Entropy (PTE), Mutual Information (MI) and Phase Locking Value (PLV). These three were chosen to do a comprehensive comparison of directed and non-directed model-free functional connectivity metrics (allows faster computations). Using these features, three deep learning classifiers, namely CNN, LSTM and Conv-LSTM were used for classifying the cognitive workload as low (1-back), medium (2-back) or high (3-back). With the high inter-subject variability in EEG and cognitive workload and recent research highlighting that EEG-based functional connectivity metrics are subject-specific, subject-specific classifiers were used. Results show the state-of-the-art multi-class classification accuracy with the combination of MI with CNN at 80.87%, followed by the combination of PLV with CNN (at 75.88%) and MI with LSTM (at 71.87%). The highest subject specific performance was achieved by the combinations of PLV with Conv-LSTM, and PLV with CNN with an accuracy of 97.92%, followed by the combination of MI with CNN (at 95.83%) and MI with Conv-LSTM (at 93.75%). The results highlight the efficacy of the combination of EEG-based model-free functional connectivity metrics and deep learning in order to classify cognitive workload. The work can further be extended to explore the possibility of classifying cognitive workload in real-time, dynamic and complex real-world scenarios.

Plant-Growth-Promoting Rhizobacteria Emerging as an Effective Bioinoculant to Improve the Growth, Production, and Stress Tolerance of Vegetable Crops.

Vegetable cultivation is a promising economic activity, and vegetable consumption is important for human health due to the high nutritional content of vegetables. Vegetables are rich in vitamins, minerals, dietary fiber, and several phytochemical compounds. However, the production of vegetables is insufficient to meet the demand of the ever-increasing population. Plant-growth-promoting rhizobacteria (PGPR) facilitate the growth and production of vegetable crops by acquiring nutrients, producing phytohormones, and protecting them from various detrimental effects. In this review, we highlight well-developed and cutting-edge findings focusing on the role of a PGPR-based bioinoculant formulation in enhancing vegetable crop production. We also discuss the role of PGPR in promoting vegetable crop growth and resisting the adverse effects arising from various abiotic (drought, salinity, heat, heavy metals) and biotic (fungi, bacteria, nematodes, and insect pests) stresses.

An assessment of compliance with the provisions of Cigarettes and Other Tobacco Products Act 2003: Is Shimla a smoke-free city?

Background: . Tobacco consumption in any form is a major contributor to non-communicable diseases, and it is the leading preventable cause of death worldwide. Secondhand smoke is also harmful. To halt the smoking epidemic and protect people from second-hand smoke, the Government of India enacted the Cigarettes and Other Tobacco Products Act (COTPA) in 2003. Methods: . We ascertained compliance with the provisions of COTPA 2003 at 183 public places and 41 transport facilities of Shimla city from August 2017 to July 2018. Results: . Only 48% of public places had good compliance with the provisions of COTPA 2003. On average, a public place was found to be compliant with 7 of 10 key indicators of Section 4. Educational institutes and government offices had a higher rate of compliance compared to other places. Active smoking and signages signalling ban on smoking were observed in 17% and 95.6% of public places, respectively. Smoking aids (e.g. ashtrays) were observed at <10% of places. A designated smoking area was not seen at any public place. Conclusion: . Overall compliance of the Act was low with less than half the places having satisfactory compliance with Section 4. There is a need to raise awareness about the negative effects of smoking on health and environment and ensure strict adherence to the provisions of COTPA 2003.

Risk factors for cancer cervix among rural women of a hilly state: a case-control study.

In Himachal Pradesh, cancer cervix is a major public health problem since it ranks as the number one female cancer. A case-control study of 226 newly diagnosed, histopathologically confirmed cases of cancer cervix and equal number of matched controls was conducted at Regional Cancer Center, Himachal Pradesh during the period from July 2008 to October 2009 with the objective to study the common factors associated with cancer cervix. Univariate analysis identified 10 risk factors associated significantly with the disease. On multiple logistic regression, however, only seven risk factors were found to be associated significantly with the disease. These were: Age at birth of first child, spacing between two children, age at marriage, literacy, socioeconomic status, multiparity, and poor genital hygiene. Risk factors such as poor genital hygiene, age at birth of first child <19 years, early marriage, illiteracy, multiparity, and low socioeconomic status were highly prevalent in the study subjects and were found to be significantly associated with cancer cervix.

Modeling Effects of Rumination on Free Recall Using ACT-R.

Ruminative thinking, characterized by a recurrent focus on negative and self-related thought, is a key cognitive vulnerability marker of depression and, therefore, a key individual difference variable. This study aimed to develop a computational cognitive model of rumination focusing on the organization and retrieval of information in memory, and how these mechanisms differ in individuals prone to rumination and individuals less prone to rumination. Adaptive Control of Thought-Rational (ACT-R) was used to develop a rumination model by adding memory chunks with negative valence to the declarative memory. In addition, their strength of association was increased to simulate recurrent negative focus, thereby making it harder to disengage from. The ACT-R models were validated by comparing them against two empirical datasets containing data from control and depressed participants. Our general and ruminative models were able to recreate the benchmarks of free recall while matching the behavior exhibited by the control and the depressed participants, respectively. Our study shows that it is possible to build a computational theory of rumination that can accurately simulate the differences in free recall dynamics between control and depressed individuals. Such a model could enable a more fine-tuned investigation of underlying cognitive mechanisms of depression and potentially help to improve interventions by allowing them to more specifically target key mechanisms that instigate and maintain depression.

Hepatitis B in Trans-Himalayan Tribal Population: High Prevalence, High Pediatric Burden, Virologic Patterns, and Implications for Public Health Interventions.

Background/Aims: The prevalence of hepatitis B is higher in tribal populations, compared to non-tribal populations in India. Therefore, this study aimed to investigate the risk factors, virological and biochemical profile of patients with hepatitis B in a tribal population. Methods: This study analyzed data collected from a community-based project conducted in Spiti, Himachal Pradesh, from July 2015 to 2017. The study included adults and children inhabiting 40 cluster villages out of 82 villages in the subdivision. The blood samples were collected for liver panel, hepatitis B surface antigen (HBsAg), hepatitis B e antigen (HBeAg), Anti-HBe antibody (anti-HBe Ab) and Hepatitis B virus DNA (HBV-DNA). Results: HBsAg was positive in 23.08% of the population (968/4201), with a prevalence of 13.51% in children under 5 years of age. HBeAg positivity was seen in 22.4% of the participants, while anti-HBe Ab positivity was seen in 59.03% of the participants. HBeAg positive infection, HBeAg positive hepatitis, HBeAg negative hepatitis and HBeAg negative infection were seen in 18.06%, 1.98%, 6.17% and 74.01% of the participants, respectively. HBeAg positivity was highest in 2nd decade (40.83% vs 22% overall). Patients with HBeAg positivity exhibited higher levels of HBV DNA [1960 (IQR: 0-108) IU/ml vs 97.2 (IQR: 0-2090) IU/ml, P < 0.001] and alanine transaminase (ALT) [22.5 (IQR: 16-33) U/L vs 19 (IQR: 14-26) U/L, P = 0.003] levels compared to HBeAg negative patients. Conclusion: This study shows a high prevalence of hepatitis B in tribal population, particularly among children under 5 years of age.

Exploring medical student decisions regarding attending live lectures and using recorded lectures.

BACKGROUND: Student decisions about lecture attendance are based on anticipated effect on learning. Factors involved in decision-making, the use of recorded lectures and their effect on lecture attendance, all warrant investigation. AIM: This study was designed to identify factors in student decisions to attend live lectures, ways in which students use recorded lectures, and if their use affects live lecture attendance. METHODS: A total of 213 first (M1) and second year (M2) medical students completed a survey about lecture attendance, and rated factors related to decisions to attend live lectures and to utilize recorded lectures. Responses were analyzed overall and by class year and gender. RESULTS: M1 attended a higher percentage of live lectures than M2, while both classes used the same percentage of recorded lectures. Females attended more live lectures, and used a smaller percentage of recorded lectures. The lecturer was a key in attendance decisions. Also considered were the subject and availability of other learning materials. Students use recorded lectures as replacement for live lectures and as supplement to them. CONCLUSIONS: Lectures, both live and recorded, are important for student learning. Decisions about lecture placement in the curriculum need to be based on course content and lecturer quality.

Raw Electroencephalogram-Based Cognitive Workload Classification Using Directed and Nondirected Functional Connectivity Analysis and Deep Learning.

With the phenomenal rise in internet-of-things devices, the use of electroencephalogram (EEG) based brain-computer interfaces (BCIs) can empower individuals to control equipment with thoughts. These allow BCI to be used and pave the way for pro-active health management and the development of internet-of-medical-things architecture. However, EEG-based BCIs have low fidelity, high variance, and EEG signals are very noisy. These challenges compel researchers to design algorithms that can process big data in real-time while being robust to temporal variations and other variations in the data. Another issue in designing a passive BCI is the regular change in user's cognitive state (measured through cognitive workload). Though considerable amount of research has been conducted on this front, methods that could withstand high variability in EEG data and still reflect the neuronal dynamics of cognitive state variations are lacking and much needed in literature. In this research, we evaluate the efficacy of a combination of functional connectivity algorithms and state-of-the-art deep learning algorithms for the classification of three different levels of cognitive workload. We acquire 64-channel EEG data from 23 participants executing the n-back task at three different levels; 1-back (low-workload condition), 2-back (medium-workload condition), and 3-back (high-workload condition). We compared two different functional connectivity algorithms, namely phase transfer entropy (PTE) and mutual information (MI). PTE is a directed functional connectivity algorithm, whereas MI is non-directed. Both methods are suitable for extracting functional connectivity matrices in real-time, which could eventually be used for rapid, robust, and efficient classification. For classification, we use the recently proposed BrainNetCNN deep learning model, designed specifically to classify functional connectivity matrices. Results reveal a classification accuracy of 92.81% with MI and BrainNetCNN and a staggering 99.50% with PTE and BrainNetCNN on test data. PTE can yield a higher classification accuracy due to its robustness to linear mixing of the data and its ability to detect functional connectivity across a range of analysis lags.

Bioactive Compounds, Antioxidant, and Antibacterial Activity Against MDR and Food-Borne Pathogenic Bacteria of Psidium guajava. L Fruit During Ripening.

Psidium guajava fruits are highly appreciated for their nutrients and bioactive compounds content, which contribute to their antioxidant and antimicrobial capacities. The purpose of this study was to determine bioactive compound (phenolic, flavonoids, and carotenoid contents), antioxidant activity (DPPH, ABTS, ORAC, and FRAP), and antibacterial potential against MDR and food-borne pathogenic strains of Escherichia coli, and Staphylococcus aureus during different stages of fruit ripening.The results elucidated that ripe fruits (methanolic extract) contain the highest total phenolic, flavonoids, and carotenoid contents (417.36 ± 2.63 µg GAE/gm of FW, 711.78 ± 0.70 µg QE/gm of FW and 0.683 ± 0.06 µg/gm of FW) followed by hexane, ethyl acetate, and aqueous. Methanolic extract of the ripe fruits showed the highest antioxidant activity when measured by DPPH (61.55 ± 0.91%), FRAP (31.83 ± 0.98 mM Fe(II)/gm of FW), ORAC (17.19 ± 0.47 mM TE/ gm of FW), and ABTS (41.31 ± 0.99 µmol Trolox/gm of FW) assays. In the antibacterial assay, the ripe stage had the highest antibacterial activity against MDR and food-borne pathogenic strains of Escherichia coli, and Staphylococcus aureus. The methanolic ripe extract was found to possess maximum antibacterial activity ZOI, MIC, and IC50 18.00 ± 1.00 mm, 95.95 ± 0.05%, and 0.58 µg/ml; 15.66 ± 0.57 mm, 94.66 ± 0.19%, and 0.50 µg/ml, respectively, against pathogenic and MDR strains of E. coli and 22.33 ± 0.57 mm, 98.97 ± 0.02%, and 0.26 µg/ml; 20.33 ± 1.15 mm, 96.82 ± 0.14%, and 0.39 µg/ml, respectively, against pathogenic and MDR strains of S. aureus. Considering the bioactive compounds and beneficial effects, these fruit extracts could be promising antibiotic alternatives, avoiding antibiotic overuse and its negative effects on human health and the environment, and can be recommended as a novel functional food.

Prevalence and Predicting Factors of Alcohol Use Among School Going Adolescents in a Hilly State of Northern India.

Background: Alcohol use among adolescents is rising globally. This habit starts in adolescence and continues throughout their life. Alcohol addiction is associated with many other risky behaviors. Social environmental interventions will be an effective measure to control the problem of alcohol use. Objectives: The purpose of this study was to estimate the prevalence of alcohol use among adolescents and to investigate the associated risk and protective factors. Methods: A cross-sectional study was carried out among school going adolescents in the hilly state Himachal. A pre-validated, self-administered questionnaire was used for data collection. Results: The prevalence of alcohol use in adolescent was 6.1% (10.7% in males and 0.4% in females). Binary logistic regression model revealed that parent's and peer's drinking behavior significantly predicts an adolescent's drinking behavior. Conclusion: Our research supports the need for an adolescent health program involving school, peers, and family. Life skill education should be given to the adolescents to inculcate the resilience so that they learn to say no to peers who try to pull them into such habits.

Enhancing object detection in aerial images.

Unmanned Aerial Vehicles have proven to be helpful in domains like defence and agriculture and will play a vital role in implementing smart cities in the upcoming years. Object detection is an essential feature in any such application. This work addresses the challenges of object detection in aerial images like improving the accuracy of small and dense object detection, handling the class-imbalance problem, and using contextual information to boost the performance. We have used a density map-based approach on the drone dataset VisDrone-2019 accompanied with increased receptive field architecture such that it can detect small objects properly. Further, to address the class imbalance problem, we have picked out the images with classes occurring fewer times and augmented them back into the dataset with rotations. Subsequently, we have used RetinaNet with adjusted anchor parameters instead of other conventional detectors to detect aerial imagery objects accurately and efficiently. The performance of the proposed three step pipeline of implementing object detection in aerial images is a significant improvement over the existing methods. Future work may include improvement in the computations of the proposed method, and minimising the effect of perspective distortions and occlusions.

Effect of brief interventions to promote behavior change on clinical outcomes of selected non-communicable diseases: The World Health Organization (WHO) Package of Essential Non-communicable disease (PEN) Interventions for primary health care settings - study protocol of a quasi-experimental study.

BACKGROUND: The World Health Organization designed a minimum set of interventions, the World Health Organization Package of Essential Noncommunicable disease interventions (WHO PEN), for detection, prevention, treatment, and care of Non-communicable diseases (NCDs) in resource constraint settings. This intervention study examines the effectiveness of the integration of components of WHO PEN protocols on improved clinical outcomes among patients of cardiovascular disease and diabetes mellitus in urban and rural primary health care settings. METHODS: In this quasi-experimental study (pre-test post-test control group design), trained non-physician health workers will provide behavior change interventions regarding four major NCD risk factors, i.e., tobacco use, excessive alcohol intake, physical inactivity, an unhealthy diet; using 'Brief Advice' to the NCD patients enrolled in the experimental arm. The health centers in the control arm will provide the usual care to all the NCD patients. The intervention will last for six months, and the two groups will be followed up at two months, four months, and six months since enrolment in the study. RESULTS: The primary outcome is improved mean blood pressure levels and the proportion of patients with controlled blood pressure levels. The secondary outcomes assess medication adherence, self-reported reductions in tobacco and alcohol intake, consumption of a heart-healthy diet, and regular physical activity. DISCUSSION: This intervention trial will provide evidence for the utility of individual-level behavioral interventions for adequate management of NCDs. TRIAL REGISTRATION: Clinical Trial Registry of India: CTRI/2018/12/016707.

Biopolymeric nanoparticles based effective delivery of bioactive compounds toward the sustainable development of anticancerous therapeutics.

Nowadays, effective cancer therapy is a global concern, and recent advances in nanomedicine are crucial. Cancer is one of the major fatal diseases and a leading cause of death globally. Nanotechnology provides rapidly evolving delivery systems in science for treating diseases in a site-specific manner using natural bioactive compounds, which are gaining widespread attention. Nanotechnology combined with bioactives is a very appealing and relatively new area in cancer treatment. Natural bioactive compounds have the potential to be employed as a chemotherapeutic agent in the treatment of cancer, in addition to their nutritional benefits. Alginate, pullulan, cellulose, polylactic acid, chitosan, and other biopolymers have been effectively used in the delivery of therapeutics to a specific site. Because of their biodegradability, biopolymeric nanoparticles (BNPs) have received a lot of attention in the development of new anticancer drug delivery systems. Biopolymer-based nanoparticle systems can be made in a variety of ways. These systems have developed as a cost-effective and environmentally friendly solution to boost treatment efficacy. Effective drug delivery systems with improved availability, increased selectivity, and lower toxicity are needed. Recent research findings and current knowledge on the use of BNPs in the administration of bioactive chemicals in cancer therapy are summarized in this review.