Integration of Density Functional Theory and Machine Learning for Electrolyte Optimization in High-Voltage Dual-Ion Battery Design.

Designing dual-ion batteries (DIBs) by using various electrolytes through experiments or computationally is highly time-consuming and needs high-cost sophisticated resources. Here, we have utilized the ultrafast screening capability of machine learning (ML) to search for suitable salt-electrolytes toward the design of DIBs, choosing voltage as the desirable descriptor. Considering 50 different salts and their suitable staging mechanisms, the XGBoost Regressor ML model has been found to perform with remarkable accuracy. This is further validated by density functional theory, cross-validation, and experimental findings. An interpretable ML technique has been employed for local and global feature analysis to interpret the ML predicted results, underscoring the importance of choosing input features. This ML assisted DIB design approach has the potential to explore unknown salt-electrolytes that have yet to be tested in DIBs. Finally, we introduce the predicted voltages for all of the salt-electrolyte combinations as well as their probable staging mechanism. We signify the absence of a general trend in the predicted voltages, as various combinations of cations and anions are found to deliver unique voltages. Our study can guide researchers toward tuning constituent salts as well as staging mechanisms for the design of efficient DIBs.

A Rare Case of Vascular Malformation in India: Cutis Marmorata Telangiectatica Congenita.

The current case report presents a male baby, second born to nonconsanguineous parents at 38 weeks of gestation by lower segment cesarean section, with engorged blood vessels and distinctive patterns of discoloration and dilation of blood vessels on the left leg. A Doppler of the femoral artery and vein showed normal triphasic flow and waveforms without any evidence of significant luminal stenosis. There was also a lower limb length discrepancy of 1.5 cm. Genetic testing using fluorometric enzyme immunoassay screening revealed a negative screening report. Otologic screening using distortion product otoacoustic emissions revealed normal functioning of outer hair cells in both ears. The case was diagnosed as cutis marmorata telangiectatica congenita (CMTC), after ruling out genetic diseases. It was not associated with any other significant health problems. The diagnosis of CMTC was based on the appearance of the skin at birth, which became more noticeable shortly after two days. In this case, no specific treatment was warranted and the condition improved with time.

Student Satisfaction and Physical Health Effects of Online Learning Among Medical and Paramedical Undergraduates in Northern India: A Cross-Sectional Study.

BACKGROUND: Online modality of pedagogy was introduced in many medical institutes globally, especially during the COVID-19 pandemic. However, these techniques were not evaluated, either with respect to effectiveness or student satisfaction in terms of promoting successful educational outcomes. The current study was conducted to identify determinants of student satisfaction with respect to online learning, in the post-pandemic era. METHODS: A pilot-tested and validated online questionnaire was administered to 370 medical/paramedical students who attended online classes during the pandemic. The students were selected randomly from four different streams of a medical university, representing all the years of study. The questionnaire included Likert-type questions and was divided into two parts: socio-demographic profile and satisfaction with online learning. RESULTS: The response rate was 81.4%. Overall satisfaction with online learning among students was 35.9% and the areas of most satisfaction for students were user-friendliness of the online portal (65.5%), self-directed responsibilities assigned to pupils (49.9%), faculty accessibility/availability (48.8%) and timely evaluation, test and feedback (47.9%). The areas of most dissatisfaction were lack of personal effect as compared to offline learning (n=71, 23.6%), effect on social life (n=54, 17.9%), and feeling of not belonging to the online session (n=38, 12.6%). Multiple regression analysis demonstrated that having previous exposure to online courses and having a separate room led to more satisfaction, whereas the emergence of health problems led to poor satisfaction with the course. The duration of previous exposure to online courses was not a statistically significant predictor of satisfaction. One or more health problems were reported by 176 (58.5%) of the respondents. Some of the common health problems reported were eye strain (72.8%), headache (56.1%), insomnia (47.2%), stress (35.2%), muscle fatigue (22.6) and tingling sensation (10.6%). CONCLUSION: Adopting a combination of online and offline approaches, i.e., blended pedagogy, involving different methods to involve students and their feedback are important to ensure student satisfaction.

The fear of smartphone notifications and calls among medical students: The phone ring phobia syndrome or telephobia.

Background: Telephobia is a kind of anxiety disorder in which the individual is afraid of either answering or making telephone calls. This study was conducted to determine the prevalence of telephobia among medical students and to determine the association of socio-demographic and other factors with this disorder. Methods: A total of 320 undergraduate medical students were enrolled at a tertiary medical college in Western India, of which 300 (93.75%) responded to the survey. A stratified sampling strategy with the proportional allocation method was used in which 40 males and 20 females were selected from each year of students, spanning 5 years. A specially designed semi-structured questionnaire was used for the study, consisting of demographic data, purpose of using the internet, gadget used, and a 10-item telephobia questionnaire modified from the Severity Measure for Agoraphobia-Adult (SMA-A) Questionnaire to measure student's avoidance of telephone calling and receiving. Results: The mean age of the study participants was 21.91 (±1.84) years, and most of the students were urban residents (184, 61.3%). The prevalence of mild, moderate, and severe telephobia was 33.0%, 7.67%, and 1.33%, respectively, giving an overall prevalence of 42%. Univariate analysis revealed that male gender (χ2 = 9.822, df = 3, p = 0.0201), higher duration of internet usage (χ2 = 41.15, df = 9, p value < 0.000), and viewing porn (χ2 = 15.94, df = 3, p = 0.0011) had significant association with higher severity of telephobia. Viewing of porn sites was reported by 65 (21.7%) medical students, exclusively among males. Conclusion: A prevalence of 9% moderate to severe telephobia among medical students is much alarming, which may aggravate further as the students move from academic to clinical settings. The phenomenon of telephobia needs further exploration, to find its determinants and predictors, especially among vulnerable populations.

Lithiophilic Dibenzamide Linkages to Impart Lithium Storage Capacity in Porous Polybenzamides.

Polymer-based organic cathode materials have shown immense promise for lithium storage, owing to their structural diversity and functional group tunability. However, designing appropriate high-performance cathode materials with a high-rate capability and long cycle life remains a significant challenge. It is quintessential to design polymer-based electrodes with lithiophilic linkages. Herein, we design a bifurcated dibenzamide (DBA) linkage having lithiophilic functionalities. 1H NMR has been used as an experimental tool to understand the lithiophilic nature of the DBAs. Considering the strong Li+ affinity of DBAs, a series of polybenzamides have been designed as lithium storage systems. The design of porous polybenzamides consists of amides as only redox-active functionalities, and the rest are inactive phenyl units. Porous polybenzamides, when tested as cathodes against a Li-metal anode, displayed high capacity and rate performance, demonstrating their redox activity. The most efficient polybenzamide (TAm-TA) delivered a specific capacity of 248 mA h g-1 at 1C. TAm-TA retained 63% of its specific capacity at a very high rate of 10C (157 mA h g-1). Notably, polybenzamides displayed a capacity enhancement during long cycling, tending to achieve their theoretical capacity. Long cycling stability tests over 3000 cycles at a rate of 1.3C and over 6000 cycles at elevated rates (5C to 40C) demonstrate the electrochemical robustness of dibenzamide linkages. Finally, two full-cell experiments using TAm-TA as both cathode and anode were conducted, which delivered high capacity, demonstrating that TAm-TA is a promising candidate for Li+-ion batteries (LIBs). Furthermore, the ex situ Fourier transform infrared (FT-IR), X-ray photoemission spectroscopy (XPS), and density functional theory (DFT) studies revealed the stepwise lithiation/delithiation mechanism for polybenzamides.

Groundwater Hardness and Alkalinity As Risk Factors for Kidney Stone Disease in Alwar, India: An Ecological Study.

INTRODUCTION: Rajasthan is a semi-arid state in India where people still use groundwater for drinking purposes. However, the quality of groundwater as compared to standards have not been studied in any details. This ecological study was done to study the groundwater quality parameters in the stone-belt states, compare the quality of groundwater in Alwar with the rest of Rajasthan, and study the morbidity profile of surgical in-patients in the same district, with special emphasis on kidney stone disease (KSDs). METHODS: The morbidity profile of patients coming to the surgery department of a tertiary teaching hospital between January 2002 and June 2023 was obtained from the medical records department, and water quality data was obtained from the publicly available Water Resources Information System (WRIS) groundwater dataset for the year 2023. The dataset provided detailed information on the chemical parameters of water samples throughout the country that were evaluated to estimate the quality of groundwater. RESULTS: It was found that the groundwater in Alwar is non-potable due to the presence of iron, alkalinity, magnesium, and total dissolved solids (TDS). Iron was estimated to be much higher than the acceptable limit of the Bureau of Indian Standards (BIS) drinking-water quality guidelines (0.3 mg/L). Similarly, most of the chemical parameters in the groundwaters of Rajasthan significantly exceeded the national average. The median electrical conductivity, fluoride, magnesium, sodium, hardness, alkalinity, and turbidity were found to be 1680 µS/cm, 1.05 parts per million (PPM), 41 PPM, 233 PPM, 330 PPM, 310 PPM, 988 PPM, respectively, which are above the WHO recommendations for drinking water guidelines. CONCLUSIONS: The levels of iron and total alkalinity were significantly higher in the study district as compared to the rest of the state. Also, magnesium hardness and TDS levels were very high in the groundwater of the entire state of Rajasthan, making the population vulnerable to KSDs in the long run.

Determination of sample size for various study designs in medical research: A practical primer.

Formulating a research question and selecting an appropriate study design for answering that question are crucial initial steps in the research process. The population, intervention, control group, and outcomes measures (PICO time and setting [TS]) framework provides a practical guide in this regard, which stands for population, intervention, control, outcome, type of research question, and study design. The various study designs have their own merits and demerits, and implementing the methodology meticulously requires knowledge of all of these. Similarly, different methods of sample size calculation are warranted based on the most appropriate study design and outcome variables of interest. Sometimes, a post hoc power analysis can be performed after the sample size calculation, to check whether the study was adequately powered or not. There are multiple validated free software tools for sample size calculation, including Open-Epi, R, StatCalc, etc. The practice by most researchers of reporting significant P values is to be replaced by reporting effect sizes, as the latter is a much better estimate of the strength of association. This review provides a comprehensive, ready reckoner for busy family physicians to quickly identify the appropriate study design for answering any applied research questions in their minds and estimating the sample size required for the same.

Integrated Supervised and Unsupervised Machine Learning Approach to Map the Electrochemical Windows Over 4500 Solvents for Battery Applications.

The compatibility between solvent electrolytes and high-voltage electrode materials represents a significant impediment to the progress of rechargeable metal-ion batteries. Rapidly identifying suitable solvent electrolytes with optimized electrochemical windows (ECWs) within an extensive search space poses a formidable challenge. In this study, we introduce a combined supervised and unsupervised (clustering) machine learning (ML) approach to discern distinct clusters of solvent electrolytes exhibiting varying ECW ranges. Through supervised machine learning, we have accurately predicted optimal solvent electrolytes with desired ECWs from a vast pool of 4882 solvents. Our ML model boasts superior accuracy compared to previously reported data from density functional theory (DFT). Besides, the exploration of the vast solvent space through K-means clustering (unsupervised approach) yields 11 optimal clusters, each encompassing different solvents characterized by diverse ECW ranges and frequencies. The expedited reduction of solvent space achieved through clustering occurs within a very short time frame and with minimal resource expenditure. Consequently, this method is highly capable of streamlining the subsequent experimental investigations for battery applications, avoiding the need for a trial-and-error approach.

Rapid survey for assessing effective cataract surgical coverage (eCSC) and effective refractive error coverage (eREC)-Novel indicators of universal eye health.

PURPOSE: As per the recent World Health Organization estimates, approximately 2.2 billion people have near and distance vision impairment (VI) globally, and out of this almost 50% is avoidable. METHODS: The Rapid Assessment of Avoidable Visual Impairment survey was a cross-sectional study conducted in September 2021, using cluster random sampling in 42 clusters with a cluster size of 140, giving a total of 6000 participants. Two teams comprising of trained optometrists and social workers conducted the ocular examination which included unaided, pinhole, and aided visual acuity assessments followed by examination of the anterior segment and lens. Distance visual acuity was measured using simplified tumbling "E" charts of different sizes for VA of 6/12, 6/18, and 6/60. The lens assessment was done in an un-dilated pupil with torch light by the optometrist. RESULTS: Overall, 6520 individuals aged 6 years and above were enumerated, of whom 5440 (83.4%) were examined. The response rate for examination was better among females (93.1%) than males (73.9%), and it decreased from 93.8% in the age group 6-15 years to 77.1% in the 45+ age group. The prevalence of blindness and VI were 0.18% (95% CI: 0.06-0.29) and 4.19% (95%CI: 3.65-4.72), respectively. The major causes of VI in all age groups were uncorrected refractive error (65.4%), cataract (23.7%), cataract surgical complications (2.6%), corneal opacity (0.4%), and other posterior segment diseases (7.5%). The effective cataract surgical coverage (eCSC) was 61.8%, effective refractive error coverage (eREC) for distance vision was 59.8%, and eREC for near vision was 47.0%. CONCLUSION: The RAAVI methodology is suitable to measure effective coverage in the general population, both for baseline measurement and periodic monitoring. The 2030 targets for the surveyed district are 90% eCSC and 100% eREC. Such exercises need to be conducted in each district of the country to determine the baseline and target values of effective coverage.

Spiritual Health and Its Determinants Among Urban Adolescents in Northern India: A Cross-Sectional Survey.

INTRODUCTION: Spiritual health is an important dimension of positive health and is often ignored as it is not amenable to measurement. The present study was conducted to generate relevant evidence on spiritual health among adolescents living in urban areas of Northern India. METHODS: A cross-sectional study was done from June 2019 - May 2020 in an urban area of Northern India on a sample of 300 adolescents selected purposively. After collection of demographic details of the participants, the Index of Core Spiritual Experiences (INSPIRIT) tool was used to capture their spiritual health. RESULTS: The Cronbach's alpha for the scale was 0.832 (0.797-0.863) indicating good internal consistency of the measure. As far as spiritual health is concerned, 217 (72.3%) of the study participants scored medium-high to high, followed by 83 (27.7%) who scored medium-low to low on the spiritual health scale. Adjusted multivariate analysis using binary logistic regression showed that positive traits like caring (odds ratio (OR) 1.19, 95% CI: 1.08-1.33), connection to school (OR 1.16, 95% CI: 1.04-1.29), having positive identity (OR 1.19, 95% CI: 1.04-1.36) and having highly educated (post-graduate) parents (OR 2.18, 95% CI: 1.13-4.21) lead to significantly higher spiritual health scores.  Discussion: Although spiritual health is not routinely measured among adolescents, the current study demonstrated high levels of spiritual health among half of the urban adolescents. Parental education was found to have a positive association with spiritual health scores, indicating the indirect effect of parental spiritual inclination. The study has important implications for policy, as it demonstrates the feasibility of measuring a covert dimension of health which tends to have an indirect effect on holistic youth development.

Vaccination coverage against COVID-19 among rural population in Haryana, India: A cross-sectional study.

BACKGROUND: Conducting a study in rural pre-dominant areas will help to understand the penetration of the vaccination campaign during the COVID-19 health crisis. This study aimed to investigate vaccination coverage against COVID-19 among the rural adult population in India and to identify factors associated with vaccination coverage. METHODS: A population-based cross-sectional study was conducted among the rural population in one district of north India from January to February 2023. A semi-structured questionnaire was designed on the SurveyMonkey digital platform for interviewing the participants, which consisted of questions related to socio-demographic profile, health problems, vaccination status, types of vaccine, re-infection after vaccination, and functional difficulties. The data regarding infection with COVID-19 was collected based on self-reported positive testing for SARS-CoV 2 on RT-PCR. FINDINGS: A total of 3700 eligible individuals were enumerated for the survey, out of which 2954 (79.8%) were interviewed. The infection rate of past COVID-19 infection, based on self-report of testing positive, was 6.2% (95%CI: 5.3-7.1). Covishield vaccine was received by most participants (81.3%, 2380) followed by Covaxin (12.3%, 361) and Pfizer manufactured vaccine (0.03,1). The coverage for first, second, and booster doses of the vaccine was 98.2% (2902), 94.8% (2802), and 10.7% (315) respectively. The risk of reinfection at 12 months or more among participants with two doses of vaccine was 1.6% (46/2802, 95%CI: 1.2-2.1). The coverage among those with severe functional difficulties was lesser as compared to those with some or no difficulties. INTERPRETATION: Vaccination coverage against COVID-19 in rural Haryana, India is not dependent on factors like gender or occupation but is dependent on age and education. Although the full and partial vaccination coverage is high, the booster dose coverage is poor. In addition, the presence of severe disability was significantly associated with reduced vaccination coverage.

Bioactives from medicinal herb against bedaquiline resistant tuberculosis: removing the dark clouds from the horizon.

Tuberculosis is a contagious bacterial ailment that primarily affects the lungs and is brought on by the bacterium Mycobacterium tuberculosis (MTB). An antimycobacterial medication called bedaquiline (BQ) is specified to treat multidrug-resistant tuberculosis (MDR-TB). Despite its contemporary use in clinical practice, the mutations (D32 A/G/N/V/P) constrain the potential of BQ by causing transitions in the structural conformation of the atpE subunit-c after binding. In this study, we have taken the benzylisoquinoline alkaloids from thalictrum foliolosum due to its antimicrobial activity reported in prior literature. We used an efficient and optimized structure-based strategy to examine the wild type (WT) and mutated protein upon molecule binding. Our results emphasize the drastic decline in BQ binding affinity of mutant and WT atpE subunit-c complexes compared to thalirugidine (top hit) from thalictrum foliolosum. The decrease in BQ binding free energy is due to electrostatic energy because nearly every atom in a macromolecule harbors a partial charge, and molecules taking part in molecular recognition will interact electrostatically. Similarly, the high potential mean force of thalirugidine than BQ in WT and mutant complexes demonstrated the remarkable ability to eradicate mycobacteria efficiently. Furthermore, the Alamar blue cell viability and ATP determination assay were performed to validate the computational outcomes in search of novel antimycobacterial. Upon closer examination of the ATP determination assay, it became apparent that both BQ and thalirugidine showed similar reductions in ATP levels at their respective MICs, presenting a potential common mechanism of action.

Unlocking the Potential of Dual-Ion Batteries: Identifying Polycyclic Aromatic Hydrocarbon Cathodes and Intercalating Salt Combinations through Machine Learning.

Dual-ion batteries (DIBs) represent a promising energy storage technology, offering a cost-effective safe solution with impressive electrochemical performance. The large combinatorial configuration space of the electrode-electrolyte leads to design challenges. We present a machine learning (ML) approach for accurately predicting the voltage and volume changes of polycyclic aromatic hydrocarbon (PAH) cathodes upon intercalation with a variety of DIB salts following different mechanisms. Gradient Boosting and XGBoost Regression models trained on the data set demonstrate exceptional performance in voltage and volume change prediction, respectively. The models are further cross-validated and utilized to predict the properties for ∼700 combinations of PAH and DIB salt intercalations, a subset of which is further validated by density functional theory. Using average voltage and volume change for all combinations of PAHs and salts, preferable combinations for high/low voltage requirements along with long-term stability are obtained. Overall, the study shows the applicability of PAHs in DIBs exhibiting good electrochemical performance with low volume change compared to graphite indicative of its potential to overcome the cycling stability issues of DIBs. This research establishes a reliable and broadly applicable ML-based workflow for efficient screening and accelerated design of advanced PAH cathodes and salts, thus driving progress in the field of DIBs.

A rare case of genital myiasis in a patient with genital prolapse.

Genital myiasis is an infestation of genital organs by fly larvae, where they feed and develop as parasites. They can cause severe infection, inflammatory reaction and can be linked to psychiatric disturbances. We report a rare case of genital myiasis in an elderly postmenopausal woman aged 82 years from Udaipur, Rajasthan. She presented with complaints of intense pain in the genital region and was diagnosed as a case of genital myiasis of a prolapsed uterus. Pelvic examination revealed 'Stage-IV' genitourinary prolapse according to Pelvic Organ Prolapse-Quantification (POP-Q classification), with a big excavatory ulcer indwelled with maggots of Musca domestica. About 100 such maggots were subsequently manually removed with forceps. With proper surgical and nonsurgical interventions, the patient healed completely and the prolapse was reduced completely.

Assistive technology usage, unmet needs and barriers to access: a sub-population-based study in India.

Background: Assistive technology (AT) is essential to minimize functional limitations. The current study aimed to estimate the prevalence of needs, met and unmet needs for AT, and barriers to accessing AT among a subnational population in India. Methods: This cross-sectional study was conducted in eight districts, representing four zones of India, using the WHO Rapid Assistive Technology Assessment (rATA) tool. The tool was administered by trained staff using read aloud technique. Multi-stage cluster random sampling was used, as well as the probability proportional to size, to select smaller administrative units from the larger ones. Findings: In total, 8486 participants were surveyed out of 8964 individuals enumerated with a response rate of 94.6%. The sample prevalence of at least one difficulty was 31.8% (2700), with 6.3% (532) having severe or total difficulties. The sample prevalence for AT need was 27.8% (2357) with an estimated population prevalence of 24.5% (95% CI: 23.5-25.4). Similarly, the sample prevalence of unmet needs was 9.7% (823) with an estimated population unmet needs of 8.0% (95% CI: 7.43-8.60). The unmet needs among persons with severe or total difficulties was 52.3% (278/532), and was higher among females, rural residents, and older persons. Spectacles were the most used products, followed by canes/sticks, tripods, and quadripods. Nearly two-thirds of AT users purchased assistive products at their own expense, particularly from the private sector. The inability to afford AT (36.9%) was the most common barrier. Interpretation: The results show that the need for AT was substantial in the study population, the highest being for seeing difficulties. The unmet needs are higher in females, older population, rural residents, and persons having serious difficulties. While the majority of users have to make out-of-pocket payments to obtain AT, inability to afford and limited availability were the common barriers among those with unmet needs. Funding: This research is non-commercial, and was conducted in the interest of public health. The authors have not declared any specific grant for this research.

Current Status of Trachoma Among Underserved Population of India: Results from the National Trachoma Rapid Assessment Survey 2014-17.

PURPOSE: To determine the burden of trachoma and its related risk factors among the underserved population of sixteen states/union territories (UTs) in India. METHODS: Trachoma rapid assessment (TRA) was conducted in seventeen Enumeration Units (EUs) spanning sixteen states/UTs in India according to standard WHO guidelines. A total of ten clusters were selected in each EU and 50 children aged 1-9 years were assessed clinically for signs of active trachoma and facial cleanliness in each cluster. Additionally, all adults aged 15 years and above in the same households were examined for evidence of trachomatous trichiasis (TT) and corneal opacity. Environmental risk factors contributing to trachoma were also noted in all households. RESULTS: Out of 766 districts in India, seventeen EUs were selected for TRA depending on evidence of socio-developmental indicators like poverty and suboptimal access to water, sanitation, and healthcare facilities. The total population of the selected clusters was 21,774 in the 17 EUs. Overall, 104 of 8807 children (1.2%; CI: 0.9-1.4) had evidence of follicular or inflammatory stages of trachoma. Nearly 16.6% (CI:15.8-17.4) children were noted to have unclean faces in the 170 clusters. Trichiasis was noted in 19 adults (2.1 per 1000; CI:1.2-3.2 per 1000). Environmental sanitation was found to be unsatisfactory in two-thirds (67.8%) of the surveyed households in the clusters mainly due to improper garbage disposal. CONCLUSION: Active trachoma was not a public health problem in any of the EUs surveyed. However, burden of TT among adults was found to be above 0.2% in two EUs; hence, further public health interventions like trichiasis surgery were recommended.

Organic-Inorganic Hybrid Nanocomposites for Nanotheranostics: Special Focus on Preventing Emerging Variants of SARS-COV-2.

The worldwide emerging cases of various respiratory viral diseases and the current escalation of novel coronavirus disease (COVID-19) make people considerably attentive to controlling these viruses through innovative methods. Most re-emerging respiratory diseases envelop RNA viruses that employ attachment between the virus and host cell to get an entry form using the host cell machinery. Emerging variants of COVD-19 also bring about a constant threat to public health as it has wide infectivity and can quickly spread to infect humans. This review focuses on insights into the current investigations to prevent the progression of incipient variants of Severe Acute Respiratory Syndrome Coronavirus (SARS-COV-2) along with similar enveloped RNA viruses that cause respiratory illness in humans and animals. Nanotheranostics is a trailblazing arena of nanomedicine that simultaneously helps prevent or treat diseases and diagnoses. Nanoparticle coating and nanofibers were extensively explored, preventing viral contaminations. Several studies have proven the virucidal activities of metal nanoparticles like copper, silver, and titanium against respiratory viral pathogens. Worldwide many researchers have shown surfaces coated with ionic nanoparticles like zinc or titanium act as potent antiviral agents against RNA viruses. Carbon nanotubes, quantum dots, silica nanoparticles (NPs), polymeric and metallic nanoparticles have also been explored in the field of nanotheranostics in viral detection. In this review, we have comprehensively discussed different types of metallic, ionic, organic nanoparticles and their hybrids showing substantial antiviral properties to stop the progression of the novel coronavirus disease focused on three key classes: prevention, diagnostics, and treatment.

Rapid Assessment of Avoidable Visual Impairment in Two Coastal Districts of Eastern India for Determining Effective Coverage: A Cross-Sectional Study.

Purpose: To measure the prevalence and causes of visual impairment (VI) among the 40+ age population in two coastal districts of India and to determine the levels of effective cataract surgical coverage (eCSC) and effective refractive error coverage (eREC) in the study population. Methods: A cross-sectional study was done on 4200 people chosen using cluster sampling in two coastal districts of Odisha, an eastern state in India. A team consisting of trained optometrists and social workers conducted the ocular examination which included unaided, pinhole, and aided visual acuity assessments followed by examination of the anterior segment and lens. Results: Overall, 3745 (89.2%) participants were examined from 60 study clusters, 30 in each district. Among those examined, 1677 (44.8%) were men, 2554 (68.2%) were educated and number? (17.8%) used distance spectacles during the survey. The prevalence of VI adjusted for age and gender was 12.77% (95% CI 11.85-13.69%). Multiple logistic regression showed that older age (OR 3.1; 95% CI 2.0-4.7) and urban residence (OR 1.2; 95% CI 1.0-1.6) were associated with VI. Being educated (OR 0.4; 95% CI 0.3-0.6) and using glasses (OR 0.3; 95% CI 0.5-0.2) were found to provide protection; therefore, resulting in lower instances of VI. Cataract (62.7%) and uncorrected refractive errors (27.1%) were the two main causes of VI. The eCSC was 35.1%, the eREC for distance was 40.0%, and the eREC for near was 35.7%. Conclusion: VI remains a challenge in Odisha, as the prevalence is high and the surgical coverage is poor. Nearly 90% of VI is avoidable indicating that targeted interventions are required to address this problem.

Improving assistive technology access to students with low vision and blindness in Delhi: A school-based model.

Purpose: Assistive technology (AT) has recently received considerable attention around the world. Studies have shown poor access to assistive technology for visual impairment (ATVI) in schools for the blind in India. The present article aimed at designing a school-based model to improve AT access in schools and provide hands-on training, and identify types of ocular morbidities present among students. Methods: The vision rehabilitation (VR) team of a tertiary eye-care center visited schools for the blind as a part of community-based VR services. The team conducted a basic eye examination and assessed best-corrected vision acuity (BCVA) and provided VR services. Furthermore, two schools were selected to establish an ATVI learning center as a pilot model. Results: In total, 1887 students were registered for VR and obtained their disability certificates in 2019-20. Retina problems (25.7%), globe abnormalities (25.5%), optic nerve atrophy (13.6%), and squint (12.0%) were common ocular problems identified in students. Around 50.3% of students had BCVA3 1/60 in the better eye who would be benefited from visual-based AT, and the remaining students with visual substitution AT. Further, 20.8% of them who had near vision between N18 to N24 would be benefitted from large print books. Two schools were provided ATVI with support from the WHO. Familiarization, demonstration, and initial training for ATVI were carried out. Conclusion: A sizable number of the students would be benefitted from visual-based AT apart from visual substitutions AT. Students were interested to have such ATVI centers in the school for academic and non-academic skills development.

Machine Learning Prediction of the Transmission Function for Protein Sequencing with Graphene Nanoslit.

Protein sequencing has rapidly changed the landscape of healthcare and life science by accelerating the growth of diagnostics and personalized medicines for a variety of fatal diseases. Next-generation nanopore/nanoslit sequencing is promising to achieve single-molecule resolution with chromosome-size-long readability. However, due to inherent complexity, high-throughput sequencing of all 20 amino acids demands different approaches. Aiming to accelerate the detection of amino acids, a general machine learning (ML) method has been developed for quick and accurate prediction of the transmission function for amino acid sequencing. Among the utilized ML models, the XGBoost regression model is found to be the most effective algorithm for fast prediction of the transmission function with a very low test root-mean-square error (RMSE ∼0.05). In addition, using the random forest ML classification technique, we are able to classify the neutral amino acids with a prediction accuracy of 100%. Therefore, our approach is an initiative for the prediction of the transmission function through ML and can provide a platform for the quick identification of amino acids with high accuracy.