Transforming air pollution management in India with AI and machine learning technologies.

A comprehensive approach is essential in India's ongoing battle against air pollution, combining technological advancements, regulatory reinforcement, and widespread societal engagement. Bridging technological gaps involves deploying sophisticated pollution control technologies and addressing the rural-urban disparity through innovative solutions. The review found that integrating Artificial Intelligence and Machine Learning (AI&ML) in air quality forecasting demonstrates promising results with a remarkable model efficiency. In this study, initially, we compute the PM2.5 concentration over India using a surface mass concentration of 5 key aerosols such as black carbon (BC), dust (DU), organic carbon (OC), sea salt (SS) and sulphates (SU), respectively. The study identifies several regions highly vulnerable to PM2.5 pollution due to specific sources. The Indo-Gangetic Plains are notably impacted by high concentrations of BC, OC, and SU resulting from anthropogenic activities. Western India experiences higher DU concentrations due to its proximity to the Sahara Desert. Additionally, certain areas in northeast India show significant contributions of OC from biogenic activities. Moreover, an AI&ML model based on convolutional autoencoder architecture underwent rigorous training, testing, and validation to forecast PM2.5 concentrations across India. The results reveal its exceptional precision in PM2.5 prediction, as demonstrated by model evaluation metrics, including a Structural Similarity Index exceeding 0.60, Peak Signal-to-Noise Ratio ranging from 28-30 dB and Mean Square Error below 10 µg/m3. However, regulatory challenges persist, necessitating robust frameworks and consistent enforcement mechanisms, as evidenced by the complexities in predicting PM2.5 concentrations. Implementing tailored regional pollution control strategies, integrating AI&ML technologies, strengthening regulatory frameworks, promoting sustainable practices, and encouraging international collaboration are essential policy measures to mitigate air pollution in India.

Torsemide in Edema Associated with Chronic Kidney Disease.

Torsemide is a loop diuretic used to manage edema associated with chronic kidney disease (CKD) and acute kidney injury (AKI). It acts by inhibiting sodium and chloride ions reabsorption in the ascending limb of the loop of Henle, thereby increasing urine output and reducing fluid accumulation. Compared to other diuretics, torsemide has an extended duration of action, higher bioavailability, and its elimination route is primarily through the hepatic route, making it effective in patients with CKD and AKI. Clinical studies indicate that torsemide can improve symptoms of fluid overload and potentially enhance renal function.

Cellulose binding and the timing of expression influence protein targeting to the double-layered cyst wall of Acanthamoeba.

The cyst wall of the eye pathogen Acanthamoeba castellanii contains cellulose and has ectocyst and endocyst layers connected by conical ostioles. Cyst walls contain families of lectins that localize to the ectocyst layer (Jonah) or the endocyst layer and ostioles (Luke and Leo). How lectins and an abundant laccase bind cellulose and why proteins go to locations in the wall are not known and are the focus of the studies here. Structural predictions identified ß-jelly-roll folds (BJRFs) of Luke and sets of four disulfide knots (4DKs) of Leo, each of which contains linear arrays of aromatic amino acids, also present in carbohydrate-binding modules of bacterial and plant endocellulases. Ala mutations showed that these aromatics are necessary for cellulose binding and proper localization of Luke and Leo in the Acanthamoeba cyst wall. BJRFs of Luke, 4DKs of Leo, a single ß-helical fold (BHF) of Jonah, and a copper oxidase domain of the laccase each bind to glycopolymers in both layers of deproteinated cyst walls. Promoter swaps showed that ectocyst localization does not just correlate with but is caused by early encystation-specific expression, while localization in the endocyst layer and ostioles is caused by later expression. Evolutionary studies showed distinct modes of assembly of duplicated domains in Luke, Leo, and Jonah lectins and suggested Jonah BHFs originated from bacteria, Luke BJRFs share common ancestry with slime molds, while 4DKs of Leo are unique to Acanthamoeba.IMPORTANCEAcanthamoebae is the only human parasite with cellulose in its cyst wall and conical ostioles that connect its inner and outer layers. Cyst walls are important virulence factors because they make Acanthamoebae resistant to surface disinfectants, hand sanitizers, contact lens sterilizers, and antibiotics applied to the eye. The goal here was to understand better how proteins are targeted to specific locations in the cyst wall. To this end, we identified three new proteins in the outer layer of the cyst wall, which may be targets for diagnostic antibodies in corneal scrapings. We used structural predictions and mutated proteins to show linear arrays of aromatic amino acids of two unrelated wall proteins are necessary for binding cellulose and proper wall localization. We showed early expression during encystation causes proteins to localize to the outer layer, while later expression causes proteins to localize to the inner layer and the ostioles.

Aerosol atmospheric rivers: patterns, impacts, and societal insights.

This study focuses on understanding how aerosols are transported over long distances, especially during extreme events. Leveraging the integrated vapour transport (IVT) based atmospheric river (AR) algorithm to integrated aerosol transport (IAT) to detect the aerosol atmospheric rivers (AARs) for key aerosol species such as black carbon (BC), organic carbon (OC), dust (DU), sea salt (SS), and sulphate (SU). The present study also assesses the occurrence, intensity, and societal impacts of AARs globally during 2015-2022 on a spatiotemporal resolution of 1.5° × 1.5° and 6 h, respectively. The detection algorithm found a total number of 128,261 AARs found globally for key aerosol species. However, the availability of BC, OC, and SU AARs is most common and intense in densely populated areas like the Indus-Brahmaputra-Ganga (IBG) plains (~ 15-20 AAR days/year), Eastern China (~ 25-40 AAR days/year), and Japan (~ 20-30 AAR days/year), where human activities including agriculture burning contribute to their formation. DU AARs, on the other hand, are more prevalent in Northern Africa (~ 15 AAR days/year), the Gulf (~ 5-10 AAR days/year), the USA, and the Amazon rainforests. SS AARs share similar characteristics with atmospheric rivers and are more intense in higher latitudes and over the oceans (~ 30-40 AAR days/year). The study also validates its findings by analysing recent extreme events involving BC and DU worldwide. The potential applications of specific AARs could assist us in identifying the causes of snow darkening, reducing snow cover area, and accelerating melting rate. Moreover, AARs could aid in quantifying the health risks associated with severe air pollution.

EEG based functional connectivity in resting and emotional states may identify major depressive disorder using machine learning.

OBJECTIVE: Disrupted brain network connectivity underlies major depressive disorder (MDD). Altered EEG based Functional connectivity (FC) with Emotional stimuli in major depressive disorder (MDD) in addition to resting state FC may help in improving the diagnostic accuracy of machine learning classification models. We explored the potential of EEG-based FC during resting state and emotional processing, for diagnosing MDD using machine learning approach. METHODS: EEG was recorded during resting state and while watching emotionally contagious happy and sad videos in 24 drug-naïve MDD patients and 25 healthy controls. FC was quantified using the Phase Lag Index. Three Random Forest classifier models were constructed to classify MDD patients and healthy controls, Model-I incorporating FC features from the resting state and Model-II and Model-III incorporating FC features while watching happy and sad videos respectively. RESULTS: Important features distinguishing MDD and healthy controls were from all frequency bands and represent functional connectivity between fronto-temporal, fronto-parietal and fronto occipital regions. The cross-validation accuracies for Model-I, Model-II and Model-III were 92.3%, 94.9% and 89.7% and test accuracies were 60%, 80% and 70% respectively. Incorporating emotionally contagious videos improved the classification accuracies. CONCLUSION: Findings support EEG FC patterns during resting state and emotional processing along with machine learning can be used to diagnose MDD. Future research should focus on replicating and validating these results. SIGNIFICANCE: EEG FC pattern combined with machine learning may be used for assisting in diagnosing MDD.

Correlation of oxygenation indices in invasive mechanical ventilated adult patients.

BACKGROUND: Mechanical ventilation is essential for managing acute respiratory failure, but traditional methods of assessing oxygenation, like the PaO2/FiO2 ratio, pose challenges due to invasiveness and cost. OBJECTIVE: This single-centre prospective observational study aimed to assess the potential of the non-invasive Oxygen Saturation Index (OSI), utilising SpO2 measurements, to diagnose hypoxemia in mechanically ventilated adults. The study sought to establish correlations between OSI, oxygenation index (OI), PaO2/FiO2 ratio and SpO2/FiO2 ratio. METHODS: From August 2022 to July 2023, data was collected from 1055 mechanically ventilated intensive care unit patients. Statistical analysis included correlation tests, receiver operating curve (ROC) analysis and cut-off value determination for hypoxemia diagnosis. RESULTS: We found that the P/F ratio had a statistically significant negative correlation with OI (correlation coefficient -0.832, P value: 0.000 in hypoxemic group and correlation coefficient -0.888, P value: 0.000 in the non-hypoxemic group), and OSI (correlation coefficient -0.746, P value: 0.000 in hypoxemic group and correlation coefficient -0.629, P value: 0.000 in non-hypoxemic group) and has a positive correlation with P/F ratio (correlation coefficient 0.92, P value: 0.000 in hypoxemic group and correlation coefficient -0.67, P value: 0.000 in non-hypoxemic group). OI and OSI had a statistically significant correlation (correlation coefficient 0.955, P value: 0.000 in hypoxemic group and correlation coefficient 0.815, P value: 0.000 in non-hypoxemic group). on ROC analysis P/F ratio was the most accurate in predicting hypoxia followed by OI and OSI. with a cut-off value, of OI being 7.07, and that for OSI being 3.90, at an 80% sensitivity level to diagnose hypoxemia. CONCLUSION: OSI can serve as a dependable surrogate for OI, simplifying ARDS severity assessment. The P/F ratio is the most accurate predictor of hypoxia. Further research, especially in larger multicentre studies, is needed to validate these findings and explore the long-term clinical implications of using OSI for oxygenation monitoring in mechanically ventilated patients.

Plasmodium falciparum Alba6 exhibits DNase activity and participates in stress response.

Alba domain proteins, owing to their functional plasticity, play a significant role in organisms. Here, we report an intrinsic DNase activity of PfAlba6 from Plasmodium falciparum, an etiological agent responsible for human malignant malaria. We identified that tyrosine28 plays a critical role in the Mg2+ driven 5'-3' DNase activity of PfAlba6. PfAlba6 cleaves both dsDNA as well as ssDNA. We also characterized PfAlba6-DNA interaction and observed concentration-dependent oligomerization in the presence of DNA, which is evident from size exclusion chromatography and single molecule AFM-imaging. PfAlba6 mRNA expression level is up-regulated several folds following heat stress and treatment with artemisinin, indicating a possible role in stress response. PfAlba6 has no human orthologs and is expressed in all intra-erythrocytic stages; thus, this protein can potentially be a new anti-malarial drug target.

Percentage of patients shifting to another treatment modality: An experience-guided decision.

OBJECTIVE: This study aimed to assess the frequency with which orthodontic patients decided to shift to another type of orthodontic appliance, among conventional metal brackets, ceramic brackets, lingual brackets and clear aligner, based on their personal experiences of pain, ulcers, bad breath, hygiene issues and social difficulties. MATERIAL AND METHODS: This study comprises of patients seeking orthodontic treatment. The sample (n = 500; age group = 19-25 years) was divided equally into four groups based on the treatment modality: conventional metal brackets, ceramic brackets, lingual brackets and clear aligner. Patients rated the questionnaire using a visual analogue scale, to assess variables (such as pain, ulcer etc) that impact various treatment modalities. Subsequently, patients from all groups provided feedback regarding their treatment experiences, and expressed their preference for an alternative modality. Intergroup comparison among the four groups was done using one-way analysis of variance with Tukey's HSD post-hoc test (p ≤ 0.05). RESULTS: Patients who received lingual brackets reported higher levels of pain and ulceration, as compared to those who received clear aligners. All four groups showed statistically significant differences for ulcers during treatment (p ≤ 0.05). Of the 125 patients who received conventional metal brackets, 28% expressed a preference for clear aligner therapy, while 20% preferred ceramic brackets. In the lingual group, 56% of 125 patients preferred clear aligner therapy, and 8% preferred ceramic brackets to complete their treatment. In the ceramic group, 83% did not want to switch, whereas 17% desired to switch to clear aligner, while in aligner group no patient desired to switch. CONCLUSIONS: A higher percentage of patients from lingual brackets group chose to shift to clear aligners, followed by conventional metal brackets group and by ceramic brackets group, in this descending order. The clear aligner group demonstrated fewer issues than the other treatment modalities.

Transboundary hazard and downstream impact of glacial lakes in Hindu-Kush Karakoram Himalayas.

Glacial Lake Outburst Floods (GLOFs) can generate catastrophic flash floods when the damming structure is breached or overtopped. Some of these glacial lakes are located in transboundary regions where floods originating from the lake in one country could inundate a neighboring country, devastating the population and infrastructure of both nations and influencing socio-political relationships. Therefore, assessing the lakes' hazard is crucial. This study investigates transboundary glacial lakes, considering their GLOF hazard, including potential mass movement intrusion, moraine's stability, upstream and downstream process cascades, downstream flood extents, and the exposure and vulnerability of the downstream infrastructure and affected population. GLOF exposure assessments were carried out to identify exposed buildings, bridges, and hydropower systems in transboundary regions. China currently has the highest number of transboundary lakes, with most of them potentially impacting India and Nepal. Most of the transboundary lakes in China, and many in India and Nepal, are susceptible to mass movements. Among the 230 transboundary glacial lakes in the Hindu Kush Karakoram Himalaya, 55 lakes can potentially impact other glacial lakes along their flow path, creating a cascade of events. Five transboundary lakes could potentially impact over 1000 buildings, and 16 lakes could impact over 500 buildings. A total of 35 lakes can impact at least one hydropower station along their flow path, and 4 lakes can impact two hydropower stations. This research emphasizes the critical importance of conducting comprehensive risk analyses of GLOFs in transboundary regions to inform policy-makers. It calls for investing in broad-scale assessments and data-driven decision-making for mitigating and adapting to GLOF risks effectively. Finally, by raising awareness among policy-makers, the study aims to drive actions that safeguard communities and infrastructure vulnerable to GLOF.

Characterizing the spatio-temporal distribution, detection, and prediction of aerosol atmospheric rivers on a global scale.

Aerosol Atmospheric Rivers (AARs) are elongated and narrow regions that carry high concentrations of aerosols (tiny particles suspended in the atmosphere) across large distances, exerting effects on both air quality and human health (Chakraborty et al., 2021, 2022). Monitoring and modeling these aerosols present distinct challenges due to their dynamic nature and complex interactions within the atmosphere. In this context, the present study detects and predicts the AARs using MERRA-2 reanalysis datasets with their seasonal climatology of key aerosol species, including Black Carbon (BC), Dust (DU), Organic Carbon (OC), Sea Salt (SS), and Sulphates (SU). The study employs an innovative Integrated Aerosol Transport (IAT) based AAR algorithm from 2015 to 2022. A total count of 44,020 BC AARs, 13,280 DU AARs, 21,599 OC AARs, 17,925 SS AARs, and 31,437 SU AARs were detected globally. The seasonal climatology of BC and OC AARs intensifies in areas such as the Amazon rainforest and Congo during AMJJAS (April-September) due to forest fires. Similarly, DU AARs are more frequent in regions near the Saharan desert, primarily around the equator during AMJJAS. SS AARs tend to predominate over the oceans, while SU AARs are predominantly found in the northern hemisphere, primarily due to higher anthropogenic emissions. Furthermore, convolutional autoencoder-based models were developed for key aerosol species, strengthening predictive accuracy by effectively capturing complex data relationships and delivering precise predictions for the last 5-time frames. During validation, the model evaluation parameters for image prediction such as the Structural Similarity Index ranged from 0.86 to 0.94, Peak Signal-to-Noise Ratio fluctuated between 1.14 and 42.25 dB, Root Mean Square Error varied from 2.39 to 296.4 mg/(m-sec), and Mean Square Error fell within the range of 1.55-17.22 mg/(m-sec). These collectively reflect image closeness, quality, dissimilarity, and accuracy in AAR prediction. This study demonstrates the effectiveness of advanced machine and deep learning models in predicting AARs, offering the potential for advanced forecasting and enhancing resilience in high-aerosol concentration regions.

Percentage of patients shifting to another treatment modality: An experience-guided decision

ABSTRACT Objective: This study aimed to assess the frequency with which orthodontic patients decided to shift to another type of orthodontic appliance, among conventional metal brackets, ceramic brackets, lingual brackets and clear aligner, based on their personal experiences of pain, ulcers, bad breath, hygiene issues and social difficulties. Material and Methods: This study comprises of patients seeking orthodontic treatment. The sample (n = 500; age group = 19-25 years) was divided equally into four groups based on the treatment modality: conventional metal brackets, ceramic brackets, lingual brackets and clear aligner. Patients rated the questionnaire using a visual analogue scale, to assess variables (such as pain, ulcer etc) that impact various treatment modalities. Subsequently, patients from all groups provided feedback regarding their treatment experiences, and expressed their preference for an alternative modality. Intergroup comparison among the four groups was done using one-way analysis of variance with Tukey's HSD post-hoc test (p ≤ 0.05). Results: Patients who received lingual brackets reported higher levels of pain and ulceration, as compared to those who received clear aligners. All four groups showed statistically significant differences for ulcers during treatment (p ≤ 0.05). Of the 125 patients who received conventional metal brackets, 28% expressed a preference for clear aligner therapy, while 20% preferred ceramic brackets. In the lingual group, 56% of 125 patients preferred clear aligner therapy, and 8% preferred ceramic brackets to complete their treatment. In the ceramic group, 83% did not want to switch, whereas 17% desired to switch to clear aligner, while in aligner group no patient desired to switch. Conclusions: A higher percentage of patients from lingual brackets group chose to shift to clear aligners, followed by conventional metal brackets group and by ceramic brackets group, in this descending order. The clear aligner group demonstrated fewer issues than the other treatment modalities.

RESUMO Objetivo: Este estudo teve como objetivo avaliar a frequência com que pacientes ortodônticos decidiram mudar para outro tipo de aparelho ortodôntico, entre braquetes convencionais de metal, braquetes cerâmicos, braquetes linguais e alinhadores transparentes, com base em suas experiências pessoais de dor, aftas, mau hálito, problemas de higiene e dificuldades sociais. Material e Métodos: Esse estudo foi composto por pacientes que procuram tratamento ortodôntico. A amostra (n = 500; faixa etária = 19-25 anos) foi dividida igualmente em quatro grupos, com base na modalidade de tratamento: braquetes metálicos convencionais, braquetes cerâmicos, braquetes linguais e alinhadores transparentes. Os pacientes responderam a um questionário, usando uma escala visual analógica, para avaliar variáveis como dor e aftas, que impactam diferentes modalidades de tratamento. Posteriormente, os pacientes de todos os grupos forneceram feedback sobre suas experiências de tratamento e expressaram sua preferência por uma modalidade alternativa. A comparação intergrupos entre os quatro grupos foi feita usando análise de variância unidirecional com teste post-hoc HSD de Tukey (p ≤ 0,05). Resultados: Os pacientes que usaram braquetes linguais relataram níveis mais elevados de dor e aftas, em comparação com aqueles que usaram alinhadores transparentes. Todos os quatro grupos apresentaram diferenças estatisticamente significativas para aftas durante o tratamento (p ≤ 0,05). Dos 125 pacientes que usaram braquetes metálicos convencionais, 28% expressaram preferência pelo tratamento com alinhadores transparentes, enquanto 20% preferiram braquetes cerâmicos. No grupo com braquetes linguais, 56% dos 125 pacientes preferiram o tratamento com alinhadores transparentes e 8% preferiram braquetes cerâmicos para completar o tratamento. No grupo com braquetes cerâmicos, 83% não queriam trocar de tratamento, enquanto 17% desejavam mudar para os alinhadores transparentes; enquanto no grupo de alinhadores nenhum paciente desejou mudar. Conclusões: Uma porcentagem maior de pacientes do grupo com braquetes linguais optou pela mudança para alinhadores transparentes, seguido pelo grupo com braquetes metálicos convencionais e pelo grupo com braquetes cerâmicos, em ordem decrescente. O grupo de alinhadores transparentes demonstrou menos problemas do que as outras modalidades de tratamento.

The Effect of Difference in Word Order on Semantic Processing in Hindi-English Bilinguals.

Background: The typology of word order in Hindi (Subject-Object-Verb, SOV) differs from that of English (Subject-Verb-Object, SVO). Bilinguals whose two languages have conflicting word order provide a unique opportunity to understand how word order affects language processing. Earlier behavioural and event-related brain potential (ERP) studies with Spanish-Basque bilinguals showed longer reading times and more errors in the comprehension of OSV sentences than SOV sentences in Basque language, indicating that non-canonical word orders (OSV) were difficult to process than canonical word order (SOV). Purpose: This study was designed to explore how the difference in word order in Hindi and English languages affects N400 parameters in proficient Hindi-English bilinguals, using semantic congruity paradigm. Methods: Twenty-five proficient Hindi-English bilingual subjects were asked to silently read the congruent and incongruent sentences presented in one word at a time in both the languages. ERPs were recorded from midline frontal, central and parietal sites. Results: The mean amplitude of the N400 effect at the parietal sites in Hindi-English proficient bilinguals was larger for English than for Hindi but there was no significant difference in the N400 latencies. Conclusion: Hindi-English bilingual subjects processed SOV and SVO sentences with equal ease as evidenced by the N400 latencies. Higher amplitude of the N400 effect with English sentences indicate that placing 'Object' as the final word makes sentences more predictable than verb as the final word. Understanding the word order difference might help to unravel the neurophysiological mechanisms of language comprehension and may offer some insights in terms of functional advantage of a particular word order in bilinguals.

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine.

Wetlands are one of the most critical components of an ecosystem, supporting many ecological niches and a rich diversity of flora and fauna. The ecological significance of these sites makes it imperative to study the changes in their inundation extent and propose necessary measures for their conservation. This study analyzes all 64 Ramsar sites in China based on their inundation patterns using Landsat imagery from 1991 to 2020. Annual composites were generated using the short-wave infrared thresholding technique from June to September to create inundation maps. The analysis was carried out on each Ramsar site individually to account for its typical behavior due to regional geographical and climatic conditions. The results of the inundation analysis for each site were subjected to the Mann-Kendall test to determine their trends. The analysis showed that 8 sites exhibited a significantly decreasing trend, while 14 sites displayed a significantly increasing trend. The accuracy of the analysis ranged from a minimum of 72.0% for Hubei Wang Lake to a maximum of 98.0% for Zhangye Heihe Wetland National Nature Reserve. The average overall accuracy of the sites was found to be 90.0%. The findings emphasize the necessity for conservation strategies and policies for Ramsar sites.

Exaggerated response to pattern reversal visual evoked potential among migraineurs.

OBJECTIVE: Visual evoked potential recording has reported ambiguous results among migraineurs, thus the present study explored the association of check-size and reversal rates on the latency and amplitude of pattern reversal VEP among migraineurs. METHOD AND MATERIAL: Monocular VEP responses for both eyes were recorded in 133 migraineurs and 111 controls. Checkerboard pattern with phase reversal frequency of 0.5, 1, 2 and 4 Hz and check-size of 16 × 16, 32 × 32, 64 × 64 and 128 × 128, i.e. spatial frequency of 0.475, 1.029, 2.056 and 4.112 cycle per degree (cpd) were used to record 100 responses each. Three-minutes gap was given after change of reversal frequency to a higher rate for next cycle of 4 check-size records. RESULT: A linear increase in latencies was observed with decreasing check-size in both groups, but migraineurs had significantly higher latencies at a given reversal rate. Amplitudes A1 and A2 were higher among migraineurs and amplitude A2 showed an inverted 'U' shaped trend with maximum amplitude at 32 × 32 check size (1.029 cpd) in both groups, with an exaggerated response among migraineurs. Check-size 32 × 32 i.e. spatial frequency of 1.029 behaves differently than other larger or smaller check-sizes. CONCLUSION: Variable VEP response for different visual stimuli may be due to differential activation of respective retinocortical pathways and cortical areas. The highest amplitude at modest check-size suggests a contributory role of foveal-parafoveal fibres in migraineurs. Exaggerated physiological response to visual stimuli may be responsible for higher amplitudes and prolonged latencies among migraineurs.

Exaggerated physiological VEP response as higher amplitudes and prolonged latencies, among migraineurs may be due to differential activation of respective retinocortical pathways and cortical areas.