A novel approach for estimation of aboveground biomass of a carbon-rich mangrove site in India.

Mangroves can play a crucial part in climate change mitigation policies due to their high carbon-storing capacity. However, the carbon sequestration potential of Indian mangroves generally remained unexplored to date. In this study, multi-temporal Sentinel-1 and 2 data-derived variables were used to estimate the AGB of a tropical carbon-rich mangrove forest of India. Ensemble prediction of multiple machine learning algorithms, including Random Forest (RF), Gradient Boosted Model (GBM), and Extreme Gradient Boosting (XGB), were used for AGB prediction. The multi-temporal dataset was used in two different ways to find the most suitable method of using them. The results of the analysis showed that the modeling field measured AGB with individual date data values results in estimates with root mean square errors (RMSE) ranging from 149.242 t/ha for XGB to 151.149 t/ha for the RF. Modeling AGB with the average and percentile metrics of the multi-temporal image stack improves the prediction accuracy of AGB, with RMSE ranging from 81.882 t/ha for the XGB to 74.493 t/ha for the RF. The AGB modeling using ensemble prediction showed further improvement in accuracy with an RMSE of 72.864 t/ha and normalized RMSE of 11.38%. In this study, the intra-seasonal variation of Sentinel-1 and 2 data for mangrove ecosystems was explored for the first time. The variations in remotely sensed variables could be attributed mainly to soil moisture availability and rainfall in the mangrove ecosystem. The efficiency of Sentinel-1 and 2 data-derived variables and ensemble prediction of machine learning models for Indian mangroves were also explored for the first time. The methodologies established in this study can be used in the future for accurate prediction and repeated monitoring of AGB for mangrove ecosystems.

A Real-Time Health 4.0 Framework with Novel Feature Extraction and Classification for Brain-Controlled IoT-Enabled Environments.

In this letter, we propose two novel methods for four-class motor imagery (MI) classification using electroencephalography (EEG). Also, we developed a real-time health 4.0 (H4.0) architecture for brain-controlled internet of things (IoT) enabled environments (BCE), which uses the classified MI task to assist disabled persons in controlling IoT-enabled environments such as lighting and heating, ventilation, and air-conditioning (HVAC). The first method for classification involves a simple and low-complex classification framework using a combination of regularized Riemannian mean (RRM) and linear SVM. Although this method performs better compared to state-of-the-art techniques, it still suffers from a nonnegligible misclassification rate. Hence, to overcome this, the second method offers a persistent decision engine (PDE) for the MI classification, which improves classification accuracy (CA) significantly. The proposed methods are validated using an in-house recorded four-class MI data set (data set I, collected over 14 subjects), and a four-class MI data set 2a of BCI competition IV (data set II, collected over 9 subjects). The proposed RRM architecture obtained average CAs of 74.30% and 67.60% when validated using datasets I and II, respectively. When analyzed along with the proposed PDE classification framework, an average CA of 92.25% on 12 subjects of data set I and 82.54% on 7 subjects of data set II is obtained. The results show that the PDE algorithm is more reliable for the classification of four-class MI and is also feasible for BCE applications. The proposed low-complex BCE architecture is implemented in real time using Raspberry Pi 3 Model B+ along with the Virgo EEG data acquisition system. The hardware implementation results show that the proposed system architecture is well suited for body-wearable devices in the scenario of Health 4.0. We strongly feel that this study can aid in driving the future scope of BCE research.

Impact of epilepsy and antiepileptic drugs on health and quality of life in Indian children.

BACKGROUND AND OBJECTIVES: Epilepsy affects the physical, cognitive, emotional, social wellbeing, and thereby the overall quality of life (QOL). Epilepsy is the most prevalent neurological disorder in the pediatric age group with a prevalence of 3.13 to 3.73 per 1000 in India. It is imperative for the primary caregiver to look beyond seizure control for improving wellbeing of children with epilepsy (CWE). Hence, there is a need to understand the predictors of QOL in Indian CWE. The objective of this study was to assess the impact of epilepsy and antiepileptic medications on the child's development, health, scholastic performance, and QOL and to identify the predictors of QOL. METHODS: This study was a cross-sectional hospital-based prospective study with sociodemographic, clinical data collected from 110 children (age 4-18 years). Seizure severity was assessed with the Hague Seizure Severity Scale, and adverse effects of antiepileptic drugs (AEDs) were assessed using the Adverse Event Profile Scale. The QOL was measured employing the Quality of Life in Children with Epilepsy (QOLCE) questionnaire. RESULTS: The mean total QOLCE score was 72.6 ±â€¯13.6. Among the subscale scores, memory had the highest mean of 86.5, and the lowest mean was observed for QOL item (40.4). There was no significant association of the total QOLCE score with any of the sociodemographic variables such as gender, place, socioeconomic status, paternal/maternal education, or family type. Children with more severe seizures had significantly lower energy and QOL subscale scores and greater depression and anxiety. Prolonged duration of epilepsy, frequent seizures, and recent seizures had a significant negative correlation with the mean total QOLCE score. Children with epilepsy who are on multiple AEDs, prolonged duration of AED intake, or poor adherence to AEDs have significantly lower total QOLCE score. Children manifesting adverse effects to AEDs had significantly lower overall QOL affecting all domains. CONCLUSION: Overall QOL in CWE is most compromised by polytherapy, poor adherence to medication, adverse effects of AEDs, hospitalization, and presence of developmental delay.

FDA-Approved Excipient N, N-Dimethylacetamide Attenuates Inflammatory Bowel Disease in In Vitro and In Vivo Models.

Inflammatory bowel disease (IBD) affects almost 7 million people worldwide and is increasing in incidence. While the precise pathogenesis of IBD remains unknown, the production of inflammatory cytokines and chemokines play a central role. We have previously found that N, N-dimethylacetamide (DMA), a widely used non-toxic drug excipient, suppresses cytokine and chemokine secretion in vitro and prevents inflammation-induced preterm birth in vivo. Using sandwich enzyme-linked immunosorbent assays (ELISAs), we tested whether DMA attenuates cytokine and chemokine secretion from LPS- or TNFα-stimulated human intestinal epithelial cells and human monocytes and HMGB1 release from RAW 264.7 cells. To test our hypothesis that the mechanism of DMA's effects in in vitro and in vivo models of IBD is inhibition of the NF-κB pathway, we used western blotting to track levels of the nuclear factor kappa B (NF-κB) inhibitory molecule I kappa B alpha (IκBα) in THP-1 human monocytes in the absence or presence of DMA. Finally, we induced colitis in C57Bl/6 mice with dextran sodium sulfate (DSS) and then tested whether i.p injections of DMA at 2.1 g/kg/day attenuates clinical and histopathologic signs of colitis. DMA attenuated cytokine and chemokine release from human intestinal epithelial cells and human monocytes and HMGB1 release from RAW 264.7 cells. Importantly, DMA prevented degradation of IκBα in THP-1 cells, thereby suggesting one mechanism for DMA's effects. Finally, we show here, for the first time, that DMA attenuates clinical and histologic features of DSS-induced colitis. Based on these data, DMA should be further explored in preclinical and clinical trials for its potential as novel drug therapy for IBD.

Microbiota in health and diseases.

The role of microbiota in health and diseases is being highlighted by numerous studies since its discovery. Depending on the localized regions, microbiota can be classified into gut, oral, respiratory, and skin microbiota. The microbial communities are in symbiosis with the host, contributing to homeostasis and regulating immune function. However, microbiota dysbiosis can lead to dysregulation of bodily functions and diseases including cardiovascular diseases (CVDs), cancers, respiratory diseases, etc. In this review, we discuss the current knowledge of how microbiota links to host health or pathogenesis. We first summarize the research of microbiota in healthy conditions, including the gut-brain axis, colonization resistance and immune modulation. Then, we highlight the pathogenesis of microbiota dysbiosis in disease development and progression, primarily associated with dysregulation of community composition, modulation of host immune response, and induction of chronic inflammation. Finally, we introduce the clinical approaches that utilize microbiota for disease treatment, such as microbiota modulation and fecal microbial transplantation.

Coronavirus Disease 2019 (COVID-19)-Associated Rhino-Orbito-Cerebral Mucormycosis: A Multi-Institutional Retrospective Study of Imaging Patterns.

BACKGROUND: Mucormycosis infection of the maxillofacial region and brain has been associated with coronavirus disease 2019 (COVID-19) infection. Mucormycosis was relatively a rare infection before COVID-19, and imaging findings are not very well described. MATERIALS AND METHODS: A retrospective imaging study of 101 patients diagnosed with COVID-19-associated mucormycosis by histopathology and/or culture was performed. All patients underwent computed tomography and/or magnetic resonance imaging based on the clinical condition of the patient and on consensus decision by the team of treating physicians. A simple 3-stage classification system based on imaging findings was adopted. RESULTS: One hundred one cases were included in the final analysis (mean age = 55.1 years; male/female ratio = 67:34). The affected patients had diabetes in 94% of the instances (n = 95), 80.1% (n = 81) received steroids), whereas 59.4% (n = 60) patients received supplemental oxygen. The majority underwent surgical intervention, whereas in 6 cases, patients were treated with antibiotic regimens. Sixty subjects improved following therapy, whereas 18 eventually succumbed to the illness. We noted a significant positive correlation between the imaging stage and outcomes. No association was seen between other clinical parameters and final clinical outcomes. Salient imaging findings include lack of normal sinonasal mucosal enhancement, perisinus inflammation, ischemic optic neuropathy, perineural spread, pachymeningeal enhancement, and presence of strokes. CONCLUSIONS: We describe the imaging findings in the largest cohort of patients with rhino-orbito-cerebral mucormycosis in the context of the current COVID-19 pandemic. A simplified staging system described here is helpful for standardized reporting and carries prognostic information.

A Novel Feature Extraction Framework for Four Class Motor Imagery Classification using Log Determinant Regularized Riemannian Manifold.

Brain-Computer Interface (BCI) systems allow the person in communicating with the external world using Electroencephalography (EEG). Motor Imagery (MI) based BCI systems play a vital role in interacting with the external environment. In this paper, we propose a novel robust feature extraction and classification framework for four class MI classification to improve the classification accuracy. The proposed architecture is developed using log-determinant (log-det) based Regularized Riemannian mean (LDRRM) and linear SVM. The robustness of features extracted from the four class MI data is improved to the outliers and noise by using the proposed LDRRM framework. We evaluated the performance of the proposed LDRRM classification framework on publicly available four class MI dataset 2a of BCI competition IV. The performance results show that the proposed LDRRM classification architecture obtained a mean classification accuracy of 69.12%, also achieved 1.54% higher classification accuracy when compared with the existing studies.

Comparative evaluation of anaesthetic efficacy and haemodynamic effects of a combination of isobaric bupivacaine with buprenorphine vs. isobaric levobupivacaine with buprenorphine for spinal anaesthesia - A double blinded randomised clinical trial.

BACKGROUND AND AIMS: Bupivacaine is the most frequently used local anaesthetic for spinal anaesthesia, however, use of levobupivacaine in clinical practice has advanced recently. This study aimed to compare the anaesthetic potency and haemodynamic effects of intrathecal bupivacaine with buprenorphine versus levobupivacaine with buprenorphine in infraumbilical surgeries. METHODS: This prospective randomised double blind study was conducted in seventy patients aged 18-65 years, American Society of Anesthesiologists grade I-II, scheduled for lower abdominal and lower limb surgery under spinal anaesthesia. The patients either received 0.5% isobaric racemic bupivacaine 3 ml with 2 µg/kg of buprenorphine (Group B) or 0.5% isobaric levobupivacaine 3 ml with 2 µg/kg of buprenorphine (Group L). The time for onset of sensory block between the two groups was the priomary end-point. Other measurements included haemodynamic variables, sensory and motor blockade characteristics, postoperative analgesia, and complications in the first 24 h. RESULTS: There was no significant difference in the onset of sensory block between the two groups. Sensory and motor blockade characteristics were similar between the two groups. However, there was significant fall in the heart rate at 5 min in Group B compared to Group L. There was statistically significant fall in systolic blood pressure in group B compared to Group L from 5 min up to 60 min and fall in diastolic blood pressure from 10 min to 45 min. CONCLUSION: Our study showed that onset of sensory block is similar between isobaric levobupivacaine with buprenorphine 37 38 and isobaric bupivacaine with buprenorphine.

The Relationship between Nerve Conduction Study and Clinical Grading of Carpal Tunnel Syndrome.

INTRODUCTION: Carpal Tunnel Syndrome (CTS) is the most common nerve entrapment. Subjective sensory symptoms are common place in patients with CTS, but sometimes they are not supported by objective findings in the neurological examination. Electrodiagnostic (EDx) studies are a valid and reliable means of confirming the diagnosis. The amplitudes along with the conduction velocities of the sensory nerve action potential and motor nerve action potential reflect the functional state of axons, and are useful parameters and complement the clinical grading in the assessment of severity of CTS. AIM: To conduct median nerve sensory and motor conduction studies on patients with carpal tunnel syndrome and correlate the relationship between nerve conduction study parameters and the clinical severity grading. MATERIALS AND METHODS: Based on clinical assessment, the study patients were divided into 03 groups with mild CTS, moderate CTS and severe CTS respectively as per Mackinnson's classification. Median and ulnar nerve conduction studies were performed on bilateral upper limbs of 50 patients with symptoms of CTS and 50 age and sex matched healthy control subjects. The relationship between the clinical severity grade and various nerve conduction study parameters were correlated. RESULTS: In this prospective case control study, 50 patients with symptoms consistent with CTS and 50 age and sex matched healthy control subjects were examined over a 10 month period. A total of 30 patients had unilateral CTS (right upper limb in 19 and left upper limb in 11) and 20 patients had bilateral CTS. Female to male ratio was 3.54 to 1. Age ranged from 25 to 81 years. The mean age at presentation was 49.68±11.7 years. Tingling paresthesias of hand and first three fingers were the most frequent symptoms 48 (98%). Tinel's and Phalen's sign were positive in 36 (72%) and 44 (88%) patients respectively. The mean duration of symptoms at presentation was 52.68±99.81 weeks. 16 patients (32%) had mild CTS, 25 (50%) had moderate CTS and 9 (18%) had severe CTS clinically. Prolongation of motor latency, latency difference between median and ulnar amplitudes, motor and sensory nerve conduction velocities, sensory latency between median and ulnar nerves, sensory nerve conduction velocities showed significant changes in comparison with controls. Among them sensory latency difference between median and ulnar nerves and sensory nerve conduction velocities are the most sensitive and specific for diagnosing CTS. CONCLUSION: In this study, there was a graded deterioration of electrophysiological parameters along with the clinical severity grades, thus reiterating the fact that NCS provide additional, independent objective evidence in the diagnosis and severity assessment of CTS. The sensory conductions were more sensitive than motor conductions in assessing CTS.

Isolation and characterization of a green tissue-specific promoter from pigeonpea [Cajanus cajan (L.) Millsp.].

Expression of rbcS genes encoding small subunit of rubisco, most abundant protein in green tissue, is regulated by at least three parameters--tissue type, light conditions and stage of development. One of the green tissue-specific promoters of rbcS gene family was isolated from pigeonpea by PCR. Expression of uidA gene encoding beta-glucuronidase in the transgenic tobacco plants under the control of pigeonpea rbcS promoter, clearly showed that this promoter was as strong as pea rbcS3A promoter characterized earlier. Study of the sequence similarity with pea rbcS3A promoter, especially the region (boxes I and III) that is required for rbcS3A expression, showed more than 50% divergence. In contrast, pigeonpea promoter sequence isolated in the present study was more similar to that of spinach and rice rbcS promoters.

Use of duodenal drainage in the diagnosis of acalculous gallbladder disease.

Because of overreliance on oral cholecystograms, we have re-evaluated a little used laboratory test, duodenal drainage. In a series of 56 patients with normal oral cholecystograms and upper GI series who underwent duodenal drainage and cholecystectomy, 53 (95%) were found to have positive microscopic examinations. We think duodenal drainage is a safe, simple test which should be used as an adjunct to history and physical examination and oral cholecystography. In regard to clinical follow-up, 96 per cent of patients followed were judged to have excellent-to-good results.

Redefining the World Health Organization algorithm for diagnosis of pneumonia with simple additional markers.

OBJECTIVES: WHO to examine the value of additional markers like history of previous respiratory distress and response to bronchodilator (BD) to redefine these guidelines. METHODS: Fifty (50) patients were analysed for presence of fever. Those who were febrile were put on antipyretic to look for resolution of tachypnea. Those who showed persistent tachypnea and those who were afebrile were analyzed for history of previous respiratory distress. Those who gave a positive history were challenged with BD. The association of persistent tachypnea and pulmonary infiltrates was recorded. RESULTS: Persistence of tachypnea after BD therapy was associated with pulmonary infiltrate in 7/8 (87.5%) whereas tachypnea persisted in 9/30 (30%) of those without infiltrates (p < 0.001). The proposed algorithm brings down the overuse of antibiotics from 78.9% to 26.3% (p <0.001) and also brings down the underuse of bronchodilators from 78.9% to 21.1 %(p<0.001). CONCLUSION: Adding simple markers like history of previous respiratory distress and response to BD therapy to the existing WHO guidelines it is possible to reliably differentiate pneumonia from acute exacerbation of asthma.

Monomethylarsonous acid (MMA(III)) and arsenite: LD(50) in hamsters and in vitro inhibition of pyruvate dehydrogenase.

Monomethylarsonous acid (MMA(III)), a metabolite of inorganic arsenic, has received very little attention from investigators of arsenic metabolism in humans. MMA(III), like sodium arsenite, contains arsenic in the +3 oxidation state. Although we have previously demonstrated that it is more toxic than arsenite in cultured Chang human hepatocytes, there are no data showing in vivo toxicity of MMA(III). When MMA(III) or sodium arsenite was administered intraperitoneally to hamsters, the LD(50)s were 29.3 and 112.0 micromol/kg of body wt, respectively. In addition, inhibition of hamster kidney or purified porcine heart pyruvate dehydrogenase (PDH) activity by MMA(III) or arsenite was determined. To inhibit hamster kidney PDH activity by 50%, the concentrations (mean +/- SE) of MMA(III) as methylarsine oxide, MMA(III) as diiodomethylarsine, and arsenite were 59.9 +/- 6.5, 62.0 +/- 1.8, and 115.7 +/- 2.3 microM, respectively. To inhibit activity of purified porcine heart PDH activity by 50%, the concentrations (mean +/- SE) of MMA(III) as methylarsine oxide and arsenite were 17.6 +/- 4.1 and 106.1 +/- 19.8 microM, respectively. These data demonstrate that MMA(III) is more toxic than inorganic arsenite, both in vivo and in vitro, and call into question the hypothesis that methylation of inorganic arsenic is a detoxication process.