Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological and neurological factors like sleep patterns, emotional states, anxiety, and memory. This research aims to explore various health factors affecting different demographic profiles and establish significant correlations among physiological and neurological factors in the post-COVID-19 state. To achieve these objectives, we have identified the post-COVID-19 health factors and based on these factors survey data were collected from COVID-recovered patients in Bangladesh. Employing diverse machine learning algorithms, we utilised the best prediction model for post-COVID-19 factors. Initial findings from statistical analysis were further validated using Chi-square to demonstrate significant relationships among these elements. Additionally, Pearson's coefficient was utilized to indicate positive or negative associations among various physiological and neurological factors in the post-COVID-19 state. Finally, we determined the most effective machine learning model and identified key features using analytical methods such as the Gini Index, Feature Coefficients, Information Gain, and SHAP Value Assessment. And found that the Decision Tree model excelled in identifying crucial features while predicting the extent of post-COVID-19 impact.

Dig up tall fescue plastid genomes for the identification of morphotype-specific DNA variants.

BACKGROUND: Tall fescue (Festuca arundinacea Schreb.) is an important cool-season perennial grass species. Hexaploid tall fescue has three distinct morphotypes used either as forage or turf purposes. Its chloroplast genome is conserved due to it being maternally inherited to the next generation progenies. To identify morphotype-specific DNA markers and the genetic variations, plastid genomes of all three tall fescue morphotypes, i.e., Continental cv. Texoma MaxQ II, Rhizomatous cv. Torpedo, and Mediterranean cv. Resolute, have been sequenced using Illumina MiSeq sequencing platform. RESULTS: The plastid genomes of Continental-, Rhizomatous-, and Mediterranean tall fescue were assembled into circular master molecules of 135,283 bp, 135,336 bp, and 135,324 bp, respectively. The tall fescue plastid genome of all morphotypes contained 77 protein-coding, 20 tRNAs, four rRNAs, two pseudo protein-coding, and three hypothetical protein-coding genes. We identified 630 SNPs and 124 InDels between Continental and Mediterranean, 62 SNPs and 20 InDels between Continental and Rhizomatous, and 635 SNPs and 123 InDels between Rhizomatous and Mediterranean tall fescue. Only four InDels in four genes (ccsA, rps18, accD, and ndhH-p) were identified, which discriminated Continental and Rhizomatous plastid genomes from the Mediterranean plastid genome. Here, we identified and reported eight InDel markers (NRITCHL18, NRITCHL35, NRITCHL43, NRITCHL65, NRITCHL72, NRITCHL101, NRITCHL104, and NRITCHL110) from the intergenic regions that can successfully discriminate tall fescue morphotypes. Divergence time estimation revealed that Mediterranean tall fescue evolved approximately 7.09 Mya, whereas the divergence between Continental- and Rhizomatous tall fescue occurred about 0.6 Mya. CONCLUSIONS: To our knowledge, this is the first report of the assembled plastid genomes of Rhizomatous and Mediterranean tall fescue. Our results will help to identify tall fescue morphotypes at the time of pre-breeding and will contribute to the development of lawn and forage types of commercial varieties.

Fertilizer use gaps of women-headed households under diverse rice-based cropping patterns: Survey-based evidence from the Eastern Gangetic Plain, South Asia.

Women-headed households (WHHs) have limited access to agricultural inputs and extension services relative to male-headed households (MHHs) which may lead to yield gaps, poorer livelihoods and greater food insecurity. Since lower fertilizer use by WHHs will restrict crop yield, we examined how limited access to fertilizer inputs and extension services was reflected in nutrient use gaps relative to Government recommendations. A total of 80 WHHs were randomly selected for interview from four Agro-ecological Zones (AEZs) covering five representative districts of Bangladesh to assess, for the first time, nutrient use gaps of WHHs under five rice-based cropping patterns. Data collected from 576 MHHs (reported elsewhere) was also utilized to examine nutrient use gaps, crop yields and farm income between MHHs and WHHs. The nutrient use rates were compared with the government Fertilizer Recommendation Guides (FRG): FRG-2012 and FRG-2018. The WHHs underuse N, P, K, S and Zn under fully rice-based cropping patterns, while MHHs overuse those nutrients, but WHH tend to overuse N, P, and K for patterns with potato and watermelon crops. WHHs seem to prioritize high-value crops for fertilizer use, but even yield was 14%, 11%, 17% and 15% lower for irrigated rice, maize, potato and watermelon, respectively compared to smallholder MHHs under diverse rice-based cropping patterns. Overall, WHHs had 10% and 14% lower farm incomes than MHHs under fully rice-based and high-value cropping patterns, respectively. Financial losses for both WHHs and the government due to overuse of NPK on high-value potato crops were estimated at around 63 and 115 USD ha-1, respectively. However, the socio-demographic information suggested that effective extension services targeted to WHH, easing of social restrictions on their mobility, access of WHHs to fertilizers at Govt. fixed price and improved financial capability through better credit access could bring WHHs towards balanced fertilizer use practices in the EGP.

Multidisciplinary Conservative Treatment Outcomes of in-Patient Physiotherapy Set-Up Among Patients with Lumbar Disc Herniation in Dhaka City, Bangladesh: A Retrospective, Cross-Sectional Study.

Background: The study aimed to determine the outcome of Multidisciplinary physiotherapist-led conservative treatment of lumbar disc herniation at an in-patient set-up of a specialized spine center in Dhaka, Bangladesh. Methods: This was a retrospective cross-sectional study of 228 cases completing treatment and follow-up sessions. The outcome was evaluated as pain at rest and five different functional positions, neurological recovery, and Magnetic resonance imaging (MRI) changes during discharge and follow-up. Results: 80.3% had a complete recovery with a typical motor and sensory status, no limitations in straight leg raise (SLR), no cauda equina symptom (CES), and no or <3 pain during more than 30 minutes of daily living activities. Statistically significant changes were noted at all outcome measures at the follow-up (day 90), compared to baseline (day 1) P<0.01. In the posthoc tests, pain, SLR, and CES had the most significant improvement at discharge (day 12) compared to the baseline (P < 0.01) and at follow-up compared to discharge (P < 0.01). No major adverse events noted. Conclusion: Physiotherapist-led in-patient treatment results in significant resting and functional pain outcomes in 12 days. Also, the improvements in neurological recovery and normalizing disc position are statistically significant in 90 days.

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN.

Deep learning-based models have achieved significant success in detecting cardiac arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the performance of such models, we have developed a novel hybrid hierarchical attention-based bidirectional recurrent neural network with dilated CNN (HARDC) method for arrhythmia classification. This solves problems that arise when traditional dilated convolutional neural network (CNN) models disregard the correlation between contexts and gradient dispersion. The proposed HARDC fully exploits the dilated CNN and bidirectional recurrent neural network unit (BiGRU-BiLSTM) architecture to generate fusion features. As a result of incorporating both local and global feature information and an attention mechanism, the model's performance for prediction is improved. By combining the fusion features with a dilated CNN and a hierarchical attention mechanism, the trained HARDC model showed significantly improved classification results and interpretability of feature extraction on the PhysioNet 2017 challenge dataset. Sequential Z-Score normalization, filtering, denoising, and segmentation are used to prepare the raw data for analysis. CGAN (Conditional Generative Adversarial Network) is then used to generate synthetic signals from the processed data. The experimental results demonstrate that the proposed HARDC model significantly outperforms other existing models, achieving an accuracy of 99.60%, F1 score of 98.21%, a precision of 97.66%, and recall of 99.60% using MIT-BIH generated ECG. In addition, this approach significantly reduces run time when using dilated CNN compared to normal convolution. Overall, this hybrid model demonstrates an innovative and cost-effective strategy for ECG signal compression and high-performance ECG recognition. Our results indicate that an automated and highly computed method to classify multiple types of arrhythmia signals holds considerable promise.

An assessment of disability and quality of life in people with spinal cord injury upon discharge from a Bangladesh rehabilitation unit.

DESIGN: Cross-sectional. OBJECTIVES: The purpose of the study was to determine the level of disability and quality of life of people with spinal cord injury at the end of their inpatient rehabilitation at a rehabilitation center in Bangladesh. These outcomes were considered indicators of successful rehabilitation and a basis for comparing the success of reintegration into community. SETTING: Center for the Rehabilitation of the Paralyzed, Bangladesh. METHODS: Two standard structured questionnaires, the WHODAS 2.0 and WHOQOL-BREF, was used to collect data to assess level of disability and quality of life (QOL). Data were analyzed using Mann-Whitney-U test and Kruskal-Wallis test. RESULTS: One hundred participants (91 men and 9 women) with SCI were recruited. Just prior to discharge from in-patient rehabilitation at CRP people with SCI perceived themselves overall as having on average a mild level of disability, and good QOL in physical, psychological, and environmental health domains. They indicated poor QOL in the social health domain. There were some specific differences in various WHODAS 2.0 Domains and overall scores when comparing age, gender, type and level of injury, occupation, and income. Between-group comparisons indicated that male participants had a significantly higher quality of life in the Environmental Health Domain and those with a paraplegic injury had a significantly higher quality of life in the Physical Health Domain. CONCLUSION: By the end of their rehabilitation people with SCI had a relatively positive perception of level of disability and QOL. However, the results of other research has found that post-discharge their disability level increase and QOL decrease across all domains. Hence, it is recommended that more monitoring of level of disability and QOL is conducted post-discharge, along with a greater focus on community-based rehabilitation strategies and procedures to contribute to long-term reduction in level of disability and improved QOL.

High index core flat fiber surface plasmon resonance bio-sensor.

Due to tremendous design flexibility and ease of light control capability, the photonic crystal fiber offers efficient, flexible, and miniaturized plasmonic biosensors with attractive features. In this work, a high index (GeO2 doped silica) core flat fiber is proposed and analyzed for RI sensing ranging from 1.53 to 1.60. A rectangular analyte channel is created on top of a flat fiber to better handle the liquid analyte. To introduce the plasmonic effect, TiO2 and gold are deposited to the analyte channel. The sensing performance is carried out for two operating wavelengths, as two peaks are obtained for each analyte. The second operating wavelength shows better sensing performance than the first one. However, the proposed sensor offers average wavelength sensitivity of 5000 nm/RIU with a sensor resolution of 2×10-05 RIU. In addition, the proposed sensor shows identical linearity, which is quite rare in prior sensors. Moreover, the proposed flat sensor provides outstanding detection accuracy of 0.01nm-1, detection limit of 79.28 nm, signal to noise ratio of -4.1497dB, and figure of merit of 50RIU-1. Owing to outstanding sensing performance and a unique detection range, this sensor can be effectively used in biological and organic analyte sensing applications.

Multimodal Hybrid Deep Learning Approach to Detect Tomato Leaf Disease Using Attention Based Dilated Convolution Feature Extractor with Logistic Regression Classification.

Automatic leaf disease detection techniques are effective for reducing the time-consuming effort of monitoring large crop farms and early identification of disease symptoms of plant leaves. Although crop tomatoes are seen to be susceptible to a variety of diseases that can reduce the production of the crop. In recent years, advanced deep learning methods show successful applications for plant disease detection based on observed symptoms on leaves. However, these methods have some limitations. This study proposed a high-performance tomato leaf disease detection approach, namely attention-based dilated CNN logistic regression (ADCLR). Firstly, we develop a new feature extraction method using attention-based dilated CNN to extract most relevant features in a faster time. In our preprocessing, we use Bilateral filtering to handle larger features to make the image smoother and the Ostu image segmentation process to remove noise in a fast and simple way. In this proposed method, we preprocess the image with bilateral filtering and Otsu segmentation. Then, we use the Conditional Generative Adversarial Network (CGAN) model to generate a synthetic image from the image which is preprocessed in the previous stage. The synthetic image is generated to handle imbalance and noisy or wrongly labeled data to obtain good prediction results. Then, the extracted features are normalized to lower the dimensionality. Finally, extracted features from preprocessed data are combined and then classified using fast and simple logistic regression (LR) classifier. The experimental outcomes show the state-of-the-art performance on the Plant Village database of tomato leaf disease by achieving 100%, 100%, 96.6% training, testing, and validation accuracy, respectively, for multiclass. From the experimental analysis, it is clearly demonstrated that the proposed multimodal approach can be utilized to detect tomato leaf disease precisely, simply and quickly. We have a potential plan to improve the model to make it cloud-based automated leaf disease classification for different plants.

Unbalanced fertilizer use in the Eastern Gangetic Plain: The influence of Government recommendations, fertilizer type, farm size and cropping patterns.

Intensive cropping systems with diverse cropping patterns present a challenge for nutrient management on smallholder farms. Government-endorsed recommendations for crop fertilizer use are designed to assist farmers achieve profitable and balanced nutrient inputs, but it is unclear how closely farmers follow these recommendations. We identified farmers' current nutrient use gaps (overuse or underuse) relative to the Government-endorsed recommended nutrient doses in two cropping patterns in three representative Agro-ecological Zones of Bangladesh. A total of 330 farms were surveyed in 2019 from three farm size categories (referred to as large-, medium and small-scale) and their gaps in nutrient use were assessed relative to Government-endorsed Fertilizer Recommendation Guides (FRG) published in 2012 and in 2018: FRG-2012 and FRG-2018. The large- and medium-scale farms used 11-16%, 80-90% and 21-30%, respectively, over-doses of NPK in the cropping season under fully rice-based cropping pattern relative to FRG-2012 recommendations, while the over-dose levels were much lower for small-scale farms. Small-scale farms used much less than recommended S, Mg, Zn, B and organic manure (OM) rates relative to FRG-2012. The FRG-2018, which increased N and K recommendations but decreased the P recommendation for rice crops relative to FRG-2012, shows that all farms can decrease the dose of P (by 50%) while small-scale farms need to increase the dose of N (7%), K (16%), S (20%) and to apply Zn in the fully rice-based cropping pattern. On the other hand, the farms could greatly reduce NPK (19%, 86% and 44%, respectively) use while increasing S (14%), Mg, Zn, B and OM use relative to FRG-2018 in the pattern with the high-value potato crop. To increase crop profitability, enhance food security and save Government treasury in the Eastern Gangetic Plain enabling approaches are needed to effectively communicate the benefits of balanced nutrient use practices to farmers.

Transcriptome of Endophyte-Positive and Endophyte-Free Tall Fescue Under Field Stresses.

Tall fescue is one of the primary sources of forage for livestock. It grows well in the marginal soils of the temperate zones. It hosts a fungal endophyte (Epichloë coenophiala), which helps the plants to tolerate abiotic and biotic stresses. The genomic and transcriptomic resources of tall fescue are very limited, due to a complex genetic background and outbreeding modes of pollination. The aim of this study was to identify differentially expressed genes (DEGs) in two tissues (pseudostem and leaf blade) between novel endophyte positive (E+) and endophyte-free (E-) Texoma MaxQ II tall fescue genotypes. Samples were collected at three diurnal time points: morning (7:40-9:00 am), afternoon (1:15-2:15 pm), and evening (4:45-5:45 pm) in the field environment. By exploring the transcriptional landscape via RNA-seq, for the first time, we generated 226,054 and 224,376 transcripts from E+ and E- tall fescue, respectively through de novo assembly. The upregulated transcripts were detected fewer than the downregulated ones in both tissues (S: 803 up and 878 down; L: 783 up and 846 down) under the freezing temperatures (-3.0-0.5°C) in the morning. Gene Ontology enrichment analysis identified 3 out of top 10 significant GO terms only in the morning samples. Metabolic pathway and biosynthesis of secondary metabolite genes showed lowest number of DEGs under morning freezing stress and highest number in evening cold condition. The 1,085 DEGs were only expressed under morning stress condition and, more importantly, the eight candidate orthologous genes of rice identified under morning freezing temperatures, including orthologs of rice phytochrome A, phytochrome C, and ethylene receptor genes, might be the possible route underlying cold tolerance in tall fescue.

Farmers' fertilizer use gaps relative to government recommendations in the saline coastal zone of the Ganges Delta.

Overuse or underuse of nutrients relative to recommendations is a likely cause of crop yield gaps and an impediment to the achievement of food security. Government-endorsed recommendations are developed to deliver the best evidence-based advice on balanced fertilizer; however, deviations of farmers' nutrient use from the recommendations are rarely examined. This study chose the salt-affected coastal zone of the Ganges Delta, where low crop productivity and cropping intensity by smallholders limit their income, to determine current nutrient use gaps for the first time of three cropping patterns in two representative districts of Bangladesh. A total of 246 farms were surveyed from three farm sizes. Farmers' nutrient use gaps were compared with Fertilizer Recommendation Guides published in 2012 (FRG-2012) and 2018 (FRG-2018). Relative to FRG-2012 recommendations, farmers used 12%, 70%, and 11% overdoses of N, P, and K, respectively, under two fully rice-based cropping patterns, but the level of overdoses increased with farm size. Rates of K (14%), S (28%), and Zn use were below the FRG-2012 recommendations, especially for the smallest category of farms. However, the FRG-2018, increased recommended N (5%), K (62%), S (12%), and Zn rates but reduced P (25%) rates for fully rice-based cropping patterns. In contrast with rice, regardless of farm size, farmers applied overdose nutrients to watermelon but compensated with underdoses in the subsequent monsoon rice implying that farmers prioritized fertilizer expenditure on the most profitable crop. For the cropping pattern with watermelon, farmers could reduce the use of N (69%) and P (46%) and increase the use of K (48%), S (5%), and B. Reducing NPK use gaps can save treasury for both the farmers and the governments by 39.1 and 73.8 USD ha-1, respectively, under fully rice-based cropping patterns. Finally, our findings suggest there is scope to promote crop yields and sustainable intensification through balanced fertilizer use in a vulnerable saline region. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-022-00797-1.

Incidence, severity and time course of pressure injuries over the first two years following discharge from hospital in people with spinal cord injuries in Bangladesh.

DESIGN: Cohort study embedded in a clinical trial. SETTING: Community, Bangladesh. OBJECTIVES: To determine the incidence, severity and time course of pressure injuries over the first two years following discharge from hospital in people with spinal cord injuries (SCI) in Bangladesh. METHODS: Participants (n = 186) were contacted by telephone 39 times and assessed face-to-face 4 to 6 times over the two years following discharge. At each point of contact the presence and severity of pressure injuries were determined using the Pressure Ulcer Scale for Healing (PUSH). Survival analyses were conducted to determine the time course of development of pressure injuries and recovery from pressure injuries. Lasso regression was used to construct multivariable prediction models. RESULTS: Seventy-seven participants (41%; 95% CI 34% to 49%) developed at least one pressure injury in the first two years after discharge (incidence rate 0.27 per person-year, 95% CI 0.22 to 0.34). Most pressure injuries were on the sacrum (23%). Pressure injuries took a median (IQR) of 40 (29 to 57) days to heal. The median (IQR) peak PUSH score was 11.0/17 (8.0 to 13.5). The multivariable prediction models had poor predictive properties (maximum c-statistic 0.75). CONCLUSION: Pressure injuries impose a large health burden on people with SCI in Bangladesh. However, they are difficult to predict, treat and prevent. Further research is needed to identify who is at most risk and to find solutions for the treatment and prevention of pressure injuries in Bangladesh and other low-middle income countries.

Designing of Hollow Core Grapefruit Fiber Using Cyclo Olefin Polymer for the Detection of Fuel Adulteration in Terahertz Region.

A grapefruit-shape hollow-core liquid infiltrated photonic crystal fiber (LI-PCF) is proposed and evaluated to identify the percentage of kerosene in adulterated petrol. The proposed hollow-fiber sensor is designed with Cyclo Olefin Polymer (Zeonex) and likely to be filled with different samples of petrol which is adulated by the kerosene up to 100%. Considering the electromagnetic radiation in THz band, the sensing properties are thoroughly investigated by adopting finite element method (FEM) based COMSOL Multiphysics software. However, the proposed sensor offers a very high relative sensitivity (RS) of 97.27% and confinement loss (CL) less than 10-10 dB/m, and total loss under 0.07 dB/cm, at 2 THz operating frequency. Besides that, the sensor also possesses a low effective material loss (EML), high numerical aperture (NA), and large Marcuse spot size (MSS). The sensor structure is fabrication feasible through existing fabrication methodologies consequently making this petrol adulteration sensor a propitious aspirant for real-life applications of petrol adulteration measurements in commercial and industrial sensing.

Drought Responsive Putative Marker-Trait Association in Tall Fescue as Influenced by the Presence of a Novel Endophyte.

Tall fescue (Festuca arundinacea Schreb.) is one of the most important cool-season perennial obligatory outcrossing forage grasses in the United States. The production and persistence of tall fescue is significantly affected by drought in the south-central United States. Shoot-specific endophyte (Epichloë coenophiala)-infected tall fescue showed superior performance under both biotic and abiotic stress conditions. We performed a genome-wide association analysis using clonal pairs of novel endophyte AR584-positive (EP) and endophyte-free (EF) tall fescue populations consisting of 205 genotypes to identify marker-trait associations (MTAs) that contribute to drought tolerance. The experiment was performed through November 2014 to June 2018 in the field, and phenotypic data were taken on plant height, plant spread, plant vigor, and dry biomass weight under natural summer conditions of sporadic drought. Genotyping-by-sequencing of the population generated 3,597 high quality single nucleotide polymorphisms (SNPs) for further analysis. We identified 26 putative drought responsive MTAs (17 specific to EP, eight specific to EF, and one in both EP and EF populations) and nine of them (i.e., V.ep_10, S.ef_12, V.ep_27, HSV.ef_31, S.ep_30, SV.ef_32, V.ep_68, V.ef_56, and H.ef_57) were identified within 0.5 Mb region in the tall fescue genome (44.5-44.7, 75.3-75.8, 77.5-77.9 and 143.7-144.2 Mb). Using 26 MTAs, 11 tall fescue genotypes were selected for subsequent study to develop EP and EF drought tolerant tall fescue populations. Ten orthologous genes (six for EP and four for EF population) were identified in Brachypodium genome as potential candidates for drought tolerance in tall fescue, which were also earlier reported for their involvement in abiotic stress tolerance. The MTAs and candidate genes identified in this study will be useful for marker-assisted selection in improving drought tolerance of tall fescue as well opening avenue for further drought study in tall fescue.

Phytochemical profiling of Blumea laciniata (Roxb.) DC. and its phytopharmaceutical potential against diabetic, obesity, and Alzheimer's.

Blumea laciniata (Roxb.) DC. is a folk medicinal annual herb of the Asteraceae family that grows in South and Southeast Asia. In order to evaluate its phytopharmaceutical potential against diabetic, obesity, and Alzheimer's, a comprehensive phytochemical profile, in vitro and in silico enzyme inhibitory activity against α-amylase, α-glucosidase, lipase, cholinesterases, and tyrosinase along with in vitro antioxidant activity were performed. Additionally, in vivo antidiabetic activity and acute toxicity were also evaluated. The total phenolic content in various organs follows the following order: old leaf > flower bud > young leaf > flower > young stem > old stem > root, while total flavonoids followed the order: flower bud > old leaf > young leaf > flower > young stem > old stem > root. The identified phenolic compounds are 3,4-dihydroxybenzoic acid, caffeic acid, vanillic acid, p-coumaric acid, syringic acid, rosmarinic acid, trans-cinnamic acid, catechin, catechol, (-) epicatechin, rutin, quercetin, myricetin, and kaempferol, which are also expressed differently in various organs. Solvent extracts demonstrated strong antioxidant activity as well as varying levels of inhibition against the enzymes tested, with strong inhibitory activity against α-amylase, α-glucosidase, and lipase. Thirteen phenolic compounds displayed strong binding affinity in silico against studied enzymes, thus documented as bioactive. Furthermore, solvent extracts significantly suppressed blood glucose levels in mice with induced diabetes and extracts were not acutely toxic. The results suggest that Blumea laciniata (Roxb.) DC. could be a potential candidate for developing new phytopharmaceuticals and bioactive ingredients.

Petrophysical and petrographic characteristics of Barail Sandstone of the Surma Basin, Bangladesh.

The Barail sandstone in the Surma Basin is a medium- to coarse-grained pinkish-colored rock exposed near the northeastern margin of Bangladesh. In this study, we evaluated the reservoir quality of the Barail sandstone based on its petrophysical and petrographic characteristics. Petrophysical analyses of outcropped samples showed that sandstones are made up of 16.48% porosity and 132.48 mD permeability. Sandstone density ranges from 1.94 g/cm3 to 2.37 g/cm3, with a mean value of 2.12 g/cm3, shown as moderately compacted sandstone. Integrated data such as bulk density, porosity, permeability, Rock Quality Index (RQI), Normalized Porosity Index (NPI), Flow Zone Indicator (FZI), compressive strength, etc. with their relationships indicate that Barail sandstone owing characters to become a good petroleum reservoir. The rock samples consisted mainly of quartz with an insignificant amount of rock fragments and plagioclase feldspar and are categorized as sub-arkose to sub-litharenite. The rock samples also contains lithic (andesine, microcline, muscovite, biotite, etc.) of granitic and gneissic fabric and some volcanic product like aguite, albite, andesine, garnet, spinel and ulvo-spinel indicating the source of nearby orogeny. The euhedral to subhedral shape of the quartz grain in a porphyritic texture, moderately sorted with a smaller amount of clay minerals indicating the moderately mature rock type. The iron oxide border around the quartz grain also indicates that the Barail sandstone was deposited under dry climatic condition.

Methanol, ethyl acetate and n-hexane extracts of Tragia involucrata L. leaves exhibit anxiolytic, sedative and analgesic activity in Swiss albino mice.

INTRODUCTION: Tragia involucrata L. have been utilized as traditional medicine in Indian subcontinent for the treatment of numerous illnesses such as inflammation, pain and skin infection. In this current study we sought to assess the anxiolytic, sedative and analgesic activity of Tragia involucrata L. leaves extract. MATERIALS AND METHODS: We first performed a phytochemical screening test of the leaves extracts following standard phytochemical screening protocols. We next examined the anxiolytic and sedative activity of crude methanol (TIME), ethyl acetate (TIEAE) and n-Hexane (TIHE) extract of Tragia involucrata L. leaves using mouse behavioral models such as elevated plus-maze test and pentobarbital-induced sleeping time test, respectively. Likewise, we evaluated the analgesic activity using acetic acid induced writhing test and formalin induced paw licking test. Additionally, we performed a quantitative analysis of heavy metals content of Tragia involucrata L. leaves by overnight digestion in concentrated nitric acid (HNO3). RESULTS: Phytochemical screening demonstrated that TIME, TIEAE and TIHE contain flavonoids, alkaloids, tannins, phenols, terpenoids and sterols. Administration of these extracts resulted in higher number of open arm entry, lower number of close arm entry and higher time spent in open arm compared to control treatment (p < 0.05). Moreover, these treatments decreased the onset of sleep time and increased the duration of sleep compared to control treated mice (all p < 0.05). Likewise, extracts treated mice exhibited decreased number of writhing as well as lower acute phase and late phase duration compared to control treatment (all p < 0.05). The average level of As and Fe in Tragia involucrata L. leaves was 5.16 ± 0.012 ppm and 2.76 ± 0.015 ppm, respectively. CONCLUSION: Results from this study support that Tragia involucrata L. leaves extracts exhibit an anxiolytic, sedative and analgesic activity in mice.

The cost of providing a community-based model of care to people with spinal cord injury, and the healthcare costs and economic burden to households of spinal cord injury in Bangladesh.

DESIGN: Descriptive. SETTING: Community, Bangladesh. OBJECTIVES: To determine the costs associated with providing a community-based model of care delivered as part of the CIVIC trial to people discharged from hospital with recent spinal cord injury (SCI), and to determine the economic burden to households. METHODS: Records were kept of the costs of providing a community-based model of care to participants of the CIVIC trial. Data were also collected at discharge and 2 years post discharge to capture out-of-pocket healthcare costs over the preceding 2 years, and the number of participants suffering catastrophic health expenditure and illness-induced poverty. RESULTS: The mean cost of providing the community-based model of care to participants assigned to the intervention group (n = 204) was US$237 per participant. The mean out-of-pocket healthcare cost over the first 2 years post discharge was US$472 per participant (n = 410), and US$448 per control participant (n = 206). Median (IQR) equivalent annual household incomes prior to SCI and at 2 years post discharge were US$721 (US$452-1129) and US$464 (US$214-799), respectively. Of the 378 participants alive at 2 years, 324 (86%) had catastrophic health expenditure, and 161 of 212 participants who were not in poverty prior to injury (76%) were pushed into illness-induced poverty within 2 years of injury. CONCLUSION: The cost of providing community-based support to people with SCI for 2 years post discharge in Bangladesh is relatively inexpensive but an overwhelming majority of households rapidly experience financial catastrophe, and most fall into poverty.

A community-based intervention to prevent serious complications and death 2 years after discharge in people with spinal cord injury in Bangladesh (CIVIC): a randomised trial.

STUDY DESIGN: Randomised controlled trial. OBJECTIVES: To determine the effectiveness of a sustainable community-based intervention designed to prevent serious complications and death 2 years after discharge in people with spinal cord injury in Bangladesh. SETTING: Bangladesh. METHODS: A pragmatic randomised controlled trial was undertaken. People who had sustained a spinal cord injury in the preceding 2 years, were wheelchair-dependent, and were about to be discharged from hospital in Bangladesh were recruited and randomised to an Intervention or Control group using a concealed allocation procedure stratified by level of lesion (tetraplegia/paraplegia). Participants in the Intervention group received 36 phone calls and three home visits over the first 2 years following discharge. All participants received usual post-discharge care. Survival status and date of death were determined by blinded assessors 2 years after randomisation. RESULTS: Between July 2015 and March 2018, 410 participants were randomised (204 to Intervention, 206 to Control). There was no loss to follow up. At 2 years, 15 (7.4%) participants in the Intervention group and 16 (7.8%) participants in the Control group had died (hazard ratio from unadjusted Cox model = 0.93 [95% CI, 0.46 to 1.89]; p from log rank test 0.85). There were no clinically important or statistically significant average causal effects of intervention on the incidence or severity of complications. CONCLUSION: A program of community-based care for people with recent spinal cord injury in Bangladesh involving frequent phone contact and occasional in-person contact with a health professional after discharge from hospital is no better at preventing death at 2 years than usual care.

Understanding how a community-based intervention for people with spinal cord injury in Bangladesh was delivered as part of a randomised controlled trial: a process evaluation.

DESIGN: Mixed methods study SETTING: Community, Bangladesh OBJECTIVES: To understand how a community-based intervention for people with spinal cord injury (SCI) in Bangladesh was delivered as part of a randomised controlled trial and to gauge the perceptions of participants and healthcare professionals to the intervention. METHODS: A community-based intervention was administered to 204 participants as part of a large randomised controlled trial (called the CIVIC trial). Case-managers followed-up participants with regular telephone calls and home visits over the first 2 years after discharge. The following data were collected alongside the trial: (i) chart audit of telephone calls and home visits (ii) recordings of 20 telephone calls (iii) interviews with 14 Intervention participants and four healthcare professionals including three case-managers. RESULTS: Participants received the target number of telephone calls and home visits. Pressure injuries were identified as a problem during at least one telephone call by 43% of participants. Participants and case-managers valued regular telephone calls and home visits, and believed that calls and visits prevented complications and alleviated social isolation. Participants trusted case-managers and were confident in the care and advice provided. Case-managers expressed concerns that people with SCI in Bangladesh face many problems impacting on well-being and motivation stemming from poverty, limited employment opportunities, societal attitudes and inaccessible environments. CONCLUSION: A community-based intervention involving regular telephone calls and home visits was administered as intended and was well received by the recipients of the care. Nonetheless, people with SCI in Bangladesh face economic and social problems which cannot be fully addressed by this type of intervention alone.