RESUMO
This study addresses the pressing challenge of inefficient waste management practices within the Rajshahi City Corporation (RCC), Bangladesh. Despite rapid urbanization and escalating waste generation rates, RCC struggles with diverse waste disposal practices, limited supervision, irregular waste collection schedules, and inadequate disposal infrastructure. In this context, this study examines the possible improvements that could be made by combining the Internet of Things (IoT), artificial intelligence (AI), and Android application to improve waste management methods in the RCC. The study's foundation is a vast amount of information gathered from residents, with particular attention paid to waste disposal methods, the role of the local government, the frequency of waste collection, and public attitudes toward waste management. The results point to a complicated waste management environment with a range of waste disposal practices, little supervision, irregular waste collection, and insufficient disposal methods. The importance of RCC in waste management is emphasized, highlighting the need for proactive measures including effective monitoring, constant waste collection, and routine drain cleaning. Additionally, it is suggested that combining IoT, AI, and Android technology is a possible way to improve waste management procedures. These technologies have the potential to increase productivity, lessen their negative effects on the environment, and produce cleaner, more sustainable urban environments.
RESUMO
Imbalances in levels of glutamate (GLU) and gamma-aminobutyric acid (GABA) and their sub-second signaling dynamics occur in several brain disorders including traumatic brain injury, epilepsy, and Alzheimer's disease. The present work reports on the optimization and in vivo testing of a silicon (Si) multifunctional biosensor probe for sub-second simultaneous real-time detection of GLU and GABA. The Si probe features four surface-functionalized platinum ultramicroelectrodes (UMEs) for detection of GLU and GABA, a sentinel site, and integrated microfluidics for in-situ calibration. Optimal enzyme concentrations, size-exclusion phenylenediamine layer and micro spotting conditions were systematically investigated. The measured GLU sensitivity for the GLU and GABA sites were as high as 219 ± 8 nA µM-1 cm-2 (n = 3). The measured GABA sensitivity was as high as 10 ± 1 nA µM-1 cm-2 (n = 3). Baseline recordings (n = 18) in live rats demonstrated a useful probe life of at least 11 days with GLU and GABA concentrations changing at the levels of 100's and 1000's of µM and with expected periodic bursts or fluctuations during walking, teeth grinding and other activities and with a clear difference in the peak amplitude of the sensor fluctuations between rest (low) and activity (higher), or when the rat was surprised (a reaction with no movement). Importantly, the probe could improve methods for large-scale monitoring of neurochemical activity and network function in disease and injury, in live rodent brain.
RESUMO
SARS-CoV-2, the virus that causes COVID-19, is a current concern for people worldwide. The virus has recently spread worldwide and is out of control in several countries, putting the outbreak into a terrifying phase. Machine learning with transcriptome analysis has advanced in recent years. Its outstanding performance in several fields has emerged as a potential option to find out how SARS-CoV-2 is related to other diseases. Idiopathic pulmonary fibrosis (IPF) disease is caused by long-term lung injury, a risk factor for SARS-CoV-2. In this article, we used a variety of combinatorial statistical approaches, machine learning, and bioinformatics tools to investigate how the SARS-CoV-2 affects IPF patients' complexity. For this study, we employed two RNA-seq datasets. The unique contributions include common genes identification to identify shared pathways and drug targets, PPI network to identify hub-genes and basic modules, and the interaction of transcription factors (TFs) genes and TFs-miRNAs with common differentially expressed genes also placed on the datasets. Furthermore, we used gene ontology and molecular pathway analysis to do functional analysis and discovered that IPF patients have certain standard connections with the SARS-CoV-2 virus. A detailed investigation was carried out to recommend therapeutic compounds for IPF patients affected by the SARS-CoV-2 virus.
RESUMO
Animals must set behavioural priority in a context-dependent manner and switch from one behaviour to another at the appropriate moment1-3. Here we probe the molecular and neuronal mechanisms that orchestrate the transition from feeding to courtship in Drosophila melanogaster. We find that feeding is prioritized over courtship in starved males, and the consumption of protein-rich food rapidly reverses this order within a few minutes. At the molecular level, a gut-derived, nutrient-specific neuropeptide hormone-Diuretic hormone 31 (Dh31)-propels a switch from feeding to courtship. We further address the underlying kinetics with calcium imaging experiments. Amino acids from food acutely activate Dh31+ enteroendocrine cells in the gut, increasing Dh31 levels in the circulation. In addition, three-photon functional imaging of intact flies shows that optogenetic stimulation of Dh31+ enteroendocrine cells rapidly excites a subset of brain neurons that express Dh31 receptor (Dh31R). Gut-derived Dh31 excites the brain neurons through the circulatory system within a few minutes, in line with the speed of the feeding-courtship behavioural switch. At the circuit level, there are two distinct populations of Dh31R+ neurons in the brain, with one population inhibiting feeding through allatostatin-C and the other promoting courtship through corazonin. Together, our findings illustrate a mechanism by which the consumption of protein-rich food triggers the release of a gut hormone, which in turn prioritizes courtship over feeding through two parallel pathways.
Assuntos
Proteínas de Drosophila , Hormônios de Inseto , Animais , Corte , Proteínas de Drosophila/metabolismo , Drosophila melanogaster/fisiologia , Hormônios de Inseto/metabolismo , Masculino , Nutrientes , Comportamento Sexual Animal/fisiologiaRESUMO
Localized disease heterogeneity on imaging extracted via radiomics approaches have recently been associated with disease prognosis and treatment response. Traditionally, radiomics analyses leverage texture operators to derive voxel- or region-wise feature values towards quantifying subtle variations in image appearance within a region-of-interest (ROI). With the goal of mining additional voxel-wise texture patterns from radiomic "expression maps", we introduce a new RADIomic Spatial TexturAl descripTor (RADISTAT). This was driven by the hypothesis that quantifying spatial organization of texture patterns within an ROI could allow for better capturing interactions between different tissue classes present in a given region; thus enabling more accurate characterization of disease or response phenotypes. RADISTAT involves: (a) robustly identifying sub-compartments of low, intermediate, and high radiomic expression (i.e. heterogeneity) in a feature map and (b) quantifying spatial organization of sub-compartments via graph interactions. RADISTAT was evaluated in two clinically challenging problems: (1) discriminating nodal/distant metastasis from metastasis-free rectal cancer patients on post-chemoradiation T2w MRI, and (2) distinguishing tumor progression from pseudo-progression in glioblastoma multiforme using post-chemoradiation T1w MRI. Across over 800 experiments, RADISTAT yielded a consistent discriminatory signature for tumor progression (GBM) and disease metastasis (RCa); where its sub-compartments were associated with pathologic tissue types (fibrosis or tumor, determined via fusion of MRI and pathology). In a multi-institutional setting for both clinical problems, RADISTAT resulted in higher classifier performance (11% improvement in AUC, on average) compared to radiomic descriptors. Furthermore, combining RADISTAT with radiomic descriptors resulted in significantly improved performance compared to using radiomic descriptors alone.
Assuntos
Glioblastoma , Humanos , Imageamento por Ressonância Magnética/métodos , PrognósticoRESUMO
Glutamate (GLU) and gamma-aminobutyric acid (GABA) are neurotransmitters (NTs) with an essential role in signal transmission in the brain. Brain disorders, such as epilepsy, Alzheimer's and Parkinson's diseases, and traumatic brain injury can be linked to imbalances in the GLU-GABA homeostasis that occurs in sub-second to seconds time frames. Current measurement techniques can detect these two NT concentrations simultaneously only in vitro. The present work reports on the fabrication of a silicon multifunctional biosensor microarray probe for sub-second simultaneous GLU-GABA detection in real-time, with excellent analyte sensitivity and selectivity and in vivo capabilities. The novel Si probes feature four surface-functionalized platinum ultramicroelectrodes (UMEs) for simultaneous amperometric detection of GLU and GABA with a sentinel, and a built-in microfluidic channel for the introduction of neurochemicals in the proximity of the UMEs. The microchannel also allows functioning of an On-Demand In-situ Calibrator that runs in-situ biosensor calibration. The probe exhibited excellent robustness at insertion in agarose-gel brain-tissue-mimicking test, and remarkably high hydrogen peroxide sensitivity (a by-product of GLU-GABA enzyme biosensor) with values on the order of 5000 nA µM -1 cm -2 and maximum sensitivities of 204±15 nA µM -1 cm -2 and 37±7 nA µM -1 cm -2 for GLU and GABA, respectively. Furthermore, the limit of detection of the biosensors reached as low as 7 nM, 165 nM and 750 nM for H 2 O 2, GLU and GABA, respectively and a temporal resolution of hundreds of milliseconds during in vivo studies using freely moving rats.
RESUMO
INTRODUCTION: Unemployment has a contributory role in the development of mental health problems and in Bangladesh there is increasing unemployment, particularly among youth. Consequently, the present study investigated depression, anxiety, and stress among recent graduates in a multi-city study across the country. METHODS: A cross-sectional study was conducted among 988 Bangladeshi graduate jobseekers in six major cities of the country between August to November 2019. The measures included socio-demographics and life-style factors, study and job-related information, Economic Hardship Questionnaire, Financial Threat Scale, Financial Well-Being Scale, and Depression Anxiety Stress Scale-21. RESULTS: Depression, anxiety and stress rates among the present sample were 81.1% (n = 801), 61.5% (n = 608) and 64.8% (n = 640) respectively. Factors related to gender, age, socioeconomic conditions, educational background, lack of extra-curricular activities, and high screen activity were significant risk factors of depression, anxiety, and stress. Structural equation modeling indicated that (while controlling for age, daily time spent on sleep study, and social media use), financial threat was moderately positively related to depression, anxiety, and stress. Financial hardship was weakly positively associated with depression, anxiety, and stress, whereas financial wellbeing was weakly negatively associated with depression, anxiety, and stress. LIMITATIONS: Due to the nature of the present study (i.e., cross-sectional study) and sampling method (i.e., convenience sampling), determining causality between the variables is not possible. CONCLUSIONS: The present results emphasized the important detrimental role of financial troubles on young people's mental health by showing that financial problems among unemployed youth predict elevated psychiatric distress in both men and women.
Assuntos
Depressão , Desemprego , Adolescente , Ansiedade/epidemiologia , Bangladesh/epidemiologia , Cidades , Estudos Transversais , Depressão/epidemiologia , Feminino , Humanos , Masculino , Estresse Psicológico/epidemiologiaRESUMO
Glutamate (GLU) and γ-aminobutyric acid (GABA) are the major excitatory (E) and inhibitory (I) neurotransmitters in the brain, respectively. Dysregulation of the E/I ratio is associated with numerous neurological disorders. Enzyme-based microelectrode array biosensors present the potential for improved biocompatibility, localized sample volumes, and much faster sampling rates over existing measurement methods. However, enzymes degrade over time. To overcome the time limitation of permanently implanted microbiosensors, we created a microwire-based biosensor that can be periodically inserted into a permanently implanted cannula. Biosensor coatings were based on our previously developed GLU and reagent-free GABA shank-type biosensor. In addition, the microwire biosensors were in the same geometric plane for the improved acquisition of signals in planar tissue including rodent brain slices, cultured cells, and brain regions with laminar structure. We measured real-time dynamics of GLU and GABA in rat hippocampal slices and observed a significant, nonlinear shift in the E/I ratio from excitatory to inhibitory dominance as electrical stimulation frequency increased from 10 to 140 Hz, suggesting that GABA release is a component of a homeostatic mechanism in the hippocampus to prevent excitotoxic damage. Additionally, we recorded from a freely moving rat over fourteen weeks, inserting fresh biosensors each time, thus demonstrating that the microwire biosensor overcomes the time limitation of permanently implanted biosensors and that the biosensors detect relevant changes in GLU and GABA levels that are consistent with various behaviors.
Assuntos
Técnicas Biossensoriais , Ácido Glutâmico/química , Microeletrodos , Ácido gama-Aminobutírico/química , Animais , Encéfalo/diagnóstico por imagem , Estimulação Elétrica , Homeostase , Masculino , Micro-Ondas , Modelos Neurológicos , Rede Nervosa , Neurônios/metabolismo , Neurotransmissores , Platina/química , Ratos , Ratos Sprague-Dawley , Propriedades de SuperfícieRESUMO
Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter that is essential for normal brain function. It is involved in multiple neuronal activities, including plasticity, information processing, and network synchronization. Abnormal GABA levels result in severe brain disorders and therefore GABA has been the target of a wide range of drug therapeutics. GABA being non-electroactive is challenging to detect in real-time. To date, GABA is detected mainly via microdialysis with a high-performance liquid chromatography (HPLC) system that employs electrochemical (EC) and spectroscopic methodology. However, these systems are bulky and unsuitable for real-time continuous monitoring. As opposed to microdialysis, biosensors are easy to miniaturize and are highly suitable for in vivo studies; they selectively oxidize GABA into a secondary electroactive product (usually hydrogen peroxide, H2O2) in the presence of enzymes, which is then detected by amperometry. Unfortunately, this method requires a rather cumbersome process with prereactors and relies on externally applied reagents. Here, we report the design and implementation of a GABA microarray probe that operates on a newly conceived principle. It consists of two microbiosensors, one for glutamate (Glu) and one for GABA detection, modified with glutamate oxidase and GABASE enzymes, respectively. By simultaneously measuring and subtracting the H2O2 oxidation currents generated from these microbiosensors, GABA and Glu can be detected continuously in real-time in vitro and ex vivo and without the addition of any externally applied reagents. The detection of GABA by this probe is based upon the in-situ generation of α-ketoglutarate from the Glu oxidation that takes place at the Glu microbiosensor. A GABA sensitivity of 36 ± 2.5 pA µM-1cm-2, which is 26-fold higher than reported in the literature, and a limit of detection of 2 ± 0.12 µM were achieved in an in vitro setting. The GABA probe was successfully tested in an adult rat brain slice preparation. These results demonstrate that the developed GABA probe constitutes a novel and powerful neuroscientific tool that could be employed in the future for in vivo longitudinal studies of the combined role of GABA and Glu (a major excitatory neurotransmitter) signaling in brain disorders, such as epilepsy and traumatic brain injury, as well as in preclinical trials of potential therapeutic agents for the treatment of these disorders.
RESUMO
Tadalafil, a type-5 phosphodiesterase enzyme inhibitor with long half-life used to treat erectile dysfunction. Recently it has been reported that tadalafil improves cognitive function. Here, we aimed to investigate the age dependent effects of tadalafil on memory, locomotor, behavior, and oxidative stress in the hippocampus. Tadalafil was orally administered everyday (5 mg/kg) to young (2 months) and old (16 months) healthy mice for 4 weeks. Control mice from each group received equal volume of 0.9% normal saline for the same duration. Memory and locomotor activity were tested using radial arm maze and open field test respectively. The level of malondialdehyde (MDA), nitric oxide (NO), and advanced protein oxidation product (APOP) was analyzed and catalase activity was determined from the isolated hippocampus. Treatment with tadalafil in aged mice improves working memory than the corresponding tadalafil treated young mice in radial arm maze test. Tadalafil treated mice traveled less distance in the center and the mean speed of tadalafil treated aged mice was significantly lower than the tadalafil treated young mice in open field test. Tadalafil treatment elicited a decrease of MDA level in the hippocampus of aged mice than that of young mice. APOP level was decreased only in aged mice treated with tadalafil. Treatment with tadalafil decreased NO and increased catalase activity in both young and aged mice. On the basis of previous and our findings, we conclude that tadalafil treatment reduces oxidative stress while increased cGMP level in the hippocampus might be responsible for memory enhancement.