Mechanisms of Naltrexone-induced Reduction of Ethanol Preference in Drosophila Melanogaster

Naltrexone is an opioid antagonist used to treat alcohol dependence in human beings ever since its approval by Food and Drug Administration in 1994. Naltrexone exerts its action by blocking on central opioid receptors that mediate the drinking or reward behaviours, thus reducing the alcohol consumption. Although various animal and clinical studies have demonstrated the efficacy of Naltrexone, its action on reducing the preferential ethanol consumption in Drosophila melanogaster has not been illustrated so far. So it was of our interest to demonstrate the effect of Naltrexone on the drinking behaviour in fruit flies and to further explore the molecular mechanisms underlying this effect. In our study, we have employed the well-established CAFE methodology to test the preference of flies to consume alcohol food over normal food. 1-3 day old male flies (wild type) were used for all the experiments which were exposed or unexposed to 15% ethanol to examine the preferential consumption. Preference assays were conducted with or without Naltrexone treatment to demonstrate its effect under various experimental conditions. In addition to the behavioural assay, we have attempted a biochemical estimation to observe the changes in the phosphorylation patterns of protein kinase C (PKC) using an ELISA-based PKC kinase activity assay in order to explore the mechanism of action of Naltrexone in relation to PKC which has been identified to mediate alcohol addiction processes. To further explore any PKC-mediated mechanism of Naltrexone effect, preference assays were conducted in Drosophila PKC mutant line-20790. Our results showed that Drosophila pre-exposed to ethanol, prefers to consume ethanol food over non-ethanol food and for the first time we have demonstrated that Naltrexone reverses this preference to consume ethanol food. Our data also shows that mechanism of Naltrexone effect appears to be independent of PKC-mediated pathway and we propose that Naltrexone might be operating through a different system (eg; pathways or receptors or signalling molecules associated with neural circuitry such as Dopamine) and more research is needed to explore these mechanisms in detail to develop new hypotheses on potential therapeutic targets

Donor-free oligothiophene based dyes with di-anchor architecture for dye-sensitized solar cells

Traditionally, metal free DSSCs are fabricated from sensitizers designed using a donor-pi-acceptor (D-π-A) architecture. More recently, non-conventional dyes without strong donor units have emerged and have provided competitive power conversion efficiencies (PCEs) with respect to their (D-π-A)-based counterparts. Here, we report the synthesis and DSSC fabrication of oligothiophene molecules featuring two anchoring groups that do not possess strong donor moieties and are able to adopt V- and U-shape conformations. PCEs of 3.70% was obtained with the smaller 5-thiophene dyes (5T2A, 5T2A-E) possessing higher PCEs than their larger 8-thiophene counterparts containing diacetylene units (8T4A, 8T4A-E). Comparison to the DSSC properties of the analogous linear dye 5T, indicates that the architecture and structure of this series of dyes are likely responsible for their lower performance

An explainable artificial intelligence model for identifying local indicators and detecting lung disease from chest X-ray images

One of the primary responsibilities of radiologists is to diagnose lung illness using chest X-ray images. The radiologist examines the patchy infection in the imaging and makes a rational decision based on their knowledge. Convolutional neural networks work incredibly well in classifying and identifying diseases from medical images. Despite being a promising prediction technology with accuracy equivalent to a person, deep learning (DL) models typically lack explainability, a crucial component for the clinical deployment of DL models in the highly regulated healthcare sector. In this paper, we mimic the radiologist’s decision-making process by identifying local discriminate regions of a chest X-ray image through weekly supervised learning and deriving rules, and explaining why the DL method gives such results. This process is carried out in three phases. Phase one is to train a model on a classification problem to predict lung disease. Phase two is identifying critical regions and training a model on the identified images with critical regions. Phase three combines the local and global features with learning more patterns to classify the diseases. The local and fusion models have shown remarkable improvement in getting 99.6 percent accuracy with fewer epochs

Automated Open Source Software Assessment and Monitoring : Through practitioners’ lens

Background: Developing and maintaining software is resource expensive. Therefore many organizations and practitioners use Open Source Software(OSS) in commercial development to minimize resource expense. But, adopting OSS mandates the organizations and practitioners to assess and monitor the OSS for updates from the community. Previous literature proposes many assessment frameworks. Many are non-automated and use complex attributes that require a steep learning curve for practitioners to understand. The OSS assessments and monitoring choke the agility of the team and delay their time to market. Practitioners need automated quick assessments with easy-to-understand attributes to assist them during OSS adoption. After adoption, monitoring and upgrading OSS can be challenging. Therefore, organizations need automatic OSS monitoring and upgrading solutions capable of checking community updates for the OSS and upgrade the internally hosted OSS if the update is compliant automatically. Objectives: The objective of our thesis is to automate OSS assessments and monitoring using OSS assessment attributes that are easily understood by the practitioners. Methods: We performed a design science research at City Network to understand OSS assessments and monitoring in organizations and identified the attributes used by the practitioners. Additionally, we identified the attributes from the previous literature that were relevant for practitioners. Following the identification, we constructed an automated solution for OSS assessments and monitoring that was accepted by City Network. To evaluate the generalizability of our automated solution, we conducted interviews with practitioners outside City Network. Results: Our automated solution was praised for its ease of use and easy-to-understand attributes. Practitioners wanted their customizations on our automated solution with additional features and attributes to fully automate their OSS assessments. But our OSS monitoring and upgrading solution was criticized for lack of rigor in assessing an update. But, its program flow and usage at scale were appreciated by practitioners. Conclusions: Our automated solution was effective in automated assessing OSS before adoption. But, it was not capable of automating OSS monitoring and upgrading. With that said, the problem of OSS assessments and monitoring is relevant for many organizations and practitioners. Therefore, such research is essential to improve and streamline OSS adoption for organizations and practitioners. Additionally, it is worthwhile to research more OSS attributes that are relevant and easy to understand for the practitioners

Prevalence and Impact of Preexisting Comorbidities on Overall Clinical Outcomes of Hospitalized COVID-19 Patients

COVID-19 risk increases with comorbidities, and the effect is magnified due to the contribution of individual and combined comorbidities to the overall clinical outcomes. We aimed to explore the influence of demographic factors, clinical manifestations, and underlying comorbidities on mortality, severity, and hospital stay in COVID-19 patients. Therefore, retrospective chart reviews were performed to identify all laboratory-confirmed cases of SARS-CoV-2 infection in Apollo Hospitals, Hyderabad, between March 2020 and August 2020.A total of 369 confirmed SARS-CoV-2 cases were identified: 272 (73.7%) patients were male, and 97 (26.2%) were female. Of the confirmed cases, 218 (59.1%) had comorbidities, and 151 (40.9%) were devoid of comorbidities. This study showed that old age and underlying comorbidities significantly increase mortality, hospital stay, and severity due to COVID-19 infection. The presence of all four comorbidities, diabetes mellitus DM+Hypertension HTN+coronary artery disease CAD+chronic kidney disease CKD, conferred the most severity (81%). The highest mortality (OR: 44.03, 95% CI: 8.64-224.27) was observed during the hospital stay (12.73±11.38; 95% CI: 5.08-20.38) in the above group. Multivariate analysis revealed that nonsurvivors are highest (81%) in (DM+HTN+CAD+CKD) category with an odds ratio (95% CI) of 44.03 (8.64-224.27). Age, gender, and comorbidities adjusted odds ratio decreased to 20.25 (3.77-108.77). Median survival of 7 days was observed in the (DM+HTN+CAD+CKD) category. In summary, the presence of underlying comorbidities has contributed to a higher mortality rate, greater risk of severe disease, and extended hospitalization periods, hence, resulting in overall poorer clinical outcomes in hospitalized COVID-19 patients. © 2022 Rajeswari Koyyada et al

Exosomal PTEN as a Predictive Marker of Aggressive Gliomas

Background: Liquid biopsies have emerged as convenient alternative diagnostic methods to invasive biopsies, by evaluating disease-specific biomarkers and monitoring the disease risk noninvasively. Phosphatase and tensin homolog deleted in chromosome 10 (PTEN) is a potent tumor suppressor, and its deletion/mutations are common in gliomas. Objective: Evaluate the feasibility of non-invasive detection of PTEN and its downstream genes in serum exosomes of glioma patients. Materials and methods: PTEN, Yes-associated-protein 1 (YAP1), and lysyl oxidase (LOX) transcript expression were monitored through polymerase chain reaction (PCR) in serum exosomes and their paired tumor tissues. The impact of PTEN and its axis genes expression on the overall survival (OS) was monitored. Results: Out of the 106 glioma serum samples evaluated, PTEN was retained/lost in 65.4%/34.6% of the tumor samples while it was retained/lost in 67.1%/32.9% of their paired exosomal fractions. PTEN expression in both tissue and paired exosomal fractions was observed in 48.11% of the samples. Sanger sequencing detected three mutations (Chr10: 89720791(A\textgreaterG), Chr10:89720749(C\textgreaterT), and Chr10:89720850(A\textgreaterG). Both PTEN-responsive downstream genes (YAP1) and LOX axis were upregulated in the PTEN-deficient samples. PTEN loss was associated with poor survival in the glioma patients (hazard ratio (HR) 0.68, confidence interval (CI): 0.35-1.31, P = 0.28). The OS of the exosomal PTEN cohort coincided with the tumor-tissue PTEN devoid group (HR 1.08, CI: 0.49-2.36, P = 0.85). While, old age yielded the worst prognosis; gender, location, and grade were not prognostic of OS in the multivariate analysis. Conclusions: PTEN and its responsive genes YAP1 and LOX can be detected in serum exosomes and can serve as essential tools for the non-invasive evaluation/identification of aggressive gliomas. © 2022 Neurology India, Neurological Society of India

Optimal Cooling System Design for Increasing the Crystal Growth Rate of Single-Crystal Silicon Ingots in the Czochralski Process Using the Crystal Growth Simulation

Here, we report a successfully modified Czochralski process system by introducing the cooling system and subsequent examination of the results using crystal growth simulation analysis. Two types of cooling system models have been designed, i.e., long type and double type cooling design (LTCD and DTCD) and their production quality of monocrystalline silicon ingot was compared with that of the basic type cooling design (BTCD) system. The designed cooling system improved the uniformity of the temperature gradient in the crystal and resulted in the significant decrease of the thermal stress. Moreover, the silicon monocrystalline ingot growth rate has been enhanced to 18% by using BTCD system. The detailed simulation results have been discussed in the manuscript. The present research demonstrates that the proposed cooling system would stand as a promising technique to be applied in CZ-Si crystal growth with a large size/high pulling rate

Enhanced Photoelectrochemical Water Oxidation Using TiO2-Co3O4 p-n Heterostructures Derived from in Situ-Loaded ZIF-67

Exposing catalytically active metal sites in metal–organic frameworks (MOFs) while maintaining porosity is beneficial for increasing electron transport to achieve better electrochemical energy conversion performance. Herein, we propose an in situ method for MOF formation and loading onto TiO2 nanorods (NR) using a simple solution-processable method followed by annealing to obtain TiO2-Co3O4. The as-prepared TiO2-ZIF-67 based photoanodes were annealed at 350, 450, and 550 °C to study the effect of carbonization on photo-electrochemical water oxidation. The successful loading of ZIF-67 on TiO2 and the formation of TiO2-Co3O4 heterojunction were confirmed by XRD, XPS, FE-SEM, and HRTEM analyses. TiO2-Co3O4-450 (the sample annealed at 450 °C) showed an enhanced photocurrent of 2.4 mA/cm2, which was 2.6 times larger than that of pristine TiO2. The improved photocurrent might be ascribed to the prepared p–n heterostructures (Co3O4 and TiO2), which promote electron–hole separation and charge transfer within the system and improve the photoelectrochemical performance. Moreover, the preparation of Co3O4 from the MOF carbonization process improved the electrical conductivity and significantly increased the number of exposed active sites and enhanced the photoresponse performance. The as-prepared ZIF-67 derived TiO2-Co3O4 based photoanodes demonstrate high PEC water oxidation, and the controlled carbonization method paves the way toward the synthesis of low-cost and efficient electrocatalysts. © 2023 by the authors.TRU

Self-Doped Carbon Dots Decorated TiO₂ Nanorods: A Novel Synthesis Route for Enhanced Photoelectrochemical Water Splitting

Herein, we have successfully prepared self-doped carbon dots with nitrogen elements (NCD) in a simple one-pot hydrothermal carbonization method, using L-histidine as a new precursor. The effect of as-prepared carbon dots was studied for photoelectrochemical (PEC) water splitting by decorating NCDs upon TiO2 nanorods systematically by changing the loading time from 2 h to 8 h (TiO2@NCD2h, TiO2@NCD4h, TiO2@NCD6h, and TiO2@NCD8h). The successful decorating of NCDs on TiO2 was confirmed by FE-TEM and Raman spectroscopy. The TiO2@NCD4h has shown a photocurrent density of 2.51 mA.cm−2, 3.4 times higher than the pristine TiO2. Moreover, TiO2@NCD4h exhibited 12% higher applied bias photon-to-current efficiency (ABPE) than the pristine TiO2. The detailed IPCE, Mott–Schottky, and impedance (EIS) analyses have revealed the enhanced light harvesting property, free carrier concentration, charge separation, and transportation upon introduction of the NCDs on TiO2. The obtained results clearly portray the key role of NCDs in improving the PEC performance, providing a new insight into the development of highly competent TiO2 and NCDs based photoanodes for PEC water splitting

In Situ Grown Mesoporous Structure of Fe-Dopant@NiCoO_X@NF Nanoneedles as an Efficient Supercapacitor Electrode Material

In this study, we designed mixed metal oxides with doping compound nano-constructions as efficient electrode materials for supercapacitors (SCs). We successfully prepared the Fe-dopant with NiCoOx grown on nickel foam (Fe-dopant@NiCoOx@NF) through a simple hydrothermal route with annealing procedures. This method provides an easy route for the preparation of high activity SCs for energy storage. Obtained results revealed that the Fe dopant has successfully assisted NiCoOx lattices. The electrochemical properties were investigated in a three-electrode configuration. As a composite electrode for SC characteristics, the Fe-dopant@NiCoOx@NF exhibits notable electrochemical performances with very high specific capacitances of 1965 F g−1 at the current density of 0.5 A g−1, and even higher at 1296 F g−1 and 30 A g−1, respectively, which indicate eminent and greater potential for SCs. Moreover, the Fe-dopant@NiCoOx@NF nanoneedle composite obtains outstanding cycling performances of 95.9% retention over 4500 long cycles. The improved SC activities of Fe-dopant@NiCoOx@NF nanoneedles might be ascribed to the synergistic reactions of the ternary mixed metals, Fe-dopant, and the ordered nanosheets grown on NF. Thus, the Fe-dopant@NiCoOx@NF nanoneedle composite with unique properties could lead to promising SC performance