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Background & aim: A potential benefit of conservation agriculture (CA) is soil organic carbon (SOC) accrual, yet recent studies indicate limited or no impact of CA on total SOC in tropical agroecosystems. We evaluated biochemical indicators of soil C cycling after 9 years (18 seasons) of contrasting tillage with and without maize residue retention in western Kenya. Methods: Potential activities of C-cycling enzymes (β-glucosidase, GLU; β-galactosidase, GAL; glucosaminidase, GLM; cellobiohydrolase, CEL), permanganate-oxidizable C (POXC), and soil organic matter (SOM) composition (by infrared spectroscopy) were measured. Results: POXC tended to be greater under reduced tillage and residue retention, but did not significantly differ among treatments (≤ 2% of SOC). Despite no significant differences in SOC concentrations or stocks, activities of all 4 C-cycling enzymes responded strongly to tillage, and to a lesser extent to residue management. Activities of GLU, GAL, and GLM were greatest under the combination of reduced tillage and residue retention relative to other treatments. Reduced tillage produced an enrichment in carboxyl C = O (+6%) and decreased polysaccharide C-O (−3.5%) relative to conventional tillage irrespective of residue management. Conclusions: Though enzyme activities and POXC are typically associated with SOC accrual, changes in soil C cycling at this site have not translated into significant differences in SOC after 9 years. Elevated enzyme activities may have offset potential SOC accumulation under CA. However, the ratio of C-cycling enzyme activities to SOC was higher under reduced tillage and residue retention relative to other treatments, indicating that stoichiometric scaling of SOC and enzyme activities does not explain absence of significant differences in SOC among tillage and residue managements. Potential factors that may explain the low SOC accrual rates in this tropical agroecosystem included the low, albeit realistic, levels of residue retention, nutrient limitations, and high temperatures favoring decomposition.

The majority of births in rural Bangladesh are carried out in unhygienic conditions by relatives and traditional birth attendants (TBAs). This results in a high incidence of maternal and infant mortality that could be reduced if childbirth were to occur in health centers or under the supervision of trained TBAs (TTBAs). In this paper, we examined factors associated with utilization of modern health resources for childbirth in 39 villages of Bangladesh. We followed a retrospective survey research design to collect relevant information from couples who experienced childbirth during a two-year period from July 1, 1995 to June 1997. The data indicate that slightly over 11% of the deliveries were performed by trained personnel with the rest attended by TBAs. Multivariate analysis clearly shows that delivery complications was the most significant factor determining the use of modern health care resources for childbirth, followed by parental education, and pre-natal care. We conclude that quick response to delivery complications and improved access to hospitals and TTBAs can reduce the risk of infant and maternal mortality and morbidity in rural Bangladesh. [ABSTRACT FROM AUTHOR]

Designing efficient drug delivery systems for optimum therapeutic outcomes and minimum adverse effects remains a pivotal focus in pharmaceutical research. Understanding the nature of interactions between drugs and drug carriers and the drug-release mechanism are the key aspects for the development of effective delivery systems. This work presents a detailed investigation into the intricate interactions between niosomes and the drug Phenosafranin (PSF), and the subsequent release induced by a variety of cyclodextrins (CDs) employing a multifaceted approach. Ensemble average spectroscopic and single molecular level investigations based on fluorescence correlation spectroscopy (FCS), are employed to explore the binding interactions of PSF with the niosome membrane. Subsequently, the release of the drug was studied by disrupting the niosome structure using various CDs, and their efficacy was accessed through steady-state and time-resolved photophysical responses. FCS experiments provided precise insights into the binding and drug release process at the single-molecule level through the variation in translational and diffusion characteristics of the drug. Additionally, isothermal titration calorimetric (ITC) investigations further revealed the thermodynamics governing the CD-niosome host:guest interactions and the varying potential of different CDs in disrupting the niosome to release the drug which were further validated by electron microscopy and confocal fluorescence microscopy analyses. A broader analysis of niosomes prepared with various nonionic surfactants highlighted the influence of cavitand size and structure on the interaction with different niosome constituents. This comprehensive analysis sheds light on the complex interplay of these components and their interactions, providing insights into drug delivery systems and their potential therapeutic applications.

Basal Cell Carcinoma (BCC) and Actinic Keratosis (AK) are prevalent skin conditions with significant health complications. The molecular mechanisms underlying these conditions and their potential shared pathways remain ambiguous despite their prevalence. Therefore, this study aims to elucidate the common molecular pathways and potential therapeutic targets for BCC and AK through comprehensive computational network analysis. Linkage analysis was performed to identify common liable genes between BCC and AK. Protein-protein interactions (PPIs), Topological properties, GO enrichment, pathway enrichment, and gene regulatory network analyses were also performed to reveal potential molecular mechanisms and pathways. Furthermore, we evaluated protein-drug interactions (PDIs) to identify potential therapeutic targets. Our analysis revealed 22 common genes between BCC and AK: TP53 , EGFR , CDKN2A , MMP9 , PTGS2 , VDR , BCL2 , MMP2 , EZH2 , TP63 , FOXP3 , MSH2 , MMP14 , FLG , MC1R , CDKN2B , TIMP3 , TYR , SOX10 , IRF4 , KRT17 , and NID1 . PPI network analysis highlighted TP53 and EGFR as central hubs, validated using RNA-seq data. Co-expression and physical interaction analysis revealed a strong interplay between the common genes at the transcriptional and functional levels. GO analysis identified skin cancer-relevant terms: "skin development", "immune system development", and "response to radiation" as significantly enriched biological processes, while pathway enrichment analysis highlighted several cancer-related pathways enrichment. Gene regulatory network analysis revealed complex interactions between genes, miRNAs, and transcription factors, with TP53 , BCL2 , and EGFR playing central roles. PDI network analysis identified ibuprofen as a potential therapeutic agent targeting PTGS2 and BCL2, while other proteins VDR, MMP2, MMP9, and TYR showed interactions with multiple drugs. This computational analysis provides valuable insights into the shared molecular mechanisms of BCC and AK, revealing common pathways and potential therapeutic targets for developing novel treatment strategies and repurposing existing drugs for these prevalent skin cancers. Therefore, these findings may guide future research in understanding and developing targeted therapies for both conditions., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2025 The Authors.)

A DFT-based computational study is carried out to delve into the interplay between hyperconjugation and rehybridization effects underlying the formation of blue- or red-shifting H-bonds (HBs) in 1 : 1 complexes of cyclic ethers (HB acceptor) of varying ring-size with haloforms, CHF 3 and CHCl 3 (HB donor). The calculations reveal that with decreasing angular strain (increasing ring-size) of the cyclic ethers, the extent of blue-shift increases for 1 : 1 complexes with CHF 3 , while a reverse sequence is observed with CHCl 3 , eventually leading to a red-shifting HB in the oxepane : CHCl 3 complex. It is noted that the trend in the shift of C-H stretching fundamental is not mirrored by the C-H bond length or interaction energies for both the systems studied, that is, the low sensitivity of the changes on the strain on the O-atom of HB acceptor (cyclic ethers) is to be emphasized., (© 2024 Wiley-VCH GmbH.)

Hypopharyngeal cancer is a disease that is associated with EGFR-mutated lung adenocarcinoma. Here we utilized a bioinformatics approach to identify genetic commonalities between these two diseases. To this end, we examined microarray datasets from GEO (Gene Expression Omnibus) to identify differentially expressed genes, common genes, and hub genes between the selected two diseases. Our analyses identified potential therapeutic molecules for the selected diseases based on 10 hub genes with the highest interactions according to the degree topology method and the maximum clique centrality (MCC). These therapeutic molecules may have the potential for simultaneous treatment of these diseases., (© 2024 The Authors. FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Diabetic foot ulcer (DFU) poses a significant threat to individuals affected by diabetes, often leading to limb amputation. Early detection of DFU can greatly improve the chances of survival for diabetic patients. This work introduces FusionNet, a novel multi-scale feature fusion network designed to accurately differentiate DFU skin from healthy skin using multiple pre-trained convolutional neural network (CNN) algorithms. A dataset comprising 6963 skin images (3574 healthy and 3389 ulcer) from various patients was divided into training (6080 images), validation (672 images), and testing (211 images) sets. Initially, three image preprocessing techniques - Gaussian filter, median filter, and motion blur estimation - were applied to eliminate irrelevant, noisy, and blurry data. Subsequently, three pre-trained CNN algorithms -DenseNet201, VGG19, and NASNetMobile - were utilized to extract high-frequency features from the input images. These features were then inputted into a meta-tuner module to predict DFU by selecting the most discriminative features. Statistical tests, including Friedman and analysis of variance (ANOVA), were employed to identify significant differences between FusionNet and other sub-networks. Finally, three eXplainable Artificial Intelligence (XAI) algorithms - SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model-agnostic Explanations), and Grad-CAM (Gradient-weighted Class Activation Mapping) - were integrated into FusionNet to enhance transparency and explainability. The FusionNet classifier achieved exceptional classification results with 99.05 % accuracy, 98.18 % recall, 100.00 % precision, 99.09 % AUC, and 99.08 % F1 score. We believe that our proposed FusionNet will be a valuable tool in the medical field to distinguish DFU from healthy skin., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Amid rising water contamination from industrial sources, tackling toxic dyes and pathogens is critical. Photocatalysis offers a cost-effective and eco-friendly solution to this pressing challenges. Herein, we synthesized Te 4+ and Er 3+ doped ZrO 2 photocatalysts through hydrothermal method and investigated their efficacy in degrading Congo red (CR) and pathogens under visible light. XRD and Raman Spectroscopy confirm monoclinic and tetragonal mixed-phases without any impurities. Doping-induced defects, reduced crystalline diameter, high surface area, modified bandgap (2.95 eV), photoluminescence quenching, coupled with interfacial polarization, contribute to EZO's excellent dielectric response (1.149 × 10 6 ), for achieving remarkable photocatalytic activity, verified by photoelectrochemical measurements, LC-MS and phytotoxicity analysis. Under optimal conditions, EZO achieves 99% CR degradation within 100 min (TOC 79.9%), surpassing ZO (77%) and TZO (84%). Catalyst dosages, dye concentrations, and solution pH effect on EZO's photocatalytic performance are systematically assessed. Scavenging experiment emphasized the pivotal role of · OH in CR degradation with 96.4% efficiency after 4 cycles, affirming its remarkable stability. Moreover, EZO demonstrates ROS-mediated antibacterial activity against E. faecalis and E. coli bacteria under visible light, achieving >97% and >94% inhibition rate with an inhibition zone > 3 mm. Hence, the nanoparticle's dual action offers a practical solution for treating contaminated wastewater, ensuring safe irrigation., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Piyali Halder reports financial support was provided by India Ministry of Science & Technology Department of Science and Technology. Indrajit Mondal reports financial support was provided by India Ministry of Science & Technology Department of Science and Technology. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The drawbacks inherent to traditional antibacterial therapies, coupled with the escalating prevalence of multi-drug resistant (MDR) microorganisms, have prompted the imperative need for novel antibacterial strategies. Accordingly, the emerging field of piezocatalysis in semiconductors harnesses mechanical stress to drive chemical reactions by utilizing piezo-generated free charge carriers, presenting a promising technology. To the best of our knowledge, this study is the first to provide a comprehensive overview of the eradication of pathogenic S. aureus bacteria using few-layer black phosphorus (SCBP) piezo catalyst under mechanical stimuli, along with the exploration of temperature dependent dielectric properties. The synthesis of the piezo catalysts involved a one-step cost-effective sonochemical method, and its structural, morphological, elemental, optical, and overall polarization properties were thoroughly characterized and compared with the traditional method-derived product (TABP). The synthesis-introduced defects, reduced crystalline diameters, modified bandgap (1.76 eV), nanoparticle aggregation, photoluminescence quenching, along with interfacial polarization, synergistically contribute to SCBP's exceptional dielectric response (4.596 × 10 7 @40 Hz), which in turn enhanced the piezocatalytic activity. When subjected to soft ultrasound stimulation at 15 kHz, the piezo catalyst SCBP demonstrated significant ROS-mediated antibacterial activity, resulting in a ∼94.7% mortality rate within 40 minutes. The impact of this study extends to cost-effective energy storage devices and advances in antibacterial therapy, opening new dimensions in both fields.

Biomarker-based cancer identification and classification tools are widely used in bioinformatics and machine learning fields. However, the high dimensionality of microarray gene expression data poses a challenge for identifying important genes in cancer diagnosis. Many feature selection algorithms optimize cancer diagnosis by selecting optimal features. This article proposes an ensemble rank-based feature selection method (EFSM) and an ensemble weighted average voting classifier (VT) to overcome this challenge. The EFSM uses a ranking method that aggregates features from individual selection methods to efficiently discover the most relevant and useful features. The VT combines support vector machine, k-nearest neighbor, and decision tree algorithms to create an ensemble model. The proposed method was tested on three benchmark datasets and compared to existing built-in ensemble models. The results show that our model achieved higher accuracy, with 100% for leukaemia, 94.74% for colon cancer, and 94.34% for the 11-tumor dataset. This study concludes by identifying a subset of the most important cancer-causing genes and demonstrating their significance compared to the original data. The proposed approach surpasses existing strategies in accuracy and stability, significantly impacting the development of ML-based gene analysis. It detects vital genes with higher precision and stability than other existing methods.

Copper (Cu) and tungsten (W) possess exceptional electrical and thermal conductivity properties, making them suitable candidates for applications such as interconnects and thermal conductivity enhancements. Solution-based additive manufacturing (SBAM) offers unique advantages, including patterning capabilities, cost-effectiveness, and scalability among the various methods for manufacturing Cu and W-based films and structures. In particular, SBAM material jetting techniques, such as inkjet printing (IJP), direct ink writing (DIW), and aerosol jet printing (AJP), present a promising approach for design freedom, low material wastes, and versatility as either stand-alone printers or integrated with powder bed-based metal additive manufacturing (MAM). Thus, this review summarizes recent advancements in solution-processed Cu and W, focusing on IJP, DIW, and AJP techniques. The discussion encompasses general aspects, current status, challenges, and recent research highlights. Furthermore, this paper addresses integrating material jetting techniques with powder bed-based MAM to fabricate functional alloys and multi-material structures. Finally, the factors influencing large-scale fabrication and potential prospects in this area are explored.

COVID-19 is a severe respiratory contagious disease that has now spread all over the world. COVID-19 has terribly impacted public health, daily lives and the global economy. Although some developed countries have advanced well in detecting and bearing this coronavirus, most developing countries are having difficulty in detecting COVID-19 cases for the mass population. In many countries, there is a scarcity of COVID-19 testing kits and other resources due to the increasing rate of COVID-19 infections. Therefore, this deficit of testing resources and the increasing figure of daily cases encouraged us to improve a deep learning model to aid clinicians, radiologists and provide timely assistance to patients. In this article, an efficient deep learning-based model to detect COVID-19 cases that utilizes a chest X-ray images dataset has been proposed and investigated. The proposed model is developed based on ResNet50V2 architecture. The base architecture of ResNet50V2 is concatenated with six extra layers to make the model more robust and efficient. Finally, a Grad-CAM-based discriminative localization is used to readily interpret the detection of radiological images. Two datasets were gathered from different sources that are publicly available with class labels: normal, confirmed COVID-19, bacterial pneumonia and viral pneumonia cases. Our proposed model obtained a comprehensive accuracy of 99.51% for four-class cases (COVID-19/normal/bacterial pneumonia/viral pneumonia) on Dataset-2, 96.52% for the cases with three classes (normal/ COVID-19/bacterial pneumonia) and 99.13% for the cases with two classes (COVID-19/normal) on Dataset-1. The accuracy level of the proposed model might motivate radiologists to rapidly detect and diagnose COVID-19 cases.

Social interactions involve both approach and avoidance toward specific individuals. Currently, the brain regions subserving these behaviors are not fully recognized. The anterior hypothalamic nucleus (AHN) is a poorly defined brain area, and recent studies have yielded contradicting conclusions regarding its behavioral role. Here we explored the role of AHN neuronal activity in regulating approach and avoidance actions during social interactions. Using electrophysiological recordings from behaving mice, we revealed that theta rhythmicity in the AHN is enhanced during affiliative interactions, but decreases during aversive ones. Moreover, the spiking activity of AHN neurons increased during the investigation of social stimuli, as compared to objects, and was modulated by theta rhythmicity. Finally, AHN optogenetic stimulation during social interactions augmented the approach toward stimuli associated with the stimulation. These results suggest the role for AHN neural activity in regulating approach behavior during social interactions, and for theta rhythmicity in mediating the valence of social stimuli., Competing Interests: The authors declare no competing interests., (© 2022 The Authors.)

Fear conditioning leads to long-term fear memory formation and is a model for studying fear-related psychopathological conditions such as phobias and post-traumatic stress disorder. Long-term fear memory formation is believed to involve alterations of synaptic efficacy mediated by changes in synaptic transmission and morphology in lateral amygdala (LA). Nck1 is a key neuronal adaptor protein involved in the regulation of the actin cytoskeleton and the neuronal processes believed to be involved in memory formation. However, the role of Nck1 in memory formation is not known. Here we explored the role of Nck1 in fear memory formation in lateral amygdala (LA). Reduction of Nck1 in excitatory neurons in LA enhanced long-term, but not short-term, auditory fear conditioning memory. Activation of Nck1, by using a photoactivatable Nck1 (PA-Nck1), during auditory fear conditioning in excitatory neurons in LA impaired long-term, but not short-term, fear memory. Activation of Nck1 immediately or a day after fear conditioning did not affect fear memory. The hippocampal-mediated contextual fear memory was not affected by the reduction or activation of Nck1 in LA. We show that Nck1 is localized to the presynapses in LA. Nck1 activation in LA excitatory neurons decreased the frequency of AMPA receptors-mediated miniature excitatory synaptic currents (mEPSCs). Nck1 activation did not affect GABA receptor-mediated inhibitory synaptic currents (mIPSCs). These results show that Nck1 activity in excitatory neurons in LA regulates glutamate release and sets the threshold for fear memory formation. Moreover, our research shows that Nck1 may serve as a target for pharmacological treatment of fear and anxiety disorders., (© 2022. The Author(s).)

Esophageal carcinoma (EsC) is a member of the cancer group that occurs in the esophagus; globally, it is known as one of the fatal malignancies. In this study, we used gene expression analysis to identify molecular biomarkers to propose therapeutic targets for the development of novel drugs. We consider EsC associated four different microarray datasets from the gene expression omnibus database. Statistical analysis is performed using R language and identified a total of 1083 differentially expressed genes (DEGs) in which 380 are overexpressed and 703 are underexpressed. The functional study is performed with the identified DEGs to screen significant Gene Ontology (GO) terms and associated pathways using the Database for Annotation, Visualization, and Integrated Discovery repository (DAVID). The analysis revealed that the overexpressed DEGs are principally connected with the protein export, axon guidance pathway, and the downexpressed DEGs are principally connected with the L13a-mediated translational silencing of ceruloplasmin expression, formation of a pool of free 40S subunits pathway. The STRING database used to collect protein-protein interaction (PPI) network information and visualize it with the Cytoscape software. We found 10 hub genes from the PPI network considering three methods in which the interleukin 6 (IL6) gene is the top in all methods. From the PPI, we found that identified clusters are associated with the complex I biogenesis, ubiquitination and proteasome degradation, signaling by interleukins, and Notch-HLH transcription pathway. The identified biomarkers and pathways may play an important role in the future for developing drugs for the EsC., Competing Interests: All the authors have read the manuscript and approved this for submission as well as no competing interests., (Copyright © 2022 Md. Rakibul Islam et al.)

Background: Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB., Methods: A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣log fold change | >1 and P < 0.05. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network., Results: Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB., Competing Interests: All the authors have read the manuscript and approved this for submission; also, there are no competing interests., (Copyright © 2022 Md. Rakibul Islam et al.)

Coronavirus disease-19 (COVID-19) is a severe respiratory viral disease first reported in late 2019 that has spread worldwide. Although some wealthy countries have made significant progress in detecting and containing this disease, most underdeveloped countries are still struggling to identify COVID-19 cases in large populations. With the rising number of COVID-19 cases, there are often insufficient COVID-19 diagnostic kits and related resources in such countries. However, other basic diagnostic resources often do exist, which motivated us to develop Deep Learning models to assist clinicians and radiologists to provide prompt diagnostic support to the patients. In this study, we have developed a deep learning-based COVID-19 case detection model trained with a dataset consisting of chest CT scans and X-ray images. A modified ResNet50V2 architecture was employed as deep learning architecture in the proposed model. The dataset utilized to train the model was collected from various publicly available sources and included four class labels: confirmed COVID-19, normal controls and confirmed viral and bacterial pneumonia cases. The aggregated dataset was preprocessed through a sharpening filter before feeding the dataset into the proposed model. This model attained an accuracy of 96.452% for four-class cases (COVID-19/Normal/Bacterial pneumonia/Viral pneumonia), 97.242% for three-class cases (COVID-19/Normal/Bacterial pneumonia) and 98.954% for two-class cases (COVID-19/Viral pneumonia) using chest X-ray images. The model acquired a comprehensive accuracy of 99.012% for three-class cases (COVID-19/Normal/Community-acquired pneumonia) and 99.99% for two-class cases (Normal/COVID-19) using CT-scan images of the chest. This high accuracy presents a new and potentially important resource to enable radiologists to identify and rapidly diagnose COVID-19 cases with only basic but widely available equipment., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Cervical cancer (CC) is the most common type of cancer in women and remains a significant cause of mortality, particularly in less developed countries, although it can be effectively treated if detected at an early stage. This study aimed to find efficient machine-learning-based classifying models to detect early stage CC using clinical data. We obtained a Kaggle data repository CC dataset which contained four classes of attributes including biopsy, cytology, Hinselmann, and Schiller. This dataset was split into four categories based on these class attributes. Three feature transformation methods, including log, sine function, and Z-score were applied to these datasets. Several supervised machine learning algorithms were assessed for their performance in classification. A Random Tree (RT) algorithm provided the best classification accuracy for the biopsy (98.33%) and cytology (98.65%) data, whereas Random Forest (RF) and Instance-Based K-nearest neighbor (IBk) provided the best performance for Hinselmann (99.16%), and Schiller (98.58%) respectively. Among the feature transformation methods, logarithmic gave the best performance for biopsy datasets whereas sine function was superior for cytology. Both logarithmic and sine functions performed the best for the Hinselmann dataset, while Z-score was best for the Schiller dataset. Various Feature Selection Techniques (FST) methods were applied to the transformed datasets to identify and prioritize important risk factors. The outcomes of this study indicate that appropriate system design and tuning, machine learning methods and classification are able to detect CC accurately and efficiently in its early stages using clinical data., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The study of the interactions of drug molecules with genetic materials plays a key role underlying the development of new drugs for many life-threatening diseases in pharmaceutical industries. Understanding their fundamental base-specific and/or groove-binding interaction is crucial to target the genetic material with an external drug, which can pave the way to curing diseases related to the genetic material. Here, we studied the interaction of cryptolepine hydrate (CRYP) with RNA under physiological conditions knowing the antimalarial and anticancer activities of the drug. Our experiments explicitly demonstrate that CRYP interacts with the guanine- and adenine-rich region within the RNA duplex. The pivotal role of the hydrophobic interaction governing the interaction is substantiated by temperature-dependent isothermal titration calorimetry experiments and spectroscopic studies. Circular dichroism study underpins a principally intercalative mode of binding of CRYP with RNA. This interaction is found to be drastically affected in the presence of magnesium salt, which has a strong propensity to coordinate with RNA nucleobases, which can in turn modulate the interaction of the drug with RNA. The temperature-dependent calorimetric results substantiate the occurrence of entropy-enthalpy compensation, which enabled us to rule out the possibility of groove binding of the drug with RNA. Furthermore, our results also show the application of host-guest chemistry in sequestering the RNA-bound drug, which is crucial to the development of safer therapeutic applications.

This paper studied the feasibility of a new solution-processed method to manufacture black tungsten nanostructures by laser conversion of tungsten hexacarbonyl precursor on the Inconel 625 substrate under argon atmosphere at ambient pressure. The results show that sublimation of the precursor can be prevented if the decomposition temperature (>170 °C) is achieved using the laser heating method. Three different laser powers from 60-400 W were used to investigate the role of laser parameters on the conversion. It was found that lower laser power of 60 W resulted in a mixture of unconverted precursor and converted tungsten. Higher laser powers >200 W resulted in α-W (BCC) in one step without further heat treatment. Different oxygen concentrations from 0.5 ppm to 21 vol% were used in the laser canister to investigate the effect of oxygen concentration on the conversion. It was found that the hard vacuum (>10 -4 torr) or hydrogen is not necessary to obtain α-W (BCC). The solar absorptance varied from 63-97%, depending on the amount of precursor deposited on the substrate and oxygen content in the laser canister. This solution-based laser conversion of tungsten precursor is a scalable method to manufacture tungsten coatings for high-temperature applications.

Machine learning and data mining-based approaches to prediction and detection of heart disease would be of great clinical utility, but are highly challenging to develop. In most countries there is a lack of cardiovascular expertise and a significant rate of incorrectly diagnosed cases which could be addressed by developing accurate and efficient early-stage heart disease prediction by analytical support of clinical decision-making with digital patient records. This study aimed to identify machine learning classifiers with the highest accuracy for such diagnostic purposes. Several supervised machine-learning algorithms were applied and compared for performance and accuracy in heart disease prediction. Feature importance scores for each feature were estimated for all applied algorithms except MLP and KNN. All the features were ranked based on the importance score to find those giving high heart disease predictions. This study found that using a heart disease dataset collected from Kaggle three-classification based on k-nearest neighbor (KNN), decision tree (DT) and random forests (RF) algorithms the RF method achieved 100% accuracy along with 100% sensitivity and specificity. Thus, we found that a relatively simple supervised machine learning algorithm can be used to make heart disease predictions with very high accuracy and excellent potential utility., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This study aimed to identify significant gene expression profiles of the human lung epithelial cells caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. We performed a comparative genomic analysis to show genomic observations between SARS-CoV and SARS-CoV-2. A phylogenetic tree has been carried for genomic analysis that confirmed the genomic variance between SARS-CoV and SARS-CoV-2. Transcriptomic analyses have been performed for SARS-CoV-2 infection responses and pulmonary arterial hypertension (PAH) patients' lungs as a number of patients have been identified who faced PAH after being diagnosed with coronavirus disease 2019 (COVID-19). Gene expression profiling showed significant expression levels for SARS-CoV-2 infection responses to human lung epithelial cells and PAH lungs as well. Differentially expressed genes identification and integration showed concordant genes (SAA2, S100A9, S100A8, SAA1, S100A12 and EDN1) for both SARS-CoV-2 and PAH samples, including S100A9 and S100A8 genes that showed significant interaction in the protein-protein interactions network. Extensive analyses of gene ontology and signaling pathways identification provided evidence of inflammatory responses regarding SARS-CoV-2 infections. The altered signaling and ontology pathways that have emerged from this research may influence the development of effective drugs, especially for the people with preexisting conditions. Identification of regulatory biomolecules revealed the presence of active promoter gene of SARS-CoV-2 in Transferrin-micro Ribonucleic acid (TF-miRNA) co-regulatory network. Predictive drug analyses provided concordant drug compounds that are associated with SARS-CoV-2 infection responses and PAH lung samples, and these compounds showed significant immune response against the RNA viruses like SARS-CoV-2, which is beneficial in therapeutic development in the COVID-19 pandemic., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the cause of coronavirus disease (COVID-19) that causes a major threat to humanity. As the spread of the virus is probably getting out of control on every day, the epidemic is now crossing the most dreadful phase. Idiopathic pulmonary fibrosis (IPF) is a risk factor for COVID-19 as patients with long-term lung injuries are more likely to suffer in the severity of the infection. Transcriptomic analyses of SARS-CoV-2 infection and IPF patients in lung epithelium cell datasets were selected to identify the synergistic effect of SARS-CoV-2 to IPF patients. Common genes were identified to find shared pathways and drug targets for IPF patients with COVID-19 infections. Using several enterprising Bioinformatics tools, protein-protein interactions (PPIs) network was designed. Hub genes and essential modules were detected based on the PPIs network. TF-genes and miRNA interaction with common differentially expressed genes and the activity of TFs are also identified. Functional analysis was performed using gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathway and found some shared associations that may cause the increased mortality of IPF patients for the SARS-CoV-2 infections. Drug molecules for the IPF were also suggested for the SARS-CoV-2 infections., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Worldwide, more than 80% of identified lung cancer cases are associated to the non-small cell lung cancer (NSCLC). We used microarray gene expression dataset GSE10245 to identify key biomarkers and associated pathways in NSCLC., Results: To collect Differentially Expressed Genes (DEGs) from the dataset GSE10245, we applied the R statistical language. Functional analysis was completed using the Database for Annotation Visualization and Integrated Discovery (DAVID) online repository. The DifferentialNet database was used to construct Protein-protein interaction (PPI) network and visualized it with the Cytoscape software. Using the Molecular Complex Detection (MCODE) method, we identify clusters from the constructed PPI network. Finally, survival analysis was performed to acquire the overall survival (OS) values of the key genes. One thousand eighty two DEGs were unveiled after applying statistical criterion. Functional analysis showed that overexpressed DEGs were greatly involved with epidermis development and keratinocyte differentiation; the under-expressed DEGs were principally associated with the positive regulation of nitric oxide biosynthetic process and signal transduction. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway investigation explored that the overexpressed DEGs were highly involved with the cell cycle; the under-expressed DEGs were involved with cell adhesion molecules. The PPI network was constructed with 474 nodes and 2233 connections., Conclusions: Using the connectivity method, 12 genes were considered as hub genes. Survival analysis showed worse OS value for SFN, DSP, and PHGDH. Outcomes indicate that Stratifin may play a crucial role in the development of NSCLC.

We study the relations between different learning paradigms and enduring changes in excitatory synaptic transmission. Here we show that auditory fear conditioning (AFC), but not olfactory fear conditioning (OFC) training, led to enduring enhancement in AMPA-mediated miniature EPSCs (mEPSCs). Moreover, olfactory unpaired training led to a stable significant reduction in excitatory synaptic transmission. However, olfactory discrimination learning (OD) did not modulate postsynaptic AMPA-mediated mEPSCs in LA. The p21-activated kinase (PAK) activity, previously shown to have a key role in maintaining persistent long-lasting enhancement in synaptic inhibition after OFC, has an opposing effect on excitatory synaptic transmission. PAK maintained the level of excitatory synaptic transmission in the amygdala in all experimental groups, except in neurons in the OFC trained rats. PAK also maintained excitatory synaptic transmission in all neurons of auditory fear conditioning and naïve training groups except in neurons of the auditory safety learning. Safety learning was previously shown in our study to enhance synaptic inhibition. We thus suggest that PAK maintains inhibitory synaptic transmission in a learning-dependent manner and on the other hand affects excitatory synaptic transmission only in groups where learning has not affected inhibitory transmission. Thus, PAK controls learning-induced changes in the excitation/inhibition balance., (Copyright © 2021. Published by Elsevier Inc.)

With the advancement and development of sophisticated bioinformatics tools, the area of computational bioinformatics and systems biology analysis is expanding day by day. The bipolar or manic-depressive disorder might be characterized as one of the most crippling mental problems that affect the people of early age and grown-ups. The objective of the present study was to investigate the association between genetic mutations in the four above listed diseases and to create a Protein-protein interaction (PPI) network or common pathways. Firstly, we need to find out the genetic relationship between them. Thus it will help us to understand the genetic association between them and help to develop the drug design for all the diseases. Genes responsible for these diseases are gathered, pre-processed, processed and mining using python scripts. This exploration is expected to carry out further measurements in the field of drug structure and also contributes to the biological and biomedical sectors.

Heat stress is a global issue constraining pig productivity, and it is likely to intensify under future climate change. Technological advances in earth observation have made tools available that enable identification and mapping livestock species that are at risk of exposure to heat stress due to climate change. Here, we present a methodology to map the current and likely future heat stress risk in pigs using R software by combining the effects of temperature and relative humidity. We applied the method to growing-finishing pigs in Uganda. We mapped monthly heat stress risk and quantified the number of pigs exposed to heat stress using 18 global circulation models and projected impacts in the 2050s. Results show that more than 800 000 pigs in Uganda will be affected by heat stress in the future. The results can feed into evidence-based policy, planning and targeted resource allocation in the livestock sector.

Herein we report the interaction of 3-hydroxyflavone (3HF) with various isomeric forms of Human Serum Albumin (HSA), namely, the N-isoform (or native HSA at pH 7.4) and the B-isoform (at pH 9.2). Spectroscopic signatures of 3HF reveal that the interaction of 3HF with the N-isoform of HSA results in significant lowering of absorbance of the neutral species (λ abs ∼ 345 nm) with concomitant increase of the anionic species (λ abs ∼ 416 nm) whereas interaction with the B-isoform of HSA leads to selective enhancement of absorbance of the anionic species. The fluorescence profile of 3HF displays marked increase of intensity of the proton transferred tautomer (λ em ∼ 538 nm) as well as the anionic species (λ em ∼ 501 nm) for both the forms of the protein. However, analyses of the associated thermodynamics through temperature-dependent isothermal titration calorimetric (ITC) indicate that the interaction of 3HF with the N-isoform of HSA is more enthalpic in the lower temperature limit while the entropy contribution predominates in the higher temperature limit. Consequently, the 3HF-HSA (N-isoform at pH 7.4) interaction reveals an unusual thermodynamic signature of a positive heat capacity change (Δ C p = 3.84 kJ mol -1 K -1 ) suggesting the instrumental role of hydrophobic hydration. On the contrary, the 3HF-HSA (B-isoform at pH 9.2) interaction shows qualitatively reverse effect. Consequently, the interaction is found to be characterized by an enthalpy-dominated hydrophobic effect (negative heat capacity change, Δ C p = -1.15 kJ mol -1 K -1 ) which is rationalized on the basis of the nonclassical hydrophobic effect.

Chronic suppurative otitis media (CSOM) is a notorious infection in developing countries causing serious local damage and threatening complications. It was a cross sectional observational study to isolate and identify aerobic bacteria and to analyze the susceptibility pattern of the aerobic bacterial isolates. It was carried out from March 2017 to July 2018 in the department of Microbiology, Mymensingh Medical College, Mymensingh, Bangladesh. Samples were collected from Outpatient of ENT department, MMCH. Out of a total 300 patients with CSOM were enrolled in this study and 209 were culture positive. Among them gram negative organisms were 129(61.72%) and gram positive organisms were 70(33.49%). The most frequently isolated organism in this study was Pseudomonas aeruginosa 72(34.44%), gram positive organisms S. aureus 63(30.14%), E. coli 21(10.04%), other Pseudomonas spp (other than P. aeruginosa) 15(7.17%), mixed bacterial infectios 10(4.78%), Proteus spp 9(4.30%), CoNS 7(3.34%), Klebsiela lspp 7(3.34%), Acinetobactor spp 5(2.39%). P. aeruginosa isolates had least resistant to imipenem and colistin, S. aureus were showed high sensitivity to Vancomycin and Linezolid and E. coli were sensitive to imipenem and amikacin, ciprofloxacin and amikacin respectively. Pseudomonas aeruginosa was the most common bacteria isolated from chronic discharging ears followed by Staphylococcus aureus. Piperacillin-Tazobactum, Ciprofioxacin, Gentamicin and Amikacin were found to be the most suitable drug for Pseudomonas aeruginosa, S. aureus and E. coli. The resistance against ceftriaxone and aztreonam was found to be very high.

Encapsulation of a persuasive anticancer drug (Sanguinarine, SGR) within microheterogeneous environment of niosome has been investigated. Utilizing steady-state and time-resolved spectroscopic methods the effects of extrinsically added salts and temperature on the photophysical properties of niosome-bound bio-active drug have been explored thoroughly. The prototropic (alkanolamine⇌ iminium) equilibrium of SGR is found to be preferentially favored toward the neutral form inside the hydrophobic interior of niosome. With addition of salts and increment of temperature the reverse tendency of stabilization of the cationic species is observed which can be explained on the basis of degree of water penetration of water molecules to the hydration layer of niosome. Furthermore, drug sequestration has been investigated via disruption of niosome applying cyclodextrins (CDs). Exploration of the effect of CDs (β-CD and γ-CD) on the niosome aids to have knowledge of the effect of CDs on cell membrane. In addition, the differential rotational relaxation behavior of SGR at various environmental circumstances has been observed to substantiate with other experimental results., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The present study reveals the effect of various divalent ions (Ca 2+ , Mg 2+ and Zn 2+ ) on the binding interaction of a prospective chloride channel blocker, 9-methylanthroate (9MA), with liposome membranes, namely, dimyristoylphosphatidylcholine (DMPC) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC). The liposome membranes DMPC and POPC differ in the unsaturation of the side-chain. The drug (9MA) is found to experience a greater degree of partitioning into the POPC lipid bilayer (containing unsaturated side-chain) in comparison to DMPC (containing saturated side-chain). The stronger 9MA-POPC binding interaction is found to be only nominally perturbed by the presence of metal salts. On the contrary, the 9MA-DMPC binding interaction is found to be significantly perturbed by the presence of metal salts and is manifested on the environment-responsive spectroscopic properties of the drug. The steady-state and picosecond-resolved fluorescence spectroscopic results reveal the effect of metal ions on DMPC bilayer to follow the trend Ca 2+ < Mg 2+ < Zn 2+ . This is also quantified by evaluating the partition coefficient of the drug into DMPC lipid in the presence of various divalent ions which is found to follow the same sequence. The degree of penetration of these cations has been rationalized on the basis of adsorption of cations on DMPC headgroup region resulting in dehydration of the headgroup along with shrinking of it., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Dairy development provides substantial potential economic opportunities for smallholder farmers in East Africa, but productivity is constrained by the scarcity of quantity and quality feed. Ruminant livestock production is also associated with negative environmental impacts, including greenhouse gas (GHG) emissions, air pollution, high water consumption, land-use change, and loss of biodiversity. Improved livestock feeding and forages have been highlighted as key entry point to sustainable intensification, increasing food security, and decreasing environmental trade-offs including GHG emission intensities. In this perspective article, we argue that farming systems approaches are essential to understand the multiple roles and impacts of forages in smallholder livelihoods. First, we outline the unique position of forages in crop-livestock systems and systemic obstacles to adoption that call for multidisciplinary thinking. Second, we discuss the importance of matching forage technologies with agroecological and socioeconomic contexts and niches, and systems agronomy that is required. Third, we demonstrate the usefulness of farming systems modeling to estimate multidimensional impacts of forages and for reducing agro-environmental trade-offs. We conclude that improved forages in East Africa are at a crossroads: if adopted by farmers at scale, they can be a cornerstone of pathways toward sustainable livestock systems in East Africa., Competing Interests: Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2020.)

In this study we explored whether learning leads to enduring changes in inhibitory synaptic transmission in lateral amygdala (LA). We revealed that olfactory discrimination (OD) learning in rats led to a long-lasting increase in postsynaptic GABA A channel-mediated miniature inhibitory postsynaptic currents (mIPSCs) in LA. Olfactory fear conditioning, but not auditory fear conditioning, also led to enduring enhancement in GABA A -mediated mIPSCs. Auditory fear conditioning, but not olfactory fear conditioning or OD learning, induced an enduring reduction in the frequency but not the current of mIPSC events. We found that p21-activated kinase (PAK) activity is needed to maintain OD and olfactory fear conditioning learning-induced enduring enhancement of mIPSCs. Further analysis revealed that OD led to an increase in GABA A channel conductance whereas olfactory fear conditioning increased the number of GABA A channels. These alterations in GABA A channels conductance and level are controlled by PAK activity. Our study shows that the learning-induced increase in postsynaptic inhibitory transmission in LA is specific to the sensory modality. However, the mechanism that mediates the increase in inhibitory transmission, namely the increase in the conductance or in the level of GABA A channel, is learning specific. NEW & NOTEWORTHY Here we studied whether learning leads to long-lasting alterations in inhibitory synaptic transmission in lateral amygdala (LA). We revealed that learning led to enduring changes in inhibitory synaptic transmission in LA that are affected by the sensory modality (auditory or olfaction) used during learning. However, the mechanism that mediated the changes in inhibitory transmission (alterations in GABA A channel level or conductance) depended on the type of learning. These long-lasting alterations are maintained by p21-activated kinase.

The present investigation reports a detailed characterization of the interaction of a cationic photosensitizer, phenosafranin (PSF) with sodium deoxycholate (NaDC) bile salt aggregates based on spectroscopic and calorimetric techniques. Our explicit spectroscopic results not only establish the occurrence of PSF-NaDC binding interaction, but also reveal marked lowering of micropolarity at the interaction site (E T (30) = 55.97 kcal mol -1 in the presence of NaDC as compared to E T (30) = 63.1 kcal mol -1 in bulk aqueous buffer). A thorough mathematical analysis of the fluorescence depolarization results based on the two-step and wobbling in cone model yields critical insight into the complex rotational relaxation dynamics of the bound drug. The impartation of motional restriction on the PSF molecules within the bile salt aggregates is evidenced from enhancement of average rotational correlation time from <τ r > = 136 ps in aqueous buffer to 1.11 ns with added NaDC (8.0 mM). This is further supported from a high value of the generalized order parameter (S = 0.81) as well as the diffusion coefficient (D w  = 1.40 × 10 12  s -1 ). Furthermore, our extensive calorimetric investigation unveils the complicated thermodynamics of the interaction process in terms of predominant entropic contribution over the enthalpic part in the lower temperature regime (TΔS = 18.84 ± 1.13 kJ mol -1 , ΔH = -5.82 ± 0.35 kJ mol -1 at 288 K) with subsequent reversal of the relative contributions with increasing temperature (TΔS = 7.54 ± 0.39 kJ mol -1 , ΔH = - 17.09 ± 0.90 kJ mol -1 at 318 K). The instrumental role of the hydrophobic effect underlying the PSF-NaDC interaction is characterized by a negative heat capacity change (ΔC p  = -364 J mol -1  K -1 ). An intriguing thermodynamic feature in terms of enthalpy-entropy compensation (with increasing temperature ΔG remains almost constant while ΔH and TΔS vary significantly) aptly corroborates the aforesaid argument and establishes an appreciable hydrophobic contribution to the overall binding energies., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Recently, titanium-based nanostructures with high nonlinear optical properties have found use in ultrafast photonic system applications. Here, we report a study of the third-order nonlinear optical property of the ${{\rm CuCo}&#95;{0.5}}{{\rm Ti}&#95;{0.5}}{{\rm O}&#95;2}$CuCo 0.5 Ti 0.5 O 2 (CCoTO) nanostructure synthesized via a simple chemical route. The 40-70 nm CCoTO nanoparticles with centrosymmetric crystalline structure show strong absorption in the 325-850 nm wavelength range due to the presence of different crystalline phases and surface vacancies. A Z-scan technique is used to study the electronic third-order nonlinearity of the synthesized nanoparticles, where a low-repetition-rate 120 fs laser source is employed to minimize thermal agitation-related nonlinearity. The CCoTO nanoparticles possess high surface defects due to oxygen- and copper-related vacancies, which are able to enhance the exciton oscillator strength resulting from the high value of third-order optical nonlinearity. The estimated values of nonlinear refractive index (${n&#95;2}$n 2 ) and nonlinear absorption coefficient ($\beta $β) of the CCoTO are $ - {1.24}\; \times \;{{10}^{ - 15}}$-1.24×10 -15 and ${3.79} \times {{10}^{ - 11}}$3.79×10 -11 , respectively, under ${188}\,\,{{\rm GW/cm}^2}$188GW/cm 2 incident intensity. The intensity-dependent nonlinear optical property of the synthesized nanoparticles is also studied under different incident laser irradiation (62.7, 93, and ${188}\,\,{{\rm GW/cm}^2}$188GW/cm 2 ). In the two-photon absorption (TPA)-dominated third-order nonlinear optical process, the values of ${n&#95;2}$n 2 and $\beta $β of CCoTO are increased with intensifying the incident laser irradiation. The obtained high value of third-order optical nonlinearity of the synthesized nanostructure can be exploited in optical power limiters, pulse power reshaping, and optical switching applications.

The interaction of a cationic photosensitizer Safranin-O with liposome membranes having similar surface charge (negative) but differing in the presence of saturation on the lipid side-chain has been studied. To this end, dimyristoyl-l-R-phosphatidylglycerol (DMPG) and 1,2-dioleoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (DOPG) phospholipids were employed to prepare small unilamellar vesicles. The dye is found to bind in the headgroup region of both the liposome membranes with significantly higher affinity to DOPG lipid containing unsaturated side chain. The effects of various cyclodextrins (CDs) on the stability of the probe-bound liposome membranes have also been investigated using steady-state and picosecond-resolved fluorescence as well as dynamic light scattering techniques. The modulations of the fluorescence properties of the lipid-bound dye were exploited to rationalize the membrane destabilization following interaction with the cyclodextrins. Experimental results reveal the selective interaction of DMPG membrane with CDs leading to rupture of the integrated structure of the liposome units accompanying release of the bound probe to the bulk aqueous phase. On the contrary, no discernible interaction of the CDs was observed with DOPG liposome membrane. Our results also show the differential extents of interaction of various CDs (α-CD, β-CD, methyl-β-CD, and γ-CD) with DMPG leading to varying degrees of release of the bound-dye molecule., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The binding interaction of a prospective anti-cancer photosensitizer, norharmane (NHM, 9H-pyrido[3,4-b]indole) with double stranded RNA reveals a primarily intercalative mode of binding. Steady-state and time-resolved fluorescence spectroscopic results demonstrate the occurrence of drug-RNA binding interaction as manifested through environment-sensitive prototropic equilibrium of NHM. However, the key finding of the present study lies in unraveling the complexities in the NHM-RNA binding thermodynamics. Isothermal Titration Calorimetry (ITC) results reveal the presence of two thermodynamically different binding modes for NHM. An extensive temperature-dependence investigation shows that the formation of Complex I is enthalpically (ΔH I  < 0) as well as entropically (TΔS I  > 0) favored with the enthalpic (entropic) contribution being increasingly predominant in the higher (lower) temperature regime. On the contrary, the formation of Complex II reveals a predominantly enthalpy-driven signature (ΔH I  < 0) along with unfavorable entropy change (TΔS I  < 0) with gradually decreasing enthalpic contribution with temperature. Such differential dependences of ΔH I and ΔH II on temperature subsequently lead to opposing heat capacity changes underlying the formation of Complex I and II (ΔC p I <0andΔC p II >0). A negative ΔC p underpins the pivotal role of 'hydrophobic effect' (release of ordered water molecules) for the formation of Complex I, while a positive ΔC p marks the thermodynamic hallmark for 'hydrophobic hydration' (solvation of hydrophobic (or nonpolar) molecular surfaces in aqueous medium) for formation of Complex II. A detailed investigation of the effect of ionic strength enables a component analysis of the total free energy change (ΔG)., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The discrete effects of a series of structurally divergent monomeric viz. Sodium Chloride (NaCl), Tetra-butyl Ammonium Chloride (TBAC) and Sodium Benzoate (NaBz) and polymeric viz. Sodium Polystyrene Sulfonate (NaPSS) electrolytes towards the morphological and/or aggregation properties of Octadecyl-trimethyl Ammonium Bromide (OTAB) micelles have been quantified spectroscopically by means of the modulations of the absorption and emission spectral properties of an extrinsic anthracene-based probe 9-methyl anthroate (9-MA) within the concerned media. Further corroboration of the spectroscopic results was acquired from the non-invasive dynamic light scattering technique. The qualitatively similar mode of action of all the monomeric salts has been explained on the basis of the archetypal Israelachvili model whereas the corresponding extent of the morphological transition of the micelles, which is found to follow the order NaBz > NaCl > TBAC, has been explained invoking the co-sphere overlap model. Conversely, to explain the aggregation behaviour of the micelles in the presence of the polymeric electrolyte, a two-step model has been formulated. According to this model, at the low concentration regime, the polymeric salt is found to only neutralize the surface charge of the micelles inducing micellar growth; whereas further increment in the concentration of the polymer assists the hydrophobic association between the micelles leading to the formation of larger aggregates, eventually causing a phase separation., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Because of the superior optical and electrical properties, copper-impregnated size tuneable high-temperature stable manganese dioxide semiconductor quantum dots (SQDs) have been successfully synthesized by a modified chemical synthesis technique. Their size-dependent dielectric properties, semiconducting properties, and current-voltage ( I- V) characteristics have been investigated. X-ray diffraction pattern and Raman spectra confirmed that the required phase is present. Because of the different sintering temperature tuneable size of SQDs has been found and confirmed by high-resolution transmission electron microscopy. The band gap energy of the material is found to be 1.25-1.67 eV, measured from Tauc plot using UV-vis absorbance spectrum and their semiconducting properties have been confirmed by the non linear current-voltage ( I- V) behavior. Most intense green emission peak of photoluminescence (PL) spectroscopy confirms the oxygen vacancy defect state. The stoke shifting of Raman spectra, UV absorption, and PL emission are the footprint of quantum confinement effect. Incorporation of a little amount of Cu in tetragonal hollandite structure of α-MnO 2 generates strain within that structure. This leads to create sufficient crystal defect state as well as rise in dielectric constant accompanied with low dielectric loss and higher ac conductivity. All these highly desirable properties make the SQDs a potential candidate for developing multifunctional photo-electronic devices. Owing to the tuneable band gap and electronic transport of the SQDs, we realized that the controllable size paves the way for designing SQDs possessing unique properties for optical and electronic device applications. Using this material as a high dielectric separator, a high-performance supercapacitor has been successfully fabricated which can light up 15 light-emitting diodes for 47 min 23 s after charging them only for 30 s.

The prime motivation of the present study is to explore the effect of reverse micellar confinement on the binding interaction of an anthracene-based probe 9-methyl anthroate with herring-sperm DNA. The structural modification of the genomic DNA from its native B-form to the non-native C-form and subsequently to the condensed Ψ-form as a function of the level of hydration (W 0 , defined as [water] / [surfactant]) of the reverse micellar core is found to reveal a remarkable regulatory role on the stability of the stacking interaction (intercalation) of the probe within the DNA helix; the interaction being progressively stabilized at higher W 0 . Particularly, a close perusal of the dynamical aspects of the interaction is found to be counter-intuitive to the popular notion of the properties of the confined water within the reverse micelles typically approaching bulk-like properties at sufficiently high hydration levels (W 0  > 10)., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this article, dataset and detailed data analysis results of Type-1 Diabetes has been given. Now-a-days Type-1 Diabetes is an appalling disease in Bangladesh. Total 306 person data (Case group- 152 and Control Group- 154) has been collected from Dhaka based on a specific questioner. The questioner includes 22 factors which were extracted by research studies. The association and significance level of factors has been elicited by using Data mining and Statistical Approach and shown in the Tables of this article. Moreover, parametric probability along with decision tree has been formed to show the effectiveness of the data was provided. The data can be used for future work like risk prediction and specific functioning on Type-1 Diabetes.