DEEP-EP: Identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery.

Epigenetic proteins (EP) play a role in the progression of a wide range of diseases, including autoimmune disorders, neurological disorders, and cancer. Recognizing their different functions has prompted researchers to investigate them as potential therapeutic targets and pharmacological targets. This paper proposes a novel deep learning-based model that accurately predicts EP. This study introduces a novel deep learning-based model that accurately predicts EP. Our approach entails generating two distinct datasets for training and evaluating the model. We then use three distinct strategies to transform protein sequences to numerical representations: Dipeptide Deviation from Expected Mean (DDE), Dipeptide Composition (DPC), and Group Amino Acid (GAAC). Following that, we train and compare the performance of four advanced deep learning models algorithms: Ensemble Residual Convolutional Neural Network (ERCNN), Generative Adversarial Network (GAN), Convolutional Neural Network (CNN), and Gated Recurrent Unit (GRU). The DDE encoding combined with the ERCNN model demonstrates the best performance on both datasets. This study demonstrates deep learning's potential for precisely predicting EP, which can considerably accelerate research and streamline drug discovery efforts. This analytical method has the potential to find new therapeutic targets and advance our understanding of EP activities in disease.

Low-Complexity 2D-DOD and 2D-DOA Estimation in Bistatic MIMO Radar Systems: A Reduced-Dimension MUSIC Algorithm Approach.

This paper presents a new technique for estimating the two-dimensional direction of departure (2D-DOD) and direction of arrival (2D-DOA) in bistatic uniform planar array Multiple-Input Multiple-Output (MIMO) radar systems. The method is based on the reduced-dimension (RD) MUSIC algorithm, aiming to achieve improved precision and computational efficiency. Primarily, this pioneering approach efficiently transforms the four-dimensional (4D) estimation problem into two-dimensional (2D) searches, thus reducing the computational complexity typically associated with conventional MUSIC algorithms. Then, exploits the spatial diversity of array response vectors to construct a 4D spatial spectrum function, which is crucial in resolving the complex angular parameters of multiple simultaneous targets. Finally, the objective is to simplify the spatial spectrum to a 2D search within a 4D measurement space to achieve an optimal balance between efficiency and accuracy. Simulation results validate the effectiveness of our proposed algorithm compared to several existing approaches, demonstrating its robustness in accurately estimating 2D-DOD and 2D-DOA across various scenarios. The proposed technique shows significant computational savings and high-resolution estimations and maintains high precision, setting a new benchmark for future explorations in the field.

AFP-SPTS: An Accurate Prediction of Antifreeze Proteins Using Sequential and Pseudo-Tri-Slicing Evolutionary Features with an Extremely Randomized Tree.

The development of intracellular ice in the bodies of cold-blooded living organisms may cause them to die. These species yield antifreeze proteins (AFPs) to live in subzero temperature environments. Additionally, AFPs are implemented in biotechnological, industrial, agricultural, and medical fields. Machine learning-based predictors were presented for AFP identification. However, more accurate predictors are still highly desirable for boosting the AFP prediction. This work presents a novel approach, named AFP-SPTS, for the correct prediction of AFPs. We explored the discriminative features with four schemes, namely, dipeptide deviation from the expected mean (DDE), reduced amino acid alphabet (RAAA), grouped dipeptide composition (GDPC), and a novel representative method, called pseudo-position-specific scoring matrix tri-slicing (PseTS-PSSM). Considering the advantages of ensemble learning strategy, we fused each feature vector into different combinations and trained the models with five machine learning algorithms, i.e., multilayer perceptron (MLP), extremely randomized tree (ERT), decision tree (DT), random forest (RF), and AdaBoost. Among all models, PseTS-PSSM + RAAA with an extremely randomized tree attained the best outcomes. The proposed predictor (AFP-SPTS) boosted the accuracies of AFPs in the literature by 1.82 and 4.1%.

Pediatric Malignant Pelvic Paraganglioma-A Diagnostic and Surgical Challenge.

Pheochromocytoma are chromaffin cell-derived tumors that have an exceptionally high genetic predisposition. The presentation of extra-adrenal and pelvic paraganglioma (PGL) in children is uncommon. Due to the relative rarity, PGL tumors' presentation and disease behavior may vary. Genetic testing, imaging, and biochemical investigation are employed to diagnose PGL. Surgical resection with preoperative angioembolization has been practiced in alleviating the burden of torrential intraoperative bleeding.

Retention of methyl iodide on metal and TEDA impregnated activated carbon using indigenously developed setup.

Removal of methyl iodide (CH3I) from the air present within nuclear facilities is a critical issue. In case of any nuclear accident, there is a great need to mitigate the radioactive organic iodide immediately as it accumulates in human bodies, causing severe consequences. Current research focuses on removing organic iodides, for which the surface of activated carbon (AC) was modified by impregnating it with different metals individually, i.e. Ag, Ni, Zn, Cu and with the novel combination of these four metals (AZNC). After the impregnation of metals, triethylenediamine (TEDA) was coated on metal impregnated activated carbon (IAC) surface. The adsorption capacity of the combination of four metals IAC was found to be 276 mg/g as the maximum for the trapping of CH3I. Whereas TEDA-metal impregnation on ACs enhanced the removal efficiency of CH3I up to 352 mg/g. After impregnation, adsorption capacity of AZNC and AZNCT is significantly higher as compared to AC. According to the finding, t5% of AZNCT IAC is 46 min, which is considerably higher than the t5% of other tested adsorbents. According to isotherm fitting data, Langmuir isotherm was found superior for describing CH3I sorption onto AC and IACs. Kinetics study shows that pseudo second order model represented the sorption of CH3I more accurately than the pseudo first order. Thermodynamic studies gave negative value of ΔG which shows that the reaction is spontaneous in nature. Based on the findings, AZNCT IAC appears to have a great potential for air purification applications in order to obtain clean environment.

Evaluation of the Resources and Inequities Among Pediatric Critical Care Facilities in Pakistan.

OBJECTIVES: To evaluate nationwide pediatric critical care facilities and resources in Pakistan. DESIGN: Cross-sectional observational study. SETTING: Accredited pediatric training facilities in Pakistan. PATIENTS: None. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A survey was conducted using the Partners in Health 4S (space, staff, stuff, systems) framework, via email or telephone correspondence. We used a scoring system in which each item in our checklist was given a score of 1, if available. Total scores were added up for each component. Additionally, we stratified and analyzed the data between the public and private healthcare sectors. Out of 114 hospitals (accredited for pediatric training), 76 (67%) responded. Fifty-three (70%) of these hospitals had a PICU, with a total of 667 specialized beds and 217 mechanical ventilators. There were 38 (72%) public hospitals and 15 (28%) private hospitals. There were 20 trained intensivists in 16 of 53 PICUs (30%), while 25 of 53 PICUs (47%) had a nurse-patient ratio less than 1:3. Overall, private hospitals were better resourced in many domains of our four Partners in Health framework. The Stuff component scored more than the other three components using analysis of variance testing ( p = 0.003). On cluster analysis, private hospitals ranked higher in Space and Stuff, along with the overall scoring. CONCLUSIONS: There is a general lack of resources, seen disproportionately in the public sector. The scarcity of qualified intensivists and nursing staff poses a challenge to Pakistan's PICU infrastructure.

In Silico Characterisation of the Aedes aegypti Gustatory Receptors.

Aedes aegypti, also known as the dengue mosquito or the yellow fewer mosquito, is the vector of dengue, chikungunya, Zika, Mayaro and yellow fever viruses. The A. aegypti genome contains an array of gustatory receptor (GR) proteins that are related to the recognition of taste. In this study, we performed in silico molecular characterization of all 72 A. aegypti GRs reported in the latest version of A. aegypti genome AaegL5. Phylogenetic analysis classified the receptors into three major clads. Multiple GRs were found to encode multiple transcripts. Physicochemical attributes such as the aliphatic index, hydropathicity index and isoelectric point indicated that A. aegypti gustatory receptors are highly stable and are tailored to perform under a variety of cellular environments. Analysis for subcellular localization indicated that all the GRs are located either in the extracellular matrix or the plasma membrane. Results also indicated that the GRs are distributed mainly on chromosomes 2 and 3, which house 22 and 49 GRs, respectively, whereas chromosome 1 houses only one GR. NCBI-CDD analysis showed the presence of a highly conserved 7tm_7 chemosensory receptor protein superfamily that includes gustatory and odorant receptors from insect species Anopheles gambiae and Drosophila melanogaster. Further, three significantly enriched ungapped motifs in the protein sequence of all 72 A. aegypti gustatory receptors were found. High-quality 3D models for the tertiary structures were predicted with significantly higher confidence, along with ligand-binding residues. Prediction of S-nitrosylation sites indicated the presence of target cysteines in all the GRs with close proximity to the ligand-bindings sites within the 3D structure of the receptors. In addition, two highly conserved motifs inside the GR proteins were discovered that house a tyrosine (Y) and a cysteine (C) residue which may serve as targets for NO-mediated tyrosine nitration and S-nitrosylation, respectively. This study will help devise strategies for functional genomic studies of these important receptor molecules in A. aegypti and other mosquito species through in vitro and in vivo studies.

Dihydropyrimidone Derivatives as Thymidine Phosphorylase Inhibitors: Inhibition Kinetics, Cytotoxicity, and Molecular Docking.

Overexpression of the thymidine phosphorylase (TP) enzyme induces angiogenesis, which eventually leads to metastasis and tumor growth. The crucial role of TP in cancer development makes it an important target for anticancer drug discovery. Currently, there is only one US-FDA-approved drug, i.e., Lonsurf, a combination of trifluridine and tipiracil, for the treatment of metastatic colorectal cancer. Unfortunately, numerous adverse effects are associated with its use, such as myelosuppression, anemia, and neutropenia. Since the last few decades, the discovery of new, safe, and effective TP inhibitory agents has been rigorously pursued. In the present study, we evaluated a series of previously synthesized dihydropyrimidone derivatives 1-40 for their TP inhibitory potential. Compounds 1, 12, and 33 showed a good activity with IC50 = 314.0 ± 0.90, 303.5 ± 0.40, and 322.6 ± 1.60 µM, respectively. The results of mechanistic studies revealed that compounds 1, 12, and 33 were the non-competitive inhibitors. These compounds were also evaluated for cytotoxicity against 3T3 (mouse fibroblast) cells and were found to be non-cytotoxic. Finally, the molecular docking suggested the plausible mechanism of non-competitive inhibition of TP. The current study thus identifies some dihydropyrimidone derivatives as potential inhibitors of TP, which can be further optimized as leads for cancer treatment.

Bacterial and Fungal Biocontrol Agents for Plant Disease Protection: Journey from Lab to Field, Current Status, Challenges, and Global Perspectives.

Plants are constantly exposed to various phytopathogens such as fungi, Oomycetes, nematodes, bacteria, and viruses. These pathogens can significantly reduce the productivity of important crops worldwide, with annual crop yield losses ranging from 20% to 40% caused by various pathogenic diseases. While the use of chemical pesticides has been effective at controlling multiple diseases in major crops, excessive use of synthetic chemicals has detrimental effects on the environment and human health, which discourages pesticide application in the agriculture sector. As a result, researchers worldwide have shifted their focus towards alternative eco-friendly strategies to prevent plant diseases. Biocontrol of phytopathogens is a less toxic and safer method that reduces the severity of various crop diseases. A variety of biological control agents (BCAs) are available for use, but further research is needed to identify potential microbes and their natural products with a broad-spectrum antagonistic activity to control crop diseases. This review aims to highlight the importance of biocontrol strategies for managing crop diseases. Furthermore, the role of beneficial microbes in controlling plant diseases and the current status of their biocontrol mechanisms will be summarized. The review will also cover the challenges and the need for the future development of biocontrol methods to ensure efficient crop disease management for sustainable agriculture.

In silico analysis of AhyI protein and AI-1 inhibition using N-cis-octadec-9z-enoyl-l-homoserine lactone inhibitor in Aeromonas hydrophila.

AhyI is homologous to the protein LuxI and is conserved throughout bacterial species including Aeromonas hydrophila. A. hydrophila causes opportunistic infections in fish and other aquatic organisms. Furthermore, this pathogennot only poses a great risk for the aquaculture industry, but also for human public health. AhyI (expressing acylhomoserine lactone) is responsible for the biosynthesis of autoinducer-1 (AI-1), commonly referred to as a quorum sensing (QS) signaling molecule, which plays an essential role in bacterial communication. Studying protein structure is essential for understanding molecular mechanisms of pathogenicity in microbes. Here, we have deduced a predicted structure of AhyI protein and characterized its function using in silico methods to aid the development of new treatments for controlling A.hydrophila infections. In addition to modeling AhyI, an appropriate inhibitor molecule was identified via high throughput virtual screening (HTVS) using mcule drug-like databases.The AhyI-inhibitor N-cis-octadec-9Z-enoyl-l-Homoserine lactone was selected withthe best drug score. In order to understand the pocket sites (ligand binding sites) and their interaction with the selected inhibitor, docking (predicted protein binding complex) servers were used and the selected ligand was docked with the predicted AhyI protein model. Remarkably, N-cis-octadec-9Z-enoyl-l-Homoserine lactone established interfaces with the protein via16 residues (V24, R27, F28, R31, W34, V36, D45, M77, F82, T101, R102, L103, 104, V143, S145, and V168), which are involved with regulating mechanisms of inhibition. These proposed predictions suggest that this inhibitor molecule may be used as a novel drug candidate for the inhibition of auto-inducer-1 (AI-1) activity.The N-cis-octadec-9Z-enoyl-l-Homoserine lactone inhibitor molecule was studied on cultured bacteria to validate its potency against AI-1 production. At a concentration of 40 µM, optimal inhibition efficiency of AI-1 was observedin bacterial culture media.These results suggest that the inhibitor molecule N-cis-octadec-9Z-enoyl-l-Homoserine lactone is a competitive inhibitor of AI-1 biosynthesis.

Role of MicroRNAs and their corresponding ACE2/Apelin signaling pathways in hypertension.

Hypertension is controlled via the alteration of microRNAs (miRNAs), their therapeutic targets angiotensin II type I receptor (AT1R) and cross talk of signaling pathways. The stimulation of the Ang II/AT1R pathway by deregulation of miRNAs, has also been linked to cardiac remodeling as well as the pathophysiology of high blood pressure. As miRNAs have been associated to ACE2/Apelin and Mitogen-activated protein kinases (MAPK) signaling, it has revealed an utmost protective impact over hypertension and cardiovascular system. The ACE2-coupled intermodulation between RAAS, Apelin system, MAPK signaling pathways, and miRNAs reveal the practicalities of high blood pressure. The research of miRNAs may ultimately lead to the expansion of an innovative treatment strategy for hypertension, which indicates the need to explore them further at the molecular level. Therefore, here we have focused on the mechanistic importance of miRNAs in hypertension, ACE2/Apelin signaling as well as their biological functions, with a focus on interplay and crosstalk between ACE2/Apelin signaling, miRNAs, and hypertension, and the progress in miRNA-based diagnostic techniques with the goal of facilitating the development of new hypertension-controlling therapeutics.

Multilayer dynamic ensemble model for intensive care unit mortality prediction of neonate patients.

Robust and rabid mortality prediction is crucial in intensive care units because it is considered one of the critical steps for treating patients with serious conditions. Combining mortality prediction with the length of stay (LoS) prediction adds another level of importance to these models. No studies in the literature predict such tasks for neonates, especially using time-series data and dynamic ensemble techniques. Dynamic ensembles are novel techniques that dynamically select the base classifiers for each new case. Medically, implementing an accurate machine learning model is insufficient to gain the trust of physicians. The model must be able to justify its decisions. While explainable AI (XAI) techniques can be used to handle this challenge, no studies have been done in this regard for neonate monitoring in the neonatal intensive care unit (NICU). This study utilizes advanced machine learning approaches to predict mortality and LoS through data-driven learning. We propose a multilayer dynamic ensemble-based model to predict mortality as a classification task and LoS as a regression task for neonates admitted to the NICU. The model has been built based on the patient's time-series data of the first 24 h in the NICU. We utilized a cohort of 3,133 infants from the MIMIC-III real dataset to build and optimize the selected algorithms. It has shown that the dynamic ensemble models achieved better results than other classifiers, and static ensemble regressors achieved better results than classical machine learning regressors. The proposed optimized model is supported by three well-known explainability techniques of SHAP, decision tree visualization, and rule-based system. To provide online assistance to physicians in monitoring and managing neonates in the NICU, we implemented a web-based clinical decision support system based on the most accurate models and selected XAI techniques. The code of the proposed models is publicly available at https://github.com/InfoLab-SKKU/neonateMortalityPrediction.

Polyethylene glycol capped copper ferrite porous nanostructured materials for efficient photocatalytic degradation of bromophenol blue.

Three different types (blank, annealed, and functionalized) of copper ferrite nanoparticles (CuFe2O4) were synthesized by the co-precipitation method. The CuFe2O4 NPs were characterized by Fourier transform infrared (FTIR), Scanning electron microscopy (SEM), X-ray diffraction (XRD), and Energy-dispersive X-ray spectroscopy (EDX) techniques. FTIR analysis confirmed that 3-APTES is successfully grafted on the surface of CuFe2O4 NPs. XRD results show the amorphous nature of blank CuFe2O4 NPs, and crystalline structure was observed for annealed and functionalized CuFe2O4 NPs. XRD results revealed that crystallite size ranges from 23.6 to 34.6 nm. SEM micrographs of blank CuFe2O4 NPs show the irregular shape and size of the nanostructure. The spherical and strongly linked structure was seen in the micrograph of functionalized CuFe2O4 NPs. EDX analysis revealed the nanostructure composed of Fe, Cu, O, and a small percentage of Si. The photocatalytic degradation efficiency of synthesized CuFe2O4 NPs was examined under UV irradiation in an aqueous medium against bromophenol blue (BPB) dye. The effect of different parameters such as irradiation time and pH on the photodegradation of BPB dye was studied by all three types of CuFe2O4 photocatalyst. Results show that the maximum photocatalytic degradation efficiency was observed for functionalized CuFe2O4 nanoparticles that degraded 98% of BPB dye in the acidic medium at pH = 1. The optimum contact time for dye degradation was 120 min by synthesized photocatalyst. Photodegradation performance of blank and annealed CuFe2O4 NPs is less than 90%. The synthesized CuFe2O4 NPs were recycled and reused, which shows good photocatalytic degradation efficiency up to 4 consecutive cycles. The kinetic model displayed that degradation reaction followed pseudo 1st order kinetics. The blank, annealed, and functionalized CuFe2O4 NPs have turnover numbers of 10.7x10 (Mudhoo et al., 2019), 12.9x10 (Mudhoo et al., 2019), and 22.2x10 (Mudhoo et al., 2019) (kg-1 sec-1) accordingly. In conclusion, all results revealed the high efficiency of prepared photocatalyst for tested hazardous dye from wastewater and encouraged more work on photodegradation of organic pollutants from wastewater.

Using Modified Technology Acceptance Model to Evaluate the Adoption of a Proposed IoT-Based Indoor Disaster Management Software Tool by Rescue Workers.

Advancements in IoT technology have been instrumental in the design and implementation of various ubiquitous services. One such design activity was carried out by the authors of this paper, who proposed a novel cloud-centric IoT-based disaster management framework and developed a multimedia-based prototype that employed real-time geographical maps. The multimedia-based system can provide vital information on maps that can improve the planning and execution of evacuation tasks. This study was intended to explore the acceptance of the proposed technology by the specific set of users that could potentially lead to its adoption by rescue agencies for carrying out indoor rescue and evacuation operations. The novelty of this study lies in the concept that the acceptability of the proposed system was ascertained before the complete implementation of the system, which prevented potential losses of time and other resources. Based on the extended Technology Acceptance Model (TAM), we proposed a model included factors such as perceived usefulness, perceived ease of use, attitude, and behavioural intention. Other factors include trust in the proposed system, job relevance, and information requirement characteristics. Online survey data collected from the respondents were analyzed using structural equation modelling (SEM) revealed that although perceived ease of use and job relevance had significant impacts on perceived usefulness, trust had a somewhat milder impact on the same. The model also demonstrated a statistically moderate impact of trust and perceived ease of use on behavioural intention. All other relationships were statistically strong. Overall, all proposed relationships were supported, with the research model providing a better understanding of the perceptions of users towards the adoption of the proposed technology. This would be particularly useful while making decisions regarding the inclusion of various features during the industrial production of the proposed system.

The DnaJ-like Zinc Finger Protein ORANGE Promotes Proline Biosynthesis in Drought-Stressed Arabidopsis Seedlings.

Orange (OR) is a DnaJ-like zinc finger protein with both nuclear and plastidial localizations. OR, and its orthologs, are highly conserved in flowering plants, sharing a characteristic C-terminal tandem 4× repeats of the CxxCxxxG signature. It was reported to trigger chromoplast biogenesis, promote carotenoid accumulation in plastids of non-pigmented tissues, and repress chlorophyll biosynthesis and chloroplast biogenesis in the nucleus of de-etiolating cotyledons cells. Its ectopic overexpression was found to enhance plant resistance to abiotic stresses. Here, we report that the expression of OR in Arabidopsis thaliana was upregulated by drought treatment, and seedlings of the OR-overexpressing (OE) lines showed improved growth performance and survival rate under drought stress. Compared with the wild-type (WT) and OR-silencing (or) lines, drought-stressed OE seedlings possessed lower contents of reactive oxygen species (such as H2O2 and O2-), higher activities of both superoxide dismutase and catalase, and a higher level of proline content. Our enzymatic assay revealed a relatively higher activity of Δ1-pyrroline-5-carboxylate synthase (P5CS), a rate-limiting enzyme for proline biosynthesis, in drought-stressed OE seedlings, compared with the WT and or lines. We further demonstrated that the P5CS activity could be enhanced by supplementing exogenous OR in our in vitro assays. Taken together, our results indicated a novel contribution of OR to drought tolerance, through its impact on proline biosynthesis.

Magnetically recoverable poly (methyl methacrylate-acrylic acid)/iron oxide magnetic composites nanomaterials with hydrophilic wettability for efficient oil-water separation.

Due to the environmental and production problems of emulsion, it is important to efficiently separate oil-water emulsion to meet the refinery requirement and clean up oil spills. Synthesis of a universal demulsifier is not an easy task because the physical properties of crude oil vary, which makes its characterization and demulsification procedure difficult. To overcome this problem, hydrophilic and magnetically recoverable poly (methyl methacrylate-acrylic acid)/iron oxide magnetic composite nanoparticles ((P(MMA-AA)/Fe3O4 NPs) were developed as an efficient and economical demulsifier via soap-free emulsion polymerization. To characterize the magnetic composite NPs for their appropriate surface morphology and magnetic domain, TEM, FTIR, VSM, and TGA analyses were carried out. The newly synthesized NPs displayed good hydrophilic properties as they migrated quickly to the aqueous emulsion phase, which was also reassured by their water contact angle of 75°. They exhibit strong magnetic characteristics (20 amu/g) in the oil-water emulsion, makings the hydrophilic wettability capable and attractive to the external magnet. Experimental results revealed that the prepared magnetic composite NPs separated 99% of the water from stable emulsion in 30 min and could be recycled 8 times through magnetic separation. The recycled magnetic composite NPs maintain their hydrophilic wettability and efficiency in separating oil-water emulsion, making them economical and commercially viable. The migration of magnetic composite NPs to the aqueous phase in the stable emulsion with a strong magnetic domain explains the coalescence of emulsified water droplets and their quick separation from the stable emulsions through the external magnet.

Comparison of MRCP and ERCP findings: A retrospective secondary data analysis.

Objective: To compare the findings of magnetic resonance cholangiopancreatography and endoscopic retrograde cholangiopancreatography in patients presenting with bile duct disorders. METHODS: The retrospective secondary-data study was conducted at the Gastroenterology Department of Lady Reading Hospital, Peshawar, Pakistan, and comprised data of patients who presented with bile duct disorders from June2019 to May2020. Data was analysed using SPSS 25. RESULTS: Of the 92 patients, 41(44.6%) were males and 51(55.4%) were females. The overall mean age was 50.12 ± 16.7 years (range: 13-80 years). Out of 28 bile duct calculi cases detected by endoscopic retrograde cholangiopancreatography, 25(89.3%) were detected by magnetic resonance cholangiopancreatography, and, of the 64 without calculi, it was 50(78.1%). Out of 8 bile duct strictures detected by endoscopic retrograde cholangiopancreatography, 3(37.5%) were correctly diagnosed by magnetic resonance cholangiopancreatography, and, of the 84 unaffected patients, were excluded 79(94%). Out of 64 bile duct dilatation cases, magnetic resonance cholangiopancreatography correctly diagnosed 59(92.2%), and, of the 28 unaffected patients, it excluded 27(96.4%). CONCLUSIONS: For bile duct stone and dilation, magnetic resonance cholangiopancreatography was found to have high diagnostic accuracy.

Do green supply chain management practices improve organizational resilience during the COVID-19 crisis? A survival analysis of global firms.

This study investigates whether green supply chain management (GSCM) practices help companies to be resilient against the buffer effect in the context of COVID-19. Building on the instrumental version of stakeholder theory, companies implementing GSCM practices should build environmental skills and competitive advantage to cope with a crisis caused by supply chain disruptions. Our survival analysis, conducted on 5,696 firms headquartered in 35 countries, shows clear evidence that GSCM companies' market prices recover quickly from the shock. Considering mounting pressure on environmental issues, this study documents the new benefits of GSCM for companies confronted with a global financial shock. By applying a large sample, the study has originality and implications for stakeholders, including investors, governments, and policymakers, to push firms to become more eco-friendly and resilient.

Trophic transfer and toxicity of heavy metals from dengue mosquito Aedes aegypti to predator dragonfly Tramea cophysa.

Heavy metal pollution in aquatic habitats can be detrimental to both prey and predators in a food web. To investigate the potential for bio-transfer and bioaccumulation of heavy metals between specific trophic levels, 3rd instar larvae of Aedes aegypti were exposed to mercury (Hg), lead (Pb), cadmium (Cd), copper (Cu), and zinc (Zn) for three consecutive generations and fed to dragonfly (Tramea cophysa) nymphs. Exposure to Hg caused the highest mortality in A. aegypti larvae and T. cophysa nymphs. Bioaccumulation and life-history parameters of A. aegypti, including egg hatching time, larval and pupal duration, male and female life span, and fecundity, were also evaluated after metals exposure. All life-history parameters except larval duration were significantly affected by heavy metal treatments. Bioaccumulation of metals in A. aegypti larvae and adults gradually and significantly increased from 1st to 3rd generation. To the best of our knowledge, this is the first study describing the acute toxicity of heavy metals to mosquitoes. Our study shows that heavy metals cause dietary toxicity to an aquatic predator, dragonfly, via trophic transfer, which could have considerable consequences on aquatic ecosystems.

Toxicological risk assessment of some commonly used insecticides on Cotesia flavipes, a larval parasitoid of the spotted stem borer Chilo partellus.

Cotesia flavipes Cameron is an important larval parasitoid exploited for the control of the spotted stem borer, Chilo partellus (Swinhoe). Several studies have evaluated the toxic effects of insecticides on C. partellus, however, little is known about non-target effects of insecticides on this parasitoid, when used to control C. partellus. This laboratory study evaluated the lethal and sublethal effects of twelve insecticides on C. flavipes. Residual toxicity tests showed that organophosphates (chlorpyrifos, triazophos and profenofos) exhibited highest contact toxicity to C. flavipes adults with a LC50 range from 0.63 to 1.05 mg a.i/l, while neonicotinoids (nitenpyram, acetamiprid and imidacloprid) were less toxic to C. flavipes with a LC50 range from 1.27 to 139.48 mg a.i/l. Sugar-insecticide feeding bioassays showed that organophosphates, pyrethroids (cypermethrin, bifenthrin and lambda-cyhalothrin) and carbamates (thiodicarb, carbaryl and methomyl) were highly toxic to C. flavipes adults and caused 100% mortality at 48 h of exposure, while imidacloprid caused 66% mortality at 48 h of exposure. Risk quotient analysis showed that among all tested insecticides, imidacloprid and acetamiprid were less toxic to C. flavipes adults with a risk quotient value of 0.88 and 1.6, respectively. Furthermore, exposure of immature C. flavipes through their host bodies significantly decreased the parasitism rate at their F1 and F2 generations. Risk quotient analysis of insecticides indicated that imidacloprid and acetamiprid were the least toxic to C. flavipes. This study provides important information that will be used in incorporating the most suitable insecticides in integrated pest management programs with reduced negative impacts on non-target beneficial arthropods.