Phosphatidylinositol (4,5)-bisphosphate drives the formation of EGFR and EphA2 complexes.

Receptor tyrosine kinases (RTKs) regulate many cellular functions and are important targets in pharmaceutical development, particularly in cancer treatment. EGFR and EphA2 are two key RTKs that are associated with oncogenic phenotypes. Several studies have reported functional interplay between these receptors, but the mechanism of interaction is still unresolved. Here we utilize a time-resolved fluorescence spectroscopy called PIE-FCCS to resolve EGFR and EphA2 interactions in live cells. We tested the role of ligands and found that EGF, but not ephrin A1 (EA1), stimulated hetero-multimerization between the receptors. To determine the effect of anionic lipids, we targeted phospholipase C (PLC) activity to alter the abundance of phosphatidylinositol (4,5)-bisphosphate (PIP 2 ). We found that higher PIP 2 levels increased homo-multimerization of both EGFR and EphA2, as well as hetero-multimerization. This study provides a direct characterization of EGFR and EphA2 interactions in live cells and shows that PIP 2 can have a substantial effect on the spatial organization of RTKs.

Arbuscular mycorrhizal fungi promote growth and enhance the accumulation of bioactive compounds in Tomato (Solanum lycopersicum L.).

Arbuscular mycorrhizal fungi (AMF) have been known to enhance plant growth and nutrient uptake. In this study, we investigated the effects of Funneliformis mosseae, Rhizophagus intraradices, and their co-inoculation on the growth and biochemical composition of tomato (Solanum lycopersicum L.) plants. The findings demonstrated that the inoculation of AMF significantly enhanced shoot and root length, shoot and root dry weight, number of fruits per plant, as well as concentrations of anthocyanin, phenolic compounds, and antioxidants in tomato plants. Both individual and co-inoculation of AMF also significantly increased nitrogen, phosphorus, and potassium concentrations in tomato plants. Our findings suggest that AMF can be used as a potential biofertilizer to enhance the growth and biochemical composition of tomato plants.

Lecanemab blocks the effects of the Aß/fibrinogen complex on blood clots and synapse toxicity in organotypic culture.

Proteinaceous brain inclusions, neuroinflammation, and vascular dysfunction are common pathologies in Alzheimer's disease (AD). Vascular deficits include a compromised blood-brain barrier, which can lead to extravasation of blood proteins like fibrinogen into the brain. Fibrinogen's interaction with the amyloid-beta (Aß) peptide is known to worsen thrombotic and cerebrovascular pathways in AD. Lecanemab, an FDA-approved antibody therapy for AD, clears Aß plaque from the brain and slows cognitive decline. Here, we show that lecanemab blocks fibrinogen's binding to Aß protofibrils, preventing Aß/fibrinogen-mediated delayed fibrinolysis and clot abnormalities in vitro and in human plasma. Additionally, we show that lecanemab dissociates the Aß/fibrinogen complex and prevents fibrinogen from exacerbating Aß-induced synaptotoxicity in mouse organotypic hippocampal cultures. These findings reveal a possible protective mechanism by which lecanemab may slow disease progression in AD.

The ß2-adrenergic receptor associates with CXCR4 multimers in human cancer cells.

While the existence and functional role of class C G-protein-coupled receptors (GPCR) dimers is well established, there is still a lack of consensus regarding class A and B GPCR multimerization. This lack of consensus is largely due to the inherent challenges of demonstrating the presence of multimeric receptor complexes in a physiologically relevant cellular context. The C-X-C motif chemokine receptor 4 (CXCR4) is a class A GPCR that is a promising target of anticancer therapy. Here, we investigated the potential of CXCR4 to form multimeric complexes with other GPCRs and characterized the relative size of the complexes in a live-cell environment. Using a bimolecular fluorescence complementation (BiFC) assay, we identified the ß2 adrenergic receptor (ß2AR) as an interaction partner. To investigate the molecular scale details of CXCR4-ß2AR interactions, we used a time-resolved fluorescence spectroscopy method called pulsed-interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS). PIE-FCCS can resolve membrane protein density, diffusion, and multimerization state in live cells at physiological expression levels. We probed CXCR4 and ß2AR homo- and heteromultimerization in model cell lines and found that CXCR4 assembles into multimeric complexes larger than dimers in MDA-MB-231 human breast cancer cells and in HCC4006 human lung cancer cells. We also found that ß2AR associates with CXCR4 multimers in MDA-MB-231 and HCC4006 cells to a higher degree than in COS-7 and CHO cells and in a ligand-dependent manner. These results suggest that CXCR4-ß2AR heteromers are present in human cancer cells and that GPCR multimerization is significantly affected by the plasma membrane environment.

A comprehensive review of critical analysis of biodegradable waste PCM for thermal energy storage systems using machine learning and deep learning to predict dynamic behavior.

This article explores the use of phase change materials (PCMs) derived from waste, in energy storage systems. It emphasizes the potential of these PCMs in addressing concerns related to fossil fuel usage and environmental impact. This article also highlights the aspects of these PCMs including reduced reliance on renewable resources minimized greenhouse gas emissions and waste reduction. The study also discusses approaches such as integrating nanotechnology to enhance thermal conductivity and utilizing machine learning and deep learning techniques for predicting dynamic behavior. The article provides an overall view of research on biodegradable waste-based PCMs and how they can play a promising role in achieving energy-efficient and sustainable thermal storage systems. However, specific conclusions drawn from the presented results are not explicitly outlined, leaving room, for investigation and exploration in this evolving field. Artificial neural network (ANN) predictive models for thermal energy storage devices perform differently. With a 4% adjusted mean absolute error, the Gaussian radial basis function kernel Support Vector Regression (SVR) model captured heat-related charging and discharging issues. The ANN model predicted finned tube heat and heat flux better than the numerical model. SVM models outperformed ANN and ANFIS in some datasets. Material property predictions favored gradient boosting, but Linear Regression and SVR models performed better, emphasizing application- and dataset-specific model selection. These predictive models provide insights into the complex thermal performance of building structures, aiding in the design and operation of energy-efficient systems. Biodegradable waste-based PCMs' sustainability includes carbon footprint, waste reduction, biodegradability, and circular economy alignment. Nanotechnology, machine learning, and deep learning improve thermal conductivity and prediction. Circular economy principles include waste reduction and carbon footprint reduction. Specific results-based conclusions are not stated. Presenting a comprehensive overview of current research highlights biodegradable waste-based PCMs' potential for energy-efficient and sustainable thermal storage systems.

Groundwater quality characterization using an integrated water quality index and multivariate statistical techniques.

This study attempts to characterize and interpret the groundwater quality (GWQ) using a GIS environment and multivariate statistical approach (MSA) for the Jakham River Basin (JRB) in Southern Rajasthan. In this paper, analysis of various statistical indicators such as the Water Quality Index (WQI) and multivariate statistical methods, i.e., principal component analysis and correspondence analysis (PCA and CA), were implemented on the pre and post-monsoon water quality datasets. All these methods help identify the most critical factor in controlling GWQ for potable water. In pre-monsoon (PRM) and post-monsoon (POM) seasons, the computed value of WQI has ranged between 28.28 to 116.74 and from 29.49 to 111.98, respectively. As per the GIS-based WQI findings, 63.42 percent of the groundwater samples during the PRM season and 42.02 percent during the POM were classed as 'good' and could be consumed for drinking. The Principal component analysis (PCA) is a suitable tool for simplification of the evaluation process in water quality analysis. The PCA correlation matrix defines the relation among the water quality parameters, which helps to detect the natural or anthropogenic influence on sub-surface water. The finding of PCA's factor analysis shows the impact of geological and human intervention, as increased levels of EC, TDS, Na+, Cl-, HCO3-, F-, and SO42- on potable water. In this study, hierarchical cluster analysis (HCA) was used to categories the WQ parameters for PRM and POR seasons using the Ward technique. The research outcomes of this study can be used as baseline data for GWQ development activities and protect human health from water-borne diseases in the southern region of Rajasthan.

Lecanemab Blocks the Effects of the Aß/Fibrinogen Complex on Blood Clots and Synapse Toxicity in Organotypic Culture.

Proteinaceous brain inclusions, neuroinflammation, and vascular dysfunction are common pathologies in Alzheimer's disease (AD). Vascular deficits include a compromised blood-brain barrier, which can lead to extravasation of blood proteins like fibrinogen into the brain. Fibrinogen's interaction with the amyloid-beta (Aß) peptide is known to worsen thrombotic and cerebrovascular pathways in AD. Lecanemab, an FDA-approved antibody therapy for AD, shows promising results in facilitating reduction of Aß from the brain and slowing cognitive decline. Here we show that lecanemab blocks fibrinogen's binding to Aß protofibrils, normalizing Aß/fibrinogen-mediated delayed fibrinolysis and clot abnormalities in vitro and in human plasma. Additionally, we show that lecanemab dissociates the Aß/fibrinogen complex and prevents fibrinogen from exacerbating Aß-induced synaptotoxicity in mouse organotypic hippocampal cultures. These findings reveal a possible protective mechanism by which lecanemab may slow disease progression in AD.

Comparison of surgical site infection (SSI) between negative pressure wound therapy (NPWT) assisted delayed primary closure and conventional delayed primary closure in grossly contaminated emergency abdominal surgeries: a randomized controlled trial.

PURPOSE: NPWT has been tried in many surgical fields, including colorectal, thoracic, vascular, and non-healing wounds, for the prevention of SSI. However, its efficacy in the prevention of SSI-grade IV closed abdominal wounds is yet to be explored. METHODS: All patients with grade IV abdominal wounds were included in the study. They were randomized into the conventional arm and the VAC arm after confirming the diagnosis intra-operatively. The sheath was closed, and the skin was laid open in the postoperative period. In the VAC arm, the NPWT dressing was applied on postoperative day (POD)-1 and removed on POD-5. In the conventional arm, only regular dressing was done postoperatively. The skin was closed with a delayed primary intention on POD-5 in both arms. The sutures were removed after 7 to 10 days of skin closure. RESULTS: The rate of SSI (10% in the VAC arm vs. 37.5% in the conventional arm, p-value = 0.004) was significantly lower in the VAC arm, as were the rates of seroma formation (2.4% in the VAC arm vs. 20% in the conventional arm, p = 0.014) and wound dehiscence (7.3% vs. 30%, p = 0.011). The conventional arm had a significant delay in skin closure beyond POD5 due to an increased rate of SSI, which also led to a prolonged hospital stay (5 days in the VAC arm vs. 6.5 days in the conventional arm, p-value = 0.005). CONCLUSION: The VAC dressing can be used routinely in grade IV closed abdominal wounds to reduce the risk of SSI and wound dehiscence.

Recent Strategies for the Remediation of Textile Dyes from Wastewater: A Systematic Review.

The presence of dye in wastewater causes substantial threats to the environment, and has negative impacts not only on human health but also on the health of other organisms that are part of the ecosystem. Because of the increase in textile manufacturing, the inhabitants of the area, along with other species, are subjected to the potentially hazardous consequences of wastewater discharge from textile and industrial manufacturing. Different types of dyes emanating from textile wastewater have adverse effects on the aquatic environment. Various methods including physical, chemical, and biological strategies are applied in order to reduce the amount of dye pollution in the environment. The development of economical, ecologically acceptable, and efficient strategies for treating dye-containing wastewater is necessary. It has been shown that microbial communities have significant potential for the remediation of hazardous dyes in an environmentally friendly manner. In order to improve the efficacy of dye remediation, numerous cutting-edge strategies, including those based on nanotechnology, microbial biosorbents, bioreactor technology, microbial fuel cells, and genetic engineering, have been utilized. This article addresses the latest developments in physical, chemical, eco-friendly biological and advanced strategies for the efficient mitigation of dye pollution in the environment, along with the related challenges.

131I dose coefficients for a reference population using age-specific models.

Age-specific dose coefficients are required to assess internal exposure to the general public. This study utilizes reference age-specific biokinetic models of iodine to estimate the total number of nuclear disintegrations ã(rS,τ) occurring in source regions (rS) during the commitment time (τ). Age-specific S values are estimated for 35 target regions due to131I present in 22rSusing data from 10 paediatric reference computational phantoms (representing five ages for both sexes) published recently by the International Commission of Radiation Protection (ICRP). Monte Carlo transport simulations are performed in FLUKA code. The estimated ã(rS,τ) and S values are then used to compute the committed tissue equivalent dose HT(τ) for 27 radiosensitive tissues and dose coefficients e(τ) for all five ages due to inhalation and ingestion of131I. The derived ã(rS,τ) values in the thyroid source are observed to increase with age due to the increased retention of iodine in the thyroid. S values are found to decrease with age, mainly due to an increase in target masses. Generally, HT(τ) values are observed to decrease with age, indicating the predominant behaviour of S values over ã(rS,τ). On average, ingestion dose coefficients are 63% higher than for inhalation in all ages. The maximum contribution to dose coefficients is from the thyroid, accounting for 96% in the case of newborns and 98%-99% for all other ages. Furthermore, the estimated e(τ) values for the reference population are observed to be lower than previously published reference values from the ICRP. The estimated S, HT(τ) and e(τ) values can be used to improve estimations of internal doses to organs/whole body for members of the public in cases of131I exposure. The estimated dose coefficients can also be interpolated for other ages to accurately evaluate the doses received by the general public during131I therapy or during a radiological emergency.

Multivariate analysis and genetic dissection of staygreen and stem reserve mobilisation under combined drought and heat stress in wheat (Triticum aestivum L.).

Introduction: Abiotic stresses significantly reduce crop yield by adversely affecting many physio-biochemical processes. Several physiological traits have been targeted and improved for yield enhancement in limiting environmental conditions. Amongst them, staygreen and stem reserve mobilisation are two important mutually exclusive traits contributing to grain filling under drought and heat stress in wheat. Henceforth, the present study was carried out to identify the QTLs governing these traits and to identify the superiors' lines through multi-trait genotype-ideotype distance index (MGIDI) Methods: A mapping population consisting of 166 recombinant inbred lines (RILs) developed from a cross between HD3086 and HI1500 was utilized in this study. The experiment was laid down in alpha lattice design in four environmental conditions viz. Control, drought, heat and combined stress (heat and drought). Genotyping of parents and RILs was carried out with 35 K Axiom® array (Wheat breeder array). Results and Discussion: Medium to high heritability with a moderate to high correlation between traits was observed. Principal component analysis (PCA) was performed to derive latent variables in the original set of traits and the relationship of these traits with latent variables.From this study, 14 QTLs were identified, out of which 11, 2, and 1 for soil plant analysis development (SPAD) value, leaf senescence rate (LSR), and stem reserve mobilisation efficiency (SRE) respectively. Quantitative trait loci (QTLs) for SPAD value harbored various genes like Dirigent protein 6-like, Protein FATTY ACID EXPORT 3, glucan synthase-3 and Ubiquitin carboxyl-terminal hydrolase, whereas QTLs for LSR were found to contain various genes like aspartyl protease family protein, potassium transporter, inositol-tetrakisphosphate 1-kinase, and DNA polymerase epsilon subunit D-like. Furthermore, the chromosomal region for SRE was found to be associated with serine-threonine protein kinase. Serine-threonine protein kinases are involved in many signaling networks such as ABA mediated ROS signaling and acclimation to environmental stimuli. After the validation of QTLs in multilocation trials, these QTLs can be used for marker-assisted selection (MAS) in breeding programs.

Marker-assisted selection for transfer of QTLs to a promising line for drought tolerance in wheat (Triticum aestivum L.).

Wheat crop is subjected to various biotic and abiotic stresses, which affect crop productivity and yield. Among various abiotic stresses, drought stress is a major problem considering the current global climate change scenario. A high-yielding wheat variety, HD3086, has been released for commercial cultivation under timely sown irrigated conditions for the North Western Plain Zone (NWPZ) and North Eastern Plain Zone NEPZ of India. Presently, HD3086 is one of the highest breeder seed indented wheat varieties and has a stable yield over the years. However, under moisture deficit conditions, its potential yield cannot be achieved. The present study was undertaken to transfer drought-tolerant QTLs in the background of the variety HD3086 using marker-assisted backcross breeding. QTLs governing Biomass (BIO), Canopy Temperature (CT), Thousand Kernel Weight (TKW), Normalized Difference Vegetation Index (NDVI), and Yield (YLD) were transferred to improve performance under moisture deficit conditions. In BC1F1, BC2F1, and BC2F2 generations, the foreground selection was carried out to identify the plants with positive QTLs conferring drought tolerance and linked to traits NDVI, CT, TKW, and yield. The positive homozygous lines for targeted QTLs were advanced from BC2F2 to BC2F4 via the pedigree-based phenotypic selection method. Background analysis was carried out in BC2F5 and obtained 78-91% recovery of the recurrent parent genome in the improved lines. Furthermore, the advanced lines were evaluated for 2 years under drought stress to assess improvement in MABB-derived lines. Increased GWPS, TKW, and NDVI and reduced CT was observed in improved lines. Seven improved lines were identified with significantly higher yields in comparison to HD3086 under stress conditions.

On-demand (SOS) analgesia through Transversus Abdominis Plane (TAP) catheter route for post-operative pain relief in Emergency Laparotomies-a non-randomised interventional study (STAPLE trial).

INTRODUCTION: This study aimed to compare the efficacy and safety of on-demand bupivacaine infusion via transversus abdominis plane (TAP) catheter in emergency laparotomy patients. METHODS: A non-randomised interventional study was conducted on patients undergoing emergency midline laparotomy. The intervention group received an on-demand infusion of 10 ml 0.5% bupivacaine through TAP catheters, whilst the control group received standard analgesic care. The primary outcome was the amount of rescue analgesic consumption. Secondary outcomes included the post-operative, measured by visual analogue scores (VAS), side effects, time to first flatus, post-operative nausea and vomiting, and pulmonary complications. RESULTS: One-hundred-twenty patients (58 in the TAP-SOS group, 62 in the control group) were included in the final analysis. The TAP-SOS group showed significantly reduced rescue analgesic requirement by 91% (p < 0.001) and lower VAS scores at 3, 6, 12, and 24 h (adjusted p < 0.00). Time to out-of-bed mobilisation was significantly shorter in the TAP-SOS group by 12.47 h (p < 0.001), and post-operative pulmonary complications were lower by 75% (p < 0.05). There were no significant differences in bowel recovery, catheter-related complications, or post-operative morbidity. No incidences of catheter-site infection were reported on follow-up; however, the catheter tip-culture was positive in 3 (5.17%) patients. CONCLUSION: On-demand bupivacaine infusion through a TAP catheter effectively reduced post-operative pain and opioid requirements in emergency laparotomy patients without complications. If an epidural is not an option, the TAP-SOS approach can be a helpful adjunct in implementing the ERAS protocol in an emergency since it allows for early ambulation and better pain management.

Defending the Defender: Adversarial Learning Based Defending Strategy for Learning Based Security Methods in Cyber-Physical Systems (CPS).

Cyber-Physical Systems (CPS) are prone to many security exploitations due to a greater attack surface being introduced by their cyber component by the nature of their remote accessibility or non-isolated capability. Security exploitations, on the other hand, rise in complexities, aiming for more powerful attacks and evasion from detections. The real-world applicability of CPS thus poses a question mark due to security infringements. Researchers have been developing new and robust techniques to enhance the security of these systems. Many techniques and security aspects are being considered to build robust security systems; these include attack prevention, attack detection, and attack mitigation as security development techniques with consideration of confidentiality, integrity, and availability as some of the important security aspects. In this paper, we have proposed machine learning-based intelligent attack detection strategies which have evolved as a result of failures in traditional signature-based techniques to detect zero-day attacks and attacks of a complex nature. Many researchers have evaluated the feasibility of learning models in the security domain and pointed out their capability to detect known as well as unknown attacks (zero-day attacks). However, these learning models are also vulnerable to adversarial attacks like poisoning attacks, evasion attacks, and exploration attacks. To make use of a robust-cum-intelligent security mechanism, we have proposed an adversarial learning-based defense strategy for the security of CPS to ensure CPS security and invoke resilience against adversarial attacks. We have evaluated the proposed strategy through the implementation of Random Forest (RF), Artificial Neural Network (ANN), and Long Short-Term Memory (LSTM) on the ToN_IoT Network dataset and an adversarial dataset generated through the Generative Adversarial Network (GAN) model.

Comparison of laparoscopic port site skin closure techniques (CLOSA): transcutaneous suturing versus subcuticular sutures versus adhesive strips: a prospective single-blinded randomized control trial.

BACKGROUND: Cosmesis is an essential aspect of laparoscopic surgery. Various methods of skin closure techniques have been described. We conducted a study to evaluate the cosmesis and patient satisfaction with the scars three months after laparoscopic surgery using transcutaneous suture (TS) vs. adhesive strips (AS) and subcuticular suturing (SS). METHODS: A randomized, controlled, prospective study was conducted at AIIMS, Bhubaneswar. The included patients were randomly assigned among the three arms. The time for skin closure was measured. Wounds were assessed till discharge, at 14 days, one month, and three months. Cosmesis was measured by the Hollander Wound evaluation scale (HWES) for each incision separately, and patient satisfaction by a 10- point Visual analog scale (VAS). RESULTS: One hundred six patients were assessed for eligibility, and 90 patients were randomized. Three-month follow-up data was obtained from 83 patients (92.22%). Baseline characteristics were similar among the groups. Cosmetic outcome was assessed in 312 incisions across 83 patients, and 206 (66.03%) incisions had an HWE Score of 0, but there was no significant difference (p = 0.86). Patient satisfaction was highest in the TS group (TS = 1.29, SS = 1.79, AS = 2.04, p = 0.03). Time for skin closure was the least in the AS arm (41.4 secs, p = 0.00). Skin dehiscence was significantly more in the AS arm. Four (4.44%) patients had port site infections. CONCLUSION: This study demonstrates that skin closure by transcutaneous, subcuticular, or adhesive strip methods had comparable cosmetic outcomes at three months. However, the transcutaneous closure method showed better patient satisfaction and minimal post-operative complications.

MTR-SDL: a soft computing based multi-tier rank model for shoulder X-ray classification.

Deep neural networks (DNN) effectiveness are contingent upon access to quality-labelled training datasets since label mistakes (label noise) in training datasets may significantly impair the accuracy of models trained on clean test data. The primary impediments to developing and using DNN models in the healthcare sector include the lack of sufficient label data. Labeling data by a domain expert are a costly and time-consuming task. To overcome this limitation, the proposed Multi-Tier Rank-based Semi-supervised deep learning (MTR-SDL) for Shoulder X-Ray Classification uses the small labelled dataset to generate a labelled dataset from unable dataset to obtain performance equivalent to approaches trained on the enormous dataset. The motivation behind the suggested model MTR-SDL approach is analogous to how physicians deal with unknown or suspicious patients in everyday life. Practitioners handle these questionable circumstances with the support of professional colleagues. Before initiating treatment, some patients consult with a range of skilled doctors. Patients are treated according to the most suitable professional diagnosis (vote count). In this article, we have proposed a new ensemble learning technique called "Rank based Ensemble Selection with machine learning models" (MTR-SDL) approach. In this technique, multiple machine learning models are trained on a labeled dataset, and their accuracy is ranked. A dynamic ensemble voting approach is then used to tag samples for each base model in the ensemble. The combination of these tags is used to generate a final tag for an unlabeled dataset. Our suggested MTR-SDL model has attained the best accuracy and specificity, sensitivity, precision, Matthew's correlation coefficient, false discovery rate, false positive rate, f1 score, negative predictive value, and false negative rate negative 92.776%, 97.376%, 86.932%, 96.192%, 85.644%, 3.808%, 2.624%, 91.072%, 90.85%, and 13.068% for unseen dataset, respectively. This approach has the potential to improve the performance of ensemble models by leveraging the strengths of multiple base models and selecting the most informative samples for each model. This study results in an improved Semi-supervised deep learning model that is more effective and precise.

Seed endophytic bacterial profiling from wheat varieties of contrasting heat sensitivity.

Wheat yield can be limited by many biotic and abiotic factors. Heat stress at the grain filling stage is a factor that reduces wheat production tremendously. The potential role of endophytic microorganisms in mitigating plant stress through various biomolecules like enzymes and growth hormones and also by improving plant nutrition has led to a more in-depth exploration of the plant microbiome for such functions. Hence, we devised this study to investigate the abundance and diversity of wheat seed endophytic bacteria (WSEB) from heatS (heat susceptible, GW322) and heatT (heat tolerant, HD3298 and HD3271) varieties by culturable and unculturable approaches. The results evidenced that the culturable diversity was higher in the heatS variety than in the heatT variety and Bacillus was found to be dominant among the 10 different bacterial genera identified. Though the WSEB population was higher in the heatS variety, a greater number of isolates from the heatT variety showed tolerance to higher temperatures (up to 55°C) along with PGP activities such as indole acetic acid (IAA) production and nutrient acquisition. Additionally, the metagenomic analysis of seed microbiota unveiled higher bacterial diversity, with a predominance of the phyla Proteobacteria covering >50% of OTUs, followed by Firmicutes and Actinobacteria. There were considerable variations in the abundance and diversity between heat sensitivity contrasting varieties, where notably more thermophilic bacterial OTUs were observed in the heatT samples, which could be attributed to conferring tolerance against heat stress. Furthermore, exploring the functional characteristics of culturable and unculturable microbiomes would provide more comprehensive information on improving plant growth and productivity for sustainable agriculture.

Microbial biosorbent for remediation of dyes and heavy metals pollution: A green strategy for sustainable environment.

Toxic wastes like heavy metals and dyes are released into the environment as a direct result of industrialization and technological progress. The biosorption of contaminants utilizes a variety of biomaterials. Biosorbents can adsorb toxic pollutants on their surface through various mechanisms like complexation, precipitation, etc. The quantity of sorption sites that are accessible on the surface of the biosorbent affects its effectiveness. Biosorption's low cost, high efficiency, lack of nutrient requirements, and ability to regenerate the biosorbent are its main advantages over other treatment methods. Optimization of environmental conditions like temperature, pH, nutrient availability, and other factors is a prerequisite to achieving optimal biosorbent performance. Recent strategies include nanomaterials, genetic engineering, and biofilm-based remediation for various types of pollutants. The removal of hazardous dyes and heavy metals from wastewater using biosorbents is a strategy that is both efficient and sustainable. This review provides a perspective on the existing literature and brings it up-to-date by including the latest research and findings in the field.

Mapping of the QTLs governing grain micronutrients and thousand kernel weight in wheat (Triticum aestivum L.) using high density SNP markers.

Biofortification is gaining importance globally to improve human nutrition through enhancing the micronutrient content, such as vitamin A, iron, and zinc, in staple food crops. The present study aims to identify the chromosomal regions governing the grain iron concentration (GFeC), grain zinc concentration (GZnC), and thousand kernel weight (TKW) using recombinant inbred lines (RILs) in wheat, developed from a cross between HD3086 and HI1500. The experiment was conducted in four different production conditions at Delhi viz., control, drought, heat, and combined heat and drought stress and at Indore under drought stress. Grain iron and zinc content increased under heat and combined stress conditions, while thousand kernel weight decreased. Medium to high heritability with a moderate correlation between grain iron and zinc was observed. Out of 4,106 polymorphic markers between the parents, 3,407 SNP markers were used for linkage map construction which spanned over a length of 14791.18 cm. QTL analysis identified a total of 32 chromosomal regions governing the traits under study, which includes 9, 11, and 12 QTLs for GFeC, GZnC, and TKW, respectively. A QTL hotspot was identified on chromosome 4B which is associated with grain iron, grain zinc, and thousand kernel weight explaining the phenotypic variance of 29.28, 10.98, and 17.53%, respectively. Similarly, common loci were identified on chromosomes 4B and 4D for grain iron, zinc, and thousand kernel weight. In silico analysis of these chromosomal regions identified putative candidate genes that code for proteins such as Inositol 1,3,4-trisphosphate 5/6-kinase, P-loop containing nucleoside triphosphate hydrolase, Pleckstrin homology (PH) domains, Serine-threonine/tyrosine-protein kinase and F-box-like domain superfamily proteins which play role in many important biochemical or physiological process. The identified markers linked to QTLs can be used in MAS once successfully validated.

Molecular Mapping of Biofortification Traits in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP Based Linkage Map.

A set of 188 recombinant inbred lines (RILs) derived from a cross between a high-yielding Indian bread wheat cultivar HD2932 and a synthetic hexaploid wheat (SHW) Synthetic 46 derived from tetraploid Triticum turgidum (AA, BB 2n = 28) and diploid Triticum tauschii (DD, 2n = 14) was used to identify novel genomic regions associated in the expression of grain iron concentration (GFeC), grain zinc concentration (GZnC), grain protein content (GPC) and thousand kernel weight (TKW). The RIL population was genotyped using SNPs from 35K Axiom® Wheat Breeder's Array and 34 SSRs and phenotyped in two environments. A total of nine QTLs including five for GPC (QGpc.iari_1B, QGpc.iari_4A, QGpc.iari_4B, QGpc.iari_5D, and QGpc.iari_6B), two for GFeC (QGfec.iari_5B and QGfec.iari_6B), and one each for GZnC (QGznc.iari_7A) and TKW (QTkw.iari_4B) were identified. A total of two stable and co-localized QTLs (QGpc.iari_4B and QTkw.iari_4B) were identified on the 4B chromosome between the flanking region of Xgwm149-AX-94559916. In silico analysis revealed that the key putative candidate genes such as P-loop containing nucleoside triphosphatehydrolase, Nodulin-like protein, NAC domain, Purine permease, Zinc-binding ribosomal protein, Cytochrome P450, Protein phosphatase 2A, Zinc finger CCCH-type, and Kinesin motor domain were located within the identified QTL regions and these putative genes are involved in the regulation of iron homeostasis, zinc transportation, Fe, Zn, and protein remobilization to the developing grain, regulation of grain size and shape, and increased nitrogen use efficiency. The identified novel QTLs, particularly stable and co-localized QTLs are useful for subsequent use in marker-assisted selection (MAS).