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Owing to its simplicity of measurement, effluent conductivity is one of the most studied factors in evaluations of desalination performance based on the ion concentrations in various ion adsorption processes such as capacitive deionization (CDI) or battery electrode deionization (BDI). However, this simple conversion from effluent conductivity to ion concentration is often incorrect, thereby necessitating a more congruent method for performing real-time measurements of effluent ion concentrations. In this study, a random forest (RF)-based artificial intelligence (AI) model was developed to address this shortcoming. The proposed RF model showed an excellent prediction accuracy when it was first validated in predicting the effluent conductivity for both CDI (R 2 = 0.86) and BDI (R 2 = 0.95) data. Moreover, the RF model successfully predicted the concentration of each ion (Na⁺, K⁺, Ca 2 ⁺, and Cl⁻) from the conductivity values. The accuracy of the ion concentration prediction was even higher than that of the effluent conductivity prediction, likely owing to the linear correlation between the input and output variables of the dataset. The effect of the sampling interval was also evaluated for conductivity and ion concentrations, and there was no significant difference up to sampling intervals of <80 s based on the error value of the model. These findings suggest that an RF model can be used to predict ion concentrations in CDI/BDI, which may be used as core indicators in evaluating desalination performance., 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 © 2024. Published by Elsevier Ltd.)

The agro-waste derived valuable products are prime interest for effective management of toxic heavy metals (THMs). The present study investigated the efficacy of biochars (BCs) on immobilization of THMs (Cr, Zn, Pb, Cu, Ni and Cd), bioaccumulation and health risk. Agro-wastes derived BCs including wheat straw biochar (WSB), orange peel biochar (OPB), rice husk biochar (RHB) and their composite biochar (CB) were applied in industrial contaminated soil (ICS) at 1% and 3% amendments rates. All the BCs significantly decreased the bioavailable THMs and significantly ( p  < 0.001) reduced bioaccumulation at 3% application with highest efficiency for CB followed by OPB, WSB and RHB as compared to control treatment. The bioaccumulation factor (BAF), concentration index (CI) and ecological risk were decreased with all BCs. The hazard quotient (HQ) and hazard index (HI) of all THMs were <1, except Cd, while carcer risk (CR) and total cancer risk index (TCRI) were decreased through all BCs. The overall results depicted that CB at 3% application rate showed higher efficacy to reduce significantly ( p  < 0.001) the THMs uptake and reduced health risk. Hence, the present study suggests that the composite of BCs prepared from agro-wastes is eco-friendly amendment to reduce THMs in ICS and minimize its subsequent uptake in vegetables.

This study investigated the coexistence and contamination of manganese (Mn(II)) and arsenite (As(III)) in groundwater and examined their oxidation behavior under different equilibrating parameters, including varying pH, bicarbonate (HCO 3 - ) concentrations, and sodium hypochlorite (NaClO) oxidant concentrations. Results showed that if the molar ratio of NaClO: As(III) was >1, the oxidation of As(III) could be achieved within a minute with an extremely high oxidation rate of 99.7 %. In the binary system, the removal of As(III) prevailed over Mn(II). The As(III) oxidation efficiency increased from 59.8 ± 0.6 % to 70.8 ± 1.9 % when pH rose from 5.7 to 8.0. The oxidation reaction between As(III) and NaClO releases H + ions, decreasing the pH from 6.77 to 6.19 and reducing the removal efficiency of Mn(II). The presence of HCO 3 - reduced the oxidation rate of Mn(II) from 63.2 % to 13.9 % within four hours. Instead, the final oxidation rate of Mn(II) increased from 68.1 % to 87.7 %. This increase can be attributed to HCO 3 - ions competing with the free Mn(II) for the adsorption sites on the sediments, inhibiting the formation of H + . Moreover, kinetic studies revealed that the oxidation reaction between Mn(II) and NaClO followed first-order kinetics based on their R 2 values. The significant factors affecting the Mn(II) oxidation efficiency were the initial concentration of NaClO and pH. Applying an artificial neural network (ANN) model for data analysis proved to be an effective tool for predicting Mn(II) oxidation rates under different experimental conditions. The actual Mn(II) oxidation data and the predicted values obtained from the ANN model showed significant consistency. The training and validation data sets yielded R 2 values of 0.995 and 0.992, respectively. Moreover, the ANN model highlights the importance of pH and NaClO concentrations in influencing the oxidation rate of Mn(II)., Competing Interests: Declaration of competing interest The authors declare no 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.)

Vector quantization (VQ) is a block coding method that is famous for its high compression ratio and simple encoder and decoder implementation. Linde-Buzo-Gray (LBG) is a renowned technique for VQ that uses a clustering-based approach for finding the optimum codebook. Numerous algorithms, such as Particle Swarm Optimization (PSO), the Cuckoo search algorithm (CS), bat algorithm, and firefly algorithm (FA), are used for codebook design. These algorithms are primarily focused on improving the image quality in terms of the PSNR and SSIM but use exhaustive searching to find the optimum codebook, which causes the computational time to be very high. In our study, our algorithm enhances LBG by minimizing the computational complexity by reducing the total number of comparisons among the codebook and training vectors using a match function. The input image is taken as a training vector at the encoder side, which is initialized with the random selection of the vectors from the input image. Rescaling using bilinear interpolation through the nearest neighborhood method is performed to reduce the comparison of the codebook with the training vector. The compressed image is first downsized by the encoder, which is then upscaled at the decoder side during decompression. Based on the results, it is demonstrated that the proposed method reduces the computational complexity by 50.2% compared to LBG and above 97% compared to the other LBG-based algorithms. Moreover, a 20% reduction in the memory size is also obtained, with no significant loss in the image quality compared to the LBG algorithm.

Metal pollution in water, soil, and vegetation is an emerging environmental issue. Therefore, this study investigated the abundance of heavy metals (HMs) within roots and shoots of native plant species i.e., Bromus pectinatus, Cynodon dactylon, Poa annua, Euphorbia heliscopa, Anagallis arvensis, and Stellaria media grown in the adjoining area of municipal wastewater channels of a Pakistani city of Abbottabad. HMs concentrations (mg L -1 ) in municipal wastewater were: chromium (Cr) (0.55) > nickel (Ni) (0.09) > lead (Pb) (0.07) > cadmium (Cd) (0.03). Accumulation of HMs in both roots and shoots of plant species varied as B. pectinatus > C. dactylon > P. annua > E. heliscopa > A. arvensis > S. media. Irrespective of the plant species, roots exhibited higher concentrations of HMs than shoots. Higher amount of Cr (131.70 mg kg -1 ) was detected in the roots of B. pectinatus and the lowest amount (81 mg kg -1 ) in A. arvensis, Highest Cd concentration was found in the shoot of B. pectinatus and the lowest in the E. heliscopa. The highest concentration of Ni was found in the roots of S. media (37.40 mg kg -1 ) and the shoot of C. dactylon (15.70 mg kg -1 ) whereas the lowest Ni concentration was achieved in the roots of A. arvensis (12.10 mg kg -1 ) and the shoot of E. heliscopa (5.90 mg kg -1 ). The concentration of HMs in individual plant species was less than 1000 mg kg -1 . Considering the higher values (> 1) of biological concentration factor (BCF), biological accumulation co-efficient (BAC), and translocation factor (TF), B. pectinatus and S. media species showed greater potential for HMs accumulation than other species. Therefore, these plants might be helpful for the remediation of HM-contaminated soil., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Groundwater contamination with arsenic (As) is a significant concern in Pakistan's Punjab Province. This study analyzed 69 groundwater samples from Faisalabad, Gujranwala, Lahore, and Multan to understand hydrogeochemistry, health impacts, contamination sources, and drinking suitability. Results revealed varying as concentrations across districts, with distinctive cation and anion orders. Faisalabad exhibited Na +  > Mg 2+  > Ca 2+  > K +  > Fe 2+ for cations and SO 4 2-  > Cl -  > HCO 3 -  > NO 3 -  > F - for anions. Gujranwala showed Na +  > Ca 2+  > Mg 2+  > K + for cations and HCO 3 -  > SO 4 2-  > Cl -  > NO 3 -  > F - for anions. In Lahore, demonstrated: Na +  > Ca 2+  > Mg 2+  > Fe > K + for cations and HCO 3 -  > SO 4 2 -  > Cl -  > NO 3 -  > F - for anions. Multan indicated K +  > Ca 2 +  > Mg 2 +  > Na +  > Fe for cations and HCO 3 -  > SO 4 2-  > Cl -  > F -  > NO 3 - ) for anions. Hydrochemical facies were identified as CaHCO 3 and CaMgCl types. Principal Component Analysis (PCA), highlighted the influence of natural processes and human activities on groundwater pollution. Water Quality Index (WQI) result reveal that most samples met water quality standards. The carcinogenic risk values for children exceeded permissible limits in all districts, emphasizing a significant cancer risk. The study highlights the need for rigorous monitoring to mitigate (As) contamination and protect public health from associated hazards., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The objective of the current research was to examine the water quality of the River Ravi and the River Sutlej, with a specific focus on potentially toxic elements (PTEs). Additionally, we sought to monitor the sources of pollution in these rivers by gathering samples from the primary drains that carry industrial and municipal waste into these water bodies. Furthermore, we aimed to evaluate the impact of PTEs in surface water on groundwater quality by collecting groundwater samples from nearby populated areas. A total of 30 samples were collected from these three sources: rivers (6 samples), drains (9 samples), and groundwater (15 samples). The analysis revealed that the levels of PTEs in the samples from these three resources having a mean value: arsenic (As) 23.5 µg/L, zinc (Zn) 2.35 mg/L, manganese (Mn) 0.51 mg/L, lead (Pb) 6.63 µg/L, and chromium (Cr) 10.9 µg/L, exceeded the recommended values set by the World Health Organization (WHO). Furthermore, PTEs including (As 84%), (Zn 65%), (Mn 69%), (Pb 53%), (Cr 53%), and (Ni 27%), samples were beyond the recommended values of WHO. The results of the Principal Component Analysis indicated that surface water and groundwater exhibited total variability of 83.87% and 85.97%, respectively. This indicates that the aquifers in the study area have been contaminated due to both natural geogenic factors and anthropogenic sources. These sources include the discharge of industrial effluents, wastewater from municipal sources, mining activities, agricultural practices, weathering of rocks, and interactions between rocks and water. Spatial distribution maps clearly illustrated the widespread mobilization of PTEs throughout the study area. Furthermore, a health risk assessment was conducted to evaluate the potential adverse health effects of PTEs through the ingestion of drinking groundwater by both children and adults. Health risk assessment result show the mean carcinogenic values for As, Cr, Pb and Ni in children are calculated to be (1.88E-04), (2.61E-04), (2.16E-02), and (5.74E-05), respectively. Similarly, the mean carcinogenic values for the above mentioned PTEs in adults were recorded to be (2.39E-05), (3.32E-05), (1.19E-03), and (7.29E-06) respectively. The total hazard index values for As, Zn, Cr, Pb, Mn, Cu, and Ni in children were observed to be (9.07E + 00), (9.95E-07), (4.59E-04), (5.75E-04), (4.72E-05), (2.78E-03), and (5.27E-05) respectively. The analysis revealed that As has an adverse effect on the population of the study area as compared to other PTEs investigated in this study., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

In the context of growing arsenic (As) contamination in the world, there is an urgent need for an effective treatment approach to remove As from the environment. Industrial wastewater is one of the primary sources of As contamination, which poses significant risks to both microorganisms and human health, as the presence of As can disrupt the vital processes and synthesis of crucial macromolecules in living organisms. The global apprehension regarding As presence in aquatic environments persists as a key environmental issue. This review summarizes the recent advances and progress in the design, strategy, and synthesis method of various manganese-based adsorbent materials for As removal. Occurrence, removal, oxidation mechanism of As(III), As adsorption on manganese oxide (MnO x )-based materials, and influence of co-existing solutes are also discussed. Furthermore, the existing knowledge gaps of MnO x -based adsorbent materials and future research directions are proposed. This review provides a reference for the application of MnO x -based adsorbent materials to As removal., 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 © 2024 Elsevier B.V. All rights reserved.)

In recent years, the growing concern over the presence of toxic aquatic pollutants has prompted intensive research into effective and environmentally friendly remediation methods. Photocatalysis using semiconductor quantum dots (QDs) has developed as a promising technology for pollutant degradation. Among various QD materials, indium phosphide (InP) and its hybrid with zinc sulfide (ZnS) have gained considerable attention due to their unique optical and photocatalytic properties. Herein, InP and InP/ZnS QDs were employed for the removal of dyes (crystal violet, and congo red), polyaromatic hydrocarbons (pyrene, naphthalene, and phenanthrene), and pesticides (deltamethrin) in the presence of visible light. The degradation efficiencies of crystal violet (CV) and congo red (CR) were 74.54% and 88.12% with InP, and 84.53% and 91.78% with InP/ZnS, respectively, within 50 min of reaction. The InP/ZnS showed efficient performance for the removal of polyaromatic hydrocarbons (PAHs). For example, the removal percentage for naphthalene, phenanthrene, and pyrene was 99.8%, 99.6%, and 88.97% after the photocatalytic reaction. However, the removal percentage of InP/ZnS for pesticide deltamethrin was 90.2% after 90 min light irradiation. Additionally, advanced characterization techniques including UV-visible spectrophotometer (UV-Vis), photoluminescence (PL), X-ray diffractometer (XRD), energy-dispersive spectrometer (EDS) elemental mapping, transmission electron microscopy (TEM), and thermogravimetric analysis (TGA) were used to analyze the crystal structure, morphology, and purity of the fabricated materials in detail. The particle size results obtained from TEM are in the range of 2.28-4.60 nm. Both materials (InP and InP/ZnS) exhibited a spherical morphology, displaying distinct lattice fringes. XRD results of InP depicted lattice planes (111), (220), and (311) in good agreement with cubic geometry. Furthermore, the addition of dopants was discovered to enhance the thermal stability of the fabricated material. In addition, QDs exhibited efficacy in the breakdown of PAHs. The analysis of their fragmentation suggests that the primary mechanism for PAHs degradation is the phthalic acid pathway., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Land use has a great impact on soil dynamics. The soils of various land use systems in Central Karakoram have been under immense pressure in the recent past due to certain anthropogenic activities such as land use practices and land use cover changes. These influences have an impact on the spatial distribution of metallic elements (MEs) in the soils of various land uses. Herein, we investigated the occurrence of the MEs, copper (Cu), zinc (Zn), and nickel (Ni), in soils of various land uses such as the permafrost, pasture, forest, and agricultural lands of the Central Karakorum region. The MEs were extracted in exchangeable, adsorbed, organically bound, carbonated, precipitated, and residual forms. The concentrations of MEs showed a significant dependence on the extraction method used, and the extraction trend followed the order of EDTA > HNO 3 > KNO 3 > NaOH > H 2 O. Zn showed the highest concentration compared to Ni and Cu in all extractions, whereas the land uses' ME concentration followed the order of agricultural land > permafrost > forest > pasturelands. The highest values of total Zn, Ni, and Cu were 712 ± 01 mg/kg, 656 ± 02 mg/kg, and 163 ± 02 mg/kg, respectively, in agricultural soil. The ME concentration showed significant variations between different land uses, and the highest concentration was noted in agricultural soil. Zn was found to be a dominant ME compared to Ni and Cu. We believe this effort will provide opportunities for scholars to investigate MEs around the globe.

Stress is one of the important factors that directly or indirectly affects the plant architecture, biochemical pathways, and growth and development. Melatonin (MEL) is an important stress hormone; however, the exogenous addition of melatonin to culture media stimulates the defense mechanism and releases higher quantities of secondary metabolites. In this study, submerged adventitious root cultures (SARCs) of diabetically important Stevia rebaudiana were exposed to variable concentrations (0.5-5.0 mg/L) of MEL in combination with 0.5 mg/L naphthalene acetic acid (NAA) to investigate the biomass accumulation during growth kinetics with 07 days intervals for a period of 56 days. The effects of exogenous MEL on the biosynthesis of stevioside (Stev.), total phenolics content (TPC), total flavonoids content (TFC), total phenolics production (TPP), total flavonoids production (TFP), total polyphenolics content (TPPC), fresh and dry weight (FW & DW), and antioxidant potential were also studied. Most of the SARCs displayed lag, exponential, stationary, and decline phases with variable biomass accumulation. The maximum fresh (236.54 g/L) and dry biomass (28.64 g/L) was observed in SARCs exposed to 3.0 mg/L MEL and 0.5 mg/L NAA. The same combination of MEL and NAA also enhanced the accumulation of TPC (18.96 mg/g-DW), TFC (6.33 mg/g-DW), TPP (271.51 mg/L), TFP (90.64 mg/L), and TPPC (25.29 mg/g-DW). Similarly, the highest stevioside biosynthesis (91.45 mg/g-DW) and antioxidant potential (86.15%) were observed in SARCs exposed to 3.0 mg/L MEL and NAA. Moreover, a strong correlation was observed between the biomass and the contents of phenolics, flavonoids, antioxidants, and stevioside. These results suggest that MEL is one of multidimensional stress hormones that modulate the biosynthetic pathways to release higher quantities of metabolites of interest for various industrial applications., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Arsenic contamination in the groundwater occurs in various parts of the world due to anthropogenic and natural sources, adversely affecting human health and ecosystems. The current study intends to examine the groundwater hydrogeochemistry containing elevated arsenic (As), predict As levels in groundwater, and determine the aptness of groundwater for drinking in the Vehari district, Pakistan. Four hundred groundwater samples from the study region were collected for physiochemical analysis. As levels in groundwater samples ranged from 0.1 to 52 μg/L, with an average of 11.64 μg/L, (43.5%), groundwater samples exceeded the WHO 2022 recommended limit of 10 μg/L for drinking purposes. Ion-exchange processes and the adsorption of ions significantly impacted the concentration of As. The HCO 3 - and Na + are the dominant ions in the study area, and the water types of samples were CaHCO 3 , mixed CaMgCl, and CaCl, demonstrating that rock-water contact significantly impacts hydrochemical behavior. The geochemical modeling indicated negative saturation indices with calcium carbonate and other salt minerals, encompassing aragonite, calcite, dolomite, and halite. The dissolution mechanism suggested that these minerals might have implications for the mobilization of As in groundwater. A combination of human-induced and natural sources of contamination was unveiled through principal component analysis (PCA). Artificial neural networks (ANN), random forest (RF), and logistic regression (LR) were used to predict As in the groundwater. The data have been divided into two parts for statistical analysis: 20% for testing and 80% for training. The most significant input variables for As prediction was determined using Chi-squared analysis. The receiver operating characteristic area under the curve and confusion matrix were used to evaluate the models; the RF, ANN, and LR accuracies were 0.89, 0.85, and 0.76. The permutation feature and mean decrease in impurity determine ten parameters that influence groundwater arsenic in the study region, including F - , Fe 2+ , K + , Mg 2+ , Ca 2+ , Cl - , SO 4 2- , NO 3 - , HCO 3 - , and Na + . The present study shows RF is the best model for predicting groundwater As contamination in the research area. The water quality index showed that 161 samples represent poor water, and 121 samples are unsuitable for drinking. Establishing effective strategies and regulatory measures is imperative in Vehari to ensure the sustainability of groundwater resources., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: In multicultural societies, traditional knowledge among minorities faces several challenges. Minority groups often face difficult situations living in specific peripheral geographies and striving to retain their biocultural heritage, including medicinal plant knowledge and practices. Folk medicinal plant knowledge is a dynamic eco-cultural complex influenced by various environmental, socio-cultural, and political factors. Examining medicinal plant knowledge among minorities has been an increasingly popular topic in cross-cultural ethnobiology. It also helps understand the dynamics of local/traditional ecological knowledge (LEK/TEK) change within a given community. The current study was designed to investigate the status of medicinal plant knowledge among two linguistic groups, i.e. Ormurs and Pathans, living in a remote valley of West Pakistan., Methods: We recruited 70 male study participants from the studied groups for semi-structured interviews to record the medicinal plant use of their communities. Data were compared among the two studied communities using the stacked charts employing the presence or absence of data with Past 4.03 and Venn diagrams. Use reports (URs) were counted for each recorded taxon., Results and Discussion: A total of seventy-four medicinal plants were quoted as used as ethnomedicines by the researched communities. Most of the reported plants were used to treat digestive and liver problems. The cross-cultural comparison revealed a considerable homogeneity of medicinal plant knowledge (the two groups commonly used more than seventy plants); however, comparing uses recorded for the widely utilised medicinal plants showed numerous idiosyncratic uses among Ormurs but very few among Pathans. Ormurs reported a higher number of cultivated, wild, and imported plant uses than did Pathans. These results indicate that, compared to Pathans, the Ormur linguistic minority retain more folk medicinal plant knowledge, which may be explained by the fact that they have incorporated different folk remedies: their "own knowledge" plus that of Pathans, with whom they have lived together for centuries. Moreover, the local plant nomenclature among Ormurs was highly affected by the plant nomenclature of Pathans., Conclusion: The current study revealed that living together for a few centuries has not implied sharing plant knowledge (as the Pathans do not seem to have learnt from the Ormurs) or, in other words, that plant knowledge exchanges have been unidirectional. The findings show that the Pashto dominant culture may have possibly put pressure on the minority groups and affected local plant-centred cultural practices, as we see in the case of local plant nomenclature hybridisation among Omuri speakers. Hence, it is imperative to employ diverse educational strategies to revitalise the decline of medicinal plant knowledge in the studied communities, especially among Ormurs, who need more attention as they face more challenges than the other group. Locally based strategies should be devised to restore the fading connection with nature, which will be advantageous for revitalising plant knowledge., (© 2023. The Author(s).)

Knee osteoarthritis (OA) is a frequent musculoskeletal disorder that leads to physical disability in older adults. Manual OA assessment is performed via visual inspection, which is highly subjective as it suffers from moderate to high inter-observer variability. Many deep learning-based techniques have been proposed to address this issue. However, owing to the limited amount of labelled data, all existing solutions have limitations in terms of performance or the number of classes. This paper proposes a novel fully automatic Kellgren and Lawrence (KL) grade classification scheme in knee radiographs. We developed a semi-supervised multi-task learning-based approach that enables the exploitation of additional unlabelled data in an unsupervised as well as supervised manner. Specifically, we propose a dual-channel adversarial autoencoder, which is first trained in an unsupervised manner for reconstruction tasks only. To exploit the additional data in a supervised way, we propose a multi-task learning framework by introducing an auxiliary task. In particular, we use leg side identification as an auxiliary task, which allows the use of more datasets, e.g., CHECK dataset. The work demonstrates that the utilization of additional data can improve the primary task of KL-grade classification for which only limited labelled data is available. This semi-supervised learning essentially helps to improve the feature learning ability of our framework, which leads to improved performance for KL-grade classification. We rigorously evaluated our proposed model on the two largest publicly available datasets for various aspects, i.e., overall performance, the effect of additional unlabelled samples and auxiliary tasks, robustness analysis, and ablation study. The proposed model achieved the accuracy, precision, recall, and F1 score of 75.53%, 74.1%, 78.51%, and 75.34%, respectively. Furthermore, the experimental results show that the suggested model not only achieves state-of-the-art performance on two publicly available datasets but also exhibits remarkable robustness., 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 © 2023 Elsevier Ltd. All rights reserved.)

Arsenic (As), contamination in drinking groundwater resources is commonly environmental problem in many developing countries including Pakistan, with significant human health risk reports. In order to examine the groundwater quality concerning As contamination, its geochemical behavior along with physicochemical parameters, 42 samples were collected from community tube wells from District Bahawalpur, Punjab, Pakistan. The results showed the concentration of elevated As, its source of mobilization, and associated public health risk. The As concentration detected in groundwater samples varied from 0.12 to 104 µg/L with an average value of 34.7 µg/L. Among 42 groundwater samples, 27 samples were beyond the permitted limit of 10 µg/L recommended by World Health Organization (WHO), for drinking purposes. Statistical analysis result show that the groundwater cations values are in decreasing order such as: Na +  > Mg 2+  > Ca 2+  > K + , while anions were HCO 3 -  > SO 4 2-  > Cl -  > NO 3 - . Hydrochemical facies result depict that the groundwater samples of the study area, 14 samples belong to CaHCO 3 type, 5 samples belong to NaCl type, 20 samples belong to Mixed CaMgCl type, and 3 samples belong to CaCl 2 type. It can be accredited due to weathering and recharge mechanism, evaporation processes, and reverse ion exchange. Gibbs diagram shows that rock water interaction controls the hydrochemistry of groundwater resources of the study area. Saturation Index (SI) result indicated the saturation of calcite, dolomite, gypsum, geothite, and hematite mineral due their positive SI values. The principal component analysis (PCA) results possess a total variability of 80.69% signifying the anthropogenic and geogenic source of contamination. The results of the exposure-health-risk-assessment method for measuring As reveal significant potential non-carcinogenic risk (HQ), exceeding the threshold level of (> 1) for children in the study area. Water quality assessment results shows that 24 samples were not suitable for drinking purposes., (© 2023. The Author(s).)

In recent decades, heavy metals (HMs) have emerged as a global health concern. Unfortunately, in Pakistan, there is a general lack of awareness regarding the potential health risks associated with HMs pollution among automobile workers. Herein, we investigated the concentration of heavy metals such as lead (Pb), cadmium (Cd), and chromium (Cr) among automobile workers who were occupationally exposed in Mingora City, Khyber Pakhtunkhwa, Pakistan. Three different automobile groups, i.e., battery recyclers, spray painters, and mechanics were studied in detail. A total of 40 blood samples were collected from automobile workers groups while 10 blood samples were collected as control individuals from different locations in the study area. We investigated heavy metals concentration with a standard method using an atomic absorption spectrometer AAS (PerkinElmer Analyst 700, United States). Based on our findings, the battery recycling group displayed the most elevated Pb levels (5.45 ± 2.11 μg/dL), exceeding those of both the spray painters' group (5.12 ± 1.98 μg/dL) and the mechanics' group (3.79 ± 2.21 μg/dL). This can be attributed to their higher exposure to Pb pollution resulting from the deterioration, dismantling, grinding, or crushing of old batteries. In the context of chromium (Cr) exposure, a similar trend was observed among the battery recycling group, as well as the spray painters and mechanics groups. However, in the case of cadmium (Cd), the mechanics' group exhibited the highest level of exposure (4.45 ± 0.65 μg/dL), surpassing the battery recycling group (1.17 ± 0.45 μg/dL) and the spray painters' group (1.35 ± 0.69 μg/dL), which was attributed to their greater exposure to welding fumes and other activities in their workplace. We believe that our findings will encourage regulatory measures to improve the health of automobile workers. However, further work is needed to determine various health-related issues associated with heavy metal exposure among automobile workers., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Khan, Room, Bacha, Nabi, Ahmad, Younas, Ullah, Iqbal, Alrefaei, Almutairi, Chang and Chi.)

Fluoride (F - ), and arsenic (As) in the groundwater cause health problems in developing countries, including Pakistan. We evaluated the occurrence, distribution, sources apportionment, and health hazards of F - , and As in the groundwater of Mardan, Pakistan. Therefore, groundwater samples (n = 130) were collected and then analyzed for F - , and As by ion-chromatography (IC) and Inductively-coupled plasma mass-spectrometry (ICP-MS). The F - , and As concentrations in groundwater were 0.7-14.4 mg/L and 0.5-11.2 µg/L. Relatively elevated F - , and As coexists with higher pH, Na + , HCO 3 - , SO 4 -2 , and depleted Ca +2 due to fluoride, sulfide-bearing minerals, and anthropogenic inputs. Both F - , and/or As are transported in subsurface water through adsorption and desorption processes. Groundwater samples 45%, and 14.2% exceeded the WHO guidelines of 1.5 mg/L and 10 µg/L. Water quality indexing (WQI-model) declared that 35.7% samples are unfit for household purposes. Saturation and undersaturation of minerals showed precipitation and mineral dissolution. Groundwater contamination by PCA-MLR and PMF-model interpreted five factors. The fitting results and R 2 values of PMF (0.52-0.99)>PCA-MLR (0.50-0.95) showed high accuracy of PMF-model. Human health risk assessment (HHRA-model) revealed high non-carcinogenic and carcinogenic risk for children than adults. The percentile recovery of F - and As was recorded 98%, and 95% with reproducibility ± 5% error., 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 © 2023 Elsevier B.V. All rights reserved.)

Children's health is one of the most significant fields in medicine. Most diseases that result in children's death or long-term morbidity are caused by preventable and treatable etiologies, and they appear in the child at the early stages as mild symptoms. This research aims to develop a machine learning (ML) framework to detect the severity of disease in children. The proposed framework helps in discriminating children's urgent/severe conditions and notifying parents whether a child needs to visit the emergency room immediately or not. The model considers several variables to detect the severity of cases, which are the symptoms, risk factors (e.g., age), and the child's medical history. The framework is implemented by using nine ML methods. The results achieved show the high performance of the proposed framework in identifying serious pediatric diseases, where decision tree and random forest outperformed the other methods with an accuracy rate of 94%. This shows the reliability of the proposed framework to be used as a pediatric decision-making system for detecting serious pediatric illnesses. The results are promising when compared to recent state-of-the-art studies. The main contribution of this research is to propose a framework that is viable for use by parents when their child suffers from any commonly developed symptoms.

Background/aim: Cutaneous leishmaniasis is an emerging tropical disease that remains a serious public health issue in Pakistan, particularly in North Waziristan. The current research was carried out to investigate the presence of cutaneous leishmaniasis in this region., Materials and Methods: This prospective observational study was conducted from October 2018 to December 2020 at District Head Quarter Hospital Miranshah in North Waziristan with the collaboration of the Pathology Department of Gomal Medical College Dera Ismail Khan, Khyber Pakhtunkhwa. Needle aspirates were used for the microscopic Giemsa-stained slides. SPSS was used for data analysis., Results: Of the 5406 clinically-suspected cases, 2603(48.2%) were positive by microscopic examination. Of these 2603 patients, 1474 (57%) were male and 1129 (43%) were female. Most of the lesions were on the face, followed by upper and lower limbs. The 5-10-year age group had the highest percentage of 1167 (45%). A single lesion affected 96.6% of the patients, while 2.7% had double lesions and 0.7% had triple lesions. A high number of cutaneous leishmaniasis were seen from April to August, while the lowest number was seen November to December., Conclusion: This study provides extensive information in relation to the existence of cutaneous leishmaniasis in the North Waziristan district of Pakistan, as well as the detailed demographic features of those affected by the disease., Competing Interests: Conflict of interest: The authors declare that they have no conflicts of interest., (© TÜBİTAK.)

Misuse of antibiotics leads to the worldwide spread of antibiotic resistance, which motivates scientists to create new antibiotics. The recurring UTI due to antibiotics-resistant microorganism's challenges scientists globally. The biogenic nanoparticles have the potential to meet the escalating requirements of novel antimicrobial agents. The green synthesis of nanoparticles (NPs) gained more attention due to their reliable applications against resistant microbes. The current study evaluates the biogenic ZnO NPs of Mentha piperata extract against resistant pathogens of urinary tract infections by agar well diffusion assay. The biogenic ZnO NPs revealed comparatively maximum inhibition in comparison to synthetic antibiotics against two bacterial strains (Proteus mirabilis, Pseudomonas aeruginosa) and a fungal strain (Candida albicans).The synthesized biogenic ZnO NPs alone revealed maximum activities than the combination of plant extract (PE) and ZnO NPs, and PE alone. The physiochemical features of ZnO NPs characterized through UV-Vis spectroscopy, FTIR, XRD, SEM, and EDX. The UV-Vis spectroscopy revealed 281.85 nm wavelengths; the XRD pattern revealed the crystalline structure of ZnO NPs. The FTIR analysis revealed the presence of carboxylic and nitro groups, which could be attributed to plant extract. SEM analysis revealed spherical hollow symmetry due to electrostatic forces. The analysis via EDX confirmed the presence of Zn and oxygen in the sample. The physiochemical features of synthesized ZnO NPs provide pivotal information such as quality and effectiveness. The current study revealed excellent dose-dependent antimicrobial activity against the pathogenic isolates from UTI-resistant patients. The higher concentration of ZnONPs interacts with the cell membrane which triggers oxidative burst. They may bind with the enzymes and proteins and brings epigenetic alteration which leads to membrane disruption or cell death., (© 2023. Springer Nature Limited.)

The present study was the first comprehensive investigation of genetic mutation and expression levels of the p53 signaling genes in cutaneous melanoma through various genetic databases providing large datasets. The mutational landscape of p53 and its signaling genes was higher than expected, with TP53 followed by CDKN2A being the most mutated gene in cutaneous melanoma. Furthermore, the expression analysis showed that TP53 , MDM2 , CDKN2A , and TP53BP1 were overexpressed, while MDM4 and CDKN2B were under-expressed in cutaneous melanoma. Overall, TCGA data revealed that among all the other p53 signaling proteins, CDKN2A was significantly higher in both sun and non-sun-exposed healthy tissues than in melanoma. Likewise, MDM4 and TP53BP1 expressions were markedly greater in non-sun-exposed healthy tissues compared to other groups. However, CDKN2B expression was higher in the sun-exposed healthy tissues than in other tissues. In addition, various genes were expressed significantly differently among males and females. In addition, CDKN2A was highly expressed in the SK-MEL-30 skin cancer cell line, whereas, Immune cell type expression analysis revealed that the MDM4 was highly expressed in naïve B-cells. Furthermore, all six genes were significantly overexpressed in extraordinarily overweight or obese tumor tissues compared to healthy tissues. MDM2 expression and tumor stage were closely related. There were differences in gene expression across patient age groups and positive nodal status. TP53 showed a positive correlation with B cells, MDM2 with CD8+ T cells, macrophages and neutrophils, and MDM4 with neutrophils. CDKN2A/B had a non-significant correlation with all six types of immune cells. However, TP53BP1 was positively correlated with all five types of immune cells except B cells. Only TP53, MDM2 , and CDKN2A had a role in cutaneous melanoma-specific tumor immunity. All TP53 and its regulating genes may be predictive for prognosis. The results of the present study need to be validated through future screening, in vivo, and in vitro studies., Competing 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) 2023.)

Ralstonia solanacearum is a phytopathogen causing bacterial wilt diseases of tomato and affecting its productivity, which leads to prominent economic losses annually. As an alternative to conventional pesticides, green synthesized nanoparticles are believed to possess strong antibacterial activities besides being cheap and ecofriendly. Here, we present the synthesis of silver nanoparticles (Sn-AgNPs) from medicinally important aqueous plant extracts of Salvia nubicola . Characterization of biologically synthesized nanoparticles was performed through UV-vis spectrophotometry, Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy, X-ray diffraction, scanning electron microscopy, transmission electron microscopy (TEM), and thermogravimetric analysis. The antibacterial activity of the biosynthesized silver nanoparticles was tested against the phytopathogen R. solanacearum through in vitro experiments. Preliminary phytochemical analysis of the plant extracts revealed the presence of substantial amounts of flavonoids (57.08 mg GAE/g), phenolics (42.30 mg GAE/g), tannins, and terpenoids. The HPLC phenolic profile indicated the presence of 25 possible bioactive compounds. Results regarding green synthesized silver nanoparticles revealed the conformation of different functional groups through FTIR analysis, which could be responsible for the bioreduction and capping of Ag ions into silver NPs. TEM results revealed the spherical, crystalline shape of nanoparticles with the size in the range of 23-63 nm, which validates SEM results. Different concentrations of Sn-AgNPs (T1 (500 μg/mL) to T7 (78.1 μg/mL)) with a combination of plant extracts (PE-Sn-AgNPs) and plant extracts alone exhibited an efficient inhibition of R. solanacearum . These findings could be used as an effective alternative preparation against the bacterial wilt of tomato., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Drought is one of the most important wheat production limiting factor, and can lead to severe yield losses. This study was designed to examine the effect of drought stress on wheat physiology and morphology under three different field capacities (FC) viz. 80% (control), 50% (moderate) and 30% (severe drought stress) in a diverse collection of wheat germplasm including cultivars, landraces, synthetic hexaploid and their derivatives. Traits like grain weight, thousand grain weight and biomass were reduced by 38.23%, 18.91% and 26.47% respectively at 30% FC, whereas the reduction rate for these traits at 50% FC were 19.57%, 8.88% and 18.68%. In principal component analysis (PCA), the first two components PC1 and PC2 accounted for 58.63% of the total variation and separated the cultivars and landraces from synthetic-based germplasm. Landraces showed wide range of phenotypic variations at 30% FC compared to synthetic-based germplasm and improved cultivars. However, least reduction in grain weight was observed in improved cultivars which indicated the progress in developing drought resilient cultivars. Allelic variations of the drought-related genes including TaSnRK2.9-5A, TaLTPs-11, TaLTPs-12, TaSAP-7B-, TaPPH-13, Dreb-B1 and 1fehw3 were significantly associated with the phenological traits under drought stress in all 91 wheats including 40 landraces, 9 varieties, 34 synthetic hexaploids and 8 synthetic derivatives. The favorable haplotypes of 1fehw3, Dreb-B1, TaLTPs-11 and TaLTPs-12 increased grain weight, and biomass. Our results iterated the fact that landraces could be promising source to deploy drought adaptability in wheat breeding. The study further identified drought tolerant wheat genetic resources across various backgrounds and identified favourable haplotypes of water-saving genes which should be considered to develop drought tolerant varieties., (© 2023. The Author(s).)

Seed priming is considered to play an essential role in the overall improvement of agricultural crops. The current research work was carried out in order to investigate the comparative effects of hydropriming and iron priming on the germination behavior and morphophysiological attributes of wheat seedlings. The experimental materials consisted of three wheat genotypes including a synthetically derived wheat line (SD-194), stay-green wheat genotype (Chirya-7), and conventional wheat variety (Chakwal-50). The treatments included hydro (distilled and tap water)- and iron priming (10 and 50 mM) of wheat seeds for 12 h duration. Results indicated that both priming treatment and wheat genotypes exhibited highly different germination and seedling characteristics. These included germination percentage, root volume, root surface, root length, relative water content, chlorophyll content, membrane stability index, and chlorophyll fluorescence attributes. Furthermore, the synthetically derived line (SD-194) was the most promising in majority of the studied attributes by exhibiting a high germination index (2.21%), root fresh weight (7.76%), shoot dry weight (3.36%), relative water content (19.9%), chlorophyll content (7.58%), and photochemical quenching coefficient (2.58%) when compared with stay-green wheat (Chirya-7). The study also found that hydropriming with tap water and priming wheat seeds with low concentrations of iron yielded better results when a comparison was made with wheat seeds primed at high concentrations of iron. Therefore, wheat seed priming with tap water and iron solution for 12 h is recommended for optimum wheat improvement. Furthermore, current findings suggest that seed priming may have the prospect of an innovative and user-friendly approach for wheat biofortification with the aim of enhanced iron acquisition and accumulation in grains., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Diabetic retinopathy (DR) is a diabetes complication that can cause vision loss among patients due to damage to blood vessels in the retina. Early retinal screening can avoid the severe consequences of DR and enable timely treatment. Nowadays, researchers are trying to develop automated deep learning-based DR segmentation tools using retinal fundus images to help Ophthalmologists with DR screening and early diagnosis. However, recent studies are unable to design accurate models due to the unavailability of larger training data with consistent and fine-grained annotations. To address this problem, we propose a semi-supervised multitask learning approach that exploits widely available unlabelled data (i.e., Kaggle-EyePACS) to improve DR segmentation performance. The proposed model consists of novel multi-decoder architecture and involves both unsupervised and supervised learning phases. The model is trained for the unsupervised auxiliary task to effectively learn from additional unlabelled data and improve the performance of the primary task of DR segmentation. The proposed technique is rigorously evaluated on two publicly available datasets (i.e., FGADR and IDRiD) and results show that the proposed technique not only outperforms existing state-of-the-art techniques but also exhibits improved generalisation and robustness for cross-data evaluation., (© 2023. The Author(s).)

The Begomovirus genus of the family Geminiviridae comprises the largest group of geminiviruses. Begomoviruses are transmitted by the whitefly complex ( Bemisia tabaci ) and infect dicotyledonous plants in tropical and subtropical regions. The list of begomoviruses is continuously increasing as a result of improvements in the methods for identification, especially from weed plants, which are considered a source of new viruses and reservoirs of economically important viruses but are often neglected during diversity studies. Lathyrus aphaca L. weed plants (yellow-flowered pea) with varicose veins and discoloration of the leaves were found. Amplified genomic DNA through rolling circular amplification was subjected to PCR analysis for the detection of the viral genome and associated DNA-satellites (alphasatellites and betasatellites). A full-length sequence (2.8 kb) of a monopartite begomovirus clone was determined; however, we could not find any associated DNA satellites. The amplified full-length clone of Rose leaf curl virus (RoLCuV) reserved all the characteristics and features of an Old World (OW) monopartite begomovirus. Furthermore, it is the first time it has been reported from a new weed host, yellow-flowered pea. Rolling circle amplification and polymerase chain reaction analysis of associated DNA satellites, alphasatellite, and betasatellite, were frequently accomplished but unable to amplify from the begomovirus-infected samples, indicating the presence of only monopartite Old World begomovirus. It is observed that RoLCuV has the capability to infect different hosts individually without the assistance of any DNA satellite component. Recombination in viruses is also a source of begomovirus infection in different hosts.

Consumption of high fluoride (F - ) and nitrate (NO 3 - ) containing water may pose serious health hazards. One hundred sixty-one groundwater samples were collected from drinking wells in Khushab district, Punjab Province, Pakistan, to determine the causes of elevated F - and NO 3 - concentrations, and to estimate the human health risks posed by groundwater contamination. The results showed pH of the groundwater samples ranged from slightly neutral to alkaline, and Na + and HCO 3 - ions dominated the groundwater. Piper diagram and bivariate plots indicated that the key factors regulating groundwater hydrochemistry were weathering of silicates, dissolution of evaporates, evaporation, cation exchange, and anthropogenic activities. The F - content of groundwater ranged from 0.06 to 7.9 mg/L, and 25.46% of groundwater samples contained high-level fluoride concentration (F -  > 1.5 mg/L), which exceeds the (WHO Guidelines for drinking-water quality: incorporating the first and second addenda, WHO, Geneva, 2022) guidelines of drinking-water quality. Inverse geochemical modeling indicates that weathering and dissolution of fluoride-rich minerals were the primary causes of F - in groundwater. High F - can be attributed to low concentration of calcium-containing minerals along the flow path. The concentrations of NO 3 - in groundwater varied from 0.1 to 70 mg/L; some samples are slightly exceeding the (WHO Guidelines for drinking-water quality: incorporating the first and second addenda, WHO, Geneva, 2022) guidelines for drinking-water quality. Elevated NO 3 - content was attributed to the anthropogenic activities revealed by PCA analysis. The high levels of nitrates found in the study region are a result of various human-caused factors, including leaks from septic systems, the use of nitrogen-rich fertilizers, and waste from households, farming operations, and livestock. The hazard quotient (HQ) and total hazard index (THI) of F - and NO 3 - showed high non-carcinogenic risk (> 1) via groundwater consumption, demonstrating a high potential risk to the local population. This study is significant because it is the most comprehensive examination of water quality, groundwater hydrogeochemistry, and health risk assessment in the Khushab district to date, and it will serve as a baseline for future studies. Some sustainable measures are urgent to reduce the F - and NO 3 - content in the groundwater., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Main Conclusion: The study provided an insight toward better understanding of stay-green mechanisms for drought tolerance improvement and identified that synthetic-derived wheats proved as a promising germplasm for improved tolerance against water stress. Stay-green (SG) trait is considered to be related with the ability of wheat plants to maintain photosynthesis and CO 2 assimilation. The present study explored the interaction of water stress with SG expression through physio-biochemical, agronomic and phenotypic responses among diverse wheat germplasm comprising of 200 synthetic hexaploids, 12 synthetic derivatives, 97 landraces and 16 conventional bread wheat varieties, for 2 years. The study established that variation of SG trait existed in the studied wheat germplasm and there was positive association between SG trait and tolerance to water stress. The relationship of SG trait with chlorophyll content (r = 0.97), ETR (r = 0.28), GNS (r = 0.44), BMP (r = 0.34) and GYP (r = 0.44) was particularly promising under water stress environment. Regarding chlorophyll fluorescence, the positive correlation of фPSII (r = 0.21), qP (r = 0.27) and ETR (r = 0.44) with grain yield per plant was noted. The improved ΦPSII and Fv/Fm of PSII photochemistry resulted in the high photosynthesis activity in SG wheat genotypes. Regarding relative water content and photochemical quenching coefficient, synthetic-derived wheats were better by maintaining 20.9, 9.8 and 16.1% more RWC and exhibiting 30.2, 13.5 and 17.9% more qP when compared with landraces, varieties and synthetic hexaploids, respectively, under water stress environment. Synthetic derived wheats also exhibited relatively more SG character with good yield and were more tolerant to water stress in terms of grain yield, grain weight per plant, better photosynthetic performance through chlorophyll fluorescence measurement, high leaf chlorophyll and proline content, and hence, may be used as novel sources for breeding drought tolerant materials. The study will further facilitate research on wheat leaf senescence and will add to better understanding of SG mechanisms for drought tolerance improvement., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Mushrooms play a crucial role in human life as well as in nature, providing food, medicine, and carrying out vital processes of decomposition, nutrient recycling, and developing mycorrhizal association with plants. The traditional system of knowledge about identification, collection, and usage of mushrooms has been accumulated through the shared experiences of many generations. Unfortunately, there have been continuous threats to the folk knowledge of mushrooms mainly due to habitat degradation, urbanization, and contemporary medication. The current research was, therefore, aimed to document an ethnomycological knowledge possessed by the ethnic communities of Swat, Pakistan. The purposive randomized sampling was carried out using chain referral method. Ethno-mycological information was collected from 62 informants using free listing, preference ranking, and use totaled methods. In total, 34 species of mushrooms belonging to 31 genera and 21 families were reported. About 85% of the reported species belong to Basidiomycetes, and 12.5% to Ascomycetes are used as food and for medicinal purposes. Morchella angusticeps , M. esculenta , Pleurotus sp., Auricularia sp., Flammulina velutipes , Agaricus bisporus , Ganoderma lucidum , and Sanghuangporus sanghuang were among the most cited edible and medicinal mushrooms. The current study revealed that district Swat is rich in wild edible and medicinal mushrooms (WEMs), and the local communities possess rich traditional knowledge about their collection, storage, and utilization. The diversity of WEMs of this region could contribute substantially to the socio-economic uplifting of the local communities through appropriate domestication and commercialization. Anthropogenic factors, coupled with depletion of traditional knowledge, threaten the diversity of WEMs in the region; therefore, in situ and ex situ conservation strategies are highly recommended.

Efficient diagnosis of COVID-19 plays an important role in preventing the spread of the disease. There are three major modalities to diagnose COVID-19 which include polymerase chain reaction tests, computed tomography scans, and chest X-rays (CXRs). Among these, diagnosis using CXRs is the most economical approach; however, it requires extensive human expertise to diagnose COVID-19 in CXRs, which may deprive it of cost-effectiveness. The computer-aided diagnosis with deep learning has the potential to perform accurate detection of COVID-19 in CXRs without human intervention while preserving its cost-effectiveness. Many efforts have been made to develop a highly accurate and robust solution. However, due to the limited amount of labeled data, existing solutions are evaluated on a small set of test dataset. In this work, we proposed a solution to this problem by using a multi-task semi-supervised learning (MTSSL) framework that utilized auxiliary tasks for which adequate data is publicly available. Specifically, we utilized Pneumonia, Lung Opacity, and Pleural Effusion as additional tasks using the ChesXpert dataset. We illustrated that the primary task of COVID-19 detection, for which only limited labeled data is available, can be improved by using this additional data. We further employed an adversarial autoencoder (AAE), which has a strong capability to learn powerful and discriminative features, within our MTSSL framework to maximize the benefit of multi-task learning. In addition, the supervised classification networks in combination with the unsupervised AAE empower semi-supervised learning, which includes a discriminative part in the unsupervised AAE training pipeline. The generalization of our framework is improved due to this semi-supervised learning and thus it leads to enhancement in COVID-19 detection performance. The proposed model is rigorously evaluated on the largest publicly available COVID-19 dataset and experimental results show that the proposed model attained state-of-the-art performance., 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., (© 2022 Elsevier Ltd. All rights reserved.)

A large amount of Cr (VI)-polluted wastewater produced in electroplating, dyeing and tanning industries seriously threatens water ecological security and human health. Due to the lack of high-performance electrodes and the coulomb repulsion between hexavalent chromium anion and cathode, the traditional DC-mediated electrochemical remediation technology possesses low Cr (VI) removal efficiency. Herein, by modifying commercial carbon felt (O-CF) with amidoxime groups, amidoxime-functionalized carbon felt electrodes (Ami-CF) with high adsorption affinity for Cr (VI) were prepared. Based on Ami-CF, an electrochemical flow-through system powered by asymmetric AC was constructed. The mechanism and influencing factors of efficient removal of Cr (VI) contaminated wastewater by an asymmetric AC electrochemical method coupling Ami-CF were studied. Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR), and X-ray photoelectron spectroscopy (XPS) characterization results showed that Ami-CF was successfully and uniformly loaded with amidoxime functional groups, and the adsorption capacity of Cr (VI) was more than 100 times higher than that of O-CF. In particular, the Coulomb repulsion effect and the side reaction of electrolytic water splitting were inhibited by the high-frequency anode and cathode switching (asymmetric AC), the mass transfer rate of Cr (VI) from electrode solution was increased, the reduction efficiency of Cr (VI) to Cr (III) was significantly promoted and a highly efficient removal of Cr (VI) was achieved. Under optimal operating conditions (positive bias 1 V, negative bias 2.5 V, duty ratio 20%, frequency 400 Hz, solution pH = 2), the asymmetric AC electrochemistry based on Ami-CF can achieve fast (30 s) and efficient removal (>99.11%) for 0.5-100 mg·L -1 Cr (VI) with a high flux of 300 L h -1 m -2 . At the same time, the durability test verified the sustainability of the AC electrochemical method. For Cr (VI)-polluted wastewater with an initial concentration of 50 mg·L -1 , the effluent concentration could still reach drinking water grade (<0.05 mg·L -1 ) after 10 cycling experiments. This study provides an innovative approach for the rapid, green and efficient removal of Cr (VI) containing wastewater at low and medium concentrations.

Breast tumor is the second deadliest disease among women around the world. Earlier tumor diagnosis is extremely important for improving the survival rate. Recent deep-learning techniques proved helpful in the timely diagnosis of various tumors. However, in the case of breast tumors, the characteristics of the tumors, i.e., low visual contrast, unclear boundary, and diversity in shape and size of breast lesions, make it more challenging to design a highly efficient detection system. Additionally, the scarcity of publicly available labeled data is also a major hurdle in the development of highly accurate and robust deep-learning models for breast tumor detection. To overcome these issues, we propose residual-attention-based uncertainty-guided mean teacher framework which incorporates the residual and attention blocks. The residual for optimizing the deep network by enabling the flow of high-level features and attention modules improves the focus of the model by optimizing its weights during the learning process. We further explore the potential of utilizing unlabeled data during the training process by employing the semi-supervised learning (SSL) method. Particularly, the uncertainty-guided mean-teacher student architecture is exploited to demonstrate the potential of incorporating the unlabeled samples during the training of residual attention U-Net model. The proposed SSL framework has been rigorously evaluated on two publicly available labeled datasets, i.e., BUSI and UDIAT datasets. The quantitative as well as qualitative results demonstrate that the proposed framework achieved competitive performance with respect to the previous state-of-the-art techniques and outperform the existing breast ultrasound masses segmentation techniques. Most importantly, the study demonstrates the potential of incorporating the additional unlabeled data for improving the performance of breast tumor segmentation., 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 © 2023 Elsevier Ltd. All rights reserved.)

With the rise of the Internet and social media, information has become available at our fingertips. However, on the dark side, these advancements have opened doors for fraudsters. Online recruitment fraud (ORF) is one of the problems created by these modern technologies, as hundreds of thousands of applicants are victimized every year globally. Fraudsters advertise bogus jobs on online platforms and target job hunters with fake offerings such as huge salaries and desirable geographical locations. The objective of these fraudsters is to collect personal information to be misused in the future, leading to the loss of applicants' privacy. To prevent such situations, there is a need for an automatic detecting system that can distinguish between real and fake job advertisements and preserve the applicants' privacy. This study attempts to build a smart secured framework for detecting and preventing ORF using ensemble machine learning (ML) techniques. In this regard, four ensemble methods-AdaBoost (AB), Xtreme Gradient Boost (XGB), Voting, and Random Forest (RF)-are used to build a detection framework. The dataset used was pre-processed using several methods for cleaning and denoising in order to achieve better outcomes. The performance evaluation measures of the applied methods were accuracy, precision, sensitivity, F-measure, and ROC curves. According to these measures, AB performed best, followed by XGB, voting, and RF. In the proposed framework, AB achieved a high accuracy of 98.374%, showing its reliability for detecting and preventing ORF. The results of AB were compared to existing methods in the literature validating the reliability of the model to be significantly used for detecting ORF., Competing Interests: The authors declare there are no competing interests., (©2023 Ullah and Jamjoom.)

In numerous perilous cases, a quick medical decision is needed for the early detection of chronic diseases to avoid austere consequences that may be fatal. Chronic kidney disease (CKD) is a prevalent disease that presents a variety of challenges, including soaring costs for intervention, urgency, and, more importantly, difficulty in early detection of the disease. The current study carries out a prediction-based method that helps in detecting and diagnosing CKD patients which enables a fast and accurate decision-making process at the early stage. A combination of preprocessing and feature selection methods was developed; additionally, several prediction models, such as K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and bagging, were trained based on the processed dataset. The performance evaluation shows higher reliability of all models in terms of accuracy, precision, sensitivity, F-measure, specificity, and area under the curve (AUC) score. Specifically, KNN outperformed with an accuracy of 99.50%, sensitivity of 99.2%, precision of 100%, specificity of 98.7%, and F-measure and AUC score of 99.6%. The experimental results of KNN show the best fitted model compared to the existing state-of-the-art methods. Moreover, the reduced feature set proves that just a few clinical tests are enough to detect CKD, resulting in diagnosis cost reduction., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2023 Zahid Ullah and Mona Jamjoom.)

Groundwater contamination by heavy metals (HMs) released by weathering and mineral dissolution of granite, gneisses, ultramafic, and basaltic rock composition causes human health concerns worldwide. This paper evaluated the heavy metals (HMs) concentrations and physicochemical variables of groundwater around enriched chromite mines of Malakand, Pakistan, with particular emphasis on water quality, hydro-geochemistry, spatial distribution, geochemical speciation, and human health impacts. To better understand the groundwater hydrogeochemical profile and HMs enrichment, groundwater samples were collected from the mining region (n = 35), non-mining region (n = 20), and chromite mines water (n = 5) and then analyzed using ICPMS (Agilent 7500 ICPMS). The ranges of concentrations in the mining, non-mining, and chromite mines water were 0.02-4.5, 0.02-2.3, and 5.8-6.0 mg/L for CR, 0.4-3.8, 0.05-3.6, and 3.2-5.8 mg/L for Ni, and 0.05-0.8, 0.05-0.8, and 0.6-1.2 mg/L for Mn. Geochemical speciation of groundwater variables such as OH - , H + , Cr +2 , Cr +3 , Cr +6 , Ni +2 , Mn +2 , and Mn +3 was assessed by atomic fluorescence spectrometry (AFS). Geochemical speciation determined the mobilization, reactivity, and toxicity of HMs in complex groundwater systems. Groundwater facies showed 45% CaHCO 3 , 30% NaHCO 3 , 23.4% NaCl, and 1.6% Ca-Mg-Cl water types. The noncarcinogenic and carcinogenic risk of HMs outlined via hazard quotient (HQ) and total hazard indices (THI) showed the following order: Ni > Cr > Mn. Thus, the HHRA model suggested that children are more vulnerable to HMs toxicity than adults. Hierarchical agglomerative cluster analysis (HACA) showed three distinct clusters, namely the least, moderately, and severely polluted clusters, which determined the severity of HMs contamination to be 66.67% overall. The PCAMLR and PMF receptor model suggested geogenic (minerals prospects), anthropogenic (industrial waste and chromite mining practices), and mixed (geogenic and anthropogenic) sources for groundwater contamination. The mineral phases of groundwater suggested saturation and undersaturation. Nemerow's pollution index (NPI) values determined the unsuitability of groundwater for domestic purposes. The EC, turbidity, PO 4 -3 , Na + , Mg +2 , Ca +2 , Cr, Ni, and Mn exceeded the guidelines suggested by the World Health Organization (WHO). The HMs contamination and carcinogenic and non-carcinogenic health impacts of HMs showed that the groundwater is extremely unfit for drinking, agriculture, and domestic demands. Therefore, groundwater wells around the mining region need remedial measures. Thus, to overcome the enrichment of HMs in groundwater sources, sustainable management plans are needed to reduce health risks and ensure health safety.

Automatic COVID-19 detection using chest X-ray (CXR) can play a vital part in large-scale screening and epidemic control. However, the radiographic features of CXR have different composite appearances, for instance, diffuse reticular-nodular opacities and widespread ground-glass opacities. This makes the automatic recognition of COVID-19 using CXR imaging a challenging task. To overcome this issue, we propose a densely attention mechanism-based network (DAM-Net) for COVID-19 detection in CXR. DAM-Net adaptively extracts spatial features of COVID-19 from the infected regions with various appearances and scales. Our proposed DAM-Net is composed of dense layers, channel attention layers, adaptive downsampling layer, and label smoothing regularization loss function. Dense layers extract the spatial features and the channel attention approach adaptively builds up the weights of major feature channels and suppresses the redundant feature representations. We use the cross-entropy loss function based on label smoothing to limit the effect of interclass similarity upon feature representations. The network is trained and tested on the largest publicly available dataset, i.e., COVIDx, consisting of 17,342 CXRs. Experimental results demonstrate that the proposed approach obtains state-of-the-art results for COVID-19 classification with an accuracy of 97.22%, a sensitivity of 96.87%, a specificity of 99.12%, and a precision of 95.54%., (© 2023. The Author(s).)

Potable groundwater (GW) contamination through arsenic (As) is a commonly reported environmental issue in Pakistan. In order to examine the groundwater quality for As contamination, its geochemical behavior, and other physicochemical parameters, 69 samples from various groundwater sources were collected from the mining area of Pind Dadan Khan, Punjab, Pakistan. The results showed the concentration of elevated As, its source of mobilization, and linked public health risk. Arsenic detected in the groundwater samples varied from 0.5 to 100 µg/L, with an average value of 21.38 µg/L. Forty-two samples were beyond the acceptable limit of 10 µg/L of the WHO for drinking purposes. The statistical summary showed that the groundwater cation concentration was in decreasing order such as Na +  > Ca 2+  > Mg 2+  > K + , while anions were as follows: HCO 3 -  > SO4 2-  > Cl -  > NO 3 - . Hydrochemical facies results depicted that groundwater samples belong to CaHCO 3 type. Rock-water interactions control the hydrochemistry of groundwater. Saturation indices' results indicated the saturation of the groundwater sources for CO 3 minerals due to their positive SI values. Such minerals include aragonite, calcite, dolomite, and fluorite. The principal component analysis (PCA) findings possess a total variability of 77.36% suggesting the anthropogenic and geogenic contributing sources of contaminant. The results of the Exposure-health-risk-assessment model for measuring As reveal significant potential carcinogenic risk exceeding the threshold level (value > 10 -4 ) and HQ level (value > 1.0)., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Dachang mining area in China is known as "paradise for mineralogists" due to its most reserves of Sn, Sb, Pb, and Zn non-ferrous metal resources; thus, its evaluation for heavy metal assessment and consequent health risk is unavoidable. Sixty road dust samples were collected from study area to explore pollution level, ecological, and health risks from heavy metals and were analyzed by an inductively coupled plasma optical emission spectrometer and atomic fluorescence spectrometer. The results showed that average concentration of all the heavy metals in road dust in both mining and residential areas were remarkable higher than its corresponding background values, the former being more severe, except for Cr and Co. The morphological investigation showed that most of the particles were much less than 100 μm illustrating fine part of the road dust samples. Based on integrated pollution indices, Cd, Sb, As, Zn, and Pb were extremely contaminated and exceeded hundred times of the maximum risk value. The health risk assessment revealed substantially higher carcinogenic and non-carcinogenic risks to children and adult. Highest non-carcinogenic risk resulted from arsenic in mining and residential area with HQ ing of 644.56 and 267.94 respectively (standard HQ ≥ 1) while carcinogenic risk to children (1.94E + 00) which greatly exceeded from the threshold value of (1.0E-4). Sb, Cd, and Pb also posed carcinogenic and non-carcinogenic risk in road dust which is caused by excessive mining activities and heavy vehicle movement in the study area., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Mining activities have serious environmental impacts, thus releasing heavy metals (HMs) such as cadmium (Cd), lead (Pb), chromium (Cr), zinc (Zn) and nickel (Ni) into the surrounding environment. The current paper investigated the impacts of mining activities of Pb-Zn sulfide on soil and medicinal plants. Hence, soil samples (n = 36) and medicinal plants (n = 36) samples were collected, acid extracted and were analyzed through Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for HMs quantification. Our results showed that mineralized zones showed high HMs enrichment levels as compared to non-mineralized zones. Various Indices for HMs assessment revealed that the contaminated soil of the study area had low to extreme level. The mean concentrations of HMs in mining degraded soil and medicinal plants were significantly higher (p ≤ 0.01) and were found in order of Zn > Pb > Cr > Ni > Cd and Cr > Zn > Pb > Ni > Cd respectively. Similarly, some widely consumable medicinal plants showed good metal accumulation for Cd, Cr and Pb i.e., 3.57 mg kg 1 , 350 mg kg -1 and 335 mg kg -1 in C. sativa, while 5.9 mg kg-1, 276.9 mg kg-1 and 188.7 mg kg-1 in R. hestatus respectively. Hence, the present study recommended that medicinal plants grown in mining areas should be analyzed for HMs concentration before consumption., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The growing issue of demand-supply management between the prosumers and the local energy market requires an efficient and reliable energy management model. The microlayers, such as prosumers, energy districts, and macro players, namely retail dealers and wholesale dealers play a pivotal role in achieving mutual benefits. The stochastic nature of renewable energy generation in energy districts requires an effective model that can contemplate all stochastic complexities. Therefore, this paper proposes a mutual trade model between energy districts and smart grid to authorize the prosumers for mutual energy transactions under the stochastic adaptive-service level agreement. Moreover, multiple smart contacts are developed between the stakeholders to design adaptability and stochastic behavior of wind speed and solar irradiance. The real-time adaptations of the stochastic adaptive-service level agreement are based on technical beneficial feasibility and achieved through stochastic and adaptive functions. The optimized solution based on a genetic algorithm is proposed for the energy cost and energy surplus of prosumers and output parameters of the mutual trade model (grid revenue). In the context of mutual benefits associated with balanced demand and supply, the economic load dispatch and simplex method maximization are used for optimized demand-supply energy management. Moreover, the effectiveness of the proposed adaptive and stochastic mutual trade model is validated through simulation and statistical analysis., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Ahmed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Vegetation structures and dynamics are the result of interactions between abiotic and biotic factors in an ecosystem. The present study was designed to investigate vegetation structure and species diversity along various environmental variables in the Yakhtangay Hills of the Hindu-Himalayan Mountain Pakistan, by using multivariate statistical analysis. Quadrat quantitative method was used for the sampling of vegetation. PC-ORD version 5 software was used to classify the vegetation into different plants communities using cluster analysis. The results of regression analysis among various edaphic variables shows that soil organic matter, total dissolved solids, electrical conductivity, CaCO 3 and moisture contents shows a significant positive correlation with species abundance, while the soil pH has inverse relationship with plant species abundance. Similarly, species richness increases with increase in soil organic matter, CaCO 3 and moisture contents, while decrease with increase in soil pH, total dissolved solids and electrical conductivity (p < 0.05). The vegetation was classified into four major plant communities and their respective indicators were identified using indicator species analysis. Indicator species analysis reflects the indicators of the study area are mostly the indicators to the Himalayan or moist temperate ecosystem. These indicators could be considered for micro-habitat conservation and respective ecosystem management plans not only in the study area but also in other region with similar sort of environmental conditions., (© 2022. The Author(s).)

Large-scale wind power integration has raised concerns about the reliability and stability of power systems. The rotor circuit of a doubly fed induction generator (DFIG) is highly vulnerable to unexpected voltage dips, which can cause considerable electromotive force in the circuit. Consequently, the DFIG must fulfil the fault-ride through (FRT) criteria to ensure the system's performance and contribute to voltage regulation during severe grid outages. This paper provides a hybrid solution for DFIG wind turbines with FRT capabilities, using both a modified switch-type fault current limiter (MSFTCL) and a direct current (DC) chopper. The proposed system has the merit of keeping the rotor current and the DC-link voltage within the permissible limits, enhancing the FRT capability of generators. Moreover, the boundness of supply voltage into its reference value ensures dynamic stability during symmetric and asymmetric grid failures. Further, electromagnetic torque variations are significantly reduced during fault events. Finally, the performance validation of the proposed scheme is performed in a simulation setup, and the results are compared with the existing sliding mode control (SMC) and proportional-integral (PI) controller-based approaches. The comparison results show that a hybrid strategy with advanced controllers provides superior performance for all critical parameters.

Water availability is considered as the main limiting factor of wheat growth illuminating the need of cultivars best adapted to drought situations for better wheat production and yield. Among these, the stay-green trait is thought to be related to the ability of wheat plants to maintain photosynthesis and CO 2 assimilation, and a detailed molecular understanding of this trait may help in the selection of high-yielding, drought-tolerant wheats. The current study, therefore, evaluated the physiological responses of the selected wheat genotypes under pot-induced water stress conditions through different field capacities. The study also focused on exploring the molecular mechanisms involved in drought tolerance conferred due to the stay-green trait by studying the expression pattern of the selected PSI-associated light-harvesting complex I (LHC1) and PSII-associated LHCII gene families related to pigment-binding proteins. The results revealed that the studied traits, including relative water content, membrane stability index and chlorophyll, were variably and negatively affected, while the proline content was positively enhanced in the studied wheats under water stress treatments. Molecular diagnosis of the selected wheat genotypes using the expression profile of 06 genes, viz. TaLhca1 , TaLhca2 , TaLhca3 , TaLhcb1 , TaLhcb4 and TaLhcb6 that encodes for the LHCI and LHCII proteins, indicated variable responses to different levels of drought stress. The results obtained showed the relation between the genotypes and the severity of the drought stress condition. Among the studied genotypes, Chirya-1 and SD-28 performed well with a higher level of gene expression under drought stress conditions and may be used in genetic crosses to enrich the genetic background of common wheat against drought stress.

Objective: The goal of this study was to understand the possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis., Methods: GEO contains datasets of gene expression, miRNA, and methylation patterns of diseased and healthy/control patients. The GSE62232 dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC and 10 healthy samples as control. GSE62232 was analysed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting the interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analysed using GEPIA to estimate the effect of their differential expression on cancer progression., Results: We identified the top 10 hub genes through CytoHubba plugin. These included BUB1, BUB1B, CCNB1, CCNA2, CCNB2, CDC20, CDK1 and MAD2L1, NCAPG, and NDC80. NCAPG and NDC80 reported for the first time in this study while the remaining from a recently reported literature. The pathogenesis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for future prognostic and predictive biomarkers studies that could promote selective molecular therapy for HCC., Competing Interests: There is no conflict of interest among the authors regarding the publication of this manuscript., (Copyright © 2022 Mohib Ullah Kakar et al.)

The study recorded the food uses of wild food plants (WFPs) among the Sarikoli diaspora and the dominant Wakhi in Broghil Valley, North Pakistan, to understand their food adaptation, mainly by looking through the lens of food ethnobotanies. A total of 30 participants took part in the study, which included 15 elderly individuals from each ethnic group. Data were gathered through semi-structured interviews. We recorded 29 WFPs, mostly used as cooked vegetables and snacks. The food uses, as well as the local plant nomenclatures, linked to WFPs of the two studied groups were completely homogenized, which could be attributed to the cultural assimilation of the Sarikoli people to Wakhi culture. We found that although traditional knowledge on WFPs has been homogenized, social change in nearby regions is also threatening the traditional knowledge of the two communities, as evidenced by the smaller number of plants reported compared to that of all other field ethnobotanical studies conducted in nearby regions. Moreover, the growth of legal restrictions and sanctions on accessing natural resources are posing serious challenges to cultural resilience in the valley, and the restrictions on cross-border movement in particular are creating challenges for those who have cross-border kinship relationships between the two groups. We suggest specific measures, such as the promotion of food tourism and educational activities, to protect traditional knowledge and bicultural heritage from further erosion in the region.

Faba bean ( Vicia faba L.), a drought-sensitive crop, is drastically affected by drought stresses compromising its growth and yield. However, wild relatives of faba bean are considered a reservoir of potential genetic resources for tolerance against abiotic stresses. This study was conducted to characterize wild relatives of faba bean for identification of a specific tolerance system required for its improvement against drought stress. The study focused on physiological, biochemical, and anatomical responses of wild Vicia species under drought stress conditions. The experiment was carried out under various levels of drought stress imposed through different field capacities (FC) which included 80% FC ie (well-watered condition), 55% FC (moderate stress), and 30% FC (severe stress). When compared to plants grown in a control environment, drought stress significantly reduced the studied physiological attributes including soluble sugars (21.3% and 15.8%), protein contents (14.7 and 14.6%), and chlorophyll (8.4 and 28.6%) under moderate (55% FC) and severe drought stress (30% FC), respectively. However, proline content increased by 20.5% and 27.6%, peroxidase activity by 48.5% and 57.1%, and superoxide dismutase activity by 72.6% and 64.8% under moderate and severe stress, respectively. The studied anatomical attributes were also affected under drought stress treatments, including diameter of stem xylem vessels (9.1% and 13.7%), leaf lower epidermal thickness (8.05% and 13.34%), and leaf phloem width (5.3% and 10.1%) under moderate and severe stress, respectively. Wild Vicia spp. showed better tolerance to water-deficit conditions as compared to cultivated Vicia L. The observed potential diversity for drought tolerance in wild Vicia spp. may assist in improvement of faba bean and may also help in understanding the mechanisms of adaptations in drought-prone environments.

Crop wild resources are excellent sources of new genetic variation for resilience against climate extremes. However, detailed characterization of the desirable phenotypes is essential before using these crop wild resources in breeding programs. This current study was, therefore, conducted to investigate the water stress responses of eight wild Elymus species and two wheat cultivars. The experiment was carried out under varying levels of osmotic stress induced by polyethylene glycol and progressive water stress through different field capacities. Water stress significantly reduced both physiological and biochemical traits compared to control, ranging from 7.1% (protein content) to 34.5% (chlorophyll) under moderate stress and 9.1-45.8% under severe stress. The anatomical features were also affected under progressive water stress, including a reduction in xylem vessel diameter (7.92 and 16.50%), phloem length (4.36 and 7.18%), vascular bundle length (3.09 and 6.04%), and ground tissue thickness (2.36 and 5.52%), respectively. Conclusively, Elymus borianus (endemic to Swat, Pakistan) , E . russelli, E . caninus, E . longioristatus , and E . dauhuricus outperformed the check wheat cultivar, Pirsabak 2005, which is a rainfed variety. The results revealed that Elymus species belonging to the tertiary gene pool of bread wheat could be an excellent drought tolerance source for use in a breeding program., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer JI declared a shared affiliation with the author AR to the handling editor at the time of the review., (Copyright © 2022 Khan, Ali, Ullah, Ali, Kaushik, Alyemeni, Rasheed and Sher.)

The light and scanning electron microscopic observations were carried out for anatomical features of leaf, pollens and powder.Microscopic studies provide useful information for identification and authentication of adulteration in A. maritima . Nutritional analysis of A. maritima revealed that life fundamental macromolecules such as carbohydrates (49.63 %) crude proteins (13.17 %) and crude fibers (21.06 %) were present in sufficient quantity while crude fats (4.11 %) reported in low quantity. The life essential elements such as Mg (9.472 ± 0.011), Ca (4.152 ± 0.135) and Fe (4.112 ± 0.002) were found in high concentration while heavy metals reported under the safety threshold of WHO. These observations favored A. maritima an alternative of food.Appreciable quantity of phenolics (17.64 ± 0.574) and flavonoids (7.67 ± 0.069) were found while qualitatively active phytochemicals were reported. The FTIR characterization of A. maritima crude powder revealed chromatogram in 3328.61 to 408.68 frequency range and 24 characteristic peaks on the basis of which different compounds of biological importance were classified. HPLC-UV technique quantifiedand identified six phenolic compounds morin,epigallocatechin gallate, catechin hydrate,ellagic acid, pyrogallol andrutin. Identification of compounds through GC-MS chromatogram revealed the presence of 46 compounds in methanolic fraction however 17 compounds of biological importance were selected. In-vitro biological evaluation of A. maritima for antioxidant, antimicrobial, antidiabetic (12.61 ± 0.113 %) and cytotoxic activities (LC 50  = 20 μg/ml) suggested that methanolic fractions exhibited the highest activity as compared to chloroform and ethyl acetate fractions. The MIC values of 10 or 15 mg/ml were recorded for most of the fungal pathogens. Antibacterial activity revealed 3.75 mg/ml of MIC values against B. subtilis and 1.87 mg/ml against S. aureus, E. coli and P. aeruginosa . In-vivo biological evaluation revealed thatmaximum inhibition was observed for crude extract at 250 mg/kg body weight. The mechanism underlined in-vivo analgesic responses was carried out which revealed that naloxone (morphine and tramadol antagonist) showed no prominent effect while Glibenclamide pretreatment minutely modified the analgesic action. These observations clearly indicted the absence of opiod receptors and involvement of ATP sensitive potassium channels., 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., (© 2022 The Authors.)