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Introduction: Invasive species have been identified as a major threat to native biodiversity and ecosystem functioning worldwide due to their superiority in spread and growth. Such superiority is explained by the invasional meltdown phenomena, which suggests that invasive species facilitate the establishment of more invasive species rather than native species by modifying the plant-soil feedback (PSF)., Methods: We conducted a two-phase plant-soil feedback experiment using the native Prosopis cineraria and the invasive Prosopis juliflora in Oman. Firstly, we conditioned the soil by planting seedlings of native species, invasive species, native and invasive species "mixed", and unconditioned soil served as a control. Secondly, we tested the feedback of these four conditioned soil on the two species separately by measuring the productivity (total biomass) and the performance in the form of plant functional traits (plant height, specific leaf area (SLA), leaf nitrogen content (Nmass), leaf carbon content (Cmass) and specific root length (SRL) of native and invasive species as well as the nutrient availability in soil (soil organic carbon (SOC) and soil total nitrogen (STN))., Results and Discussion: We found that the native species produced more biomass, best performance, and higher SOC and STN when grown in soil conditioned by native species, additionally, it gave lower biomass, reduced performance, and lower SOC and STN when grown in the soil conditioned by invasive and mixed species. These results suggest negative PSF for native species and positive PSF for invasive species in the soil conditioned by invasive species, which can be considered as red flag concerning the restoration of P. cineraria as an important native species in Oman, as such positive PSF of the invasive species P. juliflora will inhibit the regeneration of P. cineraria ., 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 © 2024 Ali, Al-Wahaibi and Shahid.)

Personalized medicine in cancer treatment aims to treat each individual's cancer tumor uniquely based on the genetic sequence of the cancer patient and is a much more effective approach compared to traditional methods which involve treating each type of cancer in the same, generic manner. However, personalized treatment requires the classification of cancer-related genes once profiled, which is a highly labor-intensive and time-consuming task for pathologists making the adoption of personalized medicine a slow progress worldwide. In this paper, we propose an intelligent multi-class classifier system that uses a combination of Natural Language Processing (NLP) techniques and Machine Learning algorithms to automatically classify clinically actionable genetic mutations using evidence from text-based medical literature. The training data set for the classifier was obtained from the Memorial Sloan Kettering Cancer Center and the Random Forest algorithm was applied with TF-IDF for feature extraction and truncated SVD for dimensionality reduction. The results show that the proposed model outperforms the previous research in terms of accuracy and precision scores, giving an accuracy score of approximately 82%. The system has the potential to revolutionize cancer treatment and lead to significant improvements in cancer therapy., 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 © 2024 Shahzad, Rafi, Alhalabi, Minaz Ali, Anwar, Jamal, Barket Ali and Alqurashi.)

Production of color-tunable emission via simple method for upcoming displays and lighting technologies, and their exceptional luminescence provide considerable potential in sensing application. As environmental pollution and diseases brought by cadmium have always been global issues, therefore, it is imperative to develop an inexpensive, quick, easy, and selective approach for detecting trace cadmium. Herein, we describe the preperation of ZnO/carbon quantum dots (ZnO/CQDs) nanocomposite that emits strongly in the yellow-orange zone with the chromaticity coordinates (0.51, 0.47) and a high color purity (CP) value of 94.3%. The as-produced ZnO/CQDs are used as a fluorescence sensor for Cd 2+ via quenching mechanism due to competitive coordination between ZnO/CQDs and Cd 2+ with the limit of detection (LOD) of 0.14 μM. Additionally, the suggested method can successfully detect Cd 2+ in water samples, demonstrating the feasibility and potential uses of the sensing platform. This study may pave the way for the development of environmentally safe, high-performing, and inexpensive color-tunable phosphor for white LEDs and sensing applications., 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.)

Cinchona alkaloid-derived sulfonamides and ester dimers containing chiral hyperbranched polymers have been successfully synthesized and applied as catalysts in asymmetric reactions. Several hyperbranched polymers derived from cinchona alkaloids, incorporating sulfonamides and esters, were synthesized through Mizoroki-Heck coupling polymerization. These polymers were subsequently applied in enantioselective Michael addition reactions. As the prepared polymers are not soluble in frequently used organic solvents, they act as efficient catalysts in the enantioselective reaction of β-ketoesters to nitroolefins, achieving up to 99% enantioselectivity with good yields. The insoluble property allows them to better satisfy "green chemistry" requirements and be used several times without losing the enantioselectivity., Competing Interests: Conflicts of interest: The authors declare no conflict of interest., (© TÜBİTAK.)

The role of neoadjuvant chemotherapy (NACT) in eyelid and orbital malignancies is not well defined. It has been tried with good success in cases of eyelid sebaceous gland carcinoma but there is very limited literature on its role in cases of ocular surface squamous neoplasia. A 54-year-old man presented with gradually increasing swelling of the right upper eyelid for the past 2 years. On examination, a large friable papillary mass was found covering the entire conjunctival surface (T3N0M0). Incisional biopsy from the mass was suggestive of papillary squamous cell carcinoma. There was no lymph node or distant metastasis as confirmed by whole-body positron emission tomography-CT scan. A trial of NACT (3 cycles of paclitaxel and cisplatin) was given and the mass shrunk in size considerably making it amenable to surgical resection. The conjunctival surface healed completely and there was no recurrence at 1 year of follow up. NACT can be tried in unresectable large ocular surface neoplasia to make the tumor more amenable to surgical resection., Competing Interests: The authors have no financial or conflicts of interest to disclose., (Copyright © 2023 The American Society of Ophthalmic Plastic and Reconstructive Surgery, Inc.)

Zinc oxide nanoparticles (ZnO NPs) have involved a lot of consideration owing to their distinctive features. The ZnO NPs can be described as particularly synthesized mineral salts via nanotechnology, varying in size from 1 to 100 nm, while zinc oxide (ZnO), it is an inorganic substrate of zinc (Zn). The Zn is a critical trace element necessary for various biological and physiological processes in the body. Studies have revealed ZnO NPs' efficient immuno-modulatory, growth-promoting, and antimicrobial properties in poultry birds. They offer increased bioavailability as compared to their traditional sources, producing better results in terms of productivity and welfare and consequently reducing ecological harm in the poultry sector. However, they have also been reported for their toxicological effects, which are size, shape, concentration, and exposure route dependent. The investigations done so far have yielded inconsistent results, therefore, a lot of additional studies and research are required to clarify the harmful consequences of ZnO NPs and to bring them to a logical end. This review explores an overview of efficient possible role of ZnO NPs, while comparing them with other nutritional Zn sources, in the poultry industry, primarily as dietary supplements that effect the growth, health, and performance of the birds. In addition to the anti-bacterial mechanisms of ZnO NPs and their promising role as antifungal, and anti-colloidal agent, this paper also covers the toxicological mechanisms of ZnO NPs and their consequent toxicological hazards to vital organs and the reproductive system of poultry birds., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Cardiovascular diseases (CVDs) continue to exert a substantial global influence in specific areas due to population growth, aging, microbiota, and genetic/environmental factors. Drinking water has a strong impact on the health of an individual. Further, emerging evidence has highlighted the therapeutic potential and benefits of Zamzam water (Zam)., Objective: We investigated the influence of Zam on doxorubicin-induced cardiac toxicity, elucidating its consequential effects on GUT microbiota dysbiosis and hepatic and renal functions., Methods: Male rats were categorized into four groups: Group 1 as Normal control (NC), Group 2 as Zamzam control (ZC), Group 3 Disease control (DC) and Group 4 as Therapeutic control (DZ) treated with Zam against doxorubicin-induced disease at a dose of 1mg/kg boy weight) intraperitoneally (i.p)., Results: Significant dysbiosis in the composition of GM was observed in the DC group along with a significant decrease (p < 0.05) in serum levels of Zinc, interleukin-10 (IL-10), IL-6 and Angiotensin II (Ang II), while C-reactive protein (CRP), fibrinogen, and CKMB increased significantly (restoration of Zinc ions (0.72 ± 0.07 mcg/mL) compared to NC. Treatment with Zamzam exhibited a marked abundance of 18-times to 72% in Romboutsia, a genus of firmicutes, along with lowering of Proteobacteria in DZ followed by significant restoration of Zinc ions (0.72 ± 0.07 mcg/mL), significant (p ˂ 0.05) reduction in CRP (7.22 ± 0.39 mg/dL), CKMB (118.8 ± 1.02 U/L) and Fibrinogen (3.18 ± 0.16 mg/dL), significant (p < 0.05) increase in IL-10 (7.22 ± 0.84 pg/mL) and IL-6 (7.18 ± 0.40 pg/ml), restoration of Ang II (18.62 ± 0.50 nmol/mL/min), marked increase in renin with normal myocyte architecture and tissue orientation of kidney, and restoration of histological architecture of hepatocyte., Conclusion: Zam treatment mitigated cardiac toxicity risk through the modulation of GUT microbiota and the renin-angiotensin system and tissue histology effectively., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Three new species Buellia darelensis, B. densitheca, B. kashmirensis and two new records B. elegans and B. taishanensis are added to the lichen biota of Pakistan. Buellia darelensis and B. kashmirensis share the same habitats found on the rock while B. densitheca colonized on bark of Pinus hardwoods in the Himalayan forest, Pakistan. Morphological, chemical, and phylogenetic analyses were carried out to elucidate the placement of these species and to support the delimitation of the new taxa. Detailed descriptions and figures for the species are given, and a key to all known buellioid species from Pakistan is provided. RESEARCH HIGHLIGHTS: During recent explorations of lichens from different regions of Pakistan, we observed specimens that could not be readily assigned to any known species. A phylogenetic analysis of the internal transcribed spacer nrDNA region confirms their position within the genus Buellia, and morphological data showed distinctiveness of three species from other known species of the genus. We therefore describe these specimens as new species to science, and two species are as new records for the country. Pakistan exhibits a large altitudinal variation, with climatic conditions and a diverse vegetation that supports a diverse and conspicuous lichen biota. The nature reserves have abundant biological resources, and it is expected that more new species of lichen may be discovered in the future., (© 2023 Wiley Periodicals LLC.)

Nurses, often considered the backbone of global health services, are disproportionately vulnerable to COVID-19 due to their front-line roles. They conduct essential patient tests, including blood pressure, temperature, and complete blood counts. The pandemic-induced loss of nursing staff has resulted in critical shortages. To address this, robotic solutions offer promising avenues. To solve this problem, we developed an ensemble deep learning (DL) model that uses seven different models to detect patients. Detected images are then used as input for the soft robot, which performs basic assessment tests. In this study, we introduce a deep learning-based approach for nursing soft robots, and propose a novel deep learning model named Deep Ensemble of Adaptive Architectures. Our method is twofold: firstly, an ensemble deep learning technique detects COVID-19 patients; secondly, a soft robot performs basic assessment tests on the identified patients. We evaluate the performance of various deep learning-based object detectors for patient detection, examining implementations of You Only Look Once (YOLO), Single Shot MultiBox Detector (SSD), Region-Based Convolutional Neural Network (RCNN), and Region-Based Fully Convolutional Network (R-FCN) on a proprietary dataset comprising 32,668 hospital surveillance images. Our results indicate that while YOLO and VGG facilitate rapid detection, Faster-RCNN (Inception ResNet-v2) and our proposed Ensemble-DL achieve the highest accuracy. Ensemble-DL offers accurate results in a reasonable timeframe, making it apt for patient detection on embedded platforms. Through real-world experiments, our method outperforms baseline approaches (including Faster-RCNN, R-FCN variants, CNN+LSTM, etc.) in terms of both precision and recall. Achieving an impressive accuracy of 98.32%, our deep learning-based model for nursing soft robots presents a significant advancement in the identification and assessment of COVID-19 patients, ultimately enhancing healthcare efficiency and patient care., 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.)

Purpose: Ototoxicity is one of the major adverse effects of cisplatin therapy which restrict its clinical application. Alpha-lipoic acid administration may mitigate cisplatin-induced ototoxicity. In the present study, we reviewed the protective potentials of alpha-lipoic acid against the cisplatin-mediated ototoxic adverse effects., Methods: Based on the PRISMA guideline, we performed a systematic search for the identification of all relevant studies in various electronic databases up to June 2022. According to the inclusion and exclusion criteria, the obtained articles (n=59) were screened and 13 eligible articles were finally included in the present study., Results: The findings of in-vitro experiments showed that cisplatin treatment significantly reduced the auditory cell viability in comparison with the control group; nevertheless, the alpha-lipoic acid co-administration protected the cells against the reduction of cell viability induced by cisplatin treatment. Moreover, the in-vivo results of the auditory brainstem response (ABR) and distortion product otoacoustic emission (DPOAE) tests revealed a decrease in DPOAE and an increase in ABR threshold of cisplatin-injected animals; however, it was shown that alpha-lipoic acid co-treatment had an opposite pattern on the evaluated parameters. Other findings demonstrated that cisplatin treatment could significantly induce the biochemical and histopathological alterations in inner ear cells/tissue; in contrast, alpha-lipoic acid co-treatment ameliorated the cisplatin-mediated biochemical and histological changes., Conclusion: The findings of audiometry, biochemical parameters, and histological evaluation showed that alpha-lipoic acid co-administration alleviates the cisplatin-induced ototoxicity. The protective role of alpha-lipoic acid against the cisplatin-induced ototoxicity can be due to different mechanisms of anti-oxidant, anti-apoptotic, anti-inflammatory activities, and regulation of cell cycle progression., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Drug repurposing is an emerging field in drug development that has provided many successful drugs. In the current study, paracetamol, a known antipyretic and analgesic agent, was chemically modified to generate paracetamol derivatives as anticancer and anticyclooxygenase-2 (COX-2) agents. Compound 11 bearing a fluoro group was the best cytotoxic candidate with half-maximal inhibitory concentration (IC 50 ) values ranging from 1.51 to 6.31 μM and anti-COX-2 activity with IC 50  = 0.29 μM, compared to the standard drugs, doxorubicin and celecoxib. The cell cycle and apoptosis studies revealed that compound 11 possesses the ability to induce cell cycle arrest in the S phase and apoptosis in colon Huh-7 cells. These results were strongly supported by docking studies, which showed strong interactions with the amino acids of the COX-2 protein, and in silico pharmacokinetic predictions were found to be favorable for these newly synthesized paracetamol derivatives. It can be concluded that compound 11 could block cell growth and proliferation by inhibiting the COX-2 enzyme in cancer therapy., (© 2023 Deutsche Pharmazeutische Gesellschaft.)

Acemannan, the main polysaccharide in Aloe vera, is a -(1, 4)-acetylated polymannose. According to numerous research findings, acemannan is a viable alternative for the treatment of pathological disorders. Streptozotocin (STZ, 60 mg/kg) administered intraperitoneally caused type 2 diabetes in rats. The current study sought to determine the anti-diabetic efficacy of acemannan (25 and 50 mg/kg) in STZ-injected rats. Different biochemical parameters including HbA1C, glucose and serum insulin, lipid profile, inflammatory markers, antioxidant, oxidative balance, liver function test, glycogen and creatinine, and caspase-3 were evaluated. In addition, a molecular docking study was performed to estimate acemannan's binding affinity to inflammatory markers. Acemannan may be a potent anti-diabetic agent for the treatment of diabetic patients, which will aid in future research into alternative diabetes medications., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This paper addresses the problem of feature encoding for gait analysis using multimodal time series sensory data. In recent years, the dramatic increase in the use of numerous sensors, e.g., inertial measurement unit (IMU), in our daily wearable devices has gained the interest of the research community to collect kinematic and kinetic data to analyze the gait. The most crucial step for gait analysis is to find the set of appropriate features from continuous time series data to accurately represent human locomotion. This paper presents a systematic assessment of numerous feature extraction techniques. In particular, three different feature encoding techniques are presented to encode multimodal time series sensory data. In the first technique, we utilized eighteen different handcrafted features which are extracted directly from the raw sensory data. The second technique follows the Bag-of-Visual-Words model; the raw sensory data are encoded using a pre-computed codebook and a locality-constrained linear encoding (LLC)-based feature encoding technique. We evaluated two different machine learning algorithms to assess the effectiveness of the proposed features in the encoding of raw sensory data. In the third feature encoding technique, we proposed two end-to-end deep learning models to automatically extract the features from raw sensory data. A thorough experimental evaluation is conducted on four large sensory datasets and their outcomes are compared. A comparison of the recognition results with current state-of-the-art methods demonstrates the computational efficiency and high efficacy of the proposed feature encoding method. The robustness of the proposed feature encoding technique is also evaluated to recognize human daily activities. Additionally, this paper also presents a new dataset consisting of the gait patterns of 42 individuals, gathered using IMU sensors.

Biochar production is an effective approach to managing abundant agricultural wastes. Pruning wastes from trimming the branches of trees such as carambola and mango, as well as coconut shells, are among the agricultural wastes that have reutilisation potential, which would simultaneously reduce the space required for disposal. In this study, the potential use of these wastes by converting them into biochar was investigated. The data presented in this study highlight the design of a pyrolysis system for a low-temperature slow pyrolysis process, as well as the characterisation data of the biochar produced using this system. The data collected included the elemental composition, porosity, as well as surface and adsorption characteristics of the biochar. These data indicate that the biochar produced had certain qualities that would enable its use for specific agricultural and industrial purposes. Meanwhile, the design indicated that it could facilitate small farms with specific outputs. In brief, these data can be used as references for developing a small-scale system for agricultural waste management using different types of crops., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (© 2024 The Authors. Published by Elsevier Inc.)

Introduction: Iron deficiency anemia is the most common type of anemia according to the World Health Organization. Females are more likely to be affected than males. There are several factors causing iron deficiency anemia, such as increased loss of iron, decreased intake of iron, and increased utilization of iron. There are limited research studies evaluating the risk factors that cause anemia among female medical students in Saudi Arabia. For this, the study aimed to identify the prevalence of undiagnosed iron deficiency anemia (IDA) among young female university students and to identify if there is any correlation between IDA and several factors including dietary habits, psychological stress, anxiety status, and body mass index., Materials and Methods: A cross-sectional observational study was performed between October 2022 and December 2022 with a sample of 100 healthy female students aged between 19 and 23 years, who were studying at the medical colleges of Umm Al-Qura University, Saudi Arabia. Blood samples were collected to perform complete blood count and iron profile tests. Also, a survey was done to find correlation between iron deficiency anemia and dietary intake, drinks, stress, anxiety, and body mass index (BMI). Independent t-test or Mann-Whitney U test were used to compare values for non-anemic with anemic participants, and linear regression tests were used to analyze differences between non-anemic and anemic participants' dietary intake factors and stress and anxiety scores. The level of significance was set at p<0.05., Results: The findings represent an overall prevalence of iron deficiency anemia in female medical students based on the lab finding results. Thus, students were divided into two following groups: anemic (13%) with hemoglobin (Hb) concentration <12 g/dL and non-anemic (84%) with Hb concentration ≥12 g/dL. When comparing the two groups, results showed significant differences in the majority of RBC indices (hematocrit {HCT}, mean corpuscular volume {MCV}, mean corpuscular hemoglobin {MCH}, red cell distribution width {RDW}) and iron profiles, p-value was <0.05. On evaluation of the different types of food consumption, the mean iron intake was around 7 mg/day, and in 65% of the participants, it was below the estimated average requirement (EAR) of iron (8.1 mg/dL). The perceived stress scale (PSS) shows that 63% of the participants experienced moderate stress and 58% reported severe anxiety by the generalized anxiety disorder (GAD) scale. In multiple linear regression, iron was positively associated with hemoglobin concentrations, whereas stress scores were negatively associated with hemoglobin concentrations., Conclusion: There is a relatively low prevalence of anemia and most of it was found of the microcytic type, indicating that this condition is a common health issue among local female college students. There was no independent association between stress or anxiety and hemoglobin levels., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Almasmoum et al.)

Alternanthera yellow vein virus (AlYVV), a monopartite begomovirus , has been identified infecting a diverse range of crops and native plants in Pakistan, India, and China. However, distinctive yellow vein symptoms, characteristic of begomovirus infection, were observed on the Ageratum conyzoides weed in Oman, prompting a thorough genomic characterization in this study. The results unveiled a complete genome sequence of 2745 base pairs and an associated betasatellite spanning 1345 base pairs. In addition, Sequence Demarcation Tool analyses indicated the highest nucleotide identity of 92.8% with a previously reported AlYVV-[IN&#95;abalpur&#95;A&#95;17:LC316182] strain, whereas the betasatellite exhibited a 99.8% nucleotide identity with isolates of tomato leaf curl betasatellite. Thus, our findings propose a novel AlYVV Oman virus (AlYVV-OM) variant, emphasizing the need for additional epidemiological surveillance to understand its prevalence and significance in Oman and the broader region. To effectively manage the spread of AlYVV-OM and minimize its potential harm to (agro)ecosystems, future research should focus on elucidating the genetic diversity of AlYVV-OM and its interactions with other begomoviruses.

Soil salinity is one of the major limiting factors in plant growth regulation. Salinity-tolerant endophytic bacteria (STEB) can be used to alleviate the negative effects of salinity and promote plant growth. In this study, thirteen endophytic bacteria were isolated from mungbean roots and tested for NaCl salt-tolerance up to 4%. Six bacterial isolates, TMB2, TMB3, TMB5, TMB6, TMB7 and TMB9, demonstrated the ability to tolerate salt. Plant growth-promoting properties such as phosphate solubilization, indole-3-acetic acid (IAA) production, nitrogen fixation, zinc solubilization, biofilm formation and hydrolytic enzyme production were tested in vitro under saline conditions. Eight bacterial isolates indicated phosphate solubilization potential ranging from 5.8-17.7 μg mL -1 , wherein TMB6 was found most efficient. Ten bacterial isolates exhibited IAA production ranging from 0.3-2.1 μg mL -1 , where TMB7 indicated the highest potential. All the bacterial isolates except TMB13 exhibited nitrogenase activity. Three isolates, TMB6, TMB7 and TMB9, were able to solubilize zinc on tris-minimal media. All isolates were capable of forming biofilm except TMB12 and TMB13. Only TMB2, TMB6 and TMB7 exhibited cellulase activity, while TMB2 and TMB7 exhibited pectinase production. Based on in vitro testing, six efficient STEB were selected and subjected to the further studies. 16S rRNA gene sequencing of efficient STEB revealed the maximum similarity between TMB2 and Rhizobium pusense , TMB3 and Agrobacterium leguminum , TMB5 and Achromobacter denitrificans , TMB6 and Pseudomonas extremorientalis , TMB7 and Bradyrhizobium japonicum and TMB9 and Serratia quinivorans . This is the first international report on the existence of A. leguminum , A. denitrificans , P. extremorientalis and S. quinivorans inside the roots of mungbean. Under controlled-conditions, inoculation of P. extremorientalis TMB6, B. japonicum TMB7 and S. quinivorans TMB9 exhibited maximum potential to increase plant growth parameters; specifically plant dry weight was increased by up to 52%, 61% and 45%, respectively. Inoculation of B. japonicum TMB7 displayed the highest potential to increase plant proline, glycine betaine and total soluble proteins contents by 77%, 78% and 64%, respectively, compared to control under saline conditions. It is suggested that the efficient STEB could be used as biofertilizers for mungbean crop productivity under saline conditions after field-testing., 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 Zahra, Tariq, Abdullah, Zafar, Yasmeen, Shahid, Zaki and Ali.)

Orphan genes (OGs) are protein-coding genes without a significant sequence similarity in closely related species. Despite their functional importance, very little is known about the underlying molecular mechanisms by which OGs participate in diverse biological processes. Here, we discuss the evolutionary mechanisms of OGs' emergence with relevance to species-specific adaptations. We also provide a mechanistic view of the involvement of OGs in multiple processes, including growth, development, reproduction, and carbon-metabolism-mediated immunity. We highlight the interconnection between OGs and the sucrose nonfermenting 1 (SNF1)-related protein kinases (SnRKs)-target of rapamycin (TOR) signaling axis for phytohormone signaling, nutrient metabolism, and stress responses. Finally, we propose a high-throughput pipeline for OGs' interspecies and intraspecies gene transfer through a transgenic approach for future biotechnological advances., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Antibiotics are gradually becoming less effective against bacteria worldwide, and this issue is of particular concern in economically-developing nations like Pakistan. We undertook a scoping review in order to review the literature on antimicrobial use, prescribing, dispensing and the challenges associated with antimicrobial resistance in primary care (PC) settings in Pakistan. Furthermore, this review aims to identify potential solutions to promote appropriate use of antimicrobials in Pakistan. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) checklist, a comprehensive scoping review was conducted to review the literature of antimicrobials used, prescribed and dispensed in PC settings in Pakistan. Google Scholar and Pub-Med were searched for the period 2000-2023. Papers were analyzed on the basis of eligibility i.e., included antimicrobial use, prescribing and dispensing practices by general population at homes, by prescribers in outpatient departments of hospitals and by pharmacists/dispensers in community pharmacies, respectively. Two researchers analyzed the articles thoroughly and disagreements were resolved through discussion with a third reviewer. Both quantitative and qualitative research studies were eligible for inclusion. Additionally, the selected papers were grouped into different themes. We identified 4070 papers out of which 46 studies satisfied our eligibility criteria. The findings revealed limited understanding of antimicrobial resistance (AMR) by physicians and community pharmacists along with inappropriate practices in prescribing and dispensing antibiotics. Moreover, a notable prevalence of self-medication with antibiotics was observed among the general population, underscoring a lack of awareness and knowledge concerning proper antibiotic usage. Given the clinical and public health implications of AMR, Pakistan must prioritize its policies in PC settings. Healthcare professionals (HCPs) need to reduce inappropriate antibiotic prescribing and dispensing, improve their understanding of the AWaRe (access, watch and reserve antibiotics) classification and guidance, monitor current usage and resistance trends, as well as implement antimicrobial stewardship (ASP) activities starting in targeted locations., Competing Interests: Declaration of Competing Interest The authors confirm 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 The Authors. Published by Elsevier Ltd.. All rights reserved.)

A 69-year-old female presented with complaints of persistent watering in the left eye for the past 8 years. She underwent a left external dacryocystorhinostomy (DCR) 8 years ago. On examination, left lacrimal passage irrigation showed regurgitation of fluid from opposite punctum. She underwent a revision external DCR with bicanalicular intubation and a portion of fibrosed sac was sent for histopathological examination (HPE). HPE showed a Microfilarial worm with surrounding granulomatous inflammation. Polymerase chain reaction (PCR) on the DNA extracted from the specimen identified the species to be Dirofilaria repens. Dirofilariasis is an accidental zoonotic infection in humans. Due to its migration, the worm can affect ocular and periocular structures. There are two case reports of perilacrimal dirofilariasis. This is the first case to report a filarial worm in the lacrimal sac causing chronic inflammation which probably led to failure of DCR. Treatment of choice is the complete eradication of the worm. PCR aids in the identification of species.

Background: Blood component transfusions are a common and often necessary medical practice during the epidemics of dengue. Transfusions are required for patients when they developed severe dengue fever or thrombocytopenia of 10×10 9 /L or less. This study therefore investigated the risk factors, performance and effectiveness of eight different machine-learning algorithms to predict blood component transfusion requirements in confirmed dengue cases admitted to hospital. The objective was to study the risk factors that can help to predict blood component transfusion needs., Methods: Eight predictive models were developed based on retrospective data from a private group of hospitals in India. A python package SHAP (SHapley Additive exPlanations) was used to explain the output of the "XGBoost" model., Results: Sixteen vital variables were finally selected as having the most significant effects on blood component transfusion prediction. The XGBoost model presented significantly better predictive performance (area under the curve: 0.793; 95 % confidence interval: 0.699-0.795) than the other models., Conclusion: Predictive modelling techniques can be utilized to streamline blood component preparation procedures and can help in the triage of high-risk patients and readiness of caregivers to provide blood component transfusions when required. This study demonstrates the potential of multilayer algorithms to reasonably predict any blood component transfusion needs which may help healthcare providers make more informed decisions regarding patient care., Competing Interests: Conflicts of interest The authors declare that they have no conflicts of interest., (Copyright © 2023 Associação Brasileira de Hematologia, Hemoterapia e Terapia Celular. Published by Elsevier España, S.L.U. All rights reserved.)

Flaxseed contains huge quantities of anti-nutritional factors (ANFs), which reduce the performance of livestock. Three different protease and multi-carbohydrase enzymes were included in wheat-flaxseed diets (WFD) and corn-flaxseed diets (CFD) to compare their effects on performance, egg n-3 deposition, and fatty acid transporter genes in laying hens. A total of 540, twenty-week-old, Nongda-3 laying hens (DW brown × Hy-line white) were randomly assigned to six dietary groups, including 10% WFD or 10% CFD plus (i) supplemental enzyme A (alkaline protease 40,000 and neutral protease 10,000 (U/g)), (ii) enzyme B (alkaline protease 40,000, neutral protease 10,000, and cellulase 4000 (U/g)), or iii) enzyme C (neutral protease 10,000, xylanase 35,000, β-mannanase 1500, β-glucanase 2000, cellulose 500, amylase 100, and pectinase 10,000 (U/g)). An interaction ( p < 0.05) was found for egg mass, hen day of egg production, and feed conversion ratio on the 9-10th week of the experiment. The WFD with enzyme B was associated with the highest egg weight in the 9-10th week. The deposition of total n-3 was superior with WFD (468.22 mg/egg) compared to CFD (397.90 mg/egg), while addition of enzyme C (464.90 mg/egg) resulted in the deposition of more total n-3 compared to enzymes A and B (411.89 and 422.42 mg/egg). The WFD and enzyme C significantly ( p < 0.001) enhanced docosahexaenoic acid (DHA) and reduced the n-6:n-3 ratio in egg yolk compared to the CFD. The hepatic mRNA expression of liver fatty acid binding protein (L-FABP) ( p = 0.006), fatty acid desaturase 1 (FADS-1) ( p < 0.001), elongase-2 (ELOV-2) ( p < 0.001), fatty acid transport protein-1 (FATP1) ( p < 0.001), and the intestinal mRNA expression of FATP and FABP genes were increased with WFD compared to CFD. In conclusion, WFD with enzyme C is favorable for optimal performance, results in the deposition of more n-3 and DHA, and increases the expression of fatty acid transporter genes, which helps in n-3 transport.

Prostate cancer (PCa) is a major global concern, particularly for men, emphasizing the urgency of early detection to reduce mortality. As the second leading cause of cancer-related male deaths worldwide, precise and efficient diagnostic methods are crucial. Due to high and multiresolution MRI in PCa, computer-aided diagnostic (CAD) methods have emerged to assist radiologists in identifying anomalies. However, the rapid advancement of medical technology has led to the adoption of deep learning methods. These techniques enhance diagnostic efficiency, reduce observer variability, and consistently outperform traditional approaches. Resource constraints that can distinguish whether a cancer is aggressive or not is a significant problem in PCa treatment. This study aims to identify PCa using MRI images by combining deep learning and transfer learning (TL). Researchers have explored numerous CNN-based Deep Learning methods for classifying MRI images related to PCa. In this study, we have developed an approach for the classification of PCa using transfer learning on a limited number of images to achieve high performance and help radiologists instantly identify PCa. The proposed methodology adopts the EfficientNet architecture, pre-trained on the ImageNet dataset, and incorporates three branches for feature extraction from different MRI sequences. The extracted features are then combined, significantly enhancing the model's ability to distinguish MRI images accurately. Our model demonstrated remarkable results in classifying prostate cancer, achieving an accuracy rate of 88.89%. Furthermore, comparative results indicate that our approach achieve higher accuracy than both traditional hand-crafted feature techniques and existing deep learning techniques in PCa classification. The proposed methodology can learn more distinctive features in prostate images and correctly identify cancer., 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 Mehmood, Abbasi, Aurangzeb, Majeed, Anwar and Alhussein.)

The inappropriate prescribing of antimicrobials increases antimicrobial resistance (AMR), which poses an appreciable threat to public health, increasing morbidity and mortality. Inappropriate antimicrobial prescribing includes their prescribing in patients hospitalized with COVID-19, despite limited evidence of bacterial infections or coinfections. Knowledge of current antimicrobial utilization in Saudi Arabia is currently limited. Consequently, the objective of this study was to document current antimicrobial prescribing patterns among Saudi hospitals during the COVID-19 pandemic. This study included patients with or without COVID-19 who were admitted to five hospitals in Makkah, Saudi Arabia. Data were gathered using the Global PPS methodology and analyzed using descriptive statistics. Out of 897 hospitalized patients, 518 were treated with antibiotics (57.7%), with an average of 1.9 antibiotics per patient. There were 174 culture reports collected, representing 36.5% of all cases. The most common indication for antibiotics use was community-acquired infections, accounting for 61.4% of all cases. 'Watch' antibiotics were the most commonly prescribed antibiotics, with the cephalosporins and carbapenems representing 38.7% of all antibiotics prescribed, followed by the penicillins (23.2%). Notably, Piperacillin/Tazobactam and Azithromycin were prescribed at relatively higher rates for COVID-19 patients. These findings highlight the need for continuous efforts to optimize the rational use of antibiotics through instigating appropriate antimicrobial stewardship programs in hospitals and, as a result, reduce AMR in the country.

Heavy metals are among the most ubiquitous environmental pollutants of recent decades. Copper is commonly used to control algal blooms or macrophyte and waste infestations, its ambient concentration has increased significantly, indicating possible environmental risk. To investigate the effects of copper exposure on bioaccumulation, antioxidant defense, immune response, and apoptosis in the Chinese Striped-necked Turtle Mauremys sinensis, three experimental groups, control (0.0 mg/L), Cu2 (2 mg/L) and Cu4 (4 mg/L) were designed, and sampled at 14 and 28 days. Results showed that copper accumulates in different organs depending on the concentration and exposure time, Liver > Kidney > Gut > Heart > Brain > Muscle and the time order was 28 days > 14 days. The liver enzymes AST, ALT, and ALP decreased when the turtles were exposed to copper stress, while the contents of bilirubin TBIL, DBIL, IBIL, and LDH showed a significant upward trend. Similarly, the mRNA expression level of acetylcholinesterase AChE in the brain was significantly downregulated upon copper exposure. An upward trend was noticed in the liver Metallothionein MT mRNA expression levels compared to the control group. The mRNA expression levels of antioxidant enzymes CAT, SOD, MnSOD, and GSH-PX1 in the liver increased initially and then significantly decreased. Furthermore, the relative mRNA expression levels of inflammatory cytokines IL-1β, IL-8, TNF-α, and IFN-γ involved in inflammatory response significantly upregulated. Copper significantly increased the hepatic mRNA transcription of heat shock proteins HSP70 and HSP90 at different exposure durations. In addition, the relative mRNA levels of caspase3, caspase8, and caspase9 related to the caspase-dependent apoptotic pathway significantly increased under copper stress. These results explain that copper toxicity causes bioaccumulation, promotes oxidative stress, obstructs immunity, and induces inflammation and apoptosis by altering their gene expression levels in M. sinensis., 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 Ali, Khan, Iqbal, Zhang, Ai, Shi, Ding and Hong.)

Background: Chest x-ray is commonly used for pulmonary abnormality screening. However, since the image characteristics of x-rays highly depend on the machine specifications, an artificial intelligence (AI) model developed for specific equipment usually fails when clinically applied to various machines. To overcome this problem, we propose an image manipulation pipeline., Methods: A total of 15,010 chest x-rays from systems with different generators/detectors were retrospectively collected from five institutions from May 2020 to February 2021. We developed an AI model to classify pulmonary abnormalities using x-rays from a single system. Then, we externally tested its performance on chest x-rays from various machine specifications. We compared the area under the receiver operating characteristics curve (AUC) of AI models developed using conventional image processing pipelines (histogram equalization [HE], contrast-limited histogram equalization [CLAHE], and unsharp masking [UM] with common data augmentations) with that of the proposed manipulation pipeline (XM-pipeline)., Results: The XM-pipeline model showed the highest performance for all the datasets of different machine specifications, such as chest x-rays acquired from a computed radiography system (n = 356, AUC 0.944 for XM-pipeline versus 0.917 for HE, 0.705 for CLAHE, 0.544 for UM, p [Formula: see text] 0.001, for all) and from a mobile x-ray generator (n = 204, AUC 0.949 for XM-pipeline versus 0.933 for HE, p = 0.042, 0.932 for CLAHE (p = 0.009), 0.925 for UM (p = 0.001)., Conclusions: Applying the XM-pipeline to AI training increased the diagnostic performance of the AI model on the chest x-rays of different machine configurations., Relevance Statement: The proposed training pipeline would successfully promote a wide application of the AI model for abnormality screening when chest x-rays are acquired using various x-ray machines., Key Points: • AI models developed using x-rays of a specific machine suffer from generalization. • We proposed a new image processing pipeline to address the generalization problem. • AI models were tested using multicenter external x-ray datasets of various machines. • AI with our pipeline achieved the highest diagnostic performance than conventional methods., (© 2023. The Author(s).)

Construction industry is indirectly the largest source of CO 2 emissions in the atmosphere, due to the use of cement in concrete. These emissions can be reduced by using industrial waste materials in place of cement. Self-Compacting Concrete (SCC) is a promising material to enhance the use of industrial wastes in concrete. However, there are very few methods available for accurate prediction of its strength, therefore, reliable models for estimating 28-day Compressive Strength (C-S) of SCC are developed in current study by using three Machine Learning (ML) algorithms including Multi Expression Programming (MEP), Extreme Gradient Boosting (XGB), and Random Forest (RF). The ML models were meticulously developed using a dataset of 231 points collected from internationally published literature considering seven most influential parameters including cement content, quantities of fly ash and silica fume, water content, coarse aggregate, fine aggregate, and superplasticizer dosage to predict C-S. The developed models were evaluated using different statistical errors including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), coefficient of determination ( R 2 ) etc. The results showed that the XGB model outperformed the MEP and RF model in terms of accuracy with a correlation R 2  = 0.998 compared to 0.923 for MEP and 0.986 for RF. Similar trend was observed for other error metrices. Thus, XGB is the most accurate model for estimating C-S of SCC. However, it is pertinent to mention here that it does not give its output in the form of an empirical equation like MEP model. The construction of these empirical models will help to efficiently estimate C-S of SCC for practical purposes., 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., (© 2023 The Authors.)

Priming-mediated stress tolerance in plants stimulates defense mechanisms and enables plants to cope with future stresses. Seed priming has been proven effective for tolerance against abiotic stresses; however, underlying genetic mechanisms are still unknown. We aimed to assess upland cotton genotypes and their transcriptional behaviors under salt priming and successive induced salt stress. We pre-selected 16 genotypes based on previous studies and performed morpho-physiological characterization, from which we selected three genotypes, representing different tolerance levels, for transcriptomic analysis. We subjected these genotypes to four different treatments: salt priming (P0), salt priming with salinity dose at 3-true-leaf stage (PD), salinity dose at 3-true-leaf stage without salt priming (0D), and control (CK). Although the three genotypes displayed distinct expression patterns, we identified common differentially expressed genes (DEGs) under PD enriched in pathways related to transferase activity, terpene synthase activity, lipid biosynthesis, and regulation of acquired resistance, indicating the beneficial role of salt priming in enhancing salt stress resistance. Moreover, the number of unique DEGs associated with G. hirsutum purpurascens was significantly higher compared to other genotypes. Coexpression network analysis identified 16 hub genes involved in cell wall biogenesis, glucan metabolic processes, and ribosomal RNA binding. Functional characterization of XTH6 (XYLOGLUCAN ENDOTRANSGLUCOSYLASE/HYDROLASE) using virus-induced gene silencing revealed that suppressing its expression improves plant growth under salt stress. Overall, findings provide insights into the regulation of candidate genes in response to salt stress and the beneficial effects of salt priming on enhancing defense responses in upland cotton., (© 2023 Scandinavian Plant Physiology Society.)

In the realm of machine vision, the convolutional neural network (CNN) is a frequently used and significant deep learning method. It is challenging to comprehend how predictions are formed since the inner workings of CNNs are sometimes seen as a black box. As a result, there has been an increase in interest among AI experts in creating AI systems that are easier to understand. Many strategies have shown promise in improving the interpretability of CNNs, including Class Activation Map (CAM), Grad-CAM, LIME, and other CAM-based approaches. These methods do, however, have certain drawbacks, such as architectural constraints or the requirement for gradient computations. We provide a simple framework termed Adaptive Learning based CAM (Adaptive-CAM) to take advantage of the connection between activation maps and network predictions. This framework includes temporarily masking particular feature maps. According to the Average Drop-Coherence-Complexity (ADCC) metrics, our method outperformed Score-CAM and another CAM-based activation map strategy in Residual Network-based models. With the exception of the VGG16 model, which witnessed a 1.94% decline in performance, the performance improvement spans from 3.78% to 7.72%. Additionally, Adaptive-CAM generates saliency maps that are on par with CAM-based methods and around 153 times superior to other CAM-based methods.

Since ancient times, dietary phytochemicals are known for their medicinal properties. They are broadly classified into polyphenols, terpenoids, alkaloids, phytosterols, and organosulfur compounds. Currently, there is considerable interest in their potential health effects against various diseases, including lung cancer. Lung cancer is the leading cause of cancer deaths with an average of five-year survival rate of lung cancer patients limited to just 14%. Identifying potential early molecular biomarkers of pre-malignant lung cancer cells may provide a strong basis to develop early cancer detection and interception methods. In this review, we will discuss molecular changes, including genetic alterations, inflammation, signal transduction pathways, redox imbalance, epigenetic and proteomic signatures associated with initiation and progression of lung carcinoma. We will also highlight molecular targets of phytochemicals during lung cancer development. These targets mainly consist of cellular signaling pathways, epigenetic regulators and metabolic reprogramming. With growing interest in natural products research, translation of these compounds into new cancer prevention approaches to medical care will be urgently needed. In this context, we will also discuss the overall pharmacokinetic challenges of phytochemicals in translating to humans. Lastly, we will discuss clinical trials of phytochemicals in lung cancer patients., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

To identify sets of genes that exhibit similar expression characteristics, co-expression networks were constructed from transcriptome datasets that were obtained from plant samples at various stages of growth and development or treated with diverse biotic, abiotic, and other environmental stresses. In addition, co-expression network analysis can provide deeper insights into gene regulation when combined with transcriptomics. The coordination and integration of all these complex networks to deduce gene regulation are major challenges for plant biologists. Python and R have emerged as major tools for managing complex scientific data over the past decade. In this study, we describe a reproducible protocol POTFUL (pant co-expression transcription factor regulators), implemented in Python 3, for integrating co-expression and transcription factor target protein networks to infer gene regulation.

Competing Interests: There are no conflicts of interest.

Background and Aims: Breast cancer is a multifactorial malignancy with different clinicopathological and molecular characteristics. It is the most frequent cancer in women in terms of both incidence and mortality. Matrix metallopeptidase 1 or MMP1 is a zinc-dependent endopeptidase associated with several physiological processes through the modification of the extracellular matrix and tumor microenvironment. However, previous results did not suggest any concluding remarks on the correlation between MMP1 gene polymorphisms and the risk of breast cancer., Methods: A comprehensive literature search was performed in PubMed database to retrieve relevant articles and extract data from suitable ones. The literature written only in English was selected for this review., Results: A total of 26 articles were included in the present narrative review. From the available studies, it is observed that MMP1 is upregulated in breast cancer tissues and found to be correlated with metastasis and invasion. The expression of MMP1 gene is mediated by numerous factors, including polymorphisms which act as a potential risk factor for the progression of breast cancer. To establish the correlation between genetic polymorphisms in MMP1 and the risk of breast cancer, several case-control studies, as well as genetic analyses, have been carried out in different ethnicities. The association of genetic polymorphisms in MMP1 with the risk and survival of breast cancer in different populations has been reviewed in this study. Moreover, the structural domain of MMP1 and the role of MMP1 in breast cancer metastasis and invasion are also discussed which will help to understand the potential impact of MMP1 as a genetic biomarker., Conclusions: This review provides an overview of the MMP1 gene polymorphisms in breast cancer. However, we recommend future studies concentrating on combined analysis of multiple SNPs, gene-gene interactions, and analysis of epigenetics, proteomics, and posttranscriptional modifications that will provide the best outcome., Competing Interests: Mohammad Safiqul Islam is an Editorial Board member of Health Science Reports and a co‐author of this article. To minimize bias, he was excluded from all editorial decision‐making related to the acceptance of this article for publication., (© 2023 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Background The diagnosis of acute appendicitis has remained difficult despite it being one of the most common surgical emergencies in the world. One of the most frequently used scoring systems is the Modified Alvarado Score (MAS). However, the MAS has been known to be less efficient in Asian populations. To overcome this issue, the Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA) score has been specifically developed to improve the diagnosis of acute appendicitis in Asian populations. This study aimed to evaluate the accuracy of the RIPASA score compared to the MAS for the diagnosis of acute appendicitis in a Southeast Asian population keeping histopathology as the gold standard. Methodology The study group comprised 150 patients. Data were collected from each patient using a simple proforma to ascertain both the MAS and the RIPASA score for each patient at the time of presentation. The patients then underwent open appendectomy and histopathology was used as the gold standard to determine the presence or absence of acute appendicitis in the excised specimens. Results The RIPASA score had a sensitivity and specificity of 89.83% and 59.38%, respectively, compared to 64.41% and 53.12%, respectively, for the MAS. Diagnostic accuracy was similarly higher for the RIPASA score at 83.33% versus 62.00% for the MAS. Conclusions The RIPASA score is superior to the MAS for the diagnosis of acute appendicitis. Using the RIPASA score instead of the MAS in Southeast Asian populations can lead to a more accurate and timely clinical diagnosis of patients with suspected acute appendicitis and help improve patient outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Mehbub et al.)

Due to global warming and climate change, the poultry industry is heavily impacted, especially the broiler industry, due to the sensitive immune system of broiler chickens. However, the continuous monitoring and controlling of the farm's environmental parameters can help to curtail the negative impacts of the environment on chickens' health, leading to increased meat production. This article presents smart solutions to such issues, which are practically implemented, and have low production and operational costs. In this article, an Internet of Things (IoT) based environmental parameters monitoring has been demonstrated for the poultry farmhouse. This system enables the collection and visualization of crucially sensed data automatically and reliably, and at a low cost to efficiently manage and operate a poultry farm. The proposed IoT-based remote monitoring system collects and visualizes environmental parameters, such as air temperature, relative humidity (RH), oxygen level (O 2 ), carbon dioxide (CO 2 ), carbon monoxide (CO), and ammonia (NH 3 ) gas concentrations. The wireless sensor nodes have been designed and deployed for efficient data collection of the essential environmental parameters that are key for monitoring and decision-making process. The hardware is implemented and deployed successfully at a site within the control shed of the poultry farmhouse. The results revealed important findings related to the environmental conditions within the poultry farm. The temperature inside the control sheds remained within the desired range throughout the monitoring period, with daily average values ranging from 32 °C to 34 °C. The RH showed slight variations monitoring period, ranging from 65% to 75%, with a daily average of 70%. The O 2 concentration exhibited an average value of 17% to 18.5% throughout the monitoring period. The CO 2 levels showed occasional increases, reaching a maximum value of 1,100 ppm. However, this value was below the maximum permissible level of 2,500 ppm, indicating that the ventilation system was effective in maintaining acceptable CO 2 levels within the control sheds. The NH 3 gas concentration remained consistently low throughout the duration, with an average value of 50 parts per million (ppm)., Competing Interests: Khursheed Aurangzeb is an Academic Editor for PeerJ., (© 2023 Lashari et al.)

In Saudi Arabia, the Ministry of Health (MoH) has implemented strict rules to ensure COVID-19 vaccination uptake by the general public. However, there is hesitancy about COVID-19 vaccination among parents for their children worldwide. We aimed to determine the concerns, behaviors, perceptions, and hesitancy of COVID-19 vaccination among parents for their children in Saudi Arabia. Parents of children aged 5-11 years were included in this cross-sectional study. A total of 1507 responses were obtained using the convenience sampling technique. The data were analyzed using SPSS version 25.0 by applying descriptive and inferential statistics. Of the parents who responded, 74.5% believed that the COVID-19 vaccination could affect the genes of children, and 72.8% believed that the COVID-19 vaccination could have a greater number of positive impacts on the overall health of children. In total, 87% of the parents were satisfied with the vaccination services and effective policies of the MoH, Saudi Arabia. This study concluded that there is a greater need to increase public awareness regarding the beneficial impact of COVID-19 vaccination on the overall health of children. Effective awareness campaigns are also required to provide empirical information to the public that COVID-19 vaccination for children is safe and effective.

The current systematic review presents COVID-19 vaccine hesitancy among parents for their children in Middle Eastern countries. Moreover, the vaccine acceptance rate of parents from the Middle East and the factors effecting the acceptance rate were reviewed and summarized. For this systematic review, basic electronic academic databases (Scopus, Science Direct, ProQuest, Web of Science and PubMed) were used for the search, along with a manual search on Google Scholar. This systematic review was conducted by following the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)" guidelines. Moreover, utilizing the framework of the PECO-S (Population Exposure Comparison Outcome Study design), various observational studies were recruited for this review. Out of 2123 studies, 25 studies meeting the inclusion criteria were included in the current review. All of the included studies were about parental vaccine hesitancy for COVID-19 in Middle Eastern countries and published during 2020-2022. Overall, 25 research papers comprising 10 different Middle Eastern countries with 33,558 parents were included. The average age of parents was 39.13 (range: 18-70) years, while the mean age of children was 7.95 (range: 0-18) years. The overall hesitancy rate was 44.2% with a SD of ± 19.7. The included studies presented enhanced COVID-19 vaccine hesitancy among parents in Middle Eastern countries. The lower vaccine acceptance rate among parents was mainly because of a fear of the potential side effects. Furthermore, the lack of information regarding vaccine safety and efficacy, the fear of unreported side effects and concerns about the authenticity of vaccine development and preparation were the predictors of parental COVID-19 vaccine hesitancy among Middle Eastern countries.

A facile and eco-friendly synthesis of PW 12 /TiO 2 @MgCO 3 hollow tubes (PW 12 ·∼· H 3 [PW 12 O 40 ] = polyoxometalate) using a soluble and reusable MgCO 3 ·3H 2 O micro-rods template was reported for the first time. The resultant hollow tubes were characterized by Fourier transform infrared spectroscopy (FT-IR), UV-visible spectroscopy, powder X-ray diffraction (PXRD), energy-dispersive X-ray spectroscopy (EDX), and scanning electron microscopy (SEM), which indicated that the [PW 12 O 40 ] 3- structure remained intact within the hollow tubes. Furthermore, the specific surface area (88.982 m 2 /g) and average pore size (2.6 nm) of the PW 12 /TiO 2 @MgCO 3 hollow tubes were calculated using the Brunauer-Emmett-Teller (BET) analysis. This study explored the catalytic performance of PW 12 /TiO 2 @MgCO 3 hollow tubes using a three-level Box-Behnken design (BBD), through which optimization curves were designed. The desulfurization of model fuel using hollow tubes was optimally performed when the catalyst dose, time, temperature, and oxidant/sulfur (O/S) were 20-80 gm, 80-120 min, 25-80 °C and 3-8 molar ratio, respectively. These results were further processed, and the experiments were replicated twenty-nine times using a model based on two quadratic polynomials to create a response surface methodology (RSM). This permits a mathematical correlation linking the desulfurization and experimental parameters. The optimal performance of reaction mixture was evaluated to be 80 mg for catalyst concentration, 25 °C of temperature, reaction time of 100 min, and 5.5 for oxidant/sulfur molar ratio from 20 mL of octane simulation oil containing 350 ppm dibenzothiophene (DBT). The predicted desulfurization rate of the model fuel under these optimal conditions was 95.3%. The correspondence between the experimental results and predicted values was verified based on regression analysis, with an R 2 value greater than 0.99. These hollow tubes could be used for their desulfurization properties ten times a row without significantly reducing catalytic activity., 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.)

Oil prices (OP) may play a significant role in determining inflation in any oil-importing economy and could have an asymmetrical effect as well. Thus, this paper aims to explore the asymmetric influence of OP, broad money supply (BMS), and domestic debt (DD) on the Consumer Price Index (CPI) in the oil-importing economy of Pakistan using the nonlinear autoregressive distributive lag (NARDL) methodology on an annual sample from 1980 to 2021. The long-run results show that increasing OP and BMS have a positive effect on CPI. Similarly, decreasing OP and BMS have a positive effect on CPI. So, increasing OP and BMS is raising price levels, and decreasing OP and BMS is reducing price levels. OP has a positive and symmetrical effect on CPI. However, the BMS has a positive but asymmetrical effect on CPI. Furthermore, the effect of decreasing BMS is found greater than increasing BMS. Moreover, the effect of DD on CPI is also found asymmetrical. The increasing DD has a positive effect, and decreasing DD has a negative effect on CPI. The most of short-run results follow the long-run results. However, energy usage shows a negative effect on CPI in the short run, which is insignificant in the long-run results. This study recommends controlling the money supply and oil prices to reduce consumer prices., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Teratomas are germ cell tumors occurring usually in gonadal organs. They are neoplasms composed of one or more of the three germ layers. Extragonadal teratomas are uncommonly reported in the literature. The liver is an extremely rare site for teratoma, constituting < 1% of all teratomas. The majority of the liver teratomas are found in the pediatric population with only a dozen cases reported in adults to the best of our knowledge. We present a case of a 27-year-old male with a history of abdominal pain of 5 months duration. CT scan revealed liver mass suggesting teratoma. The patient underwent cholecystectomy and segmental liver resection. Histopathology revealed mature cystic teratoma. Complete resection remains the best treatment option. Teratomas of the liver are extremely rare, constituting < 1% of all teratomas. An extensive review of the literature yielded < 50 cases of primary hepatic teratomas with only a dozen cases in adults and only two cases in males.

Purpose: To evaluate the efficacy of intermittent manual carotid compression (IMCC) in the management of low-flow carotid cavernous fistulae (CCF)., Materials and Methods: Patients diagnosed with low-flow CCF and treated with IMCC over a period of 13 years were retrospectively analyzed. Data analyzed included demographic details, clinical features, type of CCF, and response to therapy. Outcomes were categorized as complete cure, partial cure, and no cure or worsening. Patients with complete and partial cure were grouped as good outcome whereas those with no cure or worsening as poor outcome., Results: A total of 44 patients were advised IMCC for low-flow CCF, of whom five were lost to follow-up. Results of the remaining 39 patients were analyzed, of whom 21 (53.8%) were males. The mean age at presentation was 54.38 ± 14.54 years. The median duration between the onset of symptoms and presentation was 5.0 ± 4.10 months. The common presenting features were episcleral congestion and proptosis (89.7%), extraocular motility restriction (66.7%), and diplopia (48.7%). Most common CCF type was type D (34, 87.2%). All patients were advised to undergo IMCC. Good outcome was seen in 35 patients (89.7%, 95% CI: 80.2% to 99.2%), whereas poor outcome was seen in four (10.3%) patients. The mean duration of follow-up was 15.91 ± 21.87 months., Conclusion: The present study found a good outcome with IMCC in 89.7% cases of indirect low-flow CCF with no major complications. It should be considered the management of choice in patients who are systemically unfit or cannot afford endovascular embolization.

Despite global warming, renewable energy has gained much interest worldwide due to its ability to generate large-scale energy without emitting greenhouse gases. The availability and low cost of wind energy and its high efficiency and technological advancements make it one of the most promising renewable energy sources. Hence, capturing large amounts of wind energy is essential today. The large-scale integration of wind power sources must be evaluated and mitigated to develop a sustainable future power system. Wind energy research and the government are working together to overcome the potential barriers associated with its penetration into the power grid. This paper reviews the social, environmental, and cost-economic impacts of installing large-scale wind energy plants. A valuable review of wind energy technology and its challenges is also presented in this paper, including the effects of wind farms on nearby communities, generation uncertainty, power quality issues, angular and voltage stability, reactive power support, and fault ride-through capability. Besides, socioeconomic, environmental, and electricity market challenges due to the grid integration of wind power are also investigated. Finally, potential technical challenges to integrating large-scale wind energy into the power grid are reviewed regarding current research and their available mitigation techniques., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The aim of the study was to compare three moulting procedures and their effect on productive performance, egg quality, and antibody response of leghorn hens. For this, a total of 324 laying hens were distributed into three treatment groups having 12 replicates of 9 birds each according to completely randomized design. Treatments consisted of three moulting procedures based on feed and light restriction. The targeted weight at the end of moulting was 1450-1470 g. As soon as the moulting procedure is complete, the comparative analysis of post-moult productive performance (feed intake, egg production, egg weight, egg mass, feed per dozen eggs, feed per kg egg mass, livability), egg quality characteristics (egg weight, egg length and width, shape index, surface area, volume, albumen height, weight, Haugh unit score, yolk width, height, index, egg shell pore number, shell weight, thickness, breaking strength), and antibody response against Newcastle disease and avian influenza (H-9) were evaluated. Birds subjected to moulting procedure 3 (8 days fasting and gradual decrease in light) showed improvement in productive performance, egg geometry and quality traits, and antibody response against Newcastle disease virus. Birds experienced moulting procedure 1 (11 days fasting) had improved feed intake, egg production, and livability. However, birds moulted with procedure 2 (6 days fasting) revealed intermediate result in all the studied parameters. In conclusion, moulting through feed and light restriction with 8 days fasting and gradual reduction in light has potential to improve performance of leghorn hens., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Precise short-term load forecasting (STLF) plays a crucial role in the smooth operation of power systems, future capacity planning, unit commitment, and demand response. However, due to its non-stationary and its dependency on multiple cyclic and non-cyclic calendric features and non-linear highly correlated metrological features, an accurate load forecasting with already existing techniques is challenging. To overcome this challenge, a novel hybrid technique based on long short-term memory (LSTM) and a modified split-convolution (SC) neural network (LSTM-SC) is proposed for single-step and multi-step STLF. The concatenating order of LSTM and SC in the proposed hybrid network provides an excellent capability of extraction of sequence-dependent features and other hierarchical spatial features. The model is evaluated by the Pakistan National Grid load dataset recorded by the National Transmission and Dispatch Company (NTDC). The load data is pre-processed and multiple other correlated features are incorporated into the data for performance enhancement. For generalization capability, the performance of LSTM-SC is evaluated on publicly available datasets of American Electric Power (AEP) and Independent System Operator New England (ISO-NE). The effect of temperature, a highly correlated input feature, on load forecasting is investigated either by removing the temperature or adding a Gaussian random noise into it. The performance evaluation in terms of RMSE, MAE, and MAPE of the proposed model on the NTDC dataset are 500.98, 372.62, and 3.72% for multi-step while 322.90, 244.22, and 2.38% for single-step load forecasting. The result shows that the proposed method has less forecasting error, strong generalization capability, and satisfactory performance on multi-horizon., Competing Interests: Khursheed Aurangzeb is an Academic Editor for PeerJ., (© 2023 Ullah et al.)

Atrial fibrillation easily leads to stroke, cerebral infarction and other complications, which will seriously harm the life and health of patients. Traditional deep learning methods have weak anti-interference and generalization ability. Therefore, we propose a new-fashioned deep residual-dense network via bidirectional recurrent neural network (RNN) model for atrial fibrillation detection. The combination of one-dimensional dense residual network and bidirectional RNN for atrial fibrillation detection simplifies the tedious feature extraction steps, and constructs the end-to-end neural network to achieve atrial fibrillation detection through data feature learning. Meanwhile, the attention mechanism is utilized to fuse the different features and extract the high-value information. The accuracy of the experimental results is 97.72%, the sensitivity and specificity are 93.09% and 98.71%, respectively compared with other methods., (© 2023. Springer Nature Limited.)

Carbapenem resistance among Enterobacterales has become a global health concern. Clinical Escherichia coli isolates producing the metallo β-lactamase NDM have been isolated from two hospitals in Faisalabad, Pakistan. These E. coli strains were characterized by MALDI-TOF, PCR, antimicrobial susceptibility testing, XbaI and S1 nuclease pulsed-field gel electrophoresis (PFGE), conjugation assay, DNA hybridization, whole genome sequencing, bioinformatic analysis, and Galleria mellonella experiments. Thirty-four bla NDM producing E. coli strains were identified among 52 nonduplicate carbapenem-resistant strains. More than 90% of the isolates were found to be multidrug resistant by antimicrobial susceptibility testing. S1 PFGE confirmed the presence of bla NDM gene on plasmids ranging from 40 kbps to 250 kbps, and conjugation assays demonstrated transfer frequencies of bla NDM harboring plasmids ranging from 1.59 × 10 -1 to 6.46 × 10 -8 per donor. Whole genome sequencing analysis revealed bla NDM-5 as the prominent NDM subtype with the highest prevalence of bla OXA-1 , bla CTX-M-15 , aadA2 , aac(6')-Ib-cr , and tet(A ) associated resistant determinants. E. coli sequence types: ST405, ST361, and ST167 were prominent, and plasmid Inc types: FII, FIA, FIB, FIC, X3, R, and Y, were observed among all isolates. The genetic environment of bla NDM region on IncF plasmids included partial IS Aba125 , the bleomycin ble gene, and a class I integron. The virulence genes terC, traT, gad, fyuA, irp2, capU, and sitA were frequently observed, and G. mellonella experiments showed that virulence correlated with the number of virulence determinants. A strong infection control management in the hospital is necessary to check the emergence of carbapenem resistance in Gram-negative bacteria.IMPORTANCEWe describe a detailed analysis of highly resistant clinical E. coli isolates from two tertiary care centers in Pakistan including carbapenem resistance as well as common co-resistance mechanisms. South Asia has a huge problem with highly resistant E. coli . However, we find that though these isolates are very difficult to treat they are of low virulence. Thus the Western world has an increasing problem with virulent E. coli that are mostly of low antibiotic resistance, whereas, South Asia has an increasing problem with highly resistant E. coli that are of low virulence potential. These observations allow us to start to devise methodologies to limit both virulence and resistance and combat problems in developing nations as well as the Western world.