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The proliferation of fake news on social media platforms has become a significant concern, influencing public opinion, political decisions, and societal trust. While much research has focused on the technological and algorithmic factors behind the spread of misinformation, less attention has been given to the psychological drivers that contribute to the creation and dissemination of fake news. Cognitive biases, emotional appeals, and social identity motivations are believed to play a crucial role in shaping user behaviour on social media, yet there is limited systematic understanding of how these psychological factors intersect with online information sharing. Existing studies tend to focus on individual aspects of fake news consumption, such as susceptibility to misinformation or partisan biases, leaving a gap in understanding the broader psychological mechanisms behind both the creation and dissemination of fake news. This systematic review aims to fill this gap by synthesizing current research on the psychological factors that influence social media users' involvement in dissemination and creation of fake news. Twenty-three studies were identified from 2014 to 2024 following the PRISMA guidelines. We have identified five themes through critical review and synthesis of the literature which are personal factors, ignorance, social factors, biological process, and cognitive process. These themes help to explain the psychological factors contributing to the creation and dissemination of fake news among social media users. Based on the findings, it is evident that diverse psychological factors influence the dissemination and creation of fake news, which must be studied to design better strategies to minimize this issue., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Background: Immunotherapy has emerged as a standard treatment for deficient mismatch repair (dMMR) metastatic colorectal cancer (mCRC). Pembrolizumab became widely available as a first-line (1L) option in Australia following the Pharmaceutical Benefits Scheme (PBS) listing in August 2021. The uptake of new treatment options can be lengthy., Methods: The Treatment of Recurrent and Advanced Colorectal Cancer mCRC registry data at participating Australian sites was analysed from January 2015 (when MMR testing became routine). 1L treatment of dMMR cancers was compared with pre- and post-PBS funding., Results: Out of 2819 patients, 2344 (83%) had known MMR status. Of these, 162 (7%) were dMMR, which was associated with older age (median age 69 vs 63 years, P = 0.001), a right-side primary (68% vs 31%, P < 0.001) and a BRAF V600E mutation (49% vs 11%, P < 0.001). Prior to August 2021, 85 out of 117 (73%) patients with dMMR received 1L treatment: 63 out of 85 (74%) chemotherapy and 20 out of 85 (24%) immunotherapy. Following approval, 39 out of 45 (87%) received 1L treatment and 39 out of 39 (100%) pembrolizumab. Of the patients 75 years and older, a significantly higher proportion of patients were treated with any 1L therapy post-PBS listing (89% vs 60%, P = 0.036)., Conclusion: Previously reported associations of dMMR were observed. The higher-than-expected proportion of patients with dMMR is likely driven by the inclusion of older patients in this real-world study. Many patients were able to access immunotherapy prior to PBS listing, potentially through trials or access programs. Early uptake of pembrolizumab following PBS listing has been high, and this effective and well-tolerated option has increased the proportion of elderly patients receiving active therapy., (© 2024 Royal Australasian College of Physicians.)

Tenecteplase (TNK), as a thrombolytic treatment for acute ischemic stroke (AIS), has been found to be effective when used within 4.5 hours of symptom onset. However, the efficacy of TNK after 4.5 hours is not well established, especially in patients with large vessel occlusion and with no access to thrombectomy. In this article, we will discuss the results of the recently published TRACE-III trial. The study involved 516 patients with large vessel occlusion, either proximal middle cerebral artery or internal carotid artery, with salvageable brain tissue and no endovascular thrombectomy access. Key safety outcomes included symptomatic intracranial hemorrhage and death. TNK treatment resulted in a higher percentage of patients with a modified Rankin scale score of 0 or 1 at 90 days than standard medical treatment. Mortality at 90 days was 13.3% with TNK and 13.1% with standard medical treatment. The trial found that TNK treatment for Chinese patients with ischemic stroke resulted in less disability and similar survival compared to standard medical treatment. However, there was a higher incidence of symptomatic intracranial hemorrhage within 36 hours.

Introduction: Mixed hyperlipidemia represents a substantial public health issue and a considerable burden on healthcare systems. Although the introduction of statins and LDL-cholesterol lowering agents have significantly reduced the incidence of atherosclerotic cardiovascular diseases (ASCVD), a significant portion of the population continues to exhibit ASCVD progression due to elevated triglyceride-rich lipoprotein (TRL) levels. This persistent risk has catalyzed the development of novel pharmacological interventions targeting these lipoproteins., Areas Covered: Our special report commenced with a targeted PubMed search using keywords such as 'plozasiran,' 'zodasiran,' and terms related to APOC3 and ANGPTL3. As the review progressed, emergent research questions guided further searches, allowing for the inclusion of additional relevant articles to comprehensively illustrate the linkage between TRLs and cardiovascular disease, discuss the roles of APOC3, ANGPTL3, and the pharmaceutical agents that target these proteins, and provide a comparison on the ARCHES-2 and MUIR trials., Expert Opinion: The ARCHES-2 and MUIR trials demonstrated effective triglyceride reduction by these therapies, yet it is uncertain if this correlates with significant clinical benefits. Advances in antisense oligonucleotide technology, especially the GalNAc delivery platform, show promise for personalized lipid management, though challenges such as cost and safety concerns remain.

Boswellia serrata produces oleo gum resin, a rich source of essential oil (EO). EOs, produced as secondary metabolites by medicinal plants, are employed for medicinal and therapeutic purposes. The present study aimed to investigate the yield, chemical composition, antioxidant (AO), antimicrobial, and hemolytic activity of B. serrata EO and its fractions and sub-fractions (SFs). The EO was extracted using the superheated steam extraction (SHSE) method at 140°C. Short-path molecular vacuum distillation was used to separate the EO into fractions and SFs. Gas chromatography-mass spectrometry analysis showed α-pinene, α-thujene, trans verbenol, and linalool as major components of EO. The AO potential was evaluated using a 2,2-diphenyl-1-picrylhydrazyl assay, % inhibition in a linoleic acid assay, H 2 O 2 scavenging assay, and total AO content (TAOC) using a ferric reducing AO power assay. F2b SF exhibited the highest scavenging activity, with percentages of 95.77%, 96.20%, and 83.54%, respectively, whereas EO revealed the highest TAOC value of 115.94%. Antimicrobial activity was evaluated by disc diffusion, resazurin microtiter plate, and microdilution broth assays. F1c SF showed maximum antibacterial potential (high inhibition zone 17.65-38.28 mm and low minimum inhibitory concentration [MIC] 2.20-84.44 µg/mL). The EO showed the highest antifungal activity (high inhibition zone 12.58-25.81 mm and low MIC 35.18-225.17 µg/mL). Cytotoxicity was assessed by hemolytic assay, with the F1c SF showing the highest activity at 10.89%. It is concluded that SHSE is an effective technique for B. serrata EO extraction, and this EO can be utilized for various medicinal purposes., (© 2024 Institute of Food Technologists.)

Global grasslands were constantly being replaced and reclaimed for cropland, and such reclamations may profoundly affect ecological such as water cycles. However, the long-term effects of this conversion on evapotranspiration (ET) processes remain underexplored. To discern changes in ET from grassland to reclaimed cropland and among different crop rotations, a four-year study (2018-2021) was conducted using the eddy covariance system in a Hulunber grassland and a neighboring reclaimed cropland. The ET in reclaimed cropland (248 mm) was 49% higher than the grassland (166 mm) during the growing season (crop growth period), whereas the ET in the grassland (134 mm) exceeded that in the cropland (128 mm) by 6% in the non-growing season. The croplands experienced a 19% increase in precipitation, primarily due to artificial irrigation during the growing season. Meanwhile, the increase in ET in reclaimed cropland might also be influenced by changes in vegetation type and crop growth characteristics, as well as by rational tillage practices that increase the cover of vegetation and biomass. Notably, potato cultivation most closely matched the water balance of grasslands. In addition, irrigation directly increased soil water content (SWC), and that enhancing the sensitivity of ET to SWC. Overall, this study highlighted the importance of understanding ET variations due to grassland conversion to cropland and different crop rotations, emphasizing the role of irrigation and tillage practices., 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.)

Pistacia lentiscus L. is an aromatic plant containing a significant percentage of essential oil (EO) used in fragrance, pharmaceuticals, cosmetics, and the food industry. The purpose of this work is focused on the optimization of Pistacia lentiscus L. oleo gum resin EO yield extracted by superheated steam extraction (SHSE) by response surface methodology, including extraction parameters of particle size (0. 5 - 1 mm), temperature (140-180 °C) and time (90-150 min). The optimum conditions for Pistacia lentiscus L. EO extracted by SHSE were found to be (particle size: 0.75 mm, time: 120 min and temperature: 160 ℃) which produced the highest EO yield of 5.7%. A regression model was developed, demonstrating a robust quadratic correlation with an R 2 value of 0.9991, making it suitable for predictions. Furthermore, the yield of Pistacia lentiscus L. EO extracted by SHSE was compared with the conventional steam and hydro distillation techniques. The study revealed that SHSE yielded higher quantities of EO than other extraction methods. GC-MS analyzed the chemical composition of Pistacia lentiscus L. EO. The predominant compound of Pistacia lentiscus L. EO was determined to be α-pinene, while the other identified compounds include trans-verbenol, verbenol, cis-verbenone, camphene, β-myrcene, d-limonene, cymene, α-myrtenol, α-campholenal, α-copaene, and α-thujene, whose content differed according to different extraction techniques. Overall, superheated steam extraction is an efficient technique for extracting Pistacia lentiscus L. essential oil that enhances EO yield, requiring less time for extraction., (© 2024. The Author(s).)

Background: Recent studies have associated total neoadjuvant therapy (TNT) with better treatment adherence, decreased toxicity, improved complete clinical response and anal sphincter preservation rates in patients with locally advanced rectal cancer (LARC). However, real-world experience with TNT in the management of LARC remains limited., Aim: This study aimed to evaluate the efficacy and safety outcomes of TNT for LARC in Western Australia., Methods: Patients with LARC (cT2-4 and/or cN1-2) who underwent induction chemotherapy followed by neoadjuvant chemoradiotherapy or neoadjuvant chemoradiotherapy followed by consolidation chemotherapy, followed by surgery were recruited from two hospitals in Western Australia. Efficacy outcomes assessed included clinical response (complete, partial, no response), and pathologic complete response (pCR) rate, R0 resection rate, and R1 resection rate were evaluated. Those patients who achieved clinical complete response following TNT were given the option of active surveillance. The safety and tolerability of TNT were assessed., Results: 32 patients with LARC were treated with TNT. In total, 17 patients (53%) received chemoradiotherapy followed by consolidation chemotherapy and 15 patients (47%) received induction chemotherapy followed by chemoradiotherapy. Nine (28%) of the patients with LARC treated with TNT had a complete clinical response, twenty-one (66%) patients had a partial clinical response, and two (6%) patients had no response to TNT. Of the 32 patients, 27 (84%) underwent surgery. There was a 100% R0 resection rate. The pCR rate was 15%. pCR, clinical response, and the R0 resection rate were similar between the two TNT regimens. TNT was well tolerated, with the majority of patients (88%) completing the chemotherapy course with grade 1 and 2 adverse effects., Conclusions: In conclusion, TNT emerges as a promising approach for the management of LARC. However, further research is warranted to refine the optimal TNT protocols, determine its long-term outcomes, and identify patient populations who would benefit the most from this innovative therapeutic strategy.

The early prediction of ocular disease is certainly an obligatory concern in the domain of ophthalmic medicine. Although modern scientific discoveries have shown the potential to treat eye diseases by using artificial intelligence (AI) and machine learning, explainable AI remains a crucial challenge confronting this area of research. Although some traditional methods put in significant effort, they cannot accurately predict the proper ocular diseases. However, incorporating AI into diagnosing eye diseases in healthcare complicates the situation as the decision-making process of AI demonstrates complexity, which is a significant concern, especially in major sectors like ocular disease prediction. The lack of transparency in the AI models may hinder the confidence and trust of the doctors and the patients, as well as their perception of the AI and its abilities. Accordingly, explainable AI is significant in ensuring trust in the technology, enhancing clinical decision-making ability, and deploying ocular disease detection. This research proposed an efficient transfer learning model for eye disease prediction to transform smart vision potential in the healthcare sector and meet conventional approaches' challenges while integrating explainable artificial intelligence (XAI). The integration of XAI in the proposed model ensures the transparency of the decision-making process through the comprehensive provision of rationale. This proposed model provides promising results with 95.74% accuracy and explains the transformative potential of XAI in advancing ocular healthcare. This significant milestone underscores the effectiveness of the proposed model in accurately determining various types of ocular disease. It is clearly shown that the proposed model is performing better than the previously published methods.

The Comprehensive In-vitro Proarrhythmia Assay (CiPA) initiative aims to refine the assessment of drug-induced torsades de pointes (TdP) risk, utilizing computational models to predict cardiac drug toxicity. Despite advancements in machine learning applications for this purpose, the specific contribution of in-silico biomarkers to toxicity risk levels has yet to be thoroughly elucidated. This study addresses this gap by implementing explainable artificial intelligence (XAI) to illuminate the impact of individual biomarkers in drug toxicity prediction. We employed the Markov chain Monte Carlo method to generate a detailed dataset for 28 drugs, from which twelve in-silico biomarkers of 12 drugs were computed to train various machine learning models, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Random Forests (RF), XGBoost, K-Nearest Neighbors (KNN), and Radial Basis Function (RBF) networks. Our study's innovation is leveraging XAI, mainly through the SHAP (SHapley Additive exPlanations) method, to dissect and quantify the contributions of biomarkers across these models. Furthermore, the model performance was evaluated using the test set from 16 drugs. We found that the ANN model coupled with the eleven most influential in-silico biomarkers namely dVm dt repol , dVm dt max , APD 90 , APD 50 , APD tri , CaD 90 , CaD 50 , Ca tri , Ca Diastole , q I n w a r d , a n d q N e t showed the highest classification performance among all classifiers with Area Under the Curve (AUC) scores of 0.92 for predicting high-risk, 0.83 for intermediate-risk, and 0.98 for low-risk drugs. We also found that the optimal in silico biomarkers selected based on SHAP analysis may be different for various classification models. However, we also found that the biomarker selection only sometimes improved the performance; therefore, evaluating various classifiers is still essential to obtain the desired classification performance. Our proposed method could provide a systematic way to assess the best classifier with the optimal in-silico biomarkers for predicting the TdP risk of drugs, thereby advancing the field of cardiac safety evaluations., (© 2024. The Author(s).)

The current study focuses on assessing the activity of the N -alkylated benzimidazole based cubosomal hydrogel (cubogel) for the topical treatment of burn wounds. The study involves the synthesis of six benzimidazole derivatives (1-6) and their characterization by FT-IR and 1 H and 13 C NMR spectroscopy. The further study involves the design and formation of nanoparticles known as cubosomes loaded with selected 1-benzyl-1-benzimidazole (API 6) and the development of a cubogel for the topical treatment of burn wounds. Cubosomes were prepared by the homogenization method, using glyceryl monooleate (GMO) as a lipid polymer and poloxamer 407 (P407) as a surfactant. Cubosomes undergo in vitro characterizations (measurement of particle size, zeta potential, polydispersity index (PDI), % entrapment efficiency, drug release in phosphate buffer saline of pH 6.8, and surface morphology by utilizing TEM (transmission electron microscopy). Formulation D3 (2.5% of GMO, 1% of P407, and 2.5% of PVA) emerged as the optimized formulation, displaying a minimum particle size (PS) of 129.9 ± 1 nm, entrapment efficiency (%EE) of 96.67 ± 0.89%, and a drug release of 86 ± 2.7% at 24 h. Carbopol 940 hydrogel was prepared and incorporated with the optimized formulation to prepare cubogel. This optimized cubogel provided 92.56 ± 0.014% in vitro drug release within 24 h. An in vivo histopathological study was conducted on an animal model (rabbit) to assess the efficacy of cubogel in wound healing and wound contraction. Then cubogel was compared with the commercially available creams Clotrimazole® and Polyfax®. The wound treated with newly developed cubogel has maximum wound contraction (96.70%) as compared to the standard creams. The findings revealed that the newly formulated cubogel was highly effective in treating burns, showing superior performance to commercial products without inducing side effects. Additionally, benzimidazole derivative loaded cubogel caused a sustained release for treating burn wounds without any bacterial infections. The current results further suggested phase 0 clinical trials., Competing Interests: All the author declares that there is no conflict of interest in publish this research., (This journal is © The Royal Society of Chemistry.)

Simultaneous utilization of photogenerated electrons and holes to achieve overall redox reactions is attractive but still far from practical application. The emerging step (S)-scheme mechanism has proven to be an ideal approach to inhibit charge recombination and supply photoinduced charges with highest redox potentials. Herein, a hierarchical phosphotungstic acid (H 3 PW 12 O 40 , HPW)@Znln 2 S 4 (ZISW) heterojunction was prepared through one-pot hydrothermal method for simultaneous hydrogen (H 2 ) evolution and benzyl alcohol upgrading. The fabricated HPW-based heterojunctions indicated much enhanced visible-light absorption, promoted photogenerated charge transfer and inhibited charge recombination, owing to hierarchical architecture based on visible-light responsive Znln 2 S 4 microspheres, and S-scheme charge transfer pathway. The S-scheme mechanism was further verified by free-radical trapping electron spin resonance (ESR) spectra. Moreover, the wettability of composite heterojunction was improved by the modification of hydrophilic HPW, contributing to gaining active hydrogen (H + ) from water sustainably. The optimal ZISW-30 heterojunction photocatalyst indicated an enhanced hydrogen evolution rate of 27.59 mmol g -1  h -1 in benzyl alcohol (10 vol. %) solution under full-spectrum irradiation, along with highest benzaldehyde production rate is 8.32 mmol g -1  h -1 . This work provides a promising guideline for incorporating HPW into S-scheme heterojunctions to achieve efficient overall redox reactions., (© 2024 Wiley-VCH GmbH.)

In recent decades, there has been considerable interest in investigating advanced energetic materials characterized by high stability and favorable energetic properties. Nevertheless, reconciling the conflicting balance between high energy and the insensitivity of such materials through traditional approaches, which involve integrating fuel frameworks and oxidizing groups into an organic molecule, presents significant challenges. In this study, we employed a promising method to fabricate high-energy-density materials (HEDMs) through the intermolecular assembly of variously substituted purines with a high-energy oxidant. Purines are abundant in nature and are readily available. A series of advanced energetic materials with a good balance between energy and sensitivity were prepared by the simple and effective self-assembly of purines with high-energy oxidants. Notably, these compounds exhibit incredibly improved crystal densities (1.80-2.00 g·cm -3 ) and good detonation performance ( D : 7072-8358 m·s -1 ; P : 19.82-34.56 GPa). In comparison to RDX, these self-assembled energetic materials exhibit reduced mechanical sensitivities and enhanced thermal stabilities. Compounds 1 - 5 demonstrate both high energy and low sensitivity, indicating that self-assembly represents a straightforward and effective approach for developing advanced energetic materials with a balanced combination of energy and safety. Moreover, this study offers an avenue for synthesizing energetic materials based on naturally occurring compounds assembled through intermolecular attractions, thereby achieving a balance between energy and sensitivity along with versatile functionality.

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Importance: Antiseizure medications (ASMs) are frequently prescribed for acute symptomatic seizures and epileptiform abnormalities (EAs; eg, periodic or rhythmic patterns). There are limited data on factors associated with ASM use and their association with outcomes., Objectives: To determine factors associated with ASM use in patients with confirmed or suspected acute symptomatic seizures undergoing continuous electroencephalography, and to explore the association of ASMs with outcomes., Design, Setting, and Participants: This multicenter cohort study was performed between July 1 and September 30, 2021, at 5 US centers of the Post Acute Symptomatic Seizure Investigation and Outcomes Network. After screening 1717 patients, the study included 1172 hospitalized adults without epilepsy who underwent continuous electroencephalography after witnessed or suspected acute symptomatic seizures. Data analysis was performed from November 14, 2023, to February 2, 2024., Exposure: ASM treatment (inpatient ASM continuation ≥48 hours)., Main Outcomes and Measures: Factors associated with (1) ASM treatment, (2) discharge ASM prescription, and (3) discharge and 3-month Glasgow Outcome Scale score of 4 or 5 were ascertained., Results: A total of 1172 patients (median [IQR] age, 64 [52-75] years; 528 [45%] female) were included. Among them, 285 (24%) had clinical acute symptomatic seizures, 107 (9%) had electrographic seizures, and 364 (31%) had EAs; 532 (45%) received ASM treatment. Among 922 patients alive at discharge, 288 (31%) were prescribed ASMs. The respective frequencies of inpatient ASM treatment and discharge prescription were 82% (233 of 285) and 69% (169 of 246) for patients with clinical acute symptomatic seizures, 96% (103 of 107) and 95% (61 of 64) for electrographic seizures, and 64% (233 of 364) and 48% (128 of 267) for EAs. On multivariable analysis, acute and progressive brain injuries were independently associated with increased odds of inpatient ASM treatment (odds ratio [OR], 3.86 [95% CI, 2.06-7.32] and 8.37 [95% CI, 3.48-20.80], respectively) and discharge prescription (OR, 2.26 [95% CI, 1.04-4.98] and 10.10 [95% CI, 3.94-27.00], respectively). Admission to the neurology or neurosurgery service (OR, 2.56 [95% CI, 1.08-6.18]) or to the neurological intensive care unit (OR, 7.98 [95% CI, 3.49-19.00]) was associated with increased odds of treatment. Acute symptomatic seizures and EAs were significantly associated with increased odds of ASM treatment (OR, 14.30 [95% CI, 8.52-24.90] and 2.30 [95% CI, 1.47-3.61], respectively) and discharge prescription (OR, 12.60 [95% CI, 7.37-22.00] and 1.72 [95% CI, 1.00-2.97], respectively). ASM treatment was not associated with outcomes at discharge (OR, 0.96 [95% CI, 0.61-1.52]) or at 3 months after initial presentation (OR, 1.26 [95% CI, 0.78-2.04]). Among 623 patients alive and with complete data at 3 months after discharge, 30 (5%) had postdischarge seizures, 187 (30%) were receiving ASMs, and 202 (32%) had all-cause readmissions., Conclusions and Relevance: This study suggests that etiology and electrographic findings are associated with ASM treatment for acute symptomatic seizures and EAs; ASM treatment was not associated with functional outcomes. Comparative effectiveness studies are indicated to identify which patients may benefit from ASMs and to determine the optimal treatment duration.

Background and Objectives: Apart from known factors such as irrational use of antibiotics and horizontal gene transfer, it is now reported that clustered regularly interspaced short palindromic repeats (CRISPR) are also associated with increased antimicrobial resistance. Hence, it is critical to explore alternatives to antibiotics to control economic losses. Therefore, the present study aimed to determine not only the association of CRISPR-Cas system with antibiotic resistance but also the potential of Zinc Oxide nanoparticles (ZnO-NPs) for avian pathogenic Escherichia coli (APEC) isolated from poultry market Lahore., Materials and Methods: Samples (n = 100) were collected from live bird markets of Lahore, and isolates were confirmed as Escherichia coli (E. coli) using the Remel One fast kit, and APEC was identified using PCR. The antibiotic resistance pattern in APEC was determined using the minimum inhibitory concentration (MIC), followed by genotypic confirmation of antibiotic-resistant genes using the PCR. The CRISPR-Cas system was also identified in multidrug-resistant (MDR) isolates, and its association with antibiotics was determined using qRT-PCR. The potential of ZnO-NPs was evaluated for multidrug-resistant (MDR) isolates by MIC., Results: All isolates of APEC were resistant to nalidixic acid, whereas 95% were resistant to chloramphenicol and 89% were resistant to streptomycin. Nineteen MDR APEC were found in the present study and the CRISPR-Cas system was detected in all of these MDR isolates. In addition, an increased expression of CRISPR-related genes was observed in the standard strain and MDR isolates of APEC. ZnO-NPs inhibited the growth of resistant isolates., Conclusions: The findings showed the presence of the CRISPR-Cas system in MDR strains of APEC, along with the potential of ZnO-NPs for a possible solution to proceed. This highlights the importance of regulating antimicrobial resistance in poultry to reduce potential health consequences., (© 2024. The Author(s).)

The genus Rhododendron is an ancient and most widely distributed genus of the family Ericaceae consisting of evergreen plant species that have been utilized as traditional medicine since a very long time for the treatment of various ailments including pain, asthma, inflammation, cold, and acute bronchitis. The chemistry of polyphenolics isolated from a number of species of the genus Rhododendron has been investigated. During the currently designed study, an in-depth study on the phytochemistry, natural distribution, biosynthesis, and pharmacological properties including their potential capability as free radical scavengers has been conducted. This work provides structural characteristics of phenolic compounds isolated from the species of Rhododendron with remarkable antioxidant potential. In addition, biosynthesis and theranostic study have also been encompassed with the aims to furnish a wide platform of valuable information for designing of new drug entities. The detailed information including names, structural features, origins, classification, biosynthetic pathways, theranostics, and pharmacological effects of about 171 phenolics and flavonoids isolated from the 36 plant species of the genus Rhododendron with the antioxidant potential has been covered in this manuscript. This study demonstrated that species of Rhododendron genus have excellent antioxidant activities and great potential as a source for natural health products. This comprehensive review might serve as a foundation for more investigation into the Rhododendron genus., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In articular cartilage, the pericellular matrix acting as a specialized mechanical microenvironment modulates environmental signals to chondrocytes through mechanotransduction. Matrix viscoelastic alterations during cartilage development and osteoarthritis (OA) degeneration play an important role in regulating chondrocyte fate and cartilage matrix homeostasis. In recent years, scientists are gradually realizing the importance of matrix viscoelasticity in regulating chondrocyte function and phenotype. Notably, this is an emerging field, and this review summarizes the existing literatures to the best of our knowledge. This review provides an overview of the viscoelastic properties of hydrogels and the role of matrix viscoelasticity in directing chondrocyte behavior. In this review, we elaborated the mechanotransuction mechanisms by which cells sense and respond to the viscoelastic environment and also discussed the underlying signaling pathways. Moreover, emerging insights into the role of matrix viscoelasticity in regulating chondrocyte function and cartilage formation shed light into designing cell-instructive biomaterial. We also describe the potential use of viscoelastic biomaterials in cartilage tissue engineering and regenerative medicine. Future perspectives on mechanobiological comprehension of the viscoelastic behaviors involved in tissue homeostasis, cellular responses, and biomaterial design are highlighted. Finally, this review also highlights recent strategies utilizing viscoelastic hydrogels for designing cartilage-on-a-chip., (© 2024 John Wiley & Sons Ltd.)

Objective: This study aimed to investigate the prevalence of paratuberculosis in cattle and buffaloes at twelve public dairy farms in Punjab, Pakistan., Methods: A total of 2,181 more than two-year-old animals (1,242 cattle and 939 buffaloes) were tested by avian tuberculin, i.e., killed purified protein derivative of Mycobacterium avium paratuberculosis and indirect enzyme linked immunosorbent assay (ELISA). Blood and fecal samples were collected from tuberculin positive animals. These samples were further processed by indirect ELISA. The data were analyzed using frequency analysis and logistic analysis procedures., Results: The prevalence of paratuberculosis at public dairy farms was 3.8%, as determined by tuberculin+ELISA test. It varied from 0.71% to 13.5% with a 100% herd prevalence. Multivariate logistic regression analysis revealed that species, milk production, total animals, total small ruminants, and total buffaloes were significantly associated with the occurrence of paratuberculosis. Odd ratio analysis revealed that with a one-kilogram increase in body weight, there will be a 0.006% increase in disease occurrence. With the increase in one animal in small ruminants and buffaloes, there will be 0.008% and 0.42% greater chances of developing paratuberculosis, respectively. Bivariate logistic regression analysis of cattle and buffaloes revealed that farm number, age, and total number of cattle were significantly associated with the occurrence of paratuberculosis. A one-month increase in lactation length increases the chance of tuberculosis by 0.004%; similarly, a one-liter increase in milk production increases the chance of disease by 10%. With each additional buffalo in the herd, there will be a 0.007% greater chance for the occurrence of paratuberculosis., Conclusion: This study concluded that tuberculin testing can be used in conjunction with ELISA to screen animals for paratuberculosis in countries with scarce resources, such as Pakistan. The efficacy of disease diagnosis can be improved by combining multiple tests.

This study explores the association between natural resources rent, industrial value addition, banking development, renewable energy consumption, total reserves and environmental quality in the dynamic context of BRICS nations from 1995 to 2019. BRICS economies are responsible for global greenhouse gas emissions and confront pressing environmental challenges, including biodiversity loss and pollution. For the dependent variable, the environmental quality, the study constructed a composite index using PCA for all environmental indicators where interdependencies among variables are prevalent. Besides this, the study incorporates two interaction terms to determine the indirect influence of natural resource rent and banking development on environmental quality through the mediating role of industrial value addition. By applying the CS-ARDL technique, the outcomes of the study reveal that natural resources rent, industrial value addition, and total reserves positively influence ENQ, indicating the adverse consequences of industrial sectors on environmental quality and continued environmental degradation due to resource-intensive industrial production, underscoring the urgency of sustainable resource management. In contrast, banking development and renewable energy consumption negatively influence ENQ, signifying the positive role of developed banking sectors in supporting eco-friendly projects and enhancing environmental quality. This study offers valuable insights for policy interventions to foster a more sustainable future., 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 Ltd. All rights reserved.)

Apart from biocompatibility, ZnO quantum dots (QDs) are considered to be an efficient luminescence material due to their low cost and high redox potential. Here, we report the synthesis of ZnO QDs by using five different functionalizing ligands like mercaptoacetic acid (MAA), 3-mercaptopropionic acid (MPA), octadecene (ODE), ethylene glycol (EG), and oleyl amine (OLA) and fabricate their assemblies with graphene oxide (GO). We investigate the role of functionalizing ligands as a surface modifier of ZnO QDs for their attachment to GO. The steady-state photoluminescence (SSPL) and time-resolved photoluminescence (TRPL) analyses demonstrate the photoluminescence (PL) quenching of ZnO QDs in ZnO QDs-GO assembly. The highest reduction in PL intensity is observed with ZnO QDs-GO assembly with EG as a surface functionalizing ligand. Cyclic voltammetry (CV) analysis confirms the feasibility of charge transfer from ZnO QDs to the GO. The maximum (79.43%) charge transfer efficiency (E CT ) is observed in the case of ZnO-MAA-GO as compared to other assemblies. This means the thiol group-containing ligands facilitate charge transfer as compared to hydroxyl and amine group ligands. This leads to the conclusion that charge transfer in ZnO QDs-GO assemblies depends strongly on the nature of surface ligands., (© 2023 The American Society for Photobiology.)

This study addresses the critical issue of drug-induced torsades de pointes (TdP) risk assessment, a vital aspect of new drug development due to its association with arrhythmia and sudden cardiac death. Existing methodologies, particularly those reliant on a single biomarker derived from CiPA O'Hara-Rudy (CiPAORdv1.0) ventricular cell model without the hERG dynamic as input to the individual machine learning model, have limitations in capturing the complexity inherent in the comprehensive range of factors influencing drug-induced TdP risk. This study aims to overcome these limitations by proposing a stacking ensemble machine learning approach by integrating multiple in silico biomarkers derived from the CiPAORdv1.0 with hERG dynamic characteristics. The ensemble machine learning model consisted of three artificial neural network (ANN) models as baseline model and support vector machine (SVM), logistic regression (LR), random forest (RF), and extreme gradient boosting (XGBoost) models as meta-classifier. The highest AUC score of 1.00 (0.90-1.00) for high risk, 0.97 (0.84-1.00) for intermediate risk, and 1.00 (0.87-1.00) for low risk were obtained using seven biomarkers derived from the CiPAORdv1.0 with hERG dynamic characteristics. Furthering our investigation, we explored the model's robustness by incorporating interindividual variability into the generation of in silico biomarkers from a population of human ventricular cell models. This study also enabled an analysis of TdP risk classification under high clinical exposure and therapeutic scenarios for several drugs. Additionally, from a sensitivity analysis, we revealed four important ion channels, namely, CaL, NaL, Na, and Kr channels that affect significantly the important biomarkers for TdP risk prediction., (© 2024 The Author(s). CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

This review article offers a comprehensive analysis of current developments in the application of machine learning for cancer diagnostic systems. The effectiveness of machine learning approaches has become evident in improving the accuracy and speed of cancer detection, addressing the complexities of large and intricate medical datasets. This review aims to evaluate modern machine learning techniques employed in cancer diagnostics, covering various algorithms, including supervised and unsupervised learning, as well as deep learning and federated learning methodologies. Data acquisition and preprocessing methods for different types of data, such as imaging, genomics, and clinical records, are discussed. The paper also examines feature extraction and selection techniques specific to cancer diagnosis. Model training, evaluation metrics, and performance comparison methods are explored. Additionally, the review provides insights into the applications of machine learning in various cancer types and discusses challenges related to dataset limitations, model interpretability, multi-omics integration, and ethical considerations. The emerging field of explainable artificial intelligence (XAI) in cancer diagnosis is highlighted, emphasizing specific XAI techniques proposed to improve cancer diagnostics. These techniques include interactive visualization of model decisions and feature importance analysis tailored for enhanced clinical interpretation, aiming to enhance both diagnostic accuracy and transparency in medical decision-making. The paper concludes by outlining future directions, including personalized medicine, federated learning, deep learning advancements, and ethical considerations. This review aims to guide researchers, clinicians, and policymakers in the development of efficient and interpretable machine learning-based cancer diagnostic systems., 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 article. Authors have not recieved any funding for this manuscript., (© 2024 The Authors. Published by Elsevier Ltd.)

Emerging Industry 5.0 designs promote artificial intelligence services and data-driven applications across multiple places with varying ownership that need special data protection and privacy considerations to prevent the disclosure of private information to outsiders. Due to this, federated learning offers a method for improving machine-learning models without accessing the train data at a single manufacturing facility. We provide a self-adaptive framework for federated machine learning of healthcare intelligent systems in this research. Our method takes into account the participating parties at various levels of healthcare ecosystem abstraction. Each hospital trains its local model internally in a self-adaptive style and transmits it to the centralized server for universal model optimization and communication cycle reduction. To represent a multi-task optimization issue, we split the dataset into as many subsets as devices. Each device selects the most advantageous subset for every local iteration of the model. On a training dataset, our initial study demonstrates the algorithm's ability to converge various hospital and device counts. By merging a federated machine-learning approach with advanced deep machine-learning models, we can simply and accurately predict multidisciplinary cancer diseases in the human body. Furthermore, in the smart healthcare industry 5.0, the results of federated machine learning approaches are used to validate multidisciplinary cancer disease prediction. The proposed adaptive federated machine learning methodology achieved 90.0%, while the conventional federated learning approach achieved 87.30%, both of which were higher than the previous state-of-the-art methodologies for cancer disease prediction in the smart healthcare industry 5.0., (© 2024. The Author(s).)

Crystal violet (CV) dye, because of its non-biodegradability and harmful effects, poses a significant challenge for wastewater treatment. This study addresses the efficiency of easily accessible coal fly ash (CFA)-based adsorbents such as raw coal fly ash (RCFA) and surface enhanced coal fly ash (SECFA), in removing CV dye from waste effluents. Various analytical techniques such as FTIR, XRD, SEM, TEM, BET, zeta sizer and zeta potential were employed for the characterization of the adsorbents and dye-loaded samples. BET revealed that RCFA possesses a surface area of 19.370 m 2 g -1 and SECFA of 27.391 m 2 g -1 , exhibiting pore volumes of 0.1365 cm 3 g -1 and 0.1919 cm 3 g -1 respectively. Zeta-sizer and potential analysis showed the static charges of RCFA as -27.3 mV and SECFA as -28.2 mV, with average particle sizes of 346.6 and 315.3 nm, respectively. Langmuir and Freundlich adsorption isotherms were also employed for adsorption studies. Employing central composite design (CCD) of response surface methodology (RSM), the maximum CV removal was 81.52% for RCFA and 97.52% for SECFA, providing one minute contact time, 0.0125 g adsorbent dose and 10 ppm dye concentration. From the thermodynamic studies, all the negative values of Δ G ° showed that all the adsorption processes of both adsorbents were spontaneous in nature., Competing Interests: The authors declare that they have no competing interests as denied by Journal, or other interests that might be perceived to influence the results and/or discussion reported in this paper., (This journal is © The Royal Society of Chemistry.)

This study investigated the effects of the β-mannanase enzyme and soyhulls on production performance, economics, egg quality, hematology and serum biochemistry, nutrient digestibility, gut morphology, digesta viscosity, and excreta consistency in laying hens during the late peak production phase (37 to 40 weeks of age). Golden brown hens (RIR × Fayoumi; n = 200) were fed a control diet (no soyhulls or enzymes) and diets containing four combinations, i.e., 3% soyhulls with 20 mg/kg β-mannanase (D1), 3% soyhulls with 30 mg/kg β-mannanase (D2), 9% soyhulls with 20 mg/kg β-mannanase (D3), and 9% soyhulls with 30 mg/kg β-mannanase (D4), for four weeks in four replicates of 10 birds each. Overall, a significantly higher ( p < 0.05) feed intake, weight gain, feed conversion ratio, and water intake were calculated in the D2 group as compared to the control and remaining combinations of soyhulls and β-mannanase. No mortality was recorded during the entire experiment. Economically, the D1 and D2 groups showed the best results as compared to the D3 and D4 groups. Egg quality parameters like egg weight, shell weight and shell thickness, yolk weight, albumen weight and height, and the Haugh unit remained unchanged ( p > 0.05). Similarly, the D2 group showed significantly lower total cholesterol, LDL, and VLDL levels and enhanced gut morphology with greater villus width, height, crypt depth, and surface area across intestinal segments. Crude protein (CP), crude fiber (CF), crude fat, and ash digestibility were higher ( p < 0.05) in the D1 and D2 groups compared to the control. Digesta viscosity, excreta consistency, and other egg quality parameters remained unaffected. In conclusion, the dietary inclusion of a combination of 3% soyhulls and 30 mg/kg β-mannanase may have potential benefits for laying hens by improving some production performance and egg quality indicators and economics, lowering blood cholesterol, LDL, and VLDL levels, enhancing nutrient digestibility, and improving gut morphology without affecting egg quality.

This review explores recent advancements in synthesizing quinoid heteroaryls, namely quinazoline and quinoline, vital in chemistry due to their prevalence in natural products and pharmaceuticals. It emphasizes the rapid, highly efficient, and economically viable synthesis achieved through gold-catalyzed cascade protocols. By investigating methodologies and reaction pathways, the review underscores exceptional yields attainable in the synthesis of quinoid heteroaryls. It offers valuable insights into accessing these complex structures through efficient synthetic routes. Various strategies, including cyclization, heteroarylation, cycloisomerization, cyclo-condensation, intermolecular and intramolecular cascade reactions, are covered, highlighting the versatility of gold-catalyzed approaches. The comprehensive compilation of different synthetic approaches and elucidation of reaction mechanisms contribute to a deeper understanding of the field. This review paves the way for future advancements in synthesizing quinoid heteroaryls and their applications in drug discovery and materials science., Competing Interests: The authors declare no conflict of interest., (This journal is © The Royal Society of Chemistry.)

Biochar, an organic carbonaceous matter, is a unique feed additive that is now being used in aquaculture industry to formulate a cost-effective and eco-friendly diet. This experiment (in door) was conducted over course of 90 days to determine the most effective form of biochar, produced from various sources, for supplementation in Moringa oleifera seed meal-based diet. These sources were: farmyard manure biochar, parthenium biochar (PB), vegetable waste biochar, poultry waste biochar (PWB) and corncob waste biochar, added at 2 g/kg concentration to determine the effect of supplementation on the growth indices, nutrient absorption, carcass composition, haematology and mineral status of Labeo rohita (rohu) fingerlings. The research design consisted of six test diets with three replications (6 × 3) of each. Total of 270 fingerlings (6.30 ± 0.020 g) were fed at 5% body weight and 15 of them were kept in separate steel tanks. The results indicated that PWB was most effective in improving weight gain (285.58 ± 4.54%) and feed conversion ratio (1.060 ± 0.040) compared to control diet and other test diets. The same type of biochar (PWB) produced the best results for nutrient digestibility, that is, crude protein, crude fat and gross energy and carcass composition. In terms of haematology and mineral status, PWB showed the best results. In conclusion, it was found that PWB significantly enhanced (p < 0.05) L. rohita fingerling's growth, carcass composition, nutrient digestibility, haematological parameters (red blood cells, white blood cells, platelets and haemoglobin) and mineral composition (Ca, Na, P, Mg, Fe, Mn, Zn, K and Cu) whereas PB negatively affected all parameters. It is anticipated that the potential use of biochar will increase in aquaculture industry, as research on its incorporation in fish feeds is still limited., (© 2024 Wiley‐VCH GmbH. Published by John Wiley & Sons Ltd.)

Background: Pain is a traumatic experience for most patients on hemodialysis. In this trial, we compared prilocaine/lidocaine cream with piroxicam gel for pain reduction during arteriovenous fistula needling., Methods: This randomized double-blind crossover clinical trial was done at dialysis unit of a tertiary care hospital from June to August 2022. Adult patients, aged 18-75 years, on maintenance hemodialysis through an arteriovenous fistula were selected randomly. Pain severity during needling of fistula was assessed during initial two hemodialysis sessions without application of any drug. Patients were then randomized into two groups receiving 5% prilocaine/lidocaine cream or 0.5% piroxicam gel 1 h before the next two hemodialysis sessions. After a 7-day washout period, patients crossed over to other groups for another two hemodialysis sessions. Pain was assessed on all these occasions. Primary outcome was reduction in pain with each intervention., Results: There were 32 patients aged 46.44 ± 11.58 years. Pain intensity was 6.69 ± 0.58, 3.13 ± 1.28, and 4.55 ± 1.95 without any medication, prilocaine/lidocaine cream and piroxicam gel respectively. There was greater pain reduction with prilocaine/lidocaine cream than piroxicam gel (3.56 ± 1.35 vs 2.14 ± 1.78; p  = 0.001). Local redness with prilocaine/lidocaine cream was reported by one (3.13%) patient, whereas no side effects were seen with piroxicam gel ( p  = 1.000)., Conclusion: Prilocaine/lidocaine cream provides better pain relief than piroxicam gel during arteriovenous fistula needling., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Celiac disease (CD) is a complicated autoimmune disease that is caused by gluten sensitivity. It was commonly believed that CD only affected white Europeans, but recent findings show that it is also prevailing in some other racial groups, like South Asians, Caucasians, Africans, and Arabs. Genetics plays a profound role in increasing the risk of developing CD. Genetic Variations in non- HLA genes such as LPP , ZMIZ1 , CCR3 , and many more influence the risk of CD in various populations. This study aimed to explore the association between LPP rs1464510 and ZMIZ1 rs1250552 and CD in the Punjabi Pakistani population. For this, a total of 70 human subjects were selected and divided into healthy controls and patients. Genotyping was performed using an in-house-developed tetra-amplification refractory mutation system polymerase chain reaction. Statistical analysis revealed a significant association between LPP rs1464510 (χ 2 = 4.421, p = 0.035) and ZMIZ1 rs1250552 (χ2 = 3.867, p = 0.049) and CD. Multinomial regression analysis showed that LPP rs1464510 A allele reduces the risk of CD by ~52% (OR 0.48, CI: 0.24-0.96, 0.037), while C allele-carrying subjects are at ~2.6 fold increased risk of CD (OR 3.65, CI: 1.25-10.63, 0.017). Similarly, the ZMIZ1 rs1250552 AG genotype significantly reduces the risk of CD by 73% (OR 0.26, CI: 0.077-0.867, p = 0.028). In summary, Genetic Variations in the LPP and ZMIZ1 genes influence the risk of CD in Punjabi Pakistani subjects. LPP rs1464510 A allele and ZMIZ1 AG genotype play a protective role and reduce the risk of CD.

The agricultural sector is pivotal to food security and economic stability worldwide. Corn holds particular significance in the global food industry, especially in developing countries where agriculture is a cornerstone of the economy. However, corn crops are vulnerable to various diseases that can significantly reduce yields. Early detection and precise classification of these diseases are crucial to prevent damage and ensure high crop productivity. This study leverages the VGG16 deep learning (DL) model to classify corn leaves into four categories: healthy, blight, gray spot, and common rust. Despite the efficacy of DL models, they often face challenges related to the explainability of their decision-making processes. To address this, Layer-wise Relevance Propagation (LRP) is employed to enhance the model's transparency by generating intuitive and human-readable heat maps of input images. The proposed VGG16 model, augmented with LRP, outperformed previous state-of-the-art models in classifying corn leaf diseases. Simulation results demonstrated that the model not only achieved high accuracy but also provided interpretable results, highlighting critical regions in the images used for classification. By generating human-readable explanations, this approach ensures greater transparency and reliability in model performance, aiding farmers in improving their crop yields., 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 author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Tariq, Ali, Abbas, Hassan, Naqvi, Khan and Jeong.)

The recent advancements in utilizing organocatalysts for the synthesis of organic compounds have been described in this review by focusing on their simplicity, effectiveness, reproducibility, and high selectivity which lead to excellent product yields. The organocatalytic methods for various derivatives, such as indoles, pyrazolones, anthrone-functionalized benzylic amines, maleimide, polyester, phthalimides, dihydropyrimidin, heteroaryls, N -aryl benzimidazoles, stilbenoids, quinazolines, quinolines, and oxazolidinones have been specifically focused. The review provides more understanding by delving into potential reaction mechanisms. We anticipate that this collection of data and findings on successful synthesis of diverse compound derivatives will serve as valuable resources and stimulating current and future research efforts in organocatalysis and industrial chemistry., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Bacterial resistance towards antibiotics is a significant challenge for public health, and surface-enhanced Raman spectroscopy (SERS) has great potential to be a promising technique to provide detailed information about the effect of antibiotics against biofilms. SERS is employed to check the antibacterial potential of a lab synthesized drug ([bis(1,3-dipentyl-1 H -imidazol-2(3 H )-ylidene)silver(i)] bromide) against Bacillus subtilis and to analyze various SERS spectral features of unexposed and exposed Bacillus strains by observing biochemical changes in DNA, protein, lipid and carbohydrate contents induced by the lab synthesized imidazole derivative. Further, PCA and PLS-DA are employed to differentiate the SERS features. PCA was employed to differentiate the biochemical contents of unexposed and exposed Bacillus strains in the form of clusters of their representative SERS spectra and is also helpful in the pairwise comparison of two spectral data sets. PLS-DA provides authentic information to discriminate different unexposed and exposed Bacillus strains with 91% specificity, 93% sensitivity and 97% accuracy. SERS can be employed to characterize the complex and heterogeneous system of biofilms and to check the changes in spectral features of Bacillus strains by exposure to the lab synthesized imidazole derivative., Competing Interests: The authors have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (This journal is © The Royal Society of Chemistry.)

In this study, the methyl orange (MO) dye has been degraded after screening several azo dyes due to its effective results and being toxic and carcinogenic to aquatic life and humans. An environmentally friendly, economical, and green method for water purification was used in this study using the photooxidative method. Several organic acids were screened for oxidative applications against various azo dyes but due to better results, methyl orange was selected for the whole study. Ascorbic acid, also known as vitamin C, was found to be best for photodegradation due to its high oxidative activity among various organic acids utilized. A newly developed photoreactor box has been used to conduct the photooxidation process. To evaluate the degradation efficiency of AsA, photooxidative activity was monitored periodically. When the dose of AsA was used at a contact time of 180 minutes, degradation efficiency was 96%. The analysis of degraded products was performed using HPLC and GC-MS. The nucleophilicity of HOMO-LUMO and MEPs was confirmed using density functional theory. For the optimization of the process, central composite design (CCD) in Response Surface Methodology (RSM) was utilized., Competing Interests: The authors declare no conflict of interest., (This journal is © The Royal Society of Chemistry.)

Tetrazoles and their derivatives are essential for compound synthesis due to their versatility, effectiveness, stability in air, and cost-efficiency. This has stimulated interest in developing techniques for their production. In this work, four compounds, tetrazolo[1,5- c ]pyrimidin-5-amine ( 1 ), N-(4-azidopyrimidin-2-yl)nitramide ( 2 ), tetrazolo[1,5- c ]pyrimidin-5(6H)-one ( 3 ), and tetrazolo[1,5- a ]pyrimidin-5-amine ( 4 ), were obtained from commercially available reagents and straightforward synthetic methodologies. These new compounds were characterized by infrared (IR), 13 C, and 1 H NMR spectroscopy, differential scanning calorimetry (DSC), and single-crystal X-ray diffraction. The solvent, temperature, and electron-donating group (EDG) factors that were responsible for the steering of azido-tetrazole equilibrium in all compounds were also studied. In addition, the detonation performance of the target compounds was calculated by using heats of formation (HOFs) and crystal densities. Hirshfeld surface analysis was used to examine the intermolecular interactions of the four synthesized compounds. The results show that the excellent properties of 1 - 4 are triggered by ionic bonds, hydrogen bonds, and π-π stacking interactions, indicating that these compounds have the potential to be used in the development of high-performance energetic materials. Additionally, DFT analysis is in support of experimental results, which proved the effect of different factors that can influence the azido-tetrazole equilibrium in the synthesized pyrimidine derivatives in the solution.

To explore the possible impact of 2-Phenylbenzimidazole-5-sulfonic acid (PBSA) on the function of a sunscreen, in this work we investigate the binding of copper metal ions (Cu 2+ ) to PBSA. Due to the existence of an intrinsic interaction phenomenon between Cu 2+ ions and PBSA molecules, the photoluminescence (PL) quenching arises owing to the charge transfer from PBSA to Cu 2+ ions. The mechanism of fluorescence quenching is probed experimentally following excitation at 306 nm by evaluating various quenching parameters with the help of the Stern-Volmer plot. Through the assessment of the values of the Stern-Volmer constant ( K SV = 45.2 M - 1 ) and bimolecular quenching rate constant ( k q = 0.77 × 10 10 M - 1 . s - 1 ), it is deduced that the dynamic mode of PL quenching is operative between PBSA and Cu 2+ ions. We evaluate the number of binding sites (n = 1) that advocate the presence of a single binding site in PBSA for Cu 2+ ions. The numerical value of standard Gibbs free energy change, Δ G o ~ -27.485 kJ.mol -1 implies the spontaneous binding between Cu 2+ ions and PBSA molecules. The results obtained give an insight into the mechanism of metal-induced PL quenching of water soluble PBSA sunscreen., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Citrus fruits, revered for their nutritional value, face significant threats from diseases like citrus canker, particularly impacting global citrus cultivation, notably in Pakistan. This study delves into the critical role of NPR1 -like genes, the true receptors for salicylic acid (SA), in the defense mechanisms of citrus against Xanthomonas axonopodis pv. citri (Xcc). By conducting a comprehensive genome-wide analysis and phylogenetic study, the evolutionary dynamics of Citrus limon genes across diverse citrus cultivars are elucidated. Structural predictions unveil conserved domains, such as the BTB domain and ankyrin repeat domains, crucial for the defense mechanism. Motif analysis reveals essential conserved patterns, while cis-regulatory elements indicate their involvement in transcription, growth, response to phytohormones, and stress. The predominantly cytoplasmic and nuclear localization of NPR1 -like genes underscores their pivotal role in conferring resistance to various citrus species. Analysis of the Ks/Ka ratio indicates a purifying selection of NPR1 -like genes, emphasizing their importance in different species. Synteny and chromosomal mapping provide insights into duplication events and orthologous links among citrus species. Notably, Xac infection stimulates the expression of NPR1 -like genes, revealing their responsiveness to pathogenic challenges. Interestingly, qRT-PCR profiling post-Xac infection reveals cultivar-specific alterations in expression within susceptible and resistant citrus varieties. Beyond genetic factors, physiological parameters like peroxidase, total soluble protein, and secondary metabolites respond to SA-dependent PR genes, influencing plant characteristics. Examining the impact of defense genes (NPR1) and plant characteristics on disease resistance in citrus, this study marks the inaugural investigation into the correlation between NPR1-associated genes and various plant traits in both susceptible and resistant citrus varieties to citrus bacterial canker., 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, Shafiq, Haider, Sami, Alam, Albalawi, Kamran, Sadiq, Hussain, Shahid, Jeridi, Ashraf, Manzoor and Sabir.)

Shiitake mushrooms are renowned for their popularity and robust nutritional value, are susceptible to spoilage due to their inherent biodegradability. Nevertheless, because of their lack of protection, these mushrooms have a short shelf life. Throughout the post-harvest phase, mushrooms experience a persistent decline in quality. This is evidenced by changes such as discoloration, reduced moisture content, texture changes, an increase in microbial count, and the depletion of nutrients and flavor. Ensuring postharvest quality preservation and prolonging mushroom shelf life necessitates the utilization of post-harvest preservation techniques, including physical, chemical, and thermal processes. This review provides a comprehensive overview of the deterioration processes affecting mushroom quality, covering elements such as moisture loss, discoloration, texture alterations, increased microbial count, and the depletion of nutrients and flavor. It also explores the key factors influencing these processes, such as temperature, relative humidity, water activity, and respiration rate. Furthermore, the review delves into recent progress in preserving mushrooms through techniques such as drying, cooling, packaging, irradiation, washing, and coating., 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 Asdullah, Chen, Hassan, Abbas, Sajad, Rafiq, Raza, Tahir, Wang and Chen.)

Herbal medicinal plants have been used for centuries in traditional medicine, and it is interesting to see how modern research has identified the active compounds responsible for their therapeutic effects. The green synthesis of silver nanoparticles using herbal medicinal plants, such as Swertia chirata , is particularly noteworthy due to its antimicrobial properties. In the current study, the Swertia chirata plant was collected for the first time from the region of Murree, Punjab, Pakistan. After collection, extracts were prepared in different solvents (ethanol, methanol, chloroform, and distilled water), and silver nanoparticles were synthesized by reducing silver nitrate (AgNO 3 ). The UV-visible spectrophotometer, SEM, and EDX were used to characterize the synthesized nanoparticles in terms of their size and shape. The phytochemical analysis of crude extract was performed to determine the presence of different kinds of phytochemicals. The antibacterial activity of plant extracts and the silver nanoparticles were then assessed using the agar well diffusion method against various pathogenic bacteria. The results showed that the plant contains several phytochemicals with remarkable antioxidant potential. The antibacterial analysis revealed that silver nanoparticles and the plant extracts exhibited a significant zone of inhibition against human pathogenic bacteria ( Escherichia coli , S. capitis , B. subtilis, and Pseudomonas aeruginosa ) as compared to the cefixime and norfloxacin. This implies that the nanoparticles have the potential to be used in nano-medicine applications, such as drug delivery systems, as well as for their antibacterial, antifungal, and antiviral activities. Additionally, the development and application of materials and technologies at the nanometer scale opens possibilities for the creation of novel drugs and therapies. Overall, the study highlights the promising potential of herbal medicinal plants found in Murree, Punjab, Pakistan, and green-synthesized silver nanoparticles in various fields of medicine and nanotechnology., 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.)

A kidney stone is a solid formation that can lead to kidney failure, severe pain, and reduced quality of life from urinary system blockages. While medical experts can interpret kidney-ureter-bladder (KUB) X-ray images, specific images pose challenges for human detection, requiring significant analysis time. Consequently, developing a detection system becomes crucial for accurately classifying KUB X-ray images. This article applies a transfer learning (TL) model with a pre-trained VGG16 empowered with explainable artificial intelligence (XAI) to establish a system that takes KUB X-ray images and accurately categorizes them as kidney stones or normal cases. The findings demonstrate that the model achieves a testing accuracy of 97.41% in identifying kidney stones or normal KUB X-rays in the dataset used. VGG16 model delivers highly accurate predictions but lacks fairness and explainability in their decision-making process. This study incorporates the Layer-Wise Relevance Propagation (LRP) technique, an explainable artificial intelligence (XAI) technique, to enhance the transparency and effectiveness of the model to address this concern. The XAI technique, specifically LRP, increases the model's fairness and transparency, facilitating human comprehension of the predictions. Consequently, XAI can play an important role in assisting doctors with the accurate identification of kidney stones, thereby facilitating the execution of effective treatment strategies., (© 2024. The Author(s).)

Dibenzyltoluene (H0-DBT), a Liquid Organic Hydrogen Carrier (LOHC), presents an attractive solution for hydrogen storage due to its enhanced safety and ability to store hydrogen in a concentrated liquid form. The utilization of machine learning proves essential for accurately predicting hydrogen storage classes in H0-DBT across diverse experimental conditions. This study focuses on the classification of hydrogen storage data into three classes, low-class, medium-class and high-class, based on the hydrogen storage capacity values. We introduce Hydrogen Storage Prediction with the Support Vector Machine (HSP-SVM) model to predict the hydrogen storage classes accurately. The performance of the proposed HSP-SVM model was investigated using various techniques, which included 5-Fold Cross Validation (5-FCV), Resubstitution Validation (RV), and Holdout Validation (HV). The accuracy of the HV approach for the low, medium, and high class was 98.5%, 97%, and 98.5%, respectively. The overall accuracy of HV approach reached 97% with a miss clarification rate of 3%, whereas 5-FCV and RV possessed an overall accuracy of 93.9% with a miss clarification rate of 6.1%. The results reveal that the HV approach is optimal for predicting the hydrogen storage classes accurately.

Objective: The aim of this study was to synthesize a new bioactive and antibacterial composite by incorporating reactive calcium phosphate and antibacterial polylysine into a resin matrix and evaluate the effect of these fillers on structural analysis, degree of monomer conversion, mechanical properties, and bioactivity of these newly developed polypropylene based dental composites., Methodology: Stock monomers were prepared by mixing urethane dimethacrylate and polypropylene glycol dimethacrylate and combined with 40 wt% silica to make experimental control (E-C). The other three experimental groups contained a fixed percentage of silica (40 wt%), monocalcium phosphate monohydrate, and β-tri calcium phosphate (5 wt% each) with varying amounts of polylysine (PL). These groups include E-CCP0 (0 wt% PL), E-CCP5 (5 wt% PL) and E-CCP10 (10 wt% PL). The commercial control used was Filtek™ Z250 3M ESPE. The degree of conversion was assessed by using Fourier transform infrared spectroscopy (FTIR). Compressive strength and Vicker's micro hardness testing were evaluated after 24 h of curing the samples. For bioactivity, prepared samples were placed in simulated body fluid for 0, 1, 7, and 28 days and were analyzed using a scanning electron microscope (SEM). SPSS 23 was used to analyze the data and one-way ANOVA and post hoc tukey's test were done, where the significant level was set ≤0.05., Results: Group E-C showed better mechanical properties than other experimental and commercial control groups. Group E-C showed the highest degree of conversion (72.72 ± 1.69%) followed by E-CCP0 (72.43 ± 1.47%), Z250 (72.26 ± 1.75%), E-CCP10 (71.07 ± 0.19%), and lowest value was shown by E-CCP5 (68.85 ± 7.23%). In shear bond testing the maximum value was obtained by E-C. The order in decreasing value of bond strength is E-C (8.13 ± 3.5 MPa) > Z250 (2.15 ± 1.1 MPa) > E-CCP10 (2.08 ± 2.1 MPa) > E-CCP5 (0.94 ± 0.8 MPa) > E-CCP0 (0.66 ± 0.2 MPa). In compressive testing, the maximum strength was observed by commercial control i.e., Z250 (210.36 ± 18 MPa) and E-C (206.55 ± 23 MPa), followed by E-CCP0 (108.06 ± 19 MPa), E-CCP5 (94.16 ± 9 MPa), and E-CCP10 (80.80 ± 13 MPa). The maximum number of hardness was shown by E-C (93.04 ± 8.23) followed by E-CCP0 (38.93 ± 9.21) > E-CCP10 (35.21 ± 12.31) > E-CCP5 (34.34 ± 12.49) > Z250 (25 ± 2.61). SEM images showed that the maximum apatite layer as shown by E-CCP10 and the order followed as E-CCP10 > E-CCP5 > E-CCP0 >Z250> E-C., Conclusion: The experimental formulation showed an optimal degree of conversion with compromised mechanical properties when the polylysine percentage was increased. Apatite layer formation and polylysine at the interface may result in remineralization and ultimately lead to the prevention of secondary caries formation., 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 Ltd. All rights reserved.)

China has changed its focus from traditional high-speed economic growth to high-quality economic development (HQED) and the implementation of environmentally friendly practices. This transition can have parallel or unparallel impacts on energy insecurity (EIS). In this regards, HQED, inter Alia, is crucial in mitigating EIS and combating the energy crisis. Our study explores the impact of economic growth (EG) and HQED on EIS using the provincial panel data of China for the period 2011-2017. From the perspective of comparative analysis, the results reveal that HQED reduces EIS while EG increases it. The robustness checks indicate that industrial structure (IS) has a negative impact on EIS, whereas industrial structure upgrading (ISU) and green innovation (GI) have a positive influence. This implies that IS contributes to an increase in EIS, whereas ISU and GI result in a decrease in EIS. In addition, the analysis reveals that digital financial inclusion (DFI) exhibits a significant positive relation with EIS, albeit occasionally a negative but insignificant link. The policy implication is that the government should stimulate policies to promote HQED which reduces the EIS., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)