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Abstract Disrupted cytokine networks and autoantibodies play an important role in the pathogenesis of systemic lupus erythematosus. However, conflicting reports and non-reproducibility have hindered progress regarding the translational potential of cytokines in SLE. This study attempts to address the existing knowledge gap using multiplex cytokine assay and machine learning. 67 SLE patients fulfilling SLICC criteria were recruited after informed consent, and circulating cytokines were measured by multiplex cytokine assay kit. We observed a positive association between actual disease activity scores (SLEDAI) and predicted scores from a partial least squares regression (PLSR) analysis of multivariate cytokine response data, with MIP-1α having a strong contribution towards disease activity. Our analysis also highlights increased IL-12 as a potential biomarker in nephritis and elevated MIP-1α as a signature of NPSLE. Using a k-Modes clustering algorithm to stratify patients based on patterns of co-occurrence of circulating autoantibodies, we identified 4 distinct clusters of patients. All 4 clusters had patients with nephritis, but patients in cluster 3 with nephritis were characterised by low levels of housekeeping and homeostatic cytokines and the presence of anti-Ro antibodies, which is a novel observation. Thus, we demonstrate that cytokines can be a surrogate to predict disease activity and organ involvement in SLE. Moreover, we show the utility of unsupervised machine learning algorithms using specific autoantibody signatures to predict renal involvement in SLE.

Abstract Background Mesenchymal stem cells (MSCs) have emerged as promising candidates for immune modulation in various diseases that are associated with dysregulated immune responses like Graft-versus-Host-Disease (GVHD). MSCs are pleiotropic and the fate of MSCs following administration is a major determinant of their therapeutic efficacy. Methods Human MSCs were derived from bone marrow (BM) and Wharton’s Jelly (WJ) and preconditioned through exposure to hypoxia and induction of apoptosis, either sequentially or simultaneously. The immune programming potential of preconditioned MSCs was evaluated by assessing their effects on T cell proliferation, induction of Tregs, programming of effector T-cell towards Th2 phenotype, macrophage polarization in the direct co-culture of MSCs and aGVHD patients-derived PBMNCs. Additionally, efferocytosis of MSCs and relative change in the expression of immunomodulatory soluble factors were examined. Results Our study demonstrated that hypoxia preconditioned apoptotic MSCs (BM-MSCs, WJ-MSCs) bear more immune programming ability in a cellular model of acute Graft-versus-Host-Disease (aGVHD). Our findings revealed that WJ-MSCsHYP+APO were superior to BM-MSCsHYP+APO for immune regulation. These induced the differentiation of CD4+T-cell into Tregs, enhanced Th2 effector responses, and simultaneously mitigated Th1- and Th17 responses. Additionally, this approach led to the polarization of M1 macrophages toward an M2 phenotype. Conclusion Our study highlights the potential of WJ-MSCs conditioned with hypoxia and apoptosis concurrently, as a promising therapeutic strategy for aGVHD. It underscores the importance of considering MSC apoptosis in optimizing MSCs-based cellular therapy protocols for enhanced therapeutic efficacy in aGvHD. Graphical Abstract

Introduction: Seroma formation following inguinal hernia surgery is a significant concern, causing considerable morbidity for patients. It can lead to prolonged hospital stays and, most devastatingly, mesh infection. Every effort should be made to reduce seroma formation, and newer techniques are being advocated to address this issue. Aim: To assess the role of pseudosac fixation during Totally Extraperitoneal (TEP) repair for direct inguinal hernia in relation to postoperative seroma formation. Materials and Methods: The present single-blinded randomised controlled study was conducted in the Department of Surgery, ABVIMS and Dr. Ram Manohar Lohia Hospital, New Delhi, India, from June 2019 to May 2021. A total of 60 patients (group A: 30 patients with pseudosac fixation; group B: 30 patients without pseudosac fixation) aged 18 years and above, presenting with direct inguinal hernia, were included. All patients underwent TEP repair. Seroma formation, postoperative pain and early recurrence were assessed in the postoperative period. Statistical analysis were performed using the Statistical Package for Social Sciences (SPSS) version 22.0. Fisher’s exact test and t-tests were employed, with a p-value of

Abstract The modern world has its foundation built on data. Data is generated all the time, and many aspects of the society and economy are built upon it. In today's world, data is employed in better decision‐making, innovation, and improving the efficiency of systems. It becomes essential to protect it from being tampered with or misused. Encryptions based on cryptographic systems are used in mainstream data protection these days. There have been newer iterations of mechanisms based on new techniques using blockchain and the zero trust model and even systems that employ fog computing along with content delivery networks. The advent of computation through quantum technologies also helped in developing data security with post‐quantum mechanisms. The critical conditions for the working of these mechanisms hinder their adoption primarily. This also leads current systems to lack one or more of these technologies. Thus, the importance of a unified system that can employ quantum technologies effectively becomes prominent and requires a definitive investigation. In this article, a Quantum‐IoT‐based data protection scheme that can be of value to Industry 4.0 is analyzed. Light is also shed on innovations in quantum computing that can help solve not just current problems but also the future.

Abstract The present study comprehensively investigated the fermentation process of fresh dates pulp to alcoholic beverage, analyzing various aspects including physicochemical properties, nutraceutical potential, amino acid composition, color properties, sensory evaluation, and microbial load. Over the fermentation period, the alcohol content of the beverage reached 8.79%, suggesting it is an off-dry wine. Total Soluble Solids (TSS) decreased from an initial 24.17°Brix to 5°Brix. The pH level dropped from 7 to 3.9, and the titratable acidity increased from 0.15 to 0.22%. The nutraceutical potential of the alcoholic beverage displayed dynamic transformations, with total phenolic content (TPC) decreasing from 23 to 9 mg GAE mL−1, while total flavonoid content (TFC) increased significantly (p 0.05) between the alcoholic beverage and juice in terms of color, but the alcoholic beverage scored higher in appearance, flavor, texture, taste, mouthfeel, and overall acceptability.Microbial load increased from an initial 5–6 log CFU mL−1 to 8–9 log CFU mL−1 after 5 days, indicating the occurrence of alcoholic fermentation. Kinetics study was also performed for different quality parameters. This is the first study provides a comprehensive understanding of the multifaceted changes occurring during the fermentation process, offering valuable insights for winemakers and researchers. Graphical Abstract

ABSTRACT Respiratory tract infections are the most common triggers for heart failure in elderly people. The healthy respiratory commensal microbiota can prevent invasion by infectious pathogens and decrease the risk of respiratory tract infections. However, upper respiratory tract (URT) microbiome in the elderly is not well understood. To comprehend the profiles of URT microbiota in the elderly, and the link between the microbiome and heart failure, we investigated the oropharyngeal (OP) microbiome of these populations in Heilongjiang Province, located in the North-East of China, a high-latitude and cold area with a high prevalence of respiratory tract infection and heart failure. Taxonomy-based analysis showed that six dominant phyla were represented in the OP microbial profiles. Compared with young adults, the OP in the elderly exhibited a significantly different microbial community, mainly characterized by highly prevalent Streptococcus, unidentified_Saccharibacteria, Veillonella, unidentified_Pre votellaceae, and Neisseria. While unidentified_Prevotellaceae dominated in the young OP microbiome. There was competition for niche dominance between Streptococcus and member of Prevotellaceae in the OP. Correlation analysis revealed that the abundance of unidentified_Saccharibacteria was positive, while Streptococcus was negatively correlated to age among healthy elderly. The bacterial structure and abundance in the elderly with heart failure were much like healthy controls. Certain changes in microbial diversity indicated the potential OP microbial disorder in heart failure patients. These results presented here identify the respiratory tract core microbiota in high latitude and cold regions, and reveal the robustness of OP microbiome in the aged, supplying the basis for microbiome-targeted interventions.IMPORTANCETo date, we still lack available data on the oropharyngeal (OP) microbial communities in healthy populations, especially the elderly, in high latitude and cold regions. A better understanding of the significantly changed respiratory tract microbiota in aging can provide greater insight into characteristics of longevity and age-related diseases. In addition, determining the relationship between heart failure and OP microbiome may provide novel prevention and therapeutic strategies. Here, we compared OP microbiome in different age groups and elderly people with or without heart failure in northeastern China. We found that OP microbial communities are strongly linked to healthy aging. And the disease status of heart failure was not a powerful factor affecting OP microbiome. The findings may provide basic data to reveal respiratory bacterial signatures of individuals in a cold geographic region.

Abstract Freezing of gait (FOG) is a debilitating problem that markedly impairs the mobility and independence of 38-65% of people with Parkinson’s disease. During a FOG episode, patients report that their feet are suddenly and inexplicably “glued” to the floor. The lack of a widely applicable, objective FOG detection method obstructs research and treatment. To address this problem, we organized a 3-month machine-learning contest, inviting experts from around the world to develop wearable sensor-based FOG detection algorithms. 1,379 teams from 83 countries submitted 24,862 solutions. The winning solutions demonstrated high accuracy, high specificity, and good precision in FOG detection, with strong correlations to gold-standard references. When applied to continuous 24/7 data, the solutions revealed previously unobserved patterns in daily living FOG occurrences. This successful endeavor underscores the potential of machine learning contests to rapidly engage AI experts in addressing critical medical challenges and provides a promising means for objective FOG quantification.

This study examines the heat and mass transfer aspects of the natural convective flow of a nanofluid along a vertical flat surface, incorporating electrified nanoparticles and electric Reynolds number. While conventional nanofluid models like Buongiorno’s model overlook the nanoparticle electrification and electric Reynolds number mechanisms, this study addresses the nanoparticle electrification and electric Reynolds number mechanisms by justifying its relevance, particularly when tribo-electrification results from Brownian motion. This incorporation of the electric Reynold number and nanoparticle electrification mechanism is a unique aspect of this investigation. Using the similarity method and nondimensionalization, the governing partial differential equations of the flow are transformed into a set of locally similar equations. MATLAB's bvp4c solver is employed to solve this set of equations, along with the boundary conditions. The obtained results are validated by comparison with those from previously published works. Graphical representations are provided for the numerical outcomes of non-dimensional velocity, concentration and temperature concerning the nanoparticle electrification parameter and electric Reynolds number. The combined effects of the nanoparticle electrification parameter and the electric Reynolds number on non-dimensional heat and mass transfer coefficients are examined in tabular form. Furthermore, the impact of the nanoparticle electrification parameter on both heat and mass transfer for varying values of the Brownian motion parameter is explored graphically. The primary finding of this investigation indicates that the electrification mechanism of nanoparticles quickens the transfer of heat and mass from a flat surface to nanofluid, suggesting promising prospects for utilization in cooling systems and biomedical applications.

Abstract Cell stiffness is regulated by dynamic interaction between ras-related C3 botulinum toxin substrate 1 (Rac1) and p21 protein-activated kinase 1 (PAK1) proteins, besides other biochemical and molecular regulators. In this study, we investigated how the Placental Growth Factor (PlGF) changes endometrial mechanics by modifying the actin cytoskeleton at the maternal interface. We explored the global effects of PlGF in endometrial stromal cells (EnSCs) using the concerted approach of proteomics, atomic force microscopy (AFM), and electrical impedance spectroscopy (EIS). Proteomic analysis shows PlGF upregulated RhoGTPases activating proteins and extracellular matrix organization-associated proteins in EnSCs. Rac1 and PAK1 transcript levels, activity, and actin polymerization were significantly increased with PlGF treatment. AFM further revealed an increase in cell stiffness with PlGF treatment. The additive effect of PlGF on actin polymerization was suppressed with siRNA-mediated inhibition of Rac1, PAK1, and WAVE2. Interestingly, the increase in cell stiffness by PlGF treatment was pharmacologically reversed with pravastatin, resulting in improved trophoblast cell invasion. Taken together, aberrant PlGF levels in the endometrium can contribute to an altered pre-pregnancy maternal microenvironment and offer a unifying explanation for the pathological changes observed in conditions such as pre-eclampsia (PE).

Water contamination is a global concern as a result of growing industrialization and urbanization. Dye waste produced by numerous industries pollutes the water, so dye-based wastewater is a major alarm for animals, human health, and the environment. The elimination of these dye contaminants from water supplies is currently critical and significant due to the dyes' toxicity on humans, livestock, and plants. To remove/degrade dyes, various methods have been investigated, including extraction, absorption, membrane separation, coagulation, adsorption, biological treatment, and advanced oxidation process (AOPs). Graphitic carbon nitride (g-C3N4), a captivating formed polymer, has been transformed as an intriguing issue in AOP science because of its metal-free advantages and its high sensitivity to light. Accordingly, when AOPs are joined with g-C3N4, superb dye degradation has occurred. This paper overviewed the g-C3N4-based AOPs are discussed for dye removal. The synergist effectiveness and mechanisms behind catalytic activity of g-C3N4-based catalysts are broadly discussed. In the meantime, the impacts of pH, water temperature, dissolved oxygen, initial dye concentration, catalyst dosage, and scavengers on the reaction carried out by g-C3N4-based catalysts are illustrated.

The present study endeavours to substantially contribute towards alleviating the global water scarcity problem. The task entailed designing a computational model of a renewable energy-based evaporator. Using ANSYS Fluent, the CFD simulations of a three-dimensional conventional continuous single slope, single basin solar still were carried out in summer at 23.79°N, 86.43°E coordinates. With the optimized inclination condensation angle of 29° and water depth at 1 cm, the solar still recorded the highest hourly drinking water, about 1.5 kg m−2, at 11:00 h. The continuous production resulted in a water collection rate of 8.6 kg m−2 day −1, encompassing the production of all previous models. Additionally, compared with the literature correlation for solar still simulated mass, the Power model calculation was the closest, with a 12.4% variation. Furthermore, the study showcases that CFD is an economical, efficient, and easily diagnosable technique for designing solar stills.

Sharing accurate and lossless images with higher quality through digital mediums is challenging, particularly, images shared on social media platforms can serve as good carriers for sending hidden data. However, social media platforms apply severe compression when transferring images end-to-end to serve efficient network transporting bandwidth and provide enough storage space to the users. Within the scope of this research, the proposed method introduces a novel approach by combining cryptographic and steganographic techniques, providing a robust solution to protect hidden data even when subjected to repeatedly compression. The method first encrypts the secret data to be hidden using the Advanced Encryption Standard Cipher Block Chaining (AES-CBC) technique. Then, data hiding is performed on the coefficients obtained by applying Discrete Cosine Transform (DCT) to repeatedly compressed JPEG images, coefficients that are minimally affected by compression or remain unaffected are specifically selected for data hiding. Therefore, secret data is extracted with high accuracy. Experimental results show that the proposed method outperforms the state-of-the-art in achieving robust and effective data hiding techniques based on bit error rate.

Introduction: Guselkumab is an interleukin 23p19 inhibitor, and the first in this group, to be approved by the US Food and Drug Administration (FDA) for the management of moderate to severe psoriasis. Apart from its utility in psoriasis, there are a number of other dermatologic conditions where guselkumab has demonstrated value. Objectives: The aim of this narrative review is to describe the utility of guselkumab in psoriasis as well as its implication in off-label dermatologic disorders. Methods: Pubmed, Google Scholar, Scopus and ResearchGate were searched for scholarly articles related to guselkumab and its utility in dermatology using the search terms “Guselkumab” AND “Psoriasis” AND “other dermatological disorders”. Results: Guselkumab is a valuable biologic agent for the management of psoriasis and psoriatic arthropathy. It has also been used successfully for other dermatologic disorders like hidradenitis suppurativa, lichen planus, pityriasis rubra pilaris and pyoderma gangrenosum. Recently, its utility in Stewart-Treves angiosarcoma (STA) has been exemplified. Conclusion: Guselkumab’s usage is not limited to psoriasis. Its benefit extends to many more dermatologic conditions. Its utility in STA could open an avenue for its application in the field of oncology. Furthermore, it has an acceptable safety profile.

Background Baseline anemia is associated with poor intracerebral hemorrhage (ICH) outcomes. However, underlying drivers for anemia and whether anemia development after ICH impacts clinical outcomes are unknown. We hypothesized that inflammation drives anemia development after ICH and assessed their relationship to outcomes. Methods and Results Patients with serial hemoglobin and iron biomarker concentrations from the HIDEF (High‐Dose Deferoxamine in Intracerebral Hemorrhage) trial were analyzed. Adjusted linear mixed models assessed laboratory changes over time. Of 42 patients, significant decrements in hemoglobin occurred with anemia increasing from 19% to 45% by day 5. Anemia of inflammation iron biomarker criteria was met in 88%. A separate cohort of 521 patients with ICH with more granular serial hemoglobin and long‐term neurological outcome data was also investigated. Separate regression models assessed whether (1) systemic inflammatory response syndrome (SIRS) scores related to hemoglobin changes over time and (2) hemoglobin changes related to poor 90‐day outcome. In this cohort, anemia prevalence increased from 30% to 71% within 2 days of admission yet persisted beyond this time. Elevated systemic inflammatory response syndrome was associated with greater hemoglobin decrements over time (adjusted parameter estimate: −0.27 [95% CI, −0.37 to −0.17]) and greater hemoglobin decrements were associated with poor outcomes (adjusted odds ratio per 1 g/dL increase, 0.76 [95% CI, 0.62–0.93]) independent to inflammation and ICH severity. Conclusions We identified novel findings that acute anemia development after ICH is common, rapid, and related to inflammation. Because anemia development is associated with poor outcomes, further work is required to clarify if anemia, or its underlying drivers, are modifiable treatment targets that can improve ICH outcomes. Registration https://www.clinicaltrials.gov Unique identifier: NCT01662895

Background. Musculoskeletal diseases like osteoarthritis (OA) are widespread. OA affects the knees, makes the joints wear out and hurt, and makes it hard to move around. Body mass index (BMI) is a way to measure obesity, which is linked to a higher chance of getting OA and making it worse. The main aim of this cross-sectional study was to find out how body mass index (BMI) is related to how lousy knee osteoarthritis is. Methods. One hundred people at the Shri Guru Ram Rai Institute of Medical and Health Sciences in Dehradun met the study’s requirements and were enrolled. The Kellgren-Lawrence grading method was used to find the severity of knee osteoarthritis (OA), and standard measurements were used to calculate body mass index (BMI). A correlation study was done to examine the link between BMI and the severity of OA. Results. The sample included 100 participants on average of 60 years old. The typical knee OA symptoms lasted five years. A body mass index distribution analysis showed 35% obese, 40% overweight, and 25% underweight or average weight. Twenty percent of knee OA patients were mild, 35 percent intermediate, 30 percent severe, and 15 percent progressed. The association investigation revealed a significant positive correlation between BMI and knee osteoarthritis severity (r = 0.65, p < 0.001). Conclusion. Our results show that being overweight can worsen knee OA, proving that people with this problem need to watch their weight. If we treat obesity as a risk factor that can be changed, we might be able to improve the results of OA.

The Cosmos blockchain is a decentralized network of independent blockchains that addresses scalability and interoperability difficulties in blockchain architecture. Through the use of the Tendermint consensus mechanism and the Inter-Blockchain Communication (IBC) protocol, the Cosmos blockchain enables transactions that are both safe and smooth across a variety of blockchain platforms. One of the most important aspects of its design is the Atom token, which is responsible for ensuring the safety and governance of the network and, as a result, improving interactions across different chains. This comprehensive study covers various topics, including analyzing the techniques that facilitate communication between different blockchain systems. Exploring the subtleties of Cosmos blockchain’ architecture and assessing the usefulness and efficiency of the system through a review of transaction data and Atom token volume in the cryptocurrency market. The results contribute to the discussion on blockchain interconnectivity by highlighting the Cosmos blockchain’s potential to revolutionize engagement with distributed ledger technologies. The study also emphasizes the Cosmos blockchain’s strategic importance in developing blockchain ecosystems and their impact on digital commerce and governance.

It is now essential to ensure security because of the enormous volumes of data being exchanged. Particularly, images are very vulnerable to encryption flaws. Therefore, it is imperative to provide robust security mechanisms for image data. Conventional image encryption methods secure the privacy of necessary information by converting it into noise-like, encrypted ciphertext images that completely obscure visual content. However, the main drawback of this method is that it almost eliminates visual usability in the cloud. Thumbnail-preserving encryption (TPE) was created to solve this problem by retaining the image’s thumbnail appearance even after encryption, providing a compromise between privacy and usability. Aspiring researchers should use this review to understand TPE schemes thoroughly. In this survey, the objectives, benefits, and drawbacks of several methods are examined with an emphasis on image privacy and usability. Notable TPE applications and evaluation metrics are also highlighted in the review. These metrics are grouped into categories such as quality, encryption key, security, and resilience to different kinds of attacks. In addition, a characterization of TPE schemes is provided, along with a comparison and summary of each scheme’s contributions. In addition, we list the open research questions and difficulties that must be resolved to guarantee secure TPE for real-time applications.

In today’s digital landscape, maintaining the integrity and ownership of digital content is crucial across various fields, including the critical domain of medical applications. However, existing watermarking techniques face significant challenges, such as vulnerability to attacks and limitations in capacity and robustness. To address these challenges, this work presents a novel hybrid reversible watermarking approach utilizing the Lucas number series (LNS), normalization, and squint ternary least significant bit (STLSB). Additionally, the method incorporates a lightweight encryption technique based on homomorphic binomial coefficients (LHBC) to encrypt watermark images. The encrypted image is then embedded into the cover image at the STLSB position, specifically three bits from the left-most significant bit, resulting in a watermarked image. The Present issues in watermarking medical data include ensuring the watermark’s robustness against attacks while maintaining data integrity and confidentiality, and balancing the need for traceability with the risk of compromising sensitive patient information. Experimental results show that the proposed method significantly improves embedding capacity by approximately 10% compared to existing techniques, achieving a PSNR of 52.0 dB, NCC of 1, SSIM of 0.9967, and consistently low BER, demonstrating enhanced robustness against various attacks, including JPEG compression, sharpening, resizing, and rotation. These findings highlight the method’s effectiveness for secure medical image watermarking applications, ensuring integrity and confidentiality, and extending to practical uses in digital asset management, copyright protection, and authentication systems across diverse industries.

With recent advances in technology protecting sensitive healthcare data is challenging. Particularly, one of the most serious issues with medical information security is protecting of medical content, such as the privacy of patients. As medical information becomes more widely available, security measures must be established to protect confidentiality, integrity, and availability. Image steganography was recently proposed as an extra data protection mechanism for medical records. This paper describes a data-hiding approach for DICOM medical pictures. To ensure secrecy, we use Adversarial Neural Cryptography with SHA-256 (ANC-SHA-256) to encrypt and conceal the RGB patient picture within the medical image’s Region of Non-Interest (RONI). To ensure anonymity, we use ANC-SHA-256 to encrypt the RGB patient image before embedding. We employ a secure hash method with 256bit (SHA-256) to produce a digital signature from the information linked to the DICOM file to validate the authenticity and integrity of medical pictures. Many tests were conducted to assess visual quality using diverse medical datasets, including MRI, CT, X-ray, and ultrasound cover pictures. The LFW dataset was chosen as a patient hidden picture. The proposed method performs well in visual quality measures including the PSNR average of 67.55, the NCC average of 0.9959, the SSIM average of 0.9887, the UQI average of 0.9859, and the APE average of 3.83. It outperforms the most current techniques in these visual quality measures (PSNR, MSE, and SSIM) across six medical assessment categories. Furthermore, the proposed method offers great visual quality while being resilient to physical adjustments, histogram analysis, and other geometrical threats such as cropping, rotation, and scaling. Finally, it is particularly efficient in telemedicine applications with high achieving security with a ratio of 99% during remote transmission of Electronic Patient Records (EPR) over the Internet, which safeguards the patient’s privacy and data integrity.

Rising urbanization necessitates robust air quality monitoring and prediction systems, particularly in developing nations like India, to mitigate adverse health impacts. Previous research primarily focused on machine learning algorithms for Air Quality Index (AQI) prediction and classification. We propose a novel MI-MMA-XGB which coupled features of multimodal imputer(MI) with the features of multi-modal autoencoder (MMA) and fed to an XGBoost(XGB) algorithm for AQI prediction and classification. Moreover, imputation approaches namely, KNN, MICE, and SVD were employed to address problems with null values and outliers. Furthermore, SMOTE is employed to balance the imputed data and then the model was trained on both balanced and unbalanced imputed data to extract predictive features. In this process, our model MI-MMA-XGB achieves significant accuracy, reaching 97.14% and 93.87% with and without SMOTE, respectively. Additionally, it attains an $R^{2}$ score of 0.9578 and an RMSE of 0.203 for AQI prediction in Indian cities. The proposed model outperforms baseline models in both classification and regression tasks across various evaluation metrics.

Introduction: Indoor Air Pollution (IAP) is a serious problem, especially in enclosed environments where humans are present for a long period. Similar enclosed environments can be seen in educational Institutions, where employees and students spend much of their time. The objective of this research is to assess the Indoor Air Quality (IAQ) of engineering Institute's laboratories. Materials and methods: The sample of Indoor Air Pollutants (IAPs) such as Particulate Matters (PM1.0, PM2.5, PM10), Total Volatile Organic Compounds (TVOC), Formaldehyde (HCHO), and Carbon dioxide (CO2) were obtained by using a portable air quality meter from 12 different laboratories during July 2021 to September 2021 from 10:00 to 17:00. The statistical analysis was performed to interpret the outcomes. Results: As a result, the higher concentration of PM1.0, PM2.5, PM10, TVOC, HCHO, and CO2 was observed in ML11, ML2, ML12, ML5 and ML4. The correlation analysis shows that all laboratories, with the exception of ML4, ML5, ML9, and ML11, show good positive correlation for Particulate Matter (PM) of all sizes (R2>0.90). Additionally, ML6 and ML9 exhibited a strong positive association (R2 >0.78) for TVOC, ML4 and ML8 for HCHO (R2>0.68), and ML3 and ML10 for CO2(R2>0.66). In addition, cluster analysis was performed on the datasets to group them into similar source categories. As a result, 3, 2, 2, 4, 3, and 3 clusters for PM1.0, PM2.5, PM10, TVOC, HCHO, and CO2 are extracted. Conclusion: Overall, it appears that the presence of IAPs is caused by nearby outdoor activities, sweeping and dusting, wood furniture, paints, and poor ventilation in laboratories.

This review aims to examine the existence of Pseudomonas aeruginosa (P. aeruginosa) and their antibiotic resistance genes (ARGs) in aquatic settings and the alternative treatment ways. P. aeruginosa in a various aquatic environment have been identified as contaminants with impacts on human health and the environment. P. aeruginosa resistance to multiple antibiotics, such as sulfamethoxazole, ciprofloxacin, quinolone, trimethoprim, tetracycline, vancomycin, as well as specific antibiotic resistance genes including sul1, qnrs, blaVIM, blaTEM, blaCTX, blaAIM-1, tetA, ampC, blaVIM. The development of resistance can occur naturally, through mutations, or via horizontal gene transfer facilitated by sterilizing agents. In addition, an overview of the current knowledge on inactivation of Pseudomonas aeruginosa and ARG and the mechanisms of action of various disinfection processes in water and wastewater (UV chlorine processes, catalytic oxidation, Fenton reaction, and ozonation) is given. An overview of the effects of nanotechnology and the resulting wetlands is also given.

Purpose: The head and neck cancer (HNC) literature is rife with reports of differences in planned versus actual radiation doses to the parotid gland (PG) due to changes in anatomy during the course of radiation therapy. We prospectively studied and quantified changes in planned and delivered doses due to weight loss and changes in lateral neck dimensions. Methods and Materials: Sixty patients were enrolled in this prospective non-randomized observational study. The inclusion criterion was having a newly diagnosed, histologically proven squamous cell carcinoma of HNC. Weight loss (WL) and change in lateral neck dimensions (LND) were assessed weekly, and new hybrid plans were generated using interval replanning CT scans. Dose variations were monitored and extrapolated for replanning CT scans and correlated with WL and change in LND. Results: The Pearson correlation coefficients for WL and difference in Dmean of ipsilateral and contralateral PG was 0.3292 (P = .0124) and 0.4232 (P = .0010), respectively. There was significantly higher change in the Dmean of bilateral PG (Ipsilateral(I) > contralateral(C)) in patients who experienced WL of >5%. Change in LND correlated with difference in Dmean of ipsilateral PG at 0.4829 (P = .0001) and difference in D50 at 0.4146 (P < .0013). Contralateral PG correlated with difference in Dmean at 0.5952 (P < .0001). The difference in Dmean for ipsilateral PG was 1.8535 Gy for those showing reduction in LND of >1 cm compared with 0.8596 Gy (P = .0091) for those who had ≤1 cm reduction in LND. Conclusions: Either WL of >5% or reduction in LND of >1 cm can be used as an external parameter to help select patients who might benefit most from replanning and adaptive radiation therapy.

Introduction The propensity of nucleotide bases to form pairs, causes folding and the formation of secondary structure in the RNA. Therefore, purine (R): pyrimidine (Y) base-pairing is vital to maintain uniform lateral dimension in RNA secondary structure. Transversions or base substitutions between R and Y bases, are more detrimental to the stability of RNA secondary structure, than transitions derived from substitutions between A and G or C and T. The study of transversion and transition base substitutions is important to understand evolutionary mechanisms of RNA secondary structure in the 5′ and 3′ untranslated (UTR) regions of SARS-CoV-2. In this work, we carried out comparative analysis of transition and transversion base substitutions in the stem and loop regions of RNA secondary structure of SARS-CoV-2. Methods We have considered the experimentally determined and well documented stem and loop regions of 5′ and 3′ UTR regions of SARS-CoV-2 for base substitution analysis. The secondary structure comprising of stem and loop regions were visualized using the RNAfold web server. The GISAID repository was used to extract base sequence alignment of the UTR regions. Python scripts were developed for comparative analysis of transversion and transition frequencies in the stem and the loop regions. Results The results of base substitution analysis revealed a higher transition (ti) to transversion (tv) ratio (ti/tv) in the stem region of UTR of RNA secondary structure of SARS-CoV-2 reported during the early stage of the pandemic. The higher ti/tv ratio in the stem region suggested the influence of secondary structure in selecting the pattern of base substitutions. This differential pattern of ti/tv values between stem and loop regions was not observed among the Delta and Omicron variants that dominated the later stage of the pandemic. It is noteworthy that the ti/tv values in the stem and loop regions were similar among the later dominant Delta and Omicron variant strains which is to be investigated to understand the rapid evolution and global adaptation of SARS-CoV-2. Conclusion Our findings implicate the lower frequency of transversions than the transitions in the stem regions of UTRs of SARS-CoV-2. The RNA secondary structures are associated with replication, translation, and packaging, further investigations are needed to understand these base substitutions across different variants of SARS-CoV-2.

The discovery of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) technology has revolutionized field of cancer treatment. This review explores usage of CRISPR/Cas9 for editing and investigating genes involved in human carcinogenesis. It provides insights into the development of CRISPR as a genetic tool. Also, it explores recent developments and tools available in designing CRISPR/Cas9 systems for targeting oncogenic genes for cancer treatment. Further, we delve into an overview of cancer biology, highlighting key genetic alterations and signaling pathways whose deletion prevents malignancies. This fundamental knowledge enables a deeper understanding of how CRISPR/Cas9 can be tailored to address specific genetic aberrations and offer personalized therapeutic approaches. In this review, we showcase studies and preclinical trials that show the utility of CRISPR/Cas9 in disrupting oncogenic targets, modulating tumor microenvironment and increasing the efficiency of available anti treatments. It also provides insight into the use of CRISPR high throughput screens for cancer biomarker identifications and CRISPR based screening for drug discovery. In conclusion, this review offers an overview of exciting developments in engineering CRISPR/Cas9 therapeutics for cancer treatment and highlights the transformative potential of CRISPR for innovation and effective cancer treatments.

Background: Peyronie’s disease (PD) is a localized fibrosis of tunica albuginea, which causes the anatomical and functional changes to the penis. Corporoplasty with grafting is indicated in severe (>60°) and complex curvature. Buccal mucosa is the most favored autologous graft material nowadays. The ventrolateral aspect of lingual mucosa has similar histological features to the rest of the oral cavity. Methods: This study aimed to test the efficacy, safety, durability, and reproducibility of corporoplasty with lingual mucosal graft (LMG) in the surgical treatment of PD in terms of surgical outcome, sexual function, and donor site complications. This prospective study included 19 patients of PD with severe and complex curvature, who underwent corporoplasty with LMG. Surgical and functional outcomes were assessed at follow-up planned at 2 weeks, 3 months, 6 months, 1 year, and 2 years. Results: The mean operative time was 126.31 ± 21.45 min. Additional Nesbit’s plication to correct the residual deformity was required in 26% (5 / 19) of patients. Straightening of the penis (curvature 1 cm) postoperatively was achieved in 63% (12 / 19) of patients and a shortening of penis occurred in 5% (1 / 19) of patients. Newer onset erectile dysfunction developed in 11% (2 / 19) of patients, and patient and partner satisfaction rates were 89% (17 / 19) and 84% (16 / 19), respectively, in a mean follow-up of 20.66 ± 5.37 months. Donor site complications were minimal and no patient had any salivary changes or speech disturbances. Conclusion: LMG provided excellent short-term results in terms of deformity correction, improved sexual function, and minimal donor site morbidity. The method is simple and reproducible, and multicenter studies with larger number of cases with longer follow-up are required to confirm these favorable results.

Objective: This article presents a study comparing the responses of two AI chatbots, ChatGPT and ChatSonic, regarding inquiries about epilepsy. Overall, ChatGPT and ChatSonic are very similar in terms of their capabilities and limitations and they are the most widely used AI software. However, there are some key differences, such as their training data, supported languages, and pricing model. The study aims to assess the potential application of AI in patient counseling and decision-making regarding epilepsy treatment. Methods: The study categorized the inquiries of patients about epilepsy into two groups: patient counseling and judgment. Ten questions were formulated within these categories. Two specialized doctors evaluated the reliability and accuracy of the chatbot replies using the Global Quality Scale (GQS) and a modified version of the DISCERN score. Results: The median value for GQS of 4.5 was given by Evaluator JC, and a median value for GQS of 4.0 was given by Evaluator VV. Furthermore, a median for RS of 5.0 was given by Evaluator JC, and a median for RS of 4.0 was given by Evaluator VV. The GQS data from Evaluators JC and VV have a Spearman correlation coefficient of -0.531, indicating an inversely proportional association, and a p-value of 0.016, indicating a statistically significant relationship between the variables. However, the correlation coefficient of RS between data by Evaluator JC and Evaluator VV is 0.368 which indicates the correlation is a directly proportional relationship, with a p-value of 0.110 which is not statistically significant, does not establish a relation between the variables. Weighted Kappa was used to study the agreement between the data. With a weighted kappa value of -0.318 and a 95 %CI of -0.570, -0.065 was obtained for GQS. This can help reject the null hypothesis indicating that the values by the Evaluator JC and Evaluator VV are statistically significant and has a negative agreement. However, a weighted kappa value of 0.1327 with a 95 %CI of -0.093, 0.359 obtained for RS, fails to reject the null hypothesis indicating that the values by the Evaluator JC and Evaluator VV are not significant and no agreement exists between the Evaluators. The results of this study suggest that both ChatGPT and ChatSonic have the potential to be valuable tools for epilepsy patients and their healthcare providers. However, it is important to note that the two evaluators had better agreement on the GQS scores than on the RS scores, suggesting that the GQS may be a more reliable measure of the quality of chatbot responses. Conclusion: The findings underscore the importance of collaboration among policymakers, healthcare professionals, and AI designers to ensure appropriate and safe utilization of AI chatbots in the healthcare domain. While AI chatbots can provide valuable information, it is crucial to acknowledge their limitations, including reliance on the training data and occasional factual errors. The study highlights the need for further testing and validation of AI language models in the management of epilepsy as it concludes.

In the digital age, where information is a cornerstone for decision-making, social media's not-so-regulated environment has intensified the prevalence of fake news, with significant implications for both individuals and societies. This study employs a bibliometric analysis of a large corpus of 9678 publications spanning 2013–2022 to scrutinize the evolution of fake news research, identifying leading authors, institutions, and nations. Three thematic clusters emerge: Disinformation in social media, COVID-19-induced infodemics, and techno-scientific advancements in auto-detection. This work introduces three novel contributions: 1) a pioneering mapping of fake news research to Sustainable Development Goals (SDGs), indicating its influence on areas like health (SDG 3), peace (SDG 16), and industry (SDG 9); 2) the utilization of Prominence percentile metrics to discern critical and economically prioritized research areas, such as misinformation and object detection in deep learning; and 3) an evaluation of generative AI's role in the propagation and realism of fake news, raising pressing ethical concerns. These contributions collectively provide a comprehensive overview of the current state and future trajectories of fake news research, offering valuable insights for academia, policymakers, and industry.

ABSTRACTEscherichia coli is a highly versatile microorganism with a unique ability to survive and persist in varied niches of the human and animal hosts and the environment. While commensal strains of E. coli play a crucial role in preserving and maintaining the balance and function of their community within the gut microflora, pathogenic strains are often implicated in a wide range of infections and outbreaks, posing a serious threat to public health systems. With the increasing burden of highly virulent and antimicrobial-resistant E. coli infections, it is imperative to understand the host-defense mechanisms of bacteria from all possible dimensions. Mobile genetic elements (MGE)-mediated acquisition of genetic material, chromosomal reduction, and genome optimization are three important events that play a significant role in bacterial evolution and enable them to survive in diverse environmental niches. Toxin-antitoxin (TA) systems are genetic elements that help in the maintenance of MGEs and are often associated with stress response phenotypes, including antimicrobial resistance. In this study, large-scale comparative genomics of 950 genomes spanning 19 different sequence types (STs) (eight phylogroups) revealed ST-wide prevalence patterns of TA systems with a median of 23 toxin groups per strain. Our analyses revealed significant genomic reduction in the members of phylogroup B2 (ST131, ST95, ST73, ST12, and ST127) and phylogroup C (ST410) as evident from a diminished toxin repertoire amidst abundant orphan antitoxins. Moreover, our observations also enabled crucial insights into the copy number of toxin groups, the genetic organization of TA operons, and their association with other genetic coordinates (antimicrobial resistance encoding genes/virulence genes/mobile genetic elements). By unraveling the association of the genetic coordinates/STs with the toxin groups, this study significantly boosts our understanding of the functional implications of TA systems in different evolutionary contexts entailing pathogenic Escherichia.IMPORTANCELarge-scale genomic studies of E. coli provide an invaluable opportunity to understand how genomic fine-tuning contributes to the transition of bacterial lifestyle from being commensals to mutualists or pathogens. Within this context, through machine learning-based studies, it appears that TA systems play an important role in the classification of high-risk clonal lineages and could be attributed to their epidemiological success. Due to these profound indications and assumptions, we attempted to provide unique insights into the ordered world of TA systems at the population level by investigating the diversity and evolutionary patterns of TA genes across 19 different STs of E. coli. Further in-depth analysis of ST-specific TA structures and associated genetic coordinates holds the potential to elucidate the functional implications of TA systems in bacterial cell survival and persistence, by and large.