Pericardial fluid troponin in cardiac surgery.

BACKGROUND AND OBJECTIVE: Pericardial Fluid (PF) is a rich reservoir of biologically active factors. Due to its proximity to the heart, the biochemical structure of PF may reflect the pathological changes in the cardiac interstitial environment. This manuscript aimed to determine whether the PF level of cardiac troponins changes in patients undergoing cardiac surgery. METHODS: This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Medline, EMBASE, Cochrane, ClinicalTrials.gov, and Google Scholar databases were electronically searched for primary studies using the keywords "pericardial fluid," "troponin," and "cardiac surgery." The primary outcome of interest was changes in troponin levels within the PF preoperatively and postoperatively. Secondary outcomes of interest included comparisons between troponin level changes in the PF compared to plasma. RESULTS: A total of 2901 manuscripts were screened through a title and abstract stage by two independent blinded reviewers. Of those, 2894 studies were excluded, and the remaining seven studies underwent a full-text review. Studies were excluded if they did not provide data or failed to meet inclusion criteria. Ultimately, six articles were included that discussed cardiac troponin levels within the PF in patients who had undergone cardiac surgery. Pericardial troponin concentration increased over time after surgery, and levels were significantly higher in PF compared to serum. All studies found that the type of operation did not affect these overall observations. CONCLUSION: Our review of the literature suggest that the PF level of cardiac troponins increases in patients undergoing cardiac surgery, irrespective of the procedure type. However, these changes' exact pattern and clinical significance remain undefined.

Plexin B2 tissue expression and related gene polymorphisms in psoriasis and their relation to NB-UVB and Acitretin therapy.

Psoriasis is a chronic, immune-mediated, hyperproliferative skin disease. Etiopathogenesis of psoriasis is not well understood. Plexin B2 was found to have effects on CD100-mediated T-cell morphology and expressed in the immune system. It may play a role in the pathogenesis of psoriasis. To assess the tissue level of plexin-B2 and plexin B2 related gene polymorphism which is signal regulatory protein gamma (SIRPγ-rs71212732) in psoriatic patients before and after NB-UVB, acitretin therapy alone or in combination and to detect correlation between level of tissue plexin B2 and disease severity and improvement. This single blinded randomized controlled trial was carried on 50 psoriatic patients and 50 healthy controls. Psoriasis Area and Severity Index score (PASI) was used to evaluate the disease severity. Tissue plexin-b2 level was measured using ELISA and SIRPγ-rs71212732 (T\C) was assessed using TaqMan™ assays and real-time PCR. A significant lower tissue plexin-B2 level was observed in control group (2.9 ± 0.6 pg/g) than cases (25.8 ± 2.8, pg/g) (p < 0.001). Also, a significantly higher tissue plexin-B2 level was observed in sever psoriasis (32.7 ± 3.8 pg/ml) in than moderate psoriasis (13.6 ± 2.1 pg/ml, p = 0.001). Tissue plexin B2 was positively correlated with diseases severity. Significantly higher (TC& TT) genotypes and mutant (C) allele among patients compared to the controls, p < 0.001 for all. Tissue plexin-b2 level was high in psoriasis vulgaris with positive correlation with disease severity and decreased after treatment. This may indicate a role of plexin-b2 in psoriasis vulgaris pathogenesis.

Using Inspiratory Muscle Training to Improve Respiratory Strength, Functional Capacity, Fatigue, and Stress in Breast Cancer Patients Undergoing Surgery.

Purpose: The main aim of the trial was to assess the effectiveness of inspiratory muscle training on respiratory muscle strength, functional capacity, fatigue, and stress in post-surgical breast cancer survivors. Methods: Forty-seven females who had undergone unilateral post-mastectomy were randomly assigned to an intervention group (IG; n = 24) and a control group (CG; n = 23). Both groups received aerobic exercise training. In addition, the intervention group received inspiratory muscle training 3 days a week for 8 weeks. Maximum inspiratory and expiratory pressure (Pimax) (Pemex), 6-minute walk test, Handgrip strength by hand-held dynamometer, Fatigue Assessment Scale (FAS), and Perceived Stress Scale pss 10 values were measured before the training and then at the eighth week for both groups. Results: No differences were detected between the groups in terms of sample and clinical characteristics 8 weeks post-intervention. In favor of the intervention group, a significant difference with medium to high effect size was found in terms of Pimax, Pemax, FAS, PS, and 6MWT (p < 0.05). However, there was no difference in terms of handgrip strength (p-value: 0.072), with a medium effect size (0.070). Regarding within-group comparisons, IG exhibited substantial differences in all outcome measures (p < 0.05) compared to CG, with the exception of PImax and 6MWT. Conclusion: In post-operative breast cancer survivors, respiratory muscle training combined with aerobic training increases respiratory muscle strength and functional ability while lowering stress and tiredness.

Fabrication and characterization of a new eco-friendly sulfonamide-chitosan derivative with enhanced antimicrobial and selective cytotoxicity properties.

Chitosan (CH) exhibits low antimicrobial activity. This study addresses this issue by modifying the chitosan with a sulfonamide derivative, 3-(4-(N,N-dimethylsulfonyl)phenyl)acrylic acid. The structure of the sulfonamide-chitosan derivative (DMS-CH) was confirmed using Fourier transform infrared spectroscopy and Nuclear magnetic resonance. The results of scanning electron microscopy, thermal gravimetric analysis, and X-ray diffraction indicated that the morphology changed to a porous nature, the thermal stability decreased, and the crystallinity increased in the DMS-CH derivative compared to chitosan, respectively. The degree of substitution was calculated from the elemental analysis data and was found to be moderate (42%). The modified chitosan exhibited enhanced antimicrobial properties at low concentrations, with a minimum inhibitory concentration (MIC) of 50 µg/mL observed for B. subtilis and P. aeruginosa, and a value of 25 µg/mL for S. aureus, E. coli, and C. albicans. In the case of native chitosan, the MIC values doubled or more, with 50 µg/mL recorded for E. coli and C. albicans and 100 µg/mL recorded for B. subtilis, S. aureus, and P. aeruginosa. Furthermore, toxicological examinations conducted on MCF-7 (breast adenocarcinoma) cell lines demonstrated that DMS-CH exhibited greater toxicity (IC50 = 225.47 µg/mL) than pure CH, while still maintaining significant safety limits against normal lung fibroblasts (WI-38). Collectively, these results suggest the potential use of the newly modified chitosan in biomedical applications.

A sustainable model for the simultaneous determination of tadalafil and dapoxetine hydrochloride in their binary mixture: Overcoming the challenges of environmental, operational, and instrumental variability for spectral data.

This study employed functional principal component analysis (FPCA) and covariate design of experiments (DoE) to mitigate the susceptibility of chemometric methods to unexpected variations stemming from operational and instrumental factors. A comparative analysis with partial least squares (PLS) revealed that our proposed approach effectively reduced variability across different analysts, days, and instruments. Specifically, FPCA was utilized to compress available spectral wavelength information, while covariate DoE aided in selecting an optimal training set within the experimental space. Subsequently, PLS was applied for the simultaneous determination of tadalafil (TD) and dapoxetine hydrochloride (DP) in their binary mixture. Validation of the proposed method through accuracy profiles demonstrated its reliability, paving the way for its application in pharmaceutical analysis.

Kikuchi-Fujimoto Disease: A Case Report of Prolonged Fever and Lymphadenopathy in a Young Girl.

Kikuchi-Fujimoto disease (KFD) is a benign and self-limited disorder that usually presents with regional cervical lymphadenopathy and fever. We report a case of a 12-year-old female who complained of fever, night sweating, significant weight loss, and tender right cervical lymph node enlargement for 2 months. A full workup including laboratory tests and imaging studies, an excisional biopsy, and histopathological analysis were done, and the diagnosis of KFD was confirmed. The patient was treated with analgesia and oral prednisolone, resulting in good improvement. A high degree of clinical suspicion is imperative for physicians, given the rarity of the disease and the associated diagnostic challenges.

Real-Time Prediction of Petrophysical Properties Using Machine Learning Based on Drilling Parameters.

The prediction of rock porosity and permeability is crucial for assessing reservoir productivity and economic feasibility. However, traditional methods for obtaining these properties are time-consuming and expensive, making them impractical for comprehensive reservoir evaluation. This study introduces a novel approach to efficiently predict rock porosity and permeability for reservoir assessment by leveraging real-time machine learning models. Utilizing readily available drilling parameters, this approach offers a cost-effective alternative to traditional time-consuming methods to predict formation petrophysical parameters in real-time. The data set used in this study was collected from two vertical wells located in the Middle East. It encompasses drilling parameters such as the rate of penetration (ROP), gallons per minute (GPM), revolutions per minute (RPM), strokes per minute (SPP), torque, and weight on bit (WOB), along with the corresponding measurements of porosity (ϕ) and permeability (k) obtained through core analysis. Three machine learning models, namely, decision trees (DTs), random forest (RFs), and support vector machines (SVMs), were employed and evaluated for their effectiveness in predicting porosity and permeability. The results demonstrate promising performance across the different data sets. All three models achieved correlation coefficients (R) higher than 0.91 in predicting porosity. The RF model exhibited accurate predictions of permeability, achieving R values surpassing 0.92 in the various data sets. While the DT model displayed slightly lower performance, with the R-value decreasing to 0.88 in the testing data set, the SVM model suffered from overfitting, with R values dropping to 0.83 in the testing data set. The novelty of this work lies in the successful application of machine learning models to the real-time prediction of reservoir properties, providing a practical and efficient solution for the oil and gas industry. By achieving correlation coefficients exceeding 0.91 and showcasing the models' efficacy in a dynamic testing data set, this study paves the way for improved decision-making processes and enhanced exploration and production activities. The innovative aspect lies in the utilization of drilling parameters for timely and cost-effective estimation, transforming conventional reservoir evaluation methods.

A Novel Viscoelastic Deformation Mechanism Uncovered during Vickers Hardness Study of Bone.

This study investigates the viscoelastic deformation mechanisms of bone as a response to Vickers hardness indentation. We utilized advanced high-resolution scanning electron microscopy (SEM) to investigate a distinct deformation pattern that originates from the indentation site within the bone matrix. The focus of our research was to analyze a unique deformation mechanism observed in bone tissue, which has been colloquially termed as "screw-like" due to its resemblance to a screw thread when viewed under an optical microscope. The primary goals of this research are to investigate the distinctive characteristics of the "screw-like" deformation pattern and to determine how the microstructure of bone influences the initiation and control of this mechanism. These patterns, emerging during the dwell period of indentation, underscore the viscoelastic nature of bone, indicating its propensity for energy dissipation and microstructural reconfiguration under load. This study uncovered a direct correlation between the length of the "screw-like" deformation and the duration of the indentation dwell time, providing quantifiable evidence of the bone's viscoelastic behavior. This finding is pivotal in understanding the mechanical properties of bone, including its fracture toughness, as it relates to the complex interplay of factors such as energy dissipation, microstructural reinforcement, and stress distribution. Furthermore, this study discusses the implications of viscoelastic properties on the bone's ability to resist mechanical challenges, underscoring the significance of viscoelasticity in bone research.

Solar desalination system for fresh water production performance estimation in net-zero energy consumption building: A comparative study on various machine learning models.

This study employs diverse machine learning models, including classic artificial neural network (ANN), hybrid ANN models, and the imperialist competitive algorithm and emotional artificial neural network (EANN), to predict crucial parameters such as fresh water production and vapor temperatures. Evaluation metrics reveal the integrated ANN-ICA model outperforms the classic ANN, achieving a remarkable 20% reduction in mean squared error (MSE). The emotional artificial neural network (EANN) demonstrates superior accuracy, attaining an impressive 99% coefficient of determination (R2) in predicting freshwater production and vapor temperatures. The comprehensive comparative analysis extends to environmental assessments, displaying the solar desalination system's compatibility with renewable energy sources. Results highlight the potential for the proposed system to conserve water resources and reduce environmental impact, with a substantial decrease in total dissolved solids (TDS) from over 6,000 ppm to below 50 ppm. The findings underscore the efficacy of machine learning models in optimizing solar-driven desalination systems, providing valuable insights into their capabilities for addressing water scarcity challenges and contributing to the global shift toward sustainable and environmentally friendly water production methods.

Recent advancements and prospects in carbon-based nanomaterials derived from biomass for environmental remediation applications.

The conversion of waste biomass into a value-added carbonaceous nanomaterial highlights the appealing power of biomass valorization. The advantages of using sustainable and cheap biomass precursors exhibit the tremendous opportunity for boosting energy production and their application in environmental remediation processes. This review emphasis the development and production of carbon-based nanomaterials derived from biomass, which possess favourable characteristics such as biocompatibility and photoluminescence. The advantages and limitations of various nanomaterials synthesised from different precursors were also discussed with insights into their physicochemical properties. The surface morphology of the porous nanomaterials is also explored along with their characteristic properties like regenerative nature, non-toxicity, ecofriendly nature, unique surface area, etc. The incorporation of various functional groups confers superiority of these materials, resulting in unique and advanced functional properties. Further, the use of these biomass derived nanomaterials was also explored in different applications like adsorption, photocatalysis and sensing of hazardous pollutants, etc. The challenges and outcomes obtained from different carbon-based nanomaterials are briefly outlined and discussed in this review.

Paper-based sensors: affordable, versatile, and emerging analyte detection platforms.

Paper-based sensors, often referred to as paper-based analytical devices (PADs), stand as a transformative technology in the field of analytical chemistry. They offer an affordable, versatile, and accessible solution for diverse analyte detection. These sensors harness the unique properties of paper substrates to provide a cost-effective and adaptable platform for rapid analyte detection, spanning chemical species, biomolecules, and pathogens. This review highlights the key attributes that make paper-based sensors an attractive choice for analyte detection. PADs demonstrate their versatility by accommodating a wide range of analytes, from ions and gases to proteins, nucleic acids, and more, with customizable designs for specific applications. Their user-friendly operation and minimal infrastructure requirements suit point-of-care diagnostics, environmental monitoring, food safety, and more. This review also explores various fabrication methods such as inkjet printing, wax printing, screen printing, dip coating, and photolithography. Incorporating nanomaterials and biorecognition elements promises even more sophisticated and sensitive applications.

Exploring the detailed role of interleukins in cancer: A comprehensive review of literature.

The cancer cells that are not normal can grow into tumors, invade surrounding tissues, and travel to other parts of the body via the lymphatic or circulatory systems. Interleukins, a vital class of signaling proteins, facilitate cell-to-cell contact within the immune system. A type of non-coding RNA known as lncRNAs mediates its actions by regulating miRNA-mRNA roles (Interleukins). Because of their dual function in controlling the growth of tumors and altering the immune system's response to cancer cells, interleukins have been extensively studied concerning cancer. Understanding the complex relationships between interleukins, the immune system, the tumor microenvironment, and the components of interleukin signaling pathways that impact the miRNA-mRNA axis, including lncRNAs, has advanced significantly in cancer research. Due to the significant and all-encompassing influence of interleukins on the immune system and the development and advancement of cancers, lncRNAs play a crucial role in cancer research by modulating interleukins. Their diverse effects on immune system regulation, tumor growth encouragement, and tumor inhibition make them appealing candidates for potential cancer treatments and diagnostics. A deeper understanding of the relationship between the biology of interleukin and lncRNAs will likely result in more effective immunotherapy strategies and individualized cancer treatments.

Study of Cation Distribution and Photocatalytic Activity of Nonthermal Plasma-Modified NiZnFe2O4 Magnetic Nanocomposites.

In this study, NiZnFe2O4 composite was synthesized using a sol-gel route and subjected to nonthermal plasma treatment for tailoring their cations' distribution and physicochemical, magnetic, and photocatalytic properties. Microwave plasma treatment was given to the composites for 60 min in support of postsynthesis sintering at 700 °C for 5 h. X-ray diffraction (XRD) analysis was conducted on pre- and postplasma-modified ferrite composites to identify phase-pure cubic spinel structure and cations' distribution. The cation distributions were measured from the ratio of XRD intensity peaks corresponding to (220), (311), (422) and (440) planes. The intensity ratio of plasma-treated ferrite composites decreased compared to that of pristine composites. The crystallite size and lattice constant were increased on plasma treatment of the composite. The morphological analysis showed nanoflower-like structures of the particles with an increased surface area in the plasma-treated composites. The plasma oxidation and sputtering effects caused a reduction in the nanoflower size. The energy bandgap increased with a decrease in particle size due to plasma treatment. The rhodamine B dye solution was then irradiated with a light source in the presence of the nanocomposites. The dye degradation efficiency of the composite photocatalyst increased from 80 to 96% after plasma treatment.

Immediate Implants in Posterior Extraction Sites: A Case Series Applying the Dual-Zone Therapeutic Concept With a Three-Year Follow-Up.

The study aims to present 11 immediately placed implants in posterior extraction sockets applying the dual-zone therapeutic concept. Five patients with non-restorable molars or premolars were treated with single or multiple immediate implants after atraumatic tooth extraction using a piezotome. The dual-zone therapeutic concept included grafting the jumping gap adjacent to the implant up to the gingival margin with a bovine xenograft. A screw-retained customized healing abutment was used to allow healing, and the implant loading was delayed for four to six months. All the patients were followed up for three years. Surgical complications, implant or prosthesis loss, and peri-implant marginal tissue health were assessed annually. No surgical complications or implant loss were observed during the follow-up visits. Peri-implant marginal tissue health showed excellent results with minimal marginal bone loss. Bone gain was evident in some cases. Using the dual-zone therapeutic concept with immediate implant placement in posterior extraction sockets showed promising results over three years.

Crimean-Congo haemorrhagic fever virus uses LDLR to bind and enter host cells.

Climate change and population densities accelerated transmission of highly pathogenic viruses to humans, including the Crimean-Congo haemorrhagic fever virus (CCHFV). Here we report that the Low Density Lipoprotein Receptor (LDLR) is a critical receptor for CCHFV cell entry, playing a vital role in CCHFV infection in cell culture and blood vessel organoids. The interaction between CCHFV and LDLR is highly specific, with other members of the LDLR protein family failing to bind to or neutralize the virus. Biosensor experiments demonstrate that LDLR specifically binds the surface glycoproteins of CCHFV. Importantly, mice lacking LDLR exhibit a delay in CCHFV-induced disease. Furthermore, we identified the presence of Apolipoprotein E (ApoE) on CCHFV particles. Our findings highlight the essential role of LDLR in CCHFV infection, irrespective of ApoE presence, when the virus is produced in tick cells. This discovery holds profound implications for the development of future therapies against CCHFV.

Clinical Characteristics and Prognostic Factors of Endometrial Cancer Patients With Liver Metastasis: A Surveillance, Epidemiology, and End Results Database (SEER)-Based Study of 1,034 Women.

Background There are several patterns of metastatic spread from endometrial cancer (EC). Although studies have been conducted to study the EC population with distant metastasis in the bone and lungs, there is still a lack of studies on liver metastasis. This study aims to evaluate and assess the clinical features and prognostic factors of EC patients with liver metastasis. Methodology We conducted a retrospective cohort study adhering to the guidelines for reporting observational research. We utilized the Surveillance, Epidemiology, and End Results database to gather data on female patients diagnosed with EC and reported liver metastasis. We estimated survival curves using the Kaplan-Meier method and evaluated differences in survival using the log-rank test. We also conducted univariable and multivariable Cox proportional hazards regression analyses to determine the hazard ratios with 95% confidence intervals for overall survival (OS) and identify factors that impact survival. Results We analyzed data from 1,034 EC patients with liver metastasis. Median OS after liver metastasis was six months, and cancer-specific survival was seven months. Univariate Cox regression analysis revealed several factors associated with decreased OS in EC patients. These included age (≥60 years), non-endometrioid and sarcoma histological subtypes, absence of surgery, no chemotherapy, and the presence of distant metastasis to the lung, brain, and bone. Conversely, married marital status and white race were linked to a better prognosis. Subsequent multivariate Cox regression analysis identified age (≥60 years), non-endometrioid histological subtype, absence of surgery, no chemotherapy, and the presence of distant metastasis to lung, brain, and bone remaining as independent risk factors for decreased OS. In contrast, the white race still emerged as an independent prognostic factor for better OS. Conclusions Various risk factors, such as age, race, lung, bone, or brain metastasis, as well as chemotherapy and surgery, may influence the prognosis of individuals with primary EC liver metastases.

Debye Temperature Evaluation for Secondary Battery Cathode of α-SnxFe1-xOOH Nanoparticles Derived from the 57Fe- and 119Sn-Mössbauer Spectra.

Debye temperatures of α-SnxFe1-xOOH nanoparticles (x = 0, 0.05, 0.10, 0.15 and 0.20, abbreviated as Sn100x NPs) prepared by hydrothermal reaction were estimated with 57Fe- and 119Sn-Mössbauer spectra measured by varying the temperature from 20 to 300 K. Electrical properties were studied by solid-state impedance spectroscopy (SS-IS). Together, the charge-discharge capacity of Li- and Na-ion batteries containing Sn100x NPs as a cathode were evaluated. 57Fe-Mössbauer spectra of Sn10, Sn15, and Sn20 measured at 300 K showed only one doublet due to the superparamagnetic doublet, while the doublet decomposed into a sextet due to goethite at the temperature below 50 K for Sn 10, 200 K for Sn15, and 100 K for Sn20. These results suggest that Sn10, Sn15 and Sn20 had smaller particles than Sn0. On the other hand, 20 K 119Sn-Mössbauer spectra of Sn15 were composed of a paramagnetic doublet with an isomer shift (δ) of 0.24 mm s-1 and quadrupole splitting (∆) of 3.52 mm s-1. These values were larger than those of Sn10 (δ: 0.08 mm s-1, ∆: 0.00 mm s-1) and Sn20 (δ: 0.10 mm s-1, ∆: 0.00 mm s-1), suggesting that the SnIV-O chemical bond is shorter and the distortion of octahedral SnO6 is larger in Sn15 than in Sn10 and Sn20 due to the increase in the covalency and polarization of the SnIV-O chemical bond. Debye temperatures determined from 57Fe-Mössbauer spectra measured at the low temperature were 210 K, 228 K, and 250 K for Sn10, Sn15, and Sn20, while that of α-Fe2O3 was 324 K. Similarly, the Debye temperature of 199, 251, and 269 K for Sn10, Sn15, and Sn20 were estimated from the temperature-dependent 119Sn-Mössbauer spectra, which were significantly smaller than that of BaSnO3 (=658 K) and SnO2 (=382 K). These results suggest that Fe and Sn are a weakly bound lattice in goethite NPs with low crystallinity. Modification of NPs and addition of Sn has a positive effect, resulting in an increase in DC conductivity of almost 5 orders of magnitude, from a σDC value of 9.37 × 10-7 (Ω cm)-1 for pure goethite Sn (Sn0) up to DC plateau for samples containing 0.15 and 0.20 Sn (Sn15 and Sn20) with a DC value of ~4 × 10-7 (Ω cm)-1 @423 K. This non-linear conductivity pattern and levelling at a higher Sn content suggests that structural modifications have a notable impact on electron transport, which is primarily governed by the thermally activated via three-dimensional hopping of small polarons (SPH). Measurements of SIB performance, including the Sn100x cathode under a current density of 50 mA g-1, showed initial capacities of 81 and 85 mAh g-1 for Sn0 and Sn15, which were larger than the others. The large initial capacities were measured at a current density of 5 mA g-1 found at 170 and 182 mAh g-1 for Sn15 and Sn20, respectively. It is concluded that tin-goethite NPs are an excellent material for a secondary battery cathode and that Sn15 is the best cathode among the studied Sn100x NPs.

A novel micropeptide, Slitharin, exerts cardioprotective effects in myocardial infarction.

PURPOSE: Micropeptides are an emerging class of proteins that play critical roles in cell signaling. Here, we describe the discovery of a novel micropeptide, dubbed slitharin (Slt), in conditioned media from Cardiosphere-derived cells (CDCs), a therapeutic cardiac stromal cell type. EXPERIMENTAL DESIGN: We performed mass spectrometry of peptide-enriched fractions from the conditioned media of CDCs and a therapeutically inert cell type (human dermal fibrobasts). We then evaluated the therapeutic capacity of the candidate peptide using an in vitro model of cardiomyocyte injury and a rat model of myocardial infarction. RESULTS: We identified a novel 24-amino acid micropeptide (dubbed Slitharin [Slt]) with a non-canonical leucine start codon, arising from long intergenic non-coding (LINC) RNA 2099. Neonatal rat ventricular myocytes (NRVMs) exposed to Slt were protected from hypoxic injury in vitro compared to a vehicle or scrambled control. Transcriptomic analysis of cardiomyocytes exposed to Slt reveals cytoprotective capacity, putatively through regulation of stress-induced MAPK-ERK. Slt also exerted cardioprotective effects in rats with myocardial infarction as shown by reduced infarct size 48 h post-injury. Conclusions and clinical relavance: Thus, Slt is a non-coding RNA-derived micropeptide, identified in the extracellular space, with a potential cardioprotective function.

Synthesis and characterization of nanocomposite based polymeric membrane (PES/PVP/GO-TiO2) and performance evaluation for the removal of various antibiotics (amoxicillin, azithromycin & ciprofloxacin) from aqueous solution.

The escalating global concern regarding antibiotic pollution necessitates the development of advanced water treatment strategies. This study presents an innovative approach through the fabrication and evaluation of a Polyethersulfone (PES) membrane adorned with GO-TiO2 nanocomposites. The objective is to enhance the removal efficiency of various antibiotics, addressing the challenge of emerging organic compounds (EOCs) in water systems. The nanocomposite membranes, synthesized via the phase inversion method, incorporate hydrophilic agents, specifically GO-TiO2 nanocomposites and Polyvinylpyrrolidone (PVP). The resultant membranes underwent comprehensive characterization employing AFM, EDS, tensile strength testing, water contact angle measurements, and FESEM to elucidate their properties. Analysis revealed a substantial improvement in the hydrophilicity of the modified membranes attributed to the presence of hydroxyl groups within the GO-TiO2 structure. AFM images demonstrated an augmentation in surface roughness with increasing nanocomposite content. FESEM images unveiled structural modifications, leading to enhanced porosity and augmented water flux. The pure water flux elevated from 0.980 L/m2.h-1 for unmodified membranes to approximately 6.85 L/m2.h-1 for membranes modified with 2 wt% nanocomposites. Membrane performance analysis indicated a direct correlation between nanocomposite content and antibiotic removal efficiency, ranging from 66.52% to 89.81% with 4 wt% nanocomposite content. Furthermore, the nanocomposite-modified membrane exhibited heightened resistance to fouling. The efficacy of the membrane extended to displaying potent antibacterial properties against microbial strains, including S. aureus, E. coli, and Candida. This study underscores the immense potential of GO-TiO2 decorated PES membranes as a sustainable and efficient solution for mitigating antibiotic contamination in water systems. The utilization of nanocomposite membranes emerges as a promising technique to combat the presence of EOC pollutants, particularly antibiotics, in water bodies, thus addressing a critical environmental concern.

Exploring the therapeutic mechanism of potential phytocompounds from Kalanchoe pinnata in the treatment of diabetes mellitus by integrating network pharmacology, molecular docking and simulation approach.

Since ancient times, bioactive phytocompounds from different parts of medicinal plants have been used to heal various disease ailments and they are now regarded as a valuable source of disease prevention globally. Kalanchoe pinnata is a member of the Crassulaceae family; it has a long history of usage in traditional ayurvedic treatment. Analysis of bioactive compounds for their potential anti-type-2 diabetes mellitus (T2DM) mechanism along with in-vitro and in-silico approaches was studied in the present research. The alpha-amylase and alpha-glucosidase inhibitory activity of methanolic extract of Kalanchoe pinnata (α-amylase: IC50 29.50 ± 0.04 µg/ml; α-glucosidase IC50 32.04 ± 0.35 µg/ml) exhibit a high degree of similarity to the standard drug acarbose (IC50 35.82 ± 0.14 µg/ml). Different biological databases were used to list phytocompounds from the plant, and ADME analysis using swissADME was carried out to screen compounds that obeyed the Lipinski rule of 5 and were employed further. STRING and KEGG pathway analysis was performed for gene enrichment analysis followed by network pharmacology to identify key target proteins involved in DM. AMY2A, NOX4, RPS6KA3, ADRA2A, CHRM5, and IL2 were identified as core targets for luteolin, kaempferol, alpha amyrin, stigmasterol compounds by modulating neuroactive ligand interaction, P13-AKT, MAPK, and PPAR signaling pathways. Molecular docking was performed to study the binding affinity among bioactive compounds of K. pinnata against aldose reductase, alpha-amylase, alpha-glucosidase, and dipeptidyl peptidase IV. Alpha-amylase-friedelin [FRI] and alpha-amylase-acarbose [STD] complexes were subjected to molecular simulation for a 200 ns duration that depicted the stability of the compounds and proteins. In the current study, employing dual approach in-silico and in-vitro enzyme assays has yielded a comprehensive and strong understanding of its potential therapeutic properties, making a significant step towards the development of novel anti-diabetic treatment.