Exercise-Induced Alterations in Irisin and Osteocalcin Levels: A Comparative Analysis Across Different Training Modalities.

BACKGROUND: Physical activity significantly influences physiological biomarkers, including irisin and osteocalcin, which are pivotal for metabolic and bone health. Understanding the differential impacts of various exercise modalities on these biomarkers is essential for optimizing health benefits. OBJECTIVES: The study aimed to compare the effects of endurance training and high-intensity resistance training (HIRT) on the levels of irisin and osteocalcin and determine which exercise modality more effectively influences these health-related biomarkers. METHODS:  The study was conducted at the Nimra Institute of Medical Sciences in Andhra Pradesh, India, where 100 healthy male participants aged between 21 and 35 were recruited. These participants, who were not regularly active and had no metabolic or bone diseases, were divided into two groups to undergo an eight-week training from March to April 2022. One group participated in endurance training involving running and cycling, while the other engaged in HIRT, both targeting a heart rate set at 75% of the maximum. Baseline and follow-up measurements of irisin and osteocalcin were taken before and after the training using blood samples collected after fasting. The study used paired t-tests to analyze changes in biomarker levels, and Pearson correlation coefficients to explore the relationship between the biomarkers, with results processed using statistical software and presented as mean ± standard deviation (SD). RESULTS: Post-intervention, both exercise groups showed significant increases in irisin and a modest increase in osteocalcin levels. The HIRT group exhibited a higher increase in irisin levels (+119.33 pg/mL, p<0.015) compared to the endurance group (+108.32 pg/mL, p<0.023). Similarly, osteocalcin levels increased modestly in both groups, with the HIRT group showing a higher mean difference (+0.75 pg/mL, p<0.001) than the endurance group (+0.70 pg/mL). The study also found a link between changes in irisin and osteocalcin levels. This link was stronger in the HIRT group (r = +0.22; p < 0.039) than in the endurance group (r = +0.20; p < 0.038). CONCLUSION: Both endurance and high-intensity resistance training are effective in enhancing metabolic and bone health, evidenced by increases in irisin and osteocalcin levels. Although the differences in mean values suggest that HIRT may have a marginal advantage in boosting these biomarkers, confirming the statistical significance of this difference is essential. Further research is required to understand the mechanisms behind these effects and to assess their long-term impacts on health and disease prevention.

Pharmacokinetic studies, molecular docking, and molecular dynamics simulations of phytochemicals from Morus alba: a multi receptor approach for potential therapeutic agents in colorectal cancer.

This study explores the therapeutic potential of phytochemicals derived from Morus alba for colorectal cancer (CRC) treatment. Colorectal cancer is a global health concern with increasing mortality rates, necessitating innovative strategies for prevention and therapy. Employing in silico analysis, molecular docking techniques (MDT), and molecular dynamics simulations (MDS), the study investigates the interactions between Morus alba-derived phytochemicals and key proteins (AKT1, Src, STAT3, EGFR) implicated in CRC progression. ADME/T analysis screens 78 phytochemicals for drug-like and pharmacokinetic properties. The study integrates Lipinski's Rule of Five and comprehensive bioactivity assessments, providing a nuanced understanding of Morus alba phytoconstituent's potential as CRC therapeutic agents. Notably, 14 phytochemicals out of 78 emerge as potential candidates, demonstrating oral bioavailability and favorable bioactivity scores. Autodock 1.5.7 is employed for energy minimization followed by molecular docking with the highest binding energy observed to be - 11.7 kcal/mol exhibited by Kuwanon A against AKT1. Molecular dynamics simulations and trajectory path analysis were conducted between Kuwanon A and AKT1 at the Pleckstrin homology (PH) domain region (TRP80), revealing minimal deviations. In comparison to the standard drug Capivasertib, the phytochemical Kuwanon A emerges as a standout candidate based on computational analysis. This suggests its potential as an alternative to mitigate the limitations associated with the standard drug. The research aims to provide insights for future experimental validations and to stimulate the development of Kuwanon A as a novel, effective therapeutic agent for managing colorectal cancer.

Case Report: Holistic dental care for a child with Hunter syndrome: Addressing dental ramifications, overcoming challenges, and enhancing quality of life.

Hunter syndrome (MPS II), an X-linked recessive lysosomal storage disorder, is a result of deficiency of the iduronate 2-sulfatase enzyme (IDS), leading to cognitive impairment, systemic organ involvement, and increased dental problems. This case report describes the management of a child with Hunter syndrome who was referred to the Department of Paediatric and Preventive Dentistry for pain in the upper front teeth. Intraoral examination revealed severe early childhood caries, prompting planning for full-mouth rehabilitation under general anaesthesia due to the child's uncooperative behaviour. In response to recommendations from the Department of Otolaryngology and the Department of Paediatric Surgery, a comprehensive treatment plan consolidated full-mouth rehabilitation in addition to adenoidectomy and inguinal and umbilical herniotomy procedures during a single session of general anaesthesia. Successful interventions were reflected in the uneventful one-month follow-up of the patient, highlighting the efficacy of the interdisciplinary approach. The key takeaway underscores the importance of collaborative interventions, emphasising singular intubation for patients requiring recurrent hospitalisations, providing both monetary relief and reducing post operative healing time. Designed to address global developmental delay in the child, a personalised home care plan was also implemented. Evaluation of plaque and gingival indices before and after the home care regimen demonstrated a notable improvement, indicating an enhanced oral quality of life.

Extraction and characterization of carotenoid pigments with antioxidant and antibacterial potential from marine yeast Rhodotorula sp. KSB1.

Pigments are coloring agents used widely in different industrial sectors. There is a demand for using natural pigments rather than synthetic dyes because of the health hazards caused by synthetic dyes. Many natural pigments have different medicinal activities which can contribute to the nutritional value of the product. This study was carried forward with marine yeasts which can produce pigments. A total of 4 marine yeast isolates were recovered from the mangrove area of Sundarbans, West Bengal, India. Among them, the isolate KSB1 produced 856 µg/g total concentration of carotenoid pigment and the dry mass weight was 3.56 g/L. The stability of the extracted pigments was checked using temperature, pH, UV light exposure time, and different saline conditions. The pigments were characterized using HPLC and FTIR analysis. All of the extracted pigments showed good antioxidant activity in DPPH, metal chelating, and reducing power assay. The pigments were also found to have good antibacterial activity against the bacterial pathogens Staphylococcus aureus, Listeria monocytogenes, and Escherichia coli. Carotenoid pigment from KSB1 was found to have maximum activity in all the pathogens. The cytogenotoxicity using onion roots and phytotoxicity analysis indicated that the pigments were non-toxic and safe for cells. Finally, the potential marine yeast was identified using 18 s rRNA sequencing and identified as Rhodotorula sp. KSB1 (Accession no. MH782232).

H-Glass Supported Hybrid Gold Nano-Islands for Visible-Light-Driven Hydrogen Evolution.

Flat panel reactors, coated with photocatalytic materials, offer a sustainable approach for the commercial production of hydrogen (H2) with zero carbon footprint. Despite this, achieving high solar-to-hydrogen (STH) conversion efficiency with these reactors is still a significant challenge due to the low utilization efficiency of solar light and rapid charge recombination. Herein, hybrid gold nano-islands (HGNIs) are developed on transparent glass support to improve the STH efficiency. Plasmonic HGNIs are grown on an in-house developed active glass sheet composed of sodium aluminum phosphosilicate oxide glass (H-glass) using the thermal dewetting method at 550 °C under an ambient atmosphere. HGNIs with various oxidation states (Au0, Au+, and Au-) and multiple interfaces are obtained due to the diffusion of the elements from the glass structure, which also facilitates the lifetime of the hot electron to be ≈2.94 ps. H-glass-supported HGNIs demonstrate significant STH conversion efficiency of 0.6%, without any sacrificial agents, via water dissociation. This study unveils the specific role of H-glass-supported HGNIs in facilitating light-driven chemical conversions, offering new avenues for the development of high-performance photocatalysts in various chemical conversion reactions for large-scale commercial applications.

A preclinical study to determine the anti-epileptic effect of biotin on maximal electroshock (MES) and pentylenetetrazole (PTZ) models in albino rats.

OBJECTIVES: Vitamin B7(biotin) is not synthesized in our body and is retrieved from some food products like eggs, liver, pork and leafy vegetables and as well as microbes of gut. Deficiency of biotin majorly leads to loss of hair, rashes over skin, lethargy and seizures. It is noted that biotin is an anti-oxidant and negates free radical effects. Biotin is also involved in carbon dioxide metabolism and it might alter seizure threshold. Studies also suggest its effect on lipid metabolism as well. So, the primary objective of this study was to assess the efficacy of biotin in maximal electric shock (MES) induced generalized tonic-clonic seizures (GTCS) and pentylenetetrazole (PTZ) induced absence seizures. The secondary objective is to study the effect of combined treatment of biotin and sodium valproate on seizures as well as plasma lipid profile in rats. METHODS: In our study 30 albino Wistar rats each were used in MES and PTZ model respectively. 30 rats were divided equally into following groups: I - distilled water (negative control) II - distilled water (positive control) III - sodium valproate (300 mg/kg) IV - biotin (10 mg/kg/day) V - biotin (10 mg/kg) + sodium valproate (150 mg/kg). RESULTS: We observed that the tonic hind limb extension was significantly reduced in the treatment group in MES model. Nitric oxide levels were also seen raised in combination group in MES model and all the treated groups in PTZ model. Biotin treated group showed increased high-density lipoproteins and reduced low density lipoproteins and triglycerides. CONCLUSION: Biotin had an additive effect to sodium valproate in both the models of epilepsy in rats. Further, it was also able to counteract hyperlipidemia cause by sodium valproate.

Spatially selective narrow band and broadband absorption in Ag/SiO2/Ag based trilayer thin films by oblique angle deposition of SiO2layer.

We have experimentally demonstrated spatially selective absorption in Ag-SiO2-Ag based trilayer thin films by tuning the deposition angle of SiO2layer. These structures generate cavity resonance which can be tuned across the substrate locations due to spatially selective thickness and refractive index of silicon oxide (SiO2) film sandwiched between metallic silver (Ag) mirrors. Spatially selective property of SiO2film is obtained by oblique angle deposition technique using an electron beam evaporation system. The resonance wavelength of absorption in this trilayer structure shifts across the substrate locations along the direction of oblique deposition. The extent of shift in resonance increases with increase in angle of deposition of SiO2layer. 4.14 nm mm-1average shift of resonance wavelength is observed when SiO2is deposited at 40° whereas 4.76 nm mm-1average shift is observed when SiO2is deposited at 60°. We observed that the width of resonance increases with angle of deposition of the cavity layer and ultimately the resonant absorption disappears and becomes broadband when SiO2is deposited at glancing angle deposition (GLAD) configuration. Our study reveals that there is a suitable range of oblique angle of deposition from 40° to 60° for higher spatial tunability and resonant absorption whereas the absorption becomes broadband for glancing angle deposition.

Mitochondria-Targeted Oligomeric α-Synuclein Induces TOM40 Degradation and Mitochondrial Dysfunction in Parkinson's Disease and Parkinsonism-Dementia of Guam.

Mitochondrial dysfunction is a central aspect of Parkinson's disease (PD) pathology, yet the underlying mechanisms are not fully understood. This study investigates the link between α-Synuclein (α-Syn) pathology and the loss of translocase of the outer mitochondrial membrane 40 (TOM40), unraveling its implications for mitochondrial dysfunctions in neurons. We discovered that TOM40 protein depletion occurs in the brains of patients with Guam Parkinsonism Dementia (Guam PD) and cultured neurons expressing α-Syn proteinopathy, notably, without corresponding changes in TOM40 mRNA levels. Cultured neurons expressing α-Syn mutants, with or without a mitochondria-targeting signal (MTS) underscore the role of α-Syn's mitochondrial localization in inducing TOM40 degradation. Parkinson's Disease related etiological factors, such as 6-hydroxy dopamine or ROS/metal ions stress, which promote α-Syn oligomerization, exacerbate TOM40 depletion in PD patient-derived cells with SNCA gene triplication. Although α-Syn interacts with both TOM40 and TOM20 in the outer mitochondrial membrane, degradation is selective for TOM40, which occurs via the ubiquitin-proteasome system (UPS) pathway. Our comprehensive analyses using Seahorse technology, mitochondrial DNA sequencing, and damage assessments, demonstrate that mutant α-Syn-induced TOM40 loss results in mitochondrial dysfunction, characterized by reduced membrane potential, accumulation of mtDNA damage, deletion/insertion mutations, and altered oxygen consumption rates. Notably, ectopic supplementation of TOM40 or reducing pathological forms of α-Syn using ADP-ribosylation inhibitors ameliorate these mitochondrial defects, suggesting potential therapeutic avenues. In conclusion, our findings provide crucial mechanistic insights into how α-Syn accumulation leads to TOM40 degradation and mitochondrial dysfunction, offering insights for targeted interventions to alleviate mitochondrial defects in PD.

Self-Sanitization in a Silk Nanofibrous Network for Biodegradable PM0.3 Filters with In Situ Joule Heating.

In the contemporary way of life, face masks are crucial in managing disease transmission and battling air pollution. However, two key challenges, self-sanitization and biodegradation of face masks, need immediate attention, prompting the development of innovative solutions for the future. In this study, we present a novel approach that combines controlled acid hydrolysis and mechanical chopping to synthesize a silk nanofibrous network (SNN) seamlessly integrated with a wearable stainless steel mesh, resulting in the fabrication of self-sanitizable face masks. The distinct architecture of face masks showcases remarkable filtration efficiencies of 91.4, 95.4, and 98.3% for PM0.3, PM0.5, and PM1.0, respectively, while maintaining a comfortable level of breathability (ΔP = 92 Pa). Additionally, the face mask shows that a remarkable thermal resistance of 472 °C cm2 W-1 generates heat spontaneously at low voltage, deactivating Escherichia coli bacteria on the SNN, enabling self-sanitization. The SNN exhibited complete disintegration within the environment in just 10 days, highlighting the remarkable biodegradability of the face mask. The unique advantage of self-sanitization and biodegradation in a face mask filter is simultaneously achieved for the first time, which will open avenues to accomplish environmentally benign next-generation face masks.

Targeting mitochondrial dynamics and redox regulation in cardiovascular diseases.

Accumulating evidence highlights the pivotal role of mitochondria in cardiovascular diseases (CVDs). Understanding the molecular mechanisms underlying mitochondrial dysfunction is crucial for developing targeted therapeutics. Recent years have seen substantial advancements in unraveling mitochondrial regulatory pathways in both normal and pathological states and the development of potent drugs. However, specific delivery of drugs into the mitochondria is still a challenge. We present recent findings on regulators of mitochondrial dynamics and reactive oxygen species (ROS), critical factors influencing mitochondrial function in CVDs. We also discuss advancements in drug delivery strategies aimed at overcoming the technical barrier in targeting mitochondria for CVD treatment.

Vanillin/fungal-derived carboxy methyl chitosan/polyvinyl alcohol hydrogels prepared by freeze-thawing for wound dressing applications.

In this study, we developed hydrogels using polyvinyl alcohol (PVA), vanillin (V), and a fungus-derived carboxymethyl chitosan (FC) using a freeze-thaw-based method. These hydrogels were strengthened by bonding, including Schiff's base bonding between V and FC and hydrogen bonding between PVA, FC, and V. The physiological properties of these PFCV hydrogels were characterized by FTIR, TGA, compressive mechanical testing, and rheology and water contact angle measurements. FTIR spectra confirmed the effective integration of FC and V into the PVA network. TGA results showed that FC and V enhanced the thermal stability of PFCV hydrogels. Mechanical tests showed increasing the amount of V reduced mechanical properties but did not alter the elastic character of hydrogels. SEM images displayed a well-interconnected porous structure with excellent swelling capacity. In addition, we examined biological properties using cell-based in vitro studies and performed antibacterial assessments to assess suitability for potential wound dressing applications. Prestoblue™ and live/dead cell analysis strongly supported skin fibroblast attachment and viability, DPPH assays indicated substantial antioxidant activity, and PFCV hydrogels showed enhanced antibacterial effects against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). In summary, incorporating V and FC into PVA hydrogels appears to be attractive for wound dressing applications.

Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model.

Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and results in severe depression and suicide attempts in the social community. Prompt actions are crucial in tackling PPDD, which requires a quick recognition and accurate analysis of the probability factors associated with this condition. This concern requires attention. The primary aim of our research is to investigate the feasibility of anticipating an individual's mental state by categorizing individuals with depression from those without depression using a dataset consisting of text along with audio recordings from patients diagnosed with PPDD. This research proposes a hybrid PPDD framework that combines Improved Bi-directional Long Short-Term Memory (IBi-LSTM) with Transfer Learning (TL) based on two Convolutional Neural Network (CNN) architectures, respectively CNN-text and CNN audio. In the proposed model, the CNN section efficiently utilizes TL to obtain crucial knowledge from text and audio characteristics, whereas the improved Bi-LSTM module combines written material and sound data to obtain intricate chronological interpersonal relationships. The proposed model incorporates an attention technique to augment the effectiveness of the Bi-LSTM scheme. An experimental analysis is conducted on the PPDD online textual and speech audio dataset collected from UCI. It includes textual features such as age, women's health tracks, medical histories, demographic information, daily life metrics, psychological evaluations, and 'speech records' of PPDD patients. Data pre-processing is applied to maintain the data integrity and achieve reliable model performance. The proposed model demonstrates a great performance in better precision, recall, accuracy, and F1-score over existing deep learning models, including VGG-16, Base-CNN, and CNN-LSTM. These metrics indicate the model's ability to differentiate among women at risk of PPDD vs. non-PPDD. In addition, the feature importance analysis demonstrates that specific risk factors substantially impact the prediction of PPDD. The findings of this research establish a basis for improved precision and promptness in assessing the risk of PPDD, which may ultimately result in earlier implementation of interventions and the establishment of support networks for women who are susceptible to PPDD.

A precise model for skin cancer diagnosis using hybrid U-Net and improved MobileNet-V3 with hyperparameters optimization.

Skin cancer is a frequently occurring and possibly deadly disease that necessitates prompt and precise diagnosis in order to ensure efficacious treatment. This paper introduces an innovative approach for accurately identifying skin cancer by utilizing Convolution Neural Network architecture and optimizing hyperparameters. The proposed approach aims to increase the precision and efficacy of skin cancer recognition and consequently enhance patients' experiences. This investigation aims to tackle various significant challenges in skin cancer recognition, encompassing feature extraction, model architecture design, and optimizing hyperparameters. The proposed model utilizes advanced deep-learning methodologies to extract complex features and patterns from skin cancer images. We enhance the learning procedure of deep learning by integrating Standard U-Net and Improved MobileNet-V3 with optimization techniques, allowing the model to differentiate malignant and benign skin cancers. Also substituted the crossed-entropy loss function of the Mobilenet-v3 mathematical framework with a bias loss function to enhance the accuracy. The model's squeeze and excitation component was replaced with the practical channel attention component to achieve parameter reduction. Integrating cross-layer connections among Mobile modules has been proposed to leverage synthetic features effectively. The dilated convolutions were incorporated into the model to enhance the receptive field. The optimization of hyperparameters is of utmost importance in improving the efficiency of deep learning models. To fine-tune the model's hyperparameter, we employ sophisticated optimization methods such as the Bayesian optimization method using pre-trained CNN architecture MobileNet-V3. The proposed model is compared with existing models, i.e., MobileNet, VGG-16, MobileNet-V2, Resnet-152v2 and VGG-19 on the "HAM-10000 Melanoma Skin Cancer dataset". The empirical findings illustrate that the proposed optimized hybrid MobileNet-V3 model outperforms existing skin cancer detection and segmentation techniques based on high precision of 97.84%, sensitivity of 96.35%, accuracy of 98.86% and specificity of 97.32%. The enhanced performance of this research resulted in timelier and more precise diagnoses, potentially contributing to life-saving outcomes and mitigating healthcare expenditures.

Endogenous TDP-43 mislocalization in a novel knock-in mouse model reveals DNA repair impairment, inflammation, and neuronal senescence.

TDP-43 mislocalization and aggregation are key pathological features of motor neuron diseases (MND) including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). However, transgenic hTDP-43 WT or ΔNLS-overexpression animal models mainly capture late-stages TDP-43 proteinopathy, and do not provide a complete understanding of early motor neuron-specific pathology during pre-symptomatic phases. We have now addressed this shortcoming by generating a new endogenous knock-in (KI) mouse model using a combination of CRISPR/Cas9 and FLEX Cre-switch strategy for the conditional expression of a mislocalized Tdp-43ΔNLS variant of mouse Tdp-43. This variant is either expressed conditionally in whole mice or specifically in the motor neurons. The mice exhibit loss of nuclear Tdp-43 concomitant with its cytosolic accumulation and aggregation in targeted cells, leading to increased DNA double-strand breaks (DSBs), signs of inflammation and DNA damage-associated cellular senescence. Notably, unlike WT Tdp43 which functionally interacts with Xrcc4 and DNA Ligase 4, the key DSB repair proteins in the non-homologous end-joining (NHEJ) pathway, the Tdp-43ΔNLS mutant sequesters them into cytosolic aggregates, exacerbating neuronal damage in mice brain. The mutant mice also exhibit myogenic degeneration in limb muscles and distinct motor deficits, consistent with the characteristics of MND. Our findings reveal progressive degenerative mechanisms in motor neurons expressing endogenous Tdp-43ΔNLS mutant, independent of TDP-43 overexpression or other confounding etiological factors. Thus, this unique Tdp-43 KI mouse model, which displays key molecular and phenotypic features of Tdp-43 proteinopathy, offers a significant opportunity to further characterize the early-stage progression of MND and also opens avenues for developing DNA repair-targeted approaches for treating TDP-43 pathology-linked neurodegenerative diseases.

Low Mean Perfusion Pressure Indexed to Body Surface Area is a Powerful Predictor of Poor Outcomes After Heart Transplantation in Patients With High Pre-Transplant Venous Pressure: A Clinical Study With Physiological Insights From Mathematical Modelling of Biventricular Heart Failure.

BACKGROUND & AIM: The deleterious consequences of chronically elevated venous pressure in patients with profound right ventricular or biventricular dysfunction are well known, including renal and hepatic dysfunction, and volume overload. The only option for these patients, if they fail optimal medical treatment, is a heart transplant, as they are not candidates for left ventricular assist device therapy. Mean perfusion pressure (MPP) is important in the outcomes of critically ill patients with high venous pressure. The question arises whether MPP is important for the outcomes of heart transplants in patients with elevated pre-transplant venous pressure. Medical management of heart failure patients with reduced ejection fraction involves lowering the systemic afterload with vasodilators while awaiting a transplant. We hypothesised that when venous pressure is elevated prior to transplant, a substantial reduction in systemic arterial elastance (Ea) through vasodilation may significantly decrease MPP, resulting in compromised end-organ function and consequent unfavourable outcomes after heart transplantation. This study aims to investigate whether a low MPP serves as a risk factor for adverse outcomes in heart transplant recipients with high venous pressure. METHOD: A retrospective analysis was conducted on 250 heart transplant recipients undergoing isolated heart transplantation at a single institution from October 2012 to March 2020. Right atrial pressure (RAP) of more than 15 mmHg was considered high. Additionally, Ea calculated as the ratio of end-systolic pressure to stroke volume, and MPP calculated as the difference between mean arterial pressure and RAP were considered in our analysis. The outcomes of transplantation were measured in terms of 90-day mortality and survival up to 7 years. RESULTS: High RAP was a significant risk factor for short-term and medium-term survival if Ea was low (<2.7 mmHg/mL, the median value). This group had 39.39% in-hospital mortality compared to 14.49% for RAP<15 mmHg (p∼0.005). When Ea was high, this difference in survival was not evident: 8% for RAP<15 mmHg vs 4.8% for RAP>15 mmHg (p∼0.550). This effect was mediated through a lower MPP, and the mortality due to lower MPP increased strikingly with higher body surface area (BSA). A negative correlation was observed between MPP indexed to BSA (MPPI) and the Model for End-Stage Liver Disease score (r∼-0.3580, p<0.0001) as well as creatinine (r∼-0.3551, p<0.0001). MPPI less than 40 mmHg/m2 was associated with poorer short-term (23.2% for MPPI<40 mmHg/m2 vs 7.1% for MPPI>40 mmHg/m2, p∼0.001) and medium-term survival. The impact of high RAP and low Ea on survival was evident even on medium-term follow-up; only 30% survival at 7 years follow-up for high RAP and low Ea vs 75% for RAP<15 mmHg (p∼0.0033). CONCLUSION: The acceptable blood pressure during vasodilator therapy in patients with high RAP needs to be higher, especially in those with higher BSA. MPPI less than 40 mmHg/m2 is a risk factor for survival, in the short and medium-term, after heart transplantation.

Neurogranin expression regulates mitochondrial function and redox balance in endothelial cells.

Endothelial dysfunction and endothelial activation are common early events in vascular diseases and can arise from mitochondrial dysfunction. Neurogranin (Ng) is a 17kD protein well known to regulate intracellular Ca2+-calmodulin (CaM) complex signaling, and its dysfunction is significantly implicated in brain aging and neurodegenerative diseases. We found that Ng is also expressed in human aortic endothelial cells (HAECs), and depleting Ng promotes Ca2+-CaM complex-dependent endothelial activation and redox imbalances. Endothelial-specific Ng knockout (Cre-CDH5-Ngf/f) mice demonstrate a significant delay in the flow-mediated dilation (FMD) response. Therefore, it is critical to characterize how endothelial Ng expression regulates reactive oxygen species (ROS) generation and affects cardiovascular disease. Label-free quantification proteomics identified that mitochondrial dysfunction and the oxidative phosphorylation pathway are significantly changed in the aorta of Cre-CDH5-Ngf/f mice. We found that a significant amount of Ng is expressed in the mitochondrial fraction of HAECs using western blotting and colocalized with the mitochondrial marker, COX IV, using immunofluorescence staining. Seahorse assay demonstrated that a lack of Ng decreases mitochondrial respiration. Treatment with MitoEbselen significantly restores the oxygen consumption rate in Ng knockdown cells. With the RoGFP-Orp1 approach, we identified that Ng knockdown increases mitochondrial-specific hydrogen peroxide (H2O2) production, and MitoEbselen treatment significantly reduced mitochondrial ROS (mtROS) levels in Ng knockdown cells. These results suggest that Ng plays a significant role in mtROS production. We discovered that MitoEbselen treatment also rescues decreased eNOS expression and nitric oxide (NO) levels in Ng knockdown cells, which implicates the critical role of Ng in mtROS-NO balance in the endothelial cells.

Future changes in the precipitation regime over the Arabian Peninsula with special emphasis on UAE: insights from NEX-GDDP CMIP6 model simulations.

Global warming can profoundly influence the mean climate over the Arabian Peninsula, which may significantly influence both natural and human systems. The present study aims to investigate the changes in the precipitation regime in response to climate change over the Arabian Peninsula, with special emphasis on the United Arab Emirates (UAE). This work is performed using a sub-set of high-resolution NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data derived from Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models under three different Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The changes are analyzed in three phases such as 2021-2050 (near future), 2051-2080 (mid future) and 2080-2100 (far future), with the period of 1985-2014 as the baseline. This study represents the first attempt to utilize data from NEX-GDDP models to project the regional patterns of precipitation regime across the Arabian Peninsula. Results suggest that the annual precipitation is expected to increase over most of the UAE by up to 30%, particularly intense from the mid-future onwards in all scenarios. Specifically, the spatiotemporal distribution of precipitation extremes such as intensity, 1-day highest precipitation, and precipitation exceeding 10 mm days are increasing; in contrast, the consecutive dry days may decrease towards the end of the century. The results show that the changes in extreme precipitation under a warming scenario relative to the historical period indicate progressive wetting across UAE, accompanied by increased heavy precipitation events and reduced dry spell events, particularly under the high emission scenarios. A high-resolution dataset is essential for a better understanding of changes in precipitation patterns, especially in regions where more detailed information is needed on a local scale to achieve water, food security, and environmental sustainability to formulate effective adaptation strategies for mitigating the potential risks and consequences associated with variations in wet and dry conditions.

A hybrid cloud load balancing and host utilization prediction method using deep learning and optimization techniques.

Virtual machine (VM) integration methods have effectively proven an optimized load balancing in cloud data centers. The main challenge with VM integration methods is the trade-off among cost effectiveness, quality of service, performance, optimal resource utilization and compliance with service level agreement violations. Deep Learning methods are widely used in existing research on cloud load balancing. However, there is still a problem with acquiring noisy multilayered fluctuations in workload due to the limited resource-level provisioning. The long short-term memory (LSTM) model plays a vital role in the prediction of server load and workload provisioning. This research presents a hybrid model using deep learning with Particle Swarm Intelligence and Genetic Algorithm ("DPSO-GA") for dynamic workload provisioning in cloud computing. The proposed model works in two phases. The first phase utilizes a hybrid PSO-GA approach to address the prediction challenge by combining the benefits of these two methods in fine-tuning the Hyperparameters. In the second phase, CNN-LSTM is utilized. Before using the CNN-LSTM approach to forecast the consumption of resources, a hybrid approach, PSO-GA, is used for training it. In the proposed framework, a one-dimensional CNN and LSTM are used to forecast the cloud resource utilization at various subsequent time steps. The LSTM module simulates temporal information that predicts the upcoming VM workload, while a CNN module extracts complicated distinguishing features gathered from VM workload statistics. The proposed model simultaneously integrates the resource utilization in a multi-resource utilization, which helps overcome the load balancing and over-provisioning issues. Comprehensive simulations are carried out utilizing the Google cluster traces benchmarks dataset to verify the efficiency of the proposed DPSO-GA technique in enhancing the distribution of resources and load balancing for the cloud. The proposed model achieves outstanding results in terms of better precision, accuracy and load allocation.

An in vitro assessment of optimizing implant positions in bilateral distal extension implant-assisted removable partial dentures: A microstress analysis.

AIM: The aim of this study was to analyze and compare the stress distribution on dental implants in various positions when used with implant-assisted removable partial dentures. SETTINGS AND DESIGN: This was an in vitro study. MATERIALS AND METHODS: A model representing a mandibular bilateral partially edentulous condition, with missing premolars and molars, was fabricated using epoxy resin. Two implants of similar diameter measuring 4.0 mm × 10 mm (Dentium, Korea) were inserted in the second molar and the second premolar region on either side of the model for comparing the biomechanical effect of various implant locations. Two types of loads 100N and 125N were applied vertically using universal testing machines in the premolar and molar regions. The loads on the implants beneath the cast partial denture were measured by physical stress analysis using a microstrain gauge. STATISTICAL ANALYSIS USED: A comparison of maximum stress observed at the premolar versus molar regions due to the application of the 100N and 125N loads was done using the Mann-Whitney U-test. RESULTS: In physical stress analysis, obtained results were statistically analyzed, and the result was statistically not significant (P = 0.435 at 100N and P = 0.718 at 125N) in positional changes of implant. CONCLUSION: In the current study, the statistical analysis of physical stress revealed no significant differences in stress values between the loadings at the premolar and molar regions. This suggests that the implant can be placed in either the premolar or molar region based on the availability of bone without affecting stress distribution.

A comprehensive review of biosurfactant production and its uses in the pharmaceutical industry.

Biosurfactants are naturally occurring, surface-active chemicals generated by microorganisms and have attracted interest recently because of their numerous industrial uses. Compared to their chemical equivalents, they exhibit qualities that include lower toxic levels, increased biodegradable properties, and unique physiochemical properties. Due to these traits, biosurfactants have become attractive substitutes for synthetic surfactants in the pharmaceutical industry. In-depth research has been done in the last few decades, demonstrating their vast use in various industries. This review article includes a thorough description of the various types of biosurfactants and their production processes. The production process discussed here is from oil-contaminated waste, agro-industrial waste, dairy, and sugar industry waste, and also how biosurfactants can be produced from animal fat. Various purification methods such as ultrafiltration, liquid-liquid extraction, acid precipitation, foam fraction, and adsorption are required to acquire a purified product, which is necessary in the pharmaceutical industry, are also discussed here. Alternative ways for large-scale production of biosurfactants using different statistical experimental designs such as CCD, ANN, and RSM are described here. Several uses of biosurfactants, including drug delivery systems, antibacterial and antifungal agents, wound healing, and cancer therapy, are discussed. Additionally, in this review, the future challenges and aspects of biosurfactant utilization in the pharmaceutical industry and how to overcome them are also discussed.