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Dermatological conditions are primarily prevalent in humans and are primarily caused by environmental and climatic fluctuations, as well as various other reasons. Timely identification is the most effective remedy to avert minor ailments from escalating into severe conditions. Diagnosing skin illnesses is consistently challenging for health practitioners. Presently, they rely on conventional methods, such as examining the condition of the skin. State-of-the-art technologies can enhance the accuracy of skin disease diagnosis by utilizing data-driven approaches. This paper presents a Computer Assisted Diagnosis (CAD) framework that has been developed to detect skin illnesses at an early stage. We suggest a computationally efficient and lightweight deep learning model that utilizes a CNN architecture. We then do thorough experiments to compare the performance of shallow and deep learning models. The CNN model under consideration consists of seven convolutional layers and has obtained an accuracy of 87.64% when applied to three distinct disease categories. The studies were conducted using the International Skin Imaging Collaboration (ISIC) dataset, which exclusively consists of dermoscopic images. This study enhances the field of skin disease diagnostics by utilizing state-of-the-art technology, attaining exceptional levels of accuracy, and striving for efficiency improvements. The unique features and future considerations of this technology create opportunities for additional advancements in the automated diagnosis of skin diseases and tailored treatment. [ABSTRACT FROM AUTHOR]

The application of magnetic resonance imaging (MRI) in the classification of brain tumors is constrained by the complex and time-consuming characteristics of traditional diagnostics procedures, mainly because of the need for a thorough assessment across several regions. Nevertheless, advancements in deep learning (DL) have facilitated the development of an automated system that improves the identification and assessment of medical images, effectively addressing these difficulties. Convolutional neural networks (CNNs) have emerged as steadfast tools for image classification and visual perception. This study introduces an innovative approach that combines CNNs with a hybrid attention mechanism to classify primary brain tumors, including glioma, meningioma, pituitary, and no-tumor cases. The proposed algorithm was rigorously tested with benchmark data from well-documented sources in the literature. It was evaluated alongside established pre-trained models such as Xception, ResNet50V2, Densenet201, ResNet101V2, and DenseNet169. The performance metrics of the proposed method were remarkable, demonstrating classification accuracy of 98.33%, precision and recall of 98.30%, and F1-score of 98.20%. The experimental finding highlights the superior performance of the new approach in identifying the most frequent types of brain tumors. Furthermore, the method shows excellent generalization capabilities, making it an invaluable tool for healthcare in diagnosing brain conditions accurately and efficiently. [ABSTRACT FROM AUTHOR]

Biogenic nanoparticles are considered effective alternatives to chemical pesticides for the management of pathogenic plant diseases. This study was focused on the synthesis of stable silver nanoparticles (AgNPs) to control challenging plant pathogenic bacteria in vitro and in planta. We synthesized AgNPs by reacting different proportions of silver nitrate and aqueous extract of Hedera nepalensis. The physicochemical properties of the synthesized AgNPs were determined by using various physical techniques. The TEM analysis revealed the AgNPs less than 50 nm in size and spherical shaped. For antibacterial assays, different concentrations (1000–15.62 µg/mL, 2-fold dilutions) of the extract-free AgNPs (Ef-AgNPs) or extract-mixed AgNPs (Em-AgNPs), and fruit extracts (FE) were used against plant pathogenic bacteria Erwinia carotovora subsp. carotovora, Erwinia carotovora subsp. atroseptica, and Ralstonia solanacearum. In the in vitro assays, we found significant inhibition of both bacterial species in response to maximum concentrations of AgNPs. Overall, Ef-AgNPs exhibited a higher percent inhibition of bacterial pathogens. In potato tubers assay, complete inhibition of Erwinia carotovora was observed, except for the lowest AgNPs concentration of 15.62 µg/mL. Similarly, exposure of tomato plants to Ralstonia solanacearum suspensions (OD600 = 0.2) in the soil-drenching experiment and post-exposure treatment with 1000 µg/mL and 125 µg/mL of AgNPs resulted in disease inhibition. This study provides the basis that biogenic nanoparticles prepared from Hedera nepalensis are one of the best substitutes to synthetic pesticide, having displayed better results to control the growth of phytopathogenic microbes. However, field studies need to be conducted in a controlled environment to scale up the current work and find out the efficacy of nanoparticles on a larger scale. [ABSTRACT FROM AUTHOR]

Objective: The present study aimed to investigate the inhibitory role of second mitochondria determined activator of caspases mimetic on inhibitor of apoptosis proteins (IAPs) and regulation of caspases in nonsmall cell lung cancer cell line.Materials and Methods: Dimethyl sulfoxide and 3-(4, 5-dimethyl thizol-2-yl)-2, 5-diphenyl tetrazolium bromide (MTT) assay was done to determine the IC50 of BV6 using NCI-H23 cell line. The levels of mRNA of X-linked IAP (XIAP), cellular IAP (cIAP-1), cIAP-2, caspase-6, and caspase-7 in H23 cell line were evaluated by a quantitative real-time polymerase chain reaction, while their protein expressions were tested using western blotting.Results: Two doses of BV6 dependently downregulated the expression of mRNA of XIAP (P = 0.002, P= 0.0003 vs. untreated), cIAP-1 (P = 0.05, P = 0.005 vs. untreated), and cIAP-2 (P = 0.001, P = 0.0002 vs. untreated), respectively, while the compound upregulated the mRNA expression of caspase-6 (P = 0.001, P < 0.0001 vs. untreated) and caspase-7 (P = 0.001, P = 0.0004 vs. untreated), respectively. Dose dependent of BV6 treatment significantly decreased the protein level of XIAP (P = 0.003, P = 0.007 vs. untreated), cIAP-1 (P = 0.02, P = 0.01 vs. untreated), and cIAP-2 (P = 0.008,P = 0.008 vs. untreated), respectively. However, the compound increased the protein level of caspase-6 and caspase-7 when compared to untreated control (P = 0.006,P = 0.001) and (P = 0.01, P = 0.001), respectively.Conclusions: The result showed that BV6 treatment reduced the level of mRNA of XIAP, cIAP-1, and cIAP-2 and increased the gene expression of caspase-6 and caspase-7 in NCI-H23 cell line. Therefore, the study revealed that BV6 could be used in future as additional therapeutics in lung cancer. [ABSTRACT FROM AUTHOR]

Sarcoidosis is a multi-organ disorder where immunology, genetic and environmental factors play a key role in causing Sarcoidosis, but its molecular mechanism remains unclear. Identification of its genetics profiling that regulates the Sarcoidosis network will be one of the main challenges to understand its aetiology. We have identified differentially expressed genes (DEGs) by analyzing the gene expression profiling of Sarcoidosis and compared it with healthy control. Gene set enrichment analysis showed that these DEGs were mainly enriched in the inflammatory response, immune system, and pathways in cancer. Sarcoidosis protein interaction network was constructed by a total of 877 DEGs (up-down) and calculated its network topological properties, which follow hierarchical scale-free fractal nature up to six levels of the organization. We identified a large number of leading hubs that contain six key regulators (KRs) including ICOS, CTLA4, FLT3LG, CD33, GPR29 and ITGA4 are deeply rooted in the network from top to bottom, considering a backbone of the network. We identified the transcriptional factors (TFs) which are closely interacted with KRs. These genes and their TFs regulating the Sarcoidosis network are expected to be the main target for the therapeutic approaches and potential biomarkers. However, experimental validations of KRs needed to confirm their efficacy. [ABSTRACT FROM AUTHOR]

Background. Obesity causes different diseases, eventually. In our study, the results of resistance exercises were examined on selected biochemical markers in Abha City, Saudi Arabia, which is at the height of 2,270 meters above sea level. Methods. A randomized controlled research was conducted with 60 participants equally divided into three groups, 20 subjects in each group: group 1 was composed of obese people who received resistance training exercise, group 2 was composed of the obese control group who did not receive resistance training exercise, and group 3 was composed of normal individuals who received resistance exercise training. The resistance exercises were done in the 6th and 12th weeks. Biochemical blood tests were done. Results. Comparing to the control group, glucose decreased very little with insulin also showing little difference. It has been seen that TC, TG, and LDL reduced to a reasonable extent after resistance exercise, while HDL was increased (p ≤ 0.01). Plasma urea and creatinine showed no differences. Interleukin-6 and leptin decreased significantly (p ≤ 0.01), while there was a significant elevation in adiponectin and testosterone (p ≤ 0.01) once comparing group 1 with group 2 and group 3. Conclusion. We have seen that resistance exercise helps in reducing lipid profile which will result in a decrease of the cardiac and related risk factors when conducted in obese patients in high-altitude regions. Also, alterations of the levels of interleukin-6, leptin, adiponectin, and testosterone showed that resistance exercise is of benefit and favourable in obese persons in high-altitude regions, which can also pave the way for added development of drugs related to the above parameters. [ABSTRACT FROM AUTHOR]

Akt, a serine‐threonine protein kinase, is regulated by class‐I PI3K signaling. Akt regulates a wide variety of cell processes including cell proliferation, survival, and angiogenesis through serine/threonine phosphorylation of downstream targets including mTOR and glycogen‐synthase‐kinase‐3‐beta (GSK3β). Targeting cancer‐specific overexpression of Akt protein could be an efficient way to control cancer‐cell proliferation. However, the ATP‐competitive inhibitors are challenged by the highly conserved ATP binding site, and by competition with high cellular concentrations of ATP. We previously developed an allosteric inhibitor, 2‐arylidene‐4, 7‐dimethyl indan‐1‐one (FXY‐1) that showed promising activity against several lung cancer models. In this work, we designed a congeneric series of molecules based on FXY‐1 and optimized lead based on computational, in vitro assays. Computational screening followed by enzyme‐inhibition and cell‐proliferation assays identified a derivative (FCX‐146) as a new lead molecule with threefold greater potency than the parent compound. FCX‐146 increased apoptosis in HL‐60 cells, mediated in part through decreased expression of antiapoptotic Bcl‐2 protein and increased levels of Bax‐2 and Caspase‐3. Molecular‐dynamic simulations showed stable binding of FCX‐146 to an allosteric (i.e., noncatalytic) pocket in Akt. Together, we propose FCX‐146 as a potent second‐generation arylidene indanone compound that binds to the allosteric pocket of Akt and potently inhibits its activation. [ABSTRACT FROM AUTHOR]

Background: The review is intended to provide the effectiveness of robotic-assisted gait training (RAGT) for functional gait recovery in poststroke survivors through a systematic review and to provide evidence for gait speed improvements through the meta-analysis of randomized controlled trials (RCTs). Summary: In this systematic review, PubMed, Web of Science, Wiley Online Library, Science Direct, Science Robotics, Scopus, UpToDate, MEDLINE, Google Scholar, -CINHAL, EMBASE, and EBSCO were reviewed to identify relevant RCTs. Articles included in the study were thoroughly examined by 2 independent reviewers. The included RCTs were having a PEDro score between 6 and 8 points. The initial database review yielded 1,371 studies and, following further screening; 9 studies finally were selected for systematic review and meta-analysis. Out of the 9 studies, 4 were on chronic stroke and 5 were on subacute stroke. The meta-analysis of gait speed showed an effect size value ranging between –0.91 and 0.64, with the total effect size of all the studies being –0.12. During subgroup analysis, the subacute stroke total effect size was identified as –0.48, and the chronic stroke total effect size was noted as 0.04. Meta-analysis revealed no significant differences between RAGT and conventional gait training (CGT). Key Messages: Our systematic review revealed that the RAGT application demonstrated a better or similar effect to that of CGT in a poststroke population. A meta-analysis of gait speed involving all the studies identified here indicated no significant differences between RAGT and CGT. However, the subanalysis of chronic stroke survivors showed a slight positive effect of RAGT on gait speed. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak continues to spread worldwide at a rapid rate. Currently, the absence of any effective antiviral treatment is the major concern for the global population. The reports of the occurrence of various point mutations within the important therapeutic target protein of SARS-CoV-2 has elevated the problem. The SARS-CoV-2 main protease (Mpro) is a major therapeutic target for new antiviral designs. In this study, the efficacy of PF-00835231 was investigated (a Mpro inhibitor under clinical trials) against the Mpro and their reported mutants. Various in silico approaches were used to investigate and compare the efficacy of PF-00835231 and five drugs previously documented to inhibit the Mpro. Our study shows that PF-00835231 is not only effective against the wild type but demonstrates a high affinity against the studied mutants as well. [ABSTRACT FROM AUTHOR]

E-Learning has proven to be the only resort as a replacement of traditional face-to-face learning methods in the current global lockdown due to COVID-19 pandemic. Academic institutions across the globe have invested heavily into E-Learning and the majority of the courses offered in traditional classroom mode have been converted into E-Learning mode. The success of E-Learning initiatives needs to be ensured to make it a sustainable mode of learning. The objective of the current study is to propose a holistic E-Learning service framework to ensure effective delivery and use of E-Learning Services that contributes to sustainable learning and academic performance. Based on an extensive literature review, a proposed theoretical model has been developed and tested empirically. The model identifies a broad range of success determinants and relates them to different success measures, including learning and academic performance. The proposed model was validated with the response from 397 respondents involved with an E-Learning system in the top five public universities in the southern region of Saudi Arabia through the Partial Least Squares regression technique using SmartPLS software. Five main factors (Learner's Quality, Instructor's Quality, Information's Quality, System's Quality and Institutional Quality) were identified as a determinant of E-Learning service performance which together explains 48.7% of the variance of perceived usefulness of ELS, 71.2% of the variance of use of the E-Learning system. Perceived usefulness of ELS and use of ELS together explain 70.6% of learning and academic performance of students. Hence the framework will help achieve the sustainable and successful adoption of E-Learning services. [ABSTRACT FROM AUTHOR]

Background: The red-complex bacteria are one of the most significant complexes found simultaneously in subgingival plaque next to the periodontal pocket. The current antibacterial treatment is not adequate, and multidrug resistance to it is developing. Henceforth, the antibacterial effect of the ethanolic extract of Nepeta deflersiana was put to test against red-complex bacteria in patients with chronic periodontitis. Methods: Well diffusion and micro broth dilution procedure by Alamar blue were applied to assess the zone of inhibition (ZOI), the minimum inhibitory concentration (MIC), and the minimum bactericidal concentration (MBC). Anti-virulence efficacies of the plant extract that comprise of adherence and formation of biofilms were examined by the process of adherence and biofilm production assay. Results: The crude extract of Nepeta deflersiana exhibited significant inhibitory outcome against periodontopathic bacteria with noteworthy MIC (0.78–3.12 mg/mL), inhibitory zone (12–20 mm), as well as MBC (3.12–12.50 mg/mL). The N. deflersiana extract inhibited bacterial adhesion ranging from 41% to 52%, 53% to 66%, and 60% to 79% at the given MIC × 0.5, MIC × 1, and MIC × 2 in succession. Substantial suppression was also developed in the biofilm production of the investigated periodontopathic strains following exposure to numerous concentrations of N. deflersianan extract for a period of 24 and 48 h. Conclusion: These outcomes divulge a new concept that N. deflersiana extract can be utilized to manufacture valuable antibacterial compounds to treat chronic and acute periodontitis. This identifies N. deflersiana as an essential natural source for future drug development. [ABSTRACT FROM AUTHOR]

Background: Cervical proprioception is critical in the maintenance of posture and movements, so its assessment in different cervical conditions has gained importance in recent clinical practice. Studies reporting this assessment in subjects with cervical spondylosis (CS) have not previously been investigated. The goals of the study are (1) comparison of joint position error (JPE) in subjects with CS to healthy control group. (2) Correlation of neck pain intensity to cervical proprioception in patients with CS.Methods: In a Cross-sectional study, 132 subjects with CS and 132 healthy age-matched control subjects were evaluated for cervical JPE with the cervical range of motion device. The subjects were blindfolded and repositioned their heads to a target position, which was determined by the examiner previously and their repositioning accuracy (absolute error in degrees) was measured in the frontal (flexion and extension) and transverse planes (left rotation and right rotation). The CS subjects resting neck pain intensity was assessed using visual analog scale (VAS).Results: CS subjects showed statistically significantly larger JPEs compared to healthy control subjects in all the directions tested (flexion - 95% CI = 2.38-3.55, p < 0.001, extension - 95% CI =3.26-4.33, p < 0.001, left rotation - 95% CI = 2.64 - 3.83, p < 0.001, right rotation - 95% CI = 3.77-4.76, p < 0.001). The mean JPE errors in the CS group ranged from 6.27° to 8.28° and in the control group ranged from 2.36° to 4.48°. Pearson's correlation coefficient showed a significant and positive relationship between neck pain intensity and cervical proprioception (p ≤ 0.001).Conclusions: Proprioception is impaired in subjects with CS when compared to healthy control group. Higher pain intensity was associated with greater cervical JPE in patients with CS. [ABSTRACT FROM AUTHOR]