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Inflammatory microenvironment after transplantation affects the proliferation and causes senescence of adipose-derived mesenchymal stem cells (hADMSCs) thus compromising their clinical efficacy. Priming stem cells with herbal extracts is considered very promising to improve their viability in the inflammatory milieu. Aesculus indica ( A . indica ) is used to treat many inflammatory diseases in Asia for decades. Herein, we explored the protective role of A . indica extract on human adipose-derived Mesenchymal Stem Cells (hADMSCs) against Monosodium Iodoacetate (MIA) induced stress in vitro . A . indica ameliorated the injury as depicted by significantly enhanced proliferation, viability, improved cell migration and superoxide dismutase activity. Furthermore, reduced lactate dehydrogenase activity, reactive oxygen species release, senescent and apoptotic cells were detected in A . indica primed hADMSCs. Downregulation of NF-κB pathway and associated inflammatory genes, NF-κB p65/RelA and p50/NF-κB 1, Interleukin 6 (IL-6), Interleukin 1 (IL-1β), Tumor necrosis factor alpha (TNF-α) and matrix metalloproteinase 13 (MMP-13) were observed in A . indica primed hADMSCs as compared to stressed hADMSCs. Complementary to gene expression, A . indica priming reduced the release of transcription factor p65, inhibitory-κB kinase (IKK) α and β, IL-1β and TNF-α proteins expression. Our data elucidates that A . indica extract preconditioning rescued hADMSCs against oxidative stress and improved their therapeutic potential by relieving inflammation through regulation of NF-κB pathway.

To observe the combined effect of platelet-rich plasma (PRP) and preconditioned adipose-derived mesenchymal stem cells (ADMSCs) on the injured articular cartilage of the rat. Animals in the study received an intra-articular injection of PRP and preconditioned ADMSCs, both in combination and separately. The response to therapeutic intervention was evaluated by inflammatory markers, proteoglycans content, chondrogenesis and gene expression analyses. The combined therapy resulted in a reduction of  and  , increased proteoglycan content of the articular cartilage, upregulation of , and  genes. Downregulation of , and genes was observed as compared with the untreated osteoarthritis rat model. PRP potentiates the effects of ADMSCs on the repair of damaged articular cartilage.

Inflammatory microenvironment after transplantation affects the proliferation and causes senescence of adipose-derived mesenchymal stem cells (hADMSCs) thus compromising their clinical efficacy. Priming stem cells with herbal extracts is considered very promising to improve their viability in the inflammatory milieu. Aesculus indica (A. indica) is used to treat many inflammatory diseases in Asia for decades. Herein, we explored the protective role of A. indica extract on human adipose-derived Mesenchymal Stem Cells (hADMSCs) against Monosodium Iodoacetate (MIA) induced stress in vitro. A. indica ameliorated the injury as depicted by significantly enhanced proliferation, viability, improved cell migration and superoxide dismutase activity. Furthermore, reduced lactate dehydrogenase activity, reactive oxygen species release, senescent and apoptotic cells were detected in A. indica primed hADMSCs. Downregulation of NF-[kappa]B pathway and associated inflammatory genes, NF-[kappa]B p65/RelA and p50/NF-[kappa]B 1, Interleukin 6 (IL-6), Interleukin 1 (IL-1[beta]), Tumor necrosis factor alpha (TNF-[alpha]) and matrix metalloproteinase 13 (MMP-13) were observed in A. indica primed hADMSCs as compared to stressed hADMSCs. Complementary to gene expression, A. indica priming reduced the release of transcription factor p65, inhibitory-[kappa]B kinase (IKK) [alpha] and [beta], IL-1[beta] and TNF-[alpha] proteins expression. Our data elucidates that A. indica extract preconditioning rescued hADMSCs against oxidative stress and improved their therapeutic potential by relieving inflammation through regulation of NF-[kappa]B pathway.

Caregivers of dialysis patients often face substantial physical, psychological, and social challenges impacting their quality of life. This study aimed to evaluate caregivers' quality of life across multiple domains using the World Health Organization Quality of Life-BREF (WHOQOL-BREF) assessment tool. A hospital-based cross-sectional study was conducted at the Dialysis Center of Services Hospital Lahore from March to August 2024. A total of 164 caregivers of adult patients undergoing maintenance hemodialysis were enrolled using consecutive sampling after obtaining written informed consent. Data were collected through face-to-face interviews using a structured Urdu-language questionnaire incorporating the WHOQOL-BREF tool. Caregivers aged ≥18 years, providing unpaid care for ≥3 months, were included. WHOQOL-BREF assessed four quality-of-life domains. Data were analyzed using IBM SPSS Statistics for Windows, Version 26 (Released 2019; IBM Corp., Armonk, New York), with p ≤ 0.05 considered statistically significant. Out of 164 caregivers enrolled, 88 (53.7%) were male and 76 (46.3%) female, with the majority being married and having at least intermediate education. Most caregivers were sons, wives, or daughters of the dialysis patients. The mean scores across WHOQOL-BREF domains were physical health 50.01 ± 13.70, psychological health 54.10 ± 14.50, social relationships 60.83 ± 22.08, and environmental domain 51.57 ± 16.91. No statistically significant associations were observed between physical, psychological, or environmental domain scores and gender, marital status, education level, age group, or caregiver-patient relationship (p > 0.05). However, the social relationships domain showed a statistically significant difference across age groups (p = 0.017), with higher scores in older caregivers. All other domain comparisons remained statistically non-significant (p > 0.05). Overall, caregiver quality of life was highest in the social domain and lowest in the physical domain. Caregivers of dialysis patients reported moderate overall quality of life, with the highest scores in social relationships and the lowest in physical health. While caregiver age significantly influenced social domain scores, other sociodemographic factors (gender, marital status, education, and relationship) did not show significant associations. These findings highlight the need for targeted interventions addressing physical health and age-specific social support.

Background Kidney transplantation is the preferred treatment for end-stage renal disease (ESRD), offering better survival and quality of life compared to dialysis. However, in Pakistan, multiple socio-economic, legal, and healthcare-related barriers limit the accessibility of kidney transplants. The objective of the current study is to evaluate the barriers to kidney transplant among ESRD patients in Pakistan. Methods A cross-sectional study was conducted among 244 ESRD patients undergoing maintenance haemodialysis (MHD) in three major hospitals in Lahore, Pakistan. Data were collected through structured interviews using a comprehensive questionnaire covering socio-demographics, medical history, transplant awareness, donor availability, and legal knowledge. Results The mean age of participants was 46 ± 15 years, with 57.8% males and 42.2% females. Awareness of kidney transplantation was low, with only 29.9% expressing interest in undergoing transplantation. Only 5.7% had a legally eligible donor, primarily siblings (28.5%) and spouses (14.2%). Awareness of the Punjab Human Organ Transplant Authority (PHOTA) was poor (15.6%). Legal knowledge gaps were prominent, as only 9.8% knew that unrelated donors were prohibited by law and 4.9% were aware that financial compensation for organ donation is illegal. Economic constraints, lack of awareness, religious misconceptions, and gender disparities were identified as key barriers. Moreover, 3.3% of potential donors initially agreed but later withdrew, and 2.5% were rejected during medical evaluations. Conclusion The study highlights significant socioeconomic, cultural, and legal barriers to kidney transplantation in Pakistan. Targeted awareness campaigns, improved healthcare infrastructure, legal reinforcement, and financial assistance programs are needed to bridge the gap between demand and access to kidney transplants. Addressing these barriers can enhance transplantation rates and improve patient outcomes.

Inflammatory microenvironment after transplantation affects the proliferation and causes senescence of adipose-derived mesenchymal stem cells (hADMSCs) thus compromising their clinical efficacy. Priming stem cells with herbal extracts is considered very promising to improve their viability in the inflammatory milieu. Aesculus indica (A. indica) is used to treat many inflammatory diseases in Asia for decades. Herein, we explored the protective role of A. indica extract on human adipose-derived Mesenchymal Stem Cells (hADMSCs) against Monosodium Iodoacetate (MIA) induced stress in vitro. A. indica ameliorated the injury as depicted by significantly enhanced proliferation, viability, improved cell migration and superoxide dismutase activity. Furthermore, reduced lactate dehydrogenase activity, reactive oxygen species release, senescent and apoptotic cells were detected in A. indica primed hADMSCs. Downregulation of NF-κB pathway and associated inflammatory genes, NF-κB p65/RelA and p50/NF-κB 1, Interleukin 6 (IL-6), Interleukin 1 (IL-1β), Tumor necrosis factor alpha (TNF-α) and matrix metalloproteinase 13 (MMP-13) were observed in A. indica primed hADMSCs as compared to stressed hADMSCs. Complementary to gene expression, A. indica priming reduced the release of transcription factor p65, inhibitory-κB kinase (IKK) α and β, IL-1β and TNF-α proteins expression. Our data elucidates that A. indica extract preconditioning rescued hADMSCs against oxidative stress and improved their therapeutic potential by relieving inflammation through regulation of NF-κB pathway.

In this project, we have analyzed some useful models, based on an approximation introduced by G. E. P. Box; hence, the next few chapters map an odyssey wherein Box and his adage go hand in hand. In a nutshell, one- and two-sample test statistics are developed for the analysis of repeated measures designs when the dimension, d, can be large com-pared to the sample size, n (d > n). The statistics do not depend on any specific structure of the covariance matrix and can be used in a variety of situations: they are valid for testing any general linear hypothesis, are equally applicable to the design set up of profile analysis and to the usual multivariate structure, are invariant to an orthogonal linear transformation, and are also valid when the data are not high dimensional. The test statistics, a modification of the ANOVA-type statistic (Brunner, 2001), are based on Box's approximation (Box, 1954a), and follow a χf2. The estimators, the building blocks of the test statistics, are composed of quadratic and symmetric bilinear forms, and are proved to be unbiased, L2-consistent and uniformly bounded in dimension, d. This last property of estimators helps us in the asymptotic derivations in that we need not let both n and d approach infinity. We let n→∞, while keep d fixed, such that the approximation of the distribution of the test statistic to the χ2 distribution remains accurate when d > n, or even d >> n. The performance of the statistics is evaluated through simulations and it is shown that, for n as small as 10 or 20, the approximation is quite accurate, whatever be d. The statistic is also applied to a number of real data sets for numerical illustrations.

Genistein is an isoflavone first isolated from the brooming plant Dyer’s Genista tinctoria L. and is widely distributed in the Fabaceae family. As an isoflavone, mammalian genistein exerts estrogen-like functions. Several biological effects of genistein have been reported in preclinical studies, such as the antioxidant, anti-inflammatory, antibacterial, and antiviral activities, the effects of angiogenesis and estrogen, and the pharmacological activities on diabetes and lipid metabolism. The purpose of this review is to provide up-to-date evidence of preclinical pharmacological activities with mechanisms of action, bioavailability, and clinical evidence of genistein. The literature was researched using the most important keyword “genistein” from the PubMed, Science, and Google Scholar databases, and the taxonomy was validated using The Plant List. Data were also collected from specialized books and other online resources. The main positive effects of genistein refer to the protection against cardiovascular diseases and to the decrease of the incidence of some types of cancer, especially breast cancer. Although the mechanism of protection against cancer involves several aspects of genistein metabolism, the researchers attribute this effect to the similarity between the structure of soy genistein and that of estrogen. This structural similarity allows genistein to displace estrogen from cellular receptors, thus blocking their hormonal activity. The pharmacological activities resulting from the experimental studies of this review support the traditional uses of genistein, but in the future, further investigations are needed on the efficacy, safety, and use of nanotechnologies to increase bioavailability and therapeutic efficacy.

Plant diseases can cause a considerable reduction in the quality and number of agricultural products. Guava, well known to be the tropics’ apple, is one significant fruit cultivated in tropical regions. It is attacked by 177 pathogens, including 167 fungal and others such as bacterial, algal, and nematodes. In addition, postharvest diseases may cause crucial production loss. Due to minor variations in various guava disease symptoms, an expert opinion is required for disease analysis. Improper diagnosis may cause economic losses to farmers’ improper use of pesticides. Automatic detection of diseases in plants once they emerge on the plants’ leaves and fruit is required to maintain high crop fields. In this paper, an artificial intelligence (AI) driven framework is presented to detect and classify the most common guava plant diseases. The proposed framework employs the ΔE color difference image segmentation to segregate the areas infected by the disease. Furthermore, color (RGB, HSV) histogram and textural (LBP) features are applied to extract rich, informative feature vectors. The combination of color and textural features are used to identify and attain similar outcomes compared to individual channels, while disease recognition is performed by employing advanced machine-learning classifiers (Fine KNN, Complex Tree, Boosted Tree, Bagged Tree, Cubic SVM). The proposed framework is evaluated on a high-resolution (18 MP) image dataset of guava leaves and fruit. The best recognition results were obtained by Bagged Tree classifier on a set of RGB, HSV, and LBP features (99% accuracy in recognizing four guava fruit diseases (Canker, Mummification, Dot, and Rust) against healthy fruit). The proposed framework may help the farmers to avoid possible production loss by taking early precautions.

The skin is the human body’s largest organ and its cancer is considered among the most dangerous kinds of cancer. Various pathological variations in the human body can cause abnormal cell growth due to genetic disorders. These changes in human skin cells are very dangerous. Skin cancer slowly develops over further parts of the body and because of the high mortality rate of skin cancer, early diagnosis is essential. The visual checkup and the manual examination of the skin lesions are very tricky for the determination of skin cancer. Considering these concerns, numerous early recognition approaches have been proposed for skin cancer. With the fast progression in computer-aided diagnosis systems, a variety of deep learning, machine learning, and computer vision approaches were merged for the determination of medical samples and uncommon skin lesion samples. This research provides an extensive literature review of the methodologies, techniques, and approaches applied for the examination of skin lesions to date. This survey includes preprocessing, segmentation, feature extraction, selection, and classification approaches for skin cancer recognition. The results of these approaches are very impressive but still, some challenges occur in the analysis of skin lesions because of complex and rare features. Hence, the main objective is to examine the existing techniques utilized in the discovery of skin cancer by finding the obstacle that helps researchers contribute to future research.