A Cutaneous Phaeohyphomycosis Case Caused by Paraconiothyrium cyclothyrioides in Southern China.

Paraconiothyrium cyclothyrioides is a coelomycetous fungus species that was recently identified. We present a case of an elderly farmer with chronic skin lesions of the opisthenar caused by P. cyclothyrioides.

Inorganic nitrate benefits contrast-induced nephropathy after coronary angiography for acute coronary syndromes: the NITRATE-CIN trial.

BACKGROUND AND AIMS: Contrast-induced nephropathy (CIN), also known as contrast-associated acute kidney injury (CA-AKI) underlies a significant proportion of the morbidity and mortality following coronary angiographic procedures in high-risk patients and remains a significant unmet need. In pre-clinical studies inorganic nitrate, which is chemically reduced in vivo to nitric oxide, is renoprotective but this observation is yet to be translated clinically. In this study, the efficacy of inorganic nitrate in the prevention of CIN in high-risk patients presenting with acute coronary syndromes (ACS) is reported. METHODS: NITRATE-CIN is a double-blind, randomized, single-centre, placebo-controlled trial assessing efficacy of inorganic nitrate in CIN prevention in at-risk patients presenting with ACS. Patients were randomized 1:1 to once daily potassium nitrate (12 mmol) or placebo (potassium chloride) capsules for 5 days. The primary endpoint was CIN (KDIGO criteria). Secondary outcomes included kidney function [estimated glomerular filtration rate (eGFR)] at 3 months, rates of procedural myocardial infarction, and major adverse cardiac events (MACE) at 12 months. This study is registered with ClinicalTrials.gov: NCT03627130. RESULTS: Over 3 years, 640 patients were randomized with a median follow-up of 1.0 years, 319 received inorganic nitrate with 321 received placebo. The mean age of trial participants was 71.0 years, with 73.3% male and 75.2% Caucasian; 45.9% had diabetes, 56.0% had chronic kidney disease (eGFR <60 mL/min) and the mean Mehran score of the population was 10. Inorganic nitrate treatment significantly reduced CIN rates (9.1%) vs. placebo (30.5%, P < .001). This difference persisted after adjustment for baseline creatinine and diabetes status (odds ratio 0.21, 95% confidence interval 0.13-0.34). Secondary outcomes were improved with inorganic nitrate, with lower rates of procedural myocardial infarction (2.7% vs. 12.5%, P = .003), improved 3-month renal function (between-group change in eGFR 5.17, 95% CI 2.94-7.39) and reduced 1-year MACE (9.1% vs. 18.1%, P = .001) vs. placebo. CONCLUSIONS: In patients at risk of renal injury undergoing coronary angiography for ACS, a short (5 day) course of once-daily inorganic nitrate reduced CIN, improved kidney outcomes at 3 months, and MACE events at 1 year compared to placebo.

Gender and its association with cardiac defects in down syndrome population at Children Hospital & Institute of Child Health, Lahore, Pakistan.

Objective: The objective of this study was to determine the frequency of different congenital cardiac defects co-existing in karyotypically proved Down syndrome population. It also highlighted the association between gender and pattern of congenital cardiac defects and gender as a risk factor. Methods: A cross sectional comparative study was done in the Department of Genetics, Children Hospital Lahore in the year 2017. A total of 160 patients were subjected to karyotypic analysis through blood test for determining the type of Down Syndrome and Echocardiography of all established cases was performed for determining presence and types of congenital cardiac defects. Results were evaluated in terms of establishing co-existence of various cardiac phenotypes in Down Syndrome cases. Results: In karyotypically proven 160 cases of Down syndrome, 58.1% of Down Syndrome cases and 88.2% of Down Syndrome with Congenital Cardiac Defects presented in infancy. The odds ratio (OR) suggested that females are 1.72 times more likely to experience a cardiac effect compared to males. Female gender was potentially associated (p-value 0.07) with occurrence of Patent Ductus Arteriosus (47.8%), whereas VSD (Ventricular Septal Defects) was most prevalent (41.1%) in males. Patent Ductus Arteriosus + Atrial Septal Defects (44.4%) was the commonest cardiac defect in female cases. The combined data for pattern of cardiac anomalies showed no significant association with gender, as indicated by a p-value of 0.990. Conclusion: The study concluded that most of Down syndrome cases and Down syndrome with congenital cardiac defects present to the hospital in infancy. Female cases are more prone to develop cardiac defects as compared to males. The manifestation of PDA (Patent Ductus Arteriosus) was significantly associated as an isolated anomaly in females and VSD (Ventricular Septal Defects) as isolated anomaly in males. Patent Ductus Arteriosus tend to co-exist most with ASD (Atrial Septal Defects) in female cases. Gender was not established as a risk factor for affecting the pattern of cardiac defects.

Coated cysteamine, a potential feed additive for ruminants - An updated review.

For sustainable development, better performance, and less gas pollution during rumen fermentation, there is a need to find a green and safe feed additive for ruminants. Cysteamine (CS) is a biological compound naturally produced in mammalian cells. It is widely used as a growth promoter in ruminants because of its ability to control hormone secretions. It mainly controls the circulating concentration of somatostatin and enhances growth hormone production, leading to improved growth performance. CS modulates the rumen fermentation process in a way beneficial for the animals and environment, leading to less methane production and nutrients loss. Another beneficial effect of using CS is that it improves the availability of nutrients to the animals and enhances their absorption. CS also works as an antioxidant and protects the cells from oxidative damage. In addition, CS has no adverse effects on bacterial and fungal alpha diversity in ruminants. Dietary supplementation of CS enhances the population of beneficial microorganisms. Still, no data is available on the use of CS on reproductive performance in ruminants, so there is a need to evaluate the effects of using CS in breeding animals for an extended period. In this review, the action mode of CS was updated according to recently published data to highlight the beneficial effects of using CS in ruminants.

Frequency of dysnatremia in patients admitted with COVID-19 infection and its prognostic implication.

OBJECTIVE: We aimed to investigate the frequency of dysnatremia among patients admitted with COVID-19 infection and its association with inpatient mortality. METHODS: This retrospective longitudinal study was conducted for 12 weeks. Serum sodium levels were recorded at admission, during the hospital stay, and within 48 hours of discharge or death. Logistic regression was used to determine the predictors of mortality. RESULTS: This study included 574 patients (69.7% men, age 55.6 ± 14.4 years). On admission, mean sodium was 135.9 ± 6.4 mEq/L; 39% had hyponatremia and 4.7% had hypernatremia. During admission, hypernatremia increased to 18.8%; maximum sodium in patients who survived was 140.6 ± 5.0 mEq/L versus 151.0 ± 9.9 mEq/L in those who died. The final sodium was 145.4 ± 9.4 mEq/L in patients who died versus 137.7 ± 3.7 mEq/L in those who survived (odds ratio [OR]: 1.22, 95% confidence interval [CI]: 1.13-1.32). Other predictors of mortality included ischemic heart disease (OR: 3.65, 95% CI: 1.39-9.61), acute kidney injury (OR: 6.07, 95% CI: 2.39-15.42), invasive ventilation (OR: 28.4, 95% CI: 11.14-72.40), and length of stay (OR: 0.91, 95% CI: 0.86-0.97). CONCLUSION: Hypernatremia was frequently observed in patients who were critically ill and died and may be considered a predictor of mortality in COVID-19 infection.

Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide.

The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk.

Asynchronous Federated Learning for Improved Cardiovascular Disease Prediction Using Artificial Intelligence.

Healthcare professionals consider predicting heart disease an essential task and deep learning has proven to be a promising approach for achieving this goal. This research paper introduces a novel method called the asynchronous federated deep learning approach for cardiac prediction (AFLCP), which combines a heart disease dataset and deep neural networks (DNNs) with an asynchronous learning technique. The proposed approach employs a method for asynchronously updating the parameters of DNNs and incorporates a temporally weighted aggregation technique to enhance the accuracy and convergence of the central model. To evaluate the effectiveness of the proposed AFLCP method, two datasets with various DNN architectures are tested, and the results demonstrate that the AFLCP approach outperforms the baseline method in terms of both communication cost and model accuracy.

Community centred co-design methodology for designing and implementing socio-behavioural interventions to counter COVID-19 related misinformation among marginalized population living in the squatter settlements of Karachi, Pakistan: a methodology paper.

BACKGROUND: Misinformation regarding COVID-19 pandemic and vaccination is damaging COVID-19 vaccine trust and acceptance in Low- and Middle-Income Countries (LMIC). Identification of misinformation and designing locally acceptable solutions are needed to improve COVID-19 vaccine acceptance. This study aimed to utilize community-led co-design methodology to evaluate misinformation regarding COVID-19 and develop contextual interventions to address misinformation in a marginalized peri urban slum communities of Landhi town Karachi, Pakistan. METHODS: This study was conducted between January and December 2021, in marginalized peri-urban slum dwellers of Muslimabad Colony, Landhi Town Karachi, Pakistan. We used a community-centred co-design methodology embedded within mixed study design to identify misinformation, co-design, test and implement locally acceptable solutions. The co-design methodology involved five stages of the design thinking model: (1) Empathize, (2) Define, (3) Ideate, (4) Prototype, and (5) Test. The project involved active engagement and participation of wide range of stakeholders and community beneficiaries (end users) including local EPI vaccinators, informal healthcare workers, religious leaders (male and female), schoolteachers (male and female), local government representatives, community leaders, housewives, youth, and general population. To develop a trusting relationship, and understand local culture, values, practices, and traditions, we allowed one month of observation period (observe, engage, watch, and listen) in the beginning, followed by door-to-door survey along with focus group discussions (FGD) and in-depth interviews (IDI) at baseline. Co-design workshops (separate for male and female) were conducted at each stage of co-design methodology to design and test locally acceptable solutions. CONCLUSION: Community-centred co-design methodology was not only successful in designing, testing, and evaluating locally acceptable solutions but it also actively engaged and empowered the marginalized population living in peri urban slum communities of Karachi, Pakistan.

Breast Cancer Classification through Meta-Learning Ensemble Technique Using Convolution Neural Networks.

This study aims to develop an efficient and accurate breast cancer classification model using meta-learning approaches and multiple convolutional neural networks. This Breast Ultrasound Images (BUSI) dataset contains various types of breast lesions. The goal is to classify these lesions as benign or malignant, which is crucial for the early detection and treatment of breast cancer. The problem is that traditional machine learning and deep learning approaches often fail to accurately classify these images due to their complex and diverse nature. In this research, to address this problem, the proposed model used several advanced techniques, including meta-learning ensemble technique, transfer learning, and data augmentation. Meta-learning will optimize the model's learning process, allowing it to adapt to new and unseen datasets quickly. Transfer learning will leverage the pre-trained models such as Inception, ResNet50, and DenseNet121 to enhance the model's feature extraction ability. Data augmentation techniques will be applied to artificially generate new training images, increasing the size and diversity of the dataset. Meta ensemble learning techniques will combine the outputs of multiple CNNs, improving the model's classification accuracy. The proposed work will be investigated by pre-processing the BUSI dataset first, then training and evaluating multiple CNNs using different architectures and pre-trained models. Then, a meta-learning algorithm will be applied to optimize the learning process, and ensemble learning will be used to combine the outputs of multiple CNN. Additionally, the evaluation results indicate that the model is highly effective with high accuracy. Finally, the proposed model's performance will be compared with state-of-the-art approaches in other existing systems' accuracy, precision, recall, and F1 score.

Privacy-Aware Collaborative Learning for Skin Cancer Prediction.

Cancer, including the highly dangerous melanoma, is marked by uncontrolled cell growth and the possibility of spreading to other parts of the body. However, the conventional approach to machine learning relies on centralized training data, posing challenges for data privacy in healthcare systems driven by artificial intelligence. The collection of data from diverse sensors leads to increased computing costs, while privacy restrictions make it challenging to employ traditional machine learning methods. Researchers are currently confronted with the formidable task of developing a skin cancer prediction technique that takes privacy concerns into account while simultaneously improving accuracy. In this work, we aimed to propose a decentralized privacy-aware learning mechanism to accurately predict melanoma skin cancer. In this research we analyzed federated learning from the skin cancer database. The results from the study showed that 92% accuracy was achieved by the proposed method, which was higher than baseline algorithms.

Federated Machine Learning for Skin Lesion Diagnosis: An Asynchronous and Weighted Approach.

The accurate and timely diagnosis of skin cancer is crucial as it can be a life-threatening disease. However, the implementation of traditional machine learning algorithms in healthcare settings is faced with significant challenges due to data privacy concerns. To tackle this issue, we propose a privacy-aware machine learning approach for skin cancer detection that utilizes asynchronous federated learning and convolutional neural networks (CNNs). Our method optimizes communication rounds by dividing the CNN layers into shallow and deep layers, with the shallow layers being updated more frequently. In order to enhance the accuracy and convergence of the central model, we introduce a temporally weighted aggregation approach that takes advantage of previously trained local models. Our approach is evaluated on a skin cancer dataset, and the results show that it outperforms existing methods in terms of accuracy and communication cost. Specifically, our approach achieves a higher accuracy rate while requiring fewer communication rounds. The results suggest that our proposed method can be a promising solution for improving skin cancer diagnosis while also addressing data privacy concerns in healthcare settings.

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function.

The HRAS gene plays a crucial role in regulating essential cellular processes for life, and this gene's misregulation is linked to the development of various types of cancers. Nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of HRAS can cause detrimental mutations that disrupt wild-type protein function. In the current investigation, we have employed in-silico methodologies to anticipate the consequences of infrequent genetic variations on the functional properties of the HRAS protein. We have discovered a total of 50 nsSNPs, of which 23 were located in the exon region of the HRAS gene and denoting that they were expected to cause harm or be deleterious. Out of these 23, 10 nsSNPs ([G60V], [G60D], [R123P], [D38H], [I46T], [G115R], [R123G], [P11OL], [A59L], and [G13R]) were identified as having the most delterious effect based on results of SIFT analysis and PolyPhen2 scores ranging from 0.53 to 69. The DDG values -3.21 kcal/mol to 0.87 kcal/mol represent the free energy change associated with protein stability upon mutation. Interestingly, we identified that the three mutations (Y4C, T58I, and Y12E) were found to improve the structural stability of the protein. We performed molecular dynamics (MD) simulations to investigate the structural and dynamic effects of HRAS mutations. Our results showed that the stable model of HRAS had a significantly lower energy value of -18756 kj/mol compared to the initial model of -108915 kj/mol. The RMSD value for the wild-type complex was 4.40 Å, and the binding energies for the G60V, G60D, and D38H mutants were -107.09 kcal/mol, -109.42 kcal/mol, and -107.18 kcal/mol, respectively as compared to wild-type HRAS protein had -105.85 kcal/mol. The result of our investigation presents convincing corroboration for the potential functional significance of nsSNPs in augmenting HRAS expression and adding to the activation of malignant oncogenic signalling pathways.

Epidemiological investigation of norovirus infections in Punjab, Pakistan, through the One Health approach.

Introduction: Norovirus, mainly associated with acute gastroenteritis, is very contagious and can affect a vast range of species ranging from cattle, pigs, dogs, mice, cats, sheep, and lions to humans. It is a foodborne pathogen that mainly transmits through the fecal-oral route. Methods: This is the first-ever study conducted in Lahore and Sheikhupura districts of Punjab, Pakistan, to investigate noroviruses through the One Health approach. From January 2020 to September 2021, 200 fecal samples were collected from clinical cases of hospitalized patients and 200 fecal samples from sick animals at veterinary hospitals and local farms. In addition, 500 food and beverage samples were collected from street vendors and retail stores. A predesigned questionnaire was used to assess the risk factors and clinical characteristics of sick people and animals. Results and discussion: Overall, 14% of the human clinical samples were positive by RT-PCR for genogroup GII. All bovine samples were negative. Food and beverage samples were tested in pools, resulting in sugarcane juice samples positive for genogroup GII. Previous contact with acute gastroenteritis patients, sex, and presence of vomiting were found to be significant risk factors (p ≤ 0.05). The substantial number of diarrhea cases associated with noroviruses calls for additional studies to investigate the epidemiology and transmission and to improve surveillance.

Using the artificial bee colony technique to optimize machine learning algorithms in estimating the mature weight of camels.

This paper aims to predict male and female camels' mature weight (MW) through various morphological traits using hybrid machine learning (ML) algorithms. For this aim, biometrical measurements such as birth weight (BW), length of face (FL), length of the neck (NL), a girth of the heart (HG), body length (BL), withers height (WH), and hind leg length (HLL) were used to estimate the mature weight for eight camel breeds of Pakistan. In this study, multivariate adaptive regression splines (MARS), random forest (RF), and support vector machine (SVM) were applied to develop prediction models. Furthermore, the artificial bee colony (ABC) algorithm is employed to optimize ML models' internal parameters and improve prediction accuracy. The predictive performance of ML and hybrid models was evaluated on a testing dataset using goodness-of-fit measures such as mean absolute deviation (MAD), mean absolute percentage error (MAPE), coefficient of determination (R2), and root mean square error (RMSE). The results of the study revealed the ABC-SVM model was the best predictive model. The experimental results of this study showed that the proposed ABC-SVM method could effectively improve the accuracy for MW prediction of camels, thus having a research and practical value.

An overview of biofeedback techniques in mechanical low back pain: effects on sensory integration of balance.

Low back pain is a common musculoskeletal disorder involving the lumbar spine. It affects almost 80% of the world's population and is associated with functional limitations. The reported global prevalence ranges from15-30%. Postural control involves processing the information from sensory stimulus derivative of vestibular, visual, and somatosensory systems in a coordinated manner to precisely regulate center of mass and body positioning. Failure of one or more of these systems, or incorrect processing of sensory information leads to instability or risk of fall. Low back pain can also modify the sensory input for postural control. Biofeedback can be utilized to assist "down-train" elevated muscle activity or to "up-train" weak or inhibited, muscles. Clinicians can use biofeedback to determine if patients are able to relax and evaluate psychophysiological reactions of muscles. Using biofeedback, patients can be educated about physiological processes and how biopsychosocial factors can interact causing recurrent complaints of pain.

The effect of Acacia nilotica bark extract on growth performance, carcass characteristics, immune response, and intestinal morphology in broilers as an alternative to antibiotic growth promoter.

OBJECTIVE: Present study was designed to evaluate the efficacy of Acacia nilotica bark extract as an alternative to antibiotic growth promoters in broilers. METHODS: Six hundred, day-old broiler chicks were randomly divided into six groups (NC, without any supplementation; AB, NC+Zinc Bacitracin; PB, NC+Safmannan; ANBE1, NC+A. nilotica bark extract 0.1%; ANBE3, NC+A. nilotica bark extract 0.3%; ANBE5, NC+A. nilotica bark extract 0.5%), with ten replicates per group (10 chicks/replicate) and feeding trial was lasted for 35 days. RESULTS: Results showed that weight gain (1,296.63 g) and feed conversion ratio (FCR, 1.59) of AB was better than NC, during the finisher phase. Overall FCR of AB (1.53), PB (1.54), and ANBE5 (1.54) was significantly (p<0.05) better than NC. From carcass parameters relative weight of wing and heart were highest in ANBE3 (2.5% and 1.51%, respectively). Significantly (p<0.05) highest blood glucose level was observed in NC (264.5 mg/dL) and highest albumin concentration was found in AB (1.46 mg/dL). In addition, antibody titer levels against ND and IBD were higher in ANBE5 than NC, while higher relative weight of bursa was observed in ANBE3 than NC. The villus height to crypt depth ratio in all experimental groups was better than NC. CONCLUSION: Acacia nilotica bark extract could be a suitable alternative to antibiotic growth promoters to support the growth in broilers.

A systematic review and meta-analysis of the evidence on inflammation in depressive illness and symptoms in chronic and end-stage kidney disease.

BACKGROUND: Depression affects approximately 27% of adults with chronic kidney disease (CKD) and end-stage kidney failure (ESKF). Depression in this population is associated with impaired quality of life and increased mortality. The extent of inflammation and the impact on depression in CKD/ESKF is yet to be established. Through a systematic literature review and meta-analysis, we aim to understand the relationship between depression and inflammation in CKD/ESKF patients. METHODS: We searched nine electronic databases for published studies until January 2022. Titles and abstracts were screened against inclusion and exclusion criteria. Data extraction and study quality assessment was carried out independently by two reviewers. A meta-analysis was carried out where appropriate; otherwise a narrative review of studies was completed. RESULTS: Sixty studies met our inclusion criteria and entered the review (9481 patients included in meta-analysis). Meta-analysis of cross-sectional associations revealed significantly higher levels of pro-inflammatory biomarkers; C-reactive protein; Interleukin 6 (IL-6) and tumour necrosis factor-alpha in patients with depressive symptoms (DS) compared to patients without DS. Significantly lower levels of anti-inflammatory cytokine IL-10 were found in patients with DS compared to patients without DS. Considerable heterogeneity was detected in the analysis for most inflammatory markers. CONCLUSION: We found evidence for an association of higher levels of pro-inflammatory and lower anti-inflammatory cytokines and DS in patients with CKD/ESKF. Clinical trials are needed to investigate whether anti-inflammatory therapies will be effective in the prevention and treatment of DS in these patients with multiple comorbidities.

Patient Safety Culture: A Healthcare Provider's Prospect.

INTRODUCTION AND OBJECTIVE: Safe care is a challenge around the globe, especially in developing countries. In resource-limited settings achieving patient safety is an additional complexity. Patient safety is now considered a significant public health concern worldwide. Despite a vital role in delivering quality care, little attention has been given to describe healthcare professionals' perceptions of the patient safety culture in Pakistan. This study aimed to assess the patient safety culture at a tertiary care public hospital in Lahore from the perspectives of doctors and nurses. METHODS: During this cross-sectional study, data were collected from 290 nurses and doctors using a validated safety assessment survey tool of the Hospital Survey of Patient Safety Culture (HSOPSC). The respondent's demographic characteristics and study variables influencing patient safety culture were presented, and a chi-square test was applied to identify the variables influencing patient safety. RESULTS: A total of 114 medical doctors (39.3%) and 176 registered nurses (60.7%) participated in assessing patient safety culture (PSC) across tertiary care public healthcare centers in Lahore. The dimensions of organizational learning and continuous improvement (90.6%) and teamwork within units (86.6%) were the highest. Other dimensions include feedback and communication about the error (71.8%), teamwork across units (74.9%), management support for patient safety (67.3%), supervisor/manager expectations, and actions promoting patient safety (64.6%), communication openness (64.5%), overall perceptions of patient safety (65.3%), frequency of events reported (58.7%), and handoffs and transitions (60.9%) showed moderate status. The dimensions of staffing (35.8%) and non-punitive response to errors (39.1%) had the lowest score. CONCLUSIONS: The present public hospital survey results revealed that medical staff working in a healthcare setting have a less positive perception of patient safety culture.

Synthesis, Characterization, Anti-Glycation, and Anti-Oxidant Activities of Sulfanilamide Schiff Base Metal Chelates.

The current study reports synthesis, structure establishment, anti-glycation, and anti-oxidant activities of ligand 4-[(2-hydroxynaphthalene-1-ylmethylene)-amino]-benzenesulfonamide (L) and its coordination compounds with Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) metal ions. The analytical techniques used (UV-Vis, FT-IR, CHN/S) confirmed the bidentate nature of the ligand, coordinating via O and N atoms in 2:1 ligand-to-metal ratio. The TG/DTA anylsis displayed that these compounds are thermally stable. Furthermore, the synthesized compounds were evaluated for their anti-glycation and antioxidant potential and showed significant activities with IC50 values range 184.11-386.34 µM and 37.05-126.27 µM, respectively. The Mn (IC50 = 184.11 ± 2.11 µM), Ni (IC50 = 211.26 ± 1.46 µM), Cu (IC50 = 254.56 ± 1.16 µM), and Zn (IC50 = 276.43 ± 2.14 µM) metal complexes exhibited substantial anti-glycation activity and comparatively better activity than the standard rutin (IC50 = 294.4 ± 1.50 µM), whereas Zn complex (IC50 = 37.05 ± 1.53 µM) also showed better DPPH radical scavenging activity than the standard tert-butyl-4-hydroxyanisole (IC50 = 44.7 ± 1.21 µM).