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Milk and dairy products are integral part of human nutrition and they are considered as the carriers of higher biological value proteins, calcium, essential fatty acids, amino acids, fat, water soluble vitamins and several bioactive compounds that are highly significant for several biochemical and physiological functions. In recent years, foods containing natural antioxidants are becoming popular all over the world as antioxidants can neutralize and scavenge the free radicals and their harmful effects, which are continuously produced in the biological body. Uncontrolled free radicals activity can lead to oxidative stresses, which have been implicated in breakdown of vital biochemical compounds such as lipids, protein, DNA which may lead to diabetes, accelerated ageing, carcinogenesis and cardiovascular diseases. Antioxidant capacity of milk and milk products is mainly due to sulfur containing amino acids, such as cysteine, phosphate, vitamins A, E, carotenoids, zinc, selenium, enzyme systems, superoxide dismutase, catalase, glutathione peroxidase, milk oligosaccharides and peptides that are produced during fermentation and cheese ripening. Antioxidant activity of milk and dairy products can be enhanced by phytochemicals supplementation while fermented dairy products have been reported contained higher antioxidant capacity as compared to the non-fermented dairy products. Literature review has shown that milk and dairy products have antioxidant capacity, however, information regarding the antioxidant capacity of milk and dairy products has not been previously compiled. This review briefly describes the nutritional and antioxidant capacity of milk and dairy products.

Inflammation is a physiological response to different pathological, cellular or vascular damages due to physical, chemical or mechanical trauma. It is characterized by pain, redness, heat and swelling. Current natural drugs are carefully chosen as a novel therapeutic strategy for the management of inflammatory diseases. Different phytochemical constituents are present in natural products. These phytochemicals have high efficacy both in vivo and in vitro. Among them, flavonoids occur in many foods, vegetables and herbal medicines and are considered as the most active constituent, having the ability to attenuate inflammation. Kaempferol is a polyphenol that is richly found in fruits, vegetables and herbal medicines. It is also found in plant-derived beverages. Kaempferol is used in the management of various ailments but there is no available review article that can summarize all the natural sources and biological activities specifically focusing on the anti-inflammatory effect of kaempferol. Therefore, this article is aimed at providing a brief updated review of the literature regarding the anti-inflammatory effect of kaempferol and its possible molecular mechanisms of action. Furthermore, the review provides the available updated literature regarding the natural sources, chemistry, biosynthesis, oral absorption, metabolism, bioavailability and therapeutic effect of kaempferol.

Objective: To evaluate the prevalence of reduced visual acuity (VA), refractive errors (RE), reduced contrast sensitivity and strabismus in developmentally delayed (DD) patients. Methods: This descriptive cross sectional study was carried out in Ophthalmology Departments of Mayo Hospital, Lahore, The Children’s Hospital, Lahore and The Children’s Hospital, Multan from June 2019 to December 2019. We recruited 257 patients of either gender, between the ages of 06-16 years having intelligence quotient (IQ) ≤ 80 by Wechsler Intelligence Scale for Children (WISC) from the out-patient departments. Detailed systemic and ophthalmic history was taken and through anterior and posterior segment examination was carried out. VA was assessed with age matched VA charts. Cycloplegic refraction with 1% cyclopentolate was carried out. Contrast sensitivity was measured with hiding Heidi charts. Strabismus was assessed with Hirschberg and covers /uncover tests. Results: The mean age of the patients was 8.88 years with standard deviation (SD) of ± 2.70. The prevalence of reduced VA, RE, strabismus and reduced contrast sensitivity in these children were 43.58%, 52.92%, 52.14% and 32.7% respectively. Out of these 52.92% RE, 56 (21.79%) were myopic, 66 (25.68%) were hyperopic and 14 (05.45%) were astigmatic. The percentage of esotropia was 72 (28.02%) and exotropia was 62 (24.12%). Conclusion: The results of our study in DD children have shown that a significant number of children have reduced VA, RE, strabismus and reduced contrast sensitivity. Apart from general management of DD children by a pediatrician, the ophthalmic management of these problems must be carried out by a pediatric ophthalmologist to improve their quality of life. doi: https://doi.org/10.12669/pjms.39.6.7328 How to cite this: Ajmal Ch M, Chaudhary MA, Bukhari MN, Ahmed N. Prevalence of visual dysfunction and ocular motility disorders in developmentally delayed patients. Pak J Med Sci. 2023;39(6):---. doi: https://doi.org/10.12669/pjms.39.6.7328 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background Milk fat is one of the complex fat and most sensitive biochemical compounds towards auto-oxidation. To enhance the shelf life, milk is subjected to Ultra-high Temperature (UHT) treatment followed by aseptic packaging. During the storage, several chemical and biochemical changes take place in lipid fraction of UHT milk. In current investigation, the effect of UHT treatment and storage was determined by making a comparison in fatty acid profile, triglyceride composition, organic acids and lipid oxidation of the thermally treated and stored milk with raw milk, which was not reported in earlier investigations. Methods Raw milk samples were collected from the bulk storage facility of a dairy industry. The same milk was routed to UHT treatment and aseptically packaged samples were collected. The fatty acid profile, triglyceride composition, organic acids and lipid oxidation was determined in raw and UHT treated milk at 0, 30, 60 and 90 days. Fatty acid and triglyceride profile was determined on GC-MS while organic acids were determined by HPLC. For the measurement of induction period, professional Rancimat was used. Lipid oxidation was characterized through free fatty acids, peroxide value, anisidine value and conjugated dienes. Results Compositional attributes of milk remain unchanged during the entire length of storage. Concentrations of short-chain fatty acids in raw and UHT milk were 10.49% and 9.62%. UHT treatment resulted in 8.3% loss of short-chain fatty acids. Up to 30 days, storage did not have any significant effect on fatty acid profile of UHT milk. Concentration of medium-chain fatty acids in raw and UHT treated milk was 54.98% and 51.87%. After 30, 60 and 90 days of storage, concentration of medium chain fatty acids was found 51.23%, 47.23% and 42.82%, respectively. Concentration of C 18:1 and C 18:2 in raw and UHT milk was 26.86% and 25.43%, respectively. The loss of C 18:1 and C 18:2 in UHT treatment was 5.32%. After 30, 60 and 90 days of storage, the concentrations of C 18:1 and C 18:2 were 24.6%, 21.06% and 18.66%, respectively. Storage period of 30 days was found non-significant, while noticeable variations were found in triglyceride profile of 60 and 90 days old samples of UHT milk. UHT treatment and storage period significantly affected the concentration of organic acids in milk. After UHT treatment, concentration of lactic acid, acetic acid, citric acid, pyruvic acid, formic acid, succinic acid and oxalic acid increased by 3.45, 0.66, 3.57, 0.68, 2.24, 2.16 and 1.63 mg/100 g. Effect of storage period on the production of organic acids in UHT milk was non-significant up to 30 days. After 60 days of storage period, the increase in concentration of lactic acid, acetic acid, citric acid, pyruvic acid, formic acid, succinic acid and oxalic acid was 3.79, 0.75, 4.69, 0.78, 2.83, 3.03 and 2.38 mg/100 g. After 90 days of storage period, the increase in concentration of lactic acid, acetic acid, citric acid, pyruvic acid, formic acid, succinic acid and oxalic acid was 7.3, 2.18, 9.96, 3.58, 11.37, 5.22 and 5.96%. Free fatty acids content of raw, UHT treated and 90 days old milk were 0.08%, 0.11% and 0.19%. UHT treated version of milk showed similar peroxide value. While, the storage remarkably affected the peroxide value. After 30, 60 and 90 days, peroxide value was 0.42, 0.62 and 1.18 (MeqO 2 /kg). Induction period of raw, UHT and stored milk was strongly correlated with peroxide value and fatty acid profile. Mean value of lipase activity in raw milk was 0.73 ± 0.06 μmoles/ml. UHT treatment significantly decreased the lipase activity. The lipase activity of milk immediately after the UHT treatment was 0.18 ± 0.02 μmoles/ml. Lipase activity of UHT milk after 30, 60 and 90 days of room temperature storage was 0.44 ± 0.03, 0.95 ± 0.07 and 1.14 ± 0.09 μmoles/ml. Color, flavor and smell score decreased through the storage of UHT milk for 90 days. Conclusion The results of this investigation revealed that fatty acid and triglyceride profile changed after 60 and 90 days of storage. Production of organic acids led to the drop of pH and sensory characteristics in UHT milk during the long-term storage. Induction period can be successfully used for the determination of anticipatory shelf life of UHT milk.

Urea is the most popular and widely used nitrogenous fertilizer. High soil urease activity rapidly hydrolyses applied urea to ammonia which contributes to soil nitrogen (N) losses and reduces N use efficiency of crop plants. The ammonia losses can be minimized by the inhibition of soil urease activity which has been explored using various potential chemical inhibitors. However, the soil urease activity inhibition potential of plant extracts is rarely explored to date. In the present study, extracts of 35 plant materials were taken and evaluated against jack bean urease. Eleven extracts, showing >50% jack bean urease inhibition, were selected and further investigated in 13 soils collected from various districts of Punjab, Pakistan. Interestingly, except Capsicum annum , Melia azedarach , Citrus reticulata and Quercus infectoria , the plant extracts showed urease inhibition activities in soils, the extent of which was lower as compared to that observed in jack bean urease though. Maximum urea hydrolysis inhibition (70%) was noted with Vachellia nilotica which was 40% more than that of hydroquinone (50%) followed by that of Eucalyptus camaldulensis (24%). The extracts of V . nilotica and E . camaldulensis were coated on urea and applied to soil in the next step. At 21 st day, 239% and 116% more urea-N was recovered from soil treated with V . nilotica and E . camaldulensis extracts coated urea, respectively, as compared to uncoated urea. Conclusively, these results indicated that the coating of V . nilotica and E . camaldulensis extracts on urea prills prolonged urea persistence in soil owing to minimum urea hydrolysis, probably, the extracts of V . nilotica and E . camaldulensis showed their urease inhibition potential. The results of this study provide a base line for the identification of new soil urease inhibitor compounds from plant materials in future.

Climate change may cause severe hydrological droughts, leading to water shortages which will require to be assessed using high-resolution data. Gravity Recovery and Climate Experiment (GRACE) satellite Terrestrial Water Storage (TWSA) estimates offer a promising solution to monitor hydrological drought, but its coarse resolution (1°) limits its applications to small regions of the Indus Basin Irrigation System (IBIS). Here we employed machine learning models such as Extreme Gradient Boosting (XGBoost) and Artificial Neural Network (ANN) to downscale GRACE TWSA from 1° to 0.25°. The findings revealed that the XGBoost model outperformed the ANN model with Nash Sutcliff Efficiency (NSE) (0.99), Pearson correlation (R) (0.99), Root Mean Square Error (RMSE) (5.22 mm), and Mean Absolute Error (MAE) (2.75 mm) between the predicted and GRACE-derived TWSA. Further, Water Storage Deficit Index (WSDI) and WSD (Water Storage Deficit) were used to determine the severity and episodes of droughts, respectively. The results of WSDI exhibited a strong agreement when compared with the Standardized Precipitation Evapotranspiration Index (SPEI) at different time scales (1-, 3-, and 6-months) and self-calibrated Palmer Drought Severity Index (sc-PDSI). Moreover, the IBIS had experienced increasing drought episodes, e.g., eight drought episodes were detected within the years 2010 and 2016 with WSDI of −1.20 and −1.28 and total WSD of −496.99 mm and −734.01 mm, respectively. The Partial Least Square Regression (PLSR) model between WSDI and climatic variables indicated that potential evaporation had the largest influence on drought after precipitation. The findings of this study will be helpful for drought-related decision-making in IBIS.

Biopharmaceutical classification systems (BCS) class III drugs belongs to a group of drugs with high solubility in gastrointestinal (GI) fluids and low membrane permeability result in significantly low bioavailability. Self-emulsifying drug delivery systems (SEDDS) considered a suitable candidate to enhance the bioavailability of poorly soluble drugs by improving their membrane permeability, however, incorporating hydrophilic drugs in to these carriers remained a great challenge. The aim of this study was to develop hydrophobic ion pairs (HIPs) of a model BCS class-III drug tobramycin (TOB) in order to incorporate into SEDDS and improve its bioavailability. HIPs of TOB were formulated using anionic surfactants sodium docusate (DOC) and sodium dodecanoate (DOD). The efficiency of HIPs was estimated by measuring the concentration of formed complexes in water, zeta potential determination and log P value evaluation. Solubility studies of HIPs of TOB with DOC were accomplished to screen the suitable excipients for SEDDS development. Consequently, HIPs of TOB with DOC were loaded into SEDDS and assessed the log D SEDDS/release medium and dissociation of these complexes at different intestinal pH over time. Moreover, cytotoxic potential of HIPs of TOB and HIPs loaded SEDDS formulations was evaluated. HIPs of TOB with DOC exhibited the maximum precipitation efficiency at a stoichiometric ratio of 1:5. Log P of HIPs of TOB improved up to 1500-fold compared to free TOB. Zeta potential of TOB was shifted from positive to negative during hydrophobic ion pairing (HIP). HIPs of TOB with DOC was loaded at a concentration of 1% (w/v) into SEDDS formulations. Log D SEDDS/release medium of loaded complexes in to oily droplets was above 2 and dissociated up to 20% at various pH within 4 h. Finding of this study suggested that improvement of the lipophilic character of BCS class-III drugs followed by incorporation into oily droplets can be deliberated as a promising tool to enhance the permeation across biological membranes.

The rapid reduction of forests due to environmental impacts such as deforestation, global warming, natural disasters such as forest fires as well as various human activities is an escalating concern. The increasing frequency and severity of forest fires are causing significant harm to the ecosystem, economy, wildlife, and human safety. During dry and hot seasons, the likelihood of forest fires also increases. It is crucial to accurately monitor and analyze the large-scale changes in the forest cover to ensure sustainable forest management. Remote sensing technology helps to precisely study such changes in forest cover over a wide area over time. This research analyzes the impact of forest fires over time, identifies hotspots, and explores the environmental factors that affect forest cover change. Sentinel-2 imagery was utilized to study changes in Brunei Darussalam’s forest cover area over five years from 2017 to 2022. An object-based approach, Simple Non-Iterative Clustering (SNIC), is employed to cluster the region using NDVI values and analyze the changes per cluster. The results indicate that the area of the clusters reduced where fire incidence occurred as well as the precipitation dropped. Between 2017 and 2022, the increased forest fires and decreased precipitation levels resulted in the change in cluster areas as follows: 66.11%, 69.46%, 68.32%, 73.88%, 77.27%, and 78.70%, respectively. Additionally, hotspots in response to forest fires each year were identified in the Belait district. This study will help forest managers assess the causes of forest cover loss and develop conservation and afforestation strategies.

Flaxseeds, which have been consumed for thousands of years, have recently gained increasing popularity due to their rich composition, including omega-3 fatty acids, lignans, proteins, and fibers. These components are strongly associated with various health benefits, such as improving cardiovascular health, preventing certain types of cancer, controlling diabetes, promoting gastro-intestinal well-being, and aiding in weight management. This monograph explores the role of flaxseeds in nutrition, as well as their potential risks. Despite their numerous health benefits, flaxseeds also represent concerns due to excessive consumption and possible contamination, particularly from cyanogenic glycosides. Therefore, the levels of these compounds must be controlled, and this monograph also analyzes the available methods to detect and reduce these contaminants, ensuring the safety of flaxseed and flaxseed products consumers. Flaxseed is considered a valuable addition when incorporated into the diet, but it is necessary to continue research and promote technological improvements to maximize their benefits and minimize their risks.

In recent years, there has been a notable surge in both the complexity and volume of targeted cyber attacks, largely due to heightened vulnerabilities in widely adopted technologies. The Prediction and detection of early attacks are vital to mitigating potential risks from cyber attacks and network resilience. With the rapid increase of digital data and the increasing complexity of cyber attacks, big data has become a crucial tool for intrusion detection and forecasting. By leveraging the capabilities of unstructured big data, intrusion detection and forecasting systems can become more effective in detecting and preventing cyber attacks and anomalies. While some progress has been made on attack prediction, little attention has been given to forecasting cyber events based on time series and unstructured big data. In this research, we used the CSE-CIC-IDS2018 dataset, a comprehensive dataset containing several attacks on a realistic network. Then we used time-series forecasting techniques to construct time-series models with tuned parameters to assess the effectiveness of these techniques, which include Sequential Minimal Optimisation for regression (SMOreg), linear regression and Long Short-Term Memory (LSTM) to forecast the cyber events. We used machine learning algorithms such as Naive Bayes and random forest to evaluate the performance of the models. The best performance results of 90.4% were achieved with Support Vector Machine (SVM) and random forest. Additionally, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) metrics were used to evaluate forecasted event performance. SMOreg’s forecasted events yielded the lowest MAE, while those from linear regression exhibited the lowest RMSE. This work is anticipated to contribute to effective cyber threat detection, aiming to reduce security breaches within critical infrastructure.