Bi-allelic genetic variants in the translational GTPases GTPBP1 and GTPBP2 cause a distinct identical neurodevelopmental syndrome.

The homologous genes GTPBP1 and GTPBP2 encode GTP-binding proteins 1 and 2, which are involved in ribosomal homeostasis. Pathogenic variants in GTPBP2 were recently shown to be an ultra-rare cause of neurodegenerative or neurodevelopmental disorders (NDDs). Until now, no human phenotype has been linked to GTPBP1. Here, we describe individuals carrying bi-allelic GTPBP1 variants that display an identical phenotype with GTPBP2 and characterize the overall spectrum of GTP-binding protein (1/2)-related disorders. In this study, 20 individuals from 16 families with distinct NDDs and syndromic facial features were investigated by whole-exome (WES) or whole-genome (WGS) sequencing. To assess the functional impact of the identified genetic variants, semi-quantitative PCR, western blot, and ribosome profiling assays were performed in fibroblasts from affected individuals. We also investigated the effect of reducing expression of CG2017, an ortholog of human GTPBP1/2, in the fruit fly Drosophila melanogaster. Individuals with bi-allelic GTPBP1 or GTPBP2 variants presented with microcephaly, profound neurodevelopmental impairment, pathognomonic craniofacial features, and ectodermal defects. Abnormal vision and/or hearing, progressive spasticity, choreoathetoid movements, refractory epilepsy, and brain atrophy were part of the core phenotype of this syndrome. Cell line studies identified a loss-of-function (LoF) impact of the disease-associated variants but no significant abnormalities on ribosome profiling. Reduced expression of CG2017 isoforms was associated with locomotor impairment in Drosophila. In conclusion, bi-allelic GTPBP1 and GTPBP2 LoF variants cause an identical, distinct neurodevelopmental syndrome. Mutant CG2017 knockout flies display motor impairment, highlighting the conserved role for GTP-binding proteins in CNS development across species.

Uptake of nitrogen and nitrogen use efficiency of soil through agrotain coated urea and its integration with farmyard manure.

Since the green revolution, excessive utilization of chemical fertilizers has become prevalent due to concerns about the integrity of food production for the growing population. This indiscriminate use harms the fertility of the soil, especially in sandy soils where nutrient leaching, particularly nitrogen, results in yield losses as well as environmental and health problems. A pot experiment was carried out at Gomal University, Pakistan, in March 2022 to assess the nitrogen use efficiency, nitrogen uptake, and yield of okra. There were nine treatments with four replicates and the treatment combinations were established using a completely randomized design (CRD). Urea coated with agrotain (urease inhibitor) was applied each at 120 and 84 kg N ha-1 in 2 or 3 splits. Urea at 84 kg N ha-1 was also used in combination with Farmyard manure (FYM) and compared against the control (100% recommended urea). Obtained results showed that inhibitor-treated urea significantly increased soil concentrations of NO3-N and NH4-N over non-inhibitor-treated urea. The highest NO3-N was recorded where urea alone and urea treated with 3 L (3 L) agrotain was applied to 100%. The highest ammonical-N was recorded, where 70% urea treated with 3 L agrotain was applied. Urea, in combination with FYM, significantly increased the organic matter. Electrical conductivity in extract (ECe), and pH of the soil. The improvement in yield with inhibitor was at par with 70% and 100% urea. The highest improvement of 16% in fruit yield and 7.29% nitrogen use efficiency was obtained in the treatment receiving 120 kg N ha-1 treated with 3 L agrotain compared with non-inhibitor urea. The 2nd highest improvement of 10% in fruit yield on account of increased fruit length, stem diameter, and number of fruits, and 5.97% nitrogen use efficiency (NUE) was obtained in treatment receiving 120 kg N ha-1 in combination with FYM in comparison to control. These results suggested that the use of N inhibitor significantly increased the okra fruit yield on account of enhancing ammonical-N and increased N use efficiency.

Isolation and Bioassay of a New Terminalone A from Terminalia arjuna.

Terminalia arjuna possesses significant cardioprotective, antidiabetic and antioxidant properties as these properties are described in Ayurveda. In the present study, three flavonoids were isolated through the separation and chromatographic purification of the whole plant material of T. arjuna. Spectroscopic characterization identified one of them as a new flavonoid "Terminalone A (1)" and two known flavonoids i.e., 6-hydroxy-2-(4-hydroxyphenyl)-7-methoxy-4H-chromen-4-one (2) and 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one (3). The bioactivity studies showed considerable antibacterial and antioxidant (DPPH radical scavenging) potential for all the three compounds 1-3 where the compound 1 showed strong antibacterial and antioxidant activity.

Computer Vision-Based Microcalcification Detection in Digital Mammograms Using Fully Connected Depthwise Separable Convolutional Neural Network.

Microcalcification clusters in mammograms are one of the major signs of breast cancer. However, the detection of microcalcifications from mammograms is a challenging task for radiologists due to their tiny size and scattered location inside a denser breast composition. Automatic CAD systems need to predict breast cancer at the early stages to support clinical work. The intercluster gap, noise between individual MCs, and individual object's location can affect the classification performance, which may reduce the true-positive rate. In this study, we propose a computer-vision-based FC-DSCNN CAD system for the detection of microcalcification clusters from mammograms and classification into malignant and benign classes. The computer vision method automatically controls the noise and background color contrast and directly detects the MC object from mammograms, which increases the classification performance of the neural network. The breast cancer classification framework has four steps: image preprocessing and augmentation, RGB to grayscale channel transformation, microcalcification region segmentation, and MC ROI classification using FC-DSCNN to predict malignant and benign cases. The proposed method was evaluated on 3568 DDSM and 2885 PINUM mammogram images with automatic feature extraction, obtaining a score of 0.97 with a 2.35 and 0.99 true-positive ratio with 2.45 false positives per image, respectively. Experimental results demonstrated that the performance of the proposed method remains higher than the traditional and previous approaches.

A dynamic soft senor modeling method based on MW-ELWPLS in marine alkaline protease fermentation process.

The vital state variables in marine alkaline protease (MP) fermentation are difficult to measure in real-time online, hardly is the optimal control either. In this article, a dynamic soft sensor modeling method which combined just-in-time learning (JITL) technique and ensemble learning is proposed. First, the local weighted partial least squares algorithm (LWPLS) with JITL strategy is used as the basic modeling method. For further improving the prediction accuracy, the moving window (MW) is used to divide sub-dataset. Then the MW-LWPLS sub-model is built by selecting the diverse sub-datasets according to the cumulative similarity. Finally, stacking ensemble-learning method is utilized to fuse each MW-LWPLS sub-models. The proposed method is applied to predict the vital state variables in the MP fermentation process. The experiments and simulations results show that the prediction accuracy is better compared to other methods.

Investigating the Impact of Various Parameters On the Activity of Acid Phosphatases from Seedlings of Coronopus didymus.

The thermal stability of purified acid phosphatase from the germinating seedlings of Coronopus didymus (Jangli halon) was investigated by studying the impact of various thermodynamic parameters [t1/2, Ed, ΔH° (enthalpy change), ΔG° (free energy change), and ΔS° (entropy change)] of heat treatment in the temperature range of 55-75 °C. The thermal denaturation of acid phosphatase, assessed by loss in activity, was evidently followed by first-order kinetics, which varies with time and yield during the process of denaturation. The half-life of the enzyme was 693 min at 55 °C. The Ed (activation energy of denaturation) was calculated by the Arrhenius plot (30 kcal mol-1), and the Z-value was 17.3 °C. The various thermodynamic parameters studied were as follows: ΔH°, the change in enthalpy of inactivation, was 121.93 kJ mol-1 at 55 °C; ΔG°, the change in free energy of inactivation, was 110.65 kJ mol-1 at 55 °C; and ΔS°, the change in entropy of inactivation, was 34.39 J mol-1 k-1 at 55 °C. This suggests that acid phosphatase activity is thermostable to long heat treatment up to 60 °C.

The Role of Polyphenol (Flavonoids) Compounds in the Treatment of Cancer Cells.

Cancer remains a second leading cause of deaths and major public health problem. It occurs due to extensive DNA damage caused by ultraviolet radiations, ionizing radiations, environmental agents, therapeutic agents, etc. Among all cancers, the most frequently diagnosed cancers are lung (12.7%), breast (10.9%), colorectal (9.7%), and gastric cancer (7.81%). Natural compounds are most favorable against cancer on the count of their anti-cancerous ability, easy to avail and efficient. Among natural compounds, polyphenols (flavonoids, catechin, hesperetin, flavones, quercetin, phenolic acids, ellagic acid, lignans, stilbenes, etc.) represent a large and diverse group used in the prevention and treatment of cancer. Natural flavonoids are derived from different plant sources and from various medicinal plants including Petroselinum crispum, Apium graveolens, Flemingia vestita, Phyllanthus emblica, etc. Natural flavonoids possess antioxidant, anti-inflammation, as well as anti-cancerous activities through multiple pathways, they induce apoptosis in breast, colorectal, and prostate cancers, lower the nucleoside diphosphate kinase-B activity in lung, bladder and colon cancers, inhibit cell-proliferation and cell cycle arrest by suppressing the NF-kB pathway in various cancers, etc. The current review summarized the anticancer activities of natural polyphenols and their mechanisms of action.

Modern Soft-Sensing Modeling Methods for Fermentation Processes.

For effective monitoring and control of the fermentation process, an accurate real-time measurement of important variables is necessary. These variables are very hard to measure in real-time due to constraints such as the time-varying, nonlinearity, strong coupling, and complex mechanism of the fermentation process. Constructing soft sensors with outstanding performance and robustness has become a core issue in industrial procedures. In this paper, a comprehensive review of existing data pre-processing approaches, variable selection methods, data-driven (black-box) soft-sensing modeling methods and optimization techniques was carried out. The data-driven methods used for the soft-sensing modeling such as support vector machine, multiple least square support vector machine, neural network, deep learning, fuzzy logic, probabilistic latent variable models are reviewed in detail. The optimization techniques used for the estimation of model parameters such as particle swarm optimization algorithm, ant colony optimization, artificial bee colony, cuckoo search algorithm, and genetic algorithm, are also discussed. A comprehensive analysis of various soft-sensing models is presented in tabular form which highlights the important methods used in the field of fermentation. More than 70 research publications on soft-sensing modeling methods for the estimation of variables have been examined and listed for quick reference. This review paper may be regarded as a useful source as a reference point for researchers to explore the opportunities for further enhancement in the field of soft-sensing modeling.

A Non-linear Model Predictive Control Based on Grey-Wolf Optimization Using Least-Square Support Vector Machine for Product Concentration Control in L-Lysine Fermentation.

L-Lysine is produced by a complex non-linear fermentation process. A non-linear model predictive control (NMPC) scheme is proposed to control product concentration in real time for enhancing production. However, product concentration cannot be directly measured in real time. Least-square support vector machine (LSSVM) is used to predict product concentration in real time. Grey-Wolf Optimization (GWO) algorithm is used to optimize the key model parameters (penalty factor and kernel width) of LSSVM for increasing its prediction accuracy (GWO-LSSVM). The proposed optimal prediction model is used as a process model in the non-linear model predictive control to predict product concentration. GWO is also used to solve the non-convex optimization problem in non-linear model predictive control (GWO-NMPC) for calculating optimal future inputs. The proposed GWO-based prediction model (GWO-LSSVM) and non-linear model predictive control (GWO-NMPC) are compared with the Particle Swarm Optimization (PSO)-based prediction model (PSO-LSSVM) and non-linear model predictive control (PSO-NMPC) to validate their effectiveness. The comparative results show that the prediction accuracy, adaptability, real-time tracking ability, overall error and control precision of GWO-based predictive control is better compared to PSO-based predictive control.

Congenital Hypothyroidism in Neonates of a Tertiary Care Hospital.

OBJECTIVE: To determine neonatal congenital hypothyroidism among neonates born in a tertiary care hospital of Lahore Pakistan. METHODS: This cross-sectional study was carried out at Pathology Department of Allama Iqbal Medical College, Lahore in collaboration with Pediatrics and Gynecology & Obstetrics Department, Jinnah Hospital, Lahore Pakistan. A total of 770 babies were included in this study, both male and female. About 2 ml venous blood samples were collected aseptically from the neonates in sterile clotted tube. Serum was separated and serum TSH was determined by ELISA method. RESULTS: Out of total 770 neonates, 48.9% were female and 51.0% were males with the ratio of 1:1.04. Neonatal congenital hypothyroidisim (TSH, >30 mIU/L), was observed in 0.4% (Frequency, 1:257) nenates, with the incidence rate of 1:257. Female to male ratio of hypothyroid neonates was 2:1. The mode of delivery vise distribution showed, among n=251 neonates born by normal delivery, only a single case of hypothyroidism was detected, and among n=519 neonates delivered by cesarean section, only two neonates were belong to hypothyroidism. CONCLUSION: The frequency of Congenital Hypothyroidism is notably higher in pediatric community than reported in most other countries. This result emphasizes the necessity of a nationwide screening program.

Harnessing Quantum Capacitance in 2D Material/Molecular Layer Junctions for Novel Electronic Device Functionality.

Two-dimensional (2D) materials promise advances in electronic devices beyond Moore's scaling law through extended functionality, such as non-monotonic dependence of device parameters on input parameters. However, the robustness and performance of effects like negative differential resistance (NDR) and anti-ambipolar behavior have been limited in scale and robustness by relying on atomic defects and complex heterojunctions. In this paper, we introduce a novel device concept that utilizes the quantum capacitance of junctions between 2D materials and molecular layers. We realized a variable capacitance 2D molecular junction (vc2Dmj) diode through the scalable integration of graphene and single layers of stearic acid. The vc2Dmj exhibits NDR with a substantial peak-to-valley ratio even at room temperature and an active negative resistance region. The origin of this unique behavior was identified through thermoelectric measurements and ab initio calculations to be a hybridization effect between graphene and the molecular layer. The enhancement of device parameters through morphology optimization highlights the potential of our approach toward new functionalities that advance the landscape of future electronics.

Exploration of gut microbial diversity of pheasants through pyrosequencing of 16S rRNA gene.

Despite the diversity of microbiota in birds is similar to that of other animals, there is a lack of research on the gut microbial diversity of nondomesticated bird species. This study aims to address this gap in knowledge by analyzing the bacterial communities present in the gut of two important game bird species, the Ring-necked pheasant (Phasianus colchicus) and the Green pheasant (Phasianus versicolor) to understand the gut microbial diversity of these species. The gut microbiome of 10 individual pheasants from two different species was studied using pooled fecal samples. We used 16S rRNA gene sequencing on the Ion S5 XL System next-generation sequencing with Mothur and SILVA Database for taxonomic division. An average of 141 different operational taxonomic units were detected in the gut microbiome. Analysis of microbial classification revealed the presence of 191 genera belonging to 12 different phyla in both pheasants. Alpha diversity indices revealed that P. colchicus exhibited most prevalence firmicutes with bacillus species microbial community than P. versicolor. Alpha diversity indices indicated that P. colchicus had a more diverse community and P. versicolor had a greater diversity of evolutionary lineages, while both species had similar levels of species richness and sample inclusiveness. These findings may have implications for the health and well-being of pheasants, serving as a reference for their bacterial diversity. Additionally, they provide a baseline for future research and conservation efforts aimed at improving the health and well-being of these and possibly other avian species.

Isolation and biochemical characterization of novel acid phosphatase and zinc-dependent acid phosphatase from the chicken's brain.

The AcPase exhibits a specific activity of 31.32 U/mg of protein with a 728-fold purification, and the yield of the enzyme is raised to 3.15 %. The Zn2+-dependent AcPase showed a purification factor of 1.34 specific activity of 14 U/mg of proteins and a total recovery of 5.14. The SDS-PAGE showed a single band corresponding to a molecular weight of 18 kDa of AcPase and 29 kDa of Zn2+-dependent AcPase. The AcPase enzyme has shown a wide range of substrate specificity for p-NPP, phenyl phosphate and FMN, while in the case of ZnAcPase α and ß-Naphthyl phosphate and p-NPP were proved to be superior substrates. The divalent metal ions like Mg2+, Mn2+, and Ca2+ increased the activity, while other substrates decreased the enzyme activity. The Km (0.14 mM) and Vmax (21 µmol/min/mg) values of AcPase were higher than those of Zn2+-AcPase (Km = 0.5 mM; Vmax = 9.7 µmol/min/mg). The Zn2+ ions activate the Zn2+-AcPase while Fe3+, Al3+, Pb2+, and Hg2+ showed inhibition on enzyme activity. Molybdate, vanadate and phosphate were found to be competitive inhibitors of AcPase with Ki values 316 µM, 185 µM, and 1.6 mM, while in Zn2+-AcPase tartrate and phosphate also showed competitive inhibition with Ki values 3 mM and 0.5 mM respectively.

Immune-Escape Mutations Are Prevalent among Patients with a Coexistence of HBsAg and Anti-HBs in a Tertiary Liver Center in the United States.

The concurrent seropositivity of HBsAg and anti-HBs has been described among patients with chronic hepatitis B (CHB), but its prevalence is variable. HBV S-gene mutations can affect the antigenicity of HBsAg. Patients with mutations in the 'α' determinant region of the S gene can develop severe HBV reactivation under immunosuppression. In this study at a tertiary liver center in the United States, we evaluated the frequency and virological characteristics of the HBsAg mutations among CHB patients with the presence of both HBsAg and anti-HBs. In this cohort, 45 (2.1%) of 2178 patients were identified to have a coexistence of HBsAg and anti-HBs, and 24 had available sera for the genome analysis of the Pre-S1, Pre-S2, and S regions. The frequency of mutations in the S gene was significantly higher among those older than 50 years (mean 8.5 vs. 5.4 mutations per subject, p = 0.03). Twelve patients (50%) had mutations in the 'α' determinant region of the S gene. Mutations at amino acid position 126 were most common in eight subjects. Three had a mutation at position 133. Only one patient had a mutation at position 145-the classic vaccine-escape mutation. Despite the universal HBV vaccination program, the vaccine-escape mutant is rare in our cohort of predominantly Asian patients.

Alkaline protease functionalized hydrothermal synthesis of novel gold nanoparticles (ALPs-AuNPs): A new entry in photocatalytic and biological applications.

Researchers are consistently investigating novel and distinctive methods and materials that are compatible for human life and environmental conditions This study aimed to synthesize gold nanoparticles (ALPs-AuNPs) using for the first time an alkaline protease (ALPs) derived from Phalaris minor seed extract. A series of physicochemical techniques were used to inquire the formation, size, shape and crystalline nature of ALPs-AuNPs. The nanoparticles' ability to degrade methylene blue (MB) through photocatalysis under visible light irradiation was assessed. The findings demonstrated that ALPs-AuNPs exhibited remarkable efficacy by destroying 100 % of MB within a mere 30-minute irradiation period. In addition, the ALPs-AuNPs demonstrated remarkable effectiveness in inhibiting the growth of gram-positive (S. aureus) and gram-negative (E. coli) bacteria. The inhibition zones examined against the two bacterial strains were 23(±0.3) mm and 19(±0.4); 13(±0.3) mm and 11(±0.5) mm under light and dark conditions respectively. The ALPs-AuNPs exhibited significant antioxidant activity by effectively scavenging 88 % of stable and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals. As a result, the findings demonstrated that the environmentally friendly ALPs-AuNPs showed a strong potential for MB degradation and bacterial pathogen treatment.

Predicting the strengths of date fiber reinforced concrete subjected to elevated temperature using artificial neural network, and Weibull distribution.

Date palm fiber (DPF) is normally used as fiber material in concrete. Though its addition to concrete leads to decline in durability and mechanical strengths performance. Additionally, due to its high ligno-cellulose content and organic nature, when used in concrete for high temperature application, the DPF can easily degrade causing reduction in strength and increase in weight loss. To reduce these effects, the DPF is treated using alkaline solutions. Furthermore, pozzolanic materials are normally added to the DPF composites to reduce the effects of the ligno-cellulose content. Therefore, in this study silica fume was used as supplementary cementitious material in DPF reinforced concrete (DPFRC) to reduce the negative effects of elevated temperature. Hence this study aimed at predicting the residual strengths of DPFRC enhanced/improved with silica fume subjected to elevated temperature using different models such as artificial neural network (ANN), multi-variable regression analysis (MRA) and Weibull distribution. The DPFRC is produced by adding DPF in proportions of 0%, 1%, 2% and 3% by mass. Silica fume was used as partial substitute to cement in dosages of 0%, 5%, 10% and 15% by volume. The DPFRC was then subjected to elevated temperatures between 200 and 800 °C. The weight loss, residual compressive strength and relative strengths were measured. The residual compressive strength and relative strength of the DPFRC declined with addition of DPF at any temperature. Silica fume enhanced the residual and relative strengths of the DPFRC when heated to a temperature up to 400 °C. To forecast residual compressive strength (RCS) and relative strength (RS), we provide two distinct ANN models. The first layer's inputs include DPF (%), silica fume (%), temperature (°C), and weight loss (%). The hidden layer is thought to have ten neurons. M-I is the scenario in which we use RCS as an output, whereas M-II is the scenario in which we use RS as an output. The ANN models were trained using the Levenberg-Marquardt backpropagation algorithm (LMBA). Both neural networking models exhibit a significant correlation between the predicted and actual values, as seen by their respective R = 0.99462 and R = 0.98917. The constructed neural models M-I and M-II are highly accurate at predicting RCS and RS values. MRA and Weibull distribution were used for prediction of the strengths of the DPFRC under high temperature. The developed MRA was found to have a good prediction accuracy. The residual compressive strength and relative strength followed the two-parameter Weibull distribution.

Secondary findings in a large Pakistani cohort tested with whole genome sequencing.

Studies on genomic secondary findings (SFs) are diverse in participants' characteristics, sequencing methods, and versions of the ACMG SF list. Based on whole genome sequencing and the version 3.1 of the ACMG SF list, we studied SFs in 863 individuals from five different regions in Pakistan. We identified 24 ACMG SFs in 23 (2.7%) of 863 individuals: 18 of 24 were related to cardiovascular disease and four to cancer syndromes. In addition to ACMG SFs, we identified 16 (1.9%) participants with pathogenic and likely pathogenic variants in genes that were not related to the participants' clinical conditions but with clear medical actionability (non-ACMG SFs): 4 of 16 were related to eye diseases, two to metabolic disorders, and two to urinary system disorders. By testing a large Pakistani cohort with whole genome sequencing, we concluded that in countries such as Pakistan, the ACMG SF list could be expanded, and our non-ACMG SF list is one example.

Kinetic and thermodynamic studies of novel acid phosphatase isolated and purified from Carthamus oxyacantha seedlings.

Acid phosphatase (ACP) is a key enzyme in the regulation of phosphate feeding in plants. In this study, a new ACP from C. oxyacantha was isolated to homogeneity and biochemically described for the first time. Specific activity (283 nkat/mg) was found after 2573 times purification fold and (17 %) yield. Using SDS-PAGE under denaturing and nondenaturing conditions, ACP was isolated as a monomer with a molecular weight of 36 kDa. LC-MS/MS confirmed the presence of this band, suggesting that C. oxycantha ACP is a monomer. The enzyme could also hydrolyze orthophosphate monoester with an optimal pH of 5.0 and a temperature of 50 °C. Thermodynamic parameters were also determined (Ea, ΔH°, ΔG°, and ΔS°). ACP activity was further studied in the presence of cysteine, DTT, SDS, EDTA, ß-ME, Triton-X-100 H2O2, and PMSF. The enzyme had a Km of 0.167 mM and an Ea of 9 kcal/mol for p-nitrophenyl phosphate. The biochemical properties of the C. oxyacantha enzyme distinguish it from other plant acid phosphatases and give a basic understanding of ACP in C. oxyacantha. The results of this investigation also advance our knowledge about the biochemical significance of ACP in C. oxyacantha. Thermal stability over a wide pH and temperature range make it more suitable for use in harsh industrial environments. However, further structural and physiological studies are anticipated to completely comprehend its important aspects in oxyacantha species.

Prospect of herbal medication as prevention against COVID variants.

Personal immunity frolicked an essential role in combating COVID-19 impacts on human health individually and collectively in community. Literature represented the fact about food or nutritional supplements are certified to protect against diseases; this was the reason behind public trust on certain plants and other commercial products to boost up immunity against coronavirus disease. Present study was conducted to observe the attitude of common public towards natural herbs in treating various diseases and to assess the possible potential of herbal medication in prevention of negative impacts of different variants of COVID-19 on human health at herbal clinic named "Pakistan Matab". Results concluded that most of the patients (About 80%) avoided COVID-19 testing even on experiencing major symptoms and they preferred herbal medication. Patients who died by COVID-19 were also experiencing different diseases like liver and Kideny malfunctioning; old age was another significant factor in this case. About 90% of patients were COVID symptomatic and 10% were carrying other diseases during observational study period at herbal clinic. Study represented that patients who visited clinic, have a faith on herbal medication with about 60% of patients in favor of vaccine and allopathic medication in combination with herbal treatment. Study investigated that vaccine was only for one type of variant and use of herbal medicines could be better option to boost up immunity against various COVID variants.

Reducing the Threshold of Primary Prevention of Cardiovascular Disease to 10% Over 10 Years: The Implications of Altered Intensity "Statin" Therapy Guidance.

Cardiovascular disease (CVD) is a significant noncommunicable disease associated with high long-term mortality. In addition to more effective secondary therapies, the primary prevention of CVD has developed markedly in the past several years. This study aims to investigate the evidence and impact of reducing the threshold for primary CVD risk management to 10% over 10 years with "statin" therapy. To conduct research a systematic review utilizing 5 electronic database searches was completed for studies, analyzing the clinical effect of reducing the threshold of CVD risk to 10% over 10 years for primary prevention with statin therapy. The study included six (6) trials. Statin therapy was allocated to 31,018 participants. The mean age was 61 years and the mean follow-up was 4.6 years. The mean relative reduction in total cholesterol was 19% (from an average of), low-density lipoprotein cholesterol was 28.3% (from mmol/L to mmol/L) and triglycerides were 14.8% (from mmol/L to mmol/L). High-density lipoprotein cholesterol was observed to increase by a mean of 3.3% (from mmol/L to mmol/L). When examining all-cause mortality, statin therapy was associated with a 12% relative risk reduction compared with control, where overall rates were reduced from 1.4% to 1. % There is a 30% risk reduction in general major coronary events (from to %). There is a 19% risk reduction in general major cerebrovascular events with the statin group. While there is undoubtedly statistical evidence that supports the observation of the effectiveness of statin therapy for primary prevention, there is a risk that many hundreds of patients need to be treated to avoid a single adverse clinical outcome.