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Samia Q Alghamdi,1 NF Alotaibi,2 Sameera N Al-Ghamdi,3 Laila S Alqarni,4 Touseef Amna,1 Shaima MN Moustafa,5 Ibrahim Hotan Alsohaimi,2 IA Alruwaili,2 AM Nassar2 1Department of Biology, Faculty of Science, Al-Baha University, Al-Baha, 65799 Saudi Arabia; 2Chemistry Department, College of Science, Jouf University, Sakaka, Saudi Arabia; 3Chemistry Department, Faculty of Science, Al-Baha University, Al-Baha, Saudi Arabia; 4Chemistry Department, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11623 Saudi Arabia; 5Biology Department, College of Science, Jouf University, Sakaka, Saudi ArabiaCorrespondence: AM Nassar, Jouf University, Sakaka, Aljouf, 2014, Saudi Arabia, Tel +966555978016, Email amnassar@ju.edu.saBackground: Nowadays, recycling agricultural waste is of the utmost importance in the world for the production of valuable bioactive compounds and environmental protection. Olive leaf bioactive compounds have a significant potential impact on the pharmaceutical industry. These compounds possess remarkable biological characteristics, including antimicrobial, antiviral, anti-inflammatory, hypoglycemic, and antioxidant properties.Methods: The present study demonstrates a green synthetic approach for the fabrication of nickel oxide nanoparticles (NiO-olive) using aqueous wasted olive leaf extract. Calcination of NiO-olive at 500°C led to the fabrication of pure NiO nanoparticles (NiO-pure). Different techniques, such as thermal gravimetric analysis (TGA), Fourier-transform infrared spectra (FTIR), ultraviolet-visible spectra (UV-Vis), X-ray diffraction (XRD), scanning electron microscopy (SEM) fitted with energy-dispersive X-ray analysis (EDX), and transmission electron microscopy (TEM), were used to characterize both NiO-olive and NiO-pure. The extract and nanoparticles were assessed for antiparasitic activity against adult ticks (Hyalomma dromedarii) and antimicrobial activity against Bacillus cereus, Pseudomonas aeruginosa, Aspergillus niger, and Candida albicans.Results: From XRD, the crystal sizes of NiO-olive and NiO-pure were 32.94 nm and 13.85 nm, respectively. TGA, FTIR, and EDX showed the presence of olive organic residues in NiO-olive and their absence in NiO-pure. SEM and TEM showed an asymmetrical structure of NiO-olive and a regular, semi-spherical structure of NiO-pure. UV–Vis spectra showed surface plasmon resonance of NPs. Antiparasitic activity showed the highest mortality rate of 95% observed at a concentration of 0.06 mg/mL after four days of incubation. The antimicrobial activity showed the largest inhibition zone diameter of 33 ± 0.2 mm against the Candida albicans strain.Conclusion: Nanoparticles of NiO-olive outperformed nanoparticles of NiO-pure and olive leaf extract in both antiparasitic and antimicrobial tests. These findings imply that NiO-olive may be widely used as an eco-friendly and effective antiparasitic and disinfection of sewage.Keywords: biosynthesis, olive, NiO-NP, antiparasitic, antimicrobial]

Touseef Amna,1 M Shamshi Hassan,2 Jieun Yang,1 Myung-Seob Khil,2 Ki-Duk Song,3 Jae-Don Oh,3 Inho Hwang1 1Department of Animal Sciences and Biotechnology, 2Department of Organic Materials and Fiber Engineering, Chonbuk National University, Jeonju, South Korea; 3Genomic Informatics Center, Hankyong National University, Anseong, South Korea Abstract: Recently, substantial interest has been generated in using electrospun biomimetic nanofibers of hybrids, particularly organic/inorganic, to engineer different tissues. The present work, for the first time, introduced a unique natural and synthetic hybrid micronanofiber wound dressing, composed of virgin olive oil/copper oxide nanocrystals and polyurethane (PU), developed via facile electrospinning. The as-spun organic/inorganic hybrid micronanofibers were characterized by scanning electron microscopy (SEM), energy dispersive X-ray analysis, X-ray diffraction, electron probe microanalysis, and transmission electron microscopy. The interaction of cells with scaffold was studied by culturing NIH 3T3 fibroblasts on an as-spun hybrid micronanofibrous mat, and viability, proliferation, and growth were assessed. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay results and SEM observation showed that the hybrid micronanofibrous scaffold was noncytotoxic to fibroblast cell culture and was found to benefit cell attachment and proliferation. Hence our results suggest the potential utilization of as-spun micronanoscaffolds for tissue engineering. Copper oxide–olive oil/PU wound dressing may exert its positive beneficial effects at every stage during wound-healing progression, and these micronanofibers may serve diverse biomedical applications, such as tissue regeneration, damaged skin treatment, wound healing applications, etc. Conclusively, the fabricated olive oil–copper oxide/PU micronanofibers combine the benefits of virgin olive oil and copper oxide, and therefore hold great promise for biomedical applications in the near future. Keywords: micronanofibers, copper oxide, wound healing, polyurethane, olive oil

Touseef Amna1, M Shamshi Hassan2, Ki-Taek Nam2, Yang You Bing3, Nasser AM Barakat2, Myung-Seob Khil2, Hak Yong Kim1,21Center for Healthcare Technology Development, 2Department of Organic Materials and Fiber Engineering, Chonbuk National University, Jeonju, Korea; 3Animal Science and Technology College, Henan University of Science and Technology, Luoyang, ChinaAbstract: The aim of this study was to fabricate camptothecin/iron(III) oxide (CPT/Fe2O3)-loaded poly(D,L-lactide-co-glycolide) (PLGA) composite mats to modulate the CPT release and to improve the structural integrity and antitumor activity of the released drug. The CPT/ Fe2O3-loaded PLGA ultrafine fibers were prepared for the first time by electrospinning a composite solution of CPT/Fe2O3 and neat PLGA (4 weight percent). The physicochemical characterization of the electrospun composite mat was carried out by scanning electron microscopy, energy dispersive X-ray spectroscopy, electron probe microanalysis, thermogravimetry, transmission electron microscopy, ultraviolet-visible spectroscopy, and X-ray diffraction pattern. The medicated composite fibers were evaluated for their cytotoxicity on C2C12 cells using Cell Counting Kit-8 assay (Sigma-Aldrich Corporation, St Louis, MO). The in vitro studies indicated a slow and prolonged release over a period of 96 hours with mild initial burst. Scanning electron microscopy, thermogravimetry, and X-ray diffraction studies confirmed the interaction of CPT/Fe2O3 with the PLGA matrix and showed that the crystallinity of CPT decreased after loading. Incorporation of CPT in the polymer media affected both the morphology and the size of the CPT/Fe2O3-loaded PLGA composite fibers. Electron probe microanalysis and energy dispersive X-ray spectroscopy results confirmed well-oriented composite ultrafine fibers with good incorporation of CPT/Fe2O3. The cytotoxicity results illustrate that the pristine PLGA did not exhibit noteworthy cytotoxicity; conversely, the CPT/Fe2O3 composite fibers inhibited C2C12 cells significantly. Thus, the current work demonstrates that the CPT/Fe2O3-loaded PLGA composite fibers represent a promising chemotherapeutic system for enhancing anticancer drug efficacy and selectively targeting cancer cells in order to treat diverse cancers.Keywords: camptothecin, C2C12 cells, Fe2O3 nanoparticles, electrospinning, cytotoxicity

Background: Athletes have general complaints about sleep disturbance which is important for body recovery, healthy brain and body functions, tissue wear and tear, and the body's immune system. Objective: To determine the effectiveness of Progressive Muscle Relaxation (PMR) on sleep disturbance in athletes. Methodology: N=24 athletes aged 18 to 36 years participating in a competition were included in a randomized controlled trial. Athletes who were training for a competition, aged between 18 -and 36 years, and athletes with sleep disturbance score (SDS) falling above 4 on the Athletic Sleep Screening Questionnaire were included. Athlete sleep screening questionnaire (ASSQ) was used to assess sleep disturbance score (SDS). Athletes were randomly assigned to the experimental (n=12) and control (n=12) groups. The experimental group was given progressive muscle relaxation and re-assessed the next day for SDS. Results: The pre-post analysis showed that progressive muscle relaxation reduced the athletes' sleep disturbance score significantly one day after the intervention with a large effect size (p=0.006 Cohen's d= 1.44) in the experimental group. The mean of the mean differences of SDS of both groups were compared which showed a group had a significantly improved sleep disturbance score compared to a control group with a large effect size. (Mean= 1.41 ±1.44 v/s 0.00±1.85, p≤ 0.01, Cohen's d= 1.66). Conclusion: Progressive Muscle Relaxation exercises can be a non-pharmacological method to help athletes sleep by simple head-to-toe muscles contract and relax technique. Clinical Trail No: NCT05695092

Abstract Background Dynamical mathematical models defined by a system of differential equations are typically not easily accessible to non-experts. However, forecasts based on these types of models can help gain insights into the mechanisms driving the process and may outcompete simpler phenomenological growth models. Here we introduce a friendly toolbox, SpatialWavePredict, to characterize and forecast the spatial wave sub-epidemic model, which captures diverse wave dynamics by aggregating multiple asynchronous growth processes and has outperformed simpler phenomenological growth models in short-term forecasts of various infectious diseases outbreaks including SARS, Ebola, and the early waves of the COVID-19 pandemic in the US. Results This tutorial-based primer introduces and illustrates a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using an ensemble spatial wave sub-epidemic model based on ordinary differential equations. Scientists, policymakers, and students can use the toolbox to conduct real-time short-term forecasts. The five-parameter epidemic wave model in the toolbox aggregates linked overlapping sub-epidemics and captures a rich spectrum of epidemic wave dynamics, including oscillatory wave behavior and plateaus. An ensemble strategy aims to improve forecasting performance by combining the resulting top-ranked models. The toolbox provides a tutorial for forecasting time-series trajectories, including the full uncertainty distribution derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. Conclusions We have developed the first comprehensive toolbox to characterize and forecast time-series data using an ensemble spatial wave sub-epidemic wave model. As an epidemic situation or contagion occurs, the tools presented in this tutorial can facilitate policymakers to guide the implementation of containment strategies and assess the impact of control interventions. We demonstrate the functionality of the toolbox with examples, including a tutorial video, and is illustrated using daily data on the COVID-19 pandemic in the USA.

An ensemble n-sub-epidemic modeling framework that integrates sub-epidemics to capture complex temporal dynamics has demonstrated powerful forecasting capability in previous works. This modeling framework can characterize complex epidemic patterns, including plateaus, epidemic resurgences, and epidemic waves characterized by multiple peaks of different sizes. In this tutorial paper, we introduce and illustrate SubEpiPredict, a user-friendly MATLAB toolbox for fitting and forecasting time series data using an ensemble n-sub-epidemic modeling framework. The toolbox can be used for model fitting, forecasting, and evaluation of model performance of the calibration and forecasting periods using metrics such as the weighted interval score (WIS). We also provide a detailed description of these methods including the concept of the n-sub-epidemic model, constructing ensemble forecasts from the top-ranking models, etc. For the illustration of the toolbox, we utilize publicly available daily COVID-19 death data at the national level for the United States. The MATLAB toolbox introduced in this paper can be very useful for a wider group of audiences, including policymakers, and can be easily utilized by those without extensive coding and modeling backgrounds.

Background Moderate physical activity (MPA) has proven advantages for glycemic control, cardiovascular health, and functional independence. However, physical activity is not part of routine conventional physical therapy (CPT) in managing diabetic adhesive capsulitis patients. Objective To determine the effects of moderate MPA on diabetic adhesive capsulitis (AC). Methodology A randomized control trial was conducted at the Combined Military Hospital (CMH), Muzaffarabad, Pakistan from March 2022 to October 2022. A total of n = 44 patients with diabetic AC, aged 40 to 65 years, HbA1c > 6.5% were enrolled. Group A received MPA and CPT, while Group B only received CPT for six weeks. The upper extremity function, pain, and range of motion were assessed at baseline, third week, and sixth week through the disability of arm, shoulder, and hand (DASH) questionnaire, numeric pain rating scale (NPRSS), and goniometer respectively. Results The NPRS score and ROMs showed significant improvement (p < 0.05) in group A compared to group B with a large effect size. When comparing the mean difference of the DASH score (73 + 7.21 vs. 57.9 + 12.64, p < 0.001, Cohen’s d = 1.46) was significantly improved with large effect size in group A as compared to group B. Conclusion MPA along with CPT has positive effects on patient pain, range of motion, and disability in patients with diabetic adhesive capsulitis.

Background: Teenage is an important stage for brain development, with significant impacts on education and health. Exploring how high-intensity interval training (HIIT) affects cognitive function in this population is crucial to comprehending how HIIT can improve general well-being and academic performance. Objective: To determine the effects of high-intensity interval training on cognitive flexibility among female teenagers. Methodology: A randomized clinical trial was conducted on n=40 female participants between 13-19 years without any serious medical, physical, or psychological illness for 6 months. All participants (n=40) were randomly divided into experimental (HIIT) and control groups equally. The protocols were performed in 4 mins in the first three weeks, 8 mins in the 4th to 6th week, and 12 mins in the 7th and 8th week, with sessions thrice a week. Data on cognitive flexibility was collected at baseline, after 4th week and 8th week from both groups through Digit Span (DST). Results: With-in-group analysis the experimental group showed significant improvement (p

Our study pioneers an innovative use of unsupervised machine learning, a powerful tool for navigating unclassified data, to unravel the complexities of subsurface seismic activities and extract meaningful patterns. Our central objective is to comprehensively characterize seismicity within an active region by identifying distinct seismic clusters in spatial distribution, thereby gaining a deeper understanding of subsurface stress distribution and tectonic dynamics. Employing a diverse range of clustering algorithms, with particular emphasis on Fuzzy C-Means (FCM), our research meticulously dissects the intricate physical processes that govern a complex tectonic zone. This technique effectively delineates distinct tectonic zones, aligning seamlessly with established seismological knowledge and underscoring the transformative potential of Artificial Intelligence (AI) in analyzing regional subsurface phenomena, even under conditions of data scarcity. Moreover, associating earthquakes with specific seismogenic structures significantly enhances seismic hazard analyses, potentially paving the way for autonomous insights that inform engineering hazard assessments.

Abstract Simple dynamic modeling tools can help generate real-time short-term forecasts with quantified uncertainty of the trajectory of diverse growth processes unfolding in nature and society, including disease outbreaks. An easy-to-use and flexible toolbox for this purpose is lacking. This tutorial-based primer introduces and illustrates GrowthPredict, a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using phenomenological dynamic growth models based on ordinary differential equations. This toolbox is accessible to a broad audience, including students training in mathematical biology, applied statistics, and infectious disease modeling, as well as researchers and policymakers who need to conduct short-term forecasts in real-time. The models included in the toolbox capture exponential and sub-exponential growth patterns that typically follow a rising pattern followed by a decline phase, a common feature of contagion processes. Models include the 1-parameter exponential growth model and the 2-parameter generalized-growth model, which have proven useful in characterizing and forecasting the ascending phase of epidemic outbreaks. It also includes the 2-parameter Gompertz model, the 3-parameter generalized logistic-growth model, and the 3-parameter Richards model, which have demonstrated competitive performance in forecasting single peak outbreaks. We provide detailed guidance on forecasting time-series trajectories and available software ( https://github.com/gchowell/forecasting_growthmodels ), including the full uncertainty distribution derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance across different models, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. This tutorial and toolbox can be broadly applied to characterizing and forecasting time-series data using simple phenomenological growth models. As a contagion process takes off, the tools presented in this tutorial can help create forecasts to guide policy regarding implementing control strategies and assess the impact of interventions. The toolbox functionality is demonstrated through various examples, including a tutorial video, and the examples use publicly available data on the monkeypox (mpox) epidemic in the USA.

Abstract Hyperglycemia is an outcome of dysregulated glucose homeostasis in the human body and may induce chronic elevation of blood glucose levels. Lifestyle factors such as overnutrition, physical inactivity, and psychosocials coupled with systemic low-grade inflammation have a strong negative impact on glucose homeostasis, in particular, insulin sensitivity. Together, these factors contribute to the pathophysiology of diabetes (DM) and expanding landscape of its prevalence regionally and globally. The rapid rise in the prevalence of type 2 diabetes, therefore, underscores the need for its early diagnosis and treatment. In this work, we have evaluated the discriminatory capacity of different diagnostic markers including inflammatory biomolecules and RBC (Red Blood Cell) indices in predicting the risk of hyperglycemia and borderline hyperglycemia. For that, 208,137 clinical diagnostic entries obtained over five years from Chugtai Labs, Pakistan, were retrospectively evaluated. The dataset included HbA1c (n = 142,011), complete blood count (CBC, n = 84,263), fasting blood glucose (FBG, n = 35,363), and C-reactive protein (CRP, n = 9035) tests. Our results provide four glycemic predictive models for two cohorts HbA1c and FBG) each having an overall predictive accuracy of more than 80% (p-value

A method for the in situ production of formaldehyde from dimethylsulfoxide, bromine, and cesium carbonate is reported for reactions with difluoroenolates and difluorobenzyl carbanions. This process also generates formaldehyde-d2 for the production of 2,2-difluoro-1,1-deuteroethanols. Mechanistic and computational studies further characterize the production of hydroxymethylated and hydroxydeuteromethylated difluorinated organic molecules. [ABSTRACT FROM AUTHOR]

Licorice is a therapeutic herb in traditional Chinese herbal medicine. Licorice is considered as an anti-inflammatory agent due to its suppression and inhibition of inflammatory pathways. Licorice has many bioactive compounds such as glycyrrhetinic acid, glycyrrhizin, liquiritigenin, and isoliquirtigenin which are principally accountable for its therapeutic benefits. These bioactive components reduce inflammation by preventing the activation of important inflammatory pathways including mitogen-activated protein kinases (MAPKs) and nuclear factor-kappa B (NF-κB). As a result of this tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β) and interleukin-6 (IL-6) are among the proinflammatory cytokines whose production is inhibited. Components present in licorice inhibit the activation by suppressing the IκBα phosphorylation and degradation. Moreover, licorice compounds also attenuate the MAPK signaling cascades by inhibiting the MAPK kinase phosphorylation and downstream MAPKs such as extracellular signal–regulated kinase (ERK), p38 MAPK, and c-Jun N-terminal kinase (JNK). The present review focuses on the current understanding of licorice effect on the NF-κB and MAPK inflammatory cell signaling pathways at molecular level. Furthermore, emerging evidence suggested that licorice-derived bioactive compounds may attenuate the molecular mechanism which is associated with inflammation, providing the additional insights into the therapeutic potential. Further studies explained the precise molecular mechanism at the cellular level underlying the licorice anti-inflammatory effect and potential application in managing inflammatory disorders. In conclusion, licorice has a complex mode of action and is a valuable natural anti-inflammatory. Its natural origin and effectiveness in clinical applications make it an intriguing topic for additional study. As licorice becomes more widely used in medicine, future research should focus on refining its formulations to optimize therapeutic advantages.

Context: Rivaroxaban is an oral direct factor Xa inhibitor reducing the risk of systemic embolism and stroke in patients with nonvalvular atrial fibrillation. Aims: The primary objective was to evaluate the effectiveness of rivaroxaban therapy in reducing the risk of systemic embolism and stroke in patients with nonvalvular atrial fibrillation, whereas secondary objectives were to monitor therapy safety and the patients' adherence to treatment. Settings and Design: The prospective, postmarketing clinical trial was conducted on patients with nonvalvular atrial fibrillation with one or more risk factors, such as congestive heart failure, hypertension, and diabetes mellitus, who suffered a stroke or a transient ischemic attack. Subjects and Methods: At the baseline visit, the CHA2DS2 score was determined, and therapy was introduced. At three control visits (1, 3, and 6 months after baseline), systemic embolism, stroke, bruises, or bleeding occurrences were recorded. Furthemore, adverse events were monitored, and the Morisky score (MMAS-8) for treatment compliance was determined. Results were compared to previous studies. Results: The study included 471 patients. The incidence rate in events per 100 patient-years (95% confidence interval) was 2.6 (0.1–5.1) for systemic embolism and 4.3 (1.6–7.0) for stroke. The most common form of bleeding during rivaroxaban therapy was epistaxis. Adverse events were reported in 12 (2.7%) patients. Therapy adherence was in the range of medium adherence for the entire study period, with the average score decreasing significantly from the 1st to 6th months (P < 0.001). Conclusions: Rivaroxaban showed good efficacy and safety in reducing the risk of systemic embolism and stroke in patients with nonvalvular atrial fibrillation including patients with comorbidities.

Abstract Background Ventricular septal defects (VSDs) are one of the leading causes of death due to cardiac anomalies during the first months of life. The prevalence of VSD in neonates is reported up to 4%. Despite the remarkable progress in medication, treatment and surgical procedure for VSDs, the genetic etiology of VSDs is still in infancy because of the complex genetic and environmental interactions. Methods Three hundred fifty subjects (200 VSD children and 150 healthy controls) were recruited from different pediatric cardiac units. Pediatric clinical and demographic data were collected. A total of six variants, rs1017 (ISL1), rs7240256 (NFATc1), rs36208048 (VEGF), variant of HEY2, rs11067075 (TBX5) and rs1801133 (MTHFR) genes were genotyped by tetra-ARMS PCR and PCR–RFLP methods. Results The results showed that in cases, the rs1017 (g.16138A > T) variant in the ISL1 gene has an allele frequency of 0.42 and 0.58 respectively for the T and A alleles, and 0.75 and 0.25 respectively in the controls. The frequencies of the AA, TA and TT genotypes were, 52%, 11% and 37% in cases versus 21%, 8% and 71% respectively in the controls. For the NFATc1 variant rs7240256, minor allele frequency (MAF) was 0.43 in cases while 0.23 in controls. For the variant in the VEGF gene, genotype frequencies were 0% (A), 32% (CA) and 68% (CC) in cases and 0.0%, 33% and 67% respectively in controls. The allele frequency of C and A were 0.84 and 0.16 in cases and 0.83 and 0.17 respectively in controls. The TBX5 polymorphism rs11067075 (g.51682G > T) had an allelic frequency of 0.44 and 0.56 respectively for T and G alleles in cases, versus 0.26 and 0.74 in the controls. We did not detect the presence of the HEY2 gene variant (g.126117350A > C) in our pediatric cohort. For the rs1801133 (g.14783C > T) variant in the MTHFR gene, the genotype frequencies were 25% (CC), 62% (CT) and 13% (TT) in cases, versus 88%, 10% and 2% in controls. The ISL1, NFATc1, TBX5 and MTHFR variants were found to be in association with VSD in the Pakistani pediatric cohort whilst the VEGF and HEY2 variants were completely absent in our cohort. Conclusion We propose that a wider programme of genetic screening of the Pakistani population for genetic markers in heart development genes would be helpful in reducing the risk of VSDs.

Abstract Background The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ( $${R}_{0}$$ R 0 ) for twelve most affected South American countries. Methods We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and $${R}_{0}$$ R 0 of COVID-19 for the South American countries. Results We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and $${R}_{0}$$ R 0 (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America. Conclusions This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America. Graphical Abstract

The aim of the current study was to evaluate the toxic effect of silver nanoparticles (Ag-NPs) on biochemical biomarkers, immune responses, and the curative potential effects of vitamin C and E on grass carp. Fish (n = 420) with an average initial body weight of 8.045 ± 0.13 g were shifted to glass aquaria (36 x 18 x 18 inches, filled with 160-L tap water) in triplicates. Aquaria were randomly designated as A, B, C, D with alone Ag-NPs (Control (0), 0.25, 0.50, 0.75 mg/L) and E, F, G with Ag-NPs + Vit. C + Vit. E (0.25+0.25+0.25, 0.50+0.50+0.50, 0.75+0.75+0.75 mg/L). NPs particles were administrated viz, oral and intravenous routes for 7 days. The results indicated that both routes had non-significant effect, but levels of Ag-NPs had significant effect. Treatments C, D and G showed significant decrease in levels of RBC, HGB and HCT except for WBC and NEUT levels, which significantly increased. ALT, ALP, AST, urea, and creatinine showed significant increase in activity in the C, D, and G groups. CAT, SOD decreased significantly in all Ag-NPs alone groups, while significantly increased with vitamin E and C. LYZ, TP, ALB, GLB showed significant low activity in the B, C, and D groups while significantly high activity in the E, F, and G groups. Cortisol, glucose and triglycerides showed significant increase in the B, C, and D groups, while E, F, and G groups showed significant low levels of triglycerides, COR, and GLU. Cholesterol level was same across all treatment groups. In conclusion, vitamin E and C as powerful antioxidants protect the fish against Ag-NPs except high dose level of 0.75mg/L, while 0.25mg/L of Ag-NPs was presumably safe for C. idella.

We analyze an ensemble of n-sub-epidemic modeling for forecasting the trajectory of epidemics and pandemics. These ensemble modeling approaches, and models that integrate sub-epidemics to capture complex temporal dynamics, have demonstrated powerful forecasting capability. This modeling framework can characterize complex epidemic patterns, including plateaus, epidemic resurgences, and epidemic waves characterized by multiple peaks of different sizes. We systematically assess their calibration and short-term forecasting performance in short-term forecasts for the COVID-19 pandemic in the USA from late April 2020 to late February 2022. We compare their performance with two commonly used statistical ARIMA models. The best fit sub-epidemic model and three ensemble models constructed using the top-ranking sub-epidemic models consistently outperformed the ARIMA models in terms of the weighted interval score (WIS) and the coverage of the 95% prediction interval across the 10-, 20-, and 30-day short-term forecasts. In our 30-day forecasts, the average WIS ranged from 377.6 to 421.3 for the sub-epidemic models, whereas it ranged from 439.29 to 767.05 for the ARIMA models. Across 98 short-term forecasts, the ensemble model incorporating the top four ranking sub-epidemic models (Ensemble(4)) outperformed the (log) ARIMA model 66.3% of the time, and the ARIMA model, 69.4% of the time in 30-day ahead forecasts in terms of the WIS. Ensemble(4) consistently yielded the best performance in terms of the metrics that account for the uncertainty of the predictions. This framework can be readily applied to investigate the spread of epidemics and pandemics beyond COVID-19, as well as other dynamic growth processes found in nature and society that would benefit from short-term predictions.

Objectives: To study the effect of the COVID-19 pandemic on the socio-demographic and clinical profiles of patients who were admitted to a tertiary psychiatric hospital in the UAE during 2020 compared with the corresponding period in 2019, and to evaluate the effect of the pandemic on the mental healthcare system. Methods: Socio-demographic and clinical data of the patients from March 11 to June 11 in 2019 and 2020 was collected anonymously from hospital electronic medical records. The characteristics of the two patient cohorts were compared statistically. Results: A total of 337 patient admissions to the hospital during March 11 to June 11, 2020 against 189 admissions in the corresponding period in 2019. In the multiple logistic regression model, the admissions in 2020 were significantly more likely to be diagnosed with bipolar disorder (odds ratio ( OR) = 1.902; p =0.028) and were significantly to have no prior psychiatric history (OR = 4.255, p < 0.001), compared to those cases admitted in 2019. Conclusions: This study is unique for evaluating the patterns of hospitalization at a specific psychiatric hospital during the first three months of the pandemic in the UAE. The findings of this study will support the public health sector in designing mental health strategies in pandemic situations. A longitudinal multicenter study would give more insight into the overall impact of the pandemic on mental health.

Abstract Background Great disparities in immunization coverage exist in Pakistan between urban and rural areas. However, coverage estimates for large peri-urban slums in Sindh are largely unknown and implementation challenges remain unexplored. This study explores key supply- and demand-side immunization barriers in peri-urban slums, as well as strategies to address them. It also assesses immunization coverage in the target slums. Methods Conducted in four peri-urban slums in Karachi, this mixed-methods study consists of a baseline cross-sectional coverage survey of a representative sample of 840 caregivers of children aged 12–23 months, and 155 in-depth interviews (IDIs) through purposive sampling of respondents (caregivers, community influencers and immunization staff). After identifying the barriers, a further six IDIs were then conducted with immunization policy-makers and policy influencers to determine strategies to address these barriers, resulting in the development of an original validated implementation framework for immunization in peri-urban slums. A thematic analysis approach was applied to qualitative data. Results The survey revealed 49% of children were fully vaccinated, 43% were partially vaccinated and 8% were unvaccinated. Demand-side immunization barriers included household barriers, lack of knowledge and awareness, misconceptions and fears regarding vaccines and social and religious barriers. Supply-side barriers included underperformance of staff, inefficient utilization of funds, unreliable immunization and household data and interference of polio campaigns with immunization. The implementation framework’s policy recommendations to address these barriers include: (1) improved human resource management; (2) staff training on counselling; (3) re-allocation of funds towards incentives, outreach, salaries and infrastructure; (4) a digital platform integrating birth registry and vaccination tracking systems for monitoring and reporting by frontline staff; (5) use of digital platform for immunization targets and generating dose reminders; and (6) mutual sharing of resources and data between the immunization, Lady Health Worker and polio programmes for improved coverage. Conclusions The implementation framework is underpinned by the study of uncharted immunization barriers in complex peri-urban slums, and can be used by implementers in Pakistan and other developing countries to improve immunization programmes in limited-resource settings, with possible application at a larger scale. In particular, a digital platform integrating vaccination tracking and birth registry data can be expanded for nationwide use.

Abstract Background Diabetes mellitus (DM), an endocrine disease is characterized by increased level of blood glucose. Diabetes may affect other functions of the body and organs including, renal function and lipid metabolism. Pandanus tectorius (P. tectorius) Parkinson ex Du Roi is a small tree used in folk medicine in treatment of many diseases. Methods Diabetes in rats was induced by intraperitoneal injection of alloxan at a dose of 100 mg/kg body weight for 3 days. Water and ethanol extracts of root, stem and leave of P. tectorius were given to rats at 200 mg/kg body weight at day 3. Rats were sacrificed on day 4 after 12 h fasting. Serum glucose and other biochemical parameters like liver enzymes; [alanine aminotransferases (ALT), aspartate aminotransferases (AST), alkaline phosphatase (ALP) and lactate dehydrogenase (LDH)], kidney parameters (urea & creatinine), lipid profile [total cholesterol, HDL and LDL cholesterol and triglycerides] and coronary artery risk index (CRI) were estimated in blood serum. Antioxidant potential, polyphenol content and phytochemical constituents in different parts of P. tectorius were also determined. Results Results showed that water extract of stem and ethanol extract of root of P. tectorius produced maximum fall in sugar level of alloxan diabetic rats. Extracts of all three plant parts significantly dropped the increased level of urea and creatinine with maximum reduction in creatinine was observed by water extract of root. P.tectorius extracts showed positive effect on liver enzymes and lipid profile by bringing them closer to normal range in comparison to alloxan diabetic control rats. Phytochemical screening indicated presence of flavonoids, alkaloids, tannins and saponin in P. tectorius. In DPPH free radical scavenging test the highest antioxidant potential was found in water extract of roots, while ethanol extract of stem also showed good activity. Conclusion The study demonstrated that different parts of P.tectorius have potential to attenuate diabetes and diabetes related complications like, liver, kidney dysfunction and lipid metabolism.

Abstract Background Ventricular septal defects (VSDs) are malformations in the septum separating the heart’s ventricles. VSDs may present as a single anomaly (isolated/nonsyndromic VSD) or as part of a group of phenotypes (syndromic VSD). The exact location of the defect is crucial in linking the defect to the underlying genetic cause. The number of children visiting cardiac surgery units is constantly increasing. However, there are no representative data available on the genetics of VSDs in Pakistani children. Methods Two hundred forty-two subjects (121 VSD children and 121 healthy controls) were recruited from pediatric cardiac units of Lahore. The clinical and demographic data of the subjects were collected. A total of four SNPs, one each from MTRR, GATA4, VEGF, and ISL1 genes were genotyped by PCR-RFLP. Results The results showed that the minor allele (T) frequency (MAFs) for the MTRR gene variant rs1532268 (c.524C > T) was 0.20 and 0.41 in the controls and the cases, respectively, with the genotype frequencies 3, 35, 62% in the controls and 12, 59 and 29% in the cases for TT, CT, CC genotypes, respectively (allelic OR: 5.73, CI: 3.82–8.61, p-value: 5.11 × 10− 7). For the GATA4 variant rs104894073 (c.886G > A), the MAF for the controls and the cases was 0.16 and 0.37, respectively, the frequencies of AA, GA and GG genotypes were 2, 28, and 70% in the controls and 5, 64 and 31% of the cases (allelic OR: 3.08, CI: 2.00–4.74, p-value: 8.36 × 10− 8). The rs699947 (c.-2578C > A) of VEGF gene showed MAF 0.36 and 0.53 for the controls and cases, respectively, with the genotype frequencies 13, 42, and 45% in the controls and 22, 15, and 63% in the cases for the AA, CA, CC (allelic OR: 2.03, CI: 1.41–2.92, p-value: 0.0001). The ISL1 gene variant rs6867206 (g.51356860 T > C), the MAFs were 0.26 and 0.31 in the controls and cases, respectively. The genotype frequencies were 48, 52, 0% in the controls and 39, 61, 0% in the cases for TT, TC, CC genotypes (allelic OR: 0.27, CI: 0.85–1.89, p-value: 0.227). The MTRR, GATA4 and VEGF variants showed association while ISL1 variant did not appear to be associated with the VSD in the recruited cohort. Conclusion This first report in Pakistani children demonstrates that single nucleotide polymorphisms in genes encoding transcription factors, signaling molecules and structural heart genes involved in fetal heart development are associated with developmental heart defects., however further work is needed to validate the results of the current investigation.

Objectives: In South Korea, 13 745 cases of coronavirus disease (COVID-19) had been reported as of 19 July, 2020. To examine spatiotemporal changes in the transmission potential, we aimed to present regional estimates of the doubling time and reproduction number (Rt) for COVID-19 in the country. Methods: Daily series of confirmed COVID-19 cases in the most affected regions were extracted from publicly available sources. We employed established mathematical and statistical methods to investigate the time-varying reproduction numbers and doubling time for COVID-19 in Korea. Results: At the regional level, Seoul and Gyeonggi Province experienced the first peak of COVID-19 in early March, followed by a second wave in early June, withRt exceeding 3.0 and mean doubling time ranging from 3.6 to 10.1 days. As of 19 July, 2020, Gyeongbuk Province and Daegu had yet to experience a second wave of the disease. During the first wave, mean Rt for these areas reached 3.5–4.4, and doubling time ranged from 2.8 to 4.6 days. Conclusions: Our findings support the effectiveness of control measures against COVID-19 in Korea. However, the easing of restrictions that had been imposed by the government in May 2020 facilitated a second wave in the greater Seoul area.

Abstract Sedentary life styles coupled with high-calorie diets and unhealthy social habits such as smoking, have put an ever-increasing number of people at risk of cardiovascular disorders (CVD), worldwide. A concomitant increase in the prevalence of type 2-diabetes (hyperglycemia), a risk factor for CVD, has further contributed towards escalating CVD-related mortalities. The increase in number of cases of type 2-diabetes underscores the importance of early diagnosis of cardiovascular disease in those with diabetes. In this work, we have evaluated the sensitivity and specificity of dyslipidemia and proinflammatory cytokines to be used as biomarkers for predicting the risk of CVD in those with diabetes. We hypothesize that interplay between dyslipidemia and diabetes-induced low-grade inflammation in those with type 2-diabetes increases the risk of CVD. A total of 215 participants were randomly recruited from the Cameron County Hispanic Cohort (CCHC). Of these, 99% were Mexican Americans living on Texas-Mexico border. Levels of cytokines, adipokines and lipid profile were measured. Cardiovascular disease (CVD) for this study was defined as prior diagnosis of heart attack, angina and stroke, while diabetes was defined by fasting blood glucose (FBG) of > 100 mg/dL and HbA1c of > 6.5, in accordance with American Diabetes Association (ADA) guidelines. Depending on type and distribution of data, various statistical tests were performed. Our results demonstrated higher rates of heart attack (14% vs 11.8%) and stroke (19.8% vs 10%) in those with diabetes as compared to non-diabetes. The odds of having a heart attack were eight times higher in the presence of elevated triglycerides and pro-inflammatory markers (TNFα and IL6) as compared to presence of pro-inflammatory markers only. The odds for heart attack among those with diabetes, increased by 20 fold in presence of high levels of triglycerides, TNFα, and IL6 when coupled with low levels of high-density lipid cholesterol (HDL-C). Lastly, our analysis showed that poorly controlled diabetes, characterized by HbA1c values of > 6.5 increases the odds of stroke by more than three fold. The study quantifies the role of lipid profile and pro-inflammatory markers in combination with standard risk factors towards predicting the risk of CVD in those with type 2-diabetes. The findings from the study can be directly translated for use in early diagnosis of heart disease and guiding interventions leading to a reduction in CVD-associated mortality in those with type 2-diabetes.

Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 5,002,387 cases and 127,258 deaths as of October 31, 2021. The aggressive transmission dynamics of SARS-CoV-2 motivate an investigation of COVID-19 at the national and regional levels in Colombia. We utilize the case incidence and mortality data to estimate the transmission potential and generate short-term forecasts of the COVID-19 pandemic to inform the public health policies using previously validated mathematical models. The analysis is augmented by the examination of geographic heterogeneity of COVID-19 at the departmental level along with the investigation of mobility and social media trends. Overall, the national and regional reproduction numbers show sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Whereas the most recent estimates of reproduction number indicate disease containment, with Rt

Objective: To compare the performance index of private and public sector hospitals of Karachi, Pakistan. Study Design: Cross-sectional study. Place and Duration of Study: In a tertiary care hospitals (one private and one public sector) of Karachi, from Nov 2016 to Nov 2017. Methodology: A sample size of 153 were enrolled by purposive sampling technique. Performance index of both hospitals was compared by asking questions from the hospitals staff. Data were collected by the researcher using closed ended questionnaire. Results: Out of 153, 78 (51%) cases were for private hospitals and 75 (49%) cases were for public hospitals. While evaluating the performance index by hospital work area/unit elements, “Enough staff to handle workload" was significantly higher for private hospitals with the p-value of