Quantification of carbon dioxide released from effervescent granules as a predictor of formulation quality using modified Chittick apparatus

Purpose: To develop a method for the measurement of carbon dioxide (CO2) released from effervescent formulations. Methods: Effervescent granules were prepared using sodium bicarbonate and citric acid by fusion and solvent-assisted granulation methods. The amount of CO2 released was determined from the maximum pressure of gas release, time profile of pressure gradient using modified Chittick apparatus and gravimetric changes following effervescence. Results: The amount of CO2 released from effervescent granules prepared by fusion method was 8.125, 8.763 and 7.98 mM/g measured by ideal gas equation, pressure gradient and gravimetric method, respectively. The formulation prepared by solvent-assisted granulation showed 5.525, 5.475 5.36 mM/g of carbon dioxide measured by the above three methods, respectively. The effervescent granules prepared by fusion method showed approximately 2 % loss in effervescence. However, approximately 39 % loss in effervescence was observed for the formulation prepared by solventassisted granulation. The commercial products showed a loss in effervescence in the range of 5 - 15%. Conclusion: Modified Chittick’s apparatus is a useful analytical tool for monitoring of the CO2 from effervescent granules as a function of method of preparation

Različitost interferona-α-A (IFN-α-A) u jaka (Bos grunniens) iz Pakistana

Among the various species of livestock, the domestic yak (Bos grunniens) belongs to the class Bovidae and is specially adapted for survival at high altitudes under extreme climatic conditions. Yak is a very useful species due to the multiple products it provides, such as meat, hide, milk and other dairy products. Like other livestock species, domestic yak is also in danger of infection by microbial infections. However, multiple immunity genes encode special protein products to fight infection. One of these immunity genes is interferon-α-A (IFN-α-A), which encodes proteins that belongs to cytokines and fights viral infections. The current study analysed the genetic variation and phylogenetic analysis of the IFN-α-A gene in domestic yak, with comparisons to other mammalian species to investigate immune diversity level, with the aim of designing molecular selection strategies for better disease resistant animals.Među različitim vrstama stoke, jedna je vrsta i jak (Bos grunniens). Ova životinja pripada obitelji Bovidae. Ova je vrsta prilagođena je preživljavanju na velikim visinama i u ekstremnim klimatskim uvjetima. Jak je vrlo korisna životinja zbog brojnih proizvoda koje od njega dobivamo, poput mesa, kože, mlijeka i mliječnih proizvoda. Kao i druge vrste stoke i jak je u opasnosti od infekcije brojnim mikrobnim infekcijama. Međutim, mnogo je imunogena koji kodiraju posebne proteinske proizvode za borbu protiv infekcija. Jedan od tih imunogena je interferon-α-A (IFN-α-A) koji kodira proteine koji pripadaju citokinima i bori se protiv virusnih infekcija. Ova studija osmišljena je za analizu genetske varijacije i filogenetsku analizu IFN-α –A gena u jaka (Bos grunniens) te njegovu usporedbu s drugim vrstama sisavaca u svrhu istraživanja razine različitosti imunosti za osmišljenja strategija molekularnog odabira za veću otpornost životinja na bolesti

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Integrating Multiple Datasets in Google Earth Engine for Advanced Hydrological Modeling Using the Soil Conservation Service Curve Number Method

This research explores the feasibility of using cloud computing and open data sources for hydrological modeling, specifically leveraging Google Earth Engine (GEE) and the Soil Conservation Service Curve Number (SCS CN) method to estimate runoff. The SCS CN approach is commonly applied in simulating rainfall-runoff processes and is effective for estimating water inflow into rivers, lakes, and streams. Google Earth Engine provides a range of functionalities, including algorithms for rapid data manipulation and visualization, and access to extensive global remote sensing and geographic information system (GIS) datasets. The study introduces an algorithm developed in GEE to analyze precipitation data and generate antecedent moisture condition (AMC) maps. This algorithm integrates MODIS land use/land cover (LULC) data with USDA soil texture data to classify hydrological soil groups. Runoff estimation utilizes three datasets: CHIRPS, GPM, and TRMM. A thorough analysis of the rainfall-runoff relationship in the Mangla watershed from 2005 to 2015 is conducted. The study quantifies runoff estimates from each dataset and performs comparative analysis to validate the accuracy and reliability of the hydrological modeling. Over the ten-year period (2005-2015), significant fluctuations in average rainfall and runoff levels are observed, with notable seasonal patterns. The highest average precipitation of 1412.194 mm occurred in 2015, resulting in an average runoff of 215.021 mm. Conversely, 2009 recorded the lowest average precipitation of 672.808 mm and an average runoff of 78.476 mm. The accuracy of the modeled runoff observations is validated using meteorological data from the Pakistan Meteorological Department (PMD), Water and Power Development Authority (WAPDA), and Climate Forecast System Reanalysis (CFSR). In 2008, 2009, and 2010, CHIRPS consistently demonstrated better accuracy compared to GPM and TRMM, with accuracies of 90%, 79%, and 86% respectively. Additionally, a sensitivity analysis of the SCS CN model parameters reveals the effects of initial abstraction and Curve Number values on runoff estimation. In conclusion, this research enhances the understanding of hydrological processes in monsoon-affected regions and offers valuable recommendations for implementing sustainable water resource management practices

Integrating Multiple Datasets in Google Earth Engine for Advanced Hydrological Modeling Using the Soil Conservation Service Curve Number Method

This research explores the feasibility of using cloud computing and open data sources for hydrological modeling, specifically leveraging Google Earth Engine (GEE) and the Soil Conservation Service Curve Number (SCS CN) method to estimate runoff. The SCS CN approach is commonly applied in simulating rainfall-runoff processes and is effective for estimating water inflow into rivers, lakes, and streams. Google Earth Engine provides a range of functionalities, including algorithms for rapid data manipulation and visualization, and access to extensive global remote sensing and geographic information system (GIS) datasets. The study introduces an algorithm developed in GEE to analyze precipitation data and generate antecedent moisture condition (AMC) maps. This algorithm integrates MODIS land use/land cover (LULC) data with USDA soil texture data to classify hydrological soil groups. Runoff estimation utilizes three datasets: CHIRPS, GPM, and TRMM. A thorough analysis of the rainfall-runoff relationship in the Mangla watershed from 2005 to 2015 is conducted. The study quantifies runoff estimates from each dataset and performs comparative analysis to validate the accuracy and reliability of the hydrological modeling. Over the ten-year period (2005-2015), significant fluctuations in average rainfall and runoff levels are observed, with notable seasonal patterns. The highest average precipitation of 1412.194 mm occurred in 2015, resulting in an average runoff of 215.021 mm. Conversely, 2009 recorded the lowest average precipitation of 672.808 mm and an average runoff of 78.476 mm. The accuracy of the modeled runoff observations is validated using meteorological data from the Pakistan Meteorological Department (PMD), Water and Power Development Authority (WAPDA), and Climate Forecast System Reanalysis (CFSR). In 2008, 2009, and 2010, CHIRPS consistently demonstrated better accuracy compared to GPM and TRMM, with accuracies of 90%, 79%, and 86% respectively. Additionally, a sensitivity analysis of the SCS CN model parameters reveals the effects of initial abstraction and Curve Number values on runoff estimation. In conclusion, this research enhances the understanding of hydrological processes in monsoon-affected regions and offers valuable recommendations for implementing sustainable water resource management practices

Formulation, Optimization, in vitro and in-vivo evaluation of levofloxacin hemihydrate Floating Tablets

The objective of the present investigation was to design, optimize and characterize the gastro retentive floating levofloxacin tablets and perform&nbsp;in-vivo&nbsp;evaluation using radiographic imaging. The floating tablets were prepared by using polymers i.e hydroxy propyl methyl cellulose (HPMC-K4M) and carbopol-940 individually and in combination by nonaquous granulation method. All the Formulations were evaluated for swelling index (S.I), floating behavior and in-vitro drug release kinetics. The compatibility study of levofloxacin with other polymers was investigated by FTIR, DSC, TGA and XRD. Results from FTIR and DSC revealed no chemical interaction amongst the formulation components. The optimized formulation (F11) showed floating lag time (FLT), total floating time (TFT) swelling index (S.I) of 60 sec, &gt;16h and approximately 75 %, respectively. Moreover, F11 showed zero order levofloxacin release in simulated gastric fluid over the period of 6 h. X-ray studies showed that total buoyancy time was able to delay the gastric emptying of levofloxacin floating tablets in rabbits for more than 4 hours. In conclusion the optimized formulation (F11) can be used for the sustained delivery of levofloxacin for the treatment of peptic ulcer

Fabrication and Characterization of Celecoxib-Loaded Chitosan/Guar Gum-Based Hydrogel Beads

The aim of this study was to fabricate celecoxib-loaded chitosan/guar gum (CS/GG) single (SC) and dual (DC) crosslinked hydrogel beads using the ionotropic gelation approach. The prepared formulations were evaluated for entrapment efficiency (EE%), loading efficiency (LE%), particle size and swelling studies. The performance efficiency was assessed by in vitro drug release, ex-vivo mucoadhesion, permeability, ex-in vivo swelling and in vivo anti-inflammatory studies. The EE% was found to be ~55% and ~44% for SC5 and DC5 beads, respectively. The LE% was ~11% and ~7% for SC5 and DC5 beads, respectively. The beads showed a matrix-like network with thick fibers. The particle size of beads ranged from ~2.74 to 1.91 mm. About 74% and 24% celecoxib was released from SC and DC hydrogel beads, respectively, within 24 h. The SC formulation showed higher %swelling and permeability than the DC counterpart, while the %mucoadhesion was relatively higher for DC beads. During the in vivo study, a significant decrease in the inflammation of the rat paw and inflammatory markers including C-reactive proteins (CRP) and interleukin-6 (IL-6) was observed following treatment with the prepared hydrogel beads; however, the SC formulation showed better therapeutic efficiency. In conclusion, celecoxib-loaded crosslinked CS/GG hydrogel beads can provide sustained drug release and act as potential candidates for managing inflammatory conditions