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Introduction: Prescription patterns significantly impact healthcare quality and patient outcomes. Evaluating these patterns using World Health Organisation (WHO) indicators helps identify areas for improvement and ensures rational drug use. The present study was conducted to evaluate prescription patterns via WHO indicators, aiming to uncover insights, identify discrepancies and enhance prescription quality within the institute for improved healthcare outcomes. Aim: To evaluate drug prescription patterns using WHO prescription indicators in the prescriptions of outdoor patients at a tertiary care teaching hospital in Chhattisgarh, India. Materials and Methods: A cross-sectional study was conducted in the Department of Pharmacology at Department of Pharmacology, Pt. J.N.M. Medical College, Raipur, Chhattisgarh, India, from July 15, 2023, to October 15, 2023 (a duration of 3 months), involving 1,000 outpatient prescriptions at Dr. Bhimrao Ambedkar Memorial Hospital (BRAM), Raipur, Chhattisgarh. Ethical clearance was obtained from the Institutional Ethics Committee (IEC) (No./MCI/Ethics/2023/45 Raipur, dated 12/07/2023). Data were collected using a digital form and analysed statistically. Parameters evaluated included the average number of medicines per prescription, the percentage of drugs prescribed by generic name, the percentage of prescriptions containing antibiotics, the percentage of prescriptions containing injections, and the percentage of drugs prescribed from the Essential Drug List (EDL). Descriptive statistics were used to summarise the data, and analysis was performed using Microsoft (MS) Excel 2021. Results: The present study included 1,000 prescriptions. A total of 4,320 medicines were prescribed across these prescriptions, with 2,853 (66.04%) prescribed by their generic name. Injections accounted for 483 (11.18%) prescriptions, while antibiotics were included in 663 (15.34%) prescriptions. Additionally, 2,973 (68.81%) medicines were prescribed from the EDL. The average number of medicines prescribed per prescription was 4.3. Conclusion: The study revealed that while certain aspects of prescription practices aligned with WHO indicators, notable discrepancies persisted. The percentage of antibiotics prescribed per prescription was in accordance with WHO guidelines. Strategic measures are needed to enhance prescription practices and align them more closely with WHO guidelines.

Abstract Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

Introduction: We aimed to describe the clinical, biochemical and etiological profile of patients referred with a provisional diagnosis of rickets in tertiary care centres. In addition, we tried to propose a diagnostic algorithm for the evaluation of such patients. Methods: This was a retrospective cross-sectional study conducted in two tertiary care centres of West Bengal. Data of patients were retrieved between 2014 and 2021. Results: Out of 101 children, 22 had conditions simulating rickets. Renal tubular acidosis (RTA) was the most common (53.2%) etiology of rickets, followed by phosphopenic rickets (PR) (22.8%) and calcipenic rickets (CR) (17.7%). The prevalence of true nutritional rickets (NR) was only 8.9%. Children with RTA had a significantly higher prevalence of chronic ill health (69%) and polyuria (95.2%). Weight standard deviation score (SDS) and body mass index (BMI) SDS scores were significantly lower in the RTA group compared to others. Around 90.5% of children with RTA, and none in the other groups, had hypokalemia. Biochemically, hypophosphatemia and elevated alkaline phosphatase (ALP) were present in all patients with PR and CR. Compared to CR, median serum phosphate was significantly lower in the PR group. A significant difference in ALP values was noticed in patients with hypophosphatemia (815 ± 627 IU/L) compared to those without (279 ± 204 IU/L). Plasma parathyroid hormone (PTH) of 100 pg/ml seemed useful to differentiate CR from other forms. Conclusion: NR is uncommon in tertiary care centres. Children with rickets should be approached systematically with the estimation of ALP, phosphorus, creatinine, calcium, PTH and 25-hydroxy vitamin D to reach an etiological diagnosis.

Lactobacillus plantarum has beneficial effects on the reduction of symptoms of poor lactose digestion and hypercholesterolemia, removal of the duration and severity of diarrheal processes, improvement of the intestinal permeability barrier, prevention of some types of cancer by adsorption or inactivation of genotoxic agents, increased resistance to intestinal and extraintestinal infections, attenuation of inflammatory bowel disease, and prevention of allergies (especially food). On the other hand, carao (Cassia grandis) has shown remarkable nutritious content with influential dietary applications. As a result, this investigation aimed to explore the effect of Cassia grandis pulp on viability of Lactobacillus plantarum under gastrointestinal conditions, immunomodulatory capacity, and probiotic potential. Adding carao to the medium under different experimental conditions, including rich and minimal culture media and a gastrointestinal digestion process of skimmed milk, did not substantially affect Lactobacillus plantarum’s growth but prolonged its viability. The administration of Lactobacillus plantarum with carao in mice did not induce a proinflammatory response at a systemic level. Still, it did cause an increase in the production of immunoregulatory cytokines. Also, the viability of TSB broth was improved by adding carao. Carao improved the growth of acid tolerance, bile tolerance, growth in TSB broth, and NaCl resistance. According to the results, carao may enhance the characteristics of L. plantarum when enriching fermented dairy products.

This study involved the evaluation of the effect of vacuum pasteurization on physicochemical characteristics (pH, total soluble solids, titratable acidity, chroma, tone, IO, vitamin C, 5-hydroxymethylfurfural), microbiological properties (Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, total coliforms, total mesophilic aerobes, molds and yeasts) and sensory characteristics of orange and carrot nectar. The thermal treatments were designed based on the thermal lethality of two heat-resistant microorganisms typical of the product (Neosartorya fischeri and Zygosaccaromyces bailii). The evaluation was carried out on raw nectar and pasteurized nectar. The shelf life was estimated to be 30 days (6 °C). The most favorable results were obtained by applying a heat treatment at 88 °C for 32.68 min, managing to retain 85.87% of vitamin C and a microbiological stability of 12 days (6 ± 0.6 °C) with regard to total mesophilic aerobes. Likewise, the tasters established that this treatment resulted in the best flavor, texture and acceptability characteristics.

Carao (Cassia grandis) contains numerous bioactive substances that contribute to gastrointestinal well-being. The present study assessed the potential impacts of carao on the viability and performance of Streptococcus thermophilus and Lactobacillus bulgaricus under various adverse conditions. These conditions included bile, acid, gastric juice, and lysozyme exposure, simulating the digestive process from the mouth to the intestines. The activity of proteases from cultures was monitored to examine their proteolytic capabilities. To achieve this, the cultures were cultivated in a solution containing plant material, and the results were compared against a control sample after an incubation period. Subsequently, the total phenolic content, total carotenoid content, antioxidant activity, sugar profile, and acid profile of the plant materials were analyzed. These analyses were conducted to explore these compounds’ influence on cultures’ survival. Seeds contained the highest total phenols (766.87 ± 11.56 µg GAE/mL), total carotenoid content (7.43 ± 0.31 mg Q/mL), and antioxidant activity (40.76 ± 1.87%). Pulp contained the highest moisture (12.55 ± 0.44%), ash (6.45 ± 0.15%), lipid (0.66 ± 0.07%), protein (16.56 ± 0.21%), sucrose (9.07 ± 0.78 g/100 g), and fructose (3.76 ± 0.06 g/ 100 g). The crust had the highest content of ash (85.14 ± 0.27%) and succinic acid (2.01 ± 0.06 g/100 g). Results indicated that seeds negatively affected cultures’ survival in the bile tolerance test and had positive effects on Lactobacillus bulgaricus in the protease activity test. Otherwise, the other carao tissues could not change the results significantly (p > 0.05) compared to the control in different tests. The carao crust positively affected cultures’ against protease activity, especially in Lactobacillus bulgaricus, and had a negative effect on the growth of S. thermophilus in the lysozyme and gastric acid resistance test.

The demand for low-sodium products is growing worldwide and is compelled by the growing number of related illnesses. However, the quality of these products could be improved, likened to products produced with common salt (NaCL), because the replacement of sodium compromises the flavor of the product. Reducing sodium salts also poses an essential challenge for the meat industry, since sodium chloride (NaCl) fulfills essential technological functions. High sodium consumption has harmful health implications for cardiovascular and hypertension disorders. As a result, this study aimed to analyze the effect of KCl with Glycine and AMP on the physicochemical and sensory characteristics, purchase intent, and consumer perception of roasted chicken. NaCl/KCl replacement levels (0%, 25%, 50%, 75%, and 100%) were established, and consumer perception, liking, emotions, and purchase intent were evaluated. The different KCl levels, except for firmness, did not impact the physicochemical attributes. Even though higher replacement levels of KCl (75–100%) impacted chicken tenderness, it had no notable impact on panelists’ liking scores and purchase intent. Health claims about the sodium content in roasted chicken have also been shown to significantly increase purchase intent, based on enhancing consumer’s emotional responses. Regarding emotional responses, feelings of being unsafe and worried decreased their scores among the highest KCl replacement levels (75% and 100%). Positive emotional responses (feeling satisfied and pleased) were decisive consumer purchase intent predictors.

Nipple fruit (Solanum mammosum), teosinte (Dioon mejiae), Caesar mushroom (Amanita caesarea), and weevil (Rhynchophorus palmarum) powders have shown great nutritional content with meaningful dietary applications. This study aspired to investigate the impact of nipple fruit, teosinte, Caesar mushroom, and weevil powders on the bile tolerance, acid tolerance, lysozyme tolerance, gastric juice resistance, and protease activity of Lactobacillus casei. Nipple fruit, teosinte, Caesar mushroom, and weevil powders were combined at 2% (wt/vol), whereas the control samples did not include the ingredients. The bile and acid tolerances were analyzed in Difco De Man–Rogosa–Sharpe broth incubated under aerobic conditions at 37 °C. The bile tolerance was investigated by adding 0.3% oxgall, whereas the acid tolerance was studied by modifying the pH to 2.0. The lysozyme tolerance was studied in electrolyte solution containing lysozyme (100 mg/L), while the gastric juice tolerance was analyzed at pH levels of 2, 3, 4, 5, and 7. The protease activity was studied spectrophotometrically at 340 nm in skim milk incubated under aerobic conditions at 37 °C. The results show that nipple fruit increased the counts, whereas Caesar mushroom and weevil powders resulted in lower counts for bile tolerance, acid tolerance, lysozyme resistance, and simulated gastric juice tolerance characteristics. Furthermore, the protease activity increased by adding nipple fruit to skim milk. According to the results, nipple fruit may improve the characteristics of L. casei in cultured dairy by-products.

Background: Collaborative comparisons and combinations of epidemic models are used as policy-relevant evidence during epidemic outbreaks. In the process of collecting multiple model projections, such collaborations may gain or lose relevant information. Typically, modellers contribute a probabilistic summary at each time-step. We compared this to directly collecting simulated trajectories. We aimed to explore information on key epidemic quantities; ensemble uncertainty; and performance against data, investigating potential to continuously gain information from a single cross-sectional collection of model results. Methods: We compared projections from the European COVID-19 Scenario Modelling Hub. Five teams modelled incidence in Belgium, the Netherlands, and Spain. We compared July 2022 projections by incidence, peaks, and cumulative totals. We created a probabilistic ensemble drawn from all trajectories, and compared to ensembles from a median across each model’s quantiles, or a linear opinion pool. We measured the predictive accuracy of individual trajectories against observations, using this in a weighted ensemble. We repeated this sequentially against increasing weeks of observed data. We evaluated these ensembles to reflect performance with varying observed data. Results: By collecting modelled trajectories, we showed policy-relevant epidemic characteristics. Trajectories contained a right-skewed distribution well represented by an ensemble of trajectories or a linear opinion pool, but not models’ quantile intervals. Ensembles weighted by performance typically retained the range of plausible incidence over time, and in some cases narrowed this by excluding some epidemic shapes. Conclusions: We observed several information gains from collecting modelled trajectories rather than quantile distributions, including potential for continuously updated information from a single model collection. The value of information gains and losses may vary with each collaborative effort’s aims, depending on the needs of projection users. Understanding the differing information potential of methods to collect model projections can support the accuracy, sustainability, and communication of collaborative infectious disease modelling efforts.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

BackgroundCoronavirus Disease 2019 (COVID-19) continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval).Methods and findingsThe COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths.ConclusionsCOVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year.

Gluten-free products present huge advantages for individuals with gluten intolerance or celiac disease. The most influential strategy to develop a product comparable to wheat-containing gluten products is to promote its nutritional and sensorial attributes. Recently, rice flour and teosinte flour were used to develop gluten-free bread. As a result, this work aimed to compare the physical/technological attributes of bread made with rice flour and teosinte flour with corn fiber fortification and examine consumer acceptance and purchase intent. An extreme vertices mixture design decided that a teosinte flour (43.4%), high protein white rice flour (55%), and high protein brown rice flour (1.6%) ratio of gluten-free flour mixture for bread was best based on the sensory attributes utilized for the desirability function methodology. After optimizing the gluten-free flour mixture, the bread was fortified with corn fiber under 1.7 g and 3.8 g per serving, and it was evaluated to examine its physical/technological attributes, consumer perception, liking, emotions, and purchase intent. Incorporating fiber into gluten-free bread impacted the color and texture, giving lighter and yellower colors with a firmer texture. Likewise, concerning health benefit claims, gluten-free bread with fiber claims only improves the purchase intent and overall liking of bread containing 1.7 g per serving of fiber. The flavor attribute was the main driver for consumers’ purchase decisions. This product could be beneficial for consumers who are seeking fiber in their diet.

The gastrointestinal tract is an environment that hosts various microorganisms, including pathogens. Generally, pathogenic bacteria enter the host body through food and the gastrointestinal tract. These pathogenic bacteria can colonize or infiltrate host cells and tissues, causing various infectious diseases. In recent years, the protective role of probiotic bacteria against gastrointestinal pathogens has been carefully investigated. Probiotics have been found to modulate intestinal microbial flora and play a significant role in the gastrointestinal tract’s function, especially by inhibiting the growth of pathogenic bacteria. However, the mechanism of action of probiotics has yet to be sufficiently proven and recognized. Several important mechanisms support the antagonistic effects of probiotics on various microorganisms, which is achieved, for example, through the production of different antimicrobial compounds, such as bacteriocins, various organic acids, antibiotics, antimicrobial proteins, and exopolysaccharides; mucosal barriers with mucosa and bacteria binding blockers; competition for nutrient uptake; and strengthening of the immune system. Accordingly, this review summarizes the recent studies that have examined the mechanism of action of probiotic bacteria and their beneficial effects in preventing pathogenic bacterial growth and improving gastrointestinal functions. Comprehending their mechanisms of action allows the selection of appropriate probiotic strains for specific applications in gastrointestinal dysfunction.

Abstract Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.

Iron deficiency anemia is a significant health problem in developing countries and this is rising, particularly in children and pregnant women. Several therapeutic properties have been attributed to Cassia grandis (carao), including the treatment against anemia, a laxative effect, and the reduction of bleeding. Yogurt is a vehicle for functional ingredients. As a result, this investigation aims to examine the application of Cassia grandis pulp as an anti-anemic and anti-dyspepsia agent in enriched yogurt. Carao pulp powder was added to milk at 0%, 0.5%, 1%, and 3% to produce yogurt. The bioavailability characteristics of iron deficiency anemia were analyzed in albino rats, which were studied for 4 weeks. Other groups of rats were used to set up the dyspepsia model by being fed a high-fat and high-calorie diet. Intestinal propulsion rate, gastric emptying rate, small intestinal contraction, motilin levels, and intestinal muscle tension were analyzed in rats with dyspepsia. Yogurt with 3% carao pulp powder restored ferritin, hemoglobin, total protein and iron at the end of the 4-week feeding period, with significant competition revealed in calcium and zinc absorbance. Furthermore, yogurt with 3% carao pulp powder improved intestinal propulsion rate, gastric emptying rate, small intestinal contraction, motilin levels, and intestinal muscle tension in dyspepsia rats. Carao can be recommended as an anti-anemia supplement in yogurt fortification.

ABSTRACTThis study used a mixed research design for several reasons. Firstly, the researchers used longitudinal data from open-source remote sensing satellite imagery dating back at least 30 years to study urban expansion into rural farmland. Then, the researchers used cross-sectional data from household surveys, where data collection tools such as questionnaires and structured interviews were utilized. A simple sampling procedure was used to ensure the representativeness of homogeneous target group households. The survey data was analyzed with SPSS software, and the urban-to-farmland extent was investigated with Landsat satellite images and observation intervals every 10 years for the last 30 years. The key finding of this study was that urban expansion is encroaching onto farmland, negatively impacting household livelihoods. It is recommended that urban expansion should be managed and minimized and that cooperation with the communities in the study area is an important issue. The study emphasizes the significance of comprehending the implications of uncontrolled urban development on rural communities in Ethiopia, using a mixed research approach comprising both longitudinal and cross-sectional data. The research demonstrates that expanding cities are having a considerable impact on agricultural livelihoods and require delicate handling to mitigate their unfavorable influence.

We proposed the SIkJalpha model at the beginning of the COVID-19 pandemic (early 2020). Since then, as the pandemic evolved, more complexities were added to capture crucial factors and variables that can assist with projecting desired future scenarios. Throughout the pandemic, multi-model collaborative efforts have been organized to predict short-term outcomes (cases, deaths, and hospitalizations) of COVID-19 and long-term scenario projections. We have been participating in five such efforts. This paper presents the evolution of the SIkJalpha model and its many versions that have been used to submit to these collaborative efforts since the beginning of the pandemic. Specifically, we show that the SIkJalpha model is an approximation of a class of epidemiological models. We demonstrate how the model can be used to incorporate various complexities, including under-reporting, multiple variants, waning of immunity, and contact rates, and to generate probabilistic outputs.

Background: Interruptions in radiation treatment are known to have a deleterious effect on oncologic outcomes,specifically, an increase in tumor recurrence and decrease in cancer cure rate. Objectives: Our primary aim was to determine the factors influencing radiotherapy interruptions and provide solutions to decrease these dropouts. Materials and Methods: This was a retrospective observational study conducted between May 2009 and July 2010 at Mahatma Gandhi Cancer Hospital and Research Institute, a tertiary cancer center in Vishakhapatnam, Andhra Pradesh, India, on patients with histopathologically proven cancer, who were receiving radiation, either as definitive concurrent chemoradiation or in the adjuvant or palliative setting. Before the start and during treatment, patients were counseled by radiation oncologists, radiation coordinators, and radiation therapy technologists. During radiotherapy, an interruption of more than five consecutive days was considered a treatment interruption. Following a treatment interruption, patients were called on the telephone, counseling was done, and the cause of the treatment interruption was recorded and attempts were made to resolve the problem. Results: We enrolled 1200 patients in the study. There were more male (n = 724 [60.4%]) than female (n = 476 [39.6%]) patients. The cohort included 379 patients (31.6%) with carcinoma of the head-and-neck and 301 patients (25.1%) with gynecological malignancies. There were 100 (8.3%) treatment interruptions recorded during the study period. The common causes of radiation interruption were radiation-induced toxicity (n = 20 [20%]), patient death (n = 15 [15%]), financial (n = 15 [15%]), and social (n = 12 [12%]) issues. After counseling over the telephone, treatment could be restarted in 25 (25%) of the 100 patients who had interrupted and stopped radiotherapy. Conclusion: Treatment interruption is relatively common in our patients receiving radiotherapy. To prevent such dropouts and increase compliance to treatment, adequate and frequent counseling before and during radiation treatment is needed.

Shock is a state of acute circulatory failure leading to decreased organ perfusion, inadequate delivery of oxygenated blood to tissues, and resultant end-organ dysfunction. A 45-year-old male patient a known case of Diabetes Mellitus (DM) presented to the Emergency Room (ER) with a complaint of fever for four days and shortness of breath for one day. The patient had a wound discharging pus over the dorsum of the right foot for two weeks following trauma. On examination, the patient’s vitals were: pulse rate-88 Beats Per Minute (bpm), respiratory rate-26 breaths per minute, SpO2-78% room air, Blood Pressure (BP)-82/40 mmHg mean arterial pressure- 54 mmHg. As a protocol of shock evaluation, Point Of Care Ultrasonography (POCUS) showed a distended Inferior Vena Cava (IVC), dilated right atrium and ventricle, and good left ventricular systolic function. Given the presence of right leg swelling, ultrasound was done, which showed a thrombus in the popliteal vein. Noradrenaline infusion was started to maintain a mean arterial blood pressure of 70 mmHg. A diagnosis of obstructive shock due to pulmonary embolism was strongly suspected, and thrombolysis with injection streptokinase was done. After two hours of thrombolysis, Two-Dimensional (2D) Echocardiography (ECHO) revealed normal right atrium and ventricle size and IVC collapsibility index of 70%, but the patient’s blood pressure didn’t improve significantly. So, adequate intravenous fluid was given as per the septic shock protocol. But, the noradrenalin requirement didn't improve. The patient was put on broad-spectrum antibiotics. Blood culture showed growth of Pseudomonas aeruginosa. So, a diagnosis of co-existing septic shock with obstructive shock was made. The patient improved and discharged in stable condition. The present case report highlights the co-existence of septic shock and obstructive shock and the usefulness of POCUS in differentiating and managing various shocks.

Bracher et al. compare 15 forecasting models of COVID-19 cases and deaths in Germany and Poland between January and mid-April 2021. Many, though not all, models outperform a simple baseline model up to four weeks ahead, with ensemble methods showing very good relative performance.

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

Introduction Unruptured intracranial aneurysms (UIA) are common in the adult population, but only a relatively small proportion will rupture. It is therefore essential to have accurate estimates of rupture risk to target treatment towards those who stand to benefit and avoid exposing patients to the risks of unnecessary treatment. The best available UIA natural history data are the PHASES study. However, this has never been validated and given the known heterogeneity in the populations, methods and biases of the constituent studies, there is a need to do so. There are also many potential predictors not considered in PHASES that require evaluation, and the estimated rupture risk is largely based on short-term follow-up (mostly 1 year). The aims of this study are to: (1) test the accuracy of PHASES in a UK population, (2) evaluate additional predictors of rupture and (3) assess long-term UIA rupture rates.Methods and analysis The Risk of Aneurysm Rupture study is a longitudinal multicentre study that will identify patients with known UIA seen in neurosurgery units. Patients will have baseline demographics and aneurysm characteristics collected by their neurosurgery unit and then a single aggregated national cohort will be linked to databases of hospital admissions and deaths to identify all patients who may have subsequently suffered a subarachnoid haemorrhage. All matched admissions and deaths will be checked against medical records to confirm the diagnosis of aneurysmal subarachnoid haemorrhage. The target sample size is 20 000 patients. The primary outcome will be aneurysm rupture resulting in hospital admission or death. Cox regression models will be built to test each of the study’s aims.Ethics and dissemination Ethical approval has been given by South Central Hampshire A Research Ethics Committee (21SC0064) and Confidentiality Advisory Group support (21CAG0033) provided under Section 251 of the NHS Act 2006. The results will be disseminated in peer-reviewed journals.Trial registration number ISRCTN17658526.

The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB) in humans, is a primary reason for treatment failure. Currently, only limited options are available for the management of multi-drug resistant TB, warranting the design of novel anti-TB drugs by exploiting newer targets. One of the caseinolytic protease (Clp) machinery components, an unfoldase known as ClpC1, has emerged as a distinct anti-TB drug target owing to its essential role in the pathogen's survival. The naturally occurring cyclic peptides targeting the Mtb ClpC1, exhibit potent antimycobacterial activity. However, the large, complex, and poor synthetic tractability of these peptides limit their clinical application. Identification of small molecule inhibitors of Mtb ClpC1 will be useful for future drug development. Here, we report the discovery of a bisquinoline chemotype from the screening of a small molecule chemical library against Mtb ClpC1. The hit molecule binds with ClpC1 and exhibits dose-dependent inhibition of its enzymatic activity by direct binding. The in vitro growth of Mtb is inhibited by the hit molecule at a minimum inhibitory concentration of 12.5 µM. Investigation of the structure–activity relationship by chemical synthesis underlines the requirement of the two quinoline rings, 9/10 carbon linker, and the importance of basic ring nitrogen for its inhibitory activity. To our knowledge, this is the first report on the systematic analysis of small molecule inhibitors of Mtb ClpC1.

Summary: Background: The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5–11 years on COVID-19 burden and resilience against variant strains. Methods: Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5–11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses. Findings: Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5–11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880–0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834–0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797–1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed. Interpretation: Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5–11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants. Funding: Various (see acknowledgments).

Introduction Glioblastoma is the most common malignant primary brain tumour with a median overall survival of 12–15 months (range 6–17 months), even with maximal treatment involving debulking neurosurgery and adjuvant concomitant chemoradiotherapy. The use of postoperative imaging to detect progression is of high importance to clinicians and patients, but currently, the optimal follow-up schedule is yet to be defined. It is also unclear how adhering to National Institute for Health and Care Excellence (NICE) guidelines—which are based on general consensus rather than evidence—affects patient outcomes such as progression-free and overall survival. The primary aim of this study is to assess MRI monitoring practice after surgery for glioblastoma, and to evaluate its association with patient outcomes.Methods and analysis ImagiNg Timing aftER surgery for glioblastoma: an eVALuation of practice in Great Britain and Ireland is a retrospective multicentre study that will include 450 patients with an operated glioblastoma, treated with any adjuvant therapy regimen in the UK and Ireland. Adult patients ≥18 years diagnosed with glioblastoma and undergoing surgery between 1 August 2018 and 1 February 2019 will be included. Clinical and radiological scanning data will be collected until the date of death or date of last known follow-up. Anonymised data will be uploaded to an online Castor database. Adherence to NICE guidelines and the effect of being concordant with NICE guidelines will be identified using descriptive statistics and Kaplan-Meier survival analysis.Ethics and dissemination Each participating centre is required to gain local institutional approval for data collection and sharing. Formal ethical approval is not required since this is a service evaluation. Results of the study will be reported through peer-reviewed presentations and articles, and will be disseminated to participating centres, patients and the public.

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model.

Introduction: Head and Neck cancer is most common cancer in developing countries like India. Oral Squamous Cell Carcinoma (OSCC) is the most common site of head and neck malignancy. Various histopathological factors prognosticates the therapeutic outcome. Clinicopathological characteristics of OSCC in Asian countries somehow differ from Western countries. Aim: To report the different clinicopathological characteristics of OSCC due to paucity of the literature even though it is one of the most common malignancy in India. Materials and Methods: In this retrospective observational study, the medical records of 1753 patients of OSCC who satisfied the eligibility criteria and were treated at a tertiary cancer centre at Cuttack, Odisha, India, from January 2009 to December 2019. Clinicopathological profile of the included subjects were noted. The data was analysed in the month of March 2021 using descriptive statistics such as mean, median, maximum, minimum value and percentage using International Business Machine (IBM) Statistical Package for the Social Sciences (SPSS) version 23.0. Results: Total of 1753 patients were analysed with the mean age of 50.55±12.56 years, however, majority 492 (28.1%) were in the age of 40-49 years. Male predominance was observed in 1379 (78.7%) patients. Buccal mucosa was the most common primary site in 731 (41.7%) patients, (41.7%) followed by the tongue in 359 (20.5%) patients. Left side lesion was seen in 1008 (57.5%) patients while 734 (41.9%) patients had lesion at right side. Morphologically, ulceroinfiltrative lesion was the most common presentation constituting in 897 (51.2%) patients. Maximum tumour size was 2.91±1.25 cm. Maximum number of patients i.e., 1529 (87.2%) had grade I disease. Mean Depth of Invasion (DOI) was 8.67±4.50 mm. Lymphovascular Space Invasion (LVI) was positive in 123 (7%) patients and Perineural Invasion (PNI) was observed in 565 (32.2%) patients. Resected margin was positive in 203 (11.6%) patients. Cervical lymph node involvement was found in 691 (39.4%) patients and 28 (1.6%) had extracapsular extension. In the present study, most of the patients presented in advanced stage of the disease i.e., stage III 380 (21.7%) and stage IV 506 (28.9%). Conclusion: The present study highlights that majority of OSCC presents in younger age groups, as left side buccal mucosal lesion with advanced stages of disease. This scenario is due to poor lifestyle pattern which can be prevented by avoidance of tobacco consumption, active screening, public awareness and early diagnosis.

Road hazards such as jaywalking pedestrians, stray animals, unmarked speed bumps, vehicles, and road damage can pose a significant threat in poor visibility conditions. Vehicles are fitted with safety technologies like advanced driver assistance systems (ADAS) and AW (automatic warning) systems to tackle these issues. However, these safety systems are complex and expensive, and these proprietary systems are exclusive to high-end models. The majority of the existing vehicles on the road lacks these systems. The YOLO model (You Only Look Once Architecture) was chosen owing to its lightweight architecture and low inference latency. Since YOLO is an open-source architecture, it can enhance interoperability and feasibility of aftermarket/retrofit ADAS devices, which helps in reducing road fatalities. An ADAS which implements a YOLO-based object detection algorithm to detect and mark obstacles (pedestrians, vehicles, animals, speed breakers, and road damage) using a visual bounding box was proposed. The performance of YOLOv3 and YOLOv5 has been evaluated on the Traffic in the Tamil Nadu Roads dataset. The YOLOv3 model has performed exceptionally well with an F1-Score of 76.3% and an mAP (mean average precision) of 0.755, whereas the YOLOv5 has achieved an F1-Score of 73.7% and an mAP of 0.7263.

Nowadays, in a world full of uncertainties and the threat of digital and cyber-attacks, blockchain technology is one of the major critical developments playing a vital role in the creative professional world. Along with energy, finance, governance, etc., the healthcare sector is one of the most prominent areas where blockchain technology is being used. We all are aware that data constitute our wealth and our currency; vulnerability and security become even more significant and a vital point of concern for healthcare. Recent cyberattacks have raised the questions of planning, requirement, and implementation to develop more cyber-secure models. This paper is based on a blockchain that classifies network participants into clusters and preserves a single copy of the blockchain for every cluster. The paper introduces a novel blockchain mechanism for secure healthcare sector data management, which reduces the communicational and computational overhead costs compared to the existing bitcoin network and the lightweight blockchain architecture. The paper also discusses how the proposed design can be utilized to address the recognized threats. The experimental results show that, as the number of nodes rises, the suggested architecture speeds up ledger updates by 63% and reduces network traffic by 10 times.