Acute Calcific Tendinitis of the Longus Colli: A Case Report and Review of the Literature.

Acute calcific tendinitis of the longus colli (ACTLC) is a rare, self-resolving condition caused by calcium hydroxyapatite crystal deposition in the longus colli muscle tendons. We present a case of a 46-year-old female with a history of hypertension who presented with right-sided neck pain, worsening abdominal pain, nausea, bloody emesis, and generalized body aches in the context of recent alcohol use. Physical examination revealed neck pain with limited range of motion, induration, and tenderness in the right and posterior neck areas. Laboratory findings showed elevated white cell count, inflammatory markers, and metabolic acidosis with an elevated anion gap and lactic acid level. Computed tomography (CT) of the neck with contrast demonstrated amorphous calcification in the longus colli tendons and retropharyngeal effusion, consistent with the diagnosis of ACTLC. The patient was treated with nonsteroidal anti-inflammatory drugs (NSAIDs) and supportive care, leading to symptom resolution. This case highlights the importance of considering ACTLC in the differential diagnosis of acute neck pain and the role of CT imaging in establishing the diagnosis. Prompt recognition and appropriate management of ACTLC can prevent unnecessary interventions and lead to improved patient outcomes.

Comparative analysis of HEC-HMS and SWAT hydrological models for simulating the streamflow in sub-humid tropical region in India.

Assessment of water availability in sub-humid regions is important due to distinct climatic and environmental conditions. In this study, Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) models have been assessed in simulating streamflows in the sub-humid tropical Kabini basin in Kerala, India, spanning 1260 km2. Calibration and validation utilized daily weather data from 1997 to 2015 from the Muthankera gauging station. The study investigated the impact of routing methods on runoff simulation in the ArcSWAT, exploring Muskingum and Variable Storage methods. Evaluation metrics encompassed Nash-Sutcliffe Efïciency (NSE), Coefficient of Determination (R2), Percent bias (PBIAS), RMSE-observations standard deviation ratio (RSR), and Peak Percent Threshold Statistics (PPTS) approach for high-flow values. The result indicates that HEC-HMS outperforms SWAT concerning R2 and NSE values during daily calibration and validation. Monthly simulations showed HEC-HMS closely aligning with SWAT (Variable storage), outperforming SWAT (Muskingum). The PPTS approach proved effective in simulating high-flow values. Both models exhibited proficiency in streamflow analysis within the study area, promising predictive potential for future hydrological studies in sub-humid regions.

Prediction of volatility and seasonality vegetation by using the GARCH and Holt-Winters models.

Seasonality and volatility of vegetation in the ecosystem are associated with climatic sensitivity, which can have severe consequences for the environment as well as on the social and economic well-being of the nation. Monitoring and forecasting vegetation growth patterns in ecosystems significantly rely on remotely sensed vegetation indices, such as Normalized Difference Vegetation Index (NDVI). A novel integration of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and the Holt-Winters (H-W) models was used to simulate the seasonality and volatility of the three different agro-climatic zones in Jharkhand, India: the central north-eastern, eastern, and south-eastern agro-climatic zones. MODIS Terra Vegetation Indices NDVI data MOD13Q1, from 2001 to 2021, was used to create NDVI time series volatility and seasonality modeled by the GARCH and the H-W models, respectively. GARCH-based Exponential GARCH (EGARCH) [1,1] and Standard GARCH (SGARCH) [1,1] models were used to check the volatility of vegetation growth in three different agro-climatic zones of Jharkhand. The SGARCH [1,1] and EGARCH [1,1] models for the western agro-climatic zone experienced the best indicator as it has maximum likelihood and minimal Schwarz-Bayesian criterion and Akaike information criterion. The seasonality results showed that the additive H-W model showed better results in the eastern agro-climatic zone with the optimized values of MAE (16.49), MAPE (0.49), NSE (0.86), RMSE (0.49), and R2 (0.82) followed by the south-eastern and central north-eastern agro-climatic zones. By utilizing the H-W and GARCH models, the finding demonstrates that vegetation orientation and monitoring seasonality can be predicted using NDVI.

Serum Krebs von den Lungen-6 for Predicting the Severity of COVID-19: A Systematic Review, Meta-Analysis, and Trial Sequence Analysis.

OBJECTIVE: This systematic review and meta-analysis aimed to find the association between serum Krebs von den Lungen-6 (KL-6) and the severity of Coronavirus disease 2019 (COVID-19) infection. DATA SOURCES: Databases of Embase, PubMed, Web of Science, Science Direct, and Google Scholar were searched for studies reporting KL-6 levels in COVID-19 patients, published between January 2020 and September 30 2022. DATA SYNTHESIS: For comparison between the groups, standard mean difference (SMD) and 95% confidence intervals (CI) were computed as the effect sizes. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were measured to assess the diagnostic power of KL-6. In addition, the summary receiver operating characteristics curve (sROC) was constructed to summarize the true positive (TP), and false positive (FP) rates. To validate the findings of meta-analysis, Trial Sequential Analysis (TSA) was conducted. RESULTS: Altogether 497 severe COVID-19 patients and 934 non-severe (mild to moderate) COVID-19 patients were included. Pooling of 12 studies indicated that the serum KL-6 level had significant association with severity of COVID-19 infection: standard mean difference = 1.18 (95% CI: 0.93-1.43), p = 0.01; I2: 58.56%]. Pooled diagnostic parameters calculated from eight studies were: sensitivity 0.53 (95% CI: 0.47-0.59); specificity 0.90 (95% CI: 0.88-0.93); positive likelihood ratio 4.80 (95% CI: 3.53-6.53); negative likelihood ratio 0.46 (95% CI: 0.32-0.68); and area under curve: 0.8841. Additionally, TSA verified the adequacy of sample size and robustness of the meta-analysis. CONCLUSION: Serum KL-6 level has a moderate degree of correlation with the severity of COVID-19 infection but has low sensitivity. So, it is not recommended as a screening test for severe COVID-19 infection.

Dynamical Analysis of COVID-19 Model Incorporating Environmental Factors.

The continuing coronavirus pandemic has come up with considerable questions in front of the world. Presently, India is among concerned countries in Asia. Even though the recovery rate is more than the death rate, it is affecting human lives and experiencing losses to the market. Several methods were employed to study the spread of novel coronavirus. Mathematical modeling is one of the prominent techniques to evaluate the dynamics of novel coronavirus. In this work, we extend the mathematical model SEIAQRDT by incorporating environmental transmission to analyze the transmission of coronavirus in India. The notable aspect of the model incorporates asymptomatic population, quarantine individuals, and environmental transmission factors. These factors have enormous significance in the ongoing COVID-19 outbreak. The basic reproduction number R 0 is calculated theoretically. Bifurcation analysis of R 0 is also done analytically. The existence and stability analysis of disease-free equilibrium (DFE) and endemic equilibrium (EE) points are established. The impact of environmental factors in spreading COVID-19 pandemic is deliberated. The case study for India and Italy is presented and compared with real data, and the results are in accordance with the real situation.

Latent Growth Curve Modeling for COVID-19 Cases in Presence of Time-Variant Covariate.

For the past two years, the entire world has been fighting against the COVID-19 pandemic. The rapid increase in COVID-19 cases can be attributed to several factors. Recent studies have revealed that changes in environmental temperature are associated with the growth of cases. In this study, we modeled the monthly growth rate of COVID-19 cases per million infected in 126 countries using various growth curves under structural equation modeling. Moreover, the environmental temperature has been introduced as a time-varying covariate to enhance the performance of the models. The parameters of growth curve models have been estimated, and accordingly, the results are discussed for the affected countries from August 2020 to July 2021.

Depression among Online Respondent Oral Healthcare Workers during COVID-19 Pandemic: A Descriptive Cross-sectional Study.

Introduction: COVID-19 outbreak brought unprecedented pressure on dental and oral health care workers leading to increased depression. This study aimed to find the prevalence of depression among online respondent oral healthcare workers during the COVID-19 pandemic. Methods: A descriptive cross-sectional study was conducted from 24 June 2020 to 13 July 2020 among oral health care workers in a tertiary care centre. Ethical approval was taken from the Ethical Review Board (Reference number: 2710). Convenience sampling method was used. The data were collected using a questionnaire through Google Forms. Point estimate and 95% confidence interval were calculated. Results: Among 133 oral health care workers, the prevalence of depression was found to be 29 (21.80%) (14.78-28.82, 95% Confidence Interval). Conclusions: The prevalence of depression among oral health care workers was lower than similar studies done in similar settings. Keywords: COVID-19; depression; oral health.

SEIAQRDT model for the spread of novel coronavirus (COVID-19): A case study in India.

COVID-19 is a global pandemic declared by WHO. This pandemic requires the execution of planned control strategies, incorporating quarantine, self-isolation, and tracing of asymptomatic cases. Mathematical modeling is one of the prominent techniques for predicting and controlling the spread of COVID-19. The predictions of earlier proposed epidemiological models (e.g. SIR, SEIR, SIRD, SEIRD, etc.) are not much accurate due to lack of consideration for transmission of the epidemic during the latent period. Moreover, it is important to classify infected individuals to control this pandemic. Therefore, a new mathematical model is proposed to incorporate infected individuals based on whether they have symptoms or not. This model forecasts the number of cases more accurately, which may help in better planning of control strategies. The model consists of eight compartments: susceptible (S), exposed (E), infected (I), asymptomatic (A), quarantined (Q), recovered (R), deaths (D), and insusceptible (T), accumulatively named as SEIAQRDT. This model is employed to predict the pandemic results for India and its majorly affected states. The estimated number of cases using the SEIAQRDT model is compared with SIRD, SEIR, and LSTM models. The relative error square analysis is used to verify the accuracy of the proposed model. The simulation is done on real datasets and results show the effectiveness of the proposed approach. These results may help the government and individuals to make the planning in this pandemic situation.

Numerical simulation and stability analysis for the fractional-order dynamics of COVID-19.

The main purpose of this work is to study the dynamics of a fractional-order Covid-19 model. An efficient computational method, which is based on the discretization of the domain and memory principle, is proposed to solve this fractional-order corona model numerically and the stability of the proposed method is also discussed. Efficiency of the proposed method is shown by listing the CPU time. It is shown that this method will work also for long-time behaviour. Numerical results and illustrative graphical simulation are given. The proposed discretization technique involves low computational cost.

Analysis for fractional dynamics of Ebola virus model.

Ebola virus is very challenging problem of the world. The main purpose of this work is to study fractional Ebola virus model. An efficient computational method based on iterative scheme is proposed to solve fractional Ebola model numerically. Stability of proposed method is also discussed. Efficiency of proposed method is shown by listing CPU time. Proposed computational method will work for long time domain. Numerical results are presented graphically. The main reason for using this technique is low computational cost and high accuracy. It is also shown how the approximate solution varies for fractional and integer order Ebola virus model.

The use of the Ganga Hospital Score to predict the treatment and outcome of open fractures of the tibia.

AIMS: Open fractures of the tibia are a heterogeneous group of injuries that can present a number of challenges to the treating surgeon. Consequently, few surgeons can reliably advise patients and relatives about the expected outcomes. The aim of this study was to determine whether these outcomes are predictable by using the Ganga Hospital Score (GHS). This has been shown to be a useful method of scoring open injuries to inform wound management and decide between limb salvage and amputation. METHODS: We collected data on 182 consecutive patients with a type II, IIIA, or IIIB open fracture of the tibia who presented to our hospital between July and December 2016. For the purposes of the study, the patients were jointly treated by experienced consultant orthopaedic and plastic surgeons who determined the type of treatment. Separately, the study team (SP, HS, AD, JD) independently calculated the GHS and prospectively collected data on six outcomes for each patient. These included time to bony union, number of admissions, length of hospital stay, total length of treatment, final functional score, and number of operations. Spearman's correlation was used to compare GHS with each outcome. Forward stepwise linear regression was used to generate predictive models based on components of the GHS. Five-fold cross-validation was used to prevent models from over-fitting. RESULTS: The mean follow-up was 11.4 months (3 to 31). The mean time to union was 9.7 months (3 to 21), the mean number of operations was 2.8 (1 to 11), the mean time in hospital was 17.7 days (5 to 84), the mean length of treatment was 92.7 days (5 to 730), the mean number of admissions was 1.7 (1 to 6), and the mean functional score (Lower Extremity Functional Score (LEFS)) was 60.13 (33 to 80). There was a significant correlation between the GHS and each of the outcome measures. A predictive model was generated from which the GHS could be used to predict the various outcome measures. CONCLUSION: The GHS can be used to predict the outcome of patients who present with an open fracture of the tibia. Our model generates a numerical value for each outcome measure that can be used in clinical practice to inform the treating team and to advise patients. Cite this article: Bone Joint J 2020;102-B(1):26-32.

A low-cost and scalable process for harvesting microalgae using commercial-grade flocculant.

A low-cost and scalable harvesting process was demonstrated for Chlorella sp. FC2 IITG, which offered an improved process economy for the production of a microalgal biomass feedstock via (i) the utilization of a cheaper commercial grade chemical flocculant; (ii) the recycling of post-harvested nutrient-rich spent water for the successive growth of the FC2 cells and (iii) the modulation of the flocculant dose, resulting in the non-requirement of a pH adjustment of the spent water and separate inoculum development step. Ferrous sulphate and ferric chloride were screened from a pool of four commercial grade flocculants, resulting in high harvesting efficiencies of 99.83% and 99.93% at the lower flocculant doses (g of flocculant g of dry biomass-1) of 2.5 and 3, respectively. The effect of the recycled nutrient-rich spent water and treated non-flocculated microalgal cells after harvesting was evaluated for the growth performance of the FC2 cells in six successive batches. It was found that ferrous sulphate was superior over ferric chloride in terms of the recyclability of the spent water for more number of batches, offering similar growth kinetics and nutrient recovery efficiency as compared with that of the control sample. The scale-up feasibility of the harvesting process was evaluated with a 5 L photobioreactor under indoor conditions and a 350 L open raceway pond under outdoor conditions with a modulated flocculant dose of 1.5 g ferrous sulphate. g dry biomass-1. The harvesting cost of 1 kg biomass using commercial grade ferrous sulphate was estimated to be in the range of 0.17-0.3 USD and was significantly lower as compared to that of analytical grade ferrous sulphate.

Association of Vitamin D and secondary hyperparathyroidism with anemia in diabetic kidney disease.

INTRODUCTION: Anemia is common in Chronic Kidney Disease (CKD) and diabetes is a major leading risk factor for it. In Diabetic Kidney Disease (DKD), it worsens more, which further increases cardiovascular morbidity and mortality. Despite of adequate iron stores anemia persist, which may be due to impaired iron release from body stores that is unable to meet the demand for erythropoiesis (also called reticuloendothelial cell iron blockade). High parathyroid hormone (PTH) along with vitamin D, may be attributable for anemia. METHODS: A cross-sectional study of 150 advanced (Stage 4 & 5) pre dialyzed DKD patients (GFR <30ml/min/1.73 m2), aged 40-70 years were included over a period of 1 year. Any other concomitant illness/ drugs leading to anemia were excluded. Serum samples were collected and urea, creatinine, hemoglobin, iron profile, vitamin D, iPTH, uric acid, calcium, phosphorous and albumin levels were measured. A data base was constructed on Microsoft Excel 2007 and statistical analyses were performed using the SPSS software version 20.0 (IBM, NY, USA). RESULTS: Stage 5 DKD had more pronounced anemia compared to stage 4 DKD (P < 0.001). Hemoglobin (Hb) was inversely correlated with iPTH (r = -0.74, P < 0.001) and was associated with vitamin D deficiency (r = 0.51, P < 0.001) but not with serum ferritin. DKD patients with low eGFR (r = -0.6, P < 0.001), vitamin D (r = -0.43, P < 0.001) and serum calcium (r = -0.37, P < 0.001) had higher iPTH. Secondary hyperparathyroidism (beta=-0.005; P < 0.001) and Vitamin D (beta=0.053; P < 0.01) were strong predictor for Hb while parameters of iron profile was not statistically significant. CONCLUSION: An efficient control of PTH hypersecretion is therefore required to achieve a better management of anemia as well as mineral metabolism in DKD patients.

Neurodevelopmental Status of Children aged 6-30 months with Severe Acute Malnutrition.

OBJECTIVE: This cross sectional study was done to assess the developmental status in children (6-30 mo old) with severe acute malutrition (SAM). METHODS: Study subjects were enrolled from children in SAM therapeutic unit, and controls were selected from well-baby clinic of the institute. Neurodevelopment of both groups was assessed using the Developmental assessment scale of Indian infants (DASII). Developmental quotient (DQ) ≤70 was considered delayed. RESULTS: Mean (SE) motor DQ 59.04 (0.74) and mental DQ 62.1 (0.57) was lower in SAM as compared to controls (both P<0.0001). Clusters of early age were normal but clusters with items of later infancy were delayed. CONCLUSION: Children with SAM show significant delay in development, and motor DQ is affected more than mental DQ.

Buschke-Lowenstein tumour of glans penis.

INTRODUCTION: Buschke-Löwenstein tumour, also known as Giant condyloma acuminatum, is a rare, sexually transmitted disease that affects ano-genital region. BLT is a slow growing cauliflower-like tumour, locally aggressive and destructive. Human papillomavirus has been identified as an important contributory factor in the development of tumour. PRESENTATION OF CASE: A 45 year uncircumcised male presented with complaints of cauliflower like growth on glans penis. Growth started as a small papule on the corona sulcus at 12 O'clock position 6 months back. Patient developed pain and dysuria due to compression of urethral meatus. Patient has history of multiple sexual partners. DISCUSSION: BLT, first described by Buschke and Lowenstein in 1925. They observed a penile lesion that clinically resembled both common condyloma acuminata and squamous cell carcinoma, but differing from both of them regarding the biological behaviour and the histopathological appearance. GCA can be differentiated from ordinary condylomas by the characteristic "pushing" rather than "infiltrating" effect that tends to compress and displace the underlying tissue. CONCLUSION: We have successfully treated a penile BLT with surgical excision and no relapse up to 6 months. Surgical excision could be considered an effective therapy in the treatment.

Development, optimization, and characterization of solid self-nanoemulsifying drug delivery systems of valsartan using porous carriers.

The present studies entail formulation development of novel solid self-nanoemulsifying drug delivery systems (S-SNEDDS) of valsartan with improved oral bioavailability, and evaluation of their in vitro and in vivo performance. Preliminary solubility studies were carried out and pseudoternary phase diagrams were constructed using blends of oil (Capmul MCM), surfactant (Labrasol), and cosurfactant (Tween 20). The SNEDDS were systematically optimized by response surface methodology employing 3(3-)Box-Behnken design. The prepared SNEDDS were characterized for viscocity, refractive index, globule size, zeta potential, and TEM. Optimized liquid SNEDDS were formulated into free flowing granules by adsorption on the porous carriers like Aerosil 200, Sylysia (350, 550, and 730) and Neusilin US2, and compressed into tablets. In vitro dissolution studies of S-SNEDDS revealed 3-3.5-fold increased in dissolution rate of the drug due to enhanced solubility. In vivo pharmacodynamic studies in Wistar rats showed significant reduction in mean systolic BP by S-SNEDDS vis-à-vis oral suspension (p < 0.05) owing to the drug absorption through lymphatic pathways. Solid-state characterization of S-SNEDDS using FT-IR and powder XRD studies confirmed lack of any significant interaction of drug with lipidic excipients and porous carriers. Further, the accelerated stability studies for 6 months revealed that S-SNEDDS are found to be stable without any change in physiochemical properties. Thus, the present studies demonstrated the bioavailability enhancement potential of porous carriers based S-SNEDDS for a BCS class II drug, valsartan.