Wastewater-based Epidemiology for COVID-19 Surveillance: A Survey.

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology (WBE) for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding WBE for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

In silico soil degradation and ecotoxicity analysis of veterinary pharmaceuticals on terrestrial species: first report.

With the aim of persistence property analysis and ecotoxicological impact of veterinary pharmaceuticals on different terrestrial species, different classes of veterinary pharmaceuticals (n = 37) with soil degradation property (DT50) were gathered and subjected to QSAR and q-RASAR model development. The models were developed from 2D descriptors under organization for economic cooperation and development guidelines with the application of multiple linear regressions along with genetic algorithm. All developed QSAR and q-RASAR were statistically significant (Internal = R2adj: 0.721-0.861, Q2LOO: 0.609-0.757, and external = Q2Fn = 0.597-0.933, MAEext = 0.174-0.260). Further, the leverage approach of applicability domain assured the model's reliability. The veterinary pharmaceuticals with no experimental values were classified based on their persistence level. Further, the terrestrial toxicity analysis of persistent veterinary pharmaceuticals was done using toxicity prediction by computer assisted technology and in-house built quantitative structure toxicity relationship models to prioritize the toxic and persistent veterinary pharmaceuticals. This study will be helpful in estimation of persistence and toxicity of existing and upcoming veterinary pharmaceuticals.

An enhanced and efficient approach for feature selection for chronic human disease prediction: A breast cancer study.

Computer-aided diagnosis (CAD) systems play a vital role in modern research by effectively minimizing both time and costs. These systems support healthcare professionals like radiologists in their decision-making process by efficiently detecting abnormalities as well as offering accurate and dependable information. These systems heavily depend on the efficient selection of features to accurately categorize high-dimensional biological data. These features can subsequently assist in the diagnosis of related medical conditions. The task of identifying patterns in biomedical data can be quite challenging due to the presence of numerous irrelevant or redundant features. Therefore, it is crucial to propose and then utilize a feature selection (FS) process in order to eliminate these features. The primary goal of FS approaches is to improve the accuracy of classification by eliminating features that are irrelevant or less informative. The FS phase plays a critical role in attaining optimal results in machine learning (ML)-driven CAD systems. The effectiveness of ML models can be significantly enhanced by incorporating efficient features during the training phase. This empirical study presents a methodology for the classification of biomedical data using the FS technique. The proposed approach incorporates three soft computing-based optimization algorithms, namely Teaching Learning-Based Optimization (TLBO), Elephant Herding Optimization (EHO), and a proposed hybrid algorithm of these two. These algorithms were previously employed; however, their effectiveness in addressing FS issues in predicting human diseases has not been investigated. The following evaluation focuses on the categorization of benign and malignant tumours using the publicly available Wisconsin Diagnostic Breast Cancer (WDBC) benchmark dataset. The five-fold cross-validation technique is employed to mitigate the risk of over-fitting. The evaluation of the proposed approach's proficiency is determined based on several metrics, including sensitivity, specificity, precision, accuracy, area under the receiver-operating characteristic curve (AUC), and F1-score. The best value of accuracy computed through the suggested approach is 97.96%. The proposed clinical decision support system demonstrates a highly favourable classification performance outcome, making it a valuable tool for medical practitioners to utilize as a secondary opinion and reducing the overburden of expert medical practitioners.

Efficient feature selection based novel clinical decision support system for glaucoma prediction from retinal fundus images.

The process of feature selection (FS) is vital aspect of machine learning (ML) model's performance enhancement where the objective is the selection of the most influential subset of features. This paper suggests the Gravitational search optimization algorithm (GSOA) technique for metaheuristic-based FS. Glaucoma disease is selected as the subject of investigation as this disease is spreading worldwide at a very fast pace; 111 million instances of glaucoma are expected by 2040, up from 64 million in 2015. It causes widespread vision impairment. Optic nerve fibres can be degraded and cannot be replaced later in this disease. As a starting point, the retinal fundus images of glaucoma infected persons and healthy persons are used, and 36 features were retrieved from these images of public benchmark datasets and private dataset. Six ML models are trained for classification on the basis of the GSOA's returned subset of features. The suggested FS technique enhances classification performance with selection of most influential features. The eight statistical performance evaluating parameters along with execution time are calculated. The training and testing have been performed using a split approach (70:30), 5-fold cross validation (CV), as well as 10-fold CV. The suggested approach achieved 95.36 % accuracy. Due to its auspicious performance, doctors might use the suggested method to receive a second opinion, which would also help overburdened skilled medical practitioners and save patients from vision loss.

Making waves: The benefits and challenges of responsibly implementing wastewater-based surveillance for rural communities.

The sampling and analysis of sewage for pathogens and other biomarkers offers a powerful tool for monitoring and understanding community health trends and potentially predicting disease outbreaks. Since the early months of the COVID-19 pandemic, the use of wastewater-based testing for public health surveillance has increased markedly. However, these efforts have focused on urban and peri­urban areas. In most rural regions of the world, healthcare service access is more limited than in urban areas, and rural public health agencies typically have less disease outcome surveillance data than their urban counterparts. The potential public health benefits of wastewater-based surveillance for rural communities are therefore substantial - though so too are the methodological and ethical challenges. For many rural communities, population dynamics and insufficient, aging, and inadequately maintained wastewater collection and treatment infrastructure present obstacles to the reliable and responsible implementation of wastewater-based surveillance. Practitioner observations and research findings indicate that for many rural systems, typical implementation approaches for wastewater-based surveillance will not yield sufficiently reliable or actionable results. We discuss key challenges and potential strategies to address them. However, to support and expand the implementation of responsible, reliable, and ethical wastewater-based surveillance for rural communities, best practice guidelines and standards are needed.

Application of wastewater-based surveillance and copula time-series model for COVID-19 forecasts.

The objective of this study was to develop a novel copula-based time series (CTS) model to forecast COVID-19 cases and trends based on wastewater SARS-CoV-2 viral load and clinical variables. Wastewater samples were collected from wastewater pumping stations in five sewersheds in the City of Chesapeake VA. Wastewater SARS-CoV-2 viral load was measured using reverse transcription droplet digital PCR (RT-ddPCR). The clinical dataset included daily COVID-19 reported cases, hospitalization cases, and death cases. The CTS model development included two steps: an autoregressive moving average (ARMA) model for time series analysis (step I), and an integration of ARMA and a copula function for marginal regression analysis (step II). Poisson and negative binomial marginal probability densities for copula functions were used to determine the forecasting capacity of the CTS model for COVID-19 forecasts in the same geographical area. The dynamic trends predicted by the CTS model were well suited to the trend of the reported cases as the forecasted cases from the CTS model fell within the 99 % confidence interval of the reported cases. Wastewater SARS CoV-2 viral load served as a reliable predictor for forecasting COVID-19 cases. The CTS model provided robust modeling to predict COVID-19 cases.

Pharmacophore based virtual screening of cholinesterase inhibitors: search of new potential drug candidates as antialzheimer agents.

Alzheimer's disease (AD) is a distinctive medical condition characterized by loss of memory, orientation, and cognitive impairments, which is an exceptionally universal form of neurodegenerative disease. The statistical data suggested that it is the 3rd major cause of death in older persons. Butyrylcholinesterase (BChE) and acetylcholinesterase (AChE) inhibitors play a vital role in the treatment of AD. Coumarins, natural derivatives, are reported as cholinesterase inhibitors and emerges as a promising scaffold for design of ligands targeting enzymes and pathological alterations related to AD. In this regard, the 3D QSAR pharmacophore models were developed for coumarin scaffold containing BChE and AChE inhibitors. Several 3D QSAR pharmacophore models were developed with FAST, BEST, and CEASER methods, and finally, statistically robust models (based on correlation coefficient, cost value, and RMSE value) were selected for further analysis for both targets. The important features ((HBA 1, HBA 2, HY, RA (BChE) HBA 1, HBA 2, HY, PI, (AChE)) were identified for good inhibitory activity of coumarin derivatives. Finally, the selected models were applied to various database compounds to find potential BChE and AChE inhibitors, and we found 13 for BChE and 1 potent compound for AChE with an estimated activity of IC50 < 10 µM. Further, the Lipinski filters, and ADMET analysis supports the selected compounds to become a drug candidate. These selected BChE and AChE inhibitors can be used in the treatment of AD. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-022-00133-1.

Modified Oyster Waste Shells as a Value-Added Sorbent for Lead Removal from Water.

Used oyster shells are considered a waste product of the seafood industry. Herein, we hypothesize that oyster shells can be used as a raw ingredient to synthesize effective sorbents. This study investigated the lead sorption ability of modified oyster shells [phosphoric-acid treated oyster shell (POS) and oyster shells with phosphoric acid (OS + P)] from water. XRD confirmed the presence of calcium phosphate. Lead removal efficiency as a function of sorbent type was as follows: OS + P > POS > OS. Sorption was quantified effectively using Freundlich isotherms with correlation coefficients ranging from 0.98 to 0.99. The Freundlich parameter values of Kf and n indicate that POS and OS + P exhibit stronger lead sorption than OS. These results indicate that modified oyster shells with OS + P and POS could be effective sorbents for lead removal from water. Kinetic models were well described by a pseudo-second-order rate constant for all the sorbents.

Cochlear Implantation in Pierre Robin Syndrome.

Hereditary hearing loss accounts for nearly 60% of deafness in developed countries and about 30% of them are syndromic. Pierre Robin Syndrome is one such condition. The patient with this syndrome usually presnts with triad of micrognathia, glossoptosis and cleft palate. Hearing loss is mostly conductive but there can be sensorineural hearing loss also. Here we present a case of Pierre Robin Syndrome who presented with congenital hearing loss. He also had bilateral serous otitis media. He underwent cochlear implant surgery and was prescribed antihistaminics and steroid spray for middle ear effusion. Therefore, proper clinical evaluation is required.

Alteration of Smell and Taste Sensations in Covid-19 Positive Patients: A Prospective Cohort Study in Western India.

Loss/alteration of Smell and taste sensation is common in CoViD-19 infection. We conducted present study to find out the frequency, onset and severity of these lost sensations and their recovery in mild, moderate and severe COVID 19 positive patients in our setup. A questionnaire based study on 574 COVID-19 positive patients admitted in a dedicated COVID hospital between September-November, 2020 were followed up until their sensations recovered completely or maximum for two months. Fever was the most common symptom reported. Loss of smell and taste sensation is seen in 200 (34.84%) and 269 (46.86%) patients respectively; 163 (28.4%) developed both. Males were affected significantly more than females (p = 0.030 and 0.027). Approximately 1/4th patients [49 (24.5%) and 55 (20.45%)] reported loss of smell and taste sensation as their first symptom. Most common taste sensation lost was salty 191 (71.0%). Loss of smell sensation is seen maximally in mild cases and the difference among mild, moderate and severe cases is statistically significant (p = 0.00001); while the difference in loss of taste among all three grades of severity is statistically insignificant (p = 0.0770). Most of the patients [smell (142; 71%) and taste (198; 73.6%)] recovered after 2 weeks of onset of lost sensations while 96.5% (193/200) and 98.1% (264/269) patients reported complete recovery of smell and taste sensations after two months of onset. Present study shows that high percentage of COVID-19 positive patients develop loss of either one or both of smell and taste sensations but recovery is fast and complete in most of them.

Development and Prospective Validation of the Levothyroxine Dose Prediction Model in Primary Hypothyroidism.

Multiple visits are needed to achieve euthyroidism on levothyroxine in newly detected primary hypothyroidism. We aimed to develop a levothyroxine dose estimation algorithm for primary hypothyroidism. Adults with newly diagnosed hypothyroidism were enrolled prospectively, first in the training cohort, followed by the validation cohort separated by time and person. We developed a predictive algorithm from Training Cohort and validated the model in Validation Cohort. Training Cohort: In this cohort, 358 subjects (259 women and 99 men) were enrolled. The median duration needed to achieve euthyroidism was 4±0.5 months. The mean levothyroxine daily dose was 60.5±34.1 µg. Data of euthyroid subjects within 6 months of treatment initiation and age range 18-65 years were used for algorithm development. In the multivariable linear regression algorithm, pretreatment serum thyrotropin level, and sex formed the best-fit predictive model (adjusted R2 0.73, p-value <0.001). Validation Cohort: Eighty-four subjects (61 women and 23 men) were enrolled and started on an estimated levothyroxine dose derived from the developed prediction model. On the first follow-up on treatment, 34/50 participants achieved euthyroidism (68%) at 1.5 months. In conclusion, the proposed prediction model for levothyroxine dose estimation effectively achieves early euthyroidism in two-third subjects in the age range of 18-65 years.

Modified Crushed Oyster Shells for Fluoride Removal from Water.

Elevated concentrations of fluoride ions (F-) in natural groundwater are a worldwide problem. Discarded oyster shells were ground to ≤100 µm particle size to produce oyster shell powder (OS). A subset of the OS was heated to produce calcined oyster shell (COS). A subset of the COS was further treated with 1 M phosphoric acid to produce phosphoric-acid-treated oyster shell (POS). OS and COS were combined with phosphoric acid (1.6 mM and 3.2 mM) to produce OS + P (oyster shell with phosphoric acid) and COS + P (calcined oyster shell with phosphoric acid). OS and COS removed 46% and 50% (10 g/L of sorbent dose) but POS, OS + P and COS + P removed 96%, 100% and 76% (1 g/L of sorbent dose) when the initial concentration of fluoride was 10 mg/L. The sorption kinetics of POS, OS + P and COS + P followed second-order reaction rates, and sorption isotherms of all sorbents were well-described by the Freundlich sorption isotherm. These results indicate that oyster shells can be an effective sorbent for fluoride removal, with the added benefit of re-use of a waste product.

Effectiveness of an mHealth-Based Electronic Decision Support System for Integrated Management of Chronic Conditions in Primary Care: The mWellcare Cluster-Randomized Controlled Trial.

BACKGROUND: The burden of noncommunicable diseases and their risk factors has rapidly increased worldwide, including in India. Innovative management strategies with electronic decision support and task sharing have been assessed for hypertension, diabetes mellitus, and depression individually, but an integrated package for multiple chronic condition management in primary care has not been evaluated. METHODS: In a prospective, multicenter, open-label, cluster-randomized controlled trial involving 40 community health centers, using hypertension and diabetes mellitus as entry points, we evaluated the effectiveness of mWellcare, an mHealth system consisting of electronic health record storage and an electronic decision support for the integrated management of 5 chronic conditions (hypertension, diabetes mellitus, current tobacco and alcohol use, and depression) versus enhanced usual care among patients with hypertension and diabetes mellitus in India. At trial end (12-month follow-up), using intention-to-treat analysis, we examined the mean difference between arms in change in systolic blood pressure and glycated hemoglobin as primary outcomes and fasting blood glucose, total cholesterol, predicted 10-year risk of cardiovascular disease, depression score, and proportions reporting tobacco and alcohol use as secondary outcomes. Mixed-effects regression models were used to account for clustering and other confounding variables. RESULTS: Among 3698 enrolled participants across 40 clusters (mean age, 55.1 years; SD, 11 years; 55.2% men), 3324 completed the trial. There was no evidence of difference between the 2 arms for systolic blood pressure (Δ=-0.98; 95% CI, -4.64 to 2.67) and glycated hemoglobin (Δ=0.11; 95% CI, -0.24 to 0.45) even after adjustment of several key variables (adjusted differences for systolic blood pressure: - 0.31 [95% CI, -3.91 to 3.29]; for glycated hemoglobin: 0.08 [95% CI, -0.27 to 0.44]). The mean within-group changes in systolic blood pressure in mWellcare and enhanced usual care were -13.65 mm Hg versus -12.66 mm Hg, respectively, and for glycated hemoglobin were -0.48% and -0.58%, respectively. Similarly, there were no differences in the changes between the 2 groups for tobacco and alcohol use or other secondary outcomes. CONCLUSIONS: We did not find an incremental benefit of mWellcare over enhanced usual care in the management of the chronic conditions studied. CLINICAL TRIAL REGISTRATION: URL: https://www. CLINICALTRIALS: gov. Unique identifier: NCT02480062.

Autoimmune thyroiditis and central serous chorioretinopathy may have a relation.

Autoimmune thyroiditis (AT) is an important cause of hypothyroidism, and central serous chorioretinopathy (CSCR) is an independent disease of the choroid and retina that leads to accumulation of fluid beneath the retina. While AT has been associated with multiple antibodies, CSCR is still regarded as idiopathic despite extensive research. We hypothesize a causative association between these 2 conditions on the basis of our experience of a case where both CSCR and AT presented simultaneously and depicted a parallel course. CSCR was documented with retinal imaging while AT was documented with serum antibody titers. Further, we discuss the possible mechanisms that may be involved in this intriguing association.

Optimal Levothyroxine Replacement Adequately Improves Symptoms of Hypothyroidism; Residual Symptoms Need Further Evaluation for Other than Hypothyroidism Causation.

OBJECTIVES: Many patients with hypothyroidism complain of persistent residual symptoms, despite optimal treatment, although the similar prevalence is seen in patients with documented absence of thyroid disorder in primary health-care setup. We aimed to investigate symptomatic relief in new cases of primary hypothyroidism and compare with controls with other chronic conditions. METHODS: This prospective case-control follow-up study enrolled patients from July 2014 to May 2015 in an endocrine outpatient clinic of a tertiary hospital. Controls were age- and gender-matched ambulatory individuals with well-controlled other chronic diseases and no major comorbidity. Thyroid symptom questionnaire (TSQ) was administered at pretreatment to all the cases and then they were started on levothyroxine (LT). At euthyroidism, TSQ was readministered. For controls, TSQ was administered only once. TSQ was measured on Likert scale 1-4 for lack of energy, dry skin, constipation, aches and pains, cold intolerance, poor memory, depression, weight gain, tiredness after walking, and difficulty in getting up (DGU). P < 0.05 was considered statistically significant. RESULTS: A total of 194 cases (147 females and 47 males) and 259 controls (187 females and 72 males) were analyzed. A significant difference in the symptoms prevalence was seen between controls and pretreatment cases, except for DGU, and between subclinical and overt hypothyroidism. Pretreatment serum thyroid-stimulating hormone in cases correlated significantly with all their pretreatment symptoms score. All symptoms prevalence decreased significantly posttreatment. At euthyroidism, the mean symptoms score in posttreatment cases was similar or lower than the controls. CONCLUSION: LT effectively improves the symptoms of hypothyroidism in newly diagnosed cases of primary hypothyroidism. The residual symptoms need an alternation explanation other than hypothyroidism.

Determinants of levothyroxine dose required to achieve euthyroidism in pediatric population-a hospital-based prospective follow-up study.

We analyzed the relation of pretreatment anthropometric measures and serum thyrotropin (TSH) with the levothyroxine requirement. Children (3-18 years) brought to endocrine clinic with newly diagnosed acquired primary hypothyroidism were enrolled consecutively and prospectively with follow-up (July 2014 to April 2016). Children were started on levothyroxine, and dose was adjusted at regular intervals until achieved euthyroidism (serum TSH 0.4 to 4.5 mIU/L). The relationship of age, gender, height, weight, and serum TSH with levothyroxine dose was analyzed by univariate and multivariate regression analysis. Data of 51 children (42 girls and 9 boys) was used for the analysis. Age, weight, height, and serum TSH had significant correlation with levothyroxine daily dose based on weight (D/W) and dose based on BSA (D/BSA). Log10 TSH and gender explained ∼60% absolute levothyroxine daily requirement. The final model built with height and serum TSH predicted ∼85% of D/W and ∼80% of D/BSA. CONCLUSION: Pretreatment height and serum TSH can be used to determine levothyroxine dose needed to achieve euthyroidism in a newly diagnosed acquired primary hypothyroidism in children. What is Known: • The starting dose of levothyroxine is currently recommended based on the age of children. What is New: • In pediatric population, the effect of age on levothyroxine daily dose requirements can be explained by pretreatment height. • Pretreatment serum TSH level is an important predictor of levothyroxine daily dose in children with newly diagnosed primary hypothyroidism.

Does One Size Fit Everyone? Replacement Dose of Levothyroxine in Long-standing Primary Hypothyroidism in Adults.

OBJECTIVES: The recommended starting dose of levothyroxine (LT4) in primary hypothyroidism is 1.6 µg/kg body weight and is based on presumption of minimal residual thyroid function in autoimmune hypothyroidism. This study aimed at finding the range and determining factors for LT4 dose in long-standing hypothyroidism. METHODS: A cross-sectional study of individuals with primary autoimmune hypothyroidism on LT4 replacement was done between March 2015 and January 2016. Individuals enrolled were euthyroid based on recent serum thyroid-stimulating hormone. The inclusion criteria included LT4 intake in the morning empty stomach, maintenance of at least 1-h food gap, not on medications known to hamper LT4 absorption within 4 h of dosing, diagnosis of hypothyroidism at least for 1 year, and on a minimum 25 µg LT4. P < 0.05 was considered statistically significant. RESULTS: A total of 346 individuals (290 women and 56 men; 214 premenopausal and 76 postmenopausal women) were enrolled. The mean duration of hypothyroidism and age were 5.7 years and 42.1 years, respectively. The range and mean of absolute LT4 daily dose (ADD), LT4 dose based on body weight (D/W), and LT4 dose based on ideal body weight (D/IBW) were 25-200 µg daily and 77.1 µg, 0.3-2.82 µg/kg and 1.21 µg/kg, and 0.42-3.5 µg/kg and 1.58 µg/kg, respectively. Duration of hypothyroidism was significant predictors of ADD, D/W, and D/IBW. Gender-based difference in ADD and D/IBW was explained by gender difference in anthropometry. CONCLUSION: Long-standing primary autoimmune hypothyroidism has variable dose requirement of LT4 for achieving euthyroidism and may be dependent on the degree of residual functional thyroid. Duration of hypothyroidism was significant positive predictor for either ADD, D/W, or D/IBW.

Tuning the Stability and the Reactivity of Substituted [3]Dendralenes for Quick Access to Diverse Copiously Functionalized Fused Polycycles with Step and Atom Economy.

This is the first comprehensive study that details the synthesis of stable acyclic trisubstituted [3]dendralenes and deciphers their structural requisite for a successful diene transmissive Diels-Alder (DTDA) reaction by employing two different dienophiles and eventually generating a small repository of complex molecules, thus exemplifying how substituted [3]dendralenes could be deployed in diversity-oriented synthesis with high selectivities. A balance of reactivity and stability was struck by prudent selection of the position and nature of functional groups on these [3]dendralenes. Upon tandem Diels-Alder reactions with several symmetrical as well as unsymmetrical dienophiles, these dendralenes afforded diversity-oriented quick access to many polycyclic complex motifs possessing several functional groups and multiple stereogenic centers. Thus, the full potential of the dendralenes could be harnessed. The reactions proceeded under mild conditions with step and atom economy and were highly regio- and stereoselective besides being excellent yielding. The DTDA sequence resulted in the generation of four new carbon-carbon bonds, two new rings, and 3-7 stereogenic centers. The key feature of the method is that we could rapidly generate complexity along with functional and structural diversity from a trivial acyclic substrate with no stereogenic centers.

Bitter Melon Extract Promotes Granulation Tissue Growth and Angiogenesis in the Diabetic Wound.

OBJECTIVE: Bitter melon is a plant fruit that has been shown to exert a hypoglycemic effect when used systemically in patients with diabetes. This study was designed to investigate the topical effect of bitter melon on diabetic wounds using the wound chamber model in rats. DESIGN: Two bilateral wound chambers were implanted subcutaneously in the thoracic-lumbar region of male Sprague-Dawley rats. Diabetes was induced with streptozotocin 7 days after implantation of wound chambers. After 24 hours of induction of diabetes, aqueous extract of bitter melon was injected into 1 wound chamber, and saline (0.9% sodium chloride solution) was injected into the contralateral chamber once daily for 3 days. Wound fluid was collected on day 4 for analysis, following which rats were euthanized. The granulation tissue encapsulating the wound chamber was removed and processed for histology. Controls included diabetic rats with wound chambers injected with saline (instead of bitter melon) and nondiabetic rats with wound chambers injected with bitter melon. RESULTS: In rats with diabetes, wound granulation tissue treated with bitter melon was well formed, with distinct cellular layers, whereas the saline-treated granulation tissue showed a severe loss of tissue organization and blood vessels. Moreover, the bitter melon treatment increased angiogenesis in the diabetic granulation tissue, marked by abundant microvessels and large blood vessels. In nondiabetic rats, no differences in wound granulation tissues were observed between saline- and bitter melon-treated groups. Bitter melon treatment had no effect on systemic blood glucose levels or insulin receptor substrate 1, suggesting that its stimulatory effect on diabetic granulation tissue was not due to alteration of systemic blood glucose levels. CONCLUSIONS: When applied locally to diabetic wounds, bitter melon extract prevents regression of granulation tissue and blood vessels, thus accelerating and improving wound healing.