Biomedical research in developing countries: Opportunities, methods, and challenges

Health research is essential for improving global health, health equity, and economic development. There are vast differences in the disease burden, research budget allocation, and scientific publications between the developed and the low-middle-income countries, which are the homes of 85% of the world's population. There are multiple challenges, as well as opportunities for health research in developing countries. One of the primary reasons for reduced research output from the developing countries is the lack of research capacity. Many developing countries are striving to build their research capacity. They are trying to understand their needs and goals to solve their fundamental health problems, but the opportunity for research education and training remains low. The first joint research meeting of the Bangladesh Gastroenterology Society and the British Society of Gastroenterology took place in February 2020 at the Bangabandhu Sheikh Mujib Medical University in Dhaka, Bangladesh, aimed at providing an overview of medical research for young, aspiring medical researchers. This review article provides an outline of the research day and covers a number of useful topics. This review aims to provide a basic guide for early career researchers, both within the field of gastroenterology and, more generally, to all spheres of medical research

Monitoring vegetation dynamics using multi-temporal Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images of Tamil Nadu

Vegetation indices serve as an essential tool in monitoring variations in vegetation. The vegetation indices used often, viz., normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were computed from MODIS vegetation index products. The present study aimed to monitor vegetation's seasonal dynamics by using time series NDVI and EVI indices in Tamil Nadu from 2011 to 2021. Two products characterize the global range of vegetation states and processes more effectively. The data sources were processed and the values of NDVI and EVI were extracted using ArcGIS software. There was a significant difference in vegetation intensity and status of vegetation over time, with NDVI having a larger value than EVI, indicating that biomass intensity varies over time in Tamil Nadu. Among the land cover classes, the deciduous forest showed the highest mean values for NDVI (0.83) and EVI (0.38), followed by cropland mean values of NDVI (0.71) and EVI (0.31) and the lowest NDVI (0.68) and EVI (0.29) was recorded in the scrubland. The study demonstrated that vegetation indices extracted from MODIS offered valuable information on vegetation status and condition at a short temporal time period

Machine Learning Creates a Simple Endoscopic Classification System that Improves Dysplasia Detection in Barrett's Oesophagus amongst Non-expert Endoscopists

INTRODUCTION: Barrett’s oesophagus (BE) is a precursor to oesophageal adenocarcinoma (OAC). Endoscopic surveillance is performed to detect dysplasia arising in BE as it is likely to be amenable to curative treatment. At present, there are no guidelines on who should perform surveillance endoscopy in BE. Machine learning (ML) is a branch of artificial intelligence (AI) that generates simple rules, known as decision trees (DTs). We hypothesised that a DT generated from recognised expert endoscopists could be used to improve dysplasia detection in non-expert endoscopists. To our knowledge, ML has never been applied in this manner. METHODS: Video recordings were collected from patients with non-dysplastic (ND-BE) and dysplastic Barrett’s oesophagus (D-BE) undergoing high-definition endoscopy with i-Scan enhancement (PENTAX®). A strict protocol was used to record areas of interest after which a corresponding biopsy was taken to confirm the histological diagnosis. In a blinded manner, videos were shown to 3 experts who were asked to interpret them based on their mucosal and microvasculature patterns and presence of nodularity and ulceration as well as overall suspected diagnosis. Data generated were entered into the WEKA package to construct a DT for dysplasia prediction. Non-expert endoscopists (gastroenterology specialist registrars in training with variable experience and undergraduate medical students with no experience) were asked to score these same videos both before and after web-based training using the DT constructed from the expert opinion. Accuracy, sensitivity, and specificity values were calculated before and after training where p < 0 05 was statistically significant. RESULTS: Videos from 40 patients were collected including 12 both before and after acetic acid (ACA) application. Experts’ average accuracy for dysplasia prediction was 88%. When experts’ answers were entered into a DT, the resultant decision model had a 92% accuracy with a mean sensitivity and specificity of 97% and 88%, respectively. Addition of ACA did not improve dysplasia detection. Untrained medical students tended to have a high sensitivity but poor specificity as they “overcalled” normal areas. Gastroenterology trainees did the opposite with overall low sensitivity but high specificity. Detection improved significantly and accuracy rose in both groups after formal web-based training although it did it reach the accuracy generated by experts. For trainees, sensitivity rose significantly from 71% to 83% with minimal loss of specificity. Specificity rose sharply in students from 31% to 49% with no loss of sensitivity. CONCLUSION: ML is able to define rules learnt from expert opinion. These generate a simple algorithm to accurately predict dysplasia. Once taught to non-experts, the algorithm significantly improves their rate of dysplasia detection. This opens the door to standardised training and assessment of competence for those who perform endoscopy in BE. It may shorten the learning curve and might also be used to compare competence of trainees with recognised experts as part of their accreditation process

Systematic assessment with I-SCAN magnification endoscopy and acetic acid improves dysplasia detection in patients with Barrett's esophagus

BACKGROUND AND STUDY AIMS: Enhanced endoscopic imaging with chromoendoscopy may improve dysplasia recognition in patients undergoing assessment of Barrett's esophagus (BE). This may reduce the need for random biopsies to detect more dysplasia. The aim of this study was to assess the effect of magnification endoscopy with I-SCAN (Pentax, Tokyo, Japan) and acetic acid (ACA) on dysplasia detection in BE using a novel mucosal and vascular classification system. METHODS: BE segments and suspicious lesions were recorded with high definition white-light and magnification endoscopy enhanced using all I-SCAN modes in combination. We created a novel mucosal and vascular classification system based on similar previously validated classifications for narrow-band imaging (NBI). A total of 27 videos were rated before and after ACA application. Following validation, a further 20 patients had their full endoscopies recorded and analyzed to model use of the system to detect dysplasia in a routine clinical scenario. RESULTS: The accuracy of the I-SCAN classification system for BE dysplasia improved with I-SCAN magnification from 69 % to 79 % post-ACA (P = 0.01). In the routine clinical scenario model in 20 new patients, accuracy of dysplasia detection increased from 76 % using a "pull-through" alone to 83 % when ACA and magnification endoscopy were combined (P = 0.047). Overall interobserver agreement between experts for dysplasia detection was substantial (0.69). CONCLUSIONS: A new I-SCAN classification system for BE was validated against similar systems for NBI with similar outcomes. When used in combination with magnification and ACA, the classification detected BE dysplasia in clinical practice with good accuracy.Trials registered at ISRCTN (58235785)

Improvement over time in outcomes for patients undergoing endoscopic therapy for Barrett's oesophagus-related neoplasia: 6-year experience from the first 500 patients treated in the UK patient registry.

BACKGROUND: Barrett's oesophagus (BE) is a pre-malignant condition leading to oesophageal adenocarcinoma (OAC). Treatment of neoplasia at an early stage is desirable. Combined endoscopic mucosal resection (EMR) followed by radiofrequency ablation (RFA) is an alternative to surgery for patients with BE-related neoplasia. METHODS: We examined prospective data from the UK registry of patients undergoing RFA/EMR for BE-related neoplasia from 2008 to 2013. Before RFA, visible lesions were removed by EMR. Thereafter, patients had RFA 3-monthly until all BE was ablated or cancer developed (endpoints). End of treatment biopsies were recommended at around 12 months from first RFA treatment or when endpoints were reached. Outcomes for clearance of dysplasia (CR-D) and BE (CR-IM) at end of treatment were assessed over two time periods (2008-2010 and 2011-2013). Durability of successful treatment and progression to OAC were also evaluated. RESULTS: 508 patients have completed treatment. CR-D and CR-IM improved significantly between the former and later time periods, from 77% and 56% to 92% and 83%, respectively (p<0.0001). EMR for visible lesions prior to RFA increased from 48% to 60% (p=0.013). Rescue EMR after RFA decreased from 13% to 2% (p<0.0001). Progression to OAC at 12 months is not significantly different (3.6% vs 2.1%, p=0.51). CONCLUSIONS: Clinical outcomes for BE neoplasia have improved significantly over the past 6 years with improved lesion recognition and aggressive resection of visible lesions before RFA. Despite advances in technique, the rate of cancer progression remains 2-4% at 1 year in these high-risk patients. TRIAL REGISTRATION NUMBER: ISRCTN93069556

A deep learning system for detection of early Barrett's neoplasia:a model development and validation study

BACKGROUND: Computer-aided detection (CADe) systems could assist endoscopists in detecting early neoplasia in Barrett's oesophagus, which could be difficult to detect in endoscopic images. The aim of this study was to develop, test, and benchmark a CADe system for early neoplasia in Barrett's oesophagus.METHODS: The CADe system was first pretrained with ImageNet followed by domain-specific pretraining with GastroNet. We trained the CADe system on a dataset of 14 046 images (2506 patients) of confirmed Barrett's oesophagus neoplasia and non-dysplastic Barrett's oesophagus from 15 centres. Neoplasia was delineated by 14 Barrett's oesophagus experts for all datasets. We tested the performance of the CADe system on two independent test sets. The all-comers test set comprised 327 (73 patients) non-dysplastic Barrett's oesophagus images, 82 (46 patients) neoplastic images, 180 (66 of the same patients) non-dysplastic Barrett's oesophagus videos, and 71 (45 of the same patients) neoplastic videos. The benchmarking test set comprised 100 (50 patients) neoplastic images, 300 (125 patients) non-dysplastic images, 47 (47 of the same patients) neoplastic videos, and 141 (82 of the same patients) non-dysplastic videos, and was enriched with subtle neoplasia cases. The benchmarking test set was evaluated by 112 endoscopists from six countries (first without CADe and, after 6 weeks, with CADe) and by 28 external international Barrett's oesophagus experts. The primary outcome was the sensitivity of Barrett's neoplasia detection by general endoscopists without CADe assistance versus with CADe assistance on the benchmarking test set. We compared sensitivity using a mixed-effects logistic regression model with conditional odds ratios (ORs; likelihood profile 95% CIs).FINDINGS: Sensitivity for neoplasia detection among endoscopists increased from 74% to 88% with CADe assistance (OR 2·04; 95% CI 1·73-2·42; p&lt;0·0001 for images and from 67% to 79% [2·35; 1·90-2·94; p&lt;0·0001] for video) without compromising specificity (from 89% to 90% [1·07; 0·96-1·19; p=0·20] for images and from 96% to 94% [0·94; 0·79-1·11; ] for video; p=0·46). In the all-comers test set, CADe detected neoplastic lesions in 95% (88-98) of images and 97% (90-99) of videos. In the benchmarking test set, the CADe system was superior to endoscopists in detecting neoplasia (90% vs 74% [OR 3·75; 95% CI 1·93-8·05; p=0·0002] for images and 91% vs 67% [11·68; 3·85-47·53; p&lt;0·0001] for video) and non-inferior to Barrett's oesophagus experts (90% vs 87% [OR 1·74; 95% CI 0·83-3·65] for images and 91% vs 86% [2·94; 0·99-11·40] for video).INTERPRETATION: CADe outperformed endoscopists in detecting Barrett's oesophagus neoplasia and, when used as an assistive tool, it improved their detection rate. CADe detected virtually all neoplasia in a test set of consecutive cases.FUNDING: Olympus.</p

BOB CAT: a Large-Scale Review and Delphi Consensus for Management of Barrett’s Esophagus With No Dysplasia, Indefinite for, or Low-Grade Dysplasia

OBJECTIVES: Barrett’s esophagus (BE) is a common premalignant lesion for which surveillance is recommended. This strategy is limited by considerable variations in clinical practice. We conducted an international, multidisciplinary, systematic search and evidence-based review of BE and provided consensus recommendations for clinical use in patients with nondysplastic, indefinite, and low-grade dysplasia (LGD). METHODS: We defined the scope, proposed statements, and searched electronic databases, yielding 20,558 publications that were screened, selected online, and formed the evidence base. We used a Delphi consensus process, with an 80% agreement threshold, using GRADE (Grading of Recommendations Assessment, Development and Evaluation) to categorize the quality of evidence and strength of recommendations. RESULTS: In total, 80% of respondents agreed with 55 of 127 statements in the final voting rounds. Population endoscopic screening is not recommended and screening should target only very high-risk cases of males aged over 60 years with chronic uncontrolled reflux. A new international definition of BE was agreed upon. For any degree of dysplasia, at least two specialist gastrointestinal (GI) pathologists are required. Risk factors for cancer include male gender, length of BE, and central obesity. Endoscopic resection should be used for visible, nodular areas. Surveillance is not recommended for <5 years of life expectancy. Management strategies for indefinite dysplasia (IND) and LGD were identified, including a de-escalation strategy for lower-risk patients and escalation to intervention with follow-up for higher-risk patients. CONCLUSIONS: In this uniquely large consensus process in gastroenterology, we made key clinical recommendations for the escalation/de-escalation of BE in clinical practice. We made strong recommendations for the prioritization of future research

Purification of an alpha amylase from Aspergillus flavus NSH9 and molecular characterization of its nucleotide gene sequence

In this study, an alpha-amylase enzyme from a locally isolated Aspergillus flavus NSH9 was purified and characterized. The extracellular α-amylase was purified by ammonium sulfate precipitation and anion-exchange chromatography at a final yield of 2.55-fold and recovery of 11.73%. The molecular mass of the purified α-amylase was estimated to be 54 kDa using SDS-PAGE and the enzyme exhibited optimal catalytic activity at pH 5.0 and temperature of 50 °C. The enzyme was also thermally stable at 50 °C, with 87% residual activity after 60 min. As a metalloenzymes containing calcium, the purified α-amylase showed significantly increased enzyme activity in the presence of Ca2+ ions. Further gene isolation and characterization shows that the α-amylase gene of A. flavus NSH9 contained eight introns and an open reading frame that encodes for 499 amino acids with the first 21 amino acids presumed to be a signal peptide. Analysis of the deduced peptide sequence showed the presence of three conserved catalytic residues of α-amylase, two Ca2+-binding sites, seven conserved peptide sequences, and several other properties that indicates the protein belongs to glycosyl hydrolase family 13 capable of acting on α-1,4-bonds only. Based on sequence similarity, the deduced peptide sequence of A. flavus NSH9 α-amylase was also found to carry two potential surface/secondary-binding site (SBS) residues (Trp 237 and Tyr 409) that might be playing crucial roles in both the enzyme activity and also the binding of starch granules. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature

Efficacy, safety, and predictive factors for a positive yield of EUS-guided Trucut biopsy: a large tertiary referral center experience

OBJECTIVES: Endoscopic ultrasound-guided trucut biopsy (EUS-TCB) technique has the advantage of obtaining tissue for histological examination rather than for cytology alone. However, the diagnostic yield may depend on factors related to both technical aspects and the lesions sampled. Safety of EUS-TCB is yet to be established in a large number of procedures. The aim of the study was to determine factors predicting a positive diagnostic yield, and safety for EUS-TCB in a large tertiary referral center-based service.METHODS: All patients were referred for EUS-guided tissue sampling as a part of their diagnostic workup. Linear-array echoendoscope (GF-2000-OL5, KeyMed) with a 19-gauge trucut needle (Quick-Core, Wilson-Cook) was used by two operators to obtain tissue samples. Clinical data, details of the EUS-TCB, post-procedure complications, and histology were prospectively collected between May 2002 and February 2008.RESULTS: In total, 247 patients (143 men) aged 57-73 (median 66) had EUS-TCB performed. Lesions sampled were in the pancreas (113), esophagogastric wall (34), and extra-pancreatic areas (100) (lymph nodes: 52). The maximum diameter of the lesion/wall thickness ranged from 0.6 to 5.4cm (median 3). One to five passes were made (median 3) to obtain tissue cores 2-18 mm (median 10) in length. The procedure failed in 6% of cases. The overall diagnostic accuracy was 75%. The overall complication rate was 2% (bronchopneumonia, minor hemoptysis, minor hematemesis, mucosal tear, retropharyngeal abscess) with no procedure-related deaths. Site of lesion (pancreatic vs. extra-pancreatic,P2,P<0.013) were predictors of a positive diagnostic yield in univariate analysis. However, only the site of biopsy (P<0.001, 95% CI: 0.58-2.32) and number of passes (P=0.05) were independent predictors in multinominal logistic regression.CONCLUSIONS: Diagnostic yield of EUS-TCB is higher when lesion is approached through the stomach and better when more than two passes were made. In this large series, the complication rate of 2% associated with EUS-TCB was similar to that reported with EUS-fine needle aspiration technique