Duhamel\u27s procedure for adult hirschsprung\u27s disease

An adult presented with chronic constipation and abdominal mass. Clinical features, abdominal radiographs and barium enema revealed features consistent with Hirschsprung\u27s disease. Full-thickness rectal biopsy was planned, but patient was lost to follow-up and presented 3 years later with intestinal obstruction. Exploratory laparotomy with resection of affected sigmoid colon and end colostomy were performed. Sequential rectal biopsies were obtained during the procedure to confirm the diagnosis. Later, Duhamel\u27s procedure with a diverting loop ileostomy was successfully performed. Ileostomy reversal was done thereafter. There was complete resolution of symptoms and dramatic improvement in bowel function

Demystifying ANN with Mathematical and Graphical Insights: An Algorithmic Review for Beginners

Developments in deep learning with ANNs (Artificial Neural Networks) are paving the way for revolutionizing all application areas, especially related to non-linear regression and classification problems of predictive modelling and forecasting. Although their explainability is more complicated and challenging, deep neural networks are preferred over conventional machine learning methods for high accuracy in non-linear and complex problems. However, machine learning and data science practitioners often use ANN like a black-box. The present article concisely overviews the mathematics and computations involved in simple feed-forward neural networks (FNNs) or multilayer perceptrons (MLPs). The purpose is to spot light on what deep neural networks’ learning (or training) is and how it works. The article includes simplified derivations of the expressions for the main workhorse of neural networks (the backpropagation) and an example to explain how it works with graphical insights. An algorithm for a basic ANN application is presented in both component-form and matrix-form, together with a detailed note on the relevant data structures, to elaborate the scheme comprehensively. Python implementation of the basic algorithm is presented, and its performance results are compared with those produced using the TensorFlow library functions that implement the neural networks. The article discusses various techniques to improve the generalization capability of neural networks and how to address various training challenges. Finally, some well-established optimization approaches based on the Gradient Descent method are also discussed. The article may serve as a comprehensive premiere for a sound understanding of deep learning for undergraduate and graduate students before indulging in the relevant industry practices so that they can step into sustainable progress in the field

Demystifying RNN with Mathematical and Graphical Insights with Application to Time Series Analysis and Natural Language Processing (NLP)

Recurrent Neural Networks (RNNs) are a type of neural network that maintains a hidden state, preserving information from previous inputs, which enables them to comprehend and generate sequences. RNNs excel in handling tasks involving sequential data over time, particularly in Natural Language Processing (NLP), including applications like voice recognition, music generation, and image captioning. Training RNNs with long sequences presents several challenges. To tackle these challenges, advanced techniques such as Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and Bidirectional RNN (BRNNs) are available in the literature. This article comprehensively explains the fundamental processes of RNNs, including the variants LSTM, GRU, and BRNN, with mathematical and graphical insights. The process is explained using detailed mathematical expressions and algorithmic constructs. The article includes a hands-on worked-out example demonstrating the word prediction. Additionally, it includes an application involving sentiment analysis and compares the performance of simple RNNs, LSTM, GRU, and BRNNs using Transfer Learning. The article also includes an example of time series analysis problem

Study of the Factors that Influence the Completion of the Thesis of Master of Health Professions Education Graduates: A Qualitative Study

Objective: To investigate the experience of timely thesis completion by the graduates of the Master of Health Professions Education (MHPE) program in Pakistan.Study Design: Qualitative interpretative study design.Settings: Riphah University Islamabad and HITEC-IMS Taxila.Duration: May 2018 to June 2019.Materials and Methods: Data was collected by semi-structured interviews. All interviews were carried out in person. Detailed notes were taken, and conversations were audio-recorded. Three authors analyzed data independently using iterative thematic analysis. Inconsistencies were resolved through discussion.Results: Two major themes out of five were identified: Intrinsic attributes of the graduates and the role of the supervisor. including sub-themes of intrinsic motivation, self-regulation, age of the participant, supervisor-trainee relationship, supervisor’s availability, supervisor’s commitment, personality traits of the supervisor. Periods of face-to-face contact sessions were considered to increase internal motivation during which participants believe to have greater self-regulation. Positive relationship with a committed supervisor who was readily available and had a friendly, yet professional attitude aided in the completion of the thesis on time while a supervisor lacking these traits posed challenges for the graduates.Conclusion: Several factors were identified which influenced thesis completion among the graduates of MHPE in Pakistan. The five major ones consisted of the following, 1) Research Project-Related Problems; 2) Support System; 3) Supervisor Guidance; 4) Attributes of the Researcher; 5) Conducive Research Environment. These results can help influence policies to evaluate and improve this program

A Computational Systems Analyses to Identify Biomarkers and Mechanistic Link in Psoriasis and Cutaneous Squamous Cell Carcinoma.

Psoriasis is the most common and chronic skin disease that affects individuals from every age group. The rate of psoriasis is increasing over the time in both developed and developing countries. Studies have revealed the possibility of association of psoriasis with skin cancers, particularly non-melanoma skin cancers (NMSC), which, include basal cell carcinoma and cutaneous squamous cell carcinoma (cSCC). There is a need to analyze the disease at molecular level to propose potential biomarkers and therapeutic targets in comparison to cSCC. Therefore, the second analyzed disease of this study is cSCC. It is the second most common prevalent skin cancer all over the world with the potential to metastasize and recur. There is an urge to validate the proposed biomarkers and discover new potential biomarkers as well. In order to achieve the goals and objectives of the study, microarray and RNA-sequencing data analyses were performed followed by network analysis. Afterwards, quantitative systems biology was implemented to analyze the results at a holistic level. The aim was to predict the molecular patterns that can lead psoriasis to cancer. The current study proposed potential biomarkers and therapeutic targets for psoriasis and cSCC. IL-17 signaling pathway is also identified as significant pathway in both diseases. Moreover, the current study proposed that autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens are sensitive towards MAPKs (MAPK13 and MAPK14) and genes for AP-1 (FOSL1 and FOS). Therefore, these genes should be further studied in gene knock down based studies as they may play significant role in leading psoriasis towards cancer

Long non-coding RNAs and their targets as potential biomarkers in breast cancer.

Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease-specific biomarkers. Recently, long non-coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post-transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co-expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co-expressed lncRNAs and their cis- and trans-regulating mRNA targets which include RP11-108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future

A Computational Systems Analyses to Identify Biomarkers and Mechanistic Link in Psoriasis and Cutaneous Squamous Cell Carcinoma

Psoriasis is the most common and chronic skin disease that affects individuals from every age group. The rate of psoriasis is increasing over the time in both developed and developing countries. Studies have revealed the possibility of association of psoriasis with skin cancers, particularly non-melanoma skin cancers (NMSC), which, include basal cell carcinoma and cutaneous squamous cell carcinoma (cSCC). There is a need to analyze the disease at molecular level to propose potential biomarkers and therapeutic targets in comparison to cSCC. Therefore, the second analyzed disease of this study is cSCC. It is the second most common prevalent skin cancer all over the world with the potential to metastasize and recur. There is an urge to validate the proposed biomarkers and discover new potential biomarkers as well. In order to achieve the goals and objectives of the study, microarray and RNA-sequencing data analyses were performed followed by network analysis. Afterwards, quantitative systems biology was implemented to analyze the results at a holistic level. The aim was to predict the molecular patterns that can lead psoriasis to cancer. The current study proposed potential biomarkers and therapeutic targets for psoriasis and cSCC. IL-17 signaling pathway is also identified as significant pathway in both diseases. Moreover, the current study proposed that autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens are sensitive towards MAPKs (MAPK13 and MAPK14) and genes for AP-1 (FOSL1 and FOS). Therefore, these genes should be further studied in gene knock down based studies as they may play significant role in leading psoriasis towards cancer

Effect of early tranexamic acid administration on mortality, hysterectomy, and other morbidities in women with post-partum haemorrhage (WOMAN): an international, randomised, double-blind, placebo-controlled trial

Background Post-partum haemorrhage is the leading cause of maternal death worldwide. Early administration of tranexamic acid reduces deaths due to bleeding in trauma patients. We aimed to assess the effects of early administration of tranexamic acid on death, hysterectomy, and other relevant outcomes in women with post-partum haemorrhage. Methods In this randomised, double-blind, placebo-controlled trial, we recruited women aged 16 years and older with a clinical diagnosis of post-partum haemorrhage after a vaginal birth or caesarean section from 193 hospitals in 21 countries. We randomly assigned women to receive either 1 g intravenous tranexamic acid or matching placebo in addition to usual care. If bleeding continued after 30 min, or stopped and restarted within 24 h of the first dose, a second dose of 1 g of tranexamic acid or placebo could be given. Patients were assigned by selection of a numbered treatment pack from a box containing eight numbered packs that were identical apart from the pack number. Participants, care givers, and those assessing outcomes were masked to allocation. We originally planned to enrol 15 000 women with a composite primary endpoint of death from all-causes or hysterectomy within 42 days of giving birth. However, during the trial it became apparent that the decision to conduct a hysterectomy was often made at the same time as randomisation. Although tranexamic acid could influence the risk of death in these cases, it could not affect the risk of hysterectomy. We therefore increased the sample size from 15 000 to 20 000 women in order to estimate the effect of tranexamic acid on the risk of death from post-partum haemorrhage. All analyses were done on an intention-to-treat basis. This trial is registered with ISRCTN76912190 (Dec 8, 2008); ClinicalTrials.gov, number NCT00872469; and PACTR201007000192283. Findings Between March, 2010, and April, 2016, 20 060 women were enrolled and randomly assigned to receive tranexamic acid (n=10 051) or placebo (n=10 009), of whom 10 036 and 9985, respectively, were included in the analysis. Death due to bleeding was significantly reduced in women given tranexamic acid (155 [1·5%] of 10 036 patients vs 191 [1·9%] of 9985 in the placebo group, risk ratio [RR] 0·81, 95% CI 0·65–1·00; p=0·045), especially in women given treatment within 3 h of giving birth (89 [1·2%] in the tranexamic acid group vs 127 [1·7%] in the placebo group, RR 0·69, 95% CI 0·52–0·91; p=0·008). All other causes of death did not differ significantly by group. Hysterectomy was not reduced with tranexamic acid (358 [3·6%] patients in the tranexamic acid group vs 351 [3·5%] in the placebo group, RR 1·02, 95% CI 0·88–1·07; p=0·84). The composite primary endpoint of death from all causes or hysterectomy was not reduced with tranexamic acid (534 [5·3%] deaths or hysterectomies in the tranexamic acid group vs 546 [5·5%] in the placebo group, RR 0·97, 95% CI 0·87-1·09; p=0·65). Adverse events (including thromboembolic events) did not differ significantly in the tranexamic acid versus placebo group. Interpretation Tranexamic acid reduces death due to bleeding in women with post-partum haemorrhage with no adverse effects. When used as a treatment for postpartum haemorrhage, tranexamic acid should be given as soon as possible after bleeding onset. Funding London School of Hygiene & Tropical Medicine, Pfizer, UK Department of Health, Wellcome Trust, and Bill & Melinda Gates Foundation

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)