Household food insecurity and dietary diversity as correlates of maternal and child undernutrition in rural Cambodia

OBJECTIVES

To assess household food insecurity and dietary diversity as correlates of maternal and child anthropometric status and anemia in rural Cambodia.

METHODS

Trained interviewers administered a survey to 900 households in four rural districts of Prey Veng, Cambodia. The Household Food Insecurity Access Scale (HFIAS) and Household Dietary Diversity Score (HDDS) were used to assess household food insecurity and dietary diversity. The height, weight and hemoglobin concentration of the mother and youngest child under 5 years in each household were measured. Multivariate logistic regression models were constructed to assess the association between household food insecurity and dietary diversity, and child stunting and wasting, maternal thinness, maternal and child anemia.

RESULTS

The mean (s.d.) HFIAS and HDDS scores were 5.3 (3.9) and 4.7 (1.6), respectively. The respective prevalences of mild, moderate and severe food insecurity were 33, 37 and 12%. Maternal thinness, child stunting and child wasting were present in 14.6, 25.4 and 8.1% of respondents, respectively. The risk of maternal thinness, but not child stunting or wasting, increased as the severity of household food insecurity increased. Household food insecurity was also positively associated with maternal, but not child, anemia. Household dietary diversity status was not significantly associated with any of the outcomes we assessed.

CONCLUSIONS

Efforts to improve household food security are important as a means of promoting maternal nutritional status; however, additional research is needed to better understand the role of other factors that are driving the burden of child undernutrition in Cambodia.

Serine phosphorylation of paxillin by heregulin-beta1: role of p38 mitogen activated protein kinase

The mechanisms through which heregulin (HRG) regulates the progression of breast cancer cells to a more invasive phenotype are currently unknown. Recently we have shown that HRG treatment of breast cancer cells leads to the formation of lamellipodia/filopodia, and increased cell migration and invasiveness through the phosphatidylinositol 3-kinase (PI-3 kinase). Since the process of cell migration must involve changes in adhesion, we explored the potential HRG regulation of paxillin, a major cytoskeletal phosphoprotein of focal adhesion. We report that HRG stimulation of non-invasive breast cancer cells resulted in stimulation of p38 mitogen-activated protein kinase (p38MAPK), extracellular signal-regulated kinases (ERK) and PI-3K, and a concurrent unexpected increase in the level of paxillin phosphorylation on serine residue which was sensitive to protein-phosphatase 2b but not to protein tyrosine phosphatase 1. In addition, HRG triggered a rapid redistribution of paxillin to the perinuclear regions from the tyrosine-phosphorylated focal adhesions, and increased cell scattering. There was no effect of HRG on the state of phosphorylation and localization of focal adhesion kinase. The HRG-induced increase in serine phosphorylation of paxillin and cell scattering were selectively inhibited by a specific inhibitor of p38MAPK or a dominant-negative p38MAPK mutant, but not by inhibitors of p42/44MAPK or PI-3 kinase pathways. For the first time our results have shown that HRG, a potent migratory growth factor stimulates serine phosphorylation of paxillin. These findings suggest a role of p38MAPK-dependent signal transduction pathway(s) in serine phosphorylation and disassembly of the paxillin from the focal complexes during HRG-induced cell shape alterations and motility.

Interpretation of deep learning in genomics and epigenomics

Machine learning methods have been widely applied to big data analysis in genomics and epigenomics research. Although accuracy and efficiency are common goals in many modeling tasks, model interpretability is especially important to these studies towards understanding the underlying molecular and cellular mechanisms. Deep neural networks (DNNs) have recently gained popularity in various types of genomic and epigenomic studies due to their capabilities in utilizing large-scale high-throughput bioinformatics data and achieving high accuracy in predictions and classifications. However, DNNs are often challenged by their potential to explain the predictions due to their black-box nature. In this review, we present current development in the model interpretation of DNNs, focusing on their applications in genomics and epigenomics. We first describe state-of-the-art DNN interpretation methods in representative machine learning fields. We then summarize the DNN interpretation methods in recent studies on genomics and epigenomics, focusing on current data- and computing-intensive topics such as sequence motif identification, genetic variations, gene expression, chromatin interactions and non-coding RNAs. We also present the biological discoveries that resulted from these interpretation methods. We finally discuss the advantages and limitations of current interpretation approaches in the context of genomic and epigenomic studies. Contact:xiaoman@mail.ucf.edu, haihu@cs.ucf.edu.

EPIP: a novel approach for condition-specific enhancer-promoter interaction prediction

MOTIVATION

The identification of enhancer-promoter interactions (EPIs), especially condition-specific ones, is important for the study of gene transcriptional regulation. Existing experimental approaches for EPI identification are still expensive, and available computational methods either do not consider or have low performance in predicting condition-specific EPIs.

RESULTS

We developed a novel computational method called EPIP to reliably predict EPIs, especially condition-specific ones. EPIP is capable of predicting interactions in samples with limited data as well as in samples with abundant data. Tested on more than eight cell lines, EPIP reliably identifies EPIs, with an average area under the receiver operating characteristic curve of 0.95 and an average area under the precision-recall curve of 0.73. Tested on condition-specific EPIPs, EPIP correctly identified 99.26% of them. Compared with two recently developed methods, EPIP outperforms them with a better accuracy.

AVAILABILITY AND IMPLEMENTATION

The EPIP tool is freely available at http://www.cs.ucf.edu/˜xiaoman/EPIP/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Differential open chromatin profile and transcriptomic signature define depot-specific human subcutaneous preadipocytes: primary outcomes

Background

Increased lower body fat is associated with reduced cardiometabolic risk. The molecular basis for depot-specific differences in gluteofemoral (GF) compared with abdominal (A) subcutaneous adipocyte function is poorly understood. In the current report, we used a combination of Assay for Transposase-Accessible Chromatin followed by sequencing (ATAC-seq), RNA-seq, and chromatin immunoprecipitation (ChIP)-qPCR analyses that provide evidence that depot-specific gene expression patterns are associated with differential epigenetic chromatin signatures.

Methods

Preadipocytes cultured from A and GF adipose tissue obtained from premenopausal apple-shaped women were used to perform transcriptome analysis by RNA-seq and assess accessible chromatin regions by ATAC-seq. We measured mRNA expression and performed ChIP-qPCR experiments for histone modifications of active (H3K4me3) and repressed chromatin (H3K27me3) regions respectively on the promoter regions of differentially expressed genes.

Results

RNA-seq experiments revealed an A-fat and GF-fat selective gene expression signature, with 126 genes upregulated in abdominal preadipocytes and 90 genes upregulated in GF cells. ATAC-seq identified almost 10-times more A-specific chromatin-accessible regions. Using a combined analysis of ATAC-seq and global gene expression data, we identified 74 of the 126 abdominal-specific genes (59%) with A-specific accessible chromatin sites within 200 kb of the transcription start site (TSS), including HOXA3, HOXA5, IL8, IL1b, and IL6. Interestingly, only 14 of the 90 GF-specific genes (15%) had GF-specific accessible chromatin sites within 200 kb of the corresponding TSS, including HOXC13 and HOTAIR, whereas 25 of them (28%) had abdominal-specific accessible chromatin sites. ChIP-qPCR experiments confirmed that the active H3K4me3 chromatin mark was significantly enriched at the promoter regions of HOXA5 and HOXA3 genes in abdominal preadipocytes, while H3K27me3 was less abundant relative to chromatin from GF. This is consistent with their A-fat specific gene expression pattern. Conversely, analysis of the promoter regions of the GF specific HOTAIR and HOXC13 genes exhibited high H3K4me3 and low H3K27me3 levels in GF chromatin compared to A chromatin.

Conclusions

Global transcriptome and open chromatin analyses of depot-specific preadipocytes identified their gene expression signature and differential open chromatin profile. Interestingly, A-fat-specific open chromatin regions can be observed in the proximity of GF-fat genes, but not vice versa.

Trial registration

Clinicaltrials.gov, NCT01745471. Registered 5 December 2012.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0582-0) contains supplementary material, which is available to authorized users.

Computational annotation of miRNA transcription start sites

Motivation

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation.

Results

In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes.

Contact

xiaoman@mail.ucf.edu, haihu@cs.ucf.edu

Mapping the mesoscale interface structure in polycrystalline materials

A new experimental approach to the quantitative characterization of polycrystalline microstructure by scanning electron microscopy is described. Combining automated electron backscattering diffraction with conventional scanning contrast imaging and with calibrated serial sectioning, the new method (mesoscale interface mapping system) recovers precision estimates of the 3D idealized aggregate function G(x). This function embodies a description of lattice phase and orientation (limiting resolution approximately 1 degree) at each point x (limiting spatial resolution approximately 100 nm), and, therefore, contains a complete mesoscale description of the interfacial network. The principal challenges of the method, achieving precise spatial registry between adjacent images and adequate distortion correction, are described. A description algorithm for control of the various components of the system is also provided.

A closed-form neural network for discriminatory feature extraction from high-dimensional data

We consider a new neural network for data discrimination in pattern recognition applications. We refer to this as a maximum discriminating feature (MDF) neural network. Its weights are obtained in closed-form, thereby overcoming problems associated with other nonlinear neural networks. It uses neuron activation functions that are dynamically chosen based on the application. It is theoretically shown to provide nonlinear transforms of the input data that are more general than those provided by other nonlinear multilayer perceptron neural network and support-vector machine techniques for cases involving high-dimensional (image) inputs where training data are limited and the classes are not linearly separable. We experimentally verify this on synthetic examples.

A deep learning method for miRNA/isomiR target detection

Accurate identification of microRNA (miRNA) targets at base-pair resolution has been an open problem for over a decade. The recent discovery of miRNA isoforms (isomiRs) adds more complexity to this problem. Despite the existence of many methods, none considers isomiRs, and their performance is still suboptimal. We hypothesize that by taking the isomiR-mRNA interactions into account and applying a deep learning model to study miRNA-mRNA interaction features, we may improve the accuracy of miRNA target predictions. We developed a deep learning tool called DMISO to capture the intricate features of miRNA/isomiR-mRNA interactions. Based on tenfold cross-validation, DMISO showed high precision (95%) and recall (90%). Evaluated on three independent datasets, DMISO had superior performance to five tools, including three popular conventional tools and two recently developed deep learning-based tools. By applying two popular feature interpretation strategies, we demonstrated the importance of the miRNA regions other than their seeds and the potential contribution of the RNA-binding motifs within miRNAs/isomiRs and mRNAs to the miRNA/isomiR-mRNA interactions.

Dengue Fever as A Cause of Acute Disseminated Encephalomyelitis (ADEM)

Dengue fever is very common in Bangladesh. Every year a large number of urban populations suffer from this viral infection. Various presentations of dengue fever have been documented. Neurological complications in dengue fever are relatively uncommon. Among these, Acute Disseminated Encephalomyelitis (ADEM) has been observed in very few cases. Here we present a case of 13 year old girl suffering from ADEM following dengue fever. Keyword: Acute Disseminated Encephalomyelitis, Dengue fever, Neurological complication.DOI: http://dx.doi.org/10.3329/jom.v12i2.8428 JOM 2011; 12(2): 185-187

A two-stream convolutional neural network for microRNA transcription start site feature integration and identification

MicroRNAs (miRNAs) play important roles in post-transcriptional gene regulation and phenotype development. Understanding the regulation of miRNA genes is critical to understand gene regulation. One of the challenges to study miRNA gene regulation is the lack of condition-specific annotation of miRNA transcription start sites (TSSs). Unlike protein-coding genes, miRNA TSSs can be tens of thousands of nucleotides away from the precursor miRNAs and they are hard to be detected by conventional RNA-Seq experiments. A number of studies have been attempted to computationally predict miRNA TSSs. However, high-resolution condition-specific miRNA TSS prediction remains a challenging problem. Recently, deep learning models have been successfully applied to various bioinformatics problems but have not been effectively created for condition-specific miRNA TSS prediction. Here we created a two-stream deep learning model called D-miRT for computational prediction of condition-specific miRNA TSSs ( http://hulab.ucf.edu/research/projects/DmiRT/ ). D-miRT is a natural fit for the integration of low-resolution epigenetic features (DNase-Seq and histone modification data) and high-resolution sequence features. Compared with alternative computational models on different sets of training data, D-miRT outperformed all baseline models and demonstrated high accuracy for condition-specific miRNA TSS prediction tasks. Comparing with the most recent approaches on cell-specific miRNA TSS identification using cell lines that were unseen to the model training processes, D-miRT also showed superior performance.

A systematic evaluation of the computational tools for lncRNA identification

The computational identification of long non-coding RNAs (lncRNAs) is important to study lncRNAs and their functions. Despite the existence of many computation tools for lncRNA identification, to our knowledge, there is no systematic evaluation of these tools on common datasets and no consensus regarding their performance and the importance of the features used. To fill this gap, in this study, we assessed the performance of 17 tools on several common datasets. We also investigated the importance of the features used by the tools. We found that the deep learning-based tools have the best performance in terms of identifying lncRNAs, and the peptide features do not contribute much to the tool accuracy. Moreover, when the transcripts in a cell type were considered, the performance of all tools significantly dropped, and the deep learning-based tools were no longer as good as other tools. Our study will serve as an excellent starting point for selecting tools and features for lncRNA identification.

Position-wise binding preference is important for miRNA target site prediction

MOTIVATION

It is a fundamental task to identify microRNAs (miRNAs) targets and accurately locate their target sites. Genome-scale experiments for miRNA target site detection are still costly. The prediction accuracies of existing computational algorithms and tools are often not up to the expectation due to a large number of false positives. One major obstacle to achieve a higher accuracy is the lack of knowledge of the target binding features of miRNAs. The published high-throughput experimental data provide an opportunity to analyze position-wise preference of miRNAs in terms of target binding, which can be an important feature in miRNA target prediction algorithms.

RESULTS

We developed a Markov model to characterize position-wise pairing patterns of miRNA-target interactions. We further integrated this model as a scoring method and developed a dynamic programming (DP) algorithm, MDPS (Markov model-scored Dynamic Programming algorithm for miRNA target site Selection) that can screen putative target sites of miRNA-target binding. The MDPS algorithm thus can take into account both the dependency of neighboring pairing positions and the global pairing information. Based on the trained Markov models from both miRNA-specific and general datasets, we discovered that the position-wise binding information specific to a given miRNA would benefit its target prediction. We also found that miRNAs maintain region-wise similarity in their target binding patterns. Combining MDPS with existing methods significantly improves their precision while only slightly reduces their recall. Therefore, position-wise pairing patterns have the promise to improve target prediction if incorporated into existing software tools.

AVAILABILITY AND IMPLEMENTATION

The source code and tool to calculate MDPS score is available at http://hulab.ucf.edu/research/projects/MDPS/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

An intriguing characteristic of enhancer-promoter interactions

Background

It is still challenging to predict interacting enhancer-promoter pairs (IEPs), partially because of our limited understanding of their characteristics. To understand IEPs better, here we studied the IEPs in nine cell lines and nine primary cell types.

Results

By measuring the bipartite clustering coefficient of the graphs constructed from these experimentally supported IEPs, we observed that one enhancer is likely to interact with either none or all of the target genes of another enhancer. This observation implies that enhancers form clusters, and every enhancer in the same cluster synchronously interact with almost every member of a set of genes and only this set of genes. We perceived that an enhancer can be up to two megabase pairs away from other enhancers in the same cluster. We also noticed that although a fraction of these clusters of enhancers do overlap with super-enhancers, the majority of the enhancer clusters are different from the known super-enhancers.

Conclusions

Our study showed a new characteristic of IEPs, which may shed new light on distal gene regulation and the identification of IEPs.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-021-07440-5).

Differences in brain spindle density during sleep between patients with and without type 2 diabetes

BACKGROUND

Sleep spindles may be implicated in sensing and regulation of peripheral glucose. Whether spindle density in patients with type 2 diabetes mellitus (T2DM) differs from that of healthy subjects is unknown.

METHODS

Our retrospective analysis of polysomnography (PSG) studies identified 952 patients with T2DM and 952 sex-, age- and BMI-matched control subjects. We extracted spindles from PSG electroencephalograms and used rank-based statistical methods to test for differences between subjects with and without diabetes. We also explored potential modifiers of spindle density differences. We replicated our analysis on independent data from the Sleep Heart Health Study.

RESULTS

We found that patients with T2DM exhibited about half the spindle density during sleep as matched controls (P < 0.0001). The replication dataset showed similar trends. The patient-minus-control paired difference in spindle density for pairs where the patient had major complications were larger than corresponding paired differences in pairs where the patient lacked major complications, despite both patient groups having significantly lower spindle density compared to their respective control subjects. Patients with a prescription for a glucagon-like peptide 1 receptor agonist had significantly higher spindle density than those without one (P ≤ 0.03). Spindle density in patients with T2DM monotonically decreased as their highest recorded HbA1C level increased (P ≤ 0.003).

CONCLUSIONS

T2DM patients had significantly lower spindle density than control subjects; the size of that difference was correlated with markers of disease severity (complications and glycemic control). These findings expand our understanding of the relationships between sleep and glucose regulation.

Influence of the Interval between Antenatal Corticosteroid Therapy and Delivery on the Incidence of Respiratory Distress Syndrome in Neonate

In spite of the recommendation for rescue antenatal corticosteroids (ACS), the optimal time interval between primary and rescue courses has not been clearly demonstrated. The aim of this retrospective study was to determine the effects of the interval between a single ACS (Dexamethasone) course and delivery on the incidence of respiratory distress syndrome (RDS) in neonates at Mymensingh Medical College Hospital Center from 1st January 2017 to 30th June 2017. Injection Dexamethasone 2 doses (12.5mg IM 12 hourly for 2 doses) or 4 doses (6mg IM every 12 hours for 4 doses) use to arrest preterm labor as well as to prevent RDS delivered beyond 48 hours after ACS administration between 24 and 34 weeks gestation. The risk of RDS was compared between patients who delivered within seven days (Group I) and 7-14 days (Group II) after ACS administration. We included 140 and 60 patients in Group I and Group II respectively. After adjusting for confounders, the ACS delivery interval was significantly associated with RDS in Group II (adjusted odds ratio 12.8, 95% confidence interval 1.31-164.7). A longer ACS delivery interval is associated with a higher risk of RDS. Thus, the use of a rescue course could be expected to reduce the incidence of RDS in patients beyond seven days after ACS administration who remain at risk for preterm delivery within seven days, especially in cases of placenta previa and/or women bearing a male fetus.

Coverage of defects over Posterior aspect of Ankle Joint and Heel with Lateral Calcaneal Artery Flap- Experience in Mymensingh Medical College Hospital

Lateral calcaneal artery flap is randomly used by many Plastic Surgeons for covering any defect on the posterior aspect of heel. A prospective observational study was conducted in the Department of Burn and Plastic Surgery, Mymensingh Medical College Hospital, Mymensingh, Bangladesh from January 2020 to June 2022, to see the outcome of the flap for coverage of defects over the posterior aspect of ankle joint and heel. A total number of 09 patients, selected by purposive sampling, were included in the study. The age of the patients ranged from 06 years to 70 years. The cause of the defects were post traumatic in 07 cases, electric burn in 01 case and pressure sore in 01 case. The defect sizes varied from 3×2 to 6×3cm. and flap size ranged from 4×2.5 to 7×4.5cm. The follow-up period ranged from 3 to 6 months. All the flaps survived completely without any complications; except in two cases. In one case, there was marginal epidermal necrolysis that healed secondarily without the need of any further surgical intervention. In the other case, there was gangrene of about 0.5 cm area at the flap tip, which was debrided and the resulting wound healed secondarily. The average operating time was 63 minutes. The results were satisfactory on the context of adequate coverage, and flap and donor site morbidity. So, the lateral calcaneal artery flap can be a good and safe option for the coverage of posterior ankle and heel defects.

Fetomaternal Outcome in Eclampsia in Relationship with Gravidity

Eclampsia is a well-recognized major cause of maternal and perinatal morbidity and mortality. Patient's age, occupational status, socioeconomic status, educational status, regular ANC (antenatal care) and gravidity may affect the outcome of mother and foetus. The purpose of this study is to see the fetomaternal outcome in eclampsia in relationship with gravidity. This prospective observational cross-sectional study carried out among the alternate cases of primigravid and multigravid eclamptic patients. Total number of patients was 100 eclamptic patients among them, 50 patients were primigravida and 50 patients were multigravida. The study was conducted in Eclampsia unit of Department of Gynaecology and Obstetrics, Dhaka Medical College Hospital, Dhaka, Bangladesh from 21 November 2011 to 20 May 2012. In this study, it was observed that ARF (acute renal failure) occurred in 6%, of these 4 cases of multigravida and 2 cases of primigravida. Cerebro vascular accident (CVA) was reported in 16 patients and 26% in multigravida and 6% in primigravid patients. HELLP (Haemolysis, Elevated liver enzymes and low platelets) syndrome developed in 25 cases of multigravida and 6 cases of primigravida. Heart failure occurred in 7% cases, out of these 6 cases were multigravida and 1 case was primigravida. Pulmonary edema was observed in 41%, among were 21 cases of multigravida and 20 cases of primigravida. Incidence of DIC (disseminated intravascular coagulation) was noted in 2 cases of multigravida and 1 case of primigravida. PPH (postpartum haemorrhage) occurred in 10 cases of multigravida and 3 cases of primigravid patients. Puerperal psychosis was reported in 8% of multigravida and 4% of primigravida. Total 4% of patients expired, among them 3 cases were multigravida and 1 case was primigravida. Perinatal mortality was 21 cases in multigravida and 8 cases in primigravida. The incidence of live birth, in case of multigravida was 39 cases and primigravida 45 cases. Data were analyzed by paired student's 't' test. There was no statistically significant difference between primi and multigravida in feto-maternal outcome. This study reveals that gravidity does not alter the feto-maternal outcome in eclampsia.

Detection of Movement and Lead-Popping Artifacts in Polysomnography EEG Data

Polysomnography (PSG) measures brain activity during sleep via electroencephalography (EEG) using six leads. Artifacts caused by movement or loose leads distort EEG measurements. We developed a method to automatically identify such artifacts in a PSG EEG trace. After preprocessing, we extracted power levels at frequencies of 0.5-32.5 Hz with multitaper spectral analysis using 4 s windows with 3 s overlap. For each resulting 1 s segment, we computed segment-specific correlations between power levels for all pairs of leads. We then averaged all pairwise correlation coefficients involving each lead, creating a time series of segment-specific average correlations for each lead. Our algorithm scans each averaged time series separately for "bad" segments using a local moving window. In a second pass, any segment whose averaged correlation is less than a global threshold among all remaining good segments is declared an outlier. We mark all segments between two outlier segments fewer than 300 s apart as artifact regions. This process is repeated, removing a channel with excessive outliers in each iteration. We compared artifact regions discovered by our algorithm to expert-assessed ground truth, achieving sensitivity and specificity of 80% and 91%, respectively. Our algorithm is an open-source tool, either as a Python package or a Docker.

Demographic Study of Epileptic Burn Patient in a Tertiary Level Hospital of Bangladesh

Burns are very common and important injuries associated with epilepsy. Epileptics are afflicted with burns when they come in contact with fire or other burning agents while seizing, due to loss of consciousness. The aim of the study was to identify the causes of burn, pattern and characteristics of burn in patients with epilepsy, duration of hospital stay and pattern of treatment in these patients. This prospective observational study was conducted in the Department of Burn and Plastic Surgery, Mymensingh Medical College Hospital, Bangladesh from January 2022 to December 2023. Epileptics were found in 0.84% (n=19) of the total admission (2274) in Burn unit. Majority of the patients were females (84.2%) and the mean age was (31.42±1.32) years. Maximum patients were housewives (78.9%). Among 19 cases, 11 cases (57.89%) had history of irregularly taking antiepileptic drugs and 8 cases (42.11%) had no history of treatment for epilepsy. Two cases (10.53%) had history of previous burn injury. Flame burn was the major etiology (89.5%). Mean total burn surface area (TBSA) was (6.94±4.12%). Most patients had full thickness burns (63.2%). Regarding distribution of burn, maximum involvement was in upper limb i.e. 68.21% cases. Surgical treatment was needed in the majority of the patients (68.5%). Mean hospital stay of these patients was (5.36±2.26) weeks. Epilepsy patients whose seizures are inadequately controlled are at increased risks of injury, especially burn. For prevention of burn, epilepsy should be treated properly.

Developments in Hand Surgery: Experience from a Tertiary Hospital of Northern Bangladesh

Hand Surgery is a specialized branch of Plastic and Reconstructive surgery. There are many conditions that require hand surgery, for example, congenital deformity, electric or flame burn, mechanical or road traffic injury, and post burn or post traumatic deformity. A retrospective observational study was conducted in the department of Burn and Plastic surgery, Mymensingh Medical College Hospital, Bangladesh during a 2 years period extending from 9th September 2021 to 8th September 2023. The objective of this study was to see the hand surgery status in a tertiary hospital of Bangladesh during the post Covid pandemic period. During this period 236 hand surgery procedures were performed in 176 patients. The age of the patients ranged from 02 to 78 years (Mean 31.14±1.52). One hundred and four (59.0%) were male and 72(41.0%) were female. Thirty-four (19.32%) patients had co-morbidities e.g., Epilepsy, Diabetes Mellitus, Chronic Kidney Diseases and HBsAg +ve. Causes of surgery included, wound due to electric burn 49(27.84%), flame burn 36(20.45%), post traumatic 24(13.64%), post infective 11(06.25%), tumor excision 02(2.24%), Dupuytren's contracture 03(1.70%), congenital anomalies 06(3.41%), post burn scar contractures 41(23.29%), nerve injury 01(00.57%) and carpal tunnel syndrome 01 (00.57%). Procedures were performed: post burn scar contracture release 41(17.37%), syndactly release 06(2.54%), release of post traumatic contracture 06(2.54%), carpal tunnel release 01(00.42%), release of Dupuytren's contracture 03(01.27%), nerve repair 01(00.42%), debridement, amputation and Fillet flap 29(12.29%), split thickness skin graft 46 (19.49%), V-Y advancement flap 06(2.54%), transposition flap 18(07.63%), cross finger flap 16 (06.78%), reverse cross finger flap 02 (00.85%), first dorsal metacarpal artery (FDMA) flap 05 (02.12%), reverse FDMA flap 01 (00.42%), metacarpal artery perforator flap 08(3.39%), radial artery perforator flap 04(01.69%), posterior interosseous artery flap 05(2.12%), abdominal flap 11(04.46%) and flap division and insetting 27(11.44%). Outcome of surgery was satisfactory in 225(95.34%) and 11(04.46%) cases had complications (p value 0.453), which was not significant. So, it can be concluded that the outcome of various types of hand surgery procedures in tertiary hospital of northern Bangladesh during the post Covid period was satisfactory overall.