A Study on Hepatic Trauma: Single Centre Experience in Rajiv Gandhi Government General Hospital, Chennai

INTRODUCTION: Liver injuries are common in any high volume trauma center. Our knowledge in its management has improved in the past three decades. Recent advances and minimally invasive techniques play a vital role in the conservative approach. It is very difficult for a trauma surgeon to control massive bleeding occurring in the liver following trauma. The bleeding structure is very tough to find out, and the crucial period of time to save the trauma victim before the onset of hypothermia, acidosis, and coagulopathy—the markers of an irreversible physiologic insult. Usual techniques of elective hepato-biliary surgery like segmental resection do not apply in hostile environment where the timing of intervention is a major factor in saving the life of the patient. It is very clear that the management of hepatic trauma has been a formidable challenge to all surgeons. The evolvement of the management of hepatic trauma over the recent years is a reflection of the rapid understanding of the key parameters deciding the line of management in hepatic trauma. There were poor outcomes in patients where resection was done but future learning of the injured patient’s patho-physiology paved way for the concept of damage control that has been the key in modern trauma management. Meanwhile better learning of the outcome of various liver injuries in clinically stable patients has increased the conservative line of approach by using the modern imaging and minimally invasive procedures. AIMS AND OBJECTIVES: 1. To identify clinical and imaging parameters to decide upon the line of management in hepatic trauma. 2. To study the clinical course of patients managed conservatively. 3. To study the profile of various other associated injuries in liver trauma. MATERIALS AND METHODS: Sample Size: 35 cases. Study Design: Observational study (Prospective & Retrospective). Study Population: 35 cases. Study period: Oct 2015 to Sep 2016. Study Centre: Madras Medical College and Rajiv Gandhi Government General Hospital , Chennai. Subject Selection: Inclusion Criteria: All trauma victims sustaining blunt and penetrating trauma to the liver with or without associated injuries. Exclusion criteria: Abdominal trauma with isolated injury to the extra hepatic biliary tree or other visceral structures without liver trauma . ASSESSMENT OF PARAMETERS: All Patients who fit the inclusion criteria were observed and following data collected 1. Routine blood investigations, Hemoglobin, Hematocrit, Liver Function Test. All these were done serially. 2. USG Abdomen. 3. CECT Abdomen (i.v. contrast)/plain CT for all cases. 4. AAST grading system was the standard methodology to assess severity of liver injury. 5. Patients managed conservatively were followed up prospectively and till discharge. 6. Conclusions were drawn based on the above parameters. CONCLUSION: From this study it is clear that all hemodynamically stable patients can be subjected to conservative line of management irrespective of the grade of the injury. • Those managed conservatively must be subjected to serial monitoring. If there are findings of sepsis like biloma, infected necrosis, liver abscess at any point of time the first option of intervention will be minimally invasive procedures like image guided drainage. • If there are features of peritonitis then laparotomy must be considered without any delay. • Non operative management is employed for hemodynamically unstable patients. • The first step will always be a Pringles maneuver to identify the possible source of bleeding which can be from either the portal vein or hepatic artery and hemostasis can be achieved by topical hemostatic agents like gel foam etc. • If the patients hemodynamic status is in jeopardy then Perihepatic packing serves as the best operative intervention in reversing the patients hemodynamic status to normalcy

The Role of CNN-RNN Hybrid Models and Attention Mechanisms in EEG Signal Recognition for Correct Seizure Detection

Epileptic seizure detection is crucial for effective management and treatment of epilepsy. This research proposes a novel hybrid model combining Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and attention mechanisms to enhance the accuracy and reliability of seizure detection from EEG signals. Utilizing the Bonn dataset, our method encompasses advanced preprocessing techniques, including noise reduction and wavelet transforms, to capture multi-scale features from raw EEG data. CNNs extract spatial features, while Bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) capture temporal dynamics, with attention mechanisms further refining feature relevance.To ensure interpretability and trust, Explainable AI (XAI) techniques such as saliency maps, Grad-CAM, and attention maps are integrated. The hybrid model demonstrates superior performance, achieving 95.2% accuracy, 94.1% sensitivity, and 96.5% specificity, significantly outperforming existing methods.The research highlights the model\u27s robustness through comprehensive evaluation metrics and comparative analysis. Future directions involve testing with diverse datasets, exploring more XAI methods, and real-time implementation. This study advances seizure detection by improving accuracy, interpretability, and clinical applicability, paving the way for enhanced patient care in epilepsy management

A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

Strategies for modeling aging and age-related diseases

The ability to reprogram patient-derived-somatic cells to IPSCs (Induced Pluripotent Stem Cells) has led to a better understanding of aging and age-related diseases like Parkinson’s, and Alzheimer’s. The established patient-derived disease models mimic disease pathology and can be used to design drugs for aging and age-related diseases. However, the age and genetic mutations of the donor cells, the employed reprogramming, and the differentiation protocol might often pose challenges in establishing an appropriate disease model. In this review, we will focus on the various strategies for the successful reprogramming and differentiation of patient-derived cells to disease models for aging and age-related diseases, emphasizing the accuracy in the recapitulation of disease pathology and ways to overcome the limitations of its potential application in cell replacement therapy and drug development

Technical Design Report for the PANDA Solenoid and Dipole Spectrometer Magnets

This document is the Technical Design Report covering the two large spectrometer magnets of the PANDA detector set-up. It shows the conceptual design of the magnets and their anticipated performance. It precedes the tender and procurement of the magnets and, hence, is subject to possible modifications arising during this process.Comment: 10 pages, 14MB, accepted by FAIR STI in May 2009, editors: Inti Lehmann (chair), Andrea Bersani, Yuri Lobanov, Jost Luehning, Jerzy Smyrski, Technical Coordiantor: Lars Schmitt, Bernd Lewandowski (deputy), Spokespersons: Ulrich Wiedner, Paola Gianotti (deputy

Clinical Profile and Outcome Oclinical of Neonatal Sepsis in a Tertiary Care Centre, Trichy, Tamil Nadu

INTRODUCTION: Neonatal septicemia refers to a clinical syndrome characterized by systemic signs and symptoms due to generalized bacterial infection with a positive blood culture in the first four weeks of life. Bacterial infections are the commonest cause of morbidity and mortality during the neonatal period. Fulminant and fatal course of infection may result from complications such as shock, disseminated intravascular coagulation and multi-system organ failure, mandating early diagnosis of this life-threatening condition for a timely treatment and a favourabIe outcome. Sepsis is the commonest cause of mortality responsible for 30-50% of the 5 million total neonatal deaths each year. The reported incidence of neonatal sepsis varies from 7.1 to 38 per 1000 live births in Asia. National Neonatal Perinatal Database (NNPD, 2002- 2003) from India has reported an incidence varying from 0.1% to 4.5%1. Sepsis to be one of the commonest causes of neonatal mortality contributing to19% of all neonatal deaths. Gram negative organisms are found to be more frequently than Gram positive organisms as evidenced by many Indian studies2,3. The clinical presentation is often subtle or nonspecific and usually mimicked by several other disorder. AIMS AND OBJECTIVES: 1. Neonatal mortality remains high in our country in spite of the decline in the infant mortality rate. One third of the neonatal mortality is reported to be due to sepsis and related illness. 2. Hence this study was planned to understand the clinical parameters, role of investigations and the outcome in neonatal sepsis. 3. To analyze the causative organisms and their sensitivity pattern. 4. To identify the perinatal risk factors in the causation and outcome of neonatal sepsis. 5. To identify modifiable risk factors in order to develop appropriate strategies to address them. 6. To identify laboratory investigations for early diagnosis of sepsis. DISCUSSION: Sepsis is the commonest cause of neonatal morbidity and mortality. It is responsible for about 30-50% of total neonatal deaths.23 Sepsis related morbidity and mortality is largely either preventable or treatable with rational antimicrobial and supportive therapy. LBW is a strong risk factor for neonatal sepsis due to multiple reasons. Unsafe delivery or unclean delivery at inappropriate place is another important predisposing factor for sepsis. Earliest clinical features of neonatal sepsis are often subtle and non specific therefore a high index of suspicion is needed for early diagnosis specially so if risk factors are also present. In the present study majority of neonates presented with refusal to feeds (91.2%) lethargy (86.4%) tachyphea (75%) and fever (50.4%) which is comparable to various other study5. In this study documented hypothermia (12%) were apnea in (10.4%), convulsions (12.8%) which is correlated well with various study.24 Male neonates were reported to be affected more with sepsis as compared to females in some studies.8,25 This is in concordance with our study as well (p < 0.05) Bias for male sex, place of study, sample including other factors may be responsible for increased number of male cases in these studies. There was statistically significant difference (p < 0.05) in sepsis cases born in the study institution (inborn) as compared to those brought from outside (out born). In inborn category (62.4%) had sepsis as compared to (37.6%) in out born group. CONCLUSION: Blood culture was positive in 50(20%) neonates. About 84% of infections were caused by gram negative organisms, Klebsiella being the commonest organism causing sepsis. For most of the gram-negative organisms, Amikacin and third generation cephalosporins were effective. The common clinical presentations are lethargy (65.8%), refusal to suck (65.8%), tachypnea (98.3%) and fever (58.3%). When clinical signs like chest retractions, grunt and Abdominal distension, bulging fontanelle were present the likelihood of proven sepsis is high. The incidence of sepsis was shown to be higher among neonates with Perinatal risk factors such as risk factors, multiple vaginal examination during labour, lowbirthweight and preterm neonates. CRP has a high negative predictive value but low positive predictive value with sensitivity and specificity of 83% and 37.2% respectively. The specificity of combinations of hematological parameters were higher than that of CRP. The positive predictive value and specificity was high when two or more tests were combined together. Neonatal septicemia is still a leading cause of mortality and morbidity in developing countries like India. It is more common among males, low birth weight and preterm neonates. It is also found to be more common among the hospital inborn neonates with spontaneous vaginal delivery. Early onset septicemia is more common compared to late onset septicemia. Gramnegative organisms are the predominant causative agents in neonatal septicemia. Infections are a major threat to the premature and low birth weight neonates with multidrug resistant microorganisms emerging as a major problem. Blood culture is still the “Gold standard” for the diagnosis of septicemia in neonates and should be done in all cases of suspected septicemia. In view of the changing spectrum of the causative agents of neonatal septicemia and their antibiotic susceptibility patterns from time to time and from one hospital to another, a positive blood culture and the antibiotic susceptibility testing of the isolates are the best guide in choosing the appropriate antimicrobial therapy in treating neonatal septicemia

An automatic screening approach for obstructive sleep apnea from photoplethysmograph using machine learning techniques

Obstructive sleep apnea (OSA), a very common sleep disorder remains as an underdiagnosed root cause for several cardiovascular and cerebrovascular diseases. In this paper, we propose an efficient and accurate system that utilizes a single sensor for effective screening of OSA using machine learning algorithms. The automatic screening system involves a photoplethysmogram (PPG) signal, a novel algorithm to detect and remove the corrupted part of the signal, a feature extraction module to extract several features from the PPG waveform and a classifier module which helps in screening for OSA. The elemental idea behind this work is that there is a characteristic relationship between the shape of the PPG waveform and the oxygen desaturation in the apnea patients. The method as described was tested on 285 subjects, inclusive of both normal and apnea patients, and the results were obtained after 10-fold-cross validation of the different machine learning techniques viz., univariate regression, multivariate regression, support vector machine and random forest. The best results in screening OSA were obtained from random forest algorithm with the highest performance (Acc:98.0%, Sen:98.6%, Spec:99.3%) for all the combined features. The proposed work is an effective system for automatic screening of OSA from a single PPG sensor, thereby reducing the need for a very expensive and overnight polysomnography sleep study

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant 0645960)National Institutes of Health (U.S.) (grant P01 NS055923)Pennsylvania State University. Center for Eukaryotic Gene Regulatio

NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Background: Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them. Results: Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs). Conclusions: The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed