Search

Aldehydes, being an integral part of carbon metabolism, energy generation, and signalling pathways, are ingrained in plant physiology. Land plants have developed intricate metabolic pathways which involve production of reactive aldehydes and its detoxification to survive harsh terrestrial environments. Here, we show that physiologically produced aldehydes, i.e., formaldehyde and methylglyoxal in addition to acetaldehyde, generate adducts with aminoacyl-tRNAs, a substrate for protein synthesis. Plants are unique in possessing two distinct chiral proofreading systems, D-aminoacyl-tRNA deacylase1 (DTD1) and DTD2, of bacterial and archaeal origins, respectively. Extensive biochemical analysis revealed that only archaeal DTD2 can remove the stable D-aminoacyl adducts on tRNA thereby shielding archaea and plants from these system-generated aldehydes. Using Arabidopsis as a model system, we have shown that the loss of DTD2 gene renders plants susceptible to these toxic aldehydes as they generate stable alkyl modification on D-aminoacyl-tRNAs, which are recycled only by DTD2. Bioinformatic analysis identifies the expansion of aldehyde metabolising repertoire in land plant ancestors which strongly correlates with the recruitment of archaeal DTD2. Finally, we demonstrate that the overexpression of DTD2 offers better protection against aldehydes than in wild type Arabidopsis highlighting its role as a multi-aldehyde detoxifier that can be explored as a transgenic crop development strategy.

Lumbosacral interbody fusion is a mainstay of surgical treatment for degenerative spinal pathologies causing chronic pain and functional impairment. However, the optimal technique for this procedure remains controversial. Well-established open approaches, including anterior lumbar interbody fusion (ALIF), posterior lumbar interbody fusion (PLIF), and transforaminal lumbar interbody fusion (TLIF), have historically been the standard of practice. A recent paradigm shift in spinal surgery has led to the investigation of minimally invasive approaches to mitigate tissue damage without compromising outcomes. This extensive review aims to examine current clinical and biomechanical evidence on the paracoccygeal transsacral approach to an axial lumbosacral interbody fusion. Since this technique was first described in 2004, accumulating evidence suggests it results in high fusion rates, consistent improvements in pain and function, reduced perioperative morbidity, and low rates of complication. Although early clinical outcomes have been promising, there is a paucity of comparative data investigating outcomes of the paracoccygeal transsacral approach to traditional alternatives and other minimally invasive techniques. Here, we summarize current evidence and discuss pertinent topics for the spinal surgeon considering this novel approach, including indications, advantages, relevant anatomy, contraindications, and technical considerations.

Retro-odontoid pseudotumor formation consists of an abnormal growth of granulation tissue typically posterior to the odontoid process, resulting as a manifestation of atlantoaxial instability. This instability can occur as a result of conditions ranging from severe mechanical trauma to metabolic disease or autoimmune conditions such as rheumatoid arthritis. A pseudotumor may impinge on the spinal nerves or even the spinal cord and brainstem, manifesting symptoms from severe neck pain to cervicomedullary compression or myelopathy, and in some cases even sudden death. The objective of this review is to consolidate the findings in published case reports and relevant prior literature reviews regarding the formation of retro-odontoid pseudotumor. We address the pathophysiology involved in acquired and congenital pseudotumor formation, including those associated with rheumatoid arthritis (panni). Additionally, we discuss past and current operative techniques designed to curtail and ultimately regress a retro-odontoid pseudotumor and pannus. Surgical techniques that are addressed include ventral decompression (both transoral and transnasal), dorsal decompression, and indications for posterior instrumentation in pannus formation, particularly in cases that may be sufficiently treated in lieu of an anterior approach. Finally, we will examine the role of external orthoses as both a method of conservative treatment as well as a potential adjunct to the aforementioned surgical procedures.

Abstract Identification of writers from images of handwriting is an interesting research problem in the handwriting recognition community. Application of image analysis and machine learning techniques to this problem allows development of computerised solutions which can facilitate forensic experts in reducing the search space against a questioned document. This article investigates the effectiveness of textural measures in characterising the writer of a handwritten document. A novel descriptor by crossing the local binary patterns (LBP) with different configurations that allows capturing the local textural information in handwriting using a column histogram is introduced. The representation is enriched with the oriented Basic Image Features (oBIFs) column histogram. Support vector machine (SVM) is employed as the classifier, and the experimental study is carried out on five different datasets in single as well as multi‐script evaluation scenarios. Multi‐script evaluations allow evaluating the hypothesis that writers share common characteristics across multiple scripts and the reported results validate the effectiveness of textural measures in capturing this script‐independent, writer‐specific information.

Abstract Non-invasive photoplethysmography (PPG) technology was developed to track heart rate during motion. Automated analysis of PPG has made it useful in both clinical and non-clinical applications. However, PPG-based heart rate tracking is a challenging problem due to motion artifacts (MAs) which are main contributors towards signal degradation as they mask the location of heart rate peak in the spectra. A practical analysis system must have good performance in MA removal as well as in tracking. In this article, we have presented state-of-art techniques in both areas of the automated analysis, i.e., MA removal and heart rate tracking, and have concluded that adaptive filtering and multi-resolution decomposition techniques are better for MA removal and machine learning-based approaches are future perspective of heart rate tracking. Hence, future systems will be composed of machine learning-based trackers fed with either empirically decomposed signal or from output of adaptive filter.

Abstract Textual content appearing in videos represents an interesting index for semantic retrieval of videos (from archives), generation of alerts (live streams), as well as high level applications like opinion mining and content summarization. The key components of such systems require detection and recognition of textual content which also make the subject of our study. This paper presents a comprehensive framework for detection and recognition of textual content in video frames. More specifically, we target cursive scripts taking Urdu text as a case study. Detection of textual regions in video frames is carried out by fine-tuning deep neural networks based object detectors for the specific case of text detection. Script of the detected textual content is identified using convoluational neural networks (CNNs), while for recognition, we propose a UrduNet, a combination of CNNs and long short- term memory (LSTM) networks. A benchmark dataset containing cursive text with more than 13,000 video frame is also developed. A comprehensive series of experiments is carried out reporting an F-measure of 88.3% for detection while a recognition rate of 87%.

Background and Objective: Assessment of learning plays a vital role in curriculum allowing faculty to evaluate the achievement of student and educational process. Quality assurance of the assessments is done to assess the quality of teaching and learning. A study is therefore conducted to find the discriminant validity and reliability of scores of Multiple Choices and Short Answer Questions.Methods: A correlation study was conducted on 272 second year MBBS students of Fatima Memorial College of Medicine and Dentistry, Lahore from 2016 – 2017. Students were assessed in end of year examination with multiple choice questions (MCQs) and short essay questions and (SEQs) in the subjects of Physiology and Biochemistry. A total of 149 second-year MBBS students took thePhysiologyand143 studentstook the end of year Biochemistry examination with 50% minimum passing level. The mean and standard deviation of the scores were calculated and the scores of MCQs and SEQs were correlated by applying Pearson’s correlation. Reliability was determined by Cronbach’s alpha. Discriminant validity of scores (MCQS and SEQS) was analyzed by Pearson’s correlation.Results: Students scored significantly higher in MCQsthan SEQsin end of year examination of Biochemistry and Physiology. Positive significant correlation of scores (MCQs and SEQs) was obtained in Biochemistry while correlation was positive but non-significant in Physiology. The reliability assessed by Cronbach’s alpha was moderate in Biochemistry and Physiology assessments. Discriminant validity was determined in both subjects by determining the correlation between the scores of the MCQs and SEQs, constructed according to the same module.Conclusion: The internal assessment of students based on end of year examinations in the subjects of Physiology and Biochemistry scored moderate in terms of reliability and discriminant validity was found between scores of MCQs and SEQs in each module.

Kikuchi-Fujimoto disease is a self-limited disease of unknown etiology that is clinically defined by fevers accompanied by tender posterior cervical lymphadenopathy. It often presents acutely or sub-acutely, and due to its non-specific features, the differential diagnosis is broad and includes infectious, autoimmune, and malignant causes. Although cases of extra-cervical disease are not uncommon, involvement of retroperitoneal lymph nodes has only rarely been reported. Here, we describe a patient with Kikuchi-Fujimoto disease who presented with fever of unknown origin, abdominal pain, and enlarged hypermetabolic retroperitoneal lymph nodes.

Background Prince George's County Maryland, historically a medically underserved region, has a population of 909 327 and a high incidence of cardiometabolic syndrome and hypertension. Application of level I evidence practices in such areas requires the availability of highly advanced cardiovascular interventions. Donabedian principles of quality of care were applied to a failing cardiac surgery program. We hypothesized that a multidisciplinary application of this model supported by partnership with a university hospital system could result in improved quality care outcomes. Methods and Results A 6‐month assessment and planning process commenced in July 2014. Preoperative, intraoperative, and postoperative protocols were developed before program restart. Staff education and training was conducted via team simulation and rehearsal sessions. A total of 425 patients underwent cardiac surgical procedures. Quality tracking of key performance measures was conducted, and 323 isolated coronary artery bypass grafting procedures were performed from July 2014 to December 2019. Key risk factors in our patient demographic were higher than the Society of Thoracic Surgeons national mean. Risk‐adjusted outcome data yielded a mortality rate of 0.3% versus 2.2% nationally. The overall major complication rate was lower than expected at 7.1% compared with 11.5% nationally. Readmission rate was less than the Society of Thoracic Surgeons mean for isolated coronary artery bypass grafting (4.0% versus 10.1%, P

This paper presents an effective technique for segmentation and recognition of electronic components from hand-drawn circuit diagrams. Segmentation is carried out by using a series of morphological operations on the binarized images of circuits and discriminating between three categories of components (closed shape, components with connected lines, disconnected components). Each segmented component is characterized by computing the Histogram of Oriented Gradients (HOG) descriptor while classification is carried out using Support Vector Machine (SVM). The system is evaluated on 100 hand-drawn circuit diagrams with a total of 350 components. A segmentation accuracy of 87.7% while a classification rate of 92% is realized demonstrating the effectiveness of the proposed technique.

Abstract Phonocardiogram (PCG) signal represents recording of sounds and murmurs resulting from heart auscultation. Analysis of these PCG signals is critical in diagnosis of different heart diseases. Over the years, a variety of methods have been proposed for automatic analysis of PCG signals in time, frequency, and time-frequency domains. This paper presents a comprehensive survey of different methods proposed for automatic analysis of PCG signals with the objective to evaluate the current state-of-the-art and to determine the potential domains of effective analysis. An important aspect of our contribution is that the review is carried out as a function of domains of analysis rather than simply discussing different methods. Our method further splits analysis into pre-processing, localization, and classification, and details are presented in terms of techniques and classifiers used during these phases. Finally, results are summarized for normal heart beat, noisy heart beat, and different pathologies using metrices like accuracy and detection rate. In addition to time and frequency domain, time-frequency based methods including wavelet, empirical mode decomposition (EMD) and time-frequency representation (TFR) are selected for detailed analysis. The review concludes that the time-frequency representations like EMD and wavelets represent areas of exploration in future along with perspective of using different time-frequency techniques together.

Abstract This paper presents a segmentation-free optical character recognition system for printed Urdu Nastaliq font using ligatures as units of recognition. The proposed technique relies on statistical features and employs Hidden Markov Models for classification. A total of 1525 unique high-frequency Urdu ligatures from the standard Urdu Printed Text Images (UPTI) database are considered in our study. Ligatures extracted from text lines are first split into primary (main body) and secondary (dots and diacritics) ligatures and multiple instances of the same ligature are grouped into clusters using a sequential clustering algorithm. Hidden Markov Models are trained separately for each ligature using the examples in the respective cluster by sliding right-to-left the overlapped windows and extracting a set of statistical features. Given the query text, the primary and secondary ligatures are separately recognized and later associated together using a set of heuristics to recognize the complete ligature. The system evaluated on the standard UPTI Urdu database reported a ligature recognition rate of 92% on more than 6000 query ligatures.

An Extramedullary Plasmacytoma (EMP) is characterized by a neoplastic proliferation of clonal plasma cells outside the medullary cavity. EMPs are a rare occurrence compared to other malignant plasma cell disorders and account for approximately 3-5% of plasma-cell neoplasms. Although most cases of EMP are not immediately life threatening at diagnosis, EMPs can progress to Multiple Myeloma (MM) and thus, warrant monitoring. Currently, there are no standard guidelines for when and how to monitor patients who are diagnosed with or treated for a solitary plasmacytoma. We present a case of solitary EMP who was treated adequately and definitively but developed a distinct, non-contiguous subsequent solitary EMP and was only discovered due to surveillance 18F-Fludeoxyglucose Positron Emission Tomography (18F-FDG) (PET) scan. Uniform surveillance guidelines should be developed and the potential benefits of PET and other imaging techniques as well as their cost should be considered.

Obesity has been associated with structural and functional changes in the gut microbiota. The abundance in, and diversity of, certain bacteria may favor energy harvest and metabolic pathways leading to obesity. Therefore, gut microbiota has become a potential target that can be manipulated to obtain optimal health. Probiotics have been shown to influence the composition of the gut microbiota, improve gut integrity, and restore the microbial shifts characteristic of obesity. Based on physical and biochemical parameters, metabolic and inflammatory markers, and alterations in gut microbe diversity, animal studies revealed beneficial results in obese models whereas the results in humans are sparse and inconsistent. Thus, the purpose of this review is to present evidence from animal studies and human clinical trials demonstrating the effects of various probiotic strains and their potential efficacy in improving obesity and associated metabolic dysfunctions. Furthermore, the review discusses current gaps in our understanding of how probiotics modulate gut microflora to protect against obesity. Finally, we propose future studies and methodological approaches that may shed light on the challenges facing the scientific community in deciphering the host⁻bacteria interaction in obesity.

Meiosis produces haploid cells essential for sexual reproduction. In yeast, entry into meiosis activates transcription factors which trigger a transcriptional cascade that results in sequential co-expression of early, middle and late meiotic genes. However, these factors are not conserved, and the factors and regulatory mechanisms that ensure proper meiotic gene expression in multicellular eukaryotes are poorly understood. Here, we report that DUET/MMD1, a PHD finger protein essential for Arabidopsis male meiosis, functions as a transcriptional regulator in plant meiosis. We find that DUET-PHD binds H3K4me2 in vitro, and show that this interaction is critical for function during meiosis. We also show that DUET is required for proper microtubule organization during meiosis II, independently of its function in meiosis I. Remarkably, DUET protein shows stage-specific expression, confined to diplotene. We identify two genes TDM1 and JAS with critical functions in cell cycle transitions and spindle organization in male meiosis, as DUET targets, with TDM1 being a direct target. Thus, DUET is required to regulate microtubule organization and cell cycle transitions during male meiosis, and functions as a direct transcription activator of the meiotic gene TDM1. Expression profiling showed reduced expression of a subset comprising about 12% of a known set of meiosis preferred genes in the duet mutant. Our results reveal the action of DUET as a transcriptional regulator during male meiosis in plants, and suggest that transcription of meiotic genes is under stagewise control in plants as in yeast.

In this paper we introduce the numerical tools that have been developed in the context of the Graphem project, in order to automate or leverage several steps in the study of medieval writing samples. We first describe various kinds of features that have been extracted from the samples, and then present two graphical tools to compare writing samples according to the features that have been extracted.