Accuracy and Systematic Biases of Heart Rate Measurements by Consumer-Grade Fitness Trackers in Postoperative Patients: Prospective Clinical Trial.

BACKGROUND: Over the recent years, technological advances of wrist-worn fitness trackers heralded a new era in the continuous monitoring of vital signs. So far, these devices have primarily been used for sports. OBJECTIVE: However, for using these technologies in health care, further validations of the measurement accuracy in hospitalized patients are essential but lacking to date. METHODS: We conducted a prospective validation study with 201 patients after moderate to major surgery in a controlled setting to benchmark the accuracy of heart rate measurements in 4 consumer-grade fitness trackers (Apple Watch 7, Garmin Fenix 6 Pro, Withings ScanWatch, and Fitbit Sense) against the clinical gold standard (electrocardiography). RESULTS: All devices exhibited high correlation (r≥0.95; P<.001) and concordance (rc≥0.94) coefficients, with a relative error as low as mean absolute percentage error <5% based on 1630 valid measurements. We identified confounders significantly biasing the measurement accuracy, although not at clinically relevant levels (mean absolute error<5 beats per minute). CONCLUSIONS: Consumer-grade fitness trackers appear promising in hospitalized patients for monitoring heart rate. TRIAL REGISTRATION: ClinicalTrials.gov NCT05418881; https://www.clinicaltrials.gov/ct2/show/NCT05418881.

Characterization of HPV integration, viral gene expression and E6E7 alternative transcripts by RNA-Seq: A descriptive study in invasive cervical cancer.

Scarce data are available on the expression of papillomavirus genome and the frequency of alternatively spliced E6E7 mRNAs in invasive cervical cancer. We carried out a comprehensive characterization of HPV expression by RNA-Seq analysis in 22 invasive cervical cancer with HPV16 or HPV18, characterizing the presence of integrated/episomal viral DNA, the integration sites in human genome and the proportion of alternative splicing products of E6 and E7 genes. The expression patterns suggested the presence of episomal and/or integrated viral DNA, with integration detected in most tumors, frequently occurring within human genes in HPV18+ and in intergenic regions in HPV16+ tumors. Alternative splicing of E6E7 transcripts showed E6*I as the most frequent isoform for both viral types, followed by E6*II and E6/E7 (unspliced) transcripts in HPV16+, and by E6/E7 in HPV18+ tumors. Previously described E6*VI and E6*V transcript isoforms for HPV16, and E6*X for HPV18, were rare or not detected.

An automated method for detecting alternatively spliced protein domains.

Motivation: Alternative splicing (AS) has been demonstrated to play a role in shaping eukaryotic gene diversity at the transcriptional level. However, the impact of AS on the proteome is still controversial. Studies that seek to explore the effect of AS at the proteomic level are hampered by technical difficulties in the cumbersome process of casting forth and back between genome, transcriptome and proteome space coordinates, and the naïve prediction of protein domains in the presence of AS suffers many redundant sequence scans that emerge from constitutively spliced regions that are shared between alternative products of a gene. Results: We developed the AstaFunk pipeline that computes for every generic transcriptome all domains that are altered by AS events in a systematic and efficient manner. In a nutshell, our method employs Viterbi dynamic programming, which guarantees to find all score-optimal hits of the domains under consideration, while complementary optimizations at different levels avoid redundant and other irrelevant computations. We evaluate AstaFunk qualitatively and quantitatively using RNAseq in well-studied genes with AS, and on large-scale employing entire transcriptomes. Our study confirms complementary reports that the effect of most AS events on the proteome seems to be rather limited, but our results also pinpoint several cases where AS could have a major impact on the function of a protein domain. Availability and implementation: The JAVA implementation of AstaFunk is available as an open source project on http://astafunk.sammeth.net. Supplementary information: Supplementary data are available at Bioinformatics online.

Transcriptome and genome sequencing uncovers functional variation in humans.

Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of messenger RNA and microRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project--the first uniformly processed high-throughput RNA-sequencing data from multiple human populations with high-quality genome sequences. We discover extremely widespread genetic variation affecting the regulation of most genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on the cellular mechanisms of regulatory and loss-of-function variation, and allows us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome.

Correction: Gene Expansion Shapes Genome Architecture in the Human Pathogen Lichtheimia corymbifera: An Evolutionary Genomics Analysis in the Ancient Terrestrial Mucorales (Mucoromycotina).

[This corrects the article DOI: 10.1371/journal.pgen.1004496.].

Gene expansion shapes genome architecture in the human pathogen Lichtheimia corymbifera: an evolutionary genomics analysis in the ancient terrestrial mucorales (Mucoromycotina).

Lichtheimia species are the second most important cause of mucormycosis in Europe. To provide broader insights into the molecular basis of the pathogenicity-associated traits of the basal Mucorales, we report the full genome sequence of L. corymbifera and compared it to the genome of Rhizopus oryzae, the most common cause of mucormycosis worldwide. The genome assembly encompasses 33.6 MB and 12,379 protein-coding genes. This study reveals four major differences of the L. corymbifera genome to R. oryzae: (i) the presence of an highly elevated number of gene duplications which are unlike R. oryzae not due to whole genome duplication (WGD), (ii) despite the relatively high incidence of introns, alternative splicing (AS) is not frequently observed for the generation of paralogs and in response to stress, (iii) the content of repetitive elements is strikingly low (<5%), (iv) L. corymbifera is typically haploid. Novel virulence factors were identified which may be involved in the regulation of the adaptation to iron-limitation, e.g. LCor01340.1 encoding a putative siderophore transporter and LCor00410.1 involved in the siderophore metabolism. Genes encoding the transcription factors LCor08192.1 and LCor01236.1, which are similar to GATA type regulators and to calcineurin regulated CRZ1, respectively, indicating an involvement of the calcineurin pathway in the adaption to iron limitation. Genes encoding MADS-box transcription factors are elevated up to 11 copies compared to the 1-4 copies usually found in other fungi. More findings are: (i) lower content of tRNAs, but unique codons in L. corymbifera, (ii) Over 25% of the proteins are apparently specific for L. corymbifera. (iii) L. corymbifera contains only 2/3 of the proteases (known to be essential virulence factors) in comparison to R. oryzae. On the other hand, the number of secreted proteases, however, is roughly twice as high as in R. oryzae.

Nova1 is a master regulator of alternative splicing in pancreatic beta cells.

Alternative splicing (AS) is a fundamental mechanism for the regulation of gene expression. It affects more than 90% of human genes but its role in the regulation of pancreatic beta cells, the producers of insulin, remains unknown. Our recently published data indicated that the 'neuron-specific' Nova1 splicing factor is expressed in pancreatic beta cells. We have presently coupled specific knockdown (KD) of Nova1 with RNA-sequencing to determine all splice variants and downstream pathways regulated by this protein in beta cells. Nova1 KD altered the splicing of nearly 5000 transcripts. Pathway analysis indicated that these genes are involved in exocytosis, apoptosis, insulin receptor signaling, splicing and transcription. In line with these findings, Nova1 silencing inhibited insulin secretion and induced apoptosis basally and after cytokine treatment in rodent and human beta cells. These observations identify a novel layer of regulation of beta cell function, namely AS controlled by key splicing regulators such as Nova1.

Estimation of alternative splicing variability in human populations.

DNA arrays have been widely used to perform transcriptome-wide analysis of gene expression, and many methods have been developed to measure gene expression variability and to compare gene expression between conditions. Because RNA-seq is also becoming increasingly popular for transcriptome characterization, the possibility exists for further quantification of individual alternative transcript isoforms, and therefore for estimating the relative ratios of alternative splice forms within a given gene. Changes in splicing ratios, even without changes in overall gene expression, may have important phenotypic effects. Here we have developed statistical methodology to measure variability in splicing ratios within conditions, to compare it between conditions, and to identify genes with condition-specific splicing ratios. Furthermore, we have developed methodology to deconvolute the relative contribution of variability in gene expression versus variability in splicing ratios to the overall variability of transcript abundances. As a proof of concept, we have applied this methodology to estimates of transcript abundances obtained from RNA-seq experiments in lymphoblastoid cells from Caucasian and Yoruban individuals. We have found that protein-coding genes exhibit low splicing variability within populations, with many genes exhibiting constant ratios across individuals. When comparing these two populations, we have found that up to 10% of the studied protein-coding genes exhibit population-specific splicing ratios. We estimate that ~60% of the total variability observed in the abundance of transcript isoforms can be explained by variability in transcription. A large fraction of the remaining variability can likely result from variability in splicing. Finally, we also detected that variability in splicing is uncommon without variability in transcription.

The GEM mapper: fast, accurate and versatile alignment by filtration.

Because of ever-increasing throughput requirements of sequencing data, most existing short-read aligners have been designed to focus on speed at the expense of accuracy. The Genome Multitool (GEM) mapper can leverage string matching by filtration to search the alignment space more efficiently, simultaneously delivering precision (performing fully tunable exhaustive searches that return all existing matches, including gapped ones) and speed (being several times faster than comparable state-of-the-art tools).

The human pancreatic islet transcriptome: expression of candidate genes for type 1 diabetes and the impact of pro-inflammatory cytokines.

Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic beta cells are killed by infiltrating immune cells and by cytokines released by these cells. Signaling events occurring in the pancreatic beta cells are decisive for their survival or death in diabetes. We have used RNA sequencing (RNA-seq) to identify transcripts, including splice variants, expressed in human islets of Langerhans under control conditions or following exposure to the pro-inflammatory cytokines interleukin-1ß (IL-1ß) and interferon-γ (IFN-γ). Based on this unique dataset, we examined whether putative candidate genes for T1D, previously identified by GWAS, are expressed in human islets. A total of 29,776 transcripts were identified as expressed in human islets. Expression of around 20% of these transcripts was modified by pro-inflammatory cytokines, including apoptosis- and inflammation-related genes. Chemokines were among the transcripts most modified by cytokines, a finding confirmed at the protein level by ELISA. Interestingly, 35% of the genes expressed in human islets undergo alternative splicing as annotated in RefSeq, and cytokines caused substantial changes in spliced transcripts. Nova1, previously considered a brain-specific regulator of mRNA splicing, is expressed in islets and its knockdown modified splicing. 25/41 of the candidate genes for T1D are expressed in islets, and cytokines modified expression of several of these transcripts. The present study doubles the number of known genes expressed in human islets and shows that cytokines modify alternative splicing in human islet cells. Importantly, it indicates that more than half of the known T1D candidate genes are expressed in human islets. This, and the production of a large number of chemokines and cytokines by cytokine-exposed islets, reinforces the concept of a dialog between pancreatic islets and the immune system in T1D. This dialog is modulated by candidate genes for the disease at both the immune system and beta cell level.

Modelling and simulating generic RNA-Seq experiments with the flux simulator.

High-throughput sequencing of cDNA libraries constructed from cellular RNA complements (RNA-Seq) naturally provides a digital quantitative measurement for every expressed RNA molecule. Nature, impact and mutual interference of biases in different experimental setups are, however, still poorly understood-mostly due to the lack of data from intermediate protocol steps. We analysed multiple RNA-Seq experiments, involving different sample preparation protocols and sequencing platforms: we broke them down into their common--and currently indispensable--technical components (reverse transcription, fragmentation, adapter ligation, PCR amplification, gel segregation and sequencing), investigating how such different steps influence abundance and distribution of the sequenced reads. For each of those steps, we developed universally applicable models, which can be parameterised by empirical attributes of any experimental protocol. Our models are implemented in a computer simulation pipeline called the Flux Simulator, and we show that read distributions generated by different combinations of these models reproduce well corresponding evidence obtained from the corresponding experimental setups. We further demonstrate that our in silico RNA-Seq provides insights about hidden precursors that determine the final configuration of reads along gene bodies; enhancing or compensatory effects that explain apparently controversial observations can be observed. Moreover, our simulations identify hitherto unreported sources of systematic bias from RNA hydrolysis, a fragmentation technique currently employed by most RNA-Seq protocols.

Comparative Methods for Demystifying Spatial Transcriptomics.

Spatial Transcriptomics (ST), coined as the term for parallel RNA-Seq on cell populations ordered spatially on a histological tissue section, has recently become increasingly popular, especially in experiments where microfluidics-based single-cell sequencing fails, such as assays on neurons. ST platforms, like the 10x Visium technology investigated herein, therefore produce in a single experiment simultaneously thousands of RNA readouts, captured by an array of micrometer scale spots under the histological section. Therefore, a central challenge of analyzing ST experiments consists of analyzing the gene expression morphology of all spots to delineate clusters of similar cell mixtures, which are then compared to each other to identify up- or down-regulated marker genes. Moreover, another level of complexity in ST experiments, compared to traditional RNA-Seq, is imposed by staining the tissue section with protein markers of cells or cell components to identify spots providing relevant information afterward. The corresponding microscopy images need to be analyzed in addition to the RNA-Seq read mappings on the reference genome and transcriptome sequences. Focusing on the software suite provided by the Visium platform manufacturer, we break down the ST analysis pipeline into its four essential steps-the image analysis, the read alignment, the gene quantification, and the spot clustering-and compare results obtained when using reads from different subsets of spots and/or when employing alternative genome or transcriptome references. Our comparative analyses demonstrate the impact of spot selection and the choice of genome/transcriptome references on the analysis results when employing the manufacturer's pipeline.

Reliability of continuous vital sign monitoring in post-operative patients employing consumer-grade fitness trackers: A randomised pilot trial.

Introduction: Fitness trackers can provide continuous monitoring of vital signs and thus have the potential to become a complementary, mobile and effective tool for early detection of patient deterioration and post-operative complications. Methods: To evaluate potential implementations in acute care setting, we included 36 patients after moderate to major surgery in a recent randomised pilot trial to compare the performance of vital sign monitoring by three different fitness trackers (Apple Watch 7, Garmin Fenix 6pro and Withings ScanWatch) with established standard clinical monitors in post-anaesthesia care units and monitoring wards. Results: During a cumulative period of 56 days, a total of 53,197 heart rate (HR) measurements, as well as 12,219 measurements of the peripheral blood oxygen saturation (SpO2) and 28,954 respiratory rate (RR) measurements were collected by fitness trackers. Under real-world conditions, HR monitoring was accurate and reliable across all benchmarked devices (r = [0.95;0.98], p < 0.001; Bias = [-0.74 bpm;-0.01 bpm]; MAPE∼2%). However, the performance of SpO2 (r = [0.21;0.68]; p < 0.001; Bias = [-0.46%;-2.29%]; root-mean-square error = [2.82%;4.1%]) monitoring was substantially inferior. RR measurements could not be obtained for two of the devices, therefore exclusively the accuracy of the Garmin tracker could be evaluated (r = 0.28, p < 0.001; Bias = -1.46/min). Moreover, the time resolution of the vital sign measurements highly depends on the tracking device, ranging from 0.7 to 117.94 data points per hour. Conclusion: According to the results of the present study, tracker devices are generally reliable and accurate for HR monitoring, whereas SpO2 and RR measurements should be interpreted carefully, considering the clinical context of the respective patients.

Evaluating blood oxygen saturation measurements by popular fitness trackers in postoperative patients: A prospective clinical trial.

Blood oxygen saturation is an important clinical parameter, especially in postoperative hospitalized patients, monitored in clinical practice by arterial blood gas (ABG) and/or pulse oximetry that both are not suitable for a long-term continuous monitoring of patients during the entire hospital stay, or beyond. Technological advances developed recently for consumer-grade fitness trackers could-at least in theory-help to fill in this gap, but benchmarks on the applicability and accuracy of these technologies in hospitalized patients are currently lacking. We therefore conducted at the postanaesthesia care unit under controlled settings a prospective clinical trial with 201 patients, comparing in total >1,000 oxygen blood saturation measurements by fitness trackers of three brands with the ABG gold standard and with pulse oximetry. Our results suggest that, despite of an overall still tolerable measuring accuracy, comparatively high dropout rates severely limit the possibilities of employing fitness trackers, particularly during the immediate postoperative period of hospitalized patients.

Bioinformatics approaches for genomics and post genomics applications of next-generation sequencing.

Technical advances such as the development of molecular cloning, Sanger sequencing, PCR and oligonucleotide microarrays are key to our current capacity to sequence, annotate and study complete organismal genomes. Recent years have seen the development of a variety of so-called 'next-generation' sequencing platforms, with several others anticipated to become available shortly. The previously unimaginable scale and economy of these methods, coupled with their enthusiastic uptake by the scientific community and the potential for further improvements in accuracy and read length, suggest that these technologies are destined to make a huge and ongoing impact upon genomic and post-genomic biology. However, like the analysis of microarray data and the assembly and annotation of complete genome sequences from conventional sequencing data, the management and analysis of next-generation sequencing data requires (and indeed has already driven) the development of informatics tools able to assemble, map, and interpret huge quantities of relatively or extremely short nucleotide sequence data. Here we provide a broad overview of bioinformatics approaches that have been introduced for several genomics and functional genomics applications of next-generation sequencing.

The Use of Non-Invasive Continuous Blood Pressure Measuring (ClearSight®) during Central Neuraxial Anaesthesia for Caesarean Section-A Retrospective Validation Study.

The close monitoring of blood pressure during a caesarean section performed under central neuraxial anaesthesia should be the standard of safe anaesthesia. As classical oscillometric and invasive blood pressure measuring have intrinsic disadvantages, we investigated a novel, non-invasive technique for continuous blood pressure measuring. Methods: In this monocentric, retrospective data analysis, the reliability of continuous non-invasive blood pressure measuring using ClearSight® (Edwards Lifesciences Corporation) is validated in 31 women undergoing central neuraxial anaesthesia for caesarean section. In addition, patients and professionals evaluated ClearSight® through questioning. Results: 139 measurements from 11 patients were included in the final analysis. Employing Bland-Altman analyses, we identified a bias of -10.8 mmHg for systolic, of -0.45 mmHg for diastolic and of +0.68 mmHg for mean arterial blood pressure measurements. Pooling all paired measurements resulted in a Pearson correlation coefficient of 0.7 for systolic, of 0.67 for diastolic and of 0.75 for mean arterial blood pressure. Compensating the interindividual differences in linear regressions of the paired measurements provided improved correlation coefficients of 0.73 for systolic, of 0.9 for diastolic and of 0.89 for mean arterial blood pressure measurements. Discussion: Diastolic and mean arterial blood pressure are within an acceptable range of deviation from the reference method, according to the Association for the Advancement of Medical Instrumentation (AAMI) in the patient collective under study. Both patients and professionals prefer ClearSight® to oscillometric blood pressure measurement in regard of comfort and handling.

Analysis of ovarian transcriptomes reveals thousands of novel genes in the insect vector Rhodnius prolixus.

Rhodnius prolixus is a Triatominae insect species and a primary vector of Chagas disease. The genome of R. prolixus has been recently sequenced and partially assembled, but few transcriptome analyses have been performed to date. In this study, we describe the stage-specific transcriptomes obtained from previtellogenic stages of oogenesis and from mature eggs. By analyzing ~ 228 million paired-end RNA-Seq reads, we significantly improved the current genome annotations for 9206 genes. We provide extended 5' and 3' UTRs, complete Open Reading Frames, and alternative transcript variants. Strikingly, using a combination of genome-guided and de novo transcriptome assembly we found more than two thousand novel genes, thus increasing the number of genes in R. prolixus from 15,738 to 17,864. We used the improved transcriptome to investigate stage-specific gene expression profiles during R. prolixus oogenesis. Our data reveal that 11,127 genes are expressed in the early previtellogenic stage of oogenesis and their transcripts are deposited in the developing egg including key factors regulating germline development, genome integrity, and the maternal-zygotic transition. In addition, GO term analyses show that transcripts encoding components of the steroid hormone receptor pathway, cytoskeleton, and intracellular signaling are abundant in the mature eggs, where they likely control early embryonic development upon fertilization. Our results significantly improve the R. prolixus genome and transcriptome and provide novel insight into oogenesis and early embryogenesis in this medically relevant insect.

A general definition and nomenclature for alternative splicing events.

Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells is one of the most challenging tasks in the postgenomic era. In this regard, alternative splicing (AS) is a key phenomenon contributing to the production of different mature transcripts from the same primary RNA sequence. As a plethora of different transcript forms is available in databases, a first step to uncover the biology that drives AS is to identify the different types of reflected splicing variation. In this work, we present a general definition of the AS event along with a notation system that involves the relative positions of the splice sites. This nomenclature univocally and dynamically assigns a specific "AS code" to every possible pattern of splicing variation. On the basis of this definition and the corresponding codes, we have developed a computational tool (AStalavista) that automatically characterizes the complete landscape of AS events in a given transcript annotation of a genome, thus providing a platform to investigate the transcriptome diversity across genes, chromosomes, and species. Our analysis reveals that a substantial part--in human more than a quarter-of the observed splicing variations are ignored in common classification pipelines. We have used AStalavista to investigate and to compare the AS landscape of different reference annotation sets in human and in other metazoan species and found that proportions of AS events change substantially depending on the annotation protocol, species-specific attributes, and coding constraints acting on the transcripts. The AStalavista system therefore provides a general framework to conduct specific studies investigating the occurrence, impact, and regulation of AS.

ASTALAVISTA: dynamic and flexible analysis of alternative splicing events in custom gene datasets.

In the process of establishing more and more complete annotations of eukaryotic genomes, a constantly growing number of alternative splicing (AS) events has been reported over the last decade. Consequently, the increasing transcript coverage also revealed the real complexity of some variations in the exon-intron structure between transcript variants and the need for computational tools to address 'complex' AS events. ASTALAVISTA (alternative splicing transcriptional landscape visualization tool) employs an intuitive and complete notation system to univocally identify such events. The method extracts AS events dynamically from custom gene annotations, classifies them into groups of common types and visualizes a comprehensive picture of the resulting AS landscape. Thus, ASTALAVISTA can characterize AS for whole transcriptome data from reference annotations (GENCODE, REFSEQ, ENSEMBL) as well as for genes selected by the user according to common functional/structural attributes of interest: http://genome.imim.es/astalavista.

Echocardiographic Measurements in a Preclinical Model of Chronic Chagasic Cardiomyopathy in Dogs: Validation and Reproducibility.

Background: The failure to translate preclinical results to the clinical setting is the rule, not the exception. One reason that is frequently overlooked is whether the animal model reproduces distinctive features of human disease. Another is the reproducibility of the method used to measure treatment effects in preclinical studies. Left ventricular (LV) function improvement is the most common endpoint in preclinical cardiovascular disease studies, while echocardiography is the most frequently used method to evaluate LV function. In this work, we conducted a robust echocardiographic evaluation of LV size and function in dogs chronically infected by Trypanosoma cruzi. Methods and Results: Echocardiography was performed blindly by two distinct observers in mongrel dogs before and between 6 and 9 months post infection. Parameters analyzed included end-systolic volume (ESV), end-diastolic volume (EDV), ejection fraction (EF), and fractional shortening (FS). We observed a significant LVEF and FS reduction in infected animals compared to controls, with no significant variation in volumes. However, the effect of chronic infection in systolic function was quite variable, with EF ranging from 17 to 66%. Using the cut-off value of EF ≤ 40%, established for dilated cardiomyopathy (DCM) in dogs, only 28% of the infected dogs were affected by the chronic infection. Conclusions: The canine model of CCC mimics human disease, reproducing the percentage of individuals that develop heart failure during the chronic infection. It is thus mandatory to establish inclusion criteria in the experimental design of canine preclinical studies to account for the variable effect that chronic infection has on systolic function.