Biosignals Research Articles (Page 1)

This study proposes a Personalized Deep Learning-Based Sleep Recommendation System Using Lifelog Data (PDSRS-LD). Traditional sleep research primarily relies on bio signals such as EEG and ECG recorded during sleep but often fails to sufficiently reflect the influence of daily activities on sleep quality. To address this limitation, we collect lifelog data such as stress levels, fatigue, and sleep satisfaction via wearable devices and use them to construct individual user profiles. Subsequently, real sleep data obtained from an AI-powered motion bed are incorporated for secondary training to enhance recommendation performance. PDSRS-LD considers comprehensive user data, including gender, age, and physical activity, to analyze the relationships among sleep quality, stress, and fatigue. Based on this analysis, the system provides personalized sleep improvement strategies. Experimental results demonstrate that the proposed system outperforms existing models in terms of F1 score and Average Precision (mAP). These results suggest that PDSRS-LD is effective for real-time, user-centric sleep management and holds significant potential for integration into future smart healthcare systems.

Molecular fossil responses to Toarcian (Early Jurassic) climate warming in the high-latitude lacustrine Junggar Basin, China

Endogenous retroviruses (ERVs), remnants of ancient viral infections integrated into host genomes, serve as invaluable molecular fossils for studying viral evolution. In this study, we performed a genomic analysis of the Chinese pangolin (Manis pentadactyla), identifying novel full-length endogenous retroviruses, designated as Manis pentadactyla ERVs (MPERVs). MPERVs span three retroviral genera: Alpha-, Beta-, and Gamma-retroviruses. Using genomic screening and phylogenetic analysis, we classified MPERVs and reconstructed their evolutionary history, uncovering evidence of complex recombination events and cross-species transmission. Estimated insertion times for MPERVs range from very recent to 18.38 million years ago. MPERVs exhibit diverse structural features, notably including conserved retroviral domains and functional motifs and highlighting their preservation across extensive evolutionary periods. These findings shed light on the evolutionary dynamics of ERVs in Chinese pangolin and suggest the potential for expanded host ranges among certain retrovirus genera.IMPORTANCEEndogenous retroviruses are unique viruses distinguished by the fact that they are retained as part of the host genome after an exogenous retrovirus infects the host. The Chinese pangolin, as a host with a long independent evolutionary history, likely holds valuable insights in its genome regarding retrovirus endogenization and transmission. In this study, we identified the footprints of exogenous retroviruses from three different genera in the pangolin genome: Alpharetrovirus, Betaretrovirus, and Gammaretrovirus. Additionally, by calculating the integration times of the pangolin's endogenous retroviruses and analyzing the domains of the three main functional proteins (GAG, POL, and ENV), we found that the insertions are relatively young. This suggests that these endogenous retroviruses infected the Chinese pangolin long before their endogenization. This study represents the exploration of endogenous retroviruses in the Chinese pangolin genome, expanding our understanding of endogenous retroviruses in mammals. Furthermore, our findings provide new evidence for the phenomenon of the cross-species transmission of retroviruses prior to endogenization.

Putative metazoan body fossils from the Precambrian are curiously lacking morphological characteristics that link them unambiguously to extant animal phyla, including sponges. Chemical fossils such as the rare C30 hydrocarbons 24-iso-propylcholestane (24-ipc) and 26-methylstigmastane (26-mes), however, have been proposed as evidence for the Neoproterozoic emergence of the Demospongiae (Porifera) due to their prevalence in rocks of this age and the occurrence of their sterol precursors in contemporary demosponges. However, there are alternative hypotheses which posit that diagenetic alteration products of algal sterols, or those from Rhizaria or other protists, account for the enigmatic steroid distributions observed in these ancient sedimentary rocks. Here, we report additional support for the Neoproterozoic rise of demosponges through the chemical characterization of two previously unrecognized C31 hydrocarbons-24-n-butylcholestane (24-nbc) and 24-sec-butylcholestane (24-secbc). Precursor C31 sterols from contemporary demosponges, as well as a suite of synthesized C31 sterol standards were reduced to their sterane counterparts. Gas chromatography-tandem mass spectrometry analysis and collisionally activated dissociation mass spectra confirmed the presence of 24-nbc and 24-secbc in well-preserved early Ediacaran rocks, and the coelution of these compounds with synthetic standards enhances the robustness of these findings. Co-occurrence of abundant 24-ipc and 24-secbc was found for numerous Neoproterozoic-Cambrian rock/oil samples, closely mimicking the abundance patterns and high structural selectivity of major C30 and C31 sterols detected in numerous species of modern demosponges. These findings support the hypothesized first emergence of sponges during the Neoproterozoic Era.

Early identification of epileptic activities is essential for clinical analysis and preventing advancement of the disease. Despite the development of neurological diagnostic techniques, the current analysis of epileptic seizures is still relying on a visual interpretation of electroencephalogram (EEG) signal. Neurology specialists manually perform this examination to detect patterns, a process that is both challenging and time-consuming. Biomedical signals, such as EEG and electrocardiogram (ECG), are important tools for studying human brain disorders, particularly epilepsy. This paper aims to develop a system that automatically detects epileptic seizures using discrete wavelet decomposition (DWT), particle swarm optimization (PSO), and support vector machine (SVM), thereby relieving clinicians of their challenging tasks. The proposed system employs the DWT method, PSO, and SVM. This approach has three steps. First, we introduce a method that uses a four-level discrete wavelet transform (DWT) to extract important information from electroencephalogram and electrocardiogram signals by breaking them down into useful features. Second, we optimize the SVM classifier parameters using the PSO algorithm. Finally, we classify the extracted parameters using the optimized SVM. The system achieves an average accuracy of 97.92%, a 100% recall, a 96.15% specificity, and a 0.96 AUC value. Our findings demonstrate the success of this method, showing that the PSO-optimized SVM performs significantly better in classification. In addition, our findings also demonstrate the importance of using ECG signals as supplemental data. One implication of our work is the potential for creating wearable, real-time, customized seizure warning systems. In the future, these systems will be deployed on embedded platforms in real time and validated using larger datasets.

This paper presents a strategy for noise suppression and stability enhancement of organic photodetectors (OPDs) by introducing pH-neutralized and transfer-laminated poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as the hole-transporting layer (HTL). Although PEDOT:PSS is widely used as an HTL material, its intrinsic acidity and structural instability hinder the performance of the OPD. Here, imidazole-induced neutralization promotes a linear entangled structure, while transfer lamination enables controlled PSS domain distribution. These structural modifications lead to a favorable energy level alignment for hole transport and improved HTL stability. Enhanced interfacial contact between the photoactive layer and HTL facilitates photocurrent flow and reduces internal noise, yielding high specific detectivity and shot-noise-limited detectivity without bias and under -0.5 V reverse bias. The optimized OPD device also exhibits increased shunt resistance, reduced trap density, and fast response to frequency-specific optical signals with high signal-to-noise and wide frequency bandwidth. An in situ stress monitoring system demonstrates the device's capability for real-time bio signal detection, maintaining stable operation after 360 h of ambient storage. These results confirm the potential use of pH-controlled, transfer-laminated PEDOT:PSS for high-performance, long-term stable OPDs in practical sensing applications.

Hemiptera, the fifth most diverse insect order, are characterized by their high diversity in deep time, with 145 known extinct families. However, the precise timing of the origin of Hemiptera lineages has remained uncertain. Traditional approaches, molecular clock analyses and fossil calibrations, have overlooked much of this extinct diversity by failing to incorporate key fossil data. Furthermore, no estimates have been proposed for the timing of the extinction of Hemiptera’s fossil lineages. In this study, we use the recently developed Bayesian Brownian Bridge model, which estimates the timing of lineage origin and extinction through fossil-based Bayesian modelling, to provide a temporal framework for the rise and fall of 310 major hemipteran lineages. Our results support an early Pennsylvanian origin of Hemiptera, and indicate that the major hemipteran lineages originated between the late Carboniferous and Late Permian (Pennsylvanian-Lopingian). Additionally, our analyses reveal a radiation of Hemiptera during the Permian (Guadalupian), followed by multiple extinctions of ancient hemipteran lineages from the Permo-Triassic boundary to the mid-Triassic. A second major radiation occurred during the Cretaceous, coinciding with numerous extinctions of relic and newly emerging Cretaceous lineages, highlighting a faunal turnover. Our study provides a holistic fossil-based picture of the evolutionary history of Hemiptera.

IntroductionOutcome after surgery depends on both patient-related as well as procedure-related risks. Complications after surgery are a significant burden to patients and to the health system. A vast amount of often unstructured data from different sources are generated during surgery, which contain valuable information associated with outcome. Advances in computer hardware and machine learning now increasingly facilitate the development of prediction models in standardised, parametric, information-rich areas such as the perioperative setting. For the development and validation of risk scores and prediction models, high-fidelity data sources are required to arrive at meaningful and reliable predictions. However, data quality standards in retrospective studies are rarely met. Therefore, the prospective Heidelberg Perioperative Deep Data Registry and Biomaterial Bank (HeiPoDD - Registry and Bio Bank) was started to implement a clinical data base and a corresponding biobank merging the entirety of available clinical records.Methods and analysisThe HeiPoDD - Registry and Bio Bank is a study-driven, prospective, single-centre observational registry data base and biomaterial bank. It contains data and material from eligible patients who give informed consent and undergo elective non-cardiac high-risk surgery at the surgical centre of the Heidelberg University Hospital. The screening for eligibility started in January 2022, with no maximum sample size specified in advance. Routine data are recorded and stored during hospital stay and potential readmissions within 90 days after index surgery. The data are merged with the potentially available genome, proteome, flow cytometry, and bio signal data. Endpoints are obtained from routine observations, stored data in the hospital information system and follow-up visits. Further, data and biological specimens from separate perioperative studies with the patients’ consent can be transferred into the HeiPoDD - Registry and Bio Bank as well. This large-scale data collection will allow the calculation of endpoint-specific prediction models using logistic regression models as well as machine learning models. The first 1040 patients included in the HeiPoDD - Registry and Bio Bank are also included in the HeiPoDD study.Ethics and disseminationThe trial protocol and subsequent amendments were approved by the ethics committee of the University of Heidelberg (S-745/2021). Participating patients’ data will be entered only in pseudonymised form. Data and biomaterials will be kept for up to 30 years. The findings will be disseminated in peer-reviewed academic journals.Trial registration numberDRKS00025924, registered on 2021-11-12.

Animal innate immunity evolved from ancient pathways in bacterial anti-phage defense. How bacterial immune components were first acquired and adapted within eukaryotic cells remains poorly understood. Here we identify a complete cGLR-STING signaling axis in choanoflagellates, the closest living relatives of animals, that exhibits a mosaic of features from both bacterial and animal immunity. Comparative genomics reveals choanoflagellate cGLR and STING genes organized in operon-like arrangements reminiscent of bacterial defense loci. Reconstitution of choanoflagellate cGLR-STING signaling in vitro demonstrates that activation occurs through the conserved nucleotide immune signal 2′3′-cGAMP. Structural analysis of a choanoflagellate STING–2′3′-cGAMP complex explains how retention of bacterial-like features in early eukaryotic proteins shapes ligand specificity and receptor activation. We analyze cGLR and STING evolution in unicellular eukaryotes and identify further STING homologs in choanoflagellates and fungi that support additional independent acquisition events. Our results reveal molecular fossils that bridge bacterial and animal immunity and illuminate early eukaryotic immune system evolution.

Artificial Intelligence has shown great promise in healthcare, particularly in non-invasive diagnostics using bio signals. This study focuses on classifying eye states (open or closed) using Electroencephalogram (EEG) signals captured via a 14-electrode neuroheadset, recorded through a Brain-Computer Interface (BCI). A publicly available dataset comprising 14,980 instances was used, where each sample represents EEG signals corresponding to eye activity. Fourteen classical machine learning (ML) models were evaluated using a tenfold cross-validation approach. The preprocessing pipeline involved removing outliers using the Z-score method, addressing class imbalance with SMOTETomek, and applying a bandpass filter to reduce signal noise. Significant EEG features were selected using a two-sample independent t-test (p < 0.05), ensuring only statistically relevant electrodes were retained. Additionally, the Common Spatial Pattern (CSP) method was used for feature extraction to enhance class separability by maximizing variance differences between eye states. Experimental results demonstrate that several classifiers achieved strong performance, with accuracy above 90%. The k-Nearest Neighbours classifier yielded the highest accuracy of 97.92% with CSP, and 97.75% without CSP. The application of CSP also enhanced the performance of Multi-Layer Perceptron and Support Vector Machine, reaching accuracies of 95.30% and 93.93%, respectively. The results affirm that integrating statistical validation, signal processing, and ML techniques can enable accurate and efficient EEG-based eye state classification, with practical implications for real-time BCI systems and offering a lightweight solution for real-time healthcare wearable applications healthcare applications.

Stroke is recognized as a source of numerous impairments, encompassing deficits in physical, motor, and emotional functions in affected individuals. While the visible manifestations of a stroke are evident, the internal effects on the brain remain mostly enigmatic. Research has shown that utilizing motor imagery tasks via Electroencephalogram (EEG) bio signals achieves a 10% increase in accuracy relative to traditional techniques. This research work aims to employ feature extraction techniques on motor imaging tasks combining right- and left-hand grasping, utilizing motor imagery-based EEG data to extract the most pertinent features from two distinct datasets. One dataset comprises individuals with stroke, and the other consists of healthy individuals. Techniques such as the Common Spatial Filter (CSP) and the Filter Bank Common Spatial Filter (FBCSP) are employed to extract relevant features from the processed and filtered data. Three supervised machine learning algorithms, including Support Vector Machines (SVM), Linear Discriminant Analysis (LDA), and Gaussian Naïve Bayes (GNB), have been employed for data classification. A comparative study has been conducted to understand the fundamental differences in the EEG signals between stroke patients and healthy individuals. The findings indicated that the FBCSP approach surpassed CSP in both categories of patients, with the SVM achieving an accuracy of up to 98.86% in classifying motor imagery tasks. This comparative study enhances our understanding of Brain-Computer Interface (BCI) systems and motor rehabilitation methods by elucidating critical differences between EEG data from stroke patients and healthy individuals.

Abstract This article focuses on the recent pronoun-sharing practice (in bio signatures or interactions) and demonstrates the need to apprehend the trend within a pragmatic framework. Basing her analysis on a questionnaire and extracts from the web via SketchEngine, the author shows that the different evaluations of the phenomenon cover the whole spectrum from politeness to impoliteness theory. Pronoun sharers evince what she calls “inclusive politeness” by paying attention to others’ face needs. Rejecters consider the practice an impingement on their sociality rights. What they regard as an impolite act towards them in turn justifies their opting out of inclusive politeness. The author then evinces that there is a middle-ground attitude between these two opposed perspectives. Some people may not consider themselves allies to the cause and yet opt for the correct pronoun out of “civility”, which can be either genuine or “virtue-signalling”. The article proposes to see pronoun sharing as a preemptive act aimed at avoiding the damaging act of misgendering, and assesses the cost such a practice entails and to whom. It finally advocates for a Critical Politeness Theory, acknowledging the subjective position of the researcher and their critical third-order perspective on matters of consideration for fellow human beings.

Endogenous viral elements (EVEs) serve as molecular fossils that record the ancient co-evolutionary arms race between viruses and their hosts. In this study, by analyzing 105 host crustacean genomes, we identified 252 infectious hypodermal and haematopoietic necrosis virus-derived EVEs (IHHNV-EVEs), which include 183 ancient and 6 recently inserted EVEs. These IHHNV-EVEs are widely distributed among Decapoda, Thoracica, and Isopoda, with some of them exhibiting a syntenic distribution relative toneighboringhost sequences, suggesting that the IHHNV or its ancestor are potential pathogens of these species with a long-time dynamic interaction during the evolutionary history. An expansion of IHHNV-EVEs was observed indecapodagenomes, reflecting a reinforced arm race betweendecapodaand IHHNV. Notably, we found that nearly all recent IHHNV-EVEs were laboratory contaminants, except for a single authentic integration in Penaeus monodon that persists intact across 16 samples from the 2 populations. These temporal dynamics-ancient genomic stabilization versus modern colonization activity-highlight that EVEs serve as dual archives: historical records of past conflicts and active participants in current evolutionary battles. Our findings redefine viral genomic colonization as a continuum, where ancient EVE fixation coexists with persistent integration processes, providing new insights into host-virus co-evolutionary trajectories.

The rise of birds represents one of the major evolutionary transitions in the history of life. Yet, much remains obscure about the origins and diversification of viruses in birds. Endogenous retroviruses (ERVs), relics of past retroviral infections, provide molecular fossils for interrogating the evolution and ecology of retroviruses. Here, we perform phylogenomic mining of ERVs within the genomes of 758 bird species and identify more than 470,000 ERVs, revealing a highly diverse and complex retrovirus repertoire in birds. These ERVs greatly expand the diversity of retroviruses in birds, indicating that exogenous retroviruses characterized in birds to date are highly underestimated. The evolution of retroviruses in birds is shaped by both coevolution and cross-species transmission. Tens of retrovirus lineages originated during the early evolution of birds, four of which contribute to more than 90% of complete ERVs in birds. We also observe recent ERV activity across the bird phylogeny (particularly in Passeriformes). Moreover, we find that ERVs can mediate genome rearrangements, potentially facilitating the genome evolution of birds. Many bird retroviruses recruited genes of cellular provenience, which might drive the evolution of the genome complexity of retroviruses. Together, these results unveil a diverse and complex retrovirosphere in birds and provide insights into the intricate evolution of retrovirus-bird interaction.

Abstract— This project proposes the design and implementation of a portable, non-invasive ECG and EMG monitoring system using the ESP32-S3 microcontroller. The system is capable of capturing and displaying real-time bioelectrical signals from the human body using two dedicated sensors—an AD8232 module for electrocardiogram (ECG) signal acquisition and a modular EMG sensor for muscle activity monitoring. The ESP32-S3’s built-in ADC is used to digitize the signals, which are then processed and displayed as scrolling waveforms on a 320×240 SPI TFT display. A push-button interface is incorporated to switch between ECG and EMG modes, allowing users to monitor both heart and muscle signals dynamically. Each mode is visually distinguished with color-coded waveforms—red for ECG and green for EMG—ensuring clarity and ease of interpretation. Additionally, the system logs the sensor values to the serial monitor in real time for further analysis and debugging. The entire hardware is compactly assembled on an acrylic casing, providing a professional and ergonomic enclosure. This cost-effective solution demonstrates a reliable and user-friendly approach to basic bio signal monitoring and is suitable for applications in academic research, physiotherapy, wearable health tech development, and biomedical education. Keywords—ESP32-S3, ECG Monitoring, EMG Signal, Non-Invasive Sensors, Biomedical Signal Acquisition, Real-Time Visualization, TFT Display, Portable Monitoring System, IoT Health Applications.

ABSTRACTThe late Palaeocene climate cooling event has been reported in the organic‐rich sediments of the second member of the Funing Formation (E1f2) in the Subei Basin. However, there is a lack of in‐depth research on the constraints of paleoclimate changes on paleoenvironment and biological sources that remain unclear. This study presents detailed molecular geochemical analyses from the lacustrine mudstones of the E1f2 in the Subei Basin. The proxies of paleosalinity (gammacerane/C30 hopane, β‐carotene/n‐C20 and extended tricyclic terpane ratio) and redox conditions (pristane/phytane, phytane/n‐C18 and dibenzothiophene/phenanthrene) suggest climate cooling enhanced a higher salinity and anoxic (ferruginous) water column during the lower unit of the E1f2 deposition. As the climate shifted to warmer and more humid conditions, water salinity and reducing conditions noticeably decreased. Proxies for biological source (maximum n‐alkane, C27/C29 sterane, 4‐methylsterane/C29 regular sterane and steranes/hopanes) indicate that cooling climate constrained biodiversity. A transition is observed from the dominance of halophilic algae in the lower unit to a bloom of phytoplankton and prokaryotes in the upper unit. In addition, high abundance aryl isoprenoids and heavy organic carbon isotope compositions suggest the occurrence of photic zone anoxia in the lower unit, potentially providing a new case of green sulphur bacteria that thrived in a ferruginous lacustrine environment. Our research provides perspectives for the evolution of watermass conditions and biological sources in the Subei Basin during the late Palaeocene, highlighting the important role of climate changes in the evolution of lacustrine environment conditions.

Endogenous retroviruses (ERVs) are remnants of ancestral viral infections in germ cells that constitute a substantial proportion of the mammalian genome and are assumed to provide molecular fossil records of ancient infections. Analysis of these sequences may reveal the mechanisms of virus–host co-evolution, viral endogenization, and extinction. Chimpanzee endogenous retrovirus 1 (CERV1), a gamma retrovirus, is estimated to have circulated within primates for ~10 million years, although it is now apparently extinct. In this study, we aimed to gain an understanding of how the extinct CERV1 was transmitted and endogenized. On the basis of the identification of CERV1 fossils in the primate genome and using the expression-cloning method with the human cDNA library, we found that riboflavin transporter human SLC52A2 served as a receptor for CERV1 entry. The ectopic expression of human and chimpanzee SLC52A2 and its related SLC52A1 in heterogenic cells confers susceptibility to infection by CERV1 and porcine endogenous retrovirus (PERV). Virus interference experiments have shown that CERV1 inhibits infection by PERV and vice versa. This finding indicates that CERV1 and PERV belong to the same virus interference group. CERV1 shows infection in a wide range of human and primate cells. Notably, CERV1 infection is observed in human cell lines that express human SLC52A2 abundantly but hardly express human SLC52A1. Although CERV1 has been established to be present at high copy numbers in the great apes (Pan troglodytes, Pan paniscus, and Gorilla gorilla) and 15 Old World monkey species of the Cercopithecinae and Colobinae subfamilies, it is absent in humans and orangutans. CERV1 gene expression is observed in primates, including chimpanzees, suggesting that CERV1 has co-evolved with its hosts. Our results suggest that ERVs may have conferred resistance to viral infections in a convergent evolutionary manner. These findings are significant not only for advancing the field of paleovirology but also in terms of gaining an understanding of the potential risks of viral infection with respect to xenotransplantation, such as that from pigs to humans.

Integrated investigation of rare earth elements, molecular fossils, and stable isotopes in drill cores from deep-buried strata in the Yangtze Block: Implications for the Early Cambrian sedimentary environments

Abstract Modern healthcare is benefiting from advanced wearable devices for the diagnosis and treatment of a wide array of medical conditions. The development of effective, comfortable, and reliable electrodes is of paramount importance for capturing essential biological signals such as electrocardiography (ECG), electromyography, and electroencephalography. There is a growing interest in developing electrodes with non-rigid and flexible materials and efficient designs to improve bio signal reception. In this study, we have focused on the design and evaluation of wearable ECG dry electrodes for long-term seamless operation. These electrodes utilize a novel hexagonal design with Kapton-supported thin film-based electrical interconnects for enhanced mechanical flexibility. 500 µm ultra-thin profile of the dry electrode contributes well to its self-adhesion to the curvilinear surface of the skin. The electrode achieves an SNR of 88 dB (compared to 87 dB for wet electrodes) and a crest factor of 5.82 dB (versus 5.56 dB for wet electrodes). Experimental results indicate comparable electrical properties to traditional wet electrodes in the frequency range of interest (0.5–100 Hz), with enhanced mechanical flexibility and comfort. Thanks to the adopted technology, the electrodes perform well under various mechanical forces and maintain conformal contact resulting in minimized motion artifacts.

At the heart of many nucleoside triphosphatases is a conserved phosphate-binding sequence motif. A current model of early enzyme evolution proposes that this six to eight residue motif could have sparked the emergence of the very first nucleoside triphosphatases—a striking example of evolutionary continuity from simple beginnings, if true. To test this provocative model, seven disembodied Walker A-derived peptides were extensively computationally characterized. Although dynamic flickers of nest-like conformations were observed, significant structural similarity between the situated peptide and its disembodied counterpart was not detected. Simulations suggest that phosphate binding is nonspecific, with a preference for GTP over orthophosphate. Control peptides with the same amino acid composition but different sequences and situated conformations behaved similarly to the Walker A peptides, revealing no indication that the Walker A sequence is privileged as a disembodied peptide. We conclude that the evolutionary history of the P-loop NTPase family is unlikely to have started with a disembodied Walker A peptide in an aqueous environment. The limits of evolutionary continuity for this protein family must be reconsidered. Finally, we argue that motifs such as the Walker A motif may represent incomplete or fragmentary molecular fossils—the true nature of which has been eroded by time.