Hasil untuk "Neurosciences. Biological psychiatry. Neuropsychiatry"

Tamas Harczos, Stefan Zirn

Yanyan Li, Xiaorui Pei, Rui Ding et al.

Xiang Zhang, Jiaqi Wei, Zijie Qiu et al.

Autoregressive (AR) models, common in sequence generation, are limited in many biological tasks such as de novo peptide sequencing and protein modeling by their unidirectional nature, failing to capture crucial global bidirectional token dependencies. Non-Autoregressive (NAR) models offer holistic, bidirectional representations but face challenges with generative coherence and scalability. To transcend this, we propose a hybrid framework enhancing AR generation by dynamically integrating rich contextual information from non-autoregressive mechanisms. Our approach couples a shared input encoder with two decoders: a non-autoregressive one learning latent bidirectional biological features, and an AR decoder synthesizing the biological sequence by leveraging these bidirectional features. A novel cross-decoder attention module enables the AR decoder to iteratively query and integrate these bidirectional features, enriching its predictions. This synergy is cultivated via a tailored training strategy with importance annealing for balanced objectives and cross-decoder gradient blocking for stable, focused learning. Evaluations on a demanding nine-species benchmark of de novo peptide sequencing show that our model substantially surpasses AR and NAR baselines. It uniquely harmonizes AR stability with NAR contextual awareness, delivering robust, superior performance on diverse downstream data. This research advances biological sequence modeling techniques and contributes a novel architectural paradigm for augmenting AR models with enhanced bidirectional understanding for complex sequence generation. Code is available at https://github.com/BEAM-Labs/denovo.

Roger D. Jones, Achille Giacometti, Alan M. Jones

We derive a formulation of the First Law of nonequilibrium thermodynamics for biological information-processing systems by partitioning entropy in the Second Law into microscopic and mesoscopic components and by assuming that natural selection promotes optimal information processing and transmission. The resulting framework demonstrates how mesoscopic information-based subsystems can attain nonequilibrium steady states (NESS) sustained by external energy and entropy fluxes, such as those generated by ATP/ADP imbalances in vivo. Moreover, mesoscopic systems may reach NESS before microscopic subsystems, leading to ordered structures in entropy flow analogous to eddies in a moving stream.

Joachim E. Sestoft, Thomas K. Jensen, Vidar Flodgren et al.

Computational hardware designed to mimic biological neural networks holds the promise to resolve the drastically growing global energy demand of artificial intelligence. A wide variety of hardware concepts have been proposed, and among these, photonic approaches offer immense strengths in terms of power efficiency, speed and synaptic connectivity. However, existing solutions have large circuit footprints limiting scaling potential and they miss key biological functions, like inhibition. We demonstrate an artificial nano-optoelectronic neuron with a circuit footprint size reduced by at least a factor of 100 compared to existing technologies and operating powers in the picowatt regime. The neuron can deterministically receive both exciting and inhibiting signals that can be summed and treated with a non-linear function. It demonstrates several biological relevant responses and memory timescales, as well as weighting of input channels. The neuron is compatible with commercial silicon technology, operates at multiple wavelengths and can be used for both computing and optical sensing. This work paves the way for two important research paths: photonic neuromorphic computing with nanosized footprints and low power consumption, and adaptive optical sensing, using the same architecture as a compact, modular front end

Charlotte Claye, Pierre Marschall, Wassila Ouerdane et al.

Single-cell RNA-seq foundation models achieve strong performance on downstream tasks but remain black boxes, limiting their utility for biological discovery. Recent work has shown that sparse dictionary learning can extract concepts from deep learning models, with promising applications in biomedical imaging and protein models. However, interpreting biological concepts remains challenging, as biological sequences are not inherently human-interpretable. We introduce a novel concept-based interpretability framework for single-cell RNA-seq models with a focus on concept interpretation and evaluation. We propose an attribution method with counterfactual perturbations that identifies genes that influence concept activation, moving beyond correlational approaches like differential expression analysis. We then provide two complementary interpretation approaches: an expert-driven analysis facilitated by an interactive interface and an ontology-driven method with attribution-based biological pathway enrichment. Applying our framework to two well-known single-cell RNA-seq models from the literature, we interpret concepts extracted by Top-K Sparse Auto-Encoders trained on two immune cell datasets. With a domain expert in immunology, we show that concepts improve interpretability compared to individual neurons while preserving the richness and informativeness of the latent representations. This work provides a principled framework for interpreting what biological knowledge foundation models have encoded, paving the way for their use for hypothesis generation and discovery.

Sung Woo Joo, Young Tak Jo, Woohyeok Choi et al.

Abstract A morphometric similarity (MS) network can be constructed using multiple magnetic resonance imaging parameters of each cortical region. An MS network can be used to assess the similarity between cortical regions. Although MS networks can detect microstructural alterations and capture connections between histologically similar cortical areas, the influence of schizophrenia on the topological characteristics of MS networks remains unclear. We obtained T1- and diffusion-weighted images of 239 healthy controls and 190 individuals with schizophrenia to construct the MS network. Group comparisons of the mean MS of the cortical regions and subnetworks were performed. The strengths of the connections between the cortical regions and the global and nodal network indices were compared between the groups. Clinical associations with the network indices were tested using Spearman’s rho. Compared with healthy controls, individuals with schizophrenia had significant group differences in the mean MS of several cortical regions and subnetworks. Individuals with schizophrenia had both superior and inferior strengths of connections between cortical regions compared with those of healthy controls. We observed regional abnormalities of the MS network in individuals with schizophrenia regarding lower centrality values of the pars opercularis, superior frontal, and superior temporal areas. Specific nodal network measures of the right pars opercularis and left superior temporal areas were associated with illness duration in individuals with schizophrenia. We identified regional abnormalities of the MS network in schizophrenia with the left superior temporal area possibly being a key region in topological organization and cortical connections.

Hannelore Findeis, Hannelore Findeis, Maria Strauß et al.

IntroductionThere is evidence that there is a small group of people with schizophrenia spectrum disorders who are more likely to commit homicide than those in the general population. However, there is limited knowledge about the psychopathology that leads to homicide in this group. The aim of this study was to examine two commonly used definitions of the Threat/Control-Override (TCO) concept, which aims to identify a certain risk of serious violence in patients with schizophrenia spectrum disorders.MethodsThis is a sub analysis of a file-based, retrospective and exploratory cross-sectional study. All forensic homicide offenders with schizophrenia spectrum disorders who were detained at the Forensic Hospital Berlin as of 31 December 2014 were examined for the occurrence of TCO according to two commonly used definitions.ResultsOf a total of 419 forensic patients with schizophrenia spectrum disorders, 78 committed homicide (18.6%). The forensic homicide offenders with schizophrenia spectrum disorders were characterised by being male, unemployed, single and having committed (attempted) manslaughter. Irrespective of the definition used, the entire TCO complex was present in less than a third of the sample. In both definitions, Threat symptoms were slightly less frequent than Control-Override symptoms. While Threat symptoms occurred less frequently in Stompe et al.’s definition, Control-Override symptoms were the most common. With regard to Kröber’s definition of Threat and Control-Override, the situation is exactly the opposite.DiscussionRegarding the entire TCO complex, Kröber’s definition seems a little more open and Stompe et al.’s more strict (38.5% vs. 35.9%). Since TCO only occurs in about one third of the subjects in both definitions, neither definition appears to be conclusive. A combination with proportions from both definitions could be a contribution to a future definition of TCO. The present study provides scarcely published primary data on psychopathology in homicide offenders with schizophrenia spectrum disorders, especially on the much discussed TCO concept in two definitions. In order to determine the most useful definition of TCO, to avoid false positives and to identify clear psychopathological risk symptoms, larger samples and comparative studies with offenders and non-offenders should be conducted in the future.

Camilla Mazzucato, Michele Coscia, Ayça Küçükakdağ Doğu et al.

Recent advances in archaeogenomics have granted access to previously unavailable biological information with the potential to further our understanding of past social dynamics at a range of scales. However, to properly integrate these data within archaeological narratives, new methodological and theoretical tools are required. Effort must be put into finding new methods for weaving together different datasets where material culture and archaeogenomic data are both constitutive elements. This is true on a small scale, when we study relationships at the individual level, and at a larger scale when we deal with social and population dynamics. Specifically, in the study of kinship systems it is essential to contextualize and make sense of biological relatedness through social relations, which, in archaeology, is achieved by using material culture as a proxy. In this paper we propose a Network Science framework to integrate archaeogenomic data and material culture at an intrasite scale to study biological relatedness and social organization at the Neolithic site of Çatalhöyük. Methodologically, we propose the use of network variance to investigate the concentration of biological relatedness and material culture within networks of houses. This approach allowed us to observe how material culture similarity between buildings gives valuable information on potential biological relationships between individuals and how biogenetic ties concentrate at specific localities on site.

Matthieu M. de Wit

Mougenot and Matheson (2024) make a compelling case for the development of a mechanistic cognitive neuroscience that is embodied. However, their analysis of extant work under this header plays down important distinctions between "minimal" and "radical" embodiment. The former remains firmly neurocentric and therefore has limited potential to move the needle in understanding the functional contributions of neural dynamics to cognition in the context of wider organism-environment dynamics.

Alessandro Cicolin, Luigi Ferini-Strambi

Sleep is an essential biological requirement for human life, alongside food, water, and air [...]

Asmaa Younis Elsary, Naglaa A. El-Sherbiny

Abstract Background Coronavirus (COVID-19) pandemic is a public health emergency. During the outbreak, a broad range of psychological disorders affected people at the individual, community, and international levels. This study aimed to assess the role of stress-coping strategies in relieving perceived stress among university students during the COVID-19 pandemic. Methods This interventional study was nested on a cross-sectional design and involved students at Faiyum University in 2022. Results Out of a sample of 2640 students, 2176 (82.4%) experienced moderate perceived stress, while 56 (2.1%) had more severe levels. Being female, nonmedical students, and rural inhabitants having a low socioeconomic status were associated with scores for severe and moderate levels of perceived stress. Among the interventional group, Modified Perceived Stress Scale scores significantly decreased after the implementation of the stress-coping program, with a p value < 0.001. Improvements in perceived stress levels were observed among male, medical, and high-socioeconomic-status students. Conclusion Perceived stress levels were associated with being female, engaging in nonmedical study, and having low socioeconomic status and decreased after a stress-coping program was implemented. These findings assert the need to develop regular campaigns to provide psychological support and stress-coping strategies that may help students overcome different stressors.

Euijun Song

Sustained spiral waves, also known as rotors, are pivotal mechanisms in persistent atrial fibrillation (AF). Stochasticity is inevitable in nonlinear biological systems such as the heart; however, it is unclear how noise affects the instability of spiral waves in human AF. This study presents a stochastic two-dimensional mathematical model of human AF and explores how Gaussian white noise affects the instability of spiral waves. In homogeneous tissue models, Gaussian white noise may lead to spiral-wave meandering and wavefront break-up. As the noise intensity increases, the spatial dispersion of phase singularity (PS) points increases. This finding indicates the potential AF-protective effects of cardiac system stochasticity by destabilizing the rotors. By contrast, Gaussian white noise is unlikely to affect the spiral-wave instability in the presence of localized scar or fibrosis regions. The PS points are located at the boundary or inside the scar/fibrosis regions. Localized scar or fibrosis may play a pivotal role in stabilizing spiral waves regardless of the presence of noise. This study suggests that fibrosis and scars are essential for stabilizing the rotors in stochastic mathematical models of AF. Further patient-derived realistic modeling studies are required to confirm the role of scar/fibrosis in AF pathophysiology.

Maxim Polyakov

Timely diagnosis of breast cancer is an important task. This type of breast cancer is one of the most common diseases. The method of microwave radiothermometry is a promising direction for solving this problem. The method is based on measuring internal temperature of biological tissues in microwave frequency range. Computer simulations are used to improve the quality of diagnostics. Computer models make it possible to evaluate the effect of heat release in a malignant tumor on the thermal dynamics inside the mammary gland. It is necessary to build personalized models, taking into account the individual nature of the internal structure of the mammary gland in each patient. One of the problems is the determination of biophysical characteristics of biological components. Methods for determining these characteristics using computer simulations are proposed. The coefficient of thermal conductivity and specific heat of biological tissues are determined from known temperature distributions. Finding the physical parameters for a quasihomogeneous biological tissue is the first approximation for solving this problem. The least squares method is used as a solution method. The results obtained are in good agreement with previously known exact solutions, which indicates the applicability of this method for solving this class of problems. The efficiency of using parallel technologies in solving the inverse problem is investigated and the applicability of Open MP technology is demonstrated.

Hen Emuna, Nadav Borenstein, Xin Qian et al.

Biologically Inspired Design (BID), or Biomimicry, is a problem-solving methodology that applies analogies from nature to solve engineering challenges. For example, Speedo engineers designed swimsuits based on shark skin. Finding relevant biological solutions for real-world problems poses significant challenges, both due to the limited biological knowledge engineers and designers typically possess and to the limited BID resources. Existing BID datasets are hand-curated and small, and scaling them up requires costly human annotations. In this paper, we introduce BARcode (Biological Analogy Retriever), a search engine for automatically mining bio-inspirations from the web at scale. Using advances in natural language understanding and data programming, BARcode identifies potential inspirations for engineering challenges. Our experiments demonstrate that BARcode can retrieve inspirations that are valuable to engineers and designers tackling real-world problems, as well as recover famous historical BID examples. We release data and code; we view BARcode as a step towards addressing the challenges that have historically hindered the practical application of BID to engineering innovation.

M. Ali Al-Radhawi, David Angeli, Eduardo Sontag

Biological networks are customarily described as structurally robust. This means that they often function extremely well under large forms of perturbations affecting both the concentrations and the kinetic parameters. In order to explain this property, various mathematical notions have been proposed in the literature. In this paper, we propose the notion of structural contractivity, building on the previous work of the authors. That previous work characterized the long-term dynamics of classes of Biological Interaction Networks (BINs), based on "rate-dependent Lyapunov functions". Here, we show that stronger notions of convergence can be established by proving structural contractivity with respect to non-standard polyhedral $\ell_\infty$-norms. In particular, we show that such networks are nonexpansive. With additional verifiable conditions, we show that they are strictly contractive over arbitrary positive compact sets. In addition, we show that such networks entrain to periodic inputs. We illustrate our theory with examples drawn from the modeling of intracellular signaling pathways.

A. D. LaMontagne, L. L. Cox, C. Lockwood et al.

Abstract Males are at higher risk of death by suicide than females in Australia, and among men, blue-collar males are at higher risk compared to other working males. In response, MATES in Construction developed a workplace suicide prevention program for the construction sector in 2007 that has been widely implemented in Australia. In the current project, this program is being adapted and trialled in the manufacturing sector. The common aims of MATES programs are to improve suicide prevention literacy, help-seeking intentions, and helping behaviours. The program will be evaluated using a cluster randomised-controlled trial design with waitlist controls across up to 12 manufacturing worksites in Australia. We hypothesise that after 8 months of the MATES in Manufacturing program, there will be significantly greater improvements in help-seeking intentions (primary outcome) compared to waitlist controls. The project is led by Deakin University in collaboration with the University of Melbourne, and in partnership with MATES in Construction and a joint labour-management Steering Group. Trial registration: The trial was registered retrospectively with the Australian New Zealand Clinical Trials Registry on 25 January 2022 (ACTRN12622000122752). Protocol version: 2.0, November 2022.

Alisa A Shaimardanova, Daria S Chulpanova, Valeriya V Solovyeva et al.

Tay-Sachs disease and Sandhoff disease are severe hereditary neurodegenerative disorders caused by a deficiency of β-hexosaminidase A (HexA) enzyme, which results in the accumulation of GM2 gangliosides in the nervous system cells. In this work, we analyzed the efficacy and safety of cell-mediated gene therapy for Sandhoff disease and Sandhoff disease using a bicistronic lentiviral vector encoding cDNA of HexA α- and β-subunit genes separated by the nucleotide sequence of a P2A peptide (HEXA-HEXB). The functionality of the bicistronic construct containing the HEXA-HEXB genetic cassette was analyzed in a culture of HEK293T cells and human umbilical cord blood mononuclear cells (hUCBMCs). Our results showed that the enzymatic activity of HexA in the conditioned medium harvested from genetically modified HEK293T-HEXA-HEXB and hUCBMCs-HEXA-HEXB was increased by 23 and 8 times, respectively, compared with the conditioned medium of native cells. Western blot analysis showed that hUCBMCs-HEXA-HEXB secreted both completely separated HEXA and HEXB proteins, and an uncleaved protein containing HEXA + HEXB linked by the P2A peptide. Intravenous injection of genetically modified hUCBMCs-HEXA-HEXB to laboratory Wistar rats was carried out, and the HexA enzymatic activity in the blood plasma of experimental animals, as well as the number of live cells of immune system organs (spleen, thymus, bone marrow, lymph nodes) were determined. A significant increase in the enzymatic activity of HexA in the blood plasma of laboratory rats on days 6 and 9 (by 2.5 and 3 times, respectively) after the administration of hUCBMCs-HEXA-HEXB was shown. At the same time, the number of live cells in the studied organs remained unchanged. Thus, the functionality of the bicistronic genetic construct encoding cDNA of the HEXA and HEXB genes separated by the nucleotide sequence of the P2A peptide was shown in vitro and in vivo. We hypothesize that due to the natural ability of hUCBMCs to overcome biological barriers, such a strategy can restore the activity of the missing enzyme in the central nervous system of patients with GM2 gangliosidoses. Based on the obtained data, it can be concluded that intravenous administration of hUCBMCs with HexA overexpression is a promising method of the therapy for GM2 gangliosidoses. The animal protocol was approved by the Animal Ethics Committee of the Kazan Federal University (No. 23) on June 30, 2020.

Suzanne M. Fielding, James O. Cochran, Junxiang Huang et al.

The rheology of biological tissue is key to processes such as embryo development, wound healing and cancer metastasis. Vertex models of confluent tissue monolayers have uncovered a spontaneous liquid-solid transition tuned by cell shape; and a shear-induced solidification transition of an initially liquid-like tissue. Alongside this jamming/unjamming behaviour, biological tissue also displays an inherent viscoelasticity, with a slow time and rate dependent mechanics. With this motivation, we combine simulations and continuum theory to examine the rheology of the vertex model in nonlinear shear across a full range of shear rates from quastistatic to fast, elucidating its nonlinear stress-strain curves after the inception of shear of finite rate, and its steady state flow curves of stress as a function of strain rate. We formulate a rheological constitutive model that couples cell shape to flow and captures both the tissue solid-liquid transition and its rich linear and nonlinear rheology.

C. Peixoto, D. Rego, M. Bicho et al.

Introduction Delusional infestation (DI), also known as delusional parasitosis or Ekbom syndrome, is a rare disorder, characterised by fixed belief that the skin, body or immediate environment is infested by small pathogens, despite the lack of any medical evidence for it. Objectives To describe and discuss two clinical cases of DI, in order to show two different ways of presenting in this entity. Methods Two case report and non-systematic review. Results We present the case of a 76-year-old woman, without psychiatric history, with an DI with 5 years of evolution, referred to a psychiatric consultation by a dermatologist. The second case, is a 41-year-old woman with a history of multiple substance use disorder, with an DI with a month of evolution, who resorted to the emergency department. DI is not a single diagnostic entity. The classic form, as represented in the first case,is a primary form, which develops without any known cause or underlying disease, corresponding to a persistent delusional disorder. However, about 60% of patients have secondary forms of DI, in the context of substance misuse, some medications or in the course of physical or psychiatric diseases (e.g. stroke, delirium, dementia, depression, schizophrenia). Conclusions DI can occur as a primary delusional disorder or secondary to several other medical conditions. An in-depth clinical history is essential in order to make the correct diagnosis. A multidisciplinary approach is also important, to exclude any possible organic etiology, not forgetting that many patients may turn to other medical specialities first. Disclosure No significant relationships.