Hasil untuk "Neurosciences. Biological psychiatry. Neuropsychiatry"

Shailesh Garg, Souvik Chakraborty

Time-dependent reliability analysis of nonlinear dynamical systems under stochastic excitations is a critical yet computationally demanding task. Conventional approaches, such as Monte Carlo simulation, necessitate repeated evaluations of computationally expensive numerical solvers, leading to significant computational bottlenecks. To address this challenge, we propose \textit{CoNBONet}, a neuroscience-inspired surrogate model that enables fast, energy-efficient, and uncertainty-aware reliability analysis, providing a scalable alternative to techniques such as Monte Carlo simulations. CoNBONet, short for \textbf{Co}nformalized \textbf{N}euroscience-inspired \textbf{B}ayesian \textbf{O}perator \textbf{Net}work, leverages the expressive power of deep operator networks while integrating neuroscience-inspired neuron models to achieve fast, low-power inference. Unlike traditional surrogates such as Gaussian processes, polynomial chaos expansions, or support vector regression, that may face scalability challenges for high-dimensional, time-dependent reliability problems, CoNBONet offers \textit{fast and energy-efficient inference} enabled by a neuroscience-inspired network architecture, \textit{calibrated uncertainty quantification with theoretical guarantees} via split conformal prediction, and \textit{strong generalization capability} through an operator-learning paradigm that maps input functions to system response trajectories. Validation of the proposed CoNBONet for various nonlinear dynamical systems demonstrates that CoNBONet preserves predictive fidelity, and achieves reliable coverage of failure probabilities, making it a powerful tool for robust and scalable reliability analysis in engineering design.

Guldeniz Cetin, Ozlem Totuk, Ozdem Erturk Cetin et al.

Abstract Objective This study aimed to compare the short-term prophylactic efficacy of greater occipital nerve (GON) blockade in menstrual migraine (MM) subgroups and evaluate the long-term effects on patients’ quality of life. Methods In this prospective study, 33 patients diagnosed with MM (15 with pure menstrual migraine [PMM] and 18 with menstrually related migraine [MRM]) received bilateral GON blockade once a month, one week before menstrual bleeding, for three months. Patients were evaluated before treatment (month 0) and after treatment completion (months 3 and 6) using the Visual Analog Scale (VAS), Headache Impact Test-6 (HIT-6), Migraine Disability Assessment (MIDAS), and Beck Depression Inventory (BDI) scores. Results MRM patients had a lower age of MM onset (p = 0.024), higher headache frequency (p = 0.004), and increased medication overuse (p = 0.027) compared to PMM patients. After GON blockade, significant improvements were observed in VAS, HIT-6, MIDAS, and BDI scores in both subgroups, with no significant differences between them. The improvement persisted during the medication-free follow-up period (months 3–6). Patients with mild or no depression showed a more substantial increase in quality of life. Patients experiencing a 50% reduction in headache days demonstrated significant improvement in BDI scores. Conclusion GON blockade may be an effective option for short-term and long-term prophylaxis in the treatment of MM, reducing the frequency and severity of headaches and improving quality of life and psychological state. Further research with larger patient cohorts and placebo-controlled trials is necessary to validate these findings.

Lu Yu, Xueying Wang, Tri H. Doan et al.

Abstract Background Alzheimer's disease (AD) is characterized by amyloid-beta (Aβ) accumulation, leading to the formation of neurotoxic soluble oligomers (AβOs) that impair calcium homeostasis in neurons and astrocytes. Aducanumab, a fully human monoclonal antibody targeting aggregated Aβ, has been approved for AD treatment due to its ability to reduce amyloid plaque burden. However, its specificity toward different AβO species and its functional impact on calcium homeostasis remain unclear. Methods We investigated aducanumab's ability to recognize and immunodeplete low-molecular-weight (LMW) and high-molecular-weight (HMW) AβOs using three Aβ preparations: (1) transgenic conditioned media (TgCM) from cultured Tg2576 neurons, (2) synthetic Aβ42-derived diffusible ligands (ADDLs), and (3) TBS-soluble fractions from aged Tg2576 mouse brain. Size exclusion chromatography and ELISA were used to characterize AβO species. Multiphoton calcium imaging of neuron-astrocyte co-cultures was performed to assess the impact of aducanumab on AβO-induced calcium overload. Results Aducanumab preferentially bound and immunodepleted HMW AβOs in ADDLs and the TBS-soluble fraction of Tg2576 mouse brain extracts but did not recognize LMW AβOs in TgCM. In calcium imaging experiments, all three AβO preparations induced calcium overload in neuron-astrocyte co-cultures. Immunodepletion with aducanumab prevented calcium overload in cultures exposed to ADDLs and Tg2576 brain extracts but not in those treated with immunodepleted TgCM, indicating that aducanumab selectively neutralizes HMW AβOs. Conclusions Our findings demonstrate that aducanumab specifically targets HMW AβOs, mitigating their neurotoxic effects by restoring intracellular calcium homeostasis. These results provide mechanistic insight into aducanumab’s therapeutic action and support its potential role in modifying AD pathology by selectively neutralizing Aβ species.

Geoffroy C. B. Berthelot, Brigitte Gelein, Eric Meinadier et al.

The increase in the collection of biological data allows for the individual and longitudinal monitoring of hematological or urine biomarkers. However, identifying abnormal behavior in these biological sequences is not trivial. Moreover, the complexity of the biological data (correlation between biomarkers, seasonal effects, etc.) is also an issue. Z-score methods can help assess the abnormality in these longitudinal sequences while capturing some features of the biological complexity. This work details a statistical framework for handling biological sequences using three custom Z-score methods in the intra-individual variability scope. These methods can detect abnormal samples in the longitudinal sequences with respect to the seasonality, chronological time or correlation between biomarkers. One of these methods is an extension of one custom Z-score method to the Gaussian linear model, which allows for including additional variables in the model design. We illustrate the use of the framework on the longitudinal data of 3,936 professional soccer players (5 biomarkers) and 1,683 amateur or professional cyclists (10 biomarkers). The results show that a particular Z-score method, designed to detect a change in a series of consecutive observations, measured a high proportion of abnormal values (more than three times the false positive rate) in the ferritin and IGF1 biomarkers for both data sets. The proposed framework and methods could be applied in other contexts, such as the clinical patient follow-up in monitoring abnormal values of biological markers. The methods are flexible enough to include more complicated biological features, which can be directly incorporated into the model design.

Jia Ma, Jia Ma, Zhidong Zheng et al.

BackgroundEncephalitis associated with antibodies against the N-methyl-D-aspartate receptor (NMDAR) results in a distinctive neuro-psychiatric syndrome. It has been reported that the serum phenylalanine-tyrosine (Phe/Tyr) ratio increases during infection. However, the connection between phenylalanine-tyrosine metabolism and psychiatric symptoms remains unclear.MethodsWe enrolled 24 individuals with anti-NMDAR encephalitis and 18 individuals with non-inflammatory neurological diseases (OND). Chromatography was used to measure serum levels of phenylalanine and tyrosine. Serum and cerebrospinal fluid (CSF) TNF-α levels were obtained from the clinical database. The modified Rankin Scale (mRS) score and Glasgow Coma Scale (GCS) score were recorded during the acute phase. The area under the curve (AUC) of the receiver operating characteristic curve was used to assess prediction efficacy.ResultsIn NMDAR patients, levels of serum Phe and the ratio of serum Phe/Tyr were higher compared to OND patients. The serum Phe/Tyr ratio was also elevated in NMDAR patients with psychiatric syndrome. Furthermore, serum Phe and Tyr levels were correlated with inflammatory indexes.ConclusionThe serum Phe/Tyr ratio is elevated in NMDAR patients with psychiatric syndrome and is associated with severity. Therefore, the serum Phe/Tyr ratio may serve as a potential prognostic biomarker.

Zelin Qiu, Jianjun Gu, Dingding Yao et al.

The spatial auditory attention decoding (Sp-AAD) technology aims to determine the direction of auditory attention in multi-talker scenarios via neural recordings. Despite the success of recent Sp-AAD algorithms, their performance is hindered by trial-specific features in EEG data. This study aims to improve decoding performance against these features. Studies in neuroscience indicate that spatial auditory attention can be reflected in the topological distribution of EEG energy across different frequency bands. This insight motivates us to propose Prototype Training, a neuroscience-inspired method for Sp-AAD. This method constructs prototypes with enhanced energy distribution representations and reduced trial-specific characteristics, enabling the model to better capture auditory attention features. To implement prototype training, an EEGWaveNet that employs the wavelet transform of EEG is further proposed. Detailed experiments indicate that the EEGWaveNet with prototype training outperforms other competitive models on various datasets, and the effectiveness of the proposed method is also validated. As a training method independent of model architecture, prototype training offers new insights into the field of Sp-AAD.

Takashi Inagaki, Akari Kato, Koichi Takahashi et al.

The use of laboratory automation by all researchers may substantially accelerate scientific activities by humans, including those in the life sciences. However, computer programs to operate robots should be written to implement laboratory automation, which requires technical knowledge and skills that may not be part of a researcher's training or expertise. In the last few years, there has been remarkable development in large language models (LLMs) such as GPT-4, which can generate computer codes based on natural language instructions. In this study, we used LLMs, including GPT-4, to generate scripts for robot operations in biological experiments based on ambiguous instructions. GPT-4 successfully generates scripts for OT-2, an automated liquid-handling robot, from simple instructions in natural language without specifying the robotic actions. Conventionally, translating the nuances of biological experiments into low-level robot actions requires researchers to understand both biology and robotics, imagine robot actions, and write robotic scripts. Our results showed that GPT-4 can connect the context of biological experiments with robot operation through simple prompts with expert-level contextual understanding and inherent knowledge. Replacing robot script programming, which is a tedious task for biological researchers, with natural-language LLM instructions that do not consider robot behavior significantly increases the number of researchers who can benefit from automating biological experiments.

Minsu Kim, Federico Berto, Sungsoo Ahn et al.

We study the problem of optimizing biological sequences, e.g., proteins, DNA, and RNA, to maximize a black-box score function that is only evaluated in an offline dataset. We propose a novel solution, bootstrapped training of score-conditioned generator (BootGen) algorithm. Our algorithm repeats a two-stage process. In the first stage, our algorithm trains the biological sequence generator with rank-based weights to enhance the accuracy of sequence generation based on high scores. The subsequent stage involves bootstrapping, which augments the training dataset with self-generated data labeled by a proxy score function. Our key idea is to align the score-based generation with a proxy score function, which distills the knowledge of the proxy score function to the generator. After training, we aggregate samples from multiple bootstrapped generators and proxies to produce a diverse design. Extensive experiments show that our method outperforms competitive baselines on biological sequential design tasks. We provide reproducible source code: \href{https://github.com/kaist-silab/bootgen}{https://github.com/kaist-silab/bootgen}.

Anat Biegon

Published epidemiological studies of traumatic brain injury (TBI) of all severities consistently report higher incidence in men. Recent increases in the participation of women in sports and active military service as well as increasing awareness of the very large number of women who sustain but do not report TBI as a result of intimate partner violence (IPV) suggest that the number of women with TBI is significantly larger than previously believed. Women are also grossly under-represented in clinical and natural history studies of TBI, most of which include relatively small numbers of women, ignore the role of sex- and age-related gonadal hormone levels, and report conflicting results. The emerging picture from recent studies powered to detect effects of biological sex as well as age (as a surrogate of hormonal status) suggest young (i.e., premenopausal) women are more likely to die from TBI relative to men of the same age group, but this is reversed in the 6th and 7th decades of life, coinciding with postmenopausal status in women. New data from concussion studies in young male and female athletes extend this finding to mild TBI, since female athletes who sustained mild TBI are significantly more likely to report more symptoms than males. Studies including information on gonadal hormone status at the time of injury are still too scarce and small to draw reliable conclusions, so there is an urgent need to include biological sex and gonadal hormone status in the design and analysis of future studies of TBI.

M. Suárez-Gómez, S.S. Sánchez Rus

Introduction It is knowed the relationship between psychological problems and cardiovascular disease. Pychological alterations can cause cardiovascular diseases, and a cardiovascular event can trigger psychological alterations. Objectives The aim was to present a clinical case about a young man with cardiovascular alterations and depressive symptoms and to analyze the role played by cardiovascular drugs, psychoactive drugs, and their interactions. Methods We present the clinical case and search the relation between cardiovascular disease and depressive symptoms and treatment at scientific literature of last five years. Results A 38-year-old man comes to the emergency room with symptoms of palpitations, fatigue and shortness of breath for 2 weeks. An electrocardiogram is performed showing premature ventricular beats. The patient reports that he is sadder recently due to the loss of work, for which he is prescribed sertraline 50 mg daily and is referred to cardiology. No medical history or consumption of alcohol, tobacco or other toxins. The cardiologist requests ergometry, echocardiography, and Holter monitoring, resulting in all normal tests, with no evidence of ischemia. Bisoprolol 2.5 mg daily is prescribed and sertraline 50 mg daily is maintained. After two months, the patient reports feeling better in spirit. The control electrocardiogram is normal and the patient reports disappearance of palpitations. You are referred to your family doctor. Conclusions Elevation of cortisol, platelet hyperactivity, and alteration in heart rate variability were found in depressives. The SSRIs would be the ones of choice. Dual serotonin and noraderaline reuptake inhibitors should be avoided. Other atypical drugs such as bupropion or trazodone should be considered. Disclosure No significant relationships.

Naonori Yasuma, Sosei Yamaguchi, Makoto Ogawa et al.

Abstract Aims The purpose of this study was to retrospectively investigate care difficulties experienced by caregivers of people with schizophrenia during COVID‐19 pandemic lockdowns in Japan (April 7‐May 25, 2020) and examine associations between these care difficulties during lockdowns and daily caregiver burden. Methods Data were collected from 132 participants of the LINE Schizophrenia Family Association using an online survey. Results Caregivers were mostly concerned about who would care for people with schizophrenia if caregivers become infected with COVID‐19. A significant association was found between higher daily caregiver burden and more difficult care experiences during COVID‐19 pandemic lockdowns (B = 0.58, 95% confidence interval, 0.40‐0.75, P < .01, adjusted R‐squared = .34). Conclusions Further studies and supports for caregivers of people with schizophrenia are needed.

Seyhan Temtek Guner, Ozden Sukran Uneri, Ebru Sekmen et al.

Objective: There are studies showing that there is a significant relationship between ADHD and obesity. However the number of studies conducted on this topic is limited in our country. It is aimed to evaluate obesity frequency, distribution of psychiatric comorbidity and food addiction in children and adolescents with ADHD who applied to our outpatient clinic. Methods: Our sample size was planned to represent Ankara city and power analysis revealed that a sample of 369 individuals would be sufficient for the representation. Our sample consisted of 400 children aged between 8-16 years who applied to our clinic between June 15, 2016 and June 15, 2017 and diagnosed as ADHD. All cases were administered a semi-structured clinical assessment interview (K-SADS-PL) and a sociodemographic data form. Body mass index (BMI) of all subjects was calculated. The Conners Parent Rating Scale, The Conners Teacher Rating Scale and the Yale Food Addiction Scale for Children (YFAS-C) were used. According to age and sex, weight percentiles between 85-94 percentiles was defined as overweight, &#8805;95 percentile was defined as obese. SPSS 17.0 was used for statistical analysis, p [PBS 2021; 11(2.000): 104-114]

Qiu‐Lin Wang, Ting‐Ting Li, Chang‐Le Fang et al.

Abstract This study aimed to explore the possible target and mechanism of the wheel treadmill (WTM) test for motor function recovery of spinal cord injury (SCI). Rats were divided into sham, control and WTM groups to establish an SCI mode. Rats in the WTM group were trained on the WTM test, and Basso–Beattie–Bresnahan (BBB) scores were determined. The samples were collected, and mRNA sequencing was conducted to determine the changes in gene expression. The coexpressed genes were screened to construct a protein–protein interaction (PPI), followed by the Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology function enrichment analysis, and the differentially expressed genes (DEGs) volcano map and hub gene expression heat map were constructed using R language. The BBB scores in the control and WTM groups increased with time, with the WTM group scoring higher than the control group. The results of rat spinal cord tissue sequencing showed that a total of 1679 DEGs were screened in the sham and control groups; 928 DEGs and 731 overlapping genes were screened in the WTM and control groups. The key genes were identified by PPI analysis. One hundred and thirty‐three genes were found to be overlapping by combined analysis of spinal cord sequencing data and BBB scores of rats at Week 7. The top 10 DEGs from high to low were Tyrobp, Rac2, Cd68, C1qb, Aif1, Cd74, Spi1, Fcer1g, RT1‐DA, and Ccl4. The terms with the highest enrichment scores were microglia‐mediated positive regulation of cytotoxicity and major histocompatibility complex class II protein complexes. Treatment with the WTM test promotes recovery of motor function after SCI in rats by modulating intercellular communication and immune function.

Kentaro Kurumada, Atsuhiko Sugiyama, Shigeki Hirano et al.

Pareidolia is a visual illusion of meaningful objects that arise from ambiguous forms embedded in visual scenes. Previous studies showed that pareidolias are frequently observed in patients with Parkinson’s disease (PD) as well as dementia with Lewy bodies. However, whether pareidolias are useful for differentiating PD from other neurodegenerative parkinsonism disorders including multiple system atrophy (MSA) is unclear. The noise pareidolia test (NPT) was performed in 40 and 48 patients with PD and MSA, respectively. A receiver operating characteristic (ROC) curve analysis was used to evaluate sensitivity and specificity. Results of neuropsychological tests were also compared between patients with PD with and without pareidolias. Visual hallucinations were present in none of the subjects. Pareidolic response in the NPT was observed in 47.5% and 18.8% of patients with PD and MSA, respectively. The number of pareidolic responses in patients with PD was significantly larger compared with patients with MSA (P=0.001). ROC curve analyses showed the sensitivity and specificity at 33% and 98%, respectively. Among patients with PD, those with pareidolias demonstrated higher State-Trait Anxiety Inventory-state (P=0.044) and State-Trait Anxiety Inventory-trait (P=0.044) than those without pareidolias. Pareidolias can be found in patients with PD without visual hallucinations, and the pareidolia test may be a highly specific test for differentiating PD from MSA. Thus, anxiety may be associated with pareidolias in patients with PD.

Tomasz Cholewinski, Diana Pereira, Matthijs Moerland et al.

Major depressive disorder (MDD) is a multifactorial psychiatric disorder with obscure pathophysiology. A biomarker-based approach in combination with standardized interview-based instruments is needed to identify MDD subtypes and novel therapeutic targets. Recent findings support the impairment of the mammalian target of rapamycin complex 1 (mTORC1) in MDD. No well-established biomarkers of mTORC1 disease- and treatment-modulated activity are currently available for use in early phase antidepressant drug (AD) development. This review aims to summarize biomarkers of mTORC1 activity in MDD and to suggest how these could be implemented in future early clinical trials on mTORC1 modulating ADs. Therefore, a PubMed-based narrative literature review of the mTORC1 involvement in MDD was performed. We have summarized recent pre-clinical and clinical findings linking the MDD to the impaired activity of several key biomarkers related to mTORC1. Also, cases of restoration of these impairments by classical ADs and novel fast-acting investigational ADs are summarized. The presented biomarkers may be used to monitor pharmacological effects by novel rapid-acting mTORC1-targeting ADs. Based on findings in the peripheral blood mononuclear cells, we argue that those may serve as an ex vivo model for evaluation of mTORC1 activity and propose the use of the summarized biomarkers for this purpose. This could both facilitate the selection of a pharmacodynamically active dose and guide future early clinical efficacy studies in MDD. In conclusion, this review provides a blueprint for the rational development of rapid-acting mTORC1-targeting ADs.

Pierre V Baudin, Victoria T Ly, Pattawong Pansodtee et al.

A low cost remote imaging platform for biological applications was developed. The "Picroscope" is a device that allows the user to perform longitudinal imaging studies on multi-well cell culture plates. Here we present the network architecture and software used to facilitate communication between modules within the device as well as external cloud services. A web based console was created to control the device and view experiment results. Post processing tools were developed to analyze captured data in the cloud. The result is a platform for controlling biological experiments from outside the lab.

Yasaman Malekizadeh, Gareth Williams, Mark Kelson et al.

Abstract Background Stroke/thromboembolic events, infections, and death are all significantly increased by antipsychotics in dementia but little is known about why they can be harmful. Using a novel application of a drug repurposing paradigm, we aimed to identify potential mechanisms underlying adverse events. Methods Whole transcriptome signatures were generated for SH‐SY5Y cells treated with amisulpride, risperidone, and volinanserin using RNA sequencing. Bioinformatic analysis was performed that scored the association between antipsychotic signatures and expression data from 415,252 samples in the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) repository. Results Atherosclerosis, venous thromboembolism, and influenza NCBI GEO‐derived samples scored positively against antipsychotic signatures. Pathways enriched in antipsychotic signatures were linked to the cardiovascular and immune systems (eg, brain derived neurotrophic factor [BDNF], platelet derived growth factor receptor [PDGFR]‐beta, tumor necrosis factor [TNF], transforming growth factor [TGF]‐beta, selenoamino acid metabolism, and influenza infection). Conclusions These findings for the first time mechanistically link antipsychotics to specific cardiovascular and infectious diseases which are known side effects of their use in dementia, providing new information to explain related adverse events.

Valerie L. Tryon, Phillip M. Baker, Jeffrey M. Long et al.

Normative aging is known to affect how decisions are made in risky situations. Although important individual variability exists, on average, aging is accompanied by greater risk aversion. Here the behavioral and neural mechanisms of greater risk aversion were examined in young and old rats trained on an instrumental probability discounting task. Consistent with the literature, old rats showed greater discounting of reward value when the probability of obtaining rewards dropped below 100%. Behaviorally, reward magnitude discrimination was the same between young and old rats, and yet these same rats exhibited reduced sensitivity to positive, but not negative, choice outcomes. The latter behavioral result was congruent with additional findings that the aged ventral tegmental neurons (including dopamine cells) were less responsive to rewards when compared to the same cell types recorded from young animals. In sum, it appears that reduced responses of dopamine neurons to rewards contribute to aging-related changes in risky decisions.

Ryan Hays, Matcheri Keshavan, Hannah Wisniewski et al.

Background Symptoms of serious mental illness are multidimensional and often interact in complex ways. Generative models offer value in elucidating the underlying relationships that characterise these networks of symptoms. Aims In this paper we use generative models to find unique interactions of schizophrenia symptoms as experienced on a moment-by-moment basis. Method Self-reported mood, anxiety and psychosis symptoms, self-reported measurements of sleep quality and social function, cognitive assessment, and smartphone touch screen data from two assessments modelled after the Trail Making A and B tests were collected with a digital phenotyping app for 47 patients in active treatment for schizophrenia over a 90-day period. Patients were retrospectively divided up into various non-exclusive subgroups based on measurements of depression, anxiety, sleep duration, cognition and psychosis symptoms taken in the clinic. Associated transition probabilities for the patient cohort and for the clinical subgroups were calculated using state transitions between adjacent 3-day timesteps of pairwise survey domains. Results The three highest probabilities for associated transitions across all patients were anxiety-inducing mood (0.357, P < 0.001), psychosis-inducing mood (0.276, P < 0.001), and anxiety-inducing poor sleep (0.268, P < 0.001). These transition probabilities were compared against a validation set of 17 patients from a pilot study, and no significant differences were found. Unique symptom networks were found for clinical subgroups. Conclusions Using a generative model using digital phenotyping data, we show that certain symptoms of schizophrenia may play a role in elevating other schizophrenia symptoms in future timesteps. Symptom networks show that it is feasible to create clinically interpretable models that reflect the unique symptom interactions of psychosis-spectrum illness. These results offer a framework for researchers capturing temporal dynamics, for clinicians seeking to move towards preventative care, and for patients to better understand their lived experience.

Konrad P. Kording, Gunnar Blohm, Paul Schrater et al.

Within computational neuroscience, informal interactions with modelers often reveal wildly divergent goals. In this opinion piece, we explicitly address the diversity of goals that motivate and ultimately influence modeling efforts. We argue that a wide range of goals can be meaningfully taken to be of highest importance. A simple informal survey conducted on the Internet confirmed the diversity of goals in the community. However, different priorities or preferences of individual researchers can lead to divergent model evaluation criteria. We propose that many disagreements in evaluating the merit of computational research stem from differences in goals and not from the mechanics of constructing, describing, and validating models. We suggest that authors state explicitly their goals when proposing models so that others can judge the quality of the research with respect to its stated goals.