Weiting Chen, Weiting Chen, Xiaoshuang Jiang
et al.
BackgroundTracheostomy is common in traumatic cervical spinal cord injury (TCSCI) because of respiratory complications, yet objective tools to estimate individual risk remain limited.MethodsIn this single-center retrospective cohort at the Second Affiliated Hospital, Zhejiang University School of Medicine, we enrolled 308 consecutive ICU admissions with TCSCI (January 2018–March 2023) and randomly split the cohort 7:3 (outcome-stratified) into training (n = 215) and validation (n = 93) sets. Candidate admission predictors were screened with Least Absolute Shrinkage and Selection Operator and then entered into multivariable logistic regression to construct a nomogram. Model performance included discrimination (AUC with bootstrap 95% CIs, 2,000 resamples), calibration (intercept, slope, Brier), and decision curve analysis (DCA). A prespecified clinical threshold of 0.30 was used to summarize sensitivity and specificity.ResultsFive independent predictors were retained—smoking history, thoracic injury, BMI ≥ 25 kg/m2, cervical dislocation, and ASIA grade (A vs. B-D). The model showed strong discrimination (AUC 0.844, 95% CI 0.788–0.896 in training; 0.903, 95% CI 0.823–0.966 in validation) and good calibration. At the 0.30 threshold, performance was Sensitivity 0.781/Specificity 0.725 (training) and Sensitivity 0.812/Specificity 0.852 (validation); DCA demonstrated greater net benefit than “treat all/none” across threshold 0.10–0.70.ConclusionA parsimonious, five-factor nomogram based on routine admission data provides accurate, clinically interpretable stratification of tracheostomy risk in TCSCI. Clear reporting of ASIA coding and a prespecified decision threshold enhance bedside usability. Prospective, multi-center external validation is warranted.
Sandy C. Simões, Livia N. Amorim, Yasmim A. Serra
et al.
IntroductionStudies suggest that serotonin (5-HT) plays an important role in alcohol use disorder (AUD). While several receptor subtypes modulate the role of 5-HT in AUD, evidence suggests that 5-HT2A and 5-HT2C receptors may be directly involved in alcohol drinking due to their interaction with the mesolimbic dopaminergic system. The aim of the present study was to investigate the effects of 5-HT2A and 5-HT2C antagonists, alone or in combination, on the acquisition and expression (i.e., return to alcohol drinking after a period of abstinence/treatment) of voluntary alcohol drinking in male mice.MethodsAnimals had intermittent access to alcohol (10% v/v) in a two-bottle choice procedure for 30 days (acquisition), and were then submitted to alcohol re-exposure sessions after periods of abstinence. Vehicle, the 5-HT2A receptor antagonist M100907 (M100, 1 mg/kg) and/or the 5-HT2C receptor antagonist SB242084 (SB, 1 mg/kg) were administered either prior to acquisition (Experiment 1) or during the abstinence period preceding re-exposure sessions (Experiment 2). During re-exposure tests, animals were submitted to the same conditions as during acquisition, with no treatments prior to those sessions.ResultsOur findings show that combined treatment with 5-HT2A and 5-HT2C antagonists, but not treatment with the antagonists separately, reduced alcohol drinking and preference when administered immediately before acquisition (Experiment 1). Combined treatment with 5-HT2A and 5-HT2C antagonists after the establishment of voluntary alcohol drinking did not alter the expression of drinking behavior (Experiment 2). On the other hand, while post-acquisition treatment with a 5-HT2A antagonist alone decreased alcohol intake and preference during re-exposure, co-administration of a 5-HT2C antagonist blocked these effects.DiscussionOur findings suggest that 5-HT2A and 5-HT2C receptors differentially modulate the acquisition and expression of voluntary alcohol drinking in mice.
IntroductionExposure to potentially morally injurious events (PMIEs) has been found to contribute to mental health difficulties (MHD). However, research on PMIE exposure and its consequences among teachers is scant. In this study, we aimed to narrow this gap by examining the associations between teachers’ exposure to PMIEs and measures of depression, anxiety, burnout, and intention to leave the profession. Furthermore, we examined the mediating role of expressions of moral injury (i.e., shame and guilt) in these associations.MethodA sample of 253 Israeli teachers (186 female, 73%) aged 23-66 (Mage = 44, SD = 10.36) completed validated self-report questionnaires assessing the study variables.ResultsThe findings demonstrated that exposure to PMIEs contributed significantly to depression, anxiety, burnout, and intention to leave the profession. Through structural equation model analysis, we found that expressions of moral injury mediated the association between PMIEs and MHD.DiscussionThis study underscores the need to address moral injury among teachers as an essential factor for maintaining their mental health, as well as the overall sustainability of the educational system. Early screening and interventions are needed to identify and treat teachers at risk for MHD stemming from moral injury.
Antea D’Andrea, Pierpaolo Croce, Jordan O’Byrne
et al.
BackgroundThe investigation of mindfulness meditation practice, classically divided into focused attention meditation (FAM), and open monitoring meditation (OMM) styles, has seen a long tradition of theoretical, affective, neurophysiological and clinical studies. In particular, the high temporal resolution of magnetoencephalography (MEG) or electroencephalography (EEG) has been exploited to fill the gap between the personal experience of meditation practice and its neural correlates. Mounting evidence, in fact, shows that human brain activity is highly dynamic, transiting between different brain states (microstates). In this study, we aimed at exploring MEG microstates at source-level during FAM, OMM and in the resting state, as well as the complexity and criticality of dynamic transitions between microstates.MethodsTen right-handed Theravada Buddhist monks with a meditative expertise of minimum 2,265 h participated in the experiment. MEG data were acquired during a randomized block design task (6 min FAM, 6 min OMM, with each meditative block preceded and followed by 3 min resting state). Source reconstruction was performed using eLORETA on individual cortical space, and then parcellated according to the Human Connect Project atlas. Microstate analysis was then applied to parcel level signals in order to derive microstate topographies and indices. In addition, from microstate sequences, the Hurst exponent and the Lempel-Ziv complexity (LZC) were computed.ResultsOur results show that the coverage and occurrence of specific microstates are modulated either by being in a meditative state or by performing a specific meditation style. Hurst exponent values in both meditation conditions are reduced with respect to the value observed during rest, LZC shows significant differences between OMM, FAM, and REST, with a progressive increase from REST to FAM to OMM.DiscussionImportantly, we report changes in brain criticality indices during meditation and between meditation styles, in line with a state-like effect of meditation on cognitive performance. In line with previous reports, we suggest that the change in cognitive state experienced in meditation is paralleled by a shift with respect to critical points in brain dynamics.
Benjamin H. Andersen, Francisco M. R. Safara, Valeriia Grudtsyna
et al.
Collective cellular movement plays a crucial role in many processes fundamental to health, including development, reproduction, infection, wound healing, and cancer. The emergent dynamics that arise in these systems are typically thought to depend on how cells interact with one another and the mechanisms used to drive motility, both of which exhibit remarkable diversity across different biological systems. Here, we report experimental evidence of a universal feature in the patterns of flow that spontaneously emerges in groups of collectively moving cells. Specifically, we demonstrate that the flows generated by collectively moving dog kidney cells, human breast cancer cells, and by two different strains of pathogenic bacteria, all exhibit conformal invariance. Remarkably, not only do our results show that all of these very different systems display robust conformal invariance, but we also discovered that the precise form of the invariance in all four systems is described by the Schramm-Loewner Evolution (SLE), and belongs to the percolation universality class. A continuum model of active matter can recapitulate both the observed conformal invariance and SLE form found in experiments. The presence of universal conformal invariance reveals that the macroscopic features of living biological matter exhibit universal translational, rotational, and scale symmetries that are independent of the microscopic properties of its constituents. Our results show that the patterns of flows generated by diverse cellular systems are highly conserved and that biological systems can unexpectedly be used to experimentally test predictions from the theories for conformally invariant structures
A new scientific field is introduced and discussed, named cybernetical neuroscience, which studies mathematical models adopted in computational neuroscience by methods of cybernetics -- the science of control and communication in a living organism, machine and society. It also considers the practical application of the results obtained when studying mathematical models. The main tasks and methods, as well as some results of cybernetic neuroscience are considered.
Alyssa M Adams, Eliott Jacopin, Praful Gagrani
et al.
While fields like Artificial Life have made huge strides in quantifying the mechanisms that distinguish living systems from non-living ones, particular mechanisms remain difficult to reproduce in silico. Known as open-endedness, we've been successful in finding mechanisms that generate new states, but have been less successful in finding mechanisms that generate new rules. Here, we weigh whether or not analyzing the effects of internal and external system constraints on a system's dynamics would be a fruitful avenue to understanding open-endedness. We discuss the connection between physical constraints and the ways that the system can physically reach possible states while those constraints are present. It seems that the physical constraints that define biological objects (and dynamics) are maintained by dynamics that occur from within the system. This is in opposition to current modeling approaches where system constraints are maintained externally. We suggest that constraints can be characterized as variables whose values are either completely conserved, quasi-conserved, or conditionally conserved. Regardless of whether or not a constrained variable is a part of the biological object or present in the object's environment, we discuss how the accessible system states under that constraint can lead to local, emergent conservation laws (rules), with examples. Finally, we discuss the possible benefits of formally understanding how system constraints that emerge from within a system lead to system dynamics that can be characterized as new, emergent rules -- particularly for artificial intelligence, hybrid life, embodiment, astrobiology, and more. Understanding how new, local rules might emerge from within the system is crucial for understanding how open-ended systems continually discover new update rules, in addition to continually discovering new states.
Mahmoud H. Nassar, Elsayed A. Tageldin, Osama A. Ragab
Abstract Background Essential tremor (ET) is a prevalent movement disorder that may be linked to neurodegenerative changes. It is marked by a mix of motor and non-motor symptoms, which include disturbances in the autonomic nervous system. Aim of the study: We aimed to assess autonomic dysfunction in individuals with essential tremor. Thirty patients with essential tremor (Group 1) and 30 age and sex-matched healthy subjects as the control group (Group 2) were recruited. Comprehensive medical and neurological examinations were conducted on all participants, followed by electrophysiological assessments of autonomic function, including heart rate variability (HRV) tests (E/I ratio, Valsalva ratio, 30:15 ratio), adrenergic tests (blood pressure responses to active standing and sustained hand grip), and sympathetic skin response (SSR) tests. Finally, the results of these tests were classified according to the Ewing classification of autonomic failure. Results: The study revealed significant differences between ET patients and the control group. Heart rate variability tests showed a marked difference between the groups. Adrenergic tests, measuring sympathetic innervation, also displayed a significant difference. The sudomotor function test exhibited noteworthy differences in onset latencies and amplitudes in the palm and sole, with ET patients showing prolonged onset latencies and decreased amplitudes. Moreover, the study found a significant correlation between disease severity and autonomic function test results and the Ewing score. Conclusion: The study highlights the presence of autonomic dysfunction in essential tremor patients, with disease severity being associated with the level of autonomic affection, as evidenced by various autonomic function tests and the Ewing score.
Elena Martín-González, Manuela Olmedo-Córdoba, Ángeles Prados-Pardo
et al.
IntroductionCompulsive behavior has been proposed as a transdiagnostic trait observed in different neuropsychiatric disorders, such as obsessive-compulsive disorder, autism, and schizophrenia. Research Domain Criteria (RDoC) strategy could help to disentangle the neuropsychological basis of compulsivity for developing new therapeutic and preventive approaches. In preclinical research, the selection of high-drinker (HD) vs. low-drinker (LD) animals by schedule-induced polydipsia (SIP) is considered a putative model of compulsivity, which includes a well-differentiated behavioral pattern.MethodsThe purpose of this research was to assess the cognitive control and the negative valence system domains in a phenotype of compulsive HD rats. After the selection of animals as HD or LD, we assessed behavioral inflexibility by probabilistic spatial reversal learning (PSRL), motor and cognitive impulsivity by variable delay-to-signal (VDS), and risky decision-making by rodent gambling task (rGT).ResultsHD rats performed fewer reversals and showed less probability of pressing the same lever that was previously reinforced on PSRL, more premature responses after the exposure to longer delays on VDS, and more disadvantageous risky choices on rGT. Moreover, HD animals performed more perseverative responses under the punishment period on rGT.DiscussionThese results highlight that HD compulsive phenotype exhibits behavioral inflexibility, insensitivity to positive feedback, waiting impulsivity, risky decision-making, and frustrative non-reward responsiveness. Moreover, these findings demonstrate the importance of mapping different behavioral domains to prevent, treat, and diagnose compulsive spectrum disorders correctly.
Introduction
COVID19 lockdown is having a significant impact on mental health, patients with eating disorders (ED) are particularly vulnerable.
Objectives
1) To explore changes in eating and other psychological features due to confinement in patients with ED from various European and Asian countries; and 2) to assess differences related to diagnostic subtypes, age and geography.
Methods
The sample comprised 829 participants, diagnosed with an ED according to DSM-5 criteria from specialized ED units in Europe and Asia. Participants were assessed using the COVID19 Isolation Scale (CIES).
Results
On one hand, patients with Binge Eating Disorder experienced the highest impact on weight and ED symptoms due to confinement. Together with subjects diagnosed with Other Specified Feeding and Eating Disorders (OFSED), they also experienced a deterioration in general psychological state. On the other hand, there was less symptomatic impact on people with Bulimia Nervosa or Anorexia Nervosa and asian and younger individuals appeared to be more resilient in this situation.
Conclusions
The impact of COVID varied by cultural context and individual variation in age and form of illness. Services may need to target preventive measures and adapting therapeutic approaches for the most vulnerable patients.
Disclosure
No significant relationships.
Melinda Hersey, Melissa Reneaux, Shane N. Berger
et al.
Abstract Background Stress-induced mental illnesses (mediated by neuroinflammation) pose one of the world’s most urgent public health challenges. A reliable in vivo chemical biomarker of stress would significantly improve the clinical communities’ diagnostic and therapeutic approaches to illnesses, such as depression. Methods Male and female C57BL/6J mice underwent a chronic stress paradigm. We paired innovative in vivo serotonin and histamine voltammetric measurement technologies, behavioral testing, and cutting-edge mathematical methods to correlate chemistry to stress and behavior. Results Inflammation-induced increases in hypothalamic histamine were co-measured with decreased in vivo extracellular hippocampal serotonin in mice that underwent a chronic stress paradigm, regardless of behavioral phenotype. In animals with depression phenotypes, correlations were found between serotonin and the extent of behavioral indices of depression. We created a high accuracy algorithm that could predict whether animals had been exposed to stress or not based solely on the serotonin measurement. We next developed a model of serotonin and histamine modulation, which predicted that stress-induced neuroinflammation increases histaminergic activity, serving to inhibit serotonin. Finally, we created a mathematical index of stress, S i and predicted that during chronic stress, where S i is high, simultaneously increasing serotonin and decreasing histamine is the most effective chemical strategy to restoring serotonin to pre-stress levels. When we pursued this idea pharmacologically, our experiments were nearly identical to the model’s predictions. Conclusions This work shines the light on two biomarkers of chronic stress, histamine and serotonin, and implies that both may be important in our future investigations of the pathology and treatment of inflammation-induced depression.
In Parkinson’s disease (PD) functional changes in the brain occur years before significant cognitive symptoms manifest yet core large-scale networks that maintain cognition and predict future cognitive decline are poorly understood. The present study investigated internetwork functional connectivity of visual (VN), anterior and posterior default mode (aDMN, pDMN), left/right frontoparietal (LFPN, RFPN), and salience (SN) networks in 63 cognitively normal PD (PDCN) and 43 healthy controls who underwent resting-state functional MRI. The functional relevance of internetwork coupling topologies was tested by their correlations with baseline cognitive performance in each group and with 2-year cognitive changes in a PDCN subsample. To disentangle heterogeneity in neurocognitive functioning, we also studied whether α-synuclein (SNCA) and microtubule-associated protein tau (MAPT) variants alter internetwork connectivity and/or accelerate cognitive decline. We found that internetwork connectivity was largely preserved in PDCN, except for reduced pDMN-RFPN/LFPN couplings, which correlated with poorer baseline global cognition. Preserved internetwork couplings also correlated with domain-specific cognition but differently for the two groups. In PDCN, stronger positive internetwork coupling topologies correlated with better cognition at baseline, suggesting a compensatory mechanism arising from less effective deployment of networks that supported cognition in healthy controls. However, stronger positive internetwork coupling topologies typically predicted greater longitudinal decline in most cognitive domains, suggesting that they were surrogate markers of neuronal vulnerability. In this regard, stronger aDMN-SN, LFPN-SN, and/or LFPN-VN connectivity predicted longitudinal decline in attention, working memory, executive functioning, and visual cognition, which is a risk factor for dementia. Coupling strengths of some internetwork topologies were altered by genetic variants. PDCN carriers of the SNCA risk allele showed amplified anticorrelations between the SN and the VN/pDMN, which supported cognition in healthy controls, but strengthened pDMN-RFPN connectivity, which maintained visual memory longitudinally. PDCN carriers of the MAPT risk allele showed greater longitudinal decline in working memory and increased VN-LFPN connectivity, which in turn predicted greater decline in visuospatial processing. Collectively, the results suggest that cognition is maintained by functional reconfiguration of large-scale internetwork communications, which are partly altered by genetic risk factors and predict future domain-specific cognitive progression.
Amal M Alkhotani,1 Alaa M Alkhotani2 1Department of Medicine, Umm Al-Qura University, Makkah, 21955, Saudi Arabia; 2Department of Pathology, Umm Al-Qura University, Makkah, 21955, Saudi ArabiaCorrespondence: Amal M Alkhotani, Department of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia, Email amkhotani@uqu.edu.saBackground: Epilepsy is a neurological disorder characterized by a persistent propensity to generate recurring epileptic seizures. Young adults such as university students can bridge the gap and improve attitudes toward patients with epilepsy and reduce stigma. This study aims to assess the knowledge and attitude of university students in the city of Makkah about epilepsy.Methods: This cross-sectional descriptive study was carried out at main universities in the Makkah region of Saudi Arabia. The study was conducted after getting approval from Umm Al-Qura University’s ethics and research committee. A total of 394 participants were enrolled in the study, and a stratified random sampling (probability sampling) technique was used to select respondents.Results: The study included students with a mean age of 20.9 ± 4.6 (18– 28 years), 271 (68.8%) students were females, 374 (94.9%) of the students agreed that epilepsy is not contagious, and 215 (54.6%) refused the impact of epilepsy on patients’ marital status, relationships and fertility, respectively, 213 (54.1%) of the students reported that they feel scared to witness a seizure. About 334 (84.8%) respondents believed that epilepsy is an affliction, and 123 (31.2%) reported that they thought epilepsy was a supernatural phenomenon or black magic.Conclusion: The study concluded a satisfactory level of awareness among university students in Makkah related to dealing with patients with epilepsy. Further scientific studies will help build student’s positive attitudes through simulation programs and interventional studies.Keywords: people with epilepsy, stigma, epileptic seizures, Saudi community, neurological disorder
Neurosciences. Biological psychiatry. Neuropsychiatry, Neurology. Diseases of the nervous system
For understanding the biological effects of neutrons, predictions of the secondary charged particle distributions by neutron irradiation are needed in biophysical models. We have performed detailed Monte-Carlo simulations using the PHITS computer code of the the dose and fluence spectra of charged particles in the biological materials irradiated by neutron beams with energies below 10 MeV. We compare the results for two different neutron spectra used in radiobiology experiments; the spontaneous fission neutron spectrum of $^{252}$Cf, and a 4 MeV d-Be generated neutron spectrum. The results show that over 90% of the dose and fluence are from secondary protons, which are low energy (<2 MeV) and high LET, and indicate higher secondary charged particle fluence near the surface compared to the deep tissue regions in a mouse. It is also suggested that the different neutron sources considered result in largely similar types of secondary particles with modestly varying fluence distributions.
Simon Van Eyndhoven, Patrick Dupont, Simon Tousseyn
et al.
EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular ‘bridge’ between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response’s variability over brain regions. By analyzing interictal data from twelve patients, we show that the extracted source signatures provide a sensitive localization of the ictal onset zone (10/12). Moreover, complementary parts of the IOZ can be uncovered by inspecting those regions with the most deviant neurovascular coupling, as quantified by two entropy-like metrics of the hemodynamic response function waveforms (9/12). Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can assist the presurgical evaluation of epilepsy. We make all code required to perform the computations available at https://github.com/svaneynd/structured-cmtf.
La paracoccidioidomicosis (PMC) es una micosis endémica que afecta a diferentes regiones de América Central y América del Sur. Esta enfermedad es causada por el Paracoccidioides brasiliensis y por el Paracoccidioides lutzii. Su presentación clínica puede ser aguda, subaguda o crónica y afectar a diversos sistemas, incluido el sistema nervioso central. El compromiso pulmonar y el de mucosa suelen ser los más comunes. La neuroparacoccidioidomicosis (NPCM) se presenta hasta en un 25 % de los pacientes con PMC y puede ser clasificada como meníngea o pseudotumoral. Sus síntomas neurológicos pueden ir desde cefalea hasta déficit motor, dependiendo de la localización. El estudio del líquido cefalorraquídeo es inespecífico y el aislamiento microbiológico es muy raro. Las lesiones observadas en neuroimágenes pueden confundirse con otras infecciones micóticas o incluso tumores. El estudio histológico permite confirmar el diagnóstico. Para el tratamiento de la NPCM se puede utilizar trimetoprim-sulfametaxazol, anfotericina B y fluconazol. Algunos casos pueden requerir manejo quirúrgico.
Background: Delayed cerebral ischemia (DCI) is the main cause of death and disability after intracranial aneurysm rupture. Previous studies have shown that smoking can lead to DCI after intracranial aneurysm rupture. However, some recent studies have shown that nicotine, as the main ingredient of tobacco, can cause cerebral vasodilation. This view has led to a debate about the relationship between smoking and DCI. This study aims to determine the relationship between smoking and DCI.Methods: A systematic literature search was performed according to PRISMA guidelines. The Cochrane Library, Web of Science, PubMed, and Embase online databases were searched for studies published up to September 2020. All studies related to smoking and DCI were included in the analysis. The R and RevMan software were used for data analysis, and random or fixed model analysis was selected depending on the degree of heterogeneity. Publication bias was examined by using the Begg–Mazumdar test and using contour-enhanced funnel plots with trim method.Results: A total of eight original articles (12 cohorts) with 10,722 patients were included in this meta-analysis. There were statistically significant higher rates of DCI in the smoking group than in the non-smoking group (RRtotal = 1.16, 95%CI: 1.05–1.27). After heterogeneity among cohorts was removed by sensitivity analysis, there was still a statistically significant difference in the incidence of DCI between the smoking and non-smoking groups (RRtotal = 1.13, 95%CI: 1.07–1.20).Conclusions: Although the effects of nicotine as the main component of tobacco are unclear in terms of cerebral vessels, the present study suggests that smoking is a risk factor for DCI in patients with ruptured aneurysm.
A major challenge in both neuroscience and machine learning is the development of useful tools for understanding complex information processing systems. One such tool is probes, i.e., supervised models that relate features of interest to activation patterns arising in biological or artificial neural networks. Neuroscience has paved the way in using such models through numerous studies conducted in recent decades. In this work, we draw insights from neuroscience to help guide probing research in machine learning. We highlight two important design choices for probes $-$ direction and expressivity $-$ and relate these choices to research goals. We argue that specific research goals play a paramount role when designing a probe and encourage future probing studies to be explicit in stating these goals.