Abnormal Behavior Research Articles

Traumatic injury to the posterior fossa: a secondary analysis and description of case series from the NEXUS head injury dataset

Traumatic brain injuries involving the posterior fossa are rare and case reports indicate they often result in severe outcomes. We seek to describe characteristics and outcomes of traumatic posterior fossa injuries. We performed a planned secondary analysis of all patients with posterior fossa injuries enrolled in the NEXUS head computed tomography (CT) validation study dataset. The dataset includes prospectively collected data on all patients undergoing non-contrast cranial CT following blunt traumatic head injury from April 2006 to December 2015, at four emergency departments comprising community and university sites, as well as urban, suburban and rural settings in California (Antelope Valley Hospital, San Francisco General Hospital, UCLA Ronald Reagan Medical Center, UCSF Fresno Community Regional Medical Center). We classified each patient into one of three injury patterns: Type I-notable traumatic injuries primarily above the tentorium, with minimal posterior fossa involvement; Type II-notable traumatic injuries both above and within the posterior fossa; and Type III-notable traumatic injuries primarily within the posterior fossa. We extracted demographic data for each patient as well as physician assessments of the NEXUS head CT and Canadian Head CT rule clinical criteria, mechanisms of injury, patient outcomes, and the location and types of intracranial injuries sustained. Of 11,770 patients in the database, 184 (1.6%) had posterior fossa injuries on CT imaging. Mean age was 55.4 years (standard deviation 22.5 years, range 2-96 years); 131 (71.2%) were males. We identified 63 patients with Type I injuries, 87 with Type II injuries, and 34 Type III injuries. The most common mechanisms of injury were falls (41%), pedestrian vs automobile (15%), and motor vehicle collisions (13%). On presentation most patients had altered mental status (72%), abnormal behavior (53%), or a neurologic deficit (55%). The majority of individuals, 151 (82%), had clinically important injuries and 111 (60%) required neurosurgical intervention. The dispositions for the subjects included 52 deaths (28%), 49 (27%) patients discharged home, and 48 (26%) discharged to rehabilitation facilities. When compared to individuals with Type I and Type II injuries, patients with Type III injuries had lower mortality (6% vs 30% and 35%) and higher percentage of patients discharged home (60% vs 19% and 21%). Patients with Type I and II injury patterns (those that involve both the posterior fossa and supratentorium) experienced high mortality and disability. Patients with Type III injuries (isolated posterior fossa) had a better prognosis. None.

Intrusion Detection System Using Probabilistic Adaptive Learning

Abstract: Machine learning and deep learning techniques are widely used to evaluate intrusion detection systems (IDS) capable of rapidly and automatically recognizing and classifying cyber-attacks on networks and hosts. However, when destructive attacks are becoming more extensive, more challenges develop, needing a comprehensive response. Numerous intrusion detection datasets are publicly accessible for further analysis by the cybersecurity research community. The Intrusion Detection System (IDS) is an effective tool utilized in cybersecurity systems to detect and identify intrusion attacks. With the increasing volume of data generation, the possibility of various forms of intrusion attacks also increases. Feature selection is crucial and often necessary enhance performance. The structure of the dataset can impact the efficiency of the machine learning model. Furthermore, data imbalance can pose a problem, but sampling approaches can help mitigate it. With technological advancements, machine learning-based methods have emerged as the cornerstone of modern intrusion detection, enabling more precise identification of abnormal behaviors and potential intrusions by learning the patterns of normal network traffic. In response to these challenges, this paper introduces an innovative intrusion detection model that amalgamates the Probabilistic Adaptiv eLearning Network architecture.

Alzheimer Disease

Alzheimer's disease (AD) is typified by memory deficiencies that worsen with time, along with cognitive and behavioral abnormalities that eventually result in dementia. AD is one of the most difficult diseases to treat because of its prevalence, high cost of care, effects on patients and caregivers, and lack of mechanism-based therapies. The malfunction and loss of neurons in particular circuits and locations, especially in the populations of nerve cells supporting memory and cognition, causes the AD condition.The neuropathology of AD is characterized by intracellular and extracellular protein aggregation accumulations. In the neuronal perikarya and dystrophic neurites, abnormally phosphorylated tau forms paired helical filaments (PHFs) that combine to form neurofibrillary tangles (NFTs). The extracellular deposition of β-pleated assemblies of Aβ peptide, which result in widespread and neuritic senile plaques, is the second pathogenic hallmark.

Progress on early diagnosing Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects both cognition and non-cognition functions. The disease follows a continuum, starting with preclinical stages, progressing to mild cognitive and behavioral impairment, ultimately leading to dementia. Early detection of AD is crucial for better diagnosis and more effective treatment. However, the current AD diagnostic tests of biomarkers using cerebrospinal fluid and/or brain imaging are invasive or expensive, and mostly are still not able to detect early disease state. Consequently, there is an urgent need to develop new diagnostic techniques with higher sensitivity and specificity during the preclinical stages of AD. Various non-cognitive manifestations, including behavioral abnormalities, sleep disturbances, sensory dysfunctions, and physical changes, have been observed in the preclinical AD stage before occurrence of notable cognitive decline. Recent research advances have identified several biofluid biomarkers as early indicators of AD. This review focuses on these non-cognitive changes and newly discovered biomarkers in AD, specifically addressing the preclinical stages of the disease. Furthermore, it is of importance to explore the potential for developing a predictive system or network to forecast disease onset and progression at the early stage of AD.

Anomaly Detection for Video Surveillance

Anomaly detection in video surveillance is critical for identifying abnormal behaviours or events that deviate from typical patterns. This abstract explores various techniques used to detect anomalies in surveillance videos, including traditional methods like motion detection and background subtraction, as well as advanced approaches such as deep learning and anomaly scoring algorithms. By leveraging these techniques, surveillance systems can automatically detect suspicious activities such as trespassing, theft, or violence, enabling timely intervention and improved security measures. Highlighting the challenges in anomaly detection, such as dealing with complex scenes, occlusions and discusses ongoing research efforts to enhance the accuracy and efficiency of anomaly detection systems in real-world surveillance scenarios. Key Words: anomaly, suspicious, pattern, motion, detection, security measure

Novel insights into presenilin 1 mutation associated with a distinctive dementia phenotype and cotton wool plaques.

The mutations in the presenilin 1 gene (PSEN1) are the main cause of familial Alzheimer's disease. PSEN1 mutations affect amyloid-beta peptide production, which accumulates in the brain as senile plaque and cotton wool plaques (CWPs) and relates to other neurodegenerative disorders. Here we report the second case of the PSEN1 G266S mutation, which showed distinctive neuropathological features, including abundant CWPs. Lewy body pathology, and altered amyloid-beta production. Using the proband's samples, we performed genetic analysis of the PSEN1, APP, MAPT, and APOE genes, histopathological and immunohistochemical analysis of the brain tissue, and biochemical analysis of Aβ production in COS cells transfected with wild-type or mutant PSEN1. The patient presented with memory loss, abnormal behavior, and visual hallucinations. Brain scans showed reduced blood flow, mild atrophy, and white matter lesions. Genetic analysis revealed a heterozygous mutation at codon 266 (G266S) of PSEN1 and polymorphism of MAPT (Q230R). The brain had many CWPs, severe cerebral amyloid angiopathy (CAA), senile plaque, Lewy bodies, and neurites. Electron microscopy displayed myelinated fiber degeneration, mitochondrial damage, and amyloid fibrils in the white matter. The production level of Aβ42 in PSEN1 G266S-transfected cells significantly increased. Our findings suggest that the PSEN1 G266S mutation may cause a heterogeneous clinical and pathological phenotype, influenced by other genetic or environmental factors.

Salivary analysis to unveil the paradigma of stress of domestic horses reared in the wild

Horse welfare is the product of multiple factors, including behavioral and physiological adjustments to cope with stressful situation regarding environment and housing condition. Collectively, it is supposed that a horse kept in the wild has a lower level of stress than other housing system, and the aim of the present study was to investigate the level of stress in domestic horses reared in the wild and then moved to human controlled housing, through saliva analysis. Twelve clinically healthy Catria (Italian local breed) mares, usually reared in the wild, were moved into collective paddocks for a folkloric event. Saliva samples were obtained before and after the change of housing condition to evaluate stress biomarkers including salivary cortisol, salivary alpha-amylase, and butyrylcholinesterase (BChol). The mares were also scored using the Welfare Aggregation and Guidance (WAG) Tool to highlight the presence of abnormal behaviors. Despite the absence of differences in behavioral scores between wild and paddocks, salivary cortisol and BChol were found to be higher in the wild and lower when mares were moved to paddocks. The highest concentrations in stress biomarkers like salivary cortisol and BChol in the wild was unexpected, but the need for managing hierarchical relationships, and the exposure to feral animals, predators, and weather changes, might explain these findings. The overall results of the present study may provide further knowledge toward stress response in domesticated horses living in the wild moved to human controlled housing system.

Loss of function of FAM177A1, a Golgi complex localized protein, causes a novel neurodevelopmental disorder.

The function of FAM177A1 and its relationship to human disease is largely unknown. Recent studies have demonstrated FAM177A1 to be a critical immune-associated gene. One previous case study has linked FAM177A1 to a neurodevelopmental disorder in four siblings. We identified five individuals from three unrelated families with biallelic variants in FAM177A1. The physiological function of FAM177A1 was studied in a zebrafish model organism and human cell lines with loss-of-function variants similar to the affected cohort. These individuals share a characteristic phenotype defined by macrocephaly, global developmental delay, intellectual disability, seizures, behavioral abnormalities, hypotonia, and gait disturbance. We show that FAM177A1 localizes to the Golgi complex in mammalian and zebrafish cells. Intersection of the RNA-seq and metabolomic datasets from FAM177A1-deficient human fibroblasts and whole zebrafish larvae demonstrated dysregulation of pathways associated with apoptosis, inflammation, and negative regulation of cell proliferation. Our data sheds light on the emerging function of FAM177A1 and defines FAM177A1-related neurodevelopmental disorder as a new clinical entity.

C8-ceramide modulates microglia BDNF expression to alleviate postoperative cognition dysfunction via PKCδ/NF-κB signaling pathway.

Postoperative cognitive dysfunction (POCD) is a kind of serious postoperative complication in surgery with general anesthesia and it may affect patients' normal lives. Activated microglia are thought to be one of the key factors in the regulation of POCD process. Once activated, resident microglia change their phenotype and secrete kinds of cytokines to regulate inflammatory response in tissues. Among these secretory factors, brain-derived neurotrophic factor (BDNF) is considered to be able to inhibit inflammation response and protect nervous system. Therefore, the enhancement of BDNF expression derived from resident microglia is suggested to be potential treatment for POCD. In our study, we focused on the role of C8-ceramide (a kind of interventional drug) and assessed its regulatory effect on improving the expression of BDNF secreted from microglia to treat POCD. According to the results of our study, we observed that C8-ceramide stimulated primary microglia to up-regulate the expression of BDNF mRNA after being treated with lipopolysaccharide (LPS) in vitro. We proved that C8-ceramide had ability to effectively improve POCD of mice after being accepted carotid artery exposure and their abnormal behavior recovered better than that of mice from the surgery group. Furthermore, we also demonstrated that C8-ceramide enhanced the cognitive function of mice via the PKCδ/NF-κB signaling pathway. In general, our study has confirmed a potential molecular mechanism that led to the occurrence of POCD caused by surgery and provided a new clinical strategy to treat POCD.

Antidepressant effects of activation of infralimbic cortex via upregulation of BDNF and β-catenin in an estradiol withdrawal model.

Clinical and preclinical studies have demonstrated that estradiol withdrawal after delivery is one of important factors involved in the pathogenesis of postpartum depression (PPD). The infralimbic cortex (IL) is related to anxiety and mood disorders. Whether IL neurons mediate PPD is still unclear. This study was to observe the antidepressant effect and expression of BDNF and β-catenin in IL by allopregnanolone (ALLO) treatment or the selective activation or inhibition of IL neurons using a chemogenetic approach in a pseudopregnancy model of PPD. Administration of estradiol combined with progesterone and the abrupt withdrawal of estradiol simulated the pregnancy and early postpartum periods to induce depression in ovariectomized rats. The relative expression levels of β-catenin and BDNF were observed by western blotting. Immobility time was significantly increased in the forced swim test and open-arm movement was reduced in the elevated plus maze test in the estradiol-withdrawn rats. After ALLO treatment, the immobility time were lower and open-arm traveling times higher than those of the estradiol-withdrawn rats. Meanwhile, the expression level of BDNF or β-catenin in the IL was reduced significantly in estradiol-withdrawn rats, which was prevented by treatment with ALLO. The hM3Dq chemogenetic activation of pyramidal neurons in the IL reversed the immobility and open-arm travel time trends in the estradiol-withdrawal rat model, but chemogenetic inhibition of IL neurons failed to affect this. Upregulated BDNF and β-catenin expression and increased c-Fos in the basolateral amygdala were found following IL neuron excitation in model rats. Our results demonstrated that pseudopregnancy and estradiol withdrawal produced depressive-like behavior and anxiety. ALLO treatment or specific excitement of IL pyramidal neurons relieved abnormal behaviors and upregulated BDNF and β-catenin expression in the IL in the PPD model, suggesting that hypofunction of IL neurons may be involved in the pathogenesis of PPD.

"Witzelsucht". On the introduction and meaning of the term by Hermann Oppenheim in 1890 and its distinction from "moria"

Hermann Oppenheim (1858-1919) was a German neurologist without an academic career, who in his productive period around 1900 made aname for himself during his lifetime as amajor player in the history of German neurology with his many contributions to multiple sclerosis, syphilis and the controversial study of traumatic neurosis; however, it is almost unknown that in 1890 he introduced the term "witzelsucht", which is still used internationally today. Moritz Jastrowitz dealt with behavioral abnormalities due to frontal brain injuries 1year earlier and used the term "moria" for aform of mental disorder associated with akind of childish behavior and inappropriate jocularity. Oppenheim was critical of this and differentiated his "witzelsucht" from this. With this term he wanted to describe humoristic feeble-mindedness in a much narrower sense, which stands in striking contrast to the usual symptoms in cases of cerebral tumors. Oppenheim recognized the frontal brain, particularly the right brain, to be an important functional unit for humorous behavior. Modern research has confirmed that the processing of humor requires a complex interaction of multiple brain regions. Damage to the right frontal lobe or to connecting structures can lead to the disorder "witzelsucht". Whether asimultaneous damage to the left hemisphere must be present or if this is dependent on the individual dominant hemisphere, needs further research.

Neighbors, Pros and Cons: Impact of Intergroup Interactions on the Welfare of Captive Chimpanzee Groups (Pan troglodytes)

Housing different animal groups in close-by facilities is common in wildlife centers. However, the impact on animal welfare is insufficiently studied in the literature. In this study, we analyzed the behavior of two adjacently housed chimpanzee groups to investigate how intergroup interactions may affect their behavior and, thus, their welfare. We recorded occurrences of abnormal and self-directed behaviors, two well-known indicators of stress in chimpanzees. Furthermore, we explored the social responses to said intergroup interactions by recording all inter- and intragroup affiliative and agonistic behaviors. Finally, we measured the number of vigilance occurrences that individuals directed towards other chimpanzees as an indicator of interest. Generalized Linear Mixed Models (GLMMs) were used to assess whether and how social interactions between neighboring groups might influence their behaviors, taking gender, age, group, and intergroup participation into account. Our results suggest that intergroup interactions promoted the occurrence of affiliative behaviors between group members. However, intergroup interactions caused the chimpanzees to exhibit a higher number of abnormal and self-directed behaviors and increased vigilance towards their group members when agonistic intergroup interactions occurred. Thus, adjacent housing does impact the chimpanzees’ behavior and welfare and should be continuously monitored and assessed to promote and maximize welfare.

FBXO11 variants are associated with intellectual disability and variable clinical manifestation in Chinese affected individuals.

F-box protein 11 (FBXO11) is a member of F-Box protein family, which has recently been proved to be associated with intellectual developmental disorder with dysmorphic facies and behavioral abnormalities (IDDFBA, OMIM: 618089). In this study, 12 intellectual disability individuals from 5 Chinese ID families were collected, and whole exome sequencing (WES), sanger sequencing, and RNA sequencing (RNA-seq) were conducted. Almost all the affected individuals presented with mild to severe intellectual disability (12/12), global developmental delay (10/12), speech and language development delay (8/12) associated with a range of alternate features including increased body weight (7/12), short stature (6/12), seizures (3/12), reduced visual acuity (4/12), hypotonia (1/12), and auditory hallucinations and hallucinations (1/12). Distinguishingly, malformation was not observed in all the affected individuals. WES analysis showed 5 novel FBXO11 variants, which include an inframe deletion variant, a missense variant, two frameshift variants, and a partial deletion of FBXO11 (exon 22-23). RNA-seq indicated that exon 22-23 deletion of FBXO11 results in a new mRNA structure. Conservation and protein structure prediction demonstrated deleterious effect of these variants. The DEGs analysis revealed 148 differentially expressed genes shared among 6 affected individuals, which were mainly associated with genes of muscle and immune system. Our research is the first report of FBXO11-associated IDDFBA in Chinese individuals, which expands the genetic and clinical spectrum of this newly identified NDD/ID syndrome.

Detecting Anomalies in 5G Networks : A Machine Learning Approach for Robust Solutions

The telecommunications industry is advancing rapidly with the introduction of 5G technology, which promises enhanced broadband cellular networks. However, alongside the benefits come challenges, particularly in ensuring the security of these networks against cyber attacks. This paper focuses on Network Anomaly Detection (NAD) in 5G, aiming to detect and prevent abnormal behaviors within the network that could signify potential security threats. Various methods, including machine learning algorithms, are explored to achieve effective NAD. Specifically, the KNN and K-prototype algorithms are tested alongside an integrated approach, with the integrated method demonstrating superior performance.

Validation and assessment of psychometric properties of the Greek Eating Behaviors Assessment for Obesity (GR-EBA-O)

IntroductionWith increasing morbidity and risk of death, obesity has become a serious health problem largely attributable to difficulties in finding proper treatments for related diseases. Many studies show how detecting abnormal eating behaviors could be useful in developing effective clinical treatments. This study aims at validating the Greek version of the Eating Behaviors Assessment for Obesity (EBA-O).MethodAfter a double English/Greek forward/backward translation of the EBA-O, 294 participants completed the Greek version (GR-EBA-O), the Eating Disorder Examination Questionnaire, the Binge Eating Scale, and the Yale Food Addiction Scale. Confirmatory factor analysis (CFA) and construct validity were calculated, and Two-way MANOVA was computed with the factors of GR-EBA-O controlling for sex and BMI categories.ResultsCFA confirmed the second-order five factors (i.e., food addiction, night eating, binge eating, sweet eating, and prandial hyperphagia) structure of the original EBA-O with excellent fit indices. GR-EBA-O factors were highly correlated. The GR-EBA-O subscales were also significantly correlated with the remaining measures, demonstrating good concurrent validity.ConclusionThe Greek version of the EBA-O has demonstrated sound psychometric properties and appears a reliable and user-friendly tool to identify pathological eating behaviors in obesity.Level of evidence: V, descriptive research.

Abnormally High Graphitic Crystallization of Cellulose Nanocrystals.

Cellulose nanocrystals (CNCs) are currently of great interest for many applications, such as energy storage and nanocomposites, because of their natural abundance. A number of carbonization studies have reported abnormal graphitization behavior of CNCs, although cellulose is generally known as a precursor for hard carbon (nongraphitizable carbon). Herein, we report a spray-freeze-drying (SFD) method for CNCs and a subsequent carbonization study to ascertain the difference in the structural development between the amorphous and crystalline phases. The morphological observation by high-resolution transmission electron microscopy of the carbonized SFD-CNC clearly shows that the amorphous and crystalline phases of CNC are attributed to the formation of hard and soft carbon, respectively. The results of a reactive molecular dynamics (RMD) study also show that the amorphous cellulose phase leads to the formation of fewer carbon ring structures, indicative of hard carbon. In contrast, the pristine crystalline cellulose phase has a higher density and thermal stability, resulting in limited molecular relaxation and the formation of a highly crystalline graphitic structure (soft carbon).

Enhanced Pet Behavior Prediction via S2GAN-Based Heterogeneous Data Synthesis

Heterogeneous data have been used to enhance behavior prediction performance; however, it involves issues such as missing data, which need to be addressed. This paper proposes enhanced pet behavior prediction via Sensor to Skeleton Generative Adversarial Networks (S2GAN)-based heterogeneous data synthesis. The S2GAN model synthesizes the key features of video skeletons based on collected nine-axis sensor data and replaces missing data, thereby enhancing the accuracy of behavior prediction. In this study, data collected from 10 pets in a real-life-like environment were used to conduct recognition experiments on 9 commonly occurring types of indoor behavior. Experimental results confirmed that the proposed S2GAN-based synthesis method effectively resolves possible missing data issues in real environments and significantly improves the performance of the pet behavior prediction model. Additionally, by utilizing data collected under conditions similar to the real environment, the method enables more accurate and reliable behavior prediction. This research demonstrates the importance and utility of synthesizing heterogeneous data in behavior prediction, laying the groundwork for applications in various fields such as abnormal behavior detection and monitoring.

Organic Ligand Engineering for Tailoring Electron-Phonon Coupling in 2D Hybrid Perovskites.

In the emerging two-dimensional organic-inorganic hybrid perovskites, the electronic structures and carrier behaviors are strongly impacted by intrinsic electron-phonon interactions, which have received inadequate attention. In this study, we report an intriguing phenomenon of negative carrier diffusion induced by electron-phonon coupling in (2T)2PbI4. Theoretical calculations reveal that the electron-phonon coupling drives the band alignment in (2T)2PbI4 to alternate between type I and type II heterostructures. As a consequence, photoexcited holes undergo transitions between the organic ligands and inorganic layers, resulting in abnormal carrier transport behavior compared to other two-dimensional hybrid perovskites. These findings provide valuable insights into the role of electron-phonon coupling in shaping the band alignments and carrier behaviors in two-dimensional hybrid perovskites. They also open up exciting avenues for designing and fabricating functional semiconductor heterostructures with tailored properties.

How do abnormal trading behaviors diffuse in electronic markets?

How do abnormal trading behaviors diffuse in electronic markets?

Gut Microbiota as a Modifier of Huntington's Disease Pathogenesis.

Huntingtin (HTT) protein is expressed in most cell lineages, and the toxicity of mutant HTT in multiple organs may contribute to the neurological and psychiatric symptoms observed in Huntington's disease (HD). The proteostasis and neurotoxicity of mutant HTT are influenced by the intracellular milieu and responses to environmental signals. Recent research has highlighted a prominent role of gut microbiota in brain and immune system development, aging, and the progression of neurological disorders. Several studies suggest that mutant HTT might disrupt the homeostasis of gut microbiota (known as dysbiosis) and impact the pathogenesis of HD. Dysbiosis has been observed in HD patients, and in animal models of the disease it coincides with mutant HTT aggregation, abnormal behaviors, and reduced lifespan. This review article aims to highlight the potential toxicity of mutant HTT in organs and pathways within the microbiota-gut-immune-central nervous system (CNS) axis. Understanding the functions of Wild-Type (WT) HTT and the toxicity of mutant HTT in these organs and the associated networks may elucidate novel pathogenic pathways, identify biomarkers and peripheral therapeutic targets for HD.