Specific Connections Research Articles

V4RIN: visual analysis of regional industry network with domain knowledge.

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

Bioactive Components of Human Milk and Their Impact on Child’s Health and Development, Literature Review

The composition of human breast milk is an ideal combination of substances necessary for the healthy development of an infant’s body while protecting from pathogens and the balanced development of the microbiota. Its composition is dynamic and changes with the age of the child, meeting their current needs. The study provides a thorough overview of human milk components, such as immunological components, growth factors, hormones, carbohydrates, lipids, minerals, and vitamins. Authors focus on capturing the most important aspects of the effects of these substances on a newborn’s body, while also looking for specific connections and describing the effects on given systems. Supplementation and the use of ingredients are also discussed. The purpose of this paper is to present the current state of knowledge about the bioactive components of human milk and their impact on the growth, development, and health of the young child.

Functional connectivity of the amygdala subnuclei in various mood states of bipolar disorder.

Amygdala functional dysconnectivity lies at the heart of the pathophysiology of bipolar disorder (BD). Recent preclinical studies suggest that the amygdala is a heterogeneous group of nuclei, whose specific connectivity could drive positive or negative emotional valence. We investigated functional connectivity (FC) changes within these circuits emerging from each amygdala's subdivision in 127 patients with BD in different mood states and 131 healthy controls (HC), who underwent resting-state functional MRI. FC was evaluated between lateral and medial nuclei of amygdalae, and key subcortical regions of the emotion processing network: anterior and posterior parts of the hippocampus, and core and shell parts of the nucleus accumbens. FC was compared across groups, and subgroups of patients depending on their mood states, using linear mixed models. We also tested correlations between FC and depression (MADRS) and mania (YMRS) scores. We found no difference between the whole sample of BD patients vs. HC but a significant correlation between MADRS and right lateral amygdala /right anterior hippocampus, right lateral amygdala/right posterior hippocampus and right lateral amygdala/left anterior hippocampus FC (r = -0.44, r = -0.32, r = -0.27, respectively, all pFDR<0.05). Subgroup analysis revealed decreased right lateral amygdala/right anterior hippocampus and right lateral amygdala/right posterior hippocampus FC in depressed vs. non-depressed patients and increased left medial amygdala/shell part of the left nucleus accumbens FC in manic vs non-manic patients. These results demonstrate that acute mood states in BD concur with FC changes in individual nuclei of the amygdala implicated in distinct emotional valence processing. Overall, our data highlight the importance to consider the amygdala subnuclei separately when studying its FC patterns including patients in distinct homogeneous mood states.

Laser Microsurgery in Drosophila Larvae Using the MicroPoint Ablation System.

Laser microsurgery is a robust method to ablate specific cells in the nervous system and probe the functional consequences of their loss in the animal. By introducing focal lesions to small locations in the animal, laser microsurgery also enables disruptions of specific connections within neuronal circuits and the study of how the nervous system responds to precise forms of damage (for instance, damage to specific axons or dendrites, which have been found to evoke different kinds of responses in neurons). The MicroPoint laser is a pulsed dye laser that can be mounted onto any standard microscope, hence is an affordable alternative to two-photon lasers for providing high powered focal ablations. This protocol describes how to use a MicroPoint laser ablation system to induce focal injuries in Drosophila larvae. This protocol guides a user who has access to a MicroPoint laser that has already been installed onto an appropriate microscope for high-resolution imaging and configured for laser ablation using Coumarin 440 dye. The protocol covers how to use the laser to carry out surgeries or ablation, how to change the laser dye and calibrate the power settings, and how to make sure the laser is properly focused. While the protocol provides an example of axotomy (axon severing) in the peripheral nervous system of Drosophila larvae, use of the MicroPoint system can be adapted to other focal surgeries in other organisms.

Directed and acyclic synaptic connectivity in the human layer 2-3 cortical microcircuit.

The computational capabilities of neuronal networks are fundamentally constrained by their specific connectivity. Previous studies of cortical connectivity have mostly been carried out in rodents; whether the principles established therein also apply to the evolutionarily expanded human cortex is unclear. We studied network properties within the human temporal cortex using samples obtained from brain surgery. We analyzed multineuron patch-clamp recordings in layer 2-3 pyramidal neurons and identified substantial differences compared with rodents. Reciprocity showed random distribution, synaptic strength was independent from connection probability, and connectivity of the supragranular temporal cortex followed a directed and mostly acyclic graph topology. Application of these principles in neuronal models increased dimensionality of network dynamics, suggesting a critical role for cortical computation.

Discovery of long non-coding RNAs in naïve CD4+ T cells in response to initiating antiretroviral therapy at acute or chronic phase of HIV-1 infection

Long non-coding RNAs (lncRNAs) have gained prominence due to their involvement in various cellular processes, but their specific roles remain elusive. Dysregulation of lncRNAs has been implicated in the pathogenesis of several diseases. In this study, we aimed to shed light on the role of lncRNAs in individuals infected with human immunodeficiency virus type 1 (HIV-1) by examining their changes in the expression patterns related to the initiation of antiretroviral therapy (ART) during acute or chronic phases of infection, compared to healthy controls. We found 316 differentially expressed (DE) lncRNAs in patients receiving long-term ART, shedding light on their potential roles. We also observed interactions between these DE lncRNAs and specific microRNAs (miRNAs). Some of these miRNAs, such as hsa-miR-574-5p, hsa-miR-765, hsa-miR-6165, hsa-miR-1207-5p, and hsa-miR-378i, are associated with cancer progression or suppression, while others, including hsa-miR-328-5p, hsa-miR-4753-3p, and MiR-664, play roles in immune system regulation. Furthermore, our study revealed substantial enrichment in distinct Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, such as axon guidance, PI3K-Akt signaling, and MAPK signaling pathways. Although our results indicate possible molecular processes impacted by the discovered lncRNAs, we cannot explicitly establish causality or specific connections between lncRNAs and genes in these pathways, fostering more specific studies. Furthermore, Gene Ontology (GO) analysis highlighted terms such as cytoskeletal protein binding, ion channel function, synaptic processes, neuron projection, and the somatodendritic compartment, underscoring the relevance of lncRNAs in these cellular components within the context of HIV-1 infection and ART treatment. In conclusion, our study emphasizes the need for further exploration of lncRNAs as potential biomarkers and therapeutic targets in HIV-1-infected patients, with a particular focus on CD4+ T cells. Understanding the functions of lncRNAs in these contexts may pave the way for novel treatment strategies and improved patient outcomes, aligning with the broader goals of our research.

A high-resolution meshfree particle method for numerical investigation of second-order macroscopic pedestrian flow models

Recent advancements in empirical observations of human psychological responses have revealed that the governing rules of human behavioral aspects can not only be predicted with adequate deterministic precision but also forged into mathematical formulations. These modeling studies enable crisis managers with reliable simulation tools to gain insights into critical facets of crowd disasters and enhance their decision-making abilities to facilitate safe egress in emergency situations. The macroscopic scale of representation in this context is often invoked to comprehend large-scale collective pattern formation in vast built environments, owing to its computational viability. The associated governing equations are typically constructed in a system of hyperbolic conservation law form, and conducting simulations in real-life complex geometric configurations can pose computational challenges. This article puts forward a high-resolution, shock-capturing meshfree particle method in an Eulerian framework for the numerical approximation of several widely adopted macroscopic pedestrian flow models. It serves as a superior alternative to traditional mesh-based methods, eliminating the need for specific mesh structures and connectivity between them. A classical Generalized Finite Difference Method (GFDM) in conjunction with several consistency conditions on spatial derivative coefficients is adopted to obtain a non-oscillatory and fairly conservative Godunov-type discretization of the governing system. The intercell flux is evaluated using a suitable Riemann solver, and a slope-limited reconstruction procedure of the corresponding Riemann states, adapted to arbitrary point distribution, is employed for improved accuracy. Moreover, the preferred direction of human motion is determined from a local density-dependent eikonal-type equation, which is solved using a generalized version of the Fast Marching Method. A thorough numerical investigation of three well-known second-order macroscopic models, namely Payne-Whitham (PW), Aw-Rascle (AR), and Aw-Rascle-Zhang (ARZ) is carried out through two hypothetical scenarios of crowd evacuation, not only to demonstrate the accuracy and applicability of the proposed approach but also to deepen understanding of their distinctive characteristics. A comparison of the flow flux with the fundamental diagram suggests that the density profile obtained with the ARZ model is equivalent to Hughes' first-order model. In contrast, the PW and AR models have proven to effectively replicate complex, unstable pedestrian phenomena such as stop-and-go waves. Finally, Helbing's counter-intuitive idea that strategically positioned barriers upstream of a bottleneck can essentially expedite evacuation is numerically investigated across various parameter choices.

483 Network Analysis of the Thalamic RNS in Patients With Drug Resistant Epilepsy: Insights to Improve Surgical Targeting

INTRODUCTION: Approximately 30% of epilepsy patients are refractory to pharmacotherapy. Patients with drug-resistant epilepsy (DRE) with seizure foci located bilaterally or in the eloquent cortex may be ineligible for resective surgery. For such cases, responsive neurostimulation (RNS) is a viable treatment strategy. METHODS: Retrospective analysis of 23 patients treated with thalamic RNS of the centromedian (CM) and anterior nuclei of the thalamus (ANT) from 2015-2022. Clinical features and seizure outcomes were recorded. RNS electrodes were used to model the electrical field using the parameters at last follow up. Patient-specific probabilistic tractography was used to define the network of the seizure onset zone (SOZ) and its thalamic involvement. Each patient’s probabilistic map was used to define the area of highest connectivity of the thalamus with the seizure network. Each of these patient-specific thalamic areas demonstrating highest connectivity with the seizure network were correlated with electrode position, stimulation modeling, and seizure outcomes. RESULTS: Seizure network from neocortical areas were highly connected to the CM and from limbic cortical areas to the ANT, MD, and parafascicularis nuclei. Results of the correlation analysis between connectivity, stimulation modelling of the RNS electrode, and seizure outcomes will be presented along with illustrative cases of patient-specific targeting using tractography for RNS placement. CONCLUSIONS: Probabilistic tractography is useful to define the networks associated with improved seizure control in thalamic RNS. The identification of these networks prior to surgery could help to identify specific corticothalamic connections and their anatomical trajectories to optimize the implantation of the leads for better and more predictable seizure control.

Circuits in the motor cortex explain oscillatory responses to transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) is a popular method used to investigate brain function. Stimulation over the motor cortex evokes muscle contractions known as motor evoked potentials (MEPs) and also high-frequency volleys of electrical activity measured in the cervical spinal cord. The physiological mechanisms of these experimentally derived responses remain unclear, but it is thought that the connections between circuits of excitatory and inhibitory neurons play a vital role. Using a spiking neural network model of the motor cortex, we explained the generation of waves of activity, so called 'I-waves', following cortical stimulation. The model reproduces a number of experimentally known responses including direction of TMS, increased inhibition, and changes in strength. Using populations of thousands of neurons in a model of cortical circuitry we showed that the cortex generated transient oscillatory responses without any tuning, and that neuron parameters such as refractory period and delays influenced the pattern and timing of those oscillations. By comparing our network with simpler, previously proposed circuits, we explored the contributions of specific connections and found that recurrent inhibitory connections are vital in producing later waves that significantly impact the production of motor evoked potentials in downstream muscles (Thickbroom, 2011). This model builds on previous work to increase our understanding of how complex circuitry of the cortex is involved in the generation of I-waves.

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data.

Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell labels are still lacking in single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) data, because of extreme sparsity and inconsistent chromatin accessibility between datasets. Here, we present a novel automated cell annotation method that transfers cell type information from a well-labeled scRNA-seq reference to an unlabeled scATAC-seq target, via a parallel graph neural network, in a semi-supervised manner. Unlike existing methods that utilize only gene expression or gene activity features, HyGAnno leverages genome-wide accessibility peak features to facilitate the training process. In addition, HyGAnno reconstructs a reference-target cell graph to detect cells with low prediction reliability, according to their specific graph connectivity patterns. HyGAnno was assessed across various datasets, showcasing its strengths in precise cell annotation, generating interpretable cell embeddings, robustness to noisy reference data and adaptability to tumor tissues.

Chronometric TMS-fMRI of personalized left dorsolateral prefrontal target reveals state-dependency of subgenual anterior cingulate cortex effects

Transcranial magnetic stimulation (TMS) applied to a left dorsolateral prefrontal cortex (DLPFC) area with a specific connectivity profile to the subgenual anterior cingulate cortex (sgACC) has emerged as a highly effective non-invasive treatment option for depression. However, antidepressant outcomes demonstrate significant variability among therapy plans and individuals. One overlooked contributing factor is the individual brain state at the time of treatment. In this study we used interleaved TMS-fMRI to investigate the influence of brain state on acute TMS effects, both locally and remotely. TMS was performed during rest and during different phases of cognitive task processing. Twenty healthy participants were included in this study. In the first session, imaging data for TMS targeting were acquired, allowing for identification of individualized targets in the left DLPFC based on highest anti-correlation with the sgACC. The second session involved chronometric interleaved TMS-fMRI measurements, with 10 Hz triplets of TMS administered during rest and at distinct timings during an N-back task. Consistent with prior findings, interleaved TMS-fMRI revealed significant BOLD activation changes in the targeted network. The precise timing of TMS relative to the cognitive states during the task demonstrated distinct BOLD response in clinically relevant brain regions, including the sgACC. Employing a standardized timing approach for TMS using a task revealed more consistent modulation of the sgACC at the group level compared to stimulation during rest. In conclusion, our findings strongly suggest that acute local and remote effects of TMS are influenced by brain state during stimulation. This study establishes a basis for considering brain state as a significant factor in designing treatment protocols, possibly improving TMS treatment outcomes.

Edge-wise analysis reveals white matter connectivity associated with focal to bilateral tonic-clonic seizures.

Focal to bilateral tonic-clonic seizures (FBTCS) represent a challenging subtype of focal temporal lobe epilepsy (TLE) in terms of both severity and treatment response. Most studies have focused on regional brain analysis that is agnostic to the distribution of white matter (WM) pathways associated with a node. We implemented a more selective, edge-wise approach that allowed for identification of the individual connections unique to FBTCS. T1-weighted and diffusion-weighted images were obtained from 22 patients with solely focal seizures (FS), 43 FBTCS patients, and 65 age/sex-matched healthy participants (HPs), yielding streamline (STR) connectome matrices. We used diffusion tensor-derived STRs in an edge-wise approach to determine specific structural connectivity changes associated with seizure generalization in FBTCS compared to matched FS and HPs. Graph theory metrics were computed on both node- and edge-based connectivity matrices. Edge-wise analyses demonstrated that all significantly abnormal cross-hemispheric connections belonged to the FBTCS group. Abnormal connections associated with FBTCS were mostly housed in the contralateral hemisphere, with graph metric values generally decreased compared to HPs. In FBTCS, the contralateral amygdala showed selective decreases in the structural connection pathways to the contralateral frontal lobe. Abnormal connections in TLE involved the amygdala, with the ipsilateral side showing increases and the contralateral decreases. All the FS findings indicated higher graph metrics for connections involving the ipsilateral amygdala. Data also showed that some FBTCS connectivity effects are moderated by aging, recent seizure frequency, and longer illness duration. Data showed that not all STR pathways are equally affected by the seizure propagation of FBTCS. We demonstrated two key biases, one indicating a large role for the amygdala in the propagation of seizures, the other pointing to the prominent role of cross-hemispheric and contralateral hemisphere connections in FBTCS. We demonstrated topographic reorganization in FBTCS, pointing to the specific WM tracts involved.

Monosynaptic Rabies Tracing Reveals Sex- and Age-Dependent Dorsal Subiculum Connectivity Alterations in an Alzheimer's Disease Mouse Model.

The subiculum (SUB), a hippocampal formation structure, is among the earliest brain regions impacted in Alzheimer's disease (AD). Toward a better understanding of AD circuit-based mechanisms, we mapped synaptic circuit inputs to dorsal SUB using monosynaptic rabies tracing in the 5xFAD mouse model by quantitatively comparing the circuit connectivity of SUB excitatory neurons in age-matched controls and 5xFAD mice at different ages for both sexes. Input-mapped brain regions include the hippocampal subregions (CA1, CA2, CA3), medial septum and diagonal band, retrosplenial cortex, SUB, postsubiculum (postSUB), visual cortex, auditory cortex, somatosensory cortex, entorhinal cortex, thalamus, perirhinal cortex (Prh), ectorhinal cortex, and temporal association cortex. We find sex- and age-dependent changes in connectivity strengths and patterns of SUB presynaptic inputs from hippocampal subregions and other brain regions in 5xFAD mice compared with control mice. Significant sex differences for SUB inputs are found in 5xFAD mice for CA1, CA2, CA3, postSUB, Prh, lateral entorhinal cortex, and medial entorhinal cortex: all of these areas are critical for learning and memory. Notably, we find significant changes at different ages for visual cortical inputs to SUB. While the visual function is not ordinarily considered defective in AD, these specific connectivity changes reflect that altered visual circuitry contributes to learning and memory deficits. Our work provides new insights into SUB-directed neural circuit mechanisms during AD progression and supports the idea that neural circuit disruptions are a prominent feature of AD.

An exploratory computational analysis in mice brain networks of widespread epileptic seizure onset locations along with potential strategies for effective intervention and propagation control.

Mean-field models have been developed to replicate key features of epileptic seizure dynamics. However, the precise mechanisms and the role of the brain area responsible for seizure onset and propagation remain incompletely understood. In this study, we employ computational methods within The Virtual Brain framework and the Epileptor model to explore how the location and connectivity of an Epileptogenic Zone (EZ) in a mouse brain are related to focal seizures (seizures that start in one brain area and may or may not remain localized), with a specific focus on the hippocampal region known for its association with epileptic seizures. We then devise computational strategies to confine seizures (prevent widespread propagation), simulating medical-like treatments such as tissue resection and the application of an anti-seizure drugs or neurostimulation to suppress hyperexcitability. Through selectively removing (blocking) specific connections informed by the structural connectome and graph network measurements or by locally reducing outgoing connection weights of EZ areas, we demonstrate that seizures can be kept constrained around the EZ region. We successfully identified the minimal connections necessary to prevent widespread seizures, with a particular focus on minimizing surgical or medical intervention while simultaneously preserving the original structural connectivity and maximizing brain functionality.

Thalamic segmentation based on diffusion tensor imaging in patients with trigeminal neuralgia

Classical trigeminal neuralgia (CTN) refers to episodic pain that is strictly confined to the trigeminal distribution area, and the thalamus is an important component of the trigeminal sensory pathway. Probabilistic tracking imaging algorithm was used to identify specific connections between the thalamus and the cortex, in order to identify structural changes in the thalamus of patients with CTN and perform thalamic segmentation. A total of 32 patients with CTN and 32 healthy controls underwent DTI-MRI scanning (3.0 T). Differences in fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) between the groups were studied. Correlation analysis was performed with clinical course and pain level. Compared to the healthy controls, patients in the CTN group had significantly reduced FA, increased AD, RD and MD in somatosensory subregion of the bilateral thalamus, increased RD in frontal subregion, increased RD and MD in motor subregion. Correlation analysis showed that patient history was positively correlated with pain grading, and that medical history was positively correlated with significantly reduced FA in somatosensory subregion, negatively correlated with increased RD and MD in motor subregion. We used DTI-based probabilistic fiber tracking to discover altered structural connectivity between the thalamus and cerebral cortex in patients with CTN and to obtain a thalamic segmentation atlas, which will help to further understand the pathophysiology of CTN and serve as a future reference for thalamic deep brain stimulation electrode implantation for the treatment of intractable pain.

A network analysis bridging the gap between the big five personality traits and burnout among medical staff

BackgroundBurnout is a common issue among medical professionals, and one of the well-studied predisposing factors is the Big Five personality traits. However, no studies have explored the relationships between these traits and burnout from a trait-to-component perspective. To understand the specific connections between each Big Five trait and burnout components, as well as the bridging effects of each trait on burnout, we employed network analysis.MethodsA cluster sampling method was used to select a total of 420 Chinese medical personnel. The 15-item Chinese Big Five Personality Inventory-15 (CBF-PI-15) assessed the Big Five personality traits, while the 15-item Maslach Burnout Inventory-General Survey (MBI-GS) assessed burnout components. Network analysis was used to estimate network structure of Big Five personality traits and burnout components and calculate the bridge expected influence.ResultsThe study revealed distinct and clear relationships between the Big Five personality traits and burnout components. For instance, Neuroticism was positively related to Doubt significance and Worthwhile, while Conscientiousness was negatively related to Accomplish all tasks. Among the Big Five traits, Neuroticism displayed the highest positive bridge expected influence, while Conscientiousness displayed the highest negative bridge expected influence.ConclusionsThe network model provides a means to investigate the connections between the Big Five personality traits and burnout components among medical professionals. This study offers new avenues for thought and potential targets for burnout prevention and treatment in medical personnel, which can be further explored and tested in clinical settings.

Oxytocin-induced birth causes sex-specific behavioral and brain connectivity changes in developing rat offspring

Despite six decades of the use of exogenous oxytocin for management of labor, little is known about its effects on the developing brain. Motivated by controversial reports suggesting a link between oxytocin use during labor and autism spectrum disorders (ASDs), we employed our recently validated rat model for labor induction with oxytocin to address this important concern. Using a combination of molecular biological, behavioral, and neuroimaging assays, we show that induced birth with oxytocin leads to sex-specific disruption of oxytocinergic signaling in the developing brain, decreased communicative ability of pups, reduced empathy-like behaviors especially in male offspring, and widespread sex-dependent changes in functional cortical connectivity. Contrary to our hypothesis, social behavior, typically impaired in ASDs, was largely preserved. Collectively, our foundational studies provide nuanced insights into the neurodevelopmental impact of birth induction with oxytocin and set the stage for mechanistic investigations in animal models and prospective longitudinal clinical studies.

Eimeria infections of plateau pika altered the patterns of temporal alterations in gut bacterial communities.

Intestinal parasites, such as Eimeria, are common among plateau pika (Ochotona curzoniae). The gut microbiome is an essential driver of the host response to gastrointestinal parasites. However, the effects of intestinal protozoal parasites on the temporal variations in the gut microbiome and behavioral and physiological activities remain unknown. Our study conducted treatments involving experimental feeding of pika with Eimeria oocysts or anticoccidia under laboratory conditions to focus on the parasite-associated alterations in gut bacterial communities, host behavioral activity, physiology, and host-bacteria relationships. The results showed insignificant differences in bacterial community structures among treatments on the basis of Bray-Curtis distance metrics, whereas the patterns of temporal alterations in the bacterial communities were changed by the treatments. Bacterial alpha diversities did not vary with the treatments, and experimental feeding with Eimeria slowed down the decrement rate of alpha diversity. Furthermore, few bacterial members were significantly changed by the treatments-only the genus Ruminococcus and the species Ruminococcus flavefaciens, which were associated with energy metabolism. Experimental feeding with Eimeria modified the temporal variations in the bacterial members, including a lower loss rate of the relative abundance of the dominant families Muribaculaceae and Ruminococcaceae in the group with Eimeria experimental feeding. Moreover, a shifting energy trade-off was suggested by the parasite-induced increments in thyroid hormones (triiodothyronine and tetraiodothyronine) and decrements in exploration behavior in the group with Eimeria feeding. However, we did not detect specific connections between gut bacterial communities and pika behaviors and physiology in terms of energy trade-offs. Further in-depth research is needed to examine the role of Eimeria-modified differences in the gut bacteria of plateau pika.

CSI-based WIFI Device Identification Solution

In recent years, wireless devices such as WIFI routers have become increasingly common in various fields. Rogue access point (RAP) is one of the threats that has persisted in wireless LAN (WLAN) for many years and can cause varying degrees of property damage and privacy leaks. In response to these threats, we propose a new security mechanism, called Rdi, which uses environment-independent features extracted from channel state information (CSI) as fingerprints for device identification. We found that the phase errors between multiple antennas on a single MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) transmitter are not the same. This phase offset is due to the I/Q imbalance and imperfect oscillator of each WiFi network card, and it will not change with factors such as environment and time. Therefore, we inferred and verified that there must be some relationship between the phase errors of multiple groups of antennas, that is, the relative phase error (RPE). In addition, RPE will also vary with different WiFi devices. Compared with some similar fingerprint detection methods in the past, the use of specific connections between group phase errors between antennas can better reveal the different attributes between devices, thereby enhancing the uniqueness of features. Therefore, we believe that RPE can be used as an effective fingerprint to detect RAP attacks. We conduct a large number of experimental demonstrations on this, and innovatively built a multi-modal convolutional neural network (CNN) model to perform efficient classification work for our solution. Experiments on 22 WiFi devices and various scenarios show that the detection rate of Rdi can reach more than 98% in both dynamic and static device states.

Immunohistochemical field parcellation of the human hippocampus along its antero-posterior axis

The primate hippocampus includes the dentate gyrus, cornu ammonis (CA), and subiculum. CA is subdivided into four fields (CA1-CA3, plus CA3h/hilus of the dentate gyrus) with specific pyramidal cell morphology and connections. Work in non-human mammals has shown that hippocampal connectivity is precisely patterned both in the laminar and longitudinal axes. One of the main handicaps in the study of neuropathological semiology in the human hippocampus is the lack of clear laminar and longitudinal borders. The aim of this study was to explore a histochemical segmentation of the adult human hippocampus, integrating field (medio-lateral), laminar, and anteroposterior longitudinal patterning. We provide criteria for head-body-tail field and subfield parcellation of the human hippocampus based on immunodetection of Rabphilin3a (Rph3a), Purkinje-cell protein 4 (PCP4), Chromogranin A and Regulation of G protein signaling-14 (RGS-14). Notably, Rph3a and PCP4 allow to identify the border between CA3 and CA2, while Chromogranin A and RGS-14 give specific staining of CA2. We also provide novel histological data about the composition of human-specific regions of the anterior and posterior hippocampus. The data are given with stereotaxic coordinates along the longitudinal axis. This study provides novel insights for a detailed region-specific parcellation of the human hippocampus useful for human brain imaging and neuropathology.