EZH2 suppresses ferroptosis in hepatocellular carcinoma and reduces sorafenib sensitivity through epigenetic regulation of TFR2.

Enhancing sensitivity to sorafenib can significantly extend the duration of resistance to it, offering substantial benefits for treating patients with hepatocellular carcinoma (HCC). However, the role of ferroptosis in influencing sorafenib sensitivity within HCC remains pivotal. The enhancer of zeste homolog 2 (EZH2) plays a significant role in promoting malignant progression in HCC, yet the relationship between ferroptosis, sorafenib sensitivity, and EZH2 is not entirely clear. Bioinformatic analysis indicates elevated EZH2 expression in HCC, predicting an unfavorable prognosis. Overexpressing EZH2 can drive HCC cell proliferation while simultaneously reducing ferroptosis. Further analysis reveals that EZH2 amplifies the modification of H3K27 me3, thereby influencing TFR2 expression. This results in decreased RNA polymerase II binding within the TFR2 promoter region, leading to reduced TFR2 expression. Knocking down EZH2 amplifies sorafenib sensitivity in HCC cells. In sorafenib-resistant HepG2(HepG2-SR) cells, the expression of EZH2 is increased. Moreover, combining tazemetostat-an EZH2 inhibitor-with sorafenib demonstrates significant synergistic ferroptosis-promoting effects in HepG2-SR cells. In conclusion, our study illustrates how EZH2 epigenetically regulates TFR2 expression through H3K27 me3, thereby suppressing ferroptosis. The combination of the tazemetostat with sorafenib exhibits superior synergistic effects in anticancer therapy and sensitizes the HepG2-SR cells to sorafenib, shedding new light on delaying and ameliorating sorafenib resistance.

Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology.

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

Ruthenium-Cobalt Solid-Solution Alloy Nanoparticles for Enhanced Photopromoted Thermocatalytic CO2 Hydrogenation to Methane.

Bimetallic alloy nanoparticles have garnered substantial attention for diverse catalytic applications owing to their abundant active sites and tunable electronic structures, whereas the synthesis of ultrafine alloy nanoparticles with atomic-level homogeneity for bulk-state immiscible couples remains a formidable challenge. Herein, we present the synthesis of RuxCo1-x solid-solution alloy nanoparticles (ca. 2 nm) across the entire composition range, for highly efficient, durable, and selective CO2 hydrogenation to CH4 under mild conditions. Notably, Ru0.88Co0.12/TiO2 and Ru0.74Co0.26/TiO2 catalysts, with 12 and 26 atom % of Ru being substituted by Co, exhibit enhanced catalytic activity compared with the monometallic Ru/TiO2 counterparts both in dark and under light irradiation. The comprehensive experimental investigations and density functional theory calculations unveil that the electronic state of Ru is subtly modulated owing to the intimate interaction between Ru and Co in the alloy nanoparticles, and this effect results in the decline in the CO2 conversion energy barrier, thus ultimately culminating in an elevated catalytic performance relative to monometallic Ru and Co catalysts. In the photopromoted thermocatalytic process, the photoinduced charge carriers and localized photothermal effect play a pivotal role in facilitating the chemical reaction process, which accounts for the further boosted CO2 methanation performance.

Graphdiyne marries PEDOT:PSS to form high-stable heterostructure from 2-unstable components toward ultra-low detection limit of uric acid detection in sweat.

PEDOT: PSS has been used as a biomimetic uric acid (UA) sensor but suffers from unfortunate low detection limit (LOD), narrow detection range and poor stability. Herein, we get graphdiyne (GDY) marry PEDOT:PSS to create a very stable GDY@PEDOT:PSS heterostructure for a biomimetic UA sensor, which accomplishes the lowest LOD (6 nM), the widest detection range (0.03 µM-7 mM) and the longest stability (98.1% for 35 days) among the related UA sensors. The sensor was successfully used to in situ real-time detection of  UA in sweat. The enhancement mechanisms of the sensor were investigated, and results discover that C≡C of GDY and C = C of PEDOT:PSS can cross-link each other by π-π interactions, making not only the former strongly resistant against oxidation deterioration, but also causes the latter to efficiently prevent water swelling of polymer for poor conductivity, thereby leading to high stability from both components. While the stabilized heterostructure can also offer more active sites by enhanced absorption of UA via π-π interactions for highly sensitive detection of UA. This work holds great promise for a practical sweat UA sensor while providing scientific insight to design a stable and electrocatalytically active structure from two unstable components.

Individualized brain mapping for navigated neuromodulation.

ABSTRACT: The brain is a complex organ that requires precise mapping to understand its structure and function. Brain atlases provide a powerful tool for studying brain circuits, discovering biological markers for early diagnosis, and developing personalized treatments for neuropsychiatric disorders. Neuromodulation techniques, such as transcranial magnetic stimulation and deep brain stimulation, have revolutionized clinical therapies for neuropsychiatric disorders. However, the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques. Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems. Still, the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions. The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles, advantages, disadvantages, and future trends of these techniques. The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

In-vivoverified anatomically aware deep learning for real-time electric field simulation.

Objective.Transcranial magnetic stimulation (TMS) has emerged as a prominent non-invasive technique for modulating brain function and treating mental disorders. By generating a high-precision magnetically evoked electric field (E-field) using a TMS coil, it enables targeted stimulation of specific brain regions. However, current computational methods employed for E-field simulations necessitate extensive preprocessing and simulation time, limiting their fast applications in the determining the optimal coil placement.Approach.We present an attentional deep learning network to simulate E-fields. This network takes individual magnetic resonance images and coil configurations as inputs, firstly transforming the images into explicit brain tissues and subsequently generating the local E-field distribution near the target brain region. Main results. Relative to the previous deep-learning simulation method, the presented method reduced the mean relative error in simulated E-field strength of gray matter by 21.1%, and increased the correlation between regional E-field strengths and corresponding electrophysiological responses by 35.0% when applied into another dataset.In-vivoTMS experiments further revealed that the optimal coil placements derived from presented method exhibit comparable stimulation performance on motor evoked potentials to those obtained using computational methods. The simplified preprocessing and increased simulation efficiency result in a significant reduction in the overall time cost of traditional TMS coil placement optimization, from several hours to mere minutes.Significance.The precision and efficiency of presented simulation method hold promise for its application in determining individualized coil placements in clinical practice, paving the way for personalized TMS treatments.

Reinforcing the Efficiency of Photothermal Catalytic CO2 Methanation through Integration of Ru Nanoparticles with Photothermal MnCo2O4 Nanosheets.

Carbon dioxide (CO2) hydrogenation to methane (CH4) is regarded as a promising approach for CO2 utilization, whereas achieving desirable conversion efficiency under mild conditions remains a significant challenge. Herein, we have identified ultrasmall Ru nanoparticles (∼2.5 nm) anchored on MnCo2O4 nanosheets as prospective photothermal catalysts for CO2 methanation at ambient pressure with light irradiation. Our findings revealed that MnCo2O4 nanosheets exhibit dual functionality as photothermal substrates for localized temperature enhancement and photocatalysts for electron donation. As such, the optimized Ru/MnCo2O4-2 gave a high CH4 production rate of 66.3 mmol gcat-1 h-1 (corresponding to 5.1 mol gRu-1 h-1) with 96% CH4 selectivity at 230 °C under ambient pressure and light irradiation (420-780 nm, 1.25 W cm-2), outperforming most reported plasmonic metal-based catalysts. The mechanisms behind the intriguing photothermal catalytic performance improvement were substantiated through a comprehensive investigation involving experimental characterizations, numerical simulations and density functional theory (DFT) calculations, which unveiled the synergistic effects of enhanced charge separation efficiency, improved reaction kinetics, facilitated reactant adsorption/activation and accelerated intermediate conversion under light irradiation over Ru/MnCo2O4. A comparison study showed that, with identical external input energy during the reaction, Ru/MnCo2O4-2 had a much higher catalytic efficiency compared to Ru/TiO2 and Ru/Al2O3. This study underscores the pivotal role played by photothermal supports and is believed to engender a heightened interest in plasmonic metal nanoparticles anchored on photothermal substrates for CO2 methanation under mild conditions.

Molecular mechanism of glutaminase activation through filamentation and the role of filaments in mitophagy protection.

Glutaminase (GLS), which deaminates glutamine to form glutamate, is a mitochondrial tetrameric protein complex. Although inorganic phosphate (Pi) is known to promote GLS filamentation and activation, the molecular basis of this mechanism is unknown. Here we aimed to determine the molecular mechanism of Pi-induced mouse GLS filamentation and its impact on mitochondrial physiology. Single-particle cryogenic electron microscopy revealed an allosteric mechanism in which Pi binding at the tetramer interface and the activation loop is coupled to direct nucleophile activation at the active site. The active conformation is prone to enzyme filamentation. Notably, human GLS filaments form inside tubulated mitochondria following glutamine withdrawal, as shown by in situ cryo-electron tomography of cells thinned by cryo-focused ion beam milling. Mitochondria with GLS filaments exhibit increased protection from mitophagy. We reveal roles of filamentous GLS in mitochondrial morphology and recycling.

Structure of the native chemotaxis core signaling unit from phage E-protein lysed E. coli cells.

IMPORTANCE: Bacterial chemotaxis is a ubiquitous behavior that enables cell movement toward or away from specific chemicals. It serves as an important model for understanding cell sensory signal transduction and motility. Characterization of the molecular mechanisms underlying chemotaxis is of fundamental interest and requires a high-resolution structural picture of the sensing machinery, the chemosensory array. In this study, we combine cryo-electron tomography and molecular simulation to present the complete structure of the core signaling unit, the basic building block of chemosensory arrays, from Escherichia coli. Our results provide new insight into previously poorly-resolved regions of the complex and offer a structural basis for designing new experiments to test mechanistic hypotheses.

Biodegradation of soil agrochemical contamination mitigates the direct horizontal transfer risk of antibiotic resistance genes to crops.

Microorganisms can drive a substrate-specific biodegradation process to mitigate soil contamination resulting from extensive agrochemical usage. However, microorganisms with high metabolic efficiency are capable of adapting to the co-occurrence of non-substrate contaminants in the soil (particularly antibiotics). Therefore, the utilization of active microorganisms for biodegradation raises concerns regarding the potential risk of antibiotic resistance development. Here, the horizontal transfer risk of antibiotic-resistance genes (ARGs) in the soil-plant biota was assessed during biodegradation by the newly isolated Proteus terrae ZQ02 (which shortened the half-life of fungicide chlorothalonil from 9.24 d to 2.35 d when exposed to tetracycline). Based on metagenomic analyses, the distribution of ARGs and mobile genetic elements (MGEs) was profiled. The ARGs shared with ∼118 core genes and mostly accumulated in the rhizosphere and maize roots. After ZQ02 was inoculated, the core genes of ARGs reduced significantly in roots. In addition, the Pseudomonas and Proteus genera were identified as the dominant microbial hosts of ARGs and MGEs after ZQ02 adoption. The richness of major ARG hosts increased in soil but barely changed in the roots, which contributed to the mitigation of hosts-mediated ARGs transfer from soil to maize. Finally, the risk of ARGs has been assessed. Compared with the regular planting system, the number of risky ARGs declined from 220 (occupied 4.77 % of the total ARGs) to 143 (occupied 2.67 %) after biodegradation. Among these, 23 out of 25 high-risk genes were aggregated in the soil whereas only 2 genes were identified in roots, which further verified the low antibiotic resistance risk for crop after biodegradation. In a nutshell, this work highlights the critical advantage of ZQ02-based biodegradation that alleviating the ARGs transfer risks from soil to crop, which offers deeper insights into the versatility and feasibility of bioremediation techniques in sustainable agriculture.

Large-Scale Synthesis of Multifunctional Single-Phase Co2 C Nanomaterials.

Achieving scalable synthesis of nanoscale transition-metal carbides (TMCs), regarded as substitutes for platinum-group noble metals, remains an ongoing challenge. Herein, a 100-g scale synthesis of single-phased cobalt carbide (Co2 C) through carburization of Co-based Prussian Blue Analog (Co-PBA) is reported in CO2 /H2 atmosphere under mild conditions (230 °C, ambient pressure). Textural property investigations indicate a successful preparation of orthorhombic-phased Co2 C nanomaterials with Pt-group-like electronic properties. As a demonstration, Co2 C achieves landmark photo-assisted thermal catalytic CO2 conversion rates with photo-switched product selectivity, which far exceeds the representative Pt-group-metal-based catalysts. This impressive result is attributed to the excellent activation of reactants, colorific light absorption, and photo-to-thermal conversion capacities. In addition to CO2 hydrogenation, the versatile Co2 C materials show huge prospects in antibacterial therapy, interfacial water evaporation, electrochemical hydrogen evolution reaction, and battery technologies. This study paves the way toward unlocking the potential of multi-functional Co2 C nanomaterials.

CHD8 mutations increase gliogenesis to enlarge brain size in the nonhuman primate.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that affects social interaction and behavior. Mutations in the gene encoding chromodomain helicase DNA-binding protein 8 (CHD8) lead to autism symptoms and macrocephaly by a haploinsufficiency mechanism. However, studies of small animal models showed inconsistent findings about the mechanisms for CHD8 deficiency-mediated autism symptoms and macrocephaly. Using the nonhuman primate as a model system, we found that CRISPR/Cas9-mediated CHD8 mutations in the embryos of cynomolgus monkeys led to increased gliogenesis to cause macrocephaly in cynomolgus monkeys. Disrupting CHD8 in the fetal monkey brain prior to gliogenesis increased the number of glial cells in newborn monkeys. Moreover, knocking down CHD8 via CRISPR/Cas9 in organotypic monkey brain slices from newborn monkeys also enhanced the proliferation of glial cells. Our findings suggest that gliogenesis is critical for brain size in primates and that abnormal gliogenesis may contribute to ASD.

Ir-CoO Active Centers Supported on Porous Al2 O3 Nanosheets as Efficient and Durable Photo-Thermal Catalysts for CO2 Conversion.

Photo-thermal catalytic CO2 hydrogenation is currently extensively studied as one of the most promising approaches for the conversion of CO2 into value-added chemicals under mild conditions; however, achieving desirable conversion efficiency and target product selectivity remains challenging. Herein, the fabrication of Ir-CoO/Al2 O3 catalysts derived from Ir/CoAl LDH composites is reported for photo-thermal CO2 methanation, which consist of Ir-CoO ensembles as active centers that are evenly anchored on amorphous Al2 O3 nanosheets. A CH4 production rate of 128.9 mmol gcat⁻ 1 h⁻1  is achieved at 250 °C under ambient pressure and visible light irradiation, outperforming most reported metal-based catalysts. Mechanism studies based on density functional theory (DFT) calculations and numerical simulations reveal that the CoO nanoparticles function as photocatalysts to donate electrons for Ir nanoparticles and meanwhile act as "nanoheaters" to effectively elevate the local temperature around Ir active sites, thus promoting the adsorption, activation, and conversion of reactant molecules. In situ diffuse reflectance infrared Fourier transform spectroscopy (in situ DRIFTS) demonstrates that illumination also efficiently boosts the conversion of formate intermediates. The mechanism of dual functions of photothermal semiconductors as photocatalysts for electron donation and as nano-heaters for local temperature enhancement provides new insight in the exploration for efficient photo-thermal catalysts.

Imbedding Pd Nanoparticles into Porous In2O3 Structure for Enhanced Low-Concentration Methane Sensing.

Methane (CH4), as the main component of natural gas and coal mine gas, is widely used in daily life and industrial processes and its leakage always causes undesirable misadventures. Thus, the rapid detection of low concentration methane is quite necessary. However, due to its robust chemical stability resulting from the strong tetrahedral-symmetry structure, the methane molecules are usually chemically inert to the sensing layers in detectors, making the rapid and efficient alert a big challenge. In this work, palladium nanoparticles (Pd NPs) embedded indium oxide porous hollow tubes (In2O3 PHTs) were successfully synthesized using Pd@MIL-68 (In) MOFs as precursors. All In2O3-based samples derived from Pd@MIL-68 (In) MOFs inherited the morphology of the precursors and exhibited the feature of hexagonal hollow tubes with porous architecture. The gas-sensing performances to 5000 ppm CH4 were evaluated and it was found that Pd@In2O3-2 gave the best response (Ra/Rg = 23.2) at 370 °C, which was 15.5 times higher than that of pristine-In2O3 sensors. In addition, the sensing materials also showed superior selectivity against interfering gases and a rather short response/recovery time of 7 s/5 s. The enhancement in sensing performances of Pd@In2O3-2 could be attributed to the large surface area, rich porosity, abundant oxygen vacancies and the catalytic function of Pd NPs.

Transition metal elements-doped SnO2 for ultrasensitive and rapid ppb-level formaldehyde sensing.

Pristine SnO2, Fe-doped SnO2 and Ni-doped SnO2 were synthesized using facile hydrothermal method. Analysis based on XRD, TEM and UV-Vis DRS measurements demonstrated the successful insertion of Fe and Ni dopants into SnO2 crystal. Formaldehyde-detection measurements revealed that transition metal-doped SnO2 exhibited improved formaldehyde-sensing properties compared with that of pristine SnO2. When the amount of incorporated dopant (Fe or Ni) was 4 at.%, the most effective enhancement on sensing performance of SnO2 was obtained. At 160 °C, the 4 at.% Fe-SnO2 and 4 at.% Ni-SnO2 exhibited higher response values of 7.52 and 4.37 with exposure to low-concentration formaldehyde, respectively, which were 2.4 and 1.4 times higher than that of pristine SnO2. The change of electronic structure and crystal structure as well as catalytic effect of transition metals are chiefly responsible for the enhanced sensing properties.

Survey on Exact kNN Queries over High-Dimensional Data Space.

k nearest neighbours (kNN) queries are fundamental in many applications, ranging from data mining, recommendation system and Internet of Things, to Industry 4.0 framework applications. In mining, specifically, it can be used for the classification of human activities, iterative closest point registration and pattern recognition and has also been helpful for intrusion detection systems and fault detection. Due to the importance of kNN queries, many algorithms have been proposed in the literature, for both static and dynamic data. In this paper, we focus on exact kNN queries and present a comprehensive survey of exact kNN queries. In particular, we study two fundamental types of exact kNN queries: the kNN Search queries and the kNN Join queries. Our survey focuses on exact approaches over high-dimensional data space, which covers 20 kNN Search methods and 9 kNN Join methods. To the best of our knowledge, this is the first work of a comprehensive survey of exact kNN queries over high-dimensional datasets. We specifically categorise the algorithms based on indexing strategies, data and space partitioning strategies, clustering techniques and the computing paradigm. We provide useful insights for the evolution of approaches based on the various categorisation factors, as well as the possibility of further expansion. Lastly, we discuss some open challenges and future research directions.

Spatiotemporal dynamics analysis of aquaculture zones and its impact on green tide disaster in Haizhou Bay, China.

With the rapid marine economic development, the problem of the marine ecological environment has become progressively prominent. Mariculture monitoring plays an essential role in sustaining ecological stability, rational planning, and green economic development of sea areas. Using the Landsat image, the raft-mariculture area information of Haizhou Bay and its adjacent southern waters were extracted by the object-oriented classification method based on remote sensing techniques. Landscape pattern index and principal component analysis were used to analyze the spatiotemporal expansion and structural changes of mariculture areas, and to quantify the effects of natural, socio-economic factors on the spatiotemporal variations of mariculture areas. This study discusses the correlation between the mariculture area and the outbreak scale of Enteromorpha Enteromorpha green tide. Results show that the object-oriented classification method has the highest accuracy, with total classification accuracy and Kappa coefficient of more than 90% and 0.79, respectively. The total area, patch density, and landscape shape index of mariculture areas in Haizhou Bay increase yearly, which demonstrates that the heterogeneity and fragmentation increase with the expansion of the mariculture area. The landscape pattern changes in the mariculture area are predominantly impacted by annual mean sea surface temperature (SST), annual average wind speed, social development level, and population density, etc. The larger the area of raft-aquaculture, the wider the outbreak scale of the Enteromorpha prolifera disaster. Study results can provide scientific references for the further development of mariculture in Haizhou Bay and marine environmental protection.

Three-dimensional porous manganese oxide/nickel/carbon microspheres as high-performance electromagnetic wave absorbers with superb photothermal property.

Regulating electromagnetic parameters and thus improving impedance matching characteristics by multi-component design is regarded as a prospective approach to obtain highly efficient electromagnetic wave absorption materials. Whereas, it is still challenging to fabricate microwave absorbers with strong absorption capacity and durability in harsh conditions. Based on the above considerations, three-dimensional porous multi-functional manganese oxide/nickel/carbon microspheres had been designed and prepared through a combined approach of facile solvothermal reactions and subsequent carbonization processes. The textural characteristic examinations demonstrated that, numerous manganese oxide and Ni nanoparticles of 15-20 nm in diameter were well dispersed in the carbon-based microspheres of approximately 0.8-1 µm in size. Microwave absorption property evaluation indicated that the minimum reflection loss reached up to -53.6 dB at 9.5 GHz, and effective absorption bandwidth of 3.7 GHz was achieved at matching thickness of merely 2.0 mm. The electromagnetic wave attenuation mechanisms analysis displayed that excellent impedance matching and various dissipation pathways, including magnetic loss, interfacial and dipole polarization relaxation synergistically contributed to the high microwave absorption performances of the porous composites. Radar cross-sectional simulation and photothermal measurements verified that the materials were supposed to have promising foregrounds in complicated circumstances.

Prolonged Longitudinal Transcutaneous Auricular Vagus Nerve Stimulation Effect on Striatal Functional Connectivity in Patients with Major Depressive Disorder.

BACKGROUND: Transcutaneous auricular vagus nerve stimulation (taVNS) is effective for treating major depressive disorder (MDD). We aimed to explore the modulating effect of prolonged longitudinal taVNS on the striatal subregions' functional connectivity (FC) in MDD patients. METHODS: Sixteen MDD patients were enrolled and treated with taVNS for 8 weeks. Sixteen healthy control subjects (HCs) were recruited without intervention. The resting-state FC (rsFC) based on striatal subregion seed points and the Hamilton Depression Scale (HAMD) were evaluated in the MDD patients and HCs at baseline and after 8 weeks. A two-way ANCOVA test was performed on each rsFC metric to obtain the (group-by-time) interactions. RESULTS: The rsFC values between the left ventral caudate (vCa) and right ventral prefrontal cortex (vPFC), and between the right nucleus accumbens (NAc) and right dorsal medial prefrontal cortex (dmPFC) and ventrolateral prefrontal cortex (vlPFC) are lower in the MDD patients compared to the HCs at baseline, and increase following taVNS; the rsFC values between the left vCa and right, superior occipital gyrus (SOG), and between the left dorsal caudate (dCa) and right cuneus are higher in MDD patients and decrease following taVNS. CONCLUSIONS: Prolonged longitudinal taVNS can modulate the striatum rsFC with the prefrontal cortex, occipital cortex, temporal cortex, and intra-striatum, and these changes partly underlie any symptomatic improvements. The results indicate that prolonged longitudinal taVNS may produce beneficial treatment effects by modulating the cortical striatum circuitry in patients with MDD.

BAI-Net: Individualized Anatomical Cerebral Cartography Using Graph Neural Network.

Brain atlas is an important tool in the diagnosis and treatment of neurological disorders. However, due to large variations in the organizational principles of individual brains, many challenges remain in clinical applications. Brain atlas individualization network (BAI-Net) is an algorithm that subdivides individual cerebral cortex into segregated areas using brain morphology and connectomes. The presented method integrates group priors derived from a population atlas, adjusts areal probabilities using the context of connectivity fingerprints derived from the fiber-tract embedding of tractography, and provides reliable and explainable individualized brain areas across multiple sessions and scanners. We demonstrate that BAI-Net outperforms the conventional iterative clustering approach by capturing significantly heritable topographic variations in individualized cartographies. The topographic variability of BAI-Net cartographies has shown strong associations with individual variability in brain morphology, connectivity as well as higher relationship on individual cognitive behaviors and genetics. This study provides an explainable framework for individualized brain cartography that may be useful in the precise localization of neuromodulation and treatments on individual brains.