An improved attention module based on nnU-Net for segmenting primary central nervous system lymphoma (PCNSL) in MRI images1.

BACKGROUND: Accurate volumetric segmentation of primary central nervous system lymphoma (PCNSL) is essential for assessing and monitoring the tumor before radiotherapy and the treatment planning. The tedious manual segmentation leads to interindividual and intraindividual differences, while existing automatic segmentation methods cause under-segmentation of PCNSL due to the complex and multifaceted nature of the tumor. OBJECTIVE: To address the challenges of small size, diffused distribution, poor inter-layer continuity on the same axis, and tendency for over-segmentation in brain MRI PCNSL segmentation, we propose an improved attention module based on nnUNet for automated segmentation. METHODS: We collected 114 T1 MRI images of patients in the Huashan Hospital, Shanghai. Then randomly split the total of 114 cases into 5 distinct training and test sets for a 5-fold cross-validation. To efficiently and accurately delineate the PCNSL, we proposed an improved attention module based on nnU-Net with 3D convolutions, batch normalization, and residual attention (res-attention) to learn the tumor region information. Additionally, multi-scale dilated convolution kernels with different dilation rates were integrated to broaden the receptive field. We further used attentional feature fusion with 3D convolutions (AFF3D) to fuse the feature maps generated by multi-scale dilated convolution kernels to reduce under-segmentation. RESULTS: Compared to existing methods, our attention module improves the ability to distinguish diffuse and edge enhanced types of tumors; and the broadened receptive field captures tumor features of various scales and shapes more effectively, achieving a 0.9349 Dice Similarity Coefficient (DSC). CONCLUSIONS: Quantitative results demonstrate the effectiveness of the proposed method in segmenting the PCNSL. To our knowledge, this is the first study to introduce attention modules into deep learning for segmenting PCNSL based on brain magnetic resonance imaging (MRI), promoting the localization of PCNSL before radiotherapy.

Comprehensive analysis reveals that LTBR is a immune-related biomarker for glioma.

Glioma is a common malignant brain tumor with great heterogeneity and huge difference in clinical outcomes. Although lymphotoxin (LT) beta receptor (LTBR) has been linked to immune system and response development for decades, the expression and function in glioma have not been investigated. To confirm the expression profile of LTBR, integrated RNA-seq data from glioma and normal brain tissues were analyzed. Functional enrichment analysis, TMEscore analysis, immune infiltration, the correlation of LTBR with immune checkpoints and ferroptosis, and scRNAseq data analysis in gliomas were in turn performed, which pointed out that LTBR was pertinent to immune functions of macrophages in gliomas. In addition, after being trained and validated in the tissue samples of the integrated dataset, an LTBR DNA methylation-based prediction model succeeded to distinguish gliomas from non-gliomas, as well as the grades of glioma. Moreover, by virtue of the candidate LTBR CpG sites, a prognostic risk-score model was finally constructed to guide the chemotherapy, radiotherapy, and immunotherapy for glioma patients. Taken together, LTBR is closely correlated with immune functions in gliomas, and LTBR DNA methylation could serve as a biomarker for diagnosis and prognosis of gliomas.

Neuromorphic one-shot learning utilizing a phase-transition material.

Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to fourfold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning in neuromorphic hardware.

Damage sensing through TLR9 Promotes Viral Clearance and Recovery During Influenza Infection.

Host response aimed at eliminating the infecting pathogen, as well as the pathogen itself, can cause tissue injury. Tissue injury leads to the release of a myriad of cellular components including mitochondrial DNA, which the host senses through pattern recognition receptors. How the sensing of tissue injury by the host shapes the anti-pathogen response remains poorly understood. In this study, we utilized mice that are deficient in toll-like receptor-9 (TLR9), which binds to unmethylated CpG DNA sequences such as those present in bacterial and mitochondrial DNA. To avoid direct pathogen sensing by TLR9, we utilized the influenza virus, which lacks ligands for TLR9, to determine how damage sensing by TLR9 contributes to anti-influenza immunity. Our data show that TLR9-mediated sensing of tissue damage promotes an inflammatory response during early infection, driven by the myeloid cells and associated cytokine responses. Along with the diminished inflammatory response, the absence of damage sensing through TLR9 led to impaired viral clearance manifested as a higher and prolonged influenza burden in the lung. The absence of TLR9 led to extensive infection of myeloid cells including monocytes and macrophages rendering them highly inflammatory, despite having a low initial inflammatory response. The persistent inflammation driven by infected myeloid cells led to persistent lung injury and impaired recovery in influenza-infected TLR9-/- mice. Further, we show elevated circulating TLR9 ligands in the plasma samples of patients with influenza, demonstrating its clinical relevance. Overall, over data show an essential role of damage sensing through TLR9 in promoting anti-influenza immunity.

Organ Boundary Circuits Regulate Sox9+ Alveolar Tuft Cells During Post-Pneumonectomy Lung Regeneration.

Tissue homeostasis is controlled by cellular circuits governing cell growth, organization, and differentation. In this study we identify previously undescribed cell-to-cell communication that mediates information flow from mechanosensitive pleural mesothelial cells to alveolar-resident stem-like tuft cells in the lung. We find mesothelial cells to express a combination of mechanotransduction genes and lineage-restricted ligands which makes them uniquely capable of responding to tissue tension and producing paracrine cues acting on parenchymal populations. In parallel, we describe a large population of stem-like alveolar tuft cells that express the endodermal stem cell markers Sox9 and Lgr5 and a receptor profile making them uniquely sensitive to cues produced by pleural Mesothelium. We hypothesized that crosstalk from mesothelial cells to alveolar tuft cells might be central to the regulation of post-penumonectomy lung regeneration. Following pneumonectomy, we find that mesothelial cells display radically altered phenotype and ligand expression, in a pattern that closely tracks with parenchymal epithelial proliferation and alveolar tissue growth. During an initial pro-inflammatory stage of tissue regeneration, Mesothelium promotes epithelial proliferation via WNT ligand secretion, orchestrates an increase in microvascular permeability, and encourages immune extravasation via chemokine secretion. This stage is followed first by a tissue remodeling period, characterized by angiogenesis and BMP pathway sensitization, and then a stable return to homeostasis. Coupled with key changes in parenchymal structure and matrix production, the cumulative effect is a now larger organ including newly-grown, fully-functional tissue parenchyma. This study paints Mesothelial cells as a key orchestrating cell type that defines the boundary of the lung and exerts critical influence over the tissue-level signaling state regulating resident stem cell populations. The cellular circuits unearthed here suggest that human lung regeneration might be inducible through well-engineered approaches targeting the induction of tissue regeneration and safe return to homeostasis.

Preparation of cellulose acetate based flexible separator and its application in zinc-air batteries.

Flexible solid-state zinc-air batteries as a wearable energy storage device with great potential, and their separators, which control ion permeability, inhibit zinc dendrite generation, and regulate catalytic active sites, have been developed as gel electrolyte separators with high retention of electrolyte uptake. However, the gel electrolyte separator still has problems such as poor affinity with the electrolyte and poor ionic conductivity, which limits its further application. In order to further improve the electrolyte absorption, ionic conductivity and mechanical strength of cellulose acetate(CA)/polyvinyl alcohol (PVA) nanofibers, TiO2was added to CA/PVA to increase the porosity, and glutaraldehyde (GA) was used to modify the CA/PVA/TiO2separator by acetal reaction with CA and PVA to make the molecules closely linked. The results shows that the optimal mass fractions of TiO2and GA were 2% and 5%, respectively. At this time, the porosity and absorption rate of the separator increased from 48% to 68.2% and 142.4% to 285.3%, respectively. The discharge capacity reached 179 mA cm-3, and the cycle stability rate was 89% after 7 stable constant current charge/discharge cycles.

PA suppresses antitumor immunity of T cells by disturbing mitochondrial activity through Akt/mTOR-mediated Ca2+ flux.

Deciphering the mechanisms behind how T cells become exhausted and regulatory T cells (Tregs) differentiate in a tumor microenvironment (TME) will significantly benefit cancer immunotherapy. A common metabolic alteration feature in TME is lipid accumulation, associated with T cell exhaustion and Treg differentiation. However, the regulatory role of free fatty acids (FFA) on T cell antitumor immunity has yet to be clearly illustrated. Our study observed that palmitic acid (PA), the most abundant saturated FFA in mouse plasma, enhanced T cell exhaustion and Tregs population in TME and increased tumor growth. In contrast, oleic acid (OA), a monounsaturated FFA, rescued PA-induced T cell exhaustion, decreased Treg population, and ameliorated T cell antitumor immunity in an obese mouse model. Mechanistically, mitochondrial metabolic activity is critical in maintaining T cell function, which PA attenuated. PA-induced T cell exhaustion and Treg formation depended on CD36 and Akt/mTOR-mediated calcium signaling. The study described a new mechanism of PA-induced downregulation of antitumor immunity of T cells and the therapeutic potential behind its restoration by targeting PA.

Mechanical properties, corrosion and degradation behaviors, and in vitro cytocompatibility of a biodegradable Zn-5La alloy for bone-implant applications.

Zinc (Zn) and its alloys are used in bone-fixation devices as biodegradable bone-implant materials due to their good biosafety, biological function, biodegradability, and formability. Unfortunately, the clinical application of pure Zn is hindered by its insufficient mechanical properties and slow degradation rate. In this study, a Zn-5 wt.% lanthanum (Zn-5La) alloy with enhanced mechanical properties, suitable degradation rate, and cytocompatibility was developed through La alloying and hot extrusion. The hot-extruded (HE) Zn-5La alloy showed ultimate tensile strength of 286.3 MPa, tensile yield strength of 139.7 MPa, elongation of 35.7%, compressive yield strength of 262.7 MPa, and microhardness of 109.7 HV. The corrosion resistance of the HE Zn-5La in Hanks' and Dulbecco's modified Eagle medium (DMEM) solutions gradually increased with prolonged immersion time. Further, the HE Zn-5La exhibited an electrochemical corrosion rate of 36.7 µm/y in Hanks' solution and 11.4 µm/y in DMEM solution, and a degradation rate of 49.5 µm/y in Hanks' solution and 30.3 µm/y in DMEM solution, after 30 d of immersion. The corrosion resistance of both HE Zn and Zn-5La in DMEM solution was higher than in Hanks' solution. The 25% concentration extract of the HE Zn-5La showed a cell viability of 106.5%, indicating no cytotoxicity toward MG-63 cells. We recommend the HE Zn-5La alloy as a promising candidate material for biodegradable bone-implant applications. STATEMENT OF SIGNIFICANCE: This work reports the mechanical properties, corrosion and degradation behaviors, in vitro cytocompatibility and antibacterial ability of biodegradable Zn-5La alloy for bone-implant applications. Our findings demonstrate that the hot-extruded (HE) Zn-5La alloy showed an ultimate tensile strength of 286.3 MPa, a yield strength of 139.7 MPa, an elongation of 35.7%, compressive yield strength of 262.7 MPa, and microhardness of 109.7 HV. HE Zn-5La exhibited appropriate degradation rates in Hanks' and DMEM solutions. Furthermore, the HE Zn-5La alloy showed good cytocompatibility toward MG-63 and MC3T3-E1 cells and greater antibacterial ability against S. aureus.

Spatial Interactions in Hydrogenated Perovskite Nickelate Synaptic Networks.

A key aspect of how the brain learns and enables decision-making processes is through synaptic interactions. Electrical transmission and communication in a network of synapses are modulated by extracellular fields generated by ionic chemical gradients. Emulating such spatial interactions in synthetic networks can be of potential use for neuromorphic learning and the hardware implementation of artificial intelligence. Here, we demonstrate that in a network of hydrogen-doped perovskite nickelate devices, electric bias across a single junction can tune the coupling strength between the neighboring cells. Electrical transport measurements and spatially resolved diffraction and nanoprobe X-ray and scanning microwave impedance spectroscopic studies suggest that graded proton distribution in the inhomogeneous medium of hydrogen-doped nickelate film enables this behavior. We further demonstrate signal integration through the coupling of various junctions.

Study on the Construction of Interlayer Adjustable C@MoS2 Fiber Anode by Biomass Confining and its Lithium/Sodium Storage Mechanism.

Building a stable and controllable interlayer structure is the key to improving the sodium storage cycling stability and rate performance of two-dimensional anode materials. This study explored the rich functional groups in bacterial cellulose culture medium in the way of biological self-assembly. Mo precursors were used to produce chemical bond in bacterial cellulose culture medium, and intercalation groups are introduced to achieve MoS2 localized nucleation and in situ localized construction of carbon intercalation stable interlaminar structure, thus improving ion transport dynamics and cycle stability. In order to avoid structural irreversibility of MoS2 at low potential, an extended voltage window of 1.5-4 V was selected for lithium/sodium intercalation testing. It was found that there was a significant improvement in sodium storage capacity and stability. During the electrochemical cycling process, in-situ Raman testing revealed that the structure of MoS2 was completely reversible, and the intensity changes of MoS2 characteristic peaks showed in-plane vibration without involving interlayer bonding fracture. Moreover, after the lithium sodium was removed from the intercalation C@MoS2 all structures have good retention.

Clinical Translation of Engineered Pulmonary Vascular Models.

Diseases in pulmonary vasculature remain a major cause of morbidity and mortality worldwide. Numerous pre-clinical animal models were developed to understand lung vasculature during diseases and development. However, these systems are typically limited in their ability to represent human pathophysiology for the study of disease and drug mechanisms. In recent years, a growing number of studies have focused on developing in vitro experimental platforms that mimic human tissues/organs. In this chapter, we discuss the key components involved in developing engineered pulmonary vascular modeling systems and provide perspectives on ways to improve the translational potential of existing models.

Convolutional neural network to predict IDH mutation status in glioma from chemical exchange saturation transfer imaging at 7 Tesla.

Background and goal: Noninvasive prediction of isocitrate dehydrogenase (IDH) mutation status in glioma guides surgical strategies and individualized management. We explored the capability on preoperatively identifying IDH status of combining a convolutional neural network (CNN) and a novel imaging modality, ultra-high field 7.0 Tesla (T) chemical exchange saturation transfer (CEST) imaging. Method: We enrolled 84 glioma patients of different tumor grades in this retrospective study. Amide proton transfer CEST and structural Magnetic Resonance (MR) imaging at 7T were performed preoperatively, and the tumor regions are manually segmented, leading to the "annotation" maps that offers the location and shape information of the tumors. The tumor region slices in CEST and T1 images were further cropped out as samples and combined with the annotation maps, which were inputted to a 2D CNN model for generating IDH predictions. Further comparison analysis to radiomics-based prediction methods was performed to demonstrate the crucial role of CNN for predicting IDH based on CEST and T1 images. Results: A fivefold cross-validation was performed on the 84 patients and 4090 slices. We observed a model based on only CEST achieved accuracy of 74.01% ± 1.15%, and the area under the curve (AUC) of 0.8022 ± 0.0147. When using T1 image only, the prediction performances dropped to accuracy of 72.52% ± 1.12% and AUC of 0.7904 ± 0.0214, which indicates no superiority of CEST over T1. However, when we combined CEST and T1 together with the annotation maps, the performances of the CNN model were further boosted to accuracy of 82.94% ± 1.23% and AUC of 0.8868 ± 0.0055, suggesting the importance of a joint analysis of CEST and T1. Finally, using the same inputs, the CNN-based predictions achieved significantly improved performances above those from radiomics-based predictions (logistic regression and support vector machine) by 10% to 20% in all metrics. Conclusion: 7T CEST and structural MRI jointly offer improved sensitivity and specificity of preoperative non-invasive imaging for the diagnosis of IDH mutation status. As the first study of CNN model on imaging acquired at ultra-high field MR, our results could demonstrate the potential of combining ultra-high-field CEST and CNN for facilitating decision-making in clinical practice. However, due to the limited cases and B1 inhomogeneities, the accuracy of this model will be improved in our further study.

Identification of Critical Modules and Biomarkers of Ulcerative Colitis by Using WGCNA.

Background: Ulcerative colitis (UC) is a chronic inflammatory disease of the colon and rectum that has no exact cause and is characterized by relapsing and remitting episodes. We aimed to find biomarkers of UC and its causes. Methods: We got GSE73661 from the GEO database and used WGCNA to find DEGs that were expressed in the same way in both normal and UC samples. To identify the co-expression modules, we used Weighted Gene Co-Expression Network Analysis. Next, we selected genes that were both DEGs and parts of main modules. Later, three datasets were used to find the hub genes, and qRT-PCR was utilized to confirm the in-silico findings. Additionally, we analyzed the connection between the hub genes and the filtration of immune cells in UC. Using the databases, we made predictions about the miRNAs and lncRNAs that regulate the hub genes and predicted possible therapeutic drugs. Results: We found 822 DEGs and three main modules related to immunity, endoplasmic reticulum, and metabolism. Using another three datasets and human samples to confirm the mRNA expression of these genes in UC patients, XBP1 and PLPP1 were selected as hub genes, and had excellent diagnostic potential. According to the findings of the immune infiltration, patients with UC exhibited a larger proportion of immune cells. And hub genes, particularly XBP1, were closely linked to a number of immune cell infiltrations. Based on the databases and hub genes, a lncRNA-miRNA-mRNA network, including two miRNAs (miR-214-3p and miR-93-5p), two hub genes, and 124 lncRNAs, and potential therapeutic medicine were identified. Conclusion: We found two new genes, XBP1 and PLPP1, that are involved in UC and can help diagnose and measure the disease. XBP1 also relates to clinical scores and immune cells. We suggested a gene network and possible drugs based on them.

Automatic bundle-specific white matter fiber tracking tool using diffusion tensor imaging data: A pilot trial in the application of language-related glioma resection.

Cerebral neoplasms like gliomas may cause intracranial pressure increasing, neural tract deviation, infiltration, or destruction in peritumoral areas, leading to neuro-functional deficits. Novel tracking technology, such as DTI, can objectively reveal and visualize three-dimensional white matter trajectories; in combination with intraoperative navigation, it can help achieve maximum resection whilst minimizing neurological deficit. Since the reconstruction of DTI raw data largely relies on the technical engineering and anatomical experience of the operator; it is time-consuming and prone to operator-induced bias. Here, we develop new user-friendly software to automatically segment and reconstruct functionally active areas to facilitate precise surgery. In this pilot trial, we used an in-house developed software (DiffusionGo) specially designed for neurosurgeons, which integrated a reliable diffusion-weighted image (DWI) preprocessing pipeline that embedded several functionalities from software packages of FSL, MRtrix3, and ANTs. The preprocessing pipeline is as follows: 1. DWI denoising, 2. Gibbs-ringing removing, 3. Susceptibility distortion correction (process if opposite polarity data were acquired), 4. Eddy current and motion correction, and 5. Bias correction. Then, this fully automatic multiple assigned criteria algorithms for fiber tracking were used to achieve easy modeling and assist precision surgery. We demonstrated the application with three language-related cases in three different centers, including a left frontal, a left temporal, and a left frontal-temporal glioma, to achieve a favorable surgical outcome with language function preservation or recovery. The DTI tracking result using DiffusionGo showed robust consistency with direct cortical stimulation (DCS) finding. We believe that this fully automatic processing pipeline provides the neurosurgeon with a solution that may reduce time costs and operating errors and improve care quality and surgical procedure quality across different neurosurgical centers.

Rational engineering of lung alveolar epithelium.

Engineered whole lungs may one day expand therapeutic options for patients with end-stage lung disease. However, the feasibility of ex vivo lung regeneration remains limited by the inability to recapitulate mature, functional alveolar epithelium. Here, we modulate multimodal components of the alveolar epithelial type 2 cell (AEC2) niche in decellularized lung scaffolds in order to guide AEC2 behavior for epithelial regeneration. First, endothelial cells coordinate with fibroblasts, in the presence of soluble growth and maturation factors, to promote alveolar scaffold population with surfactant-secreting AEC2s. Subsequent withdrawal of Wnt and FGF agonism synergizes with tidal-magnitude mechanical strain to induce the differentiation of AEC2s to squamous type 1 AECs (AEC1s) in cultured alveoli, in situ. These results outline a rational strategy to engineer an epithelium of AEC2s and AEC1s contained within epithelial-mesenchymal-endothelial alveolar-like units, and highlight the critical interplay amongst cellular, biochemical, and mechanical niche cues within the reconstituting alveolus.

Decellularization compromises mechanical and structural properties of the native trachea.

Tracheal replacement using tissue engineering technologies offers great potential to improve previously intractable clinical interventions, and interest in this area has increased in recent years. Many engineered airway constructs currently rely on decellularized native tracheas to serve as the scaffold for tissue repair. Yet, mechanical failure leading to airway narrowing and collapse remains a major cause of morbidity and mortality following clinical implantation of decellularized tracheal grafts. To understand better the factors contributing to mechanical failure in vivo, we characterized the histo-mechanical properties of tracheas following two different decellularization protocols, including one that has been used clinically. All decellularized tracheas deviated from native mechanical behavior, which may provide insights into observed in vivo graft failures. We further analyzed protein content by western blot and analyzed microstructure by histological staining and found that the specific method of decellularization resulted in significant differences in the depletion of proteoglycans and degradation of collagens I, II, III, and elastin. Taken together, this work demonstrates that the heterogeneous architecture and mechanical behavior of the trachea is severely compromised by decellularization. Such structural deterioration may contribute to graft failure clinically and limit the potential of decellularized native tracheas as viable long-term orthotopic airway replacements.

Genetically predicted visceral adipose tissue and risk of nine non-tumour gastrointestinal diseases: evidence from a Mendelian randomization study.

BACKGROUND: Numerous studies have linked visceral adipose tissue (VAT) to gastrointestinal diseases. However, it remains unclear whether these associations reflect causal relationships. METHODS: We used a two-sample Mendelian randomization (MR) approach to elucidate the causal effect of VAT on nine non-tumour gastrointestinal diseases. The inverse-variance weighted method was used to perform the MR analyses. Complementary and multivariable MR analyses were performed to confirm the results. RESULTS: Genetically predicted higher VAT was associated with an increased risk of gastro-oesophageal reflux disease (GORD) (odds ratio [OR], 1.21; 95% confidence interval [CI], 1.09-1.34; P = 3.06 × 10-4), duodenal ulcer (DU) (OR, 1.40; 95% CI, 1.10-1.77; P = 0.005), cholelithiasis (OR, 1.75; 95% CI, 1.53-2.00; P = 1.14 × 10-16), and non-alcoholic fatty liver disease (NAFLD) (OR, 2.68; 95% CI, 1.87-3.82; P = 6.26 × 10-8). There were suggestive associations between VAT and gastric ulcer (GU) (OR, 1.22; 95% CI, 1.01-1.48; P = 0.035) and acute pancreatitis (AP) (OR, 1.26; 95% CI, 1.05-1.52; P = 0.013). However, there was little evidence to support the associations between VAT and inflammatory bowel disease, irritable bowel syndrome, or chronic pancreatitis. The associations with GORD, GU, and NAFLD remained in the multivariable MR analyses with adjustment for body mass index (BMI). CONCLUSIONS: This study provided evidence in support of causal associations between VAT and GORD, GU, DU, cholelithiasis, AP, and NAFLD. Moreover, the associations between GORD, GU, and NAFLD were independent of the effect of BMI.

Brain perfusion, cognition, and plasma Alzheimer's biomarkers in moyamoya disease.

INTRODUCTION: Because growing interest has been focusing on cerebral blood flow (CBF) to predict, prevent, and treat Alzheimer's disease (AD), it is important to clarify the role of CBF in AD pathology and cognitive decline. METHODS: In a moyamoya disease (MMD) cohort, we examined CBF, specific cognitive domains, and plasma AD biomarkers, as well as correlations among these variables. RESULTS: CBF was significantly reduced in newly diagnosed MMD patients, while plasma phosphorylated tau181 was elevated and positively correlated with hypoperfusion accumulation. MMD patients scored significantly lower than controls in multiple cognitive tests. Revascularization increased CBF to the recipient brain territories as well as cognitive performance but produced no significant change in AD biomarker levels. DISCUSSION: These data suggest a link between accumulated reductions in CBF and cognitive decline, as well as a possible role of AD-like pathological burden. Further studies in MMD will provide opportunities to explore new treatment strategies.

Herpes Virus Entry Mediator Costimulation Signaling Enhances CAR T-cell Efficacy Against Solid Tumors Through Metabolic Reprogramming.

Costimulatory domains (CSD) of 4-1BB and CD28 are most widely used in chimeric antigen receptor (CAR)-engineered T cells. These CAR T cells have shown encouraging efficacy in the treatment of hematologic malignancies but have limited efficacy in solid tumors. The herpes virus entry mediator (HVEM) is a costimulatory molecule with a novel downstream signaling pathway. In response to target cells, CAR T cells with a HVEM CSD (HVEM-CAR T) displayed more robust cytokine release and cytotoxicity than 4-1BB-CAR T or CD28-CAR T in vitro. Furthermore, HVEM-CAR T showed superior therapeutic efficacy in several mouse tumor models. Mechanistically, the HVEM CSD endowed CAR T cells with attenuated exhaustion, improved function and persistence, and enhanced metabolic activities in tumor tissue compared with 4-1BB-based or CD28-based CAR T cells. These studies establish that the HVEM CSD has the potential to improve the therapeutic efficacy of CAR T cells against solid tumors.

Complex Oxides for Brain-Inspired Computing: A Review.

The fields of brain-inspired computing, robotics, and, more broadly, artificial intelligence (AI) seek to implement knowledge gleaned from the natural world into human-designed electronics and machines. In this review, the opportunities presented by complex oxides, a class of electronic ceramic materials whose properties can be elegantly tuned by doping, electron interactions, and a variety of external stimuli near room temperature, are discussed. The review begins with a discussion of natural intelligence at the elementary level in the nervous system, followed by collective intelligence and learning at the animal colony level mediated by social interactions. An important aspect highlighted is the vast spatial and temporal scales involved in learning and memory. The focus then turns to collective phenomena, such as metal-to-insulator transitions (MITs), ferroelectricity, and related examples, to highlight recent demonstrations of artificial neurons, synapses, and circuits and their learning. First-principles theoretical treatments of the electronic structure, and in situ synchrotron spectroscopy of operating devices are then discussed. The implementation of the experimental characteristics into neural networks and algorithm design is then revewed. Finally, outstanding materials challenges that require a microscopic understanding of the physical mechanisms, which will be essential for advancing the frontiers of neuromorphic computing, are highlighted.