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.

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.

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.

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.

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.

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.

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.

Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung.

BACKGROUND: Cellular diversity of the lung endothelium has not been systematically characterized in humans. We provide a reference atlas of human lung endothelial cells (ECs) to facilitate a better understanding of the phenotypic diversity and composition of cells comprising the lung endothelium. METHODS: We reprocessed human control single-cell RNA sequencing (scRNAseq) data from 6 datasets. EC populations were characterized through iterative clustering with subsequent differential expression analysis. Marker genes were validated by fluorescent microscopy and in situ hybridization. scRNAseq of primary lung ECs cultured in vitro was performed. The signaling network between different lung cell types was studied. For cross-species analysis or disease relevance, we applied the same methods to scRNAseq data obtained from mouse lungs or from human lungs with pulmonary hypertension. RESULTS: Six lung scRNAseq datasets were reanalyzed and annotated to identify >15 000 vascular EC cells from 73 individuals. Differential expression analysis of EC revealed signatures corresponding to endothelial lineage, including panendothelial, panvascular, and subpopulation-specific marker gene sets. Beyond the broad cellular categories of lymphatic, capillary, arterial, and venous ECs, we found previously indistinguishable subpopulations; among venous EC, we identified 2 previously indistinguishable populations: pulmonary-venous ECs (COL15A1neg) localized to the lung parenchyma and systemic-venous ECs (COL15A1pos) localized to the airways and the visceral pleura; among capillary ECs, we confirmed their subclassification into recently discovered aerocytes characterized by EDNRB, SOSTDC1, and TBX2 and general capillary EC. We confirmed that all 6 endothelial cell types, including the systemic-venous ECs and aerocytes, are present in mice and identified endothelial marker genes conserved in humans and mice. Ligand-receptor connectome analysis revealed important homeostatic crosstalk of EC with other lung resident cell types. scRNAseq of commercially available primary lung ECs demonstrated a loss of their native lung phenotype in culture. scRNAseq revealed that endothelial diversity is maintained in pulmonary hypertension. Our article is accompanied by an online data mining tool (www.LungEndothelialCellAtlas.com). CONCLUSIONS: Our integrated analysis provides a comprehensive and well-crafted reference atlas of ECs in the normal lung and confirms and describes in detail previously unrecognized endothelial populations across a large number of humans and mice.

Engineering of human brain organoids with a functional vascular-like system.

Human cortical organoids (hCOs), derived from human embryonic stem cells (hESCs), provide a platform to study human brain development and diseases in complex three-dimensional tissue. However, current hCOs lack microvasculature, resulting in limited oxygen and nutrient delivery to the inner-most parts of hCOs. We engineered hESCs to ectopically express human ETS variant 2 (ETV2). ETV2-expressing cells in hCOs contributed to forming a complex vascular-like network in hCOs. Importantly, the presence of vasculature-like structures resulted in enhanced functional maturation of organoids. We found that vascularized hCOs (vhCOs) acquired several blood-brain barrier characteristics, including an increase in the expression of tight junctions, nutrient transporters and trans-endothelial electrical resistance. Finally, ETV2-induced endothelium supported the formation of perfused blood vessels in vivo. These vhCOs form vasculature-like structures that resemble the vasculature in early prenatal brain, and they present a robust model to study brain disease in vitro.

Quantitative objective-based ring TIRFM system calibration through back focal plane imaging.

Being the established imaging tool for cell membrane-associated studies, total internal reflection fluorescence microscopy (TIRFM) still has some limitations. The most important one is the inhomogeneous evanescent excitation field mainly caused by the large-angle and fixed-azimuth illumination scheme, which can be eliminated by using ring-shaped illumination (ring TIRFM). However, it is challenging in assembling a ring TIRFM system with precise parameter control that works well. Here we emphasize the quantification of the ring TIRFM system and introduce a robust calibration routine to simultaneously rectify the asymmetry of the spinning light beam and determine the crucial experimental parameter, i.e., the incident angle. The calibration routine requires no specific sample preparation and is entirely based on the automatic back focal plane manipulation, avoiding possible errors caused by the sample difference and manual measurement. Its effectiveness is experimentally demonstrated by both the qualitative and quantitative comparisons of the images acquired using different samples, illumination schemes, and calibration approaches. These characteristics should enable our approach to greatly improve the practicability of TIRFM in life sciences.

Improved algorithm of non-line-of-sight imaging based on the Bayesian statistics.

The recovery of obscured objects is an important goal in imaging that has been approached by exploiting coherence properties, ballistic photons, and penetrating wavelengths. In this paper, a robust reconstruction non-line-of-sight (NLOS) algorithm was proposed based on the Bayesian statistics, using the temporal, spatial, and intensity information of each signal. Compared with conventional back-projection methods, this algorithm is able to handle random errors in data and to image occluded objects with a higher quality. An adjustable compensation mechanism in our method is effective in dealing with the diversity of objects with regard to reflective characteristics. Our algorithm was demonstrated to be efficient with both simulated and experimental data. In addition, we discuss the advantages over existing methods and further improvement of the proposed algorithm.

Identification of Key Disulfidptosis-Related Genes and Their Association with Gene Expression Subtypes in Crohn's Disease.

Background: Crohn's disease (CD) is a persistent inflammatory condition that impacts the gastrointestinal system and is characterized by a multifaceted pathogenesis involving genetic, immune, and environmental components. This study primarily investigates the relationship between gene expression and immune cell infiltration in CD, focusing on disulfidptosis-a novel form of cell death caused by abnormal disulfide accumulation-and its impact on various immune cell populations. By identifying key disulfidptosis-related genes (DRGs) and exploring their association with distinct gene expression subtypes, this research aims to enhance our understanding of CD and potentially other autoimmune diseases. Methods: Gene expression data from intestinal biopsy samples were collected from both individuals with CD and healthy controls, and these data were retrieved from the GEO database. Through gene expression level comparisons, various differentially expressed genes (DEGs) were identified. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to reveal the biological processes and pathways linked to these DEGs. Later, immune cell infiltration was evaluated. Hub candidate DRGs were identified using machine learning algorithms. Validation of the expression of hub DRGs was carried out using quantitative real-time polymerase chain reaction. The hub DRGs were subjected to unsupervised hierarchical clustering to classify CD patients into subtypes. The characteristics of each subtype were then analyzed. Results: Two hub DRGs (NDUFA11 and LRPPRC) were identified. NDUFA11 showed a significantly positive association with the abundance of Th17 cells. Conversely, higher expression levels of LRPPRC were associated with a reduced abundance of various immune cells, particularly monocytes. CD patients were classified into two disulfidptosis-related subtypes. Cluster B patients exhibited lower immune infiltration and milder clinical presentation. Conclusion: LRPPRC and NDUFA11 are identified as hub DRGs in CD, with potential roles in disulfidptosis and immune regulation. The disulfidptosis subtypes provide new insights into disease progression.

Analyzing Immune Cell Infiltration and Copper Metabolism in Diabetic Foot Ulcers.

Background: Diabetes impairs wound healing, notably in diabetic foot ulcers (DFU). Stress, marked by the accumulation of lipoylated mitochondrial enzymes and the depletion of Fe-S cluster proteins, triggers cuproptosis-a distinct form of cell death. The involvement of copper in the pathophysiology of DFU has been recognized, and currently, a copper-based therapeutic strategy is emerging as a viable option for enhancing ulcer healing. This study investigates genes linked to copper metabolism in DFU, aiming to uncover potential targets for therapeutic intervention. Methods: Two diabetic wound Gene Expression Omnibus (GEO) datasets were analyzed to study immune cell dysregulation in diabetic wounds. Differentially expressed genes related to copper metabolism were identified and analyzed using machine learning methods. Gene ontology, pathway enrichment, and immune infiltration analyses were performed using DFU samples. The expression of identified genes was validated using qRT-PCR and single-cell RNA sequencing. Results: Ten genes associated with copper metabolism were identified. Among these, SLC31A1 and ADNP were found to be significantly differentially expressed in DFU. Notably, SLC31A1 exhibited higher expression in macrophages, whereas ADNP was found to be highly expressed in fibroblasts and chondrocytes. Conclusion: The study indicates a close link between copper metabolism, the infiltration of immune cells, and DFU. It proposes that copper metabolism could influence the progression of DFU through the activation of immune responses. These observations offer fresh perspectives on the underlying mechanisms of DFU and identify potential targets for therapeutic intervention.

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.

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.

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.

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.

Hydrogen-induced tunable remanent polarization in a perovskite nickelate.

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping.

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.