Construction of a Nomogram predictive model for post-discharge psychosomatic review of psychiatric liaison consultation patients based on medical record data

Epidemiological studies have shown that almost all physical illnesses coexist with psychiatric disorders or psychological problems, and the severity of mental illness is positively correlated with the duration and severity of physical illness. Liaison consultations are valuable in identifying and treating psychiatric disorders, but the rate of psychiatric follow-up after consultation is low in outpatients. This study aimed to investigate the factors influencing post-discharge psychosomatic follow-up visits in patients undergoing psychiatric liaison consultation in general hospitals and construct a Nomogram prediction model for patients’ post-discharge psychosomatic follow-up visits. Medical record data of inpatients who received psychiatric liaison consultations at Xi’an International Medical Center Hospital in China from September 2019 to September 2020 were analyzed. Lasso regression and multivariate logistic regression analyses were conducted to screen independent influences on the occurrence of post-discharge psychosomatic follow-ups in patients undergoing psychiatric liaison consultations. Risk prediction column line graphs were constructed using R software, and the models were evaluated. Of the 494 inpatients who received psychiatric liaison consultations, 115 patients (23.279%) (mean age = 54.8 years) went for post-discharge psychosomatic follow-up, while 379 patients (mean age = 59.3 years) had no record of psychosomatic follow-up. Furthermore, occupation, interval.time, diagnosis, out.antipsychotics, and recommendations.followup were independent factors influencing post-discharge psychosomatic follow-up. The model accurately predicted post-discharge psychosomatic follow-up behavior of inpatients who received psychiatric liaison consultations. Lastly, the clinical decision curve analysis showed that the model had good validity for clinical application. Patients who received a psychiatric liaison consultation with a ≤ 10-day interval between admission to the hospital and application for consultation, were discharged with prescribed medication, and had a clear written medical order for a follow-up consultation had an increased probability of psychosomatic follow-up after discharge

Ultrasound-driven BaTiO3 nanorobots patching immunologic barrier to cure chronic rheumatoid arthritis

The disruption and reconstruction of the TREM2+ tissue resident macrophage (TRM) barrier on the surface of synovial lining play a key role in the activation and "remission" of rheumatoid arthritis (RA), which engender the prediction of this immunologic barrier as a potential driver for the achievement of "cure" in RA. However, strategies to promote the reconstruction of this barrier have not been reported, and the effect of patching this barrier remains unidentified. On the other hand, appropriate piezoelectric stimulation can reprogram macrophages, which has never been exerted on this barrier TRM yet. Herein, we design piezoelectric tetragonal BaTiO3 (BTO) ultrasound-driven nanorobots (USNRs) by the solvothermal synthesis method, which demonstrates satisfactory electro-mechanical conversion effects, paving the way to generate controllable electrical stimulation under ultrasound to reprogram the barrier TRM by minimally invasive injection into joint cavity. It is demonstrated that the immunologic barrier could be patched by this USNR effectively, thereby eliminating the hyperplasia of vessels and nerves (HVN) and synovitis. Additionally, TREM2 deficiency serum-transfected arthritis (STA) mice models are applied and proved the indispensable role of TREM2 in RA curing mediated by USNR. In all, our work is an interesting and important exploration to expand the classical tetragonal BTO nanoparticles in the treatment of autoimmune diseases, providing a new idea and direction for the biomedical application of piezoelectric ceramics

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Ectopic tissue engineered ligament with silk collagen scaffold for ACL regeneration: A preliminary study

Anterior cruciate ligament (ACL) reconstruction remains a formidable clinical challenge because of the lack of vascularization and adequate cell numbers in the joint cavity. In this study, we developed a novel strategy to mimic the early stage of repair in vivo, which recapitulated extra-articular inflammatory response to facilitate the early ingrowth of blood vessels and cells. A vascularized ectopic tissue engineered ligament (ETEL) with silk collagen scaffold was developed and then transferred to reconstruct the ACL in rabbits without interruption of perfusion. At 2 weeks after ACL reconstruction, more well-perfused cells and vessels were found in the regenerated ACL with ETEL, which decreased dramatically at the 4 and 12 week time points with collagen deposition and maturation. ACL treated with ETEL exhibited more mature ligament structure and enhanced ligament-bone healing post-reconstructive surgery at 4 and 12 weeks, as compared with the control group. In addition, the ETEL group was demonstrated to have higher modulus and stiffness than the control group significantly at 12 weeks post-reconstructive surgery. In conclusion, our results demonstrated that the ETEL can provide sufficient vascularity and cellularity during the early stages of healing, and subsequently promote ACL regeneration and ligament-bone healing, suggesting its clinic use as a promising therapeutic modality. Statement of Significance Early inflammatory cell infiltration, tissue and vessels ingrowth were significantly higher in the extra articular implanted scaffolds than theses in the joint cavity. By mimicking the early stages of wound repair, which provided extra-articular inflammatory stimulation to facilitate the early ingrowth of blood vessels and cells, a vascularized ectopic tissue engineered ligament (ETEL) with silk collagen scaffold was constructed by subcutaneous implantation for 2 weeks. The fully vascularized TE ligament was then transferred to rebuild ACL without blood perfusion interruption, and was demonstrated to exhibit improved ACL regeneration, bone tunnel healing and mechanical properties. (C) 2017 Published by Elsevier Ltd on behalf of Acta Materialia Inc

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation