Flexible organic near-infrared (NIR) phototransistors hold promising prospects for potential applications such as noninvasive bioimaging, health monitoring, and biometric authentication. For integrated circuits of high-performance devices, organic single-crystalline micro-/nanostructures with precise positioning are prominently anticipated. However, the manufacturing of organic single-crystalline arrays remains a conundrum due to difficulties encountered in patterning arrays of dewetting processes at micron-scale confined space and modulating the dewetting dynamics. Herein, we utilize a capillary-bridge lithography strategy to fabricate organic 1D arrays with high quality, homogeneous size, and deterministic location toward high-performance flexible organic NIR phototransistors. Regular micro-liquid stripes and unidirectional dewetting are synchronously achieved by adapting micropillar templates with asymmetric wettability. As a result, high-throughput 1D arrays based organic field-effect transistors exhibit high electron mobility up to 9.82 cm2  V-1  s-1 . Impressively, flexible NIR phototransistors also show outstanding photoelectronic performances with a photosensitivity of 9.87 × 105 , a responsivity of 1.79 × 104  A W-1 , and a specific detectivity of 3.92 × 1014 Jones. This work paves a novel way to pattern high-throughput organic single-crystalline microarrays toward flexible NIR organic optoelectronics.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no consensus on the molecular subtypes of TNBC, likely due to discrepancies in technical and computational methods used by different research groups. Here, we reassessed the major steps for TNBC subtyping, validated the reproducibility of established TNBC subtypes, and identified two more subtypes with a larger sample size. By comparing results from different workflows, we demonstrated the limitations of formalin-fixed, paraffin-embedded samples, as well as batch effect removal across microarray platforms. We also refined the usage of computational tools for TNBC subtyping. Furthermore, we integrated high-quality multi-institutional TNBC datasets (discovery set: n = 457; validation set: n = 165). Performing unsupervised clustering on the discovery and validation sets independently, we validated four previously discovered subtypes: luminal androgen receptor, mesenchymal, immunomodulatory, and basal-like immunosuppressed. Additionally, we identified two potential intermediate states of TNBC tumors based on their resemblance with more than one well-characterized subtype. In summary, we addressed the issues and limitations of previous TNBC subtyping through comprehensive analyses. Our results promote the rational design of future subtyping studies and provide new insights into TNBC patient stratification.

Lung cancer is the leading cause of cancer death in most countries. Although early diagnosis and treatment critically influence prognosis, lung cancers are generally only discovered in the late stages of the disease.
Widely-used screening and diagnostic methods are not suitable for preventive screening, and high-throughput technologies based on serum biomarkers are needed.
We screened 501 serum samples, including 224 lung cancer (LC), 126 disease control (DC), and 151 healthy donor (HC) samples for new serum autoantibodies as biomarkers in the early diagnosis of lung cancer. In phase I, we used HuProtTM microarrays to perform preliminary serum antibody screening on 24 LC and 24 HC samples. In phase II, we screened 60 LC, 60 DC, and 60 HC serum samples using focused arrays constructed with 22 of the candidate autoantibody biomarkers screened out in phase I.
After data modeling and validation, we selected four potential early LC protein biomarker candidates, IL2RB, CENPB, TP53, and XAGE1A, with individual specificities >90% and sensitivities ranging from 21.2% to 32.2%. These four biomarkers had a specificity of >90% and a sensitivity of >65.5% for early LC when they combined in a panel. Further evaluation of these four biomarker candidates using ELISA assays and 273 serum samples (140 LC, 66 DC, and 67 HC) gave similar results (specificity of >91.7%, sensitivity >61.43%).
IL2RB, CENPB, TP53, and XAGE1A combined biomarker panel holds potential for rapid screening and improving the diagnosis of early-stage LC, thus potentially also improving its prognosis.

Adhesion of single cells is the foundation of manifold cellular behaviors and life processes. However, investigating the function of a specific cell is still challenging due to deficiency of adhesion or interference from surrounding cells. Herein, an open microfluidic system is reported for culturing adherent single cells, implemented by a micrometer-scale droplet matrix on an inkjet-printed polylysine template. The target cells are isolated from any cell from other droplets, and their adhesion strength is determined to be comparable to conventional petri dishes via an in-situ investigation with a microfluidic extractor. On this proposed platform, isolated single cells are observed to display an entirely distinct spreading behavior featuring total absence of elongation, indicating drastic cell behavior change from their \"singleness.\" This system has high versatility and compatibility for various assaying methods, assuring a promising potential in detailed single cell behavior and cell heterogeneity studies.

Digital polymers with precisely arranged binary units provide an important option for information storage. This is especially true if the digital polymers are assembled in a device, as it would be of great benefit for data writing and reading in practice. Herein, inspired by the DNA microarray technique, the programmable information storing and reading on a mass spectrometry target plate is proposed. First, an array of 4-bit sequence-coded dithiosuccinimide oligomers is efficiently built through sequential thiol-maleimide Michael couplings with good sequence readability by tandem mass spectrometry (MS/MS). Then, toward engineering microarrays for information storage, a programmed robotic arm is specifically designed for precisely loading sequence-coded oligomers onto the target plate, and a decoding software is developed for efficient readout of the data from MS/MS sequencing. Notably, short sequence-coded oligomer chains can be used to write long strings of information, and extra error-correction codes are not required as usual due to the inherent concomitant fragmentation signals. Not only text but also bitimages can be automatically stored and decoded with excellent accuracy. This work provides a promising platform of digital polymers for programmable information storing and reading.

OBJECTIVE: The purpose of this research was to confirm the prognostic value of bestrophin-2 (BEST2), one of the hub genes in colon cancer, via bioinformatics analysis and validation in public databases and immunohistochemistry detection.
METHODS: The GEO2R online tool and Venn diagram software were utilized to identify differentially expressed genes (DEGs) from expression profiles, including GSE20916, GSE44861 and GSE74602, from the Gene Expression Omnibus (GEO). The overall survival (OS) and disease-free survival (DFS) of colon cancer patients from The Cancer Genome Atlas (TCGA) were analyzed through Kaplan-Meier survival curves. Verification of the significance of BEST2 in colon cancer was based on TCGA, Genotype Tissue Expression (GTEx) and 10 datasets from GEO. BEST2 expression was detected with immunohistochemistry (IHC) in 330 colon tissue samples on microarrays including 165 colon cancerand 165 adjacent normal tissues. For further validation, comprehensive analysis from tissue microarrays and multiple datasets was performed by the summarizing of receiver operating characteristic (SROC) curves and the standard mean differences (SMDs). BEST2 expression in various kinds of colon cancer tissues and cell lines in the context of pancancer was obtained from the Expression Atlas database. The CBioPortal database was queried to identify BEST2 gene alterations and mutation status in colon cancer. Correlated genes (CEGs) with BEST2 and DEGs from public database data were assembled for functional and pathway enrichment analysis.
RESULTS: We identified 85 DEGs from the three datasets and screened out BEST2 as a prognostic predictor via the TCGA database. Colon cancer patients with high expression of BEST2 had better survival than patients with low BEST2 (HR = 0.5, P = 0.006) as shown in Kaplan-Meier survival curves in GEPIA. In all, 1463 colon cancer tissues and 1023 colon normal tissues were gathered via public databases as well as in-house tissue microarrays. The comprehensiveexpression analysis suggested low-expression of BEST2 in colon cancer (SMD = -2.48, 95% CI [-3.15- -1.80]) and the notable efficacy of BEST2 expression in differentiating colon cancer from noncancer samples (AUC = 0.97). Gene alteration status of BEST2 occurred in 5% of colon cancer cases, mostly missense mutations and deep deletions. Genes positively correlated with BEST2 and DEGs primarily aggregated in pathways such as anion absorption, digestive juice secretion, cAMP signaling and so on (P < 0.05).
CONCLUSIONS: Ampleevidencesupportsthe role of BEST2 in distinguishing colon cancer from normal tissues in this research. Low expression of BEST2 is correlated with a shorter OS, which implies that BEST2 can be employed as a potential biomarker and therapeutictarget in colon cancer.

Over the last two decades, a large number of non-communicable/chronic disorders reached an epidemic level on a global scale such as diabetes mellitus type 2, cardio-vascular disease, several types of malignancies, neurological and eye pathologies-all exerted system\'s enormous socio-economic burden to primary, secondary, and tertiary healthcare. The paradigm change from reactive to predictive, preventive, and personalized medicine (3PM/PPPM) has been declared as an essential transformation of the overall healthcare approach to benefit the patient and society at large. To this end, specific biomarker panels are instrumental for a cost-effective predictive approach of individualized prevention and treatments tailored to the person. The source of biomarkers is crucial for specificity and reliability of diagnostic tests and treatment targets. Furthermore, any diagnostic approach preferentially should be noninvasive to increase availability of the biomaterial, and to decrease risks of potential complications as well as concomitant costs. These requirements are clearly fulfilled by tear fluid, which represents a precious source of biomarker panels. The well-justified principle of a \"sick eye in a sick body\" makes comprehensive tear fluid biomarker profiling highly relevant not only for diagnostics of eye pathologies but also for prediction, prognosis, and treatment monitoring of systemic diseases. One prominent example is the Sicca syndrome linked to a cascade of severe complications that include dry eye, neurologic, and oncologic diseases. In this review, protein profiles in tear fluid are highlighted and corresponding biomarkers are exemplified for several relevant pathologies, including dry eye disease, diabetic retinopathy, cancers, and neurological disorders. Corresponding analytical approaches such as sample pre-processing, differential proteomics, electrophoretic techniques, high-performance liquid chromatography (HPLC), enzyme-linked immuno-sorbent assay (ELISA), microarrays, and mass spectrometry (MS) methodology are detailed. Consequently, we proposed the overall strategies based on the tear fluid biomarkers application for 3P medicine practice. In the context of 3P medicine, tear fluid analytical pathways are considered to predict disease development, to target preventive measures, and to create treatment algorithms tailored to individual patient profiles.

Hypertrophic cardiomyopathy (HCM) is an autosomal dominant disease and mitochondria plays a key role in the progression in HCM. Here, we analyzed the expression pattern of nuclear-encoded mitochondrial genes (NMGenes) in HCM and found that the expression of NMGenes was significantly changed. A total of 316 differentially expressed NMGenes (DE-NMGenes) were identified. Pathway enrichment analyses showed that energy metabolism-related pathways such as \"pyruvate metabolism\" and \"fatty acid degradation\" were dysregulated, which highlighted the importance of energy metabolism in HCM. Next, we constructed a protein-protein interaction network based on 316 DE-NMGenes and identified thirteen hubs. Then, a total of 17 TFs (transcription factors) were predicted to potentially regulate the expression of 316 DE-NMGenes according to iRegulon, among which 8 TFs were already found involved in pathological hypertrophy. The remaining TFs (like GATA1, GATA5, and NFYA) were good candidates for further experimental verification. Finally, a mouse model of transverse aortic constriction (TAC) was established to validate the genes and results showed that DDIT4, TKT, CLIC1, DDOST, and SNCA were all upregulated in TAC mice. The present study represents the first effort to evaluate the global expression pattern of NMGenes in HCM and provides innovative insight into the molecular mechanism of HCM.

Fluorene-9-bisphenol (BHPF), a substitute for bisphenol A (BPA), has been widely used in the synthesis of polyester polymers. Studies have reported multiple BHPF toxicities but its effect on the liver remains unknown. In this study, we performed short-term and subchronic toxicity tests, as well as primary hepatocyte experiments, to investigate the hepatic toxicity of BHPF using CD-1 mice. And microarray was used to analyze the changes of global gene expression in the liver of mice treated with BHPF. The results showed that the liver coefficient and the activities of serum aminotransferases were obviously elevated by BHPF at doses of 27.8 mg/kg body weight (bw)/day or higher in mice treated for 10 days. Histological analysis showed obvious changes, including narrowed hepatic sinuses, dilated central vein, leucocyte infiltration, and cytoplasmic vacuolation, in the livers of mice treated with BHPF at dosages of 2 mg/kg bw/3-day and higher for 36 days. Microarray analyses revealed 2623 differentially expressed genes (DEGs) in the livers of mice treated with 50 mg/kg bw/day of BHPF for 3 days, which could be enriched in GO terms of T cell activation, leukocyte migration, and leukocyte chemotaxis and KEGG pathways of natural killer cell-mediated cytotoxicity and autoimmune thyroid disease. The top 10 hub DEGs, including LTF and MMP8, were observed in the protein-protein interaction network obtained via STRING database analysis, and are proposed as potential biomarkers for liver injury studies. Primary hepatocyte experiments demonstrated the hepatotoxicity of BHPF at concentrations of 10-6 M and higher. This study indicates that BHPF could cause liver injury at relatively low levels, suggesting that the risk of human BHPF exposure should be of concern.

Non-alcoholic steatohepatitis (NASH) is a key stage in leading development of non-alcoholic simple fatty liver (NAFL) into cirrhosis and even liver cancer. This study aimed at exploring the lncRNAs expression profile in NASH and the biological function of a novel LncRNA-gm9795.
Microarray analysis was performed to compare the expression profiles of lncRNAs in the liver of NASH, NAFLD and normal mice (5 mice for each group). Methionine-choline-deficient Medium (MCD) with Lipopolysaccharide (LPS) or palmitic acid (PA)were used to built NASH cell models. The role and mechanism of LncRNA-gm9795 in NASH were explored by knocking down or over-expressing its expression.
A total of 381 lncRNAs were found to be not only highly expressed in NAFLD, but also is going to go even higher in NASH. A novel LncRNA-gm9795 was significantly highly expressed in liver tissues of NASH animal models and NASH cell models. By staining with Nile red, we found that gm9795 did not affect the fat accumulation of NASH. However, gm9795 in NASH cell models significantly promoted the expression of TNF [Formula: see text], IL-6, IL-1[Formula: see text], the important inflammatory mediators in NASH. At the same time, we found that gm9795 upregulated the key molecules in endoplasmic reticulum stress (ERS), while NF-[Formula: see text]B/JNK pathways were also activated. When ERS activator Thapsigargin (TG) was introduced in cells with Ggm9757 si-RNA, NF-[Formula: see text]B and JNK pathways were activated. Conversely, ERS inhibitor Tauroursodeoxycholic acid (TUDCA) inhibited NF-kB and JNK pathways in cells with gm9795 overexpression plasmid.
LncRNA-gm9795 promotes inflammatory response in NASH through NF-kB and JNK pathways by ERS, which might provide theoretical basis for revealing the pathogenesis of NASH and discovering new therapeutic targets.