UNASSIGNED: Diabetic retinopathy (DR) is a serious retinal vascular disease that affects many individuals in their prime working years. The present research aimed at whether and how LOC681216 (LNC-216) is involved in retinal vascular dysfunction under diabetic conditions.
UNASSIGNED: Rat retinal microvascular endothelial cells (RRMECs) treated with high glucose (HG) were used for functional analysis. Gene expression analysis was conducted using the Clariom D Affymetrix platform. The wound healing, transwell, and vascular tube formation assays were used to identify the migration, invasion, and tube formation capability of RRMECs. The dual-luciferase reporter confirmed the binding interaction between miR-143-5p and LNC-216 or matrix metallopeptidase 2 (MMP2).
UNASSIGNED: Lnc-216 was upregulated in RRMECs treated with HG. Lnc-216 knockdown markedly suppressed the tube formation, cell migration, and wound healing of cultured RRMECs under HG conditions. Mechanistically, Lnc-216 acted as a miR-143-5p sponge to affect the biological activity of miR-143-5p, which led to increased expression of matrix metallopeptidase 2 (MMP2).
UNASSIGNED: Lnc-216 attenuates diabetic retinal vascular dysfunction through the miR-143-5p/MMP2 axis, providing a potential therapeutic strategy for DR.

BACKGROUND: Renin-angiotensin system inhibitors (RASi) treatment is the basic therapy for IgA nephropathy (IgAN) patients. However, there is few of biomarker that can predict the efficacy of RASi. This study aimed to find urinary exosomal mRNAs related to the therapeutic effect of RASi in the treatment of proteinuria in IgAN patients.
METHODS: We divided IgAN patients in screening cohort into A1 (proteinuria increase at 3 months), B1 (proteinuria decrease less than 50 % at 3 months), C1 (proteinuria decrease more than 50 % at 3 months) groups according to changes of proteinuria after treatment. The urinary exosomes were collected before biopsy, RNAs were extracted and analyzed with the microarray assay. The candidate genes were screened by differentially expressed genes (DEGs) analysis and then validated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort. A receiver operating characteristic (ROC) curve was used to evaluate gene performance in predicting therapeutic effect on RASi reducing proteinuria in IgAN patients.
RESULTS: ECE1 and PDE1A mRNAs were significantly different among the three groups, and were gradually decreased among A1, B1 and C1 groups. In the validation cohort, the level of urinary exosomal ECE1 and PDE1A mRNAs were also significantly lower in A2 group compared with C2 group(ECE1, P < 0.001;PDE1A, P < 0.01). Besides, the level of ECE1 mRNA was also lower in B2 group compared with C2 group (P < 0.01). The ROC curve verified that urinary exosomal ECE1 and PDE1A gene level predicted RASi efficacy in IgAN patients with area under curve (AUC) 0.68 and 0.63 respectively.
CONCLUSIONS: Urinary exosomal ECE1 and PDE1A mRNAs expression can serve as potential biomarkers for predicting the RASi efficacy to reduce proteinuria in IgAN patients.

UNASSIGNED: This study contributes to the evolving understanding of the pivotal involvement of Sirtuins (SIRTs) in various human cancers, with a particular focus on elucidating their expression patterns and clinical relevance within the context of hepatocellular carcinoma (HCC). The investigation involves a comprehensive analysis of mRNA expression and prognostic implications associated with distinct SIRTs in HCC.
UNASSIGNED: Initial data pertaining to SIRT expression in HCC patients were collated from publicly accessible databases. Subsequently, the expression levels of select members of the SIRT family were validated using clinicopathological specimens from HCC patients. Additionally, HCC tissue microarray was employed to scrutinize the correlation between SIRT7 expression and HCC prognosis.
UNASSIGNED: The findings indicated a substantial upregulation of SIRT2, SIRT3, SIRT4, SIRT6, and SIRT7 in HCC tissues. Survival analysis underscored a pronounced association between elevated mRNA levels of SIRT3, SIRT6, and SIRT7 and an adverse prognosis for HCC patients. Particularly, SIRT7 emerged as a potential independent risk factor for poor prognosis in HCC patients. Examination of the HCC tissue microarray revealed heightened expression of SIRT7 in 68 cases (54.8%) of HCC tissues. Multivariate analysis established high SIRT7 expression as an independent risk factor for diminished Disease-Free Survival (DFS) and Overall Survival (OS) in HCC patients.
UNASSIGNED: The aberrant expression of SIRT7 presents itself may be as a novel biomarker for predicting the prognosis of HCC patients.

Systemic amyloid A (AA) amyloidosis, which is considered the second most common form of systemic amyloidosis usually takes place several years prior to the occurrence of chronic inflammation, generally involving the kidney. Activated HSF1, which alleviated unfolded protein response (UPR) or enhanced HSR, is the potential therapeutic target of many diseases. However, the effect of HSF1 on AA amyloidosis remains unclear. This study focused on evaluating effect of HSF1 on AA amyloidosis based on HSF1 knockout mice. As a result, aggravated amyloid deposits and renal dysfunction have been found in HSF1 knockout mice. In progressive AA amyloidosis, HSF1 deficiency enhances serum amyloid A production might to lead to severe AA amyloid deposition in mice, which may be related to deactivated unfolded protein response as well as enhanced inflammation. Thus, HSF1 plays a significant role on UPR related pathway impacting AA amyloid deposition, which can mitigate amyloidogenic proteins from aggregation pathologically and is the possible way for intervening with the pathology of systemic amyloid disorder. In conclusion, HSF1 could not only serve as a new target for AA amyloidosis treatment in the future, but HSF1 knockout mice also can be considered as a valuable novel animal model for renal AA amyloidosis.

OBJECTIVE: Endoplasmic reticulum stress (ERS) has been reported to be closely associated with the development of osteoarthritis (OA), but the underlying mechanisms are not fully delineated. The present study was designed to investigate the involvement of ERS-related genes in regulating OA progression.
METHODS: The expression profiles of OA patients and normal people were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) in datasets GSE55457 and GSE55235 were screened and identified by R software with the construction of the protein-protein interaction (PPI) networks. Through the STRING and Venn diagram analysis, hub ERS-related genes were obtained. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed. Biomarkers with high diagnostic values of osteoarthritis (OA) were studied. The hematoxylin and eosin (H&E) staining and micro-CT were applied to evaluate the establishment of the OA model. The expression levels of biomarkers were validated with the use of reverse transcription‑quantitative polymerase chain reaction (RT-qPCR) and western blot. Finally, we evaluated the correlations of hub ERS-related genes with the immune infiltration cells via the CIBERSORT algorithm.
RESULTS: A total of 60 downregulated and 52 upregulated DEGs were identified, and the following GO and KEGG pathway analyses verified that those DEGs were mainly enriched in biological process (BP), cellular component (CC), molecular function (MF), and inflammation-associated signal pathways. Interestingly, among all the DEGs, six ER stress-associated genes, including activating transcription factor 3 (ATF3), DEAD-Box Helicase 3 X-Linked (DDX3X), AP-1 transcription factor subunit (JUN), eukaryotic initiation factor 4 (EIF4A1), KDEL endoplasmic reticulum protein retention receptor 3 (KDELR3), and vascular endothelial growth factor A (VEGFA), were found to be closely associated with OA progression, and the following RT-qPCR and Western Blot analysis confirmed that DDX3X, JUN, and VEGFA were upregulated, whereas KDELR3, EIF4A1, and ATF3 were downregulated in OA rats tissues compared to the normal tissues, which were in accordance with our bioinformatics findings. Furthermore, our receiver operating characteristic (ROC) curve analysis verified that the above six ER stress-associated genes could be used as ideal biomarkers for OA diagnosis and those genes also potentially regulated immune responses by influencing the biological functions of mast cells and macrophages.
CONCLUSIONS: Collectively, the present study firstly identified six ER stress-associated genes (ATF3, DDX3X, JUN, EIF4A1, KDELR3, and VEGFA) that may play critical role in regulating the progression of OA.

[This corrects the article DOI: 10.3389/fonc.2023.1206768.].

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of different variants of concerns with immune evasion that have been prevalent over the past three years. Nanobodies, the functional variable regions of camelid heavy-chain-only antibodies, have garnered interest in developing neutralizing antibodies due to their smaller size, structural stability, ease of production, high affinity, and low immunogenicity, among other characteristics. In this work, we describe an integrated proteomics platform for the high-throughput screening of nanobodies against different SARS-CoV-2 spike variants. To demonstrate this platform, we immunized a camel with subunit 1 (S1) of the wild-type spike protein and constructed a nanobody phage library. The binding and neutralizing activities of the nanobodies against 72 spike variants were then measured, resulting in the identification of two nanobodies (C-282 and C-39) with broad neutralizing activity against six non-Omicron variants (D614G, Alpha, Beta, Gamma, Delta, Kappa) and five Omicron variants (BA.1-5). Their neutralizing capability was validated using in vitro pseudovirus-based neutralization assays. All these results demonstrate the utility of our proteomics platform to identify new nanobodies with broad neutralizing capability and to develop a treatment for patients with SARS-CoV-2 variant infection in the future.

OBJECTIVE: To explore the core genes related to the diagnosis and prognosis of gastric cancer (GC) based on Gene Expression Omnibus (GEO) database and screen the molecular targets involved in the occurrence and development of GC.
METHODS: GC microarray data GSE118916, GSE54129 and GSE79973 were downloaded from GEO database, and the differentially expressed genes (DEGs) were screened. Enrichment analysis of the signaling pathways and molecular functions were preformed and protein-protein interaction networks (PPI) were constructed to identify the hub genes, whose expression levels and diagnostic and prognostic values were verifies based on gastric adenocarcinoma data from TCGA. The expression levels of these core genes were also detected in different GC cell lines using qRT- PCR.
RESULTS: Seventy-seven DEGs were identified, which encodes proteins located mainly in the extracellular matrix and basement membrane with activities of oxidoreductase and extracellular matrix receptor and ligand, involving the biological processes of digestion and hormone metabolism and the signaling pathways in retinol metabolism and gastric acid secretion. Nine hub genes were obtained, among which SPARC, TIMP1, THBS2, COL6A3 and THY1 were significantly up- regulated and TFF1, GKN1, TFF2 and PGC were significantly down-regulated in GC. The abnormal expressions of SPARC, TIMP1, THBS2, COL6A3, TFF2 and THY1 were significantly correlated with the survival time of GC patients. ROC curve analysis showed that aberrant expression of TIMP1 SPARC, THY1 and THBS2 had high diagnostic value for GC. High expressions of SPARC, TIMP1, THBS2 and COL6A3 were detected in GC tissues. In the GC cell lines, qRT- PCR revealed different expression patterns of these hub genes, but their expressions were largely consistent with those found in bioinformatics analyses.
CONCLUSIONS: SPARC, TIMP1, THBS2 and other DEGs are probably involved in GC occurrence and progression and may serve as potential candidate molecular markers for early diagnosis and prognostic evaluation of GC.

Surface-enhanced Raman scattering (SERS) technology, as an important analytical tool, has been widely applied in the field of chemical and biomedical sensing. Automated testing is often combined with biochemical analysis technologies to shorten the detection time and minimize human error. The present SERS substrates for sample detection are time-consuming and subject to high human error, which are not conducive to the combination of SERS and automated testing. Here, a novel honeycomb-inspired SERS microarray is designed for large-area automated testing of urease in saliva samples to shorten the detection time and minimize human error. The honeycomb-inspired SERS microarray is decorated with hexagonal microwells and a homogeneous distribution of silver nanostars. Compared with the other four common SERS substrates, the optimal honeycomb-inspired SERS microarray exhibits the best SERS performance. The RSD of 100 SERS spectra continuously collected from saliva samples is 6.56%, and the time of one detection is reduced from 5 min to 10 s. There is a noteworthy linear relationship with a R2 of 0.982 between SERS intensity and urease concentration, indicating the quantitative detection capability of the urease activity in saliva samples. The honeycomb-inspired SERS microarray, combined with automated testing, provides a new way in which SERS technology can be widely used in biomedical applications.

Sleep disorders have emerged as a widespread public health concern, primarily due to their association with an increased risk of developing cardiovascular diseases. Our previous research indicated a potential direct impact of insufficient sleep duration on cardiac remodeling in children and adolescents. Nevertheless, the underlying mechanisms behind the link between sleep fragmentation (SF) and cardiac abnormalities remain unclear. In this study, we aimed to investigate the effects of SF interventions at various life stages on cardiac structure and function, as well as to identify genes associated with SF-induced cardiac dysfunction. To achieve this, we established mouse models of chronic SF and two-week sleep recovery (SR). Our results revealed that chronic SF significantly compromised left ventricular contractile function across different life stages, leading to alterations in cardiac structure and ventricular remodeling, particularly during early life stages. Moreover, microarray analysis of mouse heart tissue identified two significant modules and nine hub genes (Ddx60, Irf9, Oasl2, Rnf213, Cmpk2, Stat2, Parp14, Gbp3, and Herc6) through protein-protein interaction analysis. Notably, the interactome predominantly involved innate immune responses. Importantly, all hub genes lost significance following SR. The second module primarily consisted of circadian clock genes, and real-time PCR validation demonstrated significant upregulation of Arntl, Dbp, and Cry1 after SF, while subsequent SR restored normal Arntl expression. Furthermore, the expression levels of four hub genes (Ddx60, Irf9, Oasl2, and Cmpk2) and three circadian clock genes (Arntl, Dbp, and Cry1) exhibited correlations with structural and functional echocardiographic parameters. Overall, our findings suggest that SF impairs left ventricular contractile function and ventricular remodeling during early life stages, and this may be mediated by modulation of the innate immune response and circadian rhythm. Importantly, our findings suggest that a short period of SR can alleviate the detrimental effects of SF on the cardiac immune response, while the influence of SF on circadian rhythm appears to be more persistent. These findings underscore the importance of good sleep for maintaining cardiac health, particularly during early life stages.