Prospective comparative clinical study: Efficacy evaluation of collagen combined with hyaluronic acid injections for tear trough deformity.

BACKGROUND: Tear trough filling is a popular facial rejuvenation procedure, and hyaluronic acid is typically used as the filler of choice. However, Tyndall's phenomenon, a common complication following hyaluronic acid injection, can occur, leading to skin discoloration of the lower eyelid. AIMS: This single-center, prospective, comparative clinical study aimed to evaluate the efficacy of collagen and hyaluronic acid injections in treating tear trough deformity. METHODS: Sixty patients were enrolled between June 2022 and January 2023. Patients were randomly allocated into three groups: Group A received hyaluronic acid, Group B received hyaluronic acid combined with collagen, and Group C received collagen alone. Baseline characteristics, including age, sex, and tear trough deformity grade were considered before therapy. Changes in tear trough deformity scores, Global Aesthetic Improvement Scores, and the presence of the Tyndall effect were analyzed at 1 and 3 months postinjection to determine differences among the three groups. RESULTS: Baseline profiles of the three groups were similar. In the first month postinjection, there was no difference in the Global Aesthetic Improvement Scores and tear trough deformity between the three groups. However, in the third-month postinjection, there was a significant difference in scores between patients in Group C and those in Groups A or B. The Tyndall effect manifested in three patients in Group A, which was significantly different from that in Groups B and C. CONCLUSION: The combined use of hyaluronic acid with collagen in injectable fillers corrected tear trough deformities and reduced the occurrence of the Tyndall phenomenon, which can be problematic with hyaluronic acid alone. Additionally, this combination may help overcome the disadvantage of a shorter retention period when using collagen alone.

Development of a Novel Energy Saving and Environmentally Friendly Starch via a Graft Copolymerization Strategy for Efficient Warp Sizing and Easy Removal.

Warp sizing is a key process in textile production. However, before the yarn/fabric finishing, such as dyeing, the paste adhering to the warp must be eliminated to ensure optimal dyeing properties and the flexibility of the fabric. Therefore, the sizing will often consume a lot of energy and produce a lot of industrial wastewater, which will cause serious harm to the environment. In this study, we have developed an energy saving and environmentally friendly starch-based slurry by modifying natural starch with acrylamide. The paste has excellent viscosity stability and fiber adhesion, and exhibits excellent performance during warp sizing. In addition, the slurry has good water solubility at 60-70 °C, so it is easy to desize at low temperatures. Because of this, the sizing of the warp can be deslimed directly from the yarn during subsequent washing processes. This work can not only reduce some costs for the textile industry, but also achieve the purpose of energy conservation and emission reduction.

The effects of anastomoses between anterior and posterior circulation on postoperative prognosis of patients with moyamoya disease.

BACKGROUND: Moyamoya disease (MMD) is a chronic ischemic cerebrovascular disease. Collateral circulation in MMD has emerged as a research focus. Our aims were to assess the impact of anastomoses between the anterior and posterior circulations on the prognosis of MMD patients. METHODS: We reviewed the preoperative digital subtraction angiography images of patients with MMD who underwent revascularization surgery at our hospital between March 2014 and May 2020 and divided the patients into two groups: those with anastomoses (PtoA group) and those without anastomoses (non-PtoA group). The differences in follow-up (more than 6 months) collateral vessel establishment (Matsushima grade) and the modified Rankin Scale (mRS) were compared between the two groups as well as between the patients with different degrees of anastomoses. The early complications following revascularization were also compared between the two groups. RESULTS: This study included 104 patients with MMD, of which 38 were non-PtoA and 66 were PtoA. There were no significant differences in Matsushima score (P = 0.252) and mRS score (P = 0.066) between the two groups. In addition, Matsushima score (P = 0.243) and mRS score (P = 0.360) did not differ significantly between patients with different degrees of anastomoses. However, the non-PtoA group had a significantly higher rate of cerebral hyperperfusion syndrome (CHS) than the PtoA group (34.2% vs 16.7%, P = 0.041). CONCLUSION: MMD patients without anastomoses between anterior and posterior circulations preoperatively should be vigilant of the occurrence of CHS in the early stages after revascularization.

Stimuli-Responsive Protein Hydrogels: Their Design, Properties, and Biomedical Applications.

Protein-based hydrogels are considered ideal biomaterials due to their high biocompatibility, diverse structure, and their improved bioactivity and biodegradability. However, it remains challenging to mimic the native extracellular matrices that can dynamically respond to environmental stimuli. The combination of stimuli-responsive functionalities with engineered protein hydrogels has facilitated the development of new smart hydrogels with tunable biomechanics and biological properties that are triggered by cyto-compatible stimuli. This review summarizes the recent advancements of responsive hydrogels prepared from engineered proteins and integrated with physical, chemical or biological responsive moieties. We underscore the design principles and fabrication approaches of responsive protein hydrogels, and their biomedical applications in disease treatment, drug delivery, and tissue engineering are briefly discussed. Finally, the current challenges and future perspectives in this field are highlighted.

Integrative lactylation and tumor microenvironment signature as prognostic and therapeutic biomarkers in skin cutaneous melanoma.

BACKGROUND: The incidence of skin cutaneous melanoma (SKCM), one of the most aggressive and lethal skin tumors, is increasing worldwide. However, for advanced SKCM, we still lack an accurate and valid way to predict its prognosis, as well as novel theories to guide the planning of treatment options for SKCM patients. Lactylation (LAC), a novel post-translational modification of histones, has been shown to promote tumor growth and inhibit the antitumor response of the tumor microenvironment (TME) in a variety of ways. We hope that this study will provide new ideas for treatment options for SKCM patients, as well as research on the molecular mechanisms of SKCM pathogenesis and development. METHODS: At the level of the RNA sequencing set (TCGA, GTEx), we used differential expression analysis, LASSO regression analysis, and multifactor Cox regression analysis to screen for prognosis-related genes and calculate the corresponding LAC scores. The content of TME cells in the tumor tissue was calculated using the CIBERSORT algorithm, and the TME score was calculated based on its results. Finally, the LAC-TME classifier was established and further analyzed based on the two scores, including the construction of a prognostic model, analysis of clinicopathological characteristics, and correlation analysis of tumor mutation burden (TMB) and immunotherapy. Based on single-cell RNA sequencing data, this study analyzed the cellular composition in SKCM tissues and explored the role of LAC scores in intercellular communication. To validate the functionality of the pivotal gene CLPB in the model, cellular experiments were ultimately executed. RESULTS: We screened a total of six prognosis-related genes (NDUFA10, NDUFA13, CLPB, RRM2B, HPDL, NARS2) and 7 TME cells with good prognosis. According to Kaplan-Meier survival analysis, we found that the LAClow/TMEhigh group had the highest overall survival (OS) and the LAChigh/TMElow group had the lowest OS (p value < 0.05). In further analysis of immune infiltration, tumor microenvironment (TME), functional enrichment, tumor mutational load and immunotherapy, we found that immunotherapy was more appropriate in the LAClow/TMEhigh group. Moreover, the cellular assays exhibited substantial reductions in proliferation, migration, and invasive potentials of melanoma cells in both A375 and A2058 cell lines upon CLPB knockdown. CONCLUSIONS: The prognostic model using the combined LAC score and TME score was able to predict the prognosis of SKCM patients more consistently, and the LAC-TME classifier was able to significantly differentiate the prognosis of SKCM patients across multiple clinicopathological features. The LAC-TME classifier has an important role in the development of immunotherapy regimens for SKCM patients.

Machine learning and single-cell transcriptome profiling reveal regulation of fibroblast activation through THBS2/TGFß1/P-Smad2/3 signalling pathway in hypertrophic scar.

Hypertrophic scar (HS) is a chronic inflammatory skin disorder characterized by excessive deposition of extracellular matrix, and the mechanisms underlying their formation remain poorly understood. We analysed scRNA-seq data from samples of normal skin and HS. Using the hdWGCNA method, key gene modules of fibroblasts in HS were identified. Non-negative matrix factorization was employed to perform subtype analysis of HS patients using these gene modules. Multiple machine learning algorithms were applied to screen and validate accurate gene signatures for identifying and predicting HS, and a convolutional neural network (CNN) based on deep learning was established and validated. Quantitative reverse transcription-polymerase chain reaction and western blotting were performed to measure mRNA and protein expression. Immunofluorescence was used for gene localization analysis, and biological features were assessed through CCK8 and wound healing assay. Single-cell sequencing revealed distinct subpopulations of fibroblasts in HS. HdWGCNA identified key gene characteristics of this population, and pseudotime analysis was conducted to investigate gene variation during fibroblast differentiation. By employing various machine learning algorithms, the gene range was narrowed down to three key genes. A CNN was trained using the expression of these key genes and immune cell infiltration, enabling diagnosis and prediction of HS. Functional experiments demonstrated that THBS2 is associated with fibroblast proliferation and migration in HS and affects the formation and development of HS through the TGFß1/P-Smad2/3 pathway. Our study identifies unique fibroblast subpopulations closely associated with HS and provides biomarkers for the diagnosis and treatment of HS.

Combined signature of G protein-coupled receptors and tumor microenvironment provides a prognostic and therapeutic biomarker for skin cutaneous melanoma.

BACKGROUND: G protein-coupled receptors (GPCRs) have been shown to have an important role in tumor development and metastasis, and abnormal expression of GPCRs is significantly associated with poor prognosis of tumor patients. In this study, we analyzed the GPCRs-related gene (GPRGs) and tumor microenvironment (TME) in skin cutaneous melanoma (SKCM) to construct a prognostic model to help SKCM patients obtain accurate clinical treatment strategies. METHODS: SKCM expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differential expression analysis, LASSO algorithm, and univariate and multivariate cox regression analysis were used to screen prognosis-related genes (GPR19, GPR146, S1PR2, PTH1R, ADGRE5, CXCR3, GPR143, and OR2I1P) and multiple prognosis-good immune cells; the data set was analyzed according to above results and build up a GPR-TME classifier. The model was further subjected to immune infiltration, functional enrichment, tumor mutational load, immunotherapy prediction, and scRNA-seq data analysis. Finally, cellular experiments were conducted to validate the functionality of the key gene GPR19 in the model. RESULTS: The findings indicate that high expression of GPRGs is associated with a poor prognosis in patients with SKCM, highlighting the significant role of GPRGs and the tumor microenvironment (TME) in SKCM development. Notably, the group characterized by low GPR expression and a high TME exhibited the most favorable prognosis and immunotherapeutic efficacy. Furthermore, cellular assays demonstrated that knockdown of GPR19 significantly reduced the proliferation, migration, and invasive capabilities of melanoma cells in A375 and A2058 cell lines. CONCLUSION: This study provides novel insights for the prognosis evaluation and treatment of melanoma, along with the identification of a new biomarker, GPR19.

Role of single-cell ferroptosis regulation in intercellular communication and skin cutaneous melanoma progression and immunotherapy.

BACKGROUND: The involvement of ferroptosis in the pathogenesis and progression of various cancers has been well established. However, limited studies have investigated the role of ferroptosis-mediated tumor microenvironment (TME) in skin cutaneous melanoma (SKCM). METHODS: By leveraging single-cell RNA sequencing data, the nonnegative matrix factorization (NMF) approach was employed to comprehensively characterize and identify distinct gene signatures within ferroptosis-associated TME cell clusters. Prognostic and treatment response analyses were conducted using both bulk datasets and external cancer cohort to evaluate the clinical implications of TME clusters. RESULTS: This NMF-based analysis successfully delineated fibroblasts, macrophages, T cells, and B cells into multiple clusters, enabling the identification of unique gene expression patterns and the annotation of distinct TME clusters. Furthermore, pseudotime trajectories, enrichment analysis, cellular communication analysis, and gene regulatory network analysis collectively demonstrated significant intercellular communication between key TME cell clusters, thereby influencing tumor cell development through diverse mechanisms. Importantly, our bulk RNA-seq analysis revealed the prognostic significance of ferroptosis-mediated TME cell clusters in SKCM patients. Moreover, our analysis of immune checkpoint blockade highlighted the crucial role of TME cell clusters in tumor immunotherapy, facilitating the discovery of potential immunotherapeutic targets. CONCLUSIONS: In conclusion, this pioneering study employing NMF-based analysis unravels the intricate cellular communication mediated by ferroptosis within the TME and its profound implications for the pathogenesis and progression of SKCM. We provide compelling evidence for the prognostic value of ferroptosis-regulated TME cell clusters in SKCM, as well as their potential as targets for immunotherapy.

Formononetin Inhibits Mast Cell Degranulation to Ameliorate Compound 48/80-Induced Pseudoallergic Reactions.

Formononetin (FNT) is a plant-derived isoflavone natural product with anti-inflammatory, antioxidant, and anti-allergic properties. We showed previously that FNT inhibits immunoglobulin E (IgE)-dependent mast cell (MC) activation, but the effect of FNT on IgE-independent MC activation is yet unknown. Our aim was to investigate the effects and possible mechanisms of action of FNT on IgE-independent MC activation and pseudoallergic inflammation. We studied the effects of FNT on MC degranulation in vitro with a cell culture model using compound C48/80 to stimulate either mouse bone marrow-derived mast cells (BMMCs) or RBL-2H3 cells. We subsequently measured ß-hexosaminase and histamine release, the expression of inflammatory factors, cell morphological changes, and changes in NF-κB signaling. We also studied the effects of FNT in several in vivo murine models of allergic reaction: C48/80-mediated passive cutaneous anaphylaxis (PCA), active systemic anaphylaxis (ASA), and 2,4-dinitrobenzene (DNCB)-induced atopic dermatitis (AD). The results showed that FNT inhibited IgE-independent degranulation of MCs, evaluated by a decrease in the release of ß-hexosaminase and histamine and a decreased expression of inflammatory factors. Additionally, FNT reduced cytomorphological elongation and F-actin reorganization and attenuated NF-κB p65 phosphorylation and NF-κB-dependent promoter activity. Moreover, the administration of FNT alleviated pseudoallergic responses in vivo in mouse models of C48/80-stimulated PCA and ASA, and DNCB-induced AD. In conclusion, we suggest that FNT may be a novel anti-allergic drug with great potential to alleviate pseudoallergic responses via the inhibition of IgE-independent MC degranulation and NF-κB signaling.

Deciphering the contributions of cuproptosis in the development of hypertrophic scar using single-cell analysis and machine learning techniques.

Hypertrophic scar (HS) is a chronic inflammatory skin disease characterized by excessive deposition of extracellular matrix, but the exact mechanisms related to its formation remain unclear, making it difficult to treat. This study aimed to investigate the potential role of cuproptosis in the information of HS. To this end, we used single-cell sequencing and bulk transcriptome data, and screened for cuproptosis-related genes (CRGs) using differential gene analysis and machine learning algorithms (random forest and support vector machine). Through this process, we identified a group of genes, including ATP7A, ULK1, and MTF1, as novel therapeutic targets for HS. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to confirm the mRNA expression of ATP7A, ULK1, and MTF1 in both HS and normal skin (NS) tissues. We also constructed a diagnostic model for HS and analyzed the immune infiltration characteristics. Additionally, we used the expression profiles of CRGs to perform subgroup analysis of HS. We focused mainly on fibroblasts in the transcriptional profile at single-cell resolution. By calculating the cuproptosis activity of each fibroblast, we found that cuproptosis activity of normal skin fibroblasts increased, providing further insights into the pathogenesis of HS. We also analyzed the cell communication network and transcription factor regulatory network activity, and found the existence of a fibroblast-centered communication regulation network in HS, where cuproptosis activity in fibroblasts affects intercellular communication. Using transcription factor regulatory activity network analysis, we obtained highly active transcription factors, and correlation analysis with CRGs suggested that CRGs may serve as potential target genes for transcription factors. Overall, our study provides new insights into the pathophysiological mechanisms of HS, which may inspire new ideas for the diagnosis and treatment.

Revealing the roles of glycosphingolipid metabolism pathway in the development of keloid: a conjoint analysis of single-cell and machine learning.

Keloid is a pathological scar formed by abnormal wound healing, characterized by the persistence of local inflammation and excessive collagen deposition, where the intensity of inflammation is positively correlated with the size of the scar formation. The pathophysiological mechanisms underlying keloid formation are unclear, and keloid remains a therapeutic challenge in clinical practice. This study is the first to investigate the role of glycosphingolipid (GSL) metabolism pathway in the development of keloid. Single cell sequencing and microarray data were applied to systematically analyze and screen the glycosphingolipid metabolism related genes using differential gene analysis and machine learning algorithms (random forest and support vector machine), and a set of genes, including ARSA,GBA2,SUMF2,GLTP,GALC and HEXB, were finally identified, for which keloid diagnostic model was constructed and immune infiltration profiles were analyzed, demonstrating that this set of genes could serve as a new therapeutic target for keloid. Further unsupervised clustering was performed by using expression profiles of glycosphingolipid metabolism genes to discover keloid subgroups, immune cells, inflammatory factor differences and the main pathways of enrichment between different subgroups were calculated. The single-cell resolution transcriptome landscape concentrated on fibroblasts. By calculating the activity of the GSL metabolism pathway for each fibroblast, we investigated the activity changes of GSL metabolism pathway in fibroblasts using pseudotime trajectory analysis and found that the increased activity of the GSL metabolism pathway was associated with fibroblast differentiation. Subsequent analysis of the cellular communication network revealed the existence of a fibroblast-centered communication regulatory network in keloids and that the activity of the GSL metabolism pathway in fibroblasts has an impact on cellular communication. This contributes to the further understanding of the pathogenesis of keloids. Overall, we provide new insights into the pathophysiological mechanisms of keloids, and our results may provide new ideas for the diagnosis and treatment of keloids.

Machine learning-based signature of necrosis-associated lncRNAs for prognostic and immunotherapy response prediction in cutaneous melanoma and tumor immune landscape characterization.

Background: Cutaneous melanoma (CM) is one of the malignant tumors with a relative high lethality. Necroptosis is a novel programmed cell death that participates in anti-tumor immunity and tumor prognosis. Necroptosis has been found to play an important role in tumors like CM. However, the necroptosis-associated lncRNAs' potential prognostic value in CM has not been identified. Methods: The RNA sequencing data collected from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Project (GTEx) was utilized to identify differentially expressed genes in CM. By using the univariate Cox regression analysis and machine learning LASSO algorithm, a prognostic risk model had been built depending on 5 necroptosis-associated lncRNAs and was verified by internal validation. The performance of this prognostic model was assessed by the receiver operating characteristic curves. A nomogram was constructed and verified by calibration. Furthermore, we also performed sub-group K-M analysis to explore the 5 lncRNAs' expression in different clinical stages. Function enrichment had been analyzed by GSEA and ssGSEA. In addition, qRT-PCR was performed to verify the five lncRNAs' expression level in CM cell line (A2058 and A375) and normal keratinocyte cell line (HaCaT). Results: We constructed a prognostic model based on five necroptosis-associated lncRNAs (AC245041.1, LINC00665, AC018553.1, LINC01871, and AC107464.3) and divided patients into high-risk group and low-risk group depending on risk scores. A predictive nomogram had been built to be a prognostic indicator to clinical factors. Functional enrichment analysis showed that immune functions had more relationship and immune checkpoints were more activated in low-risk group than that in high-risk group. Thus, the low-risk group would have a more sensitive response to immunotherapy. Conclusion: This risk score signature could be used to divide CM patients into low- and high-risk groups, and facilitate treatment strategy decision making that immunotherapy is more suitable for those in low-risk group, providing a new sight for CM prognostic evaluation.

Preoperative Brain Functional Connectivity Improve Predictive Accuracy of Outcomes After Revascularization in Moyamoya Disease.

BACKGROUND: In patients with moyamoya disease (MMD), focal impairments in cerebral hemodynamics are often inconsistent with patients' clinical prognoses. Evaluation of entire brain functional networks may enable predicting MMD outcomes after revascularization. OBJECTIVE: To investigate whether preoperative brain functional connectivity could predict outcomes after revascularization in MMD. METHODS: We included 34 patients with MMD who underwent preoperative MRI scanning and combined revascularization surgery. We used region of interest analyses to explore the differences in functional connectivity for 90 paired brain regions between patients who had favorable outcomes 1 year after surgery (no recurrent stroke, with improved preoperative symptoms, or modified Rankin Scale [mRS]) and those who had unimproved outcomes (recurrent stroke, persistent symptoms, or declined mRS). Variables, including age, body mass index, mRS at admission, Suzuki stage, posterior cerebral artery involvement, and functional connectivity with significant differences between the groups, were included in the discriminant function analysis to predict patient outcomes. RESULTS: Functional connectivity between posterior cingulate cortex and paracentral lobule within the right hemisphere, and interhemispheric connection between superior parietal gyrus and middle frontal gyrus, precuneus and middle cingulate cortex, cuneus and precuneus, differed significantly between the groups (P < .001, false discovery rate corrected) and had the greatest discriminant function in the prediction model. Although clinical characteristics of patients with MMD showed great accuracy in predicting outcomes (64.7%), adding information on functional connections improved accuracy to 91.2%. CONCLUSION: Preoperative functional connectivity derived from rs-fMRI may be an early hallmark for predicting patients' prognosis after revascularization surgery for MMD.

Seasonal occurrence, removal and mass loads of artificial sweeteners in the largest water reclamation plant in China.

Artificial sweeteners (ASs) are of growing concern as an emerging contaminant. In the study, the seasonal occurrence, removal and mass load of six ASs in sewage, suspended particulate matter (SPM) and sludge were investigated throughout the treatment process of the largest water reclamation plant in China. The highest ASs concentrations in the influent (13.0 µg/L), effluent (2.22 µg/L), SPM (4.48 µg/g) and sludge (0.15 µg/g) were observed in the dry season, which were 1.24- to 5.0-fold higher than in the normal season and 1.06- to 37.5-fold higher than the flood season. Following treatment, ASs concentrations decreased by 24.3 %, 51.7 % and 5.1 % (on average) in primary, secondary and reclaimed processes, respectively. Among the investigated ASs, acesulfame (93.1 %) and cyclamate (98.4 %) were removed most efficiently, with removal occurring mainly in secondary processes, while sucralose exhibited the lowest removal efficiency (38.7 %). Seasonal characteristics affect the consumption of ASs, which subsequently changes the input and discharge ASs loads of STPs. The maximum mass load of ASs occurred in the dry season, ranging from 0.002 (neotame) to 1.33 mg/d/person (cyclamate), while the maximum emission load occurred in the flood season, ranging from 0.003 (neotame) to 0.83 mg/d/person (sucralose). The mass and emission load of ASs in Beijing is significantly lower than in European or the United States, due to Beijing having low per capita consumption of ASs (5.50 mg/d/person). The highest ASs risk in the receiving water occurred in the flood season due to the input of other pollution sources by rainfall runoff. Meanwhile, attention should be paid to the risk of receiving water close to the STP outlet in the dry seasons for the highest ASs concentration in the STP effluent in the season. The present study provides important guidance on controlling the input and reducing the emission of ASs in different seasons.

A ratiometric self-powered aptasensor for simultaneous detection of cortisol and progesterone based on spatially resolved tri-channel photofuel cell.

In this work, a self-powered sensor was proposed for simultaneous detection of two typical steroid hormones, namely cortisol (COR) and progesterone (P4). A tri-channel photofuel cell (PFC) consisting of three spatially resolved SnS2@SnO2 photoanodes and one Pt cathode was designed to generate the electricity to drive the sensing process under the control of a multiplex switch. Among three photoanodes, one served as the control, while the other two were modified with COR-binding or P4-binding aptamer to respond specifically to the COR or P4 target. The ratios of the inhibited PFC output from aptamer-immobilized photoanodes to the reference signal from the control photoanode were utilized for simultaneous detection of COR and P4. The results showed that the developed self-powered sensor exhibited broad concentration ranges toward targets, with COR concentration ranging from 1 nM to 1000 nM and P4 concentration ranging from 1 nM to 500 nM. The detection limits for COR and P4 were calculated to be 0.88 nM and 0.52 nM, respectively. Moreover, the proposed sensing platform demonstrated high selectivity, good reproducibility, and high stability. Finally, the sensor was successfully applied to the simultaneous determination of COR and P4 in a human female serum sample.

Effect of finerenone on cardiovascular events in kidney disease and/or diabetes: a meta analysis of randomized control trials.

OBJECTIVE: To evaluate the effect of finerenone on cardiovascular events in Kidney Disease and/or Diabetes. METHODS: The ClinicalTrials.gov, Medline, EMBASE, Web of Science, Cochrane Library databases were systematically searched from the inception dates to December 20, 2021 in order to identify randomized controlled trials that evaluated the effect of finerenone on cardiovascular events in Kidney Disease and/or Diabetes, without language restriction. This meta-analysis collected data from 7 randomized clinical trials that evaluated the effect of finrrenone in 15,618 patients with kidney disease and/or diabetes. Risk of bias was assessed by Cochrane Risk of Bias Assessment Tool. Inconsistency among trial results was assessed by I2 statistic. The main endpoints included death from cardiovascular causes, death from any cause, incidence of myocardial infarction, rate of heart failure, hospitalization for any cause, rate of total advent events and study-drug-related adverse events. RESULTS: A total of 7 randomized controlled trials involving 15,618 fulfilled the inclusion criteria. The outcomes of this meta-analysis presented that finerenone significantly reduced the death from any cause (95% CI 0.82-0.99; P = 0.031), risk of heart failure (95% CI 0.67-0.92; P = 0.002) among patients with kidney disease and/or diabetes when compared to control group. Besides, finerenone could not reduce the incidence of death from cardiovascular, myocardial infarction and hospitalization for any cause among patients with kidney disease and/or diabetes (p > 0.05). In terms of safety, finerenone shared the same risk of total advent events with placebo among patients with kidney disease and/or diabetes (p > 0.05). However, finerenone had higher risk of study-drug-related advent events than placebo among patients with kidney disease and/or diabetes (95% CI 1.27-1.48; P < 0.001). CONCLUSIONS: In patients with kidney disease and/or diabetes, treatment with finerenone resulted in lower risk of death from any cause and heart failure than placebo. However, the study-drug-related advent events also increased significantly at the same time.

Nanoscopic evaluation on mitochondrial ultrastructures by regulating reactive oxygen species productivity within terpyridyl Zn(II) complexes with different alkyl chain lengths.

Mitochondria targeting complexes are widely utilized as photosensitizers in photodynamic therapy. However, the mechanisms by which they regulate reactive oxygen species (ROS) production at the molecular level and their influence on intracellular mitochondrial signaling and ultrastructures remain rarely studied. Herein, we present two terpyridyl Zn(II) complexes with different side alkyl chain lengths (Zn-2C and Zn-6C) that lead to low and high ROS productivities in vitro, respectively. Both complexes could enter live cells effectively with minimal dark toxicity and accumulate preferably in the mitochondria. We also demonstrated that Zn-6C, with more efficient ROS productivity, could significantly downregulate the caspase signaling pathway but showed no evident influence on mitochondrial membrane proteins. We also highlighted and compared the mitochondrial ultrastructural variations during such a process by stimulated emission depletion (STED) super-resolution nanoscopy.

Insulin-like Growth Factor-2 (IGF-2) in Fibrosis.

The insulin family consists of insulin, insulin-like growth factor 1 (IGF-1), insulin-like growth factor 2 (IGF-2), their receptors (IR, IGF-1R and IGF-2R), and their binding proteins. All three ligands are involved in cell proliferation, apoptosis, protein synthesis and metabolism due to their homologous sequences and structural similarities. Insulin-like growth factor 2, a member of the insulin family, plays an important role in embryonic development, metabolic disorders, and tumorigenesis by combining with three receptors with different degrees of affinity. The main pathological feature of various fibrotic diseases is the excessive deposition of extracellular matrix (ECM) after tissue and organ damage, which eventually results in organic dysfunction because scar formation replaces tissue parenchyma. As a mitogenic factor, IGF-2 is overexpressed in many fibrotic diseases. It can promote the proliferation of fibroblasts significantly, as well as the production of ECM in a time- and dose-dependent manner. This review aims to describe the expression changes and fibrosis-promoting effects of IGF-2 in the skin, oral cavity, heart, lung, liver, and kidney fibrotic tissues.

Characterization of coagulation-related gene signature to predict prognosis and tumor immune microenvironment in skin cutaneous melanoma.

Backgroud: Skin cutaneous melanoma (SKCM) is an extremely metastatic form of skin cancer. However, there are few valuable molecular biomarkers, and accurate diagnosis is still a challenge. Hypercoagulable state encourages the infiltration and development of tumor cells and is significantly associated with poor prognosis in cancer patients. However, the use of a coagulation-related gene (CRG) signature for prognosis in SKCM, on the other hand, has yet to be determined. Method: We used data from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases to identify differentially expressed CRGs, then designed a prognostic model by using the LASSO algorithm, univariate and multivariate Cox regression analysis, and constructed a nomogram which was evaluated by calibration curves. Moreover, the Gene Expression Omnibus (GEO), GSE54467 was used as an independent validation. The correlation between risk score and clinicopathological characteristics, tumor microenvironment (TME), and immunotherapy was further analyzed. Results: To develop a prognostic model, seven CRGs in SKCM patients related to overall survival (OS) were selected: ANG, C1QA, CFB, DUSP6, KLKB1, MMP7, and RABIF. According to the Kaplan-Meier survival analysis, an increased OS was observed in the low-risk group than in the high-risk group (P<0.05). Immunotherapy was much more beneficial in the low-risk group, as per immune infiltration, functional enrichment, and immunotherapy analysis. Conclusions: The prognosis of SKCM patients may now be predicted with the use of a CRG prognostic model, thus guiding the development of treatment plans for SKCM patients and promoting OS rates.

Lowering Contact Resistances of Two-Dimensional Semiconductors by Memristive Forming.

Two-dimensional semiconductors have great potential for beyond-silicon electronics. However, because of the lack of controllable doping methods, Fermi level pinning, and van der Waals (vdW) gaps at the metal-semiconductor interfaces, these devices exhibit high electrical contact resistances, restricting their practical applications. Here, we report a general contact-resistance-lowering strategy by constructing vertical metal-semiconductor-metal memristor structures at the contact regions and setting them into a nonvolatile low-resistance state through a memristive forming process. Through this, we reduce the contact resistances of MoS2 field-effect transistors (FETs) by at least one order of magnitude and improve the on-state current densities of MoTe2 FETs by about two orders of magnitude. We also demonstrate that this strategy is applicable to other two-dimensional semiconductors, including MoSe2, WS2, and WSe2, and a variety of contact metals, including Au, Cu, Ni, and Pd. The good stability and universality indicate the great potential for technological applications.