2-Phenylbenzothiazolyl iridium complexes as inhibitors and probes of amyloid ß aggregation.

The aggregation of amyloid ß (Aß) peptides is a significant hallmark of Alzheimer's disease (AD), and the detection of Aß aggregates and the inhibition of their formation are important for the diagnosis and treatment of AD, respectively. Herein, we report a series of benzothiazole-based Ir(III) complexes HN-1 to HN-8 that exhibit appreciable inhibition of Aß aggregation in vitro and in living cells. These Ir(III) complexes can induce a significant fluorescence increase when binding to Aß fibrils and Aß oligomers, while their measured log D values suggest these compounds could have enhanced blood-brain barrier (BBB) permeability. In vivo studies show that HN-1, HN-2, HN-3, and HN-8 successfully penetrate the BBB and stain the amyloid plaques in AD mouse brains after a 10-day treatment, suggesting that these Ir(III) complexes could act as lead compounds for AD therapeutic and diagnostic agent development.

Agonist Discovery for Membrane Proteins on Live Cells by Using DNA-encoded Libraries.

Identifying biologically active ligands for membrane proteins is an important task in chemical biology. We report an approach to directly identify small molecule agonists against membrane proteins by selecting DNA-encoded libraries (DELs) on live cells. This method connects extracellular ligand binding with intracellular biochemical transformation, thereby biasing the selection toward agonist identification. We have demonstrated the methodology with three membrane proteins: epidermal growth factor receptor (EGFR), thrombopoietin receptor (TPOR), and insulin receptor (INSR). A ∼30 million and a 1.033 billion-compound DEL were selected against these targets, and novel agonists with subnanomolar affinity and low micromolar cellular activities have been discovered. The INSR agonists activated the receptor by possibly binding to an allosteric site, exhibited clear synergistic effects with insulin, and activated the downstream signaling pathways. Notably, the agonists did not activate the insulin-like growth factor 1 receptor (IGF-1R), a highly homologous receptor whose activation may lead to tumor progression. Collectively, this work has developed an approach toward "functional" DEL selections on the cell surface and may provide a widely applicable method for agonist discovery for membrane proteins.

A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.

GloEC: a hierarchical-aware global model for predicting enzyme function.

The annotation of enzyme function is a fundamental challenge in industrial biotechnology and pathologies. Numerous computational methods have been proposed to predict enzyme function by annotating enzyme labels with Enzyme Commission number. However, the existing methods face difficulties in modelling the hierarchical structure of enzyme label in a global view. Moreover, they haven't gone entirely to leverage the mutual interactions between different levels of enzyme label. In this paper, we formulate the hierarchy of enzyme label as a directed enzyme graph and propose a hierarchy-GCN (Graph Convolutional Network) encoder to globally model enzyme label dependency on the enzyme graph. Based on the enzyme hierarchy encoder, we develop an end-to-end hierarchical-aware global model named GloEC to predict enzyme function. GloEC learns hierarchical-aware enzyme label embeddings via the hierarchy-GCN encoder and conducts deductive fusion of label-aware enzyme features to predict enzyme labels. Meanwhile, our hierarchy-GCN encoder is designed to bidirectionally compute to investigate the enzyme label correlation information in both bottom-up and top-down manners, which has not been explored in enzyme function prediction. Comparative experiments on three benchmark datasets show that GloEC achieves better predictive performance as compared to the existing methods. The case studies also demonstrate that GloEC is capable of effectively predicting the function of isoenzyme. GloEC is available at: https://github.com/hyr0771/GloEC.

Environment-responsive dendrobium polysaccharide hydrogel embedding manganese microsphere as a post-operative adjuvant to boost cascaded immune cycle against melanoma.

Rationale: Surgical resection is a primary treatment for solid tumors, but high rates of tumor recurrence and metastasis post-surgery present significant challenges. Manganese (Mn2+), known to enhance dendritic cell-mediated cancer immunotherapy by activating the cGAS-STING pathway, has potential in post-operative cancer management. However, achieving prolonged and localized delivery of Mn2+ to stimulate immune responses without systemic toxicity remains a challenge. Methods: We developed a post-operative microenvironment-responsive dendrobium polysaccharide hydrogel embedded with Mn2+-pectin microspheres (MnP@DOP-Gel). This hydrogel system releases Mn2+-pectin microspheres (MnP) in response to ROS, and MnP shows a dual effect in vitro: promoting immunogenic cell death and activating immune cells (dendritic cells and macrophages). The efficacy of MnP@DOP-Gel as a post-surgical treatment and its potential for immune activation were assessed in both subcutaneous and metastatic melanoma models in mice, exploring its synergistic effect with anti-PD1 antibody. Result: MnP@DOP-Gel exhibited ROS-responsive release of MnP, which could exert dual effects by inducing immunogenic cell death of tumor cells and activating dendritic cells and macrophages to initiate a cascade of anti-tumor immune responses. In vivo experiments showed that the implanted MnP@DOP-Gel significantly inhibited residual tumor growth and metastasis. Moreover, the combination of MnP@DOP-Gel and anti-PD1 antibody displayed superior therapeutic potency in preventing either metastasis or abscopal brain tumor growth. Conclusions: MnP@DOP-Gel represents a promising drug-free strategy for cancer post-operative management. Utilizing this Mn2+-embedding and ROS-responsive delivery system, it regulates surgery-induced immune responses and promotes sustained anti-tumor responses, potentially increasing the effectiveness of surgical cancer treatments.

AFP: Finding pathways accounting for stoichiometry along with atom group tracking in metabolic network.

Automatically finding novel pathways plays an important role in the initial designs of metabolic pathways in synthetic biology and metabolic engineering. Although path-finding methods have been successfully applied in identifying valuable synthetic pathways, few efforts have been made in fusing atom group tracking into building stoichiometry model to search metabolic pathways from arbitrary start compound via Mixed Integer Linear Programming (MILP). We propose a novel method called AFP to find metabolic pathways by incorporating atom group tracking into reaction stoichiometry via MILP. AFP tracks the movements of atom groups in the reaction stoichiometry to construct MILP model to search the pathways containing atom groups exchange in the reactions and adapts the MILP model to provide the options of searching pathways from an arbitrary or given compound to the target compound. Combining atom group tracking with reaction stoichiometry to build MILP model for pathfinding may promote the search of well-designed alternative pathways at the stoichiometric modeling level. The experimental comparisons to the known pathways show that our proposed method AFP is more effective to recover the known pathways than other existing methods and is capable of discovering biochemically feasible pathways producing the metabolites of interest.

Study of the cement implantation syndrome: A review.

Bone cement implantation syndrome (BCIS) is a critical and potentially life-threatening condition that manifests during implantation. Characterized by a constellation of symptoms, including hypoxemia, hypotension, cardiac arrhythmias, elevated pulmonary vascular resistance, and occasionally cardiac arrest, BCIS typically ensues shortly after cement introduction, albeit with rare instances of delayed onset. Primarily attributed to the exothermic reaction of bone cement implantation, this syndrome is caused by local tissue damage, histamine and prostaglandin release, and microemboli formation, ultimately triggering a systemic immune response that culminates in respiratory and circulatory failure. The current hypotheses regarding BCIS include embolism, allergic reactions, and cement autotoxicity. BCIS management emphasizes preventative strategies, encompassing meticulous patient risk assessment, comprehensive preoperative and intraoperative evaluations, and precise cement application techniques. Treatment primarily involves symptomatic therapy and life-support measures to address the systemic effects of the syndrome.

Neoadjuvant toripalimab combined with axitinib in patients with locally advanced clear cell renal cell carcinoma: a single-arm, phase II trial.

BACKGROUND: A combination of axitinib and immune checkpoint inhibitors (ICIs) demonstrated promising efficacy in the treatment of advanced renal cell carcinoma (RCC). This study aims to prospectively evaluate the safety, efficacy, and biomarkers of neoadjuvant toripalimab plus axitinib in non-metastatic clear cell RCC. METHODS: This is a single-institution, single-arm phase II clinical trial. Patients with non-metastatic biopsy-proven clear cell RCC (T2-T3N0-1M0) are enrolled. Patients will receive axitinib 5 mg twice daily combined with toripalimab 240 mg every 3 weeks (three cycles) for up to 12 weeks. Patients then will receive partial (PN) or radical nephrectomy (RN) after neoadjuvant therapy. The primary endpoint is objective response rate (ORR). Secondary endpoints include disease-free survival, safety, and perioperative complication rate. Predictive biomarkers are involved in exploratory analysis. RESULTS: A total of 20 patients were enrolled in the study, with 19 of them undergoing surgery. One patient declined surgery. The primary endpoint ORR was 45%. The posterior distribution of πORR had a mean of 0.44 (95% credible intervals: 0.24-0.64), meeting the predefined primary endpoint with an ORR of 32%. Tumor shrinkage was observed in 95% of patients prior to nephrectomy. Furthermore, four patients achieved a pathological complete response. Grade ≥3 adverse events occurred in 25% of patients, including hypertension, hyperglycemia, glutamic pyruvic transaminase/glutamic oxaloacetic transaminase (ALT/AST) increase, and proteinuria. Postoperatively, one grade 4a and eight grade 1-2 complications were noted. In comparison to patients with stable disease, responders exhibited significant differences in immune factors such as Arginase 1(ARG1), Melanoma antigen (MAGEs), Dendritic Cell (DC), TNF Superfamily Member 13 (TNFSF13), Apelin Receptor (APLNR), and C-C Motif Chemokine Ligand 3 Like 1 (CCL3-L1). The limitation of this trial was the small sample size. CONCLUSION: Neoadjuvant toripalimab combined with axitinib shows encouraging activity and acceptable toxicity in locally advanced clear cell RCC and warrants further study. TRIAL REGISTRATION NUMBER: clinicaltrials.gov, NCT04118855.

CDCA5-EEF1A1 interaction promotes progression of clear cell renal cell carcinoma by regulating mTOR signaling.

BACKGROUND: Cell division cycle associated 5 (CDCA5) plays ontogenetic role in various human cancers. However, its specific function and regulatory mechanism in ccRCC remain uncertain. METHODS: Immunohistochemistry and western blots were performed to investigate the expression of CDCA5 in ccRCC tissues. Genetic knockdown and upregulation of CDCA5 were performed to investigate its functional roles in ccRCC proliferation, migration, apoptosis and sunitinib resistance. Furthermore, Co-IP assay and LC-MS/MS were performed to investigate the underlying mechanisms. RESULTS: We found that CDCA5 expression is frequently upregulated in ccRCC tumors and is associated with poor prognosis of ccRCC patients. Functionally, CDCA5 promotes proliferation, migration, and sunitinib resistance, while inhibiting apoptosis in ccRCC cells. In vivo mouse xenograft model confirms that silencing of CDCA5 drastically inhibits the growth of ccRCC. Mechanistically, we discovered that CDCA5 interacts with Eukaryotic Translation Elongation Factor 1 Alpha 1 (EEF1A1) to regulate mTOR signaling pathway, thereby promoting ccRCC progression. CONCLUSIONS: Taken together, our results demonstrate the significant role of CDCA5 in ccRCC progression. The findings may provide insights for the development of new treatment strategies targeting CDCA5 for ccRCC patients.

A bibliometric study on trends in chiropractic research from 1920 to 2023.

OBJECTIVE: An increasing body of evidence suggests a positive role of chiropractic in the treatment of neuro-musculoskeletal disorders. This study aims to explore current research hotspots and trends, providing insights into the broad prospects of this field. METHODS: A bibliometric review was conducted on all chiropractic articles included in the Web of Science Core Collection before December 31, 2023. RESULTS: Over the past century, the volume of research in the field of chiropractic has been fluctuating annually, with four peaks observed in total. The United States, Canada, Australia, and the United Kingdom are leading countries. Chu, Eric Chun-Pu is the author with the most publications, while Bronfort, Gert has the highest total citation count. The University of Southern Denmark has produced the most publications, while Queens University - Canada is the most central institution. The Journal of Manipulative and Physiological Therapeutics is the journal with the most publications and citations, while the Journal of the American Medical Association is the most central journal. The two most-cited articles were both authored by Eisenberg DM. Emerging keywords include "chronic pain" and "skills". The theoretical mechanisms and scientific basis of chiropractic, its clinical practice and safety, education and training, integration with other disciplines, and patient experiences and satisfaction are the frontiers and hotspots of research. CONCLUSION: This study integrates bibliometric analysis to summarize the current state of research and global network centers in the field of chiropractic, further highlighting the hotspots and trends in this field. However, Individual and national rankings should be interpreted with caution due to our focus on Web of Science rather than PubMed.

Pathogenesis or a response to lithium? A novel perspective for mitochondrial mass fluctuation of naïve T cells in patients with bipolar disorder.

BACKGROUND: Immune imbalances are associated with the pathogenesis and pharmacological efficacy of bipolar disorder (BD). The underlying mechanisms remain largely obscure but may involve immunometabolic dysfunctions of T-lymphocytes. METHODS: We investigated if inflammatory cytokines and the immunometabolic function of T-lymphocytes, including frequencies of subsets, mitochondrial mass (MM), and low mitochondrial membrane potential (MMPLow) differed between BD patients (n = 47) and healthy controls (HC, n = 43). During lithium treatment of hospitalized patients (n = 33), the association between weekly T-lymphocyte immune metabolism and clinical symptoms was analyzed, and preliminary explorations on possible mechanisms were conducted. RESULTS: In comparison to HC, BD patients predominantly showed a trend toward CD4+ naïve T (Tn) activation and exhibited mitochondrial metabolic disturbances such as decreased MM and increased MMPLow. Lower CD4+ Tn-MM correlated with elevated IL-6, IL-8, and decreased IL-17 A in BD patients. With lithium treatment effective, MM of CD4+ T/Tn was negatively correlated with depression score HAMD. When lithium intolerance was present, MM of CD4+ T/Tn was positively correlated with depression score HAMD and mania score BRMS. Lithium does not mediate through the inositol depletion hypothesis, but the mRNA level of IMPA2 in peripheral blood is associated with mitochondrial function in CD8+ T cells. LIMITATIONS: The cross-sectional design and short-term follow-up meant that we could not directly examine the causality of BD and immune dysregulation. CONCLUSION: The altered metabolism of CD4+ Tn was strongly associated with remodeling of the inflammatory landscape in BD patients and can also be used to reflect the short-term therapeutic effects of lithium.

Classifying breast cancer subtypes on multi-omics data via sparse canonical correlation analysis and deep learning.

BACKGROUND: Classifying breast cancer subtypes is crucial for clinical diagnosis and treatment. However, the early symptoms of breast cancer may not be apparent. Rapid advances in high-throughput sequencing technology have led to generating large number of multi-omics biological data. Leveraging and integrating the available multi-omics data can effectively enhance the accuracy of identifying breast cancer subtypes. However, few efforts focus on identifying the associations of different omics data to predict the breast cancer subtypes. RESULTS: In this paper, we propose a differential sparse canonical correlation analysis network (DSCCN) for classifying the breast cancer subtypes. DSCCN performs differential analysis on multi-omics expression data to identify differentially expressed (DE) genes and adopts sparse canonical correlation analysis (SCCA) to mine highly correlated features between multi-omics DE-genes. Meanwhile, DSCCN uses multi-task deep learning neural network separately to train the correlated DE-genes to predict breast cancer subtypes, which spontaneously tackle the data heterogeneity problem in integrating multi-omics data. CONCLUSIONS: The experimental results show that by mining the associations among multi-omics data, DSCCN is more capable of accurately classifying breast cancer subtypes than the existing methods.

Fumarate induces LncRNA-MIR4435-2HG to regulate glutamine metabolism remodeling and promote the development of FH-deficient renal cell carcinoma.

Fumarate hydratase (FH) deficient renal cell carcinoma (RCC) is a type of tumor with definite metabolic disorder, but the mechanism of metabolic remodeling is still unclear. LncRNA was reported to closely correlate with cancer metabolism, however the biological role of LncRNA in the development of progression of FH-deficent RCC was not well studied either. FH-deficient RCC samples were collected in my hospital and used for RNA-sequencing and Mass spectrometry analysis. FH-deficient RCC cell line UOK262 and control pFH cells were used for in vitro experiments, including proliferation assay, transwell assay, western-blot, mass spectrometry and so on. PDX mouse model was used for further drug inhibition experiments in vivo. In this study, we analyzed the profiles of LncRNA and mRNA in FH-deficienct RCC samples, and we found that the LncRNA-MIR4435-2GH was specifically highly expressed in FH-deficient RCC compared with ccRCC. In vitro experiments demonstrated that MIR4435-2HG was regulated by Fumarate through histone demethylation, and the deletion of this gene could inhibit glutamine metabolism. RNA-pulldown experiments showed that MIR4435-2HG specifically binds to STAT1, which can transcriptionally activate GLS1. GLS1 inhibitor CB-839 could significantly suppress tumor growth in PDX tumor models. This study analyzed the molecular mechanism of MIR4435-2HG in regulating metabolic remodeling of FH-deficient RCC in clinical samples, cells and animal models by combining transcriptional and metabolic methods. We found that that GLS1 was a therapeutic target for this tumor, and MIR4435-2HG can be used as a drug sensitivity marker.

Warm Acupuncture Reduces Pain and Inflammation in Rats with Lumbar Disc Herniation Induced by Autologous Nucleus Pulposus Transplantation via Regulating p38MAPK/NF-κB Pathway.

Background: : Warm acupuncture (WA) has analgesic and anti-inflammatory effects. However, the underlying mechanism of these effects remain unclear. Objectives: : To explore the analgesic and anti-inflammatory effects of WA and the potential underlying mechanism in male Sprague-Dawley rats with non-compressive lumbar disk herniation (LDH) caused by autologous nucleus pulposus (NP) transplantation. Methods: : We used low-frequency (2 Hz) electrical stimulation and WA (40℃) to treat GB30 and BL54 acupoints in rats for 30 mins per day. We monitored the paw withdrawal threshold of rats during the experiment and measured serum cytokine levels using commercial kits. Dorsal root ganglion (DRG) tissue pathology was analyzed via H&E staining. We used qRT-PCR to measure the mRNA expression levels of IL-1ß, IL-6, and TNF-α genes in DRG. Western blot was used to analyze the expression levels of IL-1ß, IL-6, TNFα, P-p38MAPK, p38MAPK, P-IκBα, IκB α, and NF-κB p65 proteins. Results: : WA treatment significantly increased the pain threshold of rats, reduced serum IL-6, PEG2, NO, SP, NP-Y, and MMP-3 levels, and effected histopathological improvements in the DRG in rats. Moreover, WA treatment significantly downregulated the expression levels of inflammation-associated genes (Il-1ß, Il-6, and Tnf-α) and proteins (IL-1ß, IL-6, TNF-α, P-p38MAPK, P-IκBα, and NF-κB p65) in the DRG of non-compressive LDH rats. Conclusion: : WA can alleviate pain and inhibit inflammatory response in rats with non-compressive LDH caused by autologous NP transplantation, and these effects are likely associated with the inhibition of the p38MAPK/NF-κB pathway.

Fabrication of well-aligned Co-MOF arrays through a controlled and moderate process for the development of a flexible tetrabromobisphenol A sensor.

Tetrabromobisphenol A (TBBPA) has attracted a great deal of attention due to its side effects and potential bioaccumulation properties. It is of great importance to construct and develop novel electrochemical sensors for the sensitive and selective detection of TBBPA. In the present study, cobalt (Co) based metal-organic frameworks (MOFs) were synthesized on carbon cloth (CC) by using cobalt nitrate hexahydrate and 2-methylimidazole. The morphological characterization was carried out by transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). The results showed that Co-MOFs/CC have a leaf-like structure and abundant surface functional groups. The electrochemical properties of the sensor were investigated by differential pulse voltammetry (DPV). The effects of different ratios of metal ions to organic ligands, reaction temperature, time, concentration, pH value of the electrolyte, and incubation time on the oxidation peak current of TBBPA were studied. Under the optimal conditions, the linear range of the designed sensor was 0.1 µM-100 µM, and the limit of detection was 40 nM. The proposed sensor is simple, of low cost and efficient, which can greatly facilitate the detection tasks of environmental monitoring workers.

Exploring gene-patient association to identify personalized cancer driver genes by linear neighborhood propagation.

BACKGROUND: Driver genes play a vital role in the development of cancer. Identifying driver genes is critical for diagnosing and understanding cancer. However, challenges remain in identifying personalized driver genes due to tumor heterogeneity of cancer. Although many computational methods have been developed to solve this problem, few efforts have been undertaken to explore gene-patient associations to identify personalized driver genes. RESULTS: Here we propose a method called LPDriver to identify personalized cancer driver genes by employing linear neighborhood propagation model on individual genetic data. LPDriver builds personalized gene network based on the genetic data of individual patients, extracts the gene-patient associations from the bipartite graph of the personalized gene network and utilizes a linear neighborhood propagation model to mine gene-patient associations to detect personalized driver genes. The experimental results demonstrate that as compared to the existing methods, our method shows competitive performance and can predict cancer driver genes in a more accurate way. Furthermore, these results also show that besides revealing novel driver genes that have been reported to be related with cancer, LPDriver is also able to identify personalized cancer driver genes for individual patients by their network characteristics even if the mutation data of genes are hidden. CONCLUSIONS: LPDriver can provide an effective approach to predict personalized cancer driver genes, which could promote the diagnosis and treatment of cancer. The source code and data are freely available at https://github.com/hyr0771/LPDriver .

Retroperitoneoscopic Clampless, Sutureless Hybrid Therapy in the Management of Renal Hilar Tumors.

OBJECTIVE: We aimed to investigate the outcomes and feasibility of a retroperitoneoscopic clampless, sutureless hybrid technique in the management of renal hilar tumors. METHODS: A retrospective cohort of consecutive patients with renal hilar tumors who received retroperitoneoscopic clampless, sutureless hybrid therapy between January 2017 and April 2021 was included. The hybrid surgical technique involved microwave ablation (MWA), followed by clampless tumor enucleation and sutureless hemostasis. Surgical, pathological, and oncological outcomes were recorded and analyzed. RESULTS: Sixty patients were included in this study. The median tumor size was 3.5 cm (2-5), the median RENAL score was 7 (range 6-10), the median operative time was 110 min (70-130), and the median estimated blood loss was 80 mL (30-130). The median length of postoperative hospital stay was 3 days (2-4), and no warm ischemia time was observed, except in one patient who required conversion to conventional on-clamp laparoscopic partial nephrectomy (LPN) with a 10 min warm ischemia time. Three minor complications (Clavien-Dindo grade I) and one major complication (Clavien-Dindo grade III) were recorded postoperatively. Thus far, no blood transfusions have been required. Renal dysfunction or tumor recurrence did not occur within a median follow-up of 45 months. CONCLUSION: The retroperitoneoscopic hybrid technique involving MWA, clampless tumor enucleation, and sutureless hemostasis is a feasible and safe option for the management of selective renal hilar tumors. Complete tumor removal with maximal renal function preservation can be achieved, with a low complication rate.

Comparative analysis of salvage partial nephrectomy versus radical nephrectomy after the failure of initial partial nephrectomy.

OBJECTIVES: To compare the oncologic outcomes and renal function discrepancy of salvage partial nephrectomy (sPN) and salvage radical nephrectomy (sRN) after an initial failed PN. MATERIALS AND METHODS: Retrospective data from multiple centers between 2008 and 2022 were analyzed in this study. Patients who received sPN or sRN after an initial failed PN were identified. Comparative analysis and propensity score matching (PSM) was performed and the RENAL score, tumor size, and pathological T stage at salvage surgery were used to match the 2 groups. Local recurrence-free survival (LRFS) and recurrence-free survival (RFS) were assessed using the Cox proportional hazards model and log-rank tests. Renal function after salvage surgery was assessed using the Wilcoxon rank sum test. RESULTS: A total of 140 patients who underwent salvage surgery were evaluated, of whom 60 were considered for PSM analysis after matching. At a median follow-up of 27.0 months, LRFS and RFS showed no significant difference between sPN and sRN, either before (LRFS, HR = 0.673 [95% CI: 0.171-2.644], P = 0.610; RFS, HR = 0.744 [95% CI: 0.271-1.344], P = 0.595) or after matching (LRFS, HR = 1.080 [95% CI: 0.067-17.30], P = 0.957; RFS, HR = 1.199 [95% CI: 0.241-5.983], P = 0.822). During long-term follow-up, sPN preserved renal function (after matching, eGFR, 71.4 vs. 54.0, P < 0.001) and prevented eGFR loss (after matching: 6.6% vs. 25.6%, P < 0.001). CONCLUSION: Salvage partial nephrectomy offers a better alternative than sRN for recurrence after initial PN, as sPN preserves renal function better while maintaining parallel tumor control and acceptable complication rates.

SPAG5, the upstream protein of Wnt and the target of curcumin, inhibits hepatocellular carcinoma.

The inhibitory role of curcumin on sperm-associated antigen 5 (SPAG5) and its effects on the cancer­related Wnt classical signaling pathway has been previously demonstrated. Nevertheless, research on the modulatory role of curcumin on the Wnt signaling pathway by acting on SPAG5 has yet to be reported. The activation of the Wnt/ß­catenin pathway is frequently observed in patients suffering from hepatocellular carcinoma (HCC), suggesting that small molecular drugs that target Wnt could present a promising therapeutic strategy. However, these drugs often result in substantial side effects. In the present study, the presence of SPAG5 in the cancer tissues of patients with HCC and cell lines was validated using immunohistochemistry, cellular immunofluorescence, reverse transcription­quantitative polymerase chain reaction, and western blot analyses. Subsequently, the effect of SPAG5 and the regulatory role of curcumin on SPAG5 and the Wnt/ß­catenin pathway were examined using cell function tests, flow cytometry, and western blotting. Techniques of gene knockout and overexpression were employed. The findings revealed a significant overexpression of SPAG5 in the cancer tissues of patients with HCC. Both the mRNA and protein levels of SPAG5 in Huh7 and HCCLM3 cell lines were markedly elevated. Treatment with curcumin led to a decrease in SPAG5 expression, while also inhibiting cell migration and promoting apoptosis. Additionally, suppression of SPAG5 expression resulted in the decreased expression of ß­catenin. Furthermore, curcumin was observed to reduce the expression of cyclin D1 in SPAG5­overexpressing cell lines. However, the degree of inhibition was diminished once SPAG5 expression was silenced. These initial findings indicate that SPAG5 may function as an upstream regulatory protein of the Wnt/ß­catenin pathway, hence offering a potential alternative target for HCC. Moreover, as curcumin has the capacity to inhibit Wnt via suppressing SPAG5, it could potentially serve as a natural drug component for early intervention and treatment of HCC.

Mitochondrial mass of circulating NK cells as a novel biomarker in severe SARS-CoV-2 infection.

BACKGROUND: Severe SARS-CoV-2 infection results in lymphopenia and impaired function of T, B, and NK (TBNK-dominant) lymphocytes. Mitochondria are essential targets of SARS-CoV-2 and the efficacy of lymphocyte mitochondrial function for immunosurveillance in COVID-19 patients has not been evaluated. METHODS: Multi-parametric flow cytometry was used to characterize mitochondrial function, including mitochondrial mass (MM) and low mitochondrial membrane potential (MMPlow), in TBNK-dominant lymphocytes from severe (n = 93) and moderate (n = 77) hospitalized COVID-19 patients. We compared the role of novel lymphocyte mitochondrial indicators and routine infection biomarkers as early predictors of severity and death in COVID-19 patients. We then developed a mortality decision tree prediction model based on immunosurveillance indicators through machine learning. RESULTS: At admission, the MM of circulating NK cells (NK-MM) was the best discriminator of severe/moderate disease (AUC = 0.8067) compared with the routine infection biomarkers. The NK cell count and NK-MM displayed superior diagnostic effects to distinguish patients with non-fatal or fatal outcomes. Interestingly, NK-MM was significantly polarized in non-survivors, with some patients showing a decrease and others showing an abnormal increase. Kaplan-Meier analysis showed that NK-MM had the optimal predictive efficacy (hazard ratio = 11.66). The decision tree model has the highest proportion of importance for NK-MM, which is superior to the single diagnostic effect of the above indicators (AUC = 0.8900). CONCLUSION: NK-MM was not only associated with disease severity, its abnormal increases or decreases also predicted mortality risk. The resulting decision tree prediction model is the first to focus on immune monitoring indicators to provide decision-making clues for COVID-19 clinical management.