A GABAergic system in atrioventricular node pacemaker cells controls electrical conduction between the atria and ventricles.

Physiologically, the atria contract first, followed by the ventricles, which is the prerequisite for normal blood circulation. The above phenomenon of atrioventricular sequential contraction results from the characteristically slow conduction of electrical excitation of the atrioventricular node (AVN) between the atria and the ventricles. However, it is not clear what controls the conduction of electrical excitation within AVNs. Here, we find that AVN pacemaker cells (AVNPCs) possess an intact intrinsic GABAergic system, which plays a key role in electrical conduction from the atria to the ventricles. First, along with the discovery of abundant GABA-containing vesicles under the surface membranes of AVNPCs, key elements of the GABAergic system, including GABA metabolic enzymes, GABA receptors, and GABA transporters, were identified in AVNPCs. Second, GABA synchronously elicited GABA-gated currents in AVNPCs, which significantly weakened the excitability of AVNPCs. Third, the key molecular elements of the GABAergic system markedly modulated the conductivity of electrical excitation in the AVN. Fourth, GABAA receptor deficiency in AVNPCs accelerated atrioventricular conduction, which impaired the AVN's protective potential against rapid ventricular frequency responses, increased susceptibility to lethal ventricular arrhythmias, and decreased the cardiac contractile function. Finally, interventions targeting the GABAergic system effectively prevented the occurrence and development of atrioventricular block. In summary, the endogenous GABAergic system in AVNPCs determines the slow conduction of electrical excitation within AVNs, thereby ensuring sequential atrioventricular contraction. The endogenous GABAergic system shows promise as a novel intervention target for cardiac arrhythmias.

Impact of lipoprotein(a) and fibrinogen on prognosis in patients with coronary artery disease: A retrospective cohort study.

BACKGROUND: Despite the considerable progress made in preventative methods, medication, and interventional therapies, it remains evident that cardiovascular events (CVEs) continue to be the primary cause of both death and morbidity among individuals diagnosed with coronary artery disease (CAD). OBJECTIVE: To compare the connection between lipoprotein a (Lp[a]), fibrinogen (Fib), and both parameters combined with all-cause mortality to detect their value as prognostic biomarkers. METHODS: This is a retrospective study. Patients diagnosed with CAD between January 2007 and December 2020 at the Guangdong Provincial People's Hospital (China) were involved in the study. 43,367 patients met the eligibility criteria. The Lp(a) and Fib levels were distributed into three tertile groups (low, medium, and high). All of the patients included in the study were followed up for all-cause mortality. Kaplan-Meier and Cox regression were performed to determine the relationship between Lp(a), Fib, and all-cause mortality. A concordance statistics model was developed to detect the impact of Fib and Lp(a) in terms of anticipating poor outcomes in patients with CAD. RESULTS: Throughout a median follow-up of 67.0 months, 6,883 (15.9%) patients died. Participants with high Lp(a) (above 27.60 mg/dL) levels had a significantly higher risk for all-cause mortality than individuals with low Lp(a) levels (below 11.13 mg/dL; adjusted hazard ratio [aHR] 1.219, 95% confidence interval [CI]: 1.141-1.304, p< 0.001). Similarly, patients with high Fib levels (above 4.32 g/L) had a significantly greater risk of developing all-cause mortality compared with those with reduced Fib levels (below 3.41 g/L; aHR 1.415, 95% CI: 1.323-1.514, p< 0.001). Patients with raised Lp(a) and Fib levels had the maximum risk for all-cause mortality (aHR 1.702; 95% CI: 1.558-1.859, p< 0.001). When considered together, Lp(a) and Fib caused a significant elevation of the concordance statistic by 0.009 (p< 0.05), suggesting a higher value for predicting mortality when combining the two indicators. CONCLUSION: High Lp(a) and Fib levels could be used as predictive biomarkers for all-cause mortality in individuals with CAD. The prediction accuracy for all-cause mortality improved after combining the two parameters.

Clinicopathological Characteristics of Light and Heavy Chain Deposition Disease: A Case Series.

RATIONALE & OBJECTIVE: Light and heavy chain deposition disease (LHCDD) is a rare form of monoclonal immunoglobulin deposition disease (MIDD), and limited clinical data are available characterizing this condition. We described the clinicopathological characteristics and outcomes of LHCDD. STUDY DESIGN: Case series. SETTING & PARTICIPANTS: 13 patients with biopsy-proven LHCDD, diagnosed between January 2008 to December 2022, at two Chinese medical centers. FINDINGS: Among the 13 patients described, 6 were men and 7 were women, with a mean age of 52.6 ± 8.0 years. Patients presented with hypertension (76.9%), anemia (84.6%), elevated serum creatinine (84.6%, median serum creatinine 1.7 mg/dL), proteinuria (100%, average urine protein 3.0g/24h), nephrotic syndrome (30.8%) and microscopic hematuria (76.9%). Serum immunofixation electrophoresis showed monoclonal immunoglobulin for 11 (84.6%) patients. Serum free light chain (FLC) ratios were abnormal in 11 (84.6%) patients, and heavy/light chain (HLC) ratios were abnormal in 9 of 10 (90%) patients with available data. Five patients were diagnosed with multiple myeloma. A histological diagnosis of nodular mesangial sclerosis was made in 10 (76.9%) patients. Immunofluorescence demonstrated deposits of IgG subclass (γ-κ/γ-λ:4/3) in 7 patients, and IgA (α-κ/α-λ:2/3) in 5 patients. Six patients underwent IgG subclass staining (γ1/γ2/γ3:3/2/1). The deposits of IgD-κ were confirmed by mass spectrometry in 1 patient. Among 12 patients for whom data were available over a median of 26.5 months, 11 received chemotherapy, and 1 received conservative treatment. One patient died. Three (25%) patients progressed to kidney failure. Among the 9 patients evaluable for hematological and kidney disease progression, five (56%) had a hematologic response and one (11%) achieved improvement in kidney disease. LIMITATIONS: Retrospective descriptive study, limited number of patients, UPEP or UIFE missing for most patients. CONCLUSIONS: In this case series of LHCDD, light and heavy chain deposition in kidney tissues were most frequent with monoclonal IgG1-κ. Among patients with evaluable data, more than half had hematologic response but a kidney response was uncommon.

Primary immunodeficiency as a cause of immune-mediated kidney diseases.

Primary immunodeficiency (PID) is no longer defined by infections alone, and autoimmunity is an accompanying manifestation of PID. Recurrent infections may trigger autoimmunity through molecular mimicry, bystander activation, or superantigens. The diagnosis of PID is still challenging, but genetic analysis reveals the underlying link between PID and autoimmunity. Mutations in relevant genes affecting central and peripheral immune tolerance, regulatory T-cell function, expansion of autoreactive lymphocytes, antigen clearance, hyperactivation of type I interferon, and NF-κB pathways have all been implicated in triggering autoimmunity in PID. Autoimmunity in PID leads to chronic inflammation, tissue damage, and organ failure and increases the mortality of patients with PID. The kidneys are inextricably linked with the immune system, and kidney diseases can be mediated by both infection and autoimmunity/inflammation in PID patients. The manifestations of kidney involvement in PID patients are very heterogeneous and include lupus nephritis, C3 glomerulopathy, kidney thrombotic microangiopathy, vasculitis, and interstitial nephritis.Patients with PID-caused kidney diseases have defined immune function defects and may benefit from pathway-based biologics, stem cell transplantation, or gene therapy. Early diagnosis and appropriate treatment of PID are crucial for reducing the mortality rate and improving organ function and quality of life.

Development and external validation of a multidimensional deep learning model to dynamically predict kidney outcomes in IgA nephropathy.

BACKGROUND: Accurately predicting kidney outcomes in IgA nephropathy is crucial for clinical decision making. Insufficient use of longitudinal data in previous studies has limited the accuracy and interpretability of prediction models for failing to reflect the chronic nature of IgA nephropathy. This study aimed at establishing a multivariable dynamic deep learning model using comprehensive longitudinal data for the prediction of kidney outcomes in IgA nephropathy. METHODS: In this retrospective cohort study of 2,056 IgA nephropathy patients at 18 kidney centers, a total of 28,317 data points were collected by the sliding window method. Among them, 15,462 windows in a single center were randomly assigned to training (80%) and validation (20%) sets while 8797 windows in 18 kidney centers were assigned to an independently test set. Interpretable Multi-Variable Long Short-Term Memory (IMV-LSTM), a deep learning model, was implemented to predict kidney outcomes (kidney failure or 50% decline in kidney function) based on time-invariant variables measured at biopsy and time-variant variables measured during follow-up. Risk performance was evaluated using Kaplan-Meier analysis and the C statistic. Trajectory analysis was performed to assess the various trends of clinical variables during follow-up. RESULTS: The model achieved a higher C statistic (0.93; 95% CI, 0.92-0.95) on the test set than the XGBoost prediction model that we developed in a previous study using only baseline information (C statistic, 0.84; 95% CI, 0.80-0.88). Kaplan-Meier analysis showed that groups with lower predicted risks from the full model survived longer than groups with higher risks. Time-variant variables demonstrated higher importance scores than time-invariant variables. Within time-variant variables, more recent measurements showed higher importance scores. Further interpretation showed that certain trajectory groups of time-variant variables such as serum creatinine and urine protein were associated with elevated risks of adverse outcomes. CONCLUSIONS: In IgA nephropathy, a deep learning model can be used to accurately and dynamically predict kidney prognosis based on longitudinal data, and time-variant variables show strong ability to predict kidney outcome.

Sorting Out the Latest Advances in Separators and Pilot-Scale Microbial Electrochemical Systems for Wastewater Treatment: Concomitant Development, Practical Application, and Future Perspective.

To date, dozens of pilot-scale microbial fuel cell (MFC) devices have been successfully developed worldwide for treating various types of wastewater. The availability and configurations of separators are determining factors for the economic feasibility, efficiency, sustainability, and operability of these devices. Thus, the concomitant advances between the separators and pilot-scale MFC configurations deserve further clarification. The analysis of separator configurations has shown that their evolution proceeds as follows: from ion-selective to ion-non-selective, from nonpermeable to permeable, and from abiotic to biotic. Meanwhile, their cost is decreasing and their availability is increasing. Notably, the novel MFCs configured with biotic separators are superior to those configured with abiotic separators in terms of wastewater treatment efficiency and capital cost. Herein, a highly comprehensive review of pilot-scale MFCs (>100 L) has been conducted, and we conclude that the intensive stack of the liquid cathode configuration is more advantageous when wastewater treatment is the highest priority. The use of permeable biotic separators ensures hydrodynamic continuity within the MFCs and simplifies reactor configuration and operation. In addition, a systemic comparison is conducted between pilot-scale MFC devices and conventional decentralized wastewater treatment processes. MFCs showed comparable cost, higher efficiency, long-term stability, and significant superiority in carbon emission reduction. The development of separators has greatly contributed to the availability and usability of MFCs, which will play an important role in various wastewater treatment scenarios in the future.

Artificial intelligence assists identification and pathologic classification of glomerular lesions in patients with diabetic nephropathy.

BACKGROUND: Glomerular lesions are the main injuries of diabetic nephropathy (DN) and are used as a crucial index for pathologic classification. Manual quantification of these morphologic features currently used is semi-quantitative and time-consuming. Automatically quantifying glomerular morphologic features is urgently needed. METHODS: A series of convolutional neural networks (CNN) were designed to identify and classify glomerular morphologic features in DN patients. Associations of these digital features with pathologic classification and prognosis were further analyzed. RESULTS: Our CNN-based model achieved a 0.928 F1-score for global glomerulosclerosis and 0.953 F1-score for Kimmelstiel-Wilson lesion, further obtained a dice of 0.870 for the mesangial area and F1-score beyond 0.839 for three glomerular intrinsic cells. As the pathologic classes increased, mesangial cell numbers and mesangial area increased, and podocyte numbers decreased (p for all < 0.001), while endothelial cell numbers remained stable (p = 0.431). Glomeruli with Kimmelstiel-Wilson lesion showed more severe podocyte deletion compared to those without (p < 0.001). Furthermore, CNN-based classifications showed moderate agreement with pathologists-based classification, the kappa value between the CNN model 3 and pathologists reached 0.624 (ranging from 0.529 to 0.688, p < 0.001). Notably, CNN-based classifications obtained equivalent performance to pathologists-based classifications on predicting baseline and long-term renal function. CONCLUSION: Our CNN-based model is promising in assisting the identification and pathologic classification of glomerular lesions in DN patients.

Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients.

BACKGROUND: The analytical renal pathology system (ARPS) based on convolutional neural networks has been used successfully in native IgA nephropathy (IgAN) patients. Considering the similarity of pathologic features, we aim to evaluate the performance of the ARPS in allograft IgAN patients and broaden its implementation. METHODS: Biopsy-proven allograft IgAN patients from two different centers were enrolled for internal and external validation. We implemented the ARPS to identify glomerular lesions and intrinsic glomerular cells, and then evaluated its performance. Consistency between the ARPS and pathologists was assessed using intraclass correlation coefficients. The association of digital pathological features with clinical and pathological data was measured. Kaplan-Meier survival curve and cox proportional hazards model were applied to investigate prognosis prediction. RESULTS: A total of 56 biopsy-proven allograft IgAN patients from the internal center and 17 biopsy-proven allograft IgAN patients from the external center were enrolled in this study. The ARPS was successfully applied to identify the glomerular lesions (F1-score, 0.696-0.959) and quantify intrinsic glomerular cells (F1-score, 0.888-0.968) in allograft IgAN patients rapidly and precisely. Furthermore, the mesangial hypercellularity score was positively correlated with all mesangial metrics provided by ARPS [Spearman's correlation coefficient (r), 0.439-0.472, and all p values < 0.001]. Besides, a higher allograft survival was noticed among patients in the high-level groups of the maximum and ratio of endothelial cells, as well as the maximum and density of podocytes. CONCLUSION: We propose that the ARPS could be implemented in future clinical practice with outstanding capability.

Biosafe cerium oxide nanozymes protect human pluripotent stem cells and cardiomyocytes from oxidative stress.

BACKGROUND: Cardiovascular diseases (CVDs) have the highest mortality worldwide. Human pluripotent stem cells (hPSCs) and their cardiomyocyte derivatives (hPSC-CMs) offer a valuable resource for disease modeling, pharmacological screening, and regenerative therapy. While most CVDs are linked to significant over-production of reactive oxygen species (ROS), the effects of current antioxidants targeting excessive ROS are limited. Nanotechnology is a powerful tool to develop antioxidants with improved selectivity, solubility, and bioavailability to prevent or treat various diseases related to oxidative stress. Cerium oxide nanozymes (CeONZs) can effectively scavenge excessive ROS by mimicking the activity of endogenous antioxidant enzymes. This study aimed to assess the nanotoxicity of CeONZs and their potential antioxidant benefits in stressed human embryonic stem cells (hESCs) and their derived cardiomyocytes (hESC-CMs). RESULTS: CeONZs demonstrated reliable nanosafety and biocompatibility in hESCs and hESC-CMs within a broad range of concentrations. CeONZs exhibited protective effects on the cell viability of hESCs and hESC-CMs by alleviating excessive ROS-induced oxidative stress. Moreover, CeONZs protected hESC-CMs from doxorubicin (DOX)-induced cardiotoxicity and partially ameliorated the insults from DOX in neonatal rat cardiomyocytes (NRCMs). Furthermore, during hESCs culture, CeONZs were found to reduce ROS, decrease apoptosis, and enhance cell survival without affecting their self-renewal and differentiation potential. CONCLUSIONS: CeONZs displayed good safety and biocompatibility, as well as enhanced the cell viability of hESCs and hESC-CMs by shielding them from oxidative damage. These promising results suggest that CeONZs may be crucial, as a safe nanoantioxidant, to potentially improve the therapeutic efficacy of CVDs and be incorporated into regenerative medicine.

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data. DESIGN: A single-centre, retrospective cohort study in China. SETTING: A Chinese central tertiary hospital. PARTICIPANTS: The cohort study consisted of 1694 LN patients who had been registered in the Nanjing Glomerulonephritis Registry at the National Clinical Research Center of Kidney Diseases, Jinling Hospital from January 1985 to December 2010. METHODS: We developed a deep learning algorithm to predict LN relapse that consists of 59 features, including demographic, clinical, immunological, pathological and therapeutic characteristics that were collected for baseline analysis. A total of 32 227 data points were collected by the sliding window method and randomly divided into training (80%), validation (10%) and testing sets (10%). We developed a deep learning algorithm-based interpretable multivariable long short-term memory model for LN relapse risk prediction considering censored time-series data based on a cohort of 1694 LN patients. A mixture attention mechanism was deployed to capture variable interactions at different time points for estimating the temporal importance of the variables. Model performance was assessed according to C-index (concordance index). RESULTS: The median follow-up time since remission was 4.1 (IQR, 1.7-6.7) years. The interpretable deep learning model based on dynamic multivariable time-series data achieved the best performance, with a C-index of 0.897, among models using only variables at the point of remission or time-variant variables. The importance of urinary protein, serum albumin and serum C3 showed time dependency in the model, that is, their contributions to the risk prediction increased over time. CONCLUSIONS: Deep learning algorithms can effectively learn through time-series data to develop a predictive model for LN relapse. The model provides accurate predictions of LN relapse for different renal disease stages, which could be used in clinical practice to guide physicians on the management of LN patients.

Novel CAR-T cells targeting TRKB for the treatment of solid cancer.

Chimeric antigen receptor (CAR) T-cell therapy is highly effective for treating blood cancers such as B-cell malignancies, however, its effectiveness as an approach to treat solid tumors remains to be further explored. Here, we focused on the development of CAR-T cell therapies targeting tropomyosin-related kinase receptor B (TRKB), a highly expressed protein that is significantly associated with tumor progression, malignancy, and drug resistance in multiple forms of aggressive solid tumors. To achieve this, we screened brain-derived neurotrophic factor (BDNF) and neurotrophin 4 (NTF4) ligand-based CAR-T cells for their efficiency in targeting the TRKB receptor in the context of solid tumors, particularly hepatocellular carcinoma and pancreatic cancer. We demonstrated that TRKB is overexpressed not only in hepatocellular carcinoma and pancreatic carcinoma cell lines but also in cancer stem-like cells (CSCs). Notably, BDNF-CAR T and NTF4-CAR T cells could not only effectively target and kill TRKB-expressing pan-cancer cell lines in a dose-dependent manner but also effectively kill CSCs. We also performed in vivo studies to show that NTF4-CAR T cells have a better potential to inhibit the tumor growth of hepatocellular carcinoma xenografts in mice, compared with BDNF-CAR T cells. Taken together, our findings suggest that CAR-T targeting TRKB may be a promising approach for developing novel therapies to treat solid cancers.

Boosting Efficient Alkaline Hydrogen Evolution Reaction of CoFe-Layered Double Hydroxides Nanosheets via Co-Coordination Mechanism of W-Doping and Oxygen Defect Engineering.

While surface defects and heteroatom doping exhibit promising potential in augmenting the electrocatalytic hydrogen evolution reaction (HER), their performance remains unable to rival that of the costly Pt-based catalysts. Yet, the concurrent modification of catalysts by integrating both approaches stands as a promising strategy to effectively address the aforementioned limitation. In this work, tungsten dopants are introduced into self-supported CoFe-layered double hydroxides (LDH) on nickel foam using a hydrothermal method, and oxygen vacancies (Ov) are further introduced through calcination. The analysis results demonstrated that tungsten doping reduces the Ov formation energy of CoFeW-LDH. The Ov acted as oxophilic sites, facilitating water adsorption and dissociation, and reducing the barrier for cleaving HO─H bonds from 0.64 to 0.14 eV. Additionally, Ov regulated the electronic structure of CoFeW-LDH to endow optimized hydrogen binding ability on tungsten atoms, thereby accelerating alkaline Volmer and Heyrovsky reaction kinetics. Specifically, the abundance of Ov induced a transition of tungsten from a six-coordinated to highly active four-coordinated structure, which becomes the active site for HER. Consequently, an ultra-low overpotential of 41 mV at 10 mA cm-2 , and a low Tafel slope of 35 mV dec-1 are achieved. These findings offer crucial insights for the design of efficient HER electrocatalysts.

Prediction of treatment response in lupus nephritis using density of tubulointerstitial macrophage infiltration.

Background: Lupus nephritis (LN) is a common disease with diverse clinical and pathological manifestations. A major challenge in the management of LN is the inability to predict its treatment response at an early stage. The objective of this study was to determine whether the density of tubulointerstitial macrophage infiltration can be used to predict treatment response in LN and whether its addition to clinicopathological data at the time of biopsy would improve risk prediction. Methods: In this retrospective cohort study, 430 patients with LN in our hospital from January 2010 to December 2017 were included. We used immunohistochemistry to show macrophage and lymphocyte infiltration in their biopsy specimens, followed by quantification of the infiltration density. The outcome was the treatment response, defined as complete or partial remission at 12 months of immunosuppression. Results: The infiltration of CD68+ macrophages in the interstitium increased in patients with LN. High levels of CD68+ macrophage infiltration in the interstitium were associated with a low probability of treatment response in the adjusted analysis, and verse vice. The density of CD68+ macrophage infiltration in the interstitium alone predicted the response to immunosuppression (area under the curve [AUC], 0.70; 95% CI, 0.63 to 0.76). The addition of CD68+cells/interstitial field to the pathological and clinical data at biopsy in the prediction model resulted in an increased AUC of 0.78 (95% CI, 0.73 to 0.84). Conclusion: The density of tubulointerstitial macrophage infiltration is an independent predictor for treatment response in LN. Adding tubulointerstitial macrophage infiltration density to clinicopathological data at the time of biopsy significantly improves risk prediction of treatment response in LN patients.

HAND factors regulate cardiac lineage commitment and differentiation from human pluripotent stem cells.

BACKGROUND: Transcription factors HAND1 and HAND2 (HAND1/2) play significant roles in cardiac organogenesis. Abnormal expression and deficiency of HAND1/2 result in severe cardiac defects. However, the function and mechanism of HAND1/2 in regulating human early cardiac lineage commitment and differentiation are still unclear. METHODS: With NKX2.5eGFP H9 human embryonic stem cells (hESCs), we established single and double knockout cell lines for HAND1 and HAND2, respectively, whose cardiomyocyte differentiation efficiency could be monitored by assessing NKX2.5-eGFP+ cells with flow cytometry. The expression of specific markers for heart fields and cardiomyocyte subtypes was examined by quantitative PCR, western blot and immunofluorescence staining. Microelectrode array and whole-cell patch clamp were performed to determine the electrophysiological characteristics of differentiated cardiomyocytes. The transcriptomic changes of HAND knockout cells were revealed by RNA sequencing. The HAND1/2 target genes were identified and validated experimentally by integrating with HAND1/2 chromatin immunoprecipitation sequencing data. RESULTS: Either HAND1 or HAND2 knockout did not affect the cardiomyocyte differentiation kinetics, whereas depletion of HAND1/2 resulted in delayed differentiation onset. HAND1 knockout biased cardiac mesoderm toward second heart field progenitors at the expense of first heart field progenitors, leading to increased expression of atrial and outflow tract cardiomyocyte markers, which was further confirmed by the appearance of atrial-like action potentials. By contrast, HAND2 knockout cardiomyocytes had reduced expression of atrial cardiomyocyte markers and displayed ventricular-like action potentials. HAND1/2-deficient hESCs were more inclined to second heart field lineage and its derived cardiomyocytes with atrial-like action potentials than HAND1 single knockout during differentiation. Further mechanistic investigations suggested TBX5 as one of the downstream targets of HAND1/2, whose overexpression partially restored the abnormal cardiomyocyte differentiation in HAND1/2-deficient hESCs. CONCLUSIONS: HAND1/2 have specific and redundant roles in cardiac lineage commitment and differentiation. These findings not only reveal the essential function of HAND1/2 in cardiac organogenesis, but also provide important information on the pathogenesis of HAND1/2 deficiency-related congenital heart diseases, which could potentially lead to new therapeutic strategies.

Cell-Surface GRP78-Targeted Chimeric Antigen Receptor T Cells Eliminate Lung Cancer Tumor Xenografts.

Lung cancer is one of the most common and intractable malignancies. It is associated with low survival rates despite existing treatments, indicating that new and more effective therapies are urgently needed such as the chimeric antigen receptor-T (CAR-T) cell immunotherapy. The cell-surface glucose-regulated protein 78 (csGRP78) is expressed in various hematological malignancies and solid tumor cells including lung cancer in response to cancer-related endoplasmic reticulum stress, while GRP78 is restricted to inside the normal cells. Here, we detected the prominent expression of csGRP78 in both lung cancer cell lines, A549 and H1299, as well as cancer stemlike cells derived from A549 by immunofluorescence. Next, a csGRP78-targeted CAR was constructed, and the transduced CAR-T cells were tested for their potency to kill the two lung cancer cell lines and derived stemlike cells, which was correlated with specific interferon γ release in vitro. Finally, we found that csGRP78 CAR-T cells also efficiently killed both lung cancer cells and cancer stemlike cells, resulting into the elimination of tumor xenografts in vivo, neither with any evidence of relapse after 63 days of tumor clearance nor any detrimental impact on other body organs we examined. Our study reveals the capacity of csGRP78 as a therapeutic target and offers valuable insight into the development of csGRP78 CAR-T cells as potential therapy for lung cancer.

Deficiency of Transcription Factor Sp1 Contributes to Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disorder. However, the pathogenesis of HCM, especially its nongenetic mechanisms, remains largely unclear. Transcription factors are known to be involved in various biological processes including cell growth. We hypothesized that SP1 (specificity protein 1), the first purified TF in mammals, plays a role in the cardiomyocyte growth and cardiac hypertrophy of HCM. METHODS: Cardiac-specific conditional knockout of Sp1 mice were constructed to investigate the role of SP1 in the heart. The echocardiography, histochemical experiment, and transmission electron microscope were performed to analyze the cardiac phenotypes of cardiac-specific conditional knockout of Sp1 mice. RNA sequencing, chromatin immunoprecipitation sequencing, and adeno-associated virus experiments in vivo were performed to explore the downstream molecules of SP1. To examine the therapeutic effect of SP1 on HCM, an SP1 overexpression vector was constructed and injected into the mutant allele of Myh6 R404Q/+ (Myh6 c. 1211C>T) HCM mice. The human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from a patient with HCM were used to detect the potential therapeutic effects of SP1 in human HCM. RESULTS: The cardiac-specific conditional knockout of Sp1 mice developed a typical HCM phenotype, displaying overt myocardial hypertrophy, interstitial fibrosis, and disordered myofilament. In addition, Sp1 knockdown dramatically increased the cell area of hiPSC-CMs and caused intracellular myofibrillar disorganization, which was similar to the hypertrophic cardiomyocytes of HCM. Mechanistically, Tuft1 was identified as the key target gene of SP1. The hypertrophic phenotypes induced by Sp1 knockdown in both hiPSC-CMs and mice could be rescued by TUFT1 (tuftelin 1) overexpression. Furthermore, SP1 overexpression suppressed the development of HCM in the mutant allele of Myh6 R404Q/+ mice and also reversed the hypertrophic phenotype of HCM hiPSC-CMs. CONCLUSIONS: Our study demonstrates that SP1 deficiency leads to HCM. SP1 overexpression exhibits significant therapeutic effects on both HCM mice and HCM hiPSC-CMs, suggesting that SP1 could be a potential intervention target for HCM.

Re-evaluating the Contribution of a Fe-Based Current Collector to Bioelectrochemical Methanogenesis: Role and Mechanisms.

The metal-based current collector has been adopted as an essential component of cathodes for electron delivery in microbial electrosynthesis (MES) cells, while the effect of its corrosion on biofilm development and electromethanogenesis activity was overlooked. In this study, the corrosion of the Fe-based current collector was identified to in situ decorate cathode naturally which substantially boosted the performance of CO2 electromethanogenesis in terms of taking over two-thirds less time starting up MES and increasing the CH4 production rate by 3.5 times. Despite the low concentration of Fe (0.13 at%), the electrochemical analysis indicated that it was possible for these Fe deposits to act as electron shuttles and catalysts for H2 production to benefit methanogenesis. The Fe aggregates weakened the dependence of methanogens on electroactive bacteria (EABs) to conduct methanogenesis via interspecies electron transfer as the proportion of EABs on Bio FeCF (with Fe current collector, where CF is carbon felt) was only 25.5% of that on Bio CF (without Fe current collector). On the contrary, the abundance of genes encoding the proteins to uptake extracellular electrons of methanogens on Bio FeCF was 2.3 times higher than that on Bio CF. The enhanced energy transfer maintained high amounts of methanogens and live microorganisms. This study comprehensively explored the multiple roles of Fe-based current collectors in enhancing CO2 electromethanogenesis.

Energy effective utilization of circulating fluidized bed fly ash to prepare silicon-aluminum composite aerogel and gypsum.

To reduce the cost of Si-Al aerogels preparation, circulating fluidized bed fly ash (CFA) was developed to be as the alternative to synthetic precursors. High energy consumption of alkali-melting and secondary wastes production were the major challenges. Here, a technique characterized by effective energy consumption and non-secondary waste was developed to convert CFA into Si-Al aerogel. The process consists two stages, preparation of Si-Al sol by sintering of CFA and Na2CO3 followed by sulfuric acid leaching, and synthesis of Si-Al aerogel by so-gel with trimethyl chlorosilane modification and ambient pressure drying. The optimization results of proportion and sintering temperature showed that the optimal temperature of sintering of Na2CO3 and CFA with the mass ratio of 0.7 was 750 °C, 100 °C lower than that of most other waste aluminosilicate materials. CaSO4·0.5H2O which meet building gypsum requirement was obtained by specifying the drying temperature of acid-leached residue at 126 °C for 2 h. The modification procedure was explored to obtain Si-Al aerogel with a large specific surface area of 857 m2/g and hydrophobic angle of 139.3°. Thermal and mechanical properties tests indicated that the Si-Al aerogels and gypsum produced from CFA exhibited promising thermal insulation and the potential application in construction.

Krüppel-like Factor 15 Suppresses Ferroptosis by Activating an NRF2/GPX4 Signal to Protect against Folic Acid-Induced Acute Kidney Injury.

Acute kidney injury (AKI) is a common and serious disease with high morbidity and mortality, and its pathophysiological mechanisms are not fully understood. Increasing evidence suggests an important role of ferroptosis in AKI. Krüppel-like factor 15 (KLF15) is a transcription factor involved in several metabolic diseases, but its role in AKI and ferroptosis remains unclear. In this study, we explored the potential role of KLF15 using a folic acid-induced AKI model. Our study showed that KLF15 expression was reduced in kidney tissues of AKI mice, and KLF15 knockout exacerbated folic acid-induced ferroptosis and kidney injury. In vitro studies revealed that the ferroptosis inducer erastin significantly suppressed KLF15 expression in human tubular epithelial cells. Notably, the overexpression of KLF15 attenuated ferroptosis, as evidenced by a decrease in the lipid peroxidation marker of malondialdehyde and the upregulation of glutathione peroxidase 4 (GPX4), while KLF15 knockdown with shRNA exerted the opposite effect. Mechanistically, KLF15 stabilized the protein of nuclear factor erythroid 2-related factor 2 (NRF2) and subsequently increased the GPX4 level. Collectively, KLF15 plays an important role in the modulation of ferroptosis in AKI and may be a potential therapeutic target for treating AKI.

Association of regulatory T cells with renal outcomes in patients with proliferative lupus nephritis.

BACKGROUND: Despite progress in the diagnosis and treatment of proliferative lupus nephritis (PLN), the prognosis remains unfavorable. Previous investigations have suggested that the deficiency of regulatory T cells (Tregs) is involved in the pathogenesis of systemic lupus erythematosus (SLE) and lupus nephritis (LN). But the prognostic value of Tregs in PLN remains controversial. This study aimed to investigate the association of Tregs with renal outcomes in patients with PLN. METHODS: The baseline and follow-up data of patients with biopsy-proven PLN were collected in this study. All patients were divided into two groups according to whether the renal endpoint event occurred. Clinicopathologic features and therapeutic responses were compared between the two groups. Cox regression analyses curve fitting and threshold effect analysis were implemented to investigate the relationship between Tregs level and the long-term renal outcomes. The renal endpoint was defined as end-stage kidney disease (ESKD) or doubling the SCr value. RESULTS: A total of 405 PLN patients were included. After a follow-up of 71.53 (53.13-97.47) months, 42 (10.4%) patients reached the renal endpoint. The Treg cell counts (16/µL) in the renal endpoint group were significantly decreased than that in the non-renal endpoint group (p < 0.001). Univariate and multivariate Cox regression analyses showed that the high level of Tregs was an independent protective factor for the long-term renal prognosis of PLN. Smooth curve fitting of the generalized additive mixed model analysis indicated that the risk of renal endpoint first decreased with Tregs and then slightly increased along with Treg cell levels. The segmented linear model revealed that when Treg cell counts <46/µL, the risk of renal endpoint decreased by 6.8% for every 1 µL increase in Treg levels (p = 0.0029). CONCLUSION: Treg cell counts are closely related to the long-term renal outcomes of patients with PLN, and increasing Treg cell levels may play an important role in improving the prognosis of the kidney, but there may be a turning point (i.e., threshold effect) at the Treg cell counts that leads to directional changes in the renal outcomes.