Discovery of a Highly Potent PROTAC Degrader of p300/CBP Proteins for the Treatment of Enzalutamide-Resistant Prostate Cancer.

Prostate cancer therapies against androgen receptor (AR) eventually develop lethal resistance; thus, exploring new therapeutic approaches is urgent for prostate cancer treatment. Acetyltransferase p300/CBP are key coactivators for AR-mediated transcription and represent promising therapeutic targets to inhibit AR activity in prostate cancer. We describe the design synthesis and evaluation of a new class of p300/CBP PROTAC degraders. We identified an excellent p300/CBP degrader MJP6412, which effectively induced degradation of p300/CBP proteins, downregulated AR target genes, and inhibited cell growth of human prostate cancer cell lines and enzalutamide-resistant cells with IC50 even at nanomolar concentrations. Furthermore, MJP6412 demonstrated significant inhibition of tumor growth in a VCaP xenograft model. Collectively, MJP6412 is a promising lead compound for the treatment of prostate cancer, especially enzalutamide-resistant prostate cancer.

Intracorporeal urinary diversion offers the advantage of delaying postoperative renal function injury in patients undergoing robot-assisted radical cystectomy.

Objective: To analyze changes in renal function and associated risk factors in patients with bladder cancer undergoing robot-assisted radical cystectomy (RARC) with intracorporeal or extracorporeal urinary diversion (ICUD or ECUD). Methods: Clinical-pathological data was extracted from electronic medical records of 266 patients with bladder cancer who underwent RARC at our institution between August 2015 and August 2022. Postoperative renal function was assessed using the estimated glomerular filtration rate (eGFR). Result: Patients were classified into ECUD and ICUD groups based on the surgical approach. Significant differences in eGFR were observed between the two groups at 1, 2, and 3 years postoperatively. Moreover, 112 patients (42.1%) experienced long-term renal function injury. Independent risk factors for long-term renal function injury included the type of surgical approach, ureteroenteric anastomotic strictures, and pathological stage T3 or above. In terms of short-term renal function, 30 cases of acute kidney injury (AKI) were observed, with an incidence rate of 11.3%. No difference in AKI incidence was found between the groups. Conclusions: Postoperative AKI and chronic kidney injury are prevalent complications following RC. This study highlights that pathological stage, ureteroenteric anastomotic strictures, and ECUD significantly impact long-term renal function, but the type of urinary diversion (ileal conduit or orthotopic neobladder) had no effect on renal function, and ICUD was superior in terms of long-term renal injury rate. Therefore, precise preoperative assessment and the selection of appropriate surgical approach are crucial for preserving renal function in patients with bladder cancer.

Evaluation of novel synthetic peptides of avian hepatitis E virus ORF2 as vaccine candidate in chickens.

Avian hepatitis E virus (HEV) has resulted in significant economic losses in the poultry industry. There is currently no commercial vaccination available to prevent avian HEV infection. Previously, a novel epitope (601TFPS604) was discovered in the ORF2 protein of avian HEV. In this study, peptides were synthesized and assessed for their ability to provide immunoprotecting against avian HEV infection in poultry. Twenty-five Hy-Line Variety Brown laying hens were randomly divided into five groups; groups 1 to 3 respectively immunized with RLLDRLSRTFPS, PETRRLLDRLSR (irrelevant peptide control), or truncated avian HEV ORF2 protein (aa 339-606), while group 4 (negative control) was mock-immunized with PBS and group 5 (normal control) was not immunized or challenged. After the challenge, all hens in groups 2 and 4 showed seroconversion, fecal virus shedding, viremia, alanine aminotransferase (ALT) level increasing, liver lesions and HEV antigen in the liver. There were no pathogenic effects in other groups. Collectively, all of these findings showed that hens were completely protected against avian HEV infection when they were immunized with the peptide containing TFPS of the avian HEV ORF2 protein.

Trans-rectovesical pouch urethral-sparing robotic-assisted simple prostatectomy: A case series.

Objective: To detail a novel technique of robotic-assisted simple prostatectomy that makes handling the gland protruding into the bladder neck easier and can preserve the urethra and retain ejaculation function as much as possible. Patients and methods: This is a prospective case series. Clinical data of 17 male patients who had large volume (>80 mL) benign prostatic hyperplasia (BPH) were enrolled to undergo trans-rectovesical pouch urethral-sparing robotic-assisted simple prostatectomy (usRASP). We adopted the approach through the space between the bladder neck and seminal vesicle to perform a usRASP that can avoid the detrusor skirt and fibrous matrix area of the retropubic prostate. Between the transitional zone and the peripheral zone of the large prostate, the hyperplastic prostatic gland tissue can be enucleated under direct vision while preserving the prostatic urethra and retaining the ejaculatory duct and bladder neck intact. All preoperative, perioperative and postoperative clinical data were collected, and descriptive analysis was performed. Results: The median intravesical prostatic protrusion was 19.3 mm (8.5-32.2). The median operative time was 100 min (75-140), and the median estimated blood loss was 100 mL (10-500). The median time to catheter removal was 7 days (5-7), with a median postoperative hospital stay of 2 days (2-4). After at least 6-month follow-up, the median maximum urine flow rate and postvoid residual volume were 40.1 mL/s (12.7-52.4) and 15 mL (5-23), respectively; the median International Prostate Symptom Score and Quality of Life score were 0 (0-6.3) and 1 (0-3), respectively; and the median total prostate-specific antigen was 0.84 ng/mL (0.15-1.01). All patients successfully underwent usRASP. Fifty-eight percent of patients with normal ejaculation function before surgery can still retain normal ejaculation function. Conclusion: We described a new approach to performing usRASP. This new method remarkably improved the voiding function, maintained antegrade ejaculation and did not increase the post-operative complications.

Decorating Cage-Shaped Cavities with Carboxyl Groups on Two-Dimensional MOF Nanosheet for Trace Uranium(VI) Trapping.

The efficient and complete extraction of uranium from aqueous solutions is crucial for safeguarding human health from potential radiotoxicity and chemotoxicity. Herein, an ultrathin 2D metal-organic framework (MOF) nanosheet with cavity structures was elaborately constructed, based on a calix[4]arene ligand. The large molecular skeleton and cup-shaped feature of the calix[4]arene enabled the as-prepared MOFs with large layer separations, which can be readily delaminated into ultrathin single-layer (∼1.25 nm) nanosheets. The incorporation of permanent cavity structures to the MOF nanosheets can fully utilize their structural features of readily accessible adsorption groups and exposed surface area in uranium removal, reaching ultrafast adsorption kinetics; the functionalized cavity structure endowed MOF nanosheets with the ability to preconcentrate and extract uranium from aqueous solutions with ultrahigh efficiencies, even at extremely low concentrations. As a result, relatively high removal ratios (>95%) can be achieved for uranium within 5 min, even in the ultralow concentration range of 75-250 ppb, and the residual uranium was reduced to below 4.9 ppb. The MOF nanosheets also exhibited extremely high anti-interference ability, which could efficiently remove the low-level uranium (∼150 ppb) from various real samples. The characterizations and density functional theory calculations demonstrated that the synergistic effects of multiple interactions between the carboxylate groups and cage-like cavities with uranyl ions can be responsible for the efficient and selective uranium extraction.

Histamine H4 receptor and TRPV1 mediate itch induced by cadaverine, a metabolite of the microbiome.

Cadaverine is an endogenous metabolite produced by the gut microbiome with various activity in physiological and pathological conditions. However, whether cadaverine regulates pain or itch remains unclear. In this study, we first found that cadaverine may bind to histamine 4 receptor (H4R) with higher docking energy score using molecular docking simulations, suggesting cadaverine may act as an endogenous ligand for H4R. We subsequently found intradermal injection of cadaverine into the nape or cheek of mice induces a dose-dependent scratching response in mice, which was suppressed by a selective H4R antagonist JNJ-7777120, transient receptor potential vanilloid 1 (TRPV1) antagonist capsazepine and PLC inhibitor U73122, but not H1R antagonist or TRPA1 antagonist or TRPV4 antagonist. Consistently, cadaverine-induced itch was abolished in Trpv1-/- but not Trpa1-/- mice. Pharmacological analysis indicated that mast cells and opioid receptors were also involved in cadaverine-induced itch in mice. scRNA-Seq data analysis showed that H4R and TRPV1 are mainly co-expressed on NP2, NP3 and PEP1 DRG neurons. Calcium imaging analysis showed that cadaverine perfusion enhanced calcium influx in the dissociated dorsal root ganglion (DRG) neurons, which was suppressed by JNJ-7777120 and capsazepine, as well as in the DRG neurons from Trpv1-/- mice. Patch-clamp recordings found that cadaverine perfusion significantly increased the excitability of small diameter DRG neurons, and JNJ-7777120 abolished this effect, indicating involvement of H4R. Together, these results provide evidences that cadaverine is a novel endogenous pruritogens, which activates H4R/TRPV1 signaling pathways in the primary sensory neurons.

Transfer learning across different chemical domains: virtual screening of organic materials with deep learning models pretrained on small molecule and chemical reaction data.

Machine learning is becoming a preferred method for the virtual screening of organic materials due to its cost-effectiveness over traditional computationally demanding techniques. However, the scarcity of labeled data for organic materials poses a significant challenge for training advanced machine learning models. This study showcases the potential of utilizing databases of drug-like small molecules and chemical reactions to pretrain the BERT model, enhancing its performance in the virtual screening of organic materials. By fine-tuning the BERT models with data from five virtual screening tasks, the version pretrained with the USPTO-SMILES dataset achieved R2 scores exceeding 0.94 for three tasks and over 0.81 for two others. This performance surpasses that of models pretrained on the small molecule or organic materials databases and outperforms three traditional machine learning models trained directly on virtual screening data. The success of the USPTO-SMILES pretrained BERT model can be attributed to the diverse array of organic building blocks in the USPTO database, offering a broader exploration of the chemical space. The study further suggests that accessing a reaction database with a wider range of reactions than the USPTO could further enhance model performance. Overall, this research validates the feasibility of applying transfer learning across different chemical domains for the efficient virtual screening of organic materials.Scientific contributionThis study verifies the feasibility of applying transfer learning to large language models in different chemical fields to help organic materials perform virtual screening. Through the comparison of transfer learning from different chemical fields to a variety of organic material molecules, the high precision virtual screening of organic materials is realized.

Pathogenicity of two different genotypes avian hepatitis E strains in laying hens and silkie fowl.

To determine the pathogenicity of two different genotypes of avian hepatitis E strains in two species of birds, a total of thirty healthy 12-week-old birds were used. After inoculation, fecal virus shedding, viremia, seroconversion, serum alanine aminotransferase (ALT) increases and liver lesions were evaluated. The results revealed that CHN-GS-aHEV and CaHEV could both infect Hy-Line hens and silkie fowls, respectively. Compared to the original avian HEV strain, the cross-infected virus exhibited a delay of 2 weeks and 1 week in emerged seroconversion, viremia, fecal virus shedding, and increased ALT level, and also showed mild liver lesions. These findings suggested that CHN-GS-aHEV may have circulated in chickens. Overall, these two different genotypes of avian HEV showed some variant pathogenicity in different bird species. This study provides valuable data for further analysis of the epidemic conditions of two avian HEVs in Hy-Line hens and silkie fowls.

Construction of sub micro-nano-structured silicon based anode for lithium-ion batteries.

The significant volume change experienced by silicon (Si) anodes during lithiation/delithiation cycles often triggers mechanical-electrochemical failures, undermining their utility in high-energy-density lithium-ion batteries (LIBs). Herein, we propose a sub micro-nano-structured Si based material to address the persistent challenge of mechanic-electrochemical coupling issue during cycling. The mesoporous Si-based composite submicrospheres (M-Si/SiO2/CS) with a high Si/SiO2content of 84.6 wt.% is prepared by magnesiothermic reduction of mesoporous SiO2submicrospheres followed by carbon coating process. M-Si/SiO2/CS anode can maintain a high specific capacity of 740 mAh g-1at 0.5 A g-1after 100 cycles with a lower electrode thickness swelling rate of 63%, and exhibits a good long-term cycling stability of 570 mAh g-1at 1 A g-1after 250 cycles. This remarkable Li-storage performance can be attributed to the synergistic effects of the hierarchical structure and SiO2frameworks. The spherical structure mitigates stress/strain caused by the lithiation/delithiation, while the internal mesopores provide buffer space for Si expansion and obviously shorten the diffusion path for electrolyte/ions. Additionally, the amorphous SiO2matrix not only servers as support for structure stability, but also facilitates the rapid formation of a stable solid electrolyte interphase layer. This unique architecture offers a potential model for designing high-performance Si-based anode for LIBs.

LncRNA-LncDACH1 mediated phenotypic switching of smooth muscle cells during neointimal hyperplasia in male arteriovenous fistulas.

Arteriovenous fistulas (AVFs) are the most common vascular access points for hemodialysis (HD), but they have a high incidence of postoperative dysfunction, mainly due to excessive neointimal hyperplasia (NIH). Our previous studies have revealed a highly conserved LncRNA-LncDACH1 as an important regulator of cardiomyocyte and fibroblast proliferation. Herein, we find that LncDACH1 regulates NIH in AVF in male mice with conditional knockout of smooth muscle cell-specific LncDACH1 and in male mice model of AVF with LncDACH1 overexpression by adeno-associated virus. Mechanistically, silence of LncDACH1 activates p-AKT through promoting the expression of heat shock protein 90 (HSP90) and serine/arginine-rich splicing factor protein kinase 1 (SRPK1). Moreover, LncDACH1 is transcriptionally activated by transcription factor KLF9 that binds directly to the promoter region of the LncDACH1 gene. In this work, during AVF NIH, LncDACH1 is downregulated by KLF9 and promotes NIH through the HSP90/ SRPK1/ AKT signaling axis.

Development and performance assessment of novel machine learning models for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage patients: external validation in MIMIC-IV.

Background: Postoperative pneumonia (POP) is one of the primary complications after aneurysmal subarachnoid hemorrhage (aSAH) and is associated with postoperative mortality, extended hospital stay, and increased medical fee. Early identification of pneumonia and more aggressive treatment can improve patient outcomes. We aimed to develop a model to predict POP in aSAH patients using machine learning (ML) methods. Methods: This internal cohort study included 706 patients with aSAH undergoing intracranial aneurysm embolization or aneurysm clipping. The cohort was randomly split into a train set (80%) and a testing set (20%). Perioperative information was collected from participants to establish 6 machine learning models for predicting POP after surgical treatment. The area under the receiver operating characteristic curve (AUC), precision-recall curve were used to assess the accuracy, discriminative power, and clinical validity of the predictions. The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Results: In this study, 15.01% of patients in the training set and 12.06% in the testing set with POP after underwent surgery. Multivariate logistic regression analysis showed that mechanical ventilation time (MVT), Glasgow Coma Scale (GCS), Smoking history, albumin level, neutrophil-to-albumin Ratio (NAR), c-reactive protein (CRP)-to-albumin ratio (CAR) were independent predictors of POP. The logistic regression (LR) model presented significantly better predictive performance (AUC: 0.91) than other models and also performed well in the external validation set (AUC: 0.89). Conclusion: A machine learning model for predicting POP in aSAH patients was successfully developed using a machine learning algorithm based on six perioperative variables, which could guide high-risk POP patients to take appropriate preventive measures.

Characterization of OsPIN2 Mutants Reveal Novel Roles for Reactive Oxygen Species in Modulating Not Only Root Gravitropism but Also Hypoxia Tolerance in Rice Seedlings.

Tolerance to submergence-induced hypoxia is an important agronomic trait especially for crops in lowland and flooding-affected areas. Although rice (Oryza sativa) is considered a flood-tolerant crop, only limited cultivars display strong tolerance to prolonged submergence and/or hypoxic stress. Therefore, characterization of hypoxic resistant genes and/or germplasms have important theoretical and practical significance for rice breeding and sustained improvements. Previous investigations have demonstrated that loss-of-function of OsPIN2, a gene encoding an auxin efflux transporter, results in the loss of root gravitropism due to disrupted auxin transport in the root tip. In this study, we revealed a novel connection between OsPIN2 and reactive oxygen species (ROS) in modulating root gravitropism and hypoxia tolerance in rice. It is shown that the OsPIN2 mutant had decreased accumulation of ROS in root tip, due to the downregulation of glycolate oxidase encoding gene OsGOX6, one of the main H2O2 sources. The morphological defects of root including waved rooting and agravitropism in OsPIN2 mutant may be rescued partly by exogenous application of H2O2. The OsPIN2 mutant exhibited increased resistance to ROS toxicity in roots due to treatment with H2O2. Furthermore, it is shown that the OsPIN2 mutant had increased tolerance to hypoxic stress accompanied by lower ROS accumulation in roots, because the hypoxia stress led to over production of ROS in the roots of the wild type but not in that of OsPIN2 mutant. Accordingly, the anoxic resistance-related gene SUB1B showed differential expression in the root of the WT and OsPIN2 mutant in response to hypoxic conditions. Notably, compared with the wild type, the OsPIN2 mutant displayed a different pattern of auxin distribution in the root under hypoxia stress. It was shown that hypoxia stress caused a significant increase in auxin distribution in the root tip of the WT but not in that of the war1 mutant. In summary, these results suggested that OsPIN2 may play a role in regulating ROS accumulation probably via mediating auxin transport and distribution in the root tip, affecting root gravitropism and hypoxic tolerance in rice seedlings. These findings may contribute to the genetic improvement and identification of potential hypoxic tolerant lines in rice.

SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.

The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predicting drug synergy, but high computational cost for training models as well as great diversity and limited size in screening data escalate the difficulty of prediction. To address this challenge, we propose a simple machine learning framework, namely Similarity Network-based Synergy prediction (SNSynergy), for predicting synergistic effects towards new cell lines and new drug combinations by two locally weighted models CLSN and DCSN. This framework only requires a small amount of auxiliary data, like genomics information of cell lines and the molecular fingerprints or targets of drugs. Based on the assumption that similar cell lines and similar drug combinations have similar synergistic effects, CLSN and DCSN predict synergy scores through capturing individual synergy contributions of nearest cell line and drug combination neighbors, respectively. High correlations between predicted and measured synergy scores on two leading cancer cell line pharmacogenomic screening datasets (the O'Neil dataset and the NCI-ALMANAC dataset) demonstrate the effectiveness and robustness of SNSynergy. Many of the identified drug combinations are consistent with previous studies, or have been explored in clinical settings against the specific cancer type, showing that SNSynergy has the potential to supply cost-saving and effective high-throughput screening for prioritizing the most applicable cell lines and the most promising drug combinations.

A Potent SOS1 PROTAC Degrader with Synergistic Efficacy in Combination with KRASG12C Inhibitor.

AMG510, as the first approved inhibitor for KRASG12C mutation, has shown promising efficacy in nonsmall-cell lung cancer and colorectal cancer harboring KRASG12C mutation. However, the moderate response rate and the rapid emergence of acquired resistance limit the therapeutic potential of AMG510, highlighting the need for the development of combination strategies. Here, we observed the suppression of RAS-MAPK signaling induced by AMG510 was prolonged and enhanced by SOS1 knockdown. Thus, we design, synthesize, and characterize a potent and specific SOS1 degrader 23. Compound 23 showed efficient SOS1 degradation in KRAS-driven cancer cells and achieved significant antiproliferative potency. Importantly, the combination of 23 with AMG510 suppressed RAS signaling feedback activation, showing synergistic effects against KRASG12C mutant cells in vitro and in vivo. Our findings demonstrated that KRASG12C inhibition plus SOS1 degradation as a potential therapeutic strategy to improve antitumor response and overcome acquired resistance to KRASG12C inhibitor.

Highly accurate and effective deep neural networks in pathological diagnosis of prostate cancer.

PURPOSE: To established an AI system to make the pathological diagnosis of prostate cancer. METHODS: Prostate histopathological whole mount (WM) sections from patients underwent robot-assisted laparoscopic prostatectomy were prepared. All the prostate WM pathological sections were converted to digital image data and marked with different colors on the basis of the ISUP Gleason grade group. The image was then fed into a segmentation algorithm. We chose modified U-Net as our fundamental network architecture. RESULTS: 172 patients were involved in this study. 896 pieces of prostate WM pathological sections from 160 patients, in which 826 pieces of WM sections from 148 patients were assigned to the training set randomly. After image segmentation there were totally 2,138,895 patches, of which 1,646,535 patches were valid for training. The other WM section was arranged for testing. Based on the whole image testing, AI and pathologists presented the same answers among 21 of 22 pieces of sections. To evaluate the diagnostic results at the pixel level, we anticipated correct cancer or non-cancer diagnose from this AI system. The area under the ROC curve as 96.8%. The value of pixel accuracy of three methods (binary analysis, clinically oriented analysis and analysis for different ISUP Gleason grade) were 96.93%, 95.43% and 93.88%, respectively. The value of frequency weighted IoU were 94.32%, 92.13% and 90.21%, respectively. CONCLUSIONS: This AI system is able to assist pathologists to make a final diagnosis, indicating the great potential and a wide-range of applications of AI in the medical field.

An artificial intelligence platform for automated PFAS subgroup classification: A discovery tool for PFAS screening.

Since structural analyses and toxicity assessments have not been able to keep up with the discovery of unknown per- and polyfluoroalkyl substances (PFAS), there is an urgent need for effective categorization and grouping of PFAS. In this study, we presented PFAS-Atlas, an artificial intelligence-based platform containing a rule-based automatic classification system and a machine learning-based grouping model. Compared with previously developed classification software, the platform's classification system follows the latest Organization for Economic Co-operation and Development (OECD) definition of PFAS and reduces the number of uncategorized PFAS. In addition, the platform incorporates deep unsupervised learning models to visualize the chemical space of PFAS by clustering similar structures and linking related classes. Through real-world use cases, we demonstrate that PFAS-Atlas can rapidly screen for relationships between chemical structure and persistence, bioaccumulation, or toxicity data for PFAS. The platform can also guide the planning of the PFAS testing strategy by showing which PFAS classes urgently require further attention. Ultimately, the release of PFAS-Atlas will benefit both the PFAS research and regulation communities.

Breaking CHIPS-Mediated immune evasion with tripterin to promote neutrophil chemotaxis against MRSA infection.

Neutrophils are the most important innate immune cells in host defense against methicillin-resistant Staphylococcus aureus (MRSA). However, MRSA orchestrates precise and timely expression of a series of virulence factors, especially the chemotaxis inhibitory protein of Staphylococcus aureus (CHIPS), to evade neutrophil-mediated host defenses. Here, we demonstrated that tripterin, a plant-derived bioactive pentacyclic triterpenoid, had a low minimum inhibitory concentration (MIC) of 1.28 µg/mL and displayed excellent anti-MRSA activity in vitro and in vivo. RNA-seq and further knockdown experiments revealed that tripterin could dramatically downregulate the expression of CHIPS by regulating the SaeRS two-component regulatory system, thereby enhancing the chemotactic response of neutrophils. Furthermore, tripterin also displayed a potential inhibitory effect on biofilm components to enhance neutrophil infiltration into the interior of the biofilm. In a mouse bacteremia model, tripterin could still maintain an excellent therapeutic effect that was significantly better than that of the traditional antibiotic vancomycin. Overall, these results suggest that tripterin possesses a superior antibacterial activity via breaking CHIPS-mediated immune evasion to promote neutrophil chemotaxis, thus providing a novel strategy for combating serious pathogenic infections.

The pathogenic role of succinate-SUCNR1: a critical function that induces renal fibrosis via M2 macrophage.

BACKGROUND: Renal fibrosis significantly contributes to the progressive loss of kidney function in chronic kidney disease (CKD), with alternatively activated M2 macrophages playing a crucial role in this progression. The serum succinate level is consistently elevated in individuals with diabetes and obesity, both of which are critical factors contributing to CKD. However, it remains unclear whether elevated succinate levels can mediate M2 polarization of macrophages and contribute to renal interstitial fibrosis. METHODS: Male C57/BL6 mice were administered water supplemented with 4% succinate for 12 weeks to assess its impact on renal interstitial fibrosis. Additionally, the significance of macrophages was confirmed in vivo by using clodronate liposomes to deplete them. Furthermore, we employed RAW 264.7 and NRK-49F cells to investigate the underlying molecular mechanisms. RESULTS: Succinate caused renal interstitial macrophage infiltration, activation of profibrotic M2 phenotype, upregulation of profibrotic factors, and interstitial fibrosis. Treatment of clodronate liposomes markedly depleted macrophages and prevented the succinate-induced increase in profibrotic factors and fibrosis. Mechanically, succinate promoted CTGF transcription via triggering SUCNR1-p-Akt/p-GSK3ß/ß-catenin signaling, which was inhibited by SUCNR1 siRNA. The knockdown of succinate receptor (SUCNR1) or pretreatment of anti-CTGF(connective tissue growth factor) antibody suppressed the stimulating effects of succinate on RAW 264.7 and NRK-49F cells. CONCLUSIONS: The causative effects of succinate on renal interstitial fibrosis were mediated by the activation of profibrotic M2 macrophages. Succinate-SUCNR1 played a role in activating p-Akt/p-GSK3ß/ß-catenin, CTGF expression, and facilitating crosstalk between macrophages and fibroblasts. Our findings suggest a promising strategy to prevent the progression of metabolic CKD by promoting the excretion of succinate in urine and/or using selective antagonists for SUCNR1.

Revolutionizing the structural design and determination of covalent-organic frameworks: principles, methods, and techniques.

Covalent organic frameworks (COFs) represent an important class of crystalline porous materials with designable structures and functions. The interconnected organic monomers, featuring pre-designed symmetries and connectivities, dictate the structures of COFs, endowing them with high thermal and chemical stability, large surface area, and tunable micropores. Furthermore, by utilizing pre-functionalization or post-synthetic functionalization strategies, COFs can acquire multifunctionalities, leading to their versatile applications in gas separation/storage, catalysis, and optoelectronic devices. Our review provides a comprehensive account of the latest advancements in the principles, methods, and techniques for structural design and determination of COFs. These cutting-edge approaches enable the rational design and precise elucidation of COF structures, addressing fundamental physicochemical challenges associated with host-guest interactions, topological transformations, network interpenetration, and defect-mediated catalysis.

Biomimetic nanoplatform with selectively positioned indocyanine green for accurate sentinel lymph node imaging.

The status of draining lymph nodes (LNs) is critical for determining the treatment and prognosis of cancer that spreads through the lymphatic system. Indocyanine green (ICG) fluorescence imaging has been widely used in sentinel LN (SLN) biopsy technology and has shown favorable effects. However, this too has its own limitations, such as fluorescence instability and diffusion imaging. In this study, we developed macrophage cell membrane-camouflaged ICG-loaded biomimetic nanoparticles (M@F127-ICG) for accurate SLN imaging. ICG selectively positioned at the hydrophobic-hydrophilic interfaces of pluronic F127 micelles protected itself from quenching in aqueous solution, thereby maintaining fluorescence stability and improving fluorescence intensity. In addition, to further improve the aggregation in SLN, the micellar surface was coated with a layer of biomimetic macrophage cell membrane to target LN-resident macrophages. In vivo fluorescence imaging demonstrated that M@F127-ICG significantly enhanced the fluorescence signal and improved the imaging efficiency of SLN. Thus, selectively positioning ICG in the biomimetic nanoplatform enhanced the fluorescence intensity and stability, providing a novel tracer for timely and accurate SLN imaging.