Facile Synthesis of Rigid Binuclear Manganese Complexes for Magnetic Resonance Angiography and SLC39A14-Mediated Hepatic Imaging.

Manganese(II)-based contrast agents (MBCAs) are potential candidates for gadolinium-free enhanced magnetic resonance imaging (MRI). In this work, a rigid binuclear MBCA (Mn2-PhDTA2) with a zero-length linker was developed via facile synthetic routes, while the other dimer (Mn2-TPA-PhDTA2) with a longer rigid linker was also synthesized via more complex steps. Although the molecular weight of Mn2-PhDTA2 is lower than that of Mn2-TPA-PhDTA2, their T1 relaxivities are similar, being increased by over 71% compared to the mononuclear Mn-PhDTA. In the presence of serum albumin, the relaxivity of Mn2-PhDTA2 was slightly lower than that of Mn2-TPA-PhDTA2, possibly due to the lower affinity constant. The transmetalation reaction with copper(II) ions confirmed that Mn2-PhDTA2 has an ideal kinetic inertness with a dissociation half-life of approximately 10.4 h under physiological conditions. In the variable-temperature 17O NMR study, both Mn-PhDTA and Mn2-PhDTA2 demonstrated a similar estimated q close to 1, indicating the formation of monohydrated complexes with each manganese(II) ion. In addition, Mn2-PhDTA2 demonstrated a superior contrast enhancement to Mn-PhDTA in in vivo vascular and hepatic MRI and can be rapidly cleared through a dual hepatic and renal excretion pattern. The hepatic uptake mechanism of Mn2-PhDTA2 mediated by SLC39A14 was validated in cellular uptake studies.

Apparent diffusion coefficient and tissue stiffness are associated with different tumor microenvironment features of hepatocellular carcinoma.

OBJECTIVES: To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC). METHODS: Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors. RESULTS: Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = -0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = -0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02). CONCLUSIONS: Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment. CLINICAL RELEVANCE STATEMENT: Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy. KEY POINTS: Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma. Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes. Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment.

Controlling the nutritional status score: a new tool for predicting postoperative mortality in patients with infrarenal abdominal aortic aneurysm treated with endovascular aneurysm repair.

Background: AAA is a fatal condition that commonly occurs during vascular surgery. Nutritional status exerts a significant influence on the prognosis of various pathological conditions Scores from the CONUT screening tool have been shown to predict outcomes of certain malignancies and chronic diseases. However, the ramifications of nutritional status on AAA patients undergoing EVAR have not been elucidated in prior studies. In this study, we aimed to elucidate the correlation between CONUT scores and postoperative prognostic outcomes in patients with AAA undergoing EVAR. Methods: This was a retrospective review of 177 AAA patients treated with EVAR from June 2018 to November 2019 in a single center. Patient characteristics, CONUT scores, and postoperative status were collected. These patients were stratified into groups A and B according to CONUT scores. Subsequently, a comparative analysis of the baseline characteristics between the two cohorts was conducted. Cox proportional hazards and logistic regression analyses were employed to identify the autonomous predictors of mid-term mortality and complications, respectively. Results: Compared with group A, patients in group B had higher midterm mortality (p < 0.001). Univariate analysis showed that CONUT scores; respiratory diseases; stent types; preoperative Hb, CRP, PT, and Fb levels were risk factors for death. Multivariate analysis confirmed that CONUT score [HR, 1.276; 95% CI, 1.029-1.584; p = 0.027] was an independent risk factor for mortality. Logistic regression analysis showed that prior arterial disease, smoking, and D-dimer levels were risk factors, although multivariate analysis showed smoking (OR, 3.492; 95% CI, 1.426-8.553; p = 0.006) was an independent risk factor. Kaplan-Meier curves showed that patients in group B had shorter mid-term survival than those in group A (log-rank p < 0.001). Conclusion: Malnutrition was strongly associated with mid-term mortality in patients with infrarenal AAA treated with EVAR.

Porphyrin-Based Self-Assembled Nanoparticles for PET/MR Imaging of Sentinel Lymph Node Metastasis.

Diagnosing of lymph node metastasis is challenging sometimes, and multimodal imaging offers a promising method to improve the accuracy. This work developed porphyrin-based nanoparticles (68Ga-F127-TAPP/TCPP(Mn) NPs) as PET/MR dual-modal probes for lymph node metastasis imaging by a simple self-assembly method. Compared with F127-TCPP(Mn) NPs, F127-TAPP/TCPP(Mn) NPs synthesized by amino-porphyrins (TAPP) doping can not only construct PET/MR bimodal probes but also improve the T1 relaxivity (up to 456%). Moreover, T1 relaxivity can be adjusted by altering the molar ratio of TAPP/TCPP(Mn) and the concentration of F127. However, a similar increase in T1 relaxivity was not observed in the F127-TCPP/TCPP(Mn) NPs, which were synthesized using carboxy-porphyrins (TCPP) doping. In a breast cancer lymph node metastasis mice model, subcutaneous injection of 68Ga-F127-TAPP/TCPP(Mn) NPs through the hind foot pad, the normal lymph nodes and metastatic lymph nodes were successfully distinguished based on the difference of PET standard uptake values and MR signal intensities. Furthermore, the dark brown F127-TAPP/TCPP(Mn) NPs demonstrated the potential for staining and mapping lymph nodes. This study provides valuable insights into developing and applying PET/MR probes for lymph node metastasis imaging.

Allosteric Regulation and Inhibition of Coronavirus 3CLpro Revealed by HDX-MS.

Coronavirus (CoV) infections have caused contagious and fatal respiratory diseases in humans worldwide. CoV 3-chymotrypsin-like proteases (3CLpro or Mpro) play an important role in viral maturation, and maintenance of their dimeric conformation is crucial for viral activity. Therefore, allosterically regulated dimerization of 3CLpro can be employed as a drug development target. Here, we investigated the allosteric regulatory mechanism of 3CLpro dimerization by using hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS) technology. We found that the FLAG tag directly coupled to the N-finger of 3CLpro significantly increased HDX kinetics at the dimer interface, and 3CLpro transformed from a dimer to a monomer. The 3CLpro mutants of SARS-CoV-2, which are monomeric, also exhibited increased deuterium exchange. Binding of the allosteric inhibitor Gastrodenol to most betacoronavirus 3CLpros led to increased allosteric deuterium exchange, resulting in the monomeric conformation of the CoV 3CLpro upon binding. Molecular dynamics (MD) simulation analysis further indicated the molecular mechanism of action of Gastrodenol on CoV 3CLpro: binding of Gastrodenol to SARS-CoV-2 3CLpro destroyed the hydrogen bond in the dimer interface. These results suggest that Gastrodenol may be a potential broad-spectrum anti-betacoronavirus drug.

MRI radiomics based on deep learning automated segmentation to predict early recurrence of hepatocellular carcinoma.

OBJECTIVES: To investigate the utility of deep learning (DL) automated segmentation-based MRI radiomic features and clinical-radiological characteristics in predicting early recurrence after curative resection of single hepatocellular carcinoma (HCC). METHODS: This single-center, retrospective study included consecutive patients with surgically proven HCC who underwent contrast-enhanced MRI before curative hepatectomy from December 2009 to December 2021. Using 3D U-net-based DL algorithms, automated segmentation of the liver and HCC was performed on six MRI sequences. Radiomic features were extracted from the tumor, tumor border extensions (5 mm, 10 mm, and 20 mm), and the liver. A hybrid model incorporating the optimal radiomic signature and preoperative clinical-radiological characteristics was constructed via Cox regression analyses for early recurrence. Model discrimination was characterized with C-index and time-dependent area under the receiver operating curve (tdAUC) and compared with the widely-adopted BCLC and CNLC staging systems. RESULTS: Four hundred and thirty-four patients (median age, 52.0 years; 376 men) were included. Among all radiomic signatures, HCC with 5 mm tumor border extension and liver showed the optimal predictive performance (training set C-index, 0.696). By incorporating this radiomic signature, rim arterial phase hyperenhancement (APHE), and incomplete tumor "capsule," a hybrid model demonstrated a validation set C-index of 0.706 and superior 2-year tdAUC (0.743) than both the BCLC (0.550; p < 0.001) and CNLC (0.635; p = 0.032) systems. This model stratified patients into two prognostically distinct risk strata (both datasets p < 0.001). CONCLUSION: A preoperative imaging model incorporating the DL automated segmentation-based radiomic signature with rim APHE and incomplete tumor "capsule" accurately predicted early postsurgical recurrence of a single HCC. CRITICAL RELEVANCE STATEMENT: The DL automated segmentation-based MRI radiomic model with rim APHE and incomplete tumor "capsule" hold the potential to facilitate individualized risk estimation of postsurgical early recurrence in a single HCC. KEY POINTS: A hybrid model integrating MRI radiomic signature was constructed for early recurrence prediction of HCC. The hybrid model demonstrated superior 2-year AUC than the BCLC and CNLC systems. The model categorized the low-risk HCC group carried longer RFS.

A Frog Skin-Derived Peptide Targeting SCD1 Exerts Radioprotective Effects Against Skin Injury by Inhibiting STING-Mediated Inflammation.

The extensive application of nuclear technology has increased the potential of uncontrolled radiation exposure to the public. Since skin is the largest organ, radiation-induced skin injury remains a serious medical concern. Organisms evolutionally develop distinct strategies to protect against environment insults and the related research may bring novel insights into therapeutics development. Here, 26 increased peptides are identified in skin tissues of frogs (Pelophylax nigromaculatus) exposed to electron beams, among which four promoted the wound healing of irradiated skin in rats. Specifically, radiation-induced frog skin peptide-2 (RIFSP-2), from histone proteolysis exerted membrane permeability property, maintained cellular homeostasis, and reduced pyroptosis of irradiated cells with decreased TBK1 phosphorylation. Subsequently, stearyl-CoA desaturase 1 (SCD1) is identified, a critical enzyme in biogenesis of monounsaturated fatty acids (MUFAs) as a direct target of RIFSP-2 based on streptavidin-biotin system. The lipidomic analysis further assured the restrain of MUFAs biogenesis by RIFSP-2 following radiation. Moreover, the decreased MUFA limited radiation-induced and STING-mediated inflammation response. In addition, genetic depletion or pharmacological inhibition of STING counteracted the decreased pyroptosis by RIFSP-2 and retarded tissue repair process. Altogether, RIFSP-2 restrains radiation-induced activation of SCD1-MUFA-STING axis. Thus, the stress-induced amphibian peptides can be a bountiful source of novel radiation mitigators.

Connexin 43 Prevents Radiation-Induced Intestinal Damage via the Ca2+-Dependent PI3K/Akt Signaling Pathway.

Radiation-induced intestinal damage (RIID) is a common side effect of radiotherapy in patients with abdominopelvic malignancies. Gap junctions are special structures consisting of connexins (Cxs). This study aimed to investigate the expression and role of connexins in RIID and underlying mechanism. In this study, a calcein-AM fluorescence probe was used to detect changes in gap junctional intercellular communication in intestinal epithelial IEC-6 cells. Our results show that gap junctional intercellular communication of IEC-6 cells was reduced at 6, 12, 24, and 48 h after irradiation, with the most pronounced effect at 24 h. Western blotting and immunofluorescence results showed that the expression of Cx43, but not other connexins, was reduced in irradiated intestinal epithelial cells. Silencing of Cx43 reduced gap junctional intercellular communication between irradiated intestinal epithelial cells with increased ROS and intracellular Ca2+ levels. Furthermore, knockdown of Cx43 reduced the number of clonal clusters, decreased cell proliferation with increased cytotoxicity and apoptosis. Western blotting results showed that silencing of Cx43 resulted in changed γ-H2AX and PI3K/AKT pathway proteins in irradiated intestinal epithelial cells. Administration of the PI3K/AKT pathway inhibitor LY294002 inhibited the radioprotective effects in Cx43-overexpressing intestinal epithelial cells. Our study demonstrated that Cx43 expression is decreased by ionizing radiation, which facilitates the radioprotection of intestinal epithelial cells.

Dynamic genomic changes in methotrexate-resistant human cancer cell lines beyond DHFR amplification suggest potential new targets for preventing drug resistance.

BACKGROUND: Although DHFR gene amplification has long been known as a major mechanism for methotrexate (MTX) resistance in cancer, the early changes and detailed development of the resistance are not yet fully understood. METHODS: We performed genomic, transcriptional and proteomic analyses of human colon cancer cells with sequentially increasing levels of MTX-resistance. RESULTS: The genomic amplification evolved in three phases (pre-amplification, homogenously staining region (HSR) and extrachromosomal DNA (ecDNA)). We confirm that genomic amplification and increased expression of DHFR, with formation of HSRs and especially ecDNAs, is the major driver of resistance. However, DHFR did not play a detectable role in the early phase. In the late phase (ecDNA), increase in FAM151B protein level may also have an important role by decreasing sensitivity to MTX. In addition, although MSH3 and ZFYVE16 may be subject to different posttranscriptional regulations and therefore protein expressions are decreased in ecDNA stages compared to HSR stages, they still play important roles in MTX resistance. CONCLUSION: The study provides a detailed evolutionary trajectory of MTX-resistance and identifies new targets, especially ecDNAs, which could help to prevent drug resistance. It also presents a proof-of-principal approach which could be applied to other cancer drug resistance studies.

Generation of a human iPSC line from a Parkinson's disease patient with a novel CHCHD2 mutation (p.R145Q).

Mutations in CHCHD2 have been reported to be associated with familial Parkinson's disease (PD). We generated a human induced pluripotent stem cell (hiPSC) line by reprogramming dermal fibroblasts from a PD patient harboring a novel CHCHD2 mutation (c.434G > A, p.R145Q). This line exhibited human embryonic stem cell (hESC)-like clonal morphology, expression of undifferentiated stem cell markers, a normal karyotype and trilineage differentiation capacity and thus the potential to serve as a model for further investigating the underlying molecular mechanisms of CHCHD2 function in PD.

Corrigendum: Radiomic machine learning and external validation based on 3.0T mpMRI for prediction of intraductal carcinoma of prostate with different proportion.

[This corrects the article DOI: 10.3389/fonc.2022.934291.].

Comparative investigation of neoadjuvant immunotherapy versus adjuvant immunotherapy in perioperative patients with cancer: a global-scale, cross-sectional, large-sample informatics study.

BACKGROUND: Neoadjuvant and adjuvant immunotherapies for cancer have evolved through a series of remarkable and critical research advances; however, addressing their similarities and differences is imperative in clinical practice. Therefore, this study aimed to examine their similarities and differences from the perspective of informatics analysis. METHODS: This cross-sectional study retrospectively analyzed extensive relevant studies published between 2014 and 2023 using stringent search criteria, excluding non-peer-reviewed and non-English documents. The main outcome variables are publication volume, citation volume, connection strength, occurrence frequency, relevance percentage, and development percentage. Furthermore, an integrated comparative analysis was conducted using unsupervised hierarchical clustering, spatiotemporal analysis, regression statistics, and Walktrap algorithm analysis. RESULTS: This analysis included 1,373 relevant studies. Advancements in neoadjuvant and adjuvant immunotherapies have been promising over the last decade, with an annual growth rate of 25.18% vs. 6.52% and global collaboration (International Co-authorships) of 19.93% vs. 19.84%. Respectively, five dominant research clusters were identified through unsupervised hierarchical clustering based on machine learning, among which Cluster 4 (Balance of neoadjuvant immunotherapy efficacy and safety) and Cluster 2 (Adjuvant immunotherapy clinical trials) (Average Publication Year [APY]: 2021.70±0.70 vs. 2017.54±4.59) are emerging research populations. Burst and regression curve analyses uncovered domain pivotal research signatures, including microsatellite instability (R2=0.7500, P=0.0025) and biomarkers (R2=0.6505, P=0.0086) in neoadjuvant scenarios, and the tumor microenvironment (R2=0.5571, P=0.0209) in adjuvant scenarios. The Walktrap algorithm further revealed that "neoadjuvant immunotherapy, non-small cell lung cancer (NSCLC), immune checkpoint inhibitors, melanoma" and "adjuvant immunotherapy, melanoma, hepatocellular carcinoma, dendritic cells" (Relevance Percentage: 100% vs. 100%, Development Percentage: 37.5% vs. 17.1%) are extremely relevant to this field but remain underdeveloped, highlighting the need for further investigation. CONCLUSION: This study identified pivotal research signatures and provided substantial predictions for neoadjuvant and adjuvant cancer immunotherapies. In addition, comprehensive quantitative comparisons revealed a notable shift in focus within this field, with neoadjuvant immunotherapy taking precedence over adjuvant immunotherapy after 2020; such a qualitative finding facilitate proper decision-making for subsequent research and mitigate the wastage of healthcare resources.

Electrochemical Oxidative Sulfonylation-Azidation of Alkenes.

A novel electrochemical oxidative sulfonylation-azidation of alkenes is accomplished by using sulfonyl hydrazide and trimethylsilyl azide (TMSN3) for the one-pot and green synthesis of ß-azidoarylsulfone, which involves the direct construction of new C-S and C-N bonds. Notably, neither exogenous oxidants/additives nor metal catalysts are required for this method. In addition, this electrochemical strategy features mild conditions and wide substrate scope and has been proved to be a radical pathway by mechanistic studies.

Vertically Concentrated Quantum Wells Enabling Highly Efficient Deep-Blue Perovskite Light-Emitting Diodes.

Deep-blue perovskite light-emitting diodes (PeLEDs) based on quasi-two-dimensional (quasi-2D) systems exist heightened sensitivity to the domain distribution. The top-down crystallization mode will lead to a vertical gradient distribution of quantum well (QW) structure, which is unfavorable for deep-blue emission. Herein, a thermal gradient annealing treatment is proposed to address the polydispersity issue of vertical QWs in quasi-2D perovskites. The formation of large-n domains at the upper interface of the perovskite film can be effectively inhibited by introducing a low-temperature source in the annealing process. Combined with the utilization of NaBr to inhibit the undesirable n=1 domain, a vertically concentrated QW structure is ultimately attained. As a result, the fabricated device delivers a narrow and stable deep-blue emission at 458 nm with an impressive external quantum efficiency (EQE) of 5.82 %. Green and sky-blue PeLEDs with remarkable EQE of 21.83 % and 17.51 % are also successfully achieved, respectively, by using the same strategy. The findings provide a universal strategy across the entire quasi-2D perovskites, paving the way for future practical application of PeLEDs.

Deep learning-based compressed SENSE improved diffusion-weighted image quality and liver cancer detection: A prospective study.

PURPOSE: To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC). METHODS: This single-center prospective study enrolled consecutive at-risk participants who underwent 3.0 T gadoxetate disodium-enhanced MRI. Conventional DWI was acquired using parallel imaging (PI) with SENSE (PI-DWI). In CS-DWI and DL-CS-DWI, CS but not PI with SENSE was used to accelerate the scan with 2.5 as the acceleration factor. Qualitative and quantitative image quality were independently assessed by two masked reviewers, and were compared using the Wilcoxon signed-rank test. The detection rates of clinically-relevant (LR-4/5/M based on the Liver Imaging Reporting and Data System v2018) liver lesions for each DWI sequence were independently evaluated by another two masked reviewers against their consensus assessments based on all available non-DWI sequences, and were compared by the McNemar test. RESULTS: 67 participants (median age, 58.0 years; 56 males) with 197 clinically-relevant liver lesions were enrolled. Among the three DWI sequences, DL-CS-DWI showed the best qualitative and quantitative image qualities (p range, <0.001-0.039). For clinically-relevant liver lesions, the detection rates (91.4%-93.4%) of DL-CS-DWI showed no difference with CS-DWI (87.3%-89.8%, p = 0.230-0.231) but were superior to PI-DWI (82.7%-85.8%, p = 0.015-0.025). For lesions located in the hepatic dome, DL-CS-DWI demonstrated the highest detection rates (94.8%-97.4% vs 76.9%-79.5% vs 64.1%-69.2%, p = 0.002-0.045) among the three DWI sequences. CONCLUSION: In patients at high-risk for HCC, DL-CS-DWI improved image quality and detection for clinically-relevant liver lesions, especially for the hepatic dome.

Supermolecular Confined Silicon Phosphorescence Nanoprobes for Time-Resolved Hypoxic Imaging Analysis.

Room temperature phosphorescence (RTP) nanoprobes play crucial roles in hypoxia imaging due to their high signal-to-background ratio (SBR) in the time domain. However, synthesizing RTP probes in aqueous media with a small size and high quantum yield remains challenging for intracellular hypoxic imaging up to present. Herein, aqueous RTP nanoprobes consisting of naphthalene anhydride derivatives, cucurbit[7]uril (CB[7]), and organosilicon are reported via supermolecular confined methods. Benefiting from the noncovalent confinement of CB[7] and hydrolysis reactions of organosilicon, such small-sized RTP nanoprobes (5-10 nm) exhibit inherent tunable phosphorescence (from 400 to 680 nm) with microsecond second lifetimes (up to ∼158.7 µs) and high quantum yield (up to ∼30%). The as-prepared RTP nanoprobes illustrate excellent intracellular hypoxia responsibility in a broad range from ∼0.1 to 21% oxygen concentrations. Compared to traditional fluorescence mode, the SBR value (∼108.69) of microsecond-range time-resolved in vitro imaging is up to 2.26 times greater in severe hypoxia (<0.1% O2), offering opportunities for precision imaging analysis in a hypoxic environment.

Global research hotspots, development trends and prospect discoveries of phase separation in cancer: a decade-long informatics investigation.

Liquid-liquid phase separation (LLPS) is a complex and subtle phenomenon whose formation and regulation take essential roles in cancer initiation, growth, progression, invasion, and metastasis. This domain holds a wealth of underutilized unstructured data that needs further excavation for potentially valuable information. Therefore, we retrospectively analyzed the global scientific knowledge in the field over the last decade by using informatics methods (such as hierarchical clustering, regression statistics, hotspot burst, and Walktrap algorithm analysis). Over the past decade, this area enjoyed a favorable development trend (Annual Growth Rate: 34.98%) and global collaboration (International Co-authorship: 27.31%). Through unsupervised hierarchical clustering based on machine learning, the global research hotspots were divided into five dominant research clusters: Cluster 1 (Effects and Mechanisms of Phase Separation in Drug Delivery), Cluster 2 (Phase Separation in Gene Expression Regulation), Cluster 3 (Phase Separation in RNA-Protein Interaction), Cluster 4 (Reference Value of Phase Separation in Neurodegenerative Diseases for Cancer Research), and Cluster 5 (Roles and Mechanisms of Phase Separation). And further time-series analysis revealed that Cluster 5 is the emerging research cluster. In addition, results from the regression curve and hotspot burst analysis point in unison to super-enhancer (a=0.5515, R2=0.6586, p=0.0044) and stress granule (a=0.8000, R2=0.6000, p=0.0085) as the most potential star molecule in this field. More interestingly, the Random-Walk-Strategy-based Walktrap algorithm further revealed that "phase separation, cancer, transcription, super-enhancer, epigenetics"(Relevance Percentage[RP]=100%, Development Percentage[DP]=29.2%), "stress granule, immunotherapy, tumor microenvironment, RNA binding protein"(RP=79.2%, DP=33.3%) and "nanoparticle, apoptosis"(RP=70.8%, DP=25.0%) are closely associated with this field, but are still under-developed and worthy of further exploration. In conclusion, this study profiled the global scientific landscape, discovered a crucial emerging research cluster, identified several pivotal research molecules, and predicted several crucial but still under-developed directions that deserve further research, providing an important reference value for subsequent basic and clinical research of phase separation in cancer.

Tetrahydrobiopterin metabolism attenuates ROS generation and radiosensitivity through LDHA S-nitrosylation: novel insight into radiogenic lung injury.

Genotoxic therapy triggers reactive oxygen species (ROS) production and oxidative tissue injury. S-nitrosylation is a selective and reversible posttranslational modification of protein thiols by nitric oxide (NO), and 5,6,7,8-tetrahydrobiopterin (BH4) is an essential cofactor for NO synthesis. However, the mechanism by which BH4 affects protein S-nitrosylation and ROS generation has not been determined. Here, we showed that ionizing radiation disrupted the structural integrity of BH4 and downregulated GTP cyclohydrolase I (GCH1), which is the rate-limiting enzyme in BH4 biosynthesis, resulting in deficiency in overall protein S-nitrosylation. GCH1-mediated BH4 synthesis significantly reduced radiation-induced ROS production and fueled the global protein S-nitrosylation that was disrupted by radiation. Likewise, GCH1 overexpression or the administration of exogenous BH4 protected against radiation-induced oxidative injury in vitro and in vivo. Conditional pulmonary Gch1 knockout in mice (Gch1fl/fl; Sftpa1-Cre+/- mice) aggravated lung injury following irradiation, whereas Gch1 knock-in mice (Gch1lsl/lsl; Sftpa1-Cre+/- mice) exhibited attenuated radiation-induced pulmonary toxicity. Mechanistically, lactate dehydrogenase (LDHA) mediated ROS generation downstream of the BH4/NO axis, as determined by iodoacetyl tandem mass tag (iodoTMT)-based protein quantification. Notably, S-nitrosylation of LDHA at Cys163 and Cys293 was regulated by BH4 availability and could restrict ROS generation. The loss of S-nitrosylation in LDHA after irradiation increased radiosensitivity. Overall, the results of the present study showed that GCH1-mediated BH4 biosynthesis played a key role in the ROS cascade and radiosensitivity through LDHA S-nitrosylation, identifying novel therapeutic strategies for the treatment of radiation-induced lung injury.

Development and validation of a clinical-radiomics model for prediction of prostate cancer: a multicenter study.

PURPOSE: To develop an early diagnosis model of prostate cancer based on clinical-radiomics to improve the accuracy of imaging diagnosis of prostate cancer. METHODS: The multicenter study enrolled a total of 449 patients with prostate cancer from December 2017 to January 2022. We retrospectively collected information from 342 patients who underwent prostate biopsy at Minhang Hospital. We extracted T2WI images through 3D-Slice, and used mask tools to mark the prostate area manually. The radiomics features were extracted by Python using the "Pyradiomics" module. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for data dimensionality reduction and feature selection, and the radiomics score was calculated according to the correlation coefficients. Multivariate logistic regression analysis was used to develop predictive models. We incorporated the radiomics score, PI-RADS, and clinical features, and this was presented as a nomogram. The model was validated using a cohort of 107 patients from the Xuhui Hospital. RESULTS: In total, 110 effective radiomics features were extracted. Finally, 9 features were significantly associated with the diagnosis of prostate cancer, from which we calculated the radiomics score. The predictors contained in the individualized prediction nomogram included age, fPSA/tPSA, PI-RADS, and radiomics score. The clinical-radiomics model showed good discrimination in the validation cohort (C-index = 0.88). CONCLUSION: This study presents a clinical-radiomics model that incorporates age, fPSA/PSA, PI-RADS, and radiomics score, which can be conveniently used to facilitate individualized prediction of prostate cancer before prostate biopsy.