Synergistically Engineering Grains and Grain Boundaries toward Li Dendrite-Free Li7La3Zr2O12.

Cation-doped cubic Li7La3Zr2O12 is regarded as a promising solid electrolyte for safe and energy-dense solid-state lithium batteries. However, it suffers from the formation of Li2CO3 and high electronic conductivity, which give rise to an unconformable Li/Li7La3Zr2O12 interface and lithium dendrites. Herein, composite AlF3-Li6.4La3Zr1.4Ta0.6O12 solid electrolytes were created based on thermal AlF3 decomposition and F/O displacement reactions under a high-temperature sintering process. When the AlF3 is thermally decomposed, it leaves Al2O3/AlF3 meliorating the grain boundaries and F- ions partially displacing O2- ions in the grains. Due to the higher electronegativity of F- in the grains and the grain-boundary modification, these AlF3-Li6.4La3Zr1.4Ta0.6O12 deliver optimized electronic conduction and chemical stability against the formation of Li2CO3. The Li/AlF3-Li6.4La3Zr1.4Ta0.6O12/Li cell exhibits a low interfacial resistance of ∼16 Ω cm2 and an ultrastable long-term cycling behavior for 800 h under a current density of 200 µA/cm2, leading to Li//LiCoO2 solid-state batteries with good rate performance and cycling stability.

Correlation analysis of EGFR gene mutation abundance and the efficacy of targeted therapy with osimertinib in nonsmall cell lung cancer-a case control study.

BACKGROUND: In nonsmall cell lung cancer (NSCLC), epidermal growth factor receptor (EGFR) mutation is the primary cancer-causing mutation. But whether the practical effectiveness of EGFR tyrosine kinase inhibitors (TKIs) can be influenced by plasma EGFR mutation abundance when treating patients with advanced NSCLC remains unanswered. Therefore, this research was intended to reveal the connection between plasma EGFR mutation abundance and clinical outcomes in osimertinib-treated patients with advanced NSCLC. METHODS: A total of 120 patients with advanced NSCLC were retrospectively analyzed, and 56 patients with EGFR-mutation-positive NSCLC receiving osimertinib first-line therapy were eventually screened and included. The baseline status and abundance of plasma EGFR in patients with NSCLC were detected by cSMART, and the ratio of 0.1 was the critical value. Imaging examinations were performed every 8-12 weeks for the assessment of tumor response. The relationship between baseline EGFR mutation abundance and clinical outcomes of TKI therapy was analyzed. RESULTS: The objective response rates (ORR) of EGFR-mutant patients in the high-/low-abundance groups were 69.2% and 40.0%, respectively. The high abundance group had an obviously higher ORR than the low abundance group (P = 0.029). A much longer median progression-free survival (mPFS) was demonstrated in patients with high mutation abundance than in patients with low abundance (11.2 months vs 7.1 months, P = 0.0133). As for the median overall survival (mOS), it showed the same trend as mPFS in patients from different groups (15.5 vs 10.7 months, P = 0.0028). The role of plasma mutation abundance as an independent prognostic factor for both PFS (hazard ratios [HR]: 0.30, P = 0.006) and OS (HR: 0.35, P = 0.004) was demonstrated by multivariate Cox regression analysis. CONCLUSION: There is a close connection between plasma EGFR mutation abundance and survival benefit in patients with NSCLC, which can be used for predicting the efficacy of EGFR-TKI targeted therapy. Our study is expected to provide a research basis for screening patients to whom the EGFR-TKI therapy is beneficial.

Enhancing malignancy prediction in thyroid nodules: A multimodal ultrasound radiomics approach in TI-RADS category 4 lesions.

PURPOSE: To explore the diagnostic value of intralesional and perilesional radiomics based on multimodal ultrasound (US) images in predicting the malignant ACR TIRADS 4 thyroid nodules (TNs). METHODS: A total of 297 cases of TNs in patients who underwent preoperative thyroid grayscale US and shear wave elastography (STE) were enrolled (training cohort: n = 150, internal validation cohort: n = 77, external validation cohort: n = 70). Regions of interests (ROIs) were delineated on grayscale US images and STE images, and then an isotropic expansion of 1.0, 1.5, 2.0, 2.5, and 3.0 mm was applied. Predictive models were established using recursive feature elimination-support vector machines (RFE-SVM) based on radiomics features calculated by random forest. RESULTS: The perilesional ROI1.5mm expansion achieved the highest area under curve (AUC) (AUC: 0.753 for grayscale US, 0.728 for STE; 95% confidence interval (CI): 0.664-0.743, 0.684-0.739, respectively). The joint model had the highest AUC values of 0.936 in the training dataset, 0.926 in internal dataset, and 0.893 in external dataset. The calibration curve showed good consistency and the decision curve indicated a greater clinical net benefit of the joint model. CONCLUSION: Joint model containing perilesional radiomics (1.5 mm) had significant value in predicting the malignant ACR TIRADS 4 TNs.

Porphyrin-Thiophene Based Conjugated Polymer Cathode with High Capacity for Lithium-Organic Batteries.

Organic electrode materials are promising for next-generation energy storage materials due to their environmental friendliness and sustainable renewability. However, problems such as their high solubility in electrolytes and low intrinsic conductivity have always plagued their further application. Polymerization to form conjugated organic polymers can not only inhibit the dissolution of organic electrodes in the electrolyte, but also enhance the intrinsic conductivity of organic molecules. Herein, we synthesized a new conjugated organic polymer (COPs) COP500-CuT2TP (poly [5,10,15,20-tetra(2,2'-bithiophen-5-yl) porphyrinato] copper (II)) by electrochemical polymerization method. Due to the self-exfoliation behavior, the porphyrin cathode exhibited a reversible discharge capacity of 420 mAh g-1, and a high specific energy of 900 Wh Kg-1 with a first coulombic efficiency of 96 % at 100 mA g-1. Excellent cycling stability up to 8000 cycles without capacity loss was achieved even at a high current density of 5 A g-1. This highly conjugated structure promotes COP500-CuT2TP combined high energy density, high power density, and good cycling stability, which would open new opportunity for the designable and versatile organic electrodes for electrochemical energy storage.

Spraying performance and deposition characteristics of an improved air-assisted nozzle with induction charging.

Electrostatic spraying technology can improve the efficiency of pesticide deposition on the surface of leaves and reduce the environmental pollution caused by pesticide drift, which has an important prospect in agricultural pesticide application. To improve the deposition and penetration of droplets in the crop canopy, we designed and optimized an air-assisted electrostatic nozzle and conducted the spraying performance experiment. Parameters, such as charge-to-mass ratio (CMR) and particle size, were tested and analyzed to obtain the suitable operating parameters of nozzle. The results proved that the improved air-assisted electrostatic nozzle has good atomization and chargeability. There is a good charging effect with a charging voltage of 3,000-5,000 V, the CMR increased 127.8% from 0.86 to 1.97 mC/kg as the charge voltage increases from 1,000 to 4,000 V, at an air pressure of 1.0 bar and liquid flow rate of 200 ml/min. Furthermore, we designed a multi-factor orthogonal experiment, which was conducted using a four-factor, three-level design to investigate the effects of operational parameters and canopy characteristics on droplet deposition and penetration. Analysis of variance (ANOVA) and F-test were performed on the experiment results. The results showed that the factor effect on droplet penetration, in descending order, was as follows: spray distance, leaf area index, air pressure, and air pressure × spray distance. The factor effect on abaxial leaf deposition, in descending order, was as follows: air pressure, spray distance, air pressure × charge voltage, spray distance × charge voltage, and charge voltage. For optimal droplet penetration and abaxial leaf deposition, option A 3 B 1 D 2 (air pressure 1.5 bar, spray distance 0.2 m, charge voltage 2,500 V) is recommend. The spray nozzle atomization performance and deposition regulation were studied by experimental methods to determine the optimal values of operating parameters to provide a reference for electrostatic spray system development.

Advances in the study of tissue-engineered retinal pigment epithelial cell sheets.

Regarded as the most promising treatment modality for retinal degenerative diseases, retinal pigment epithelium cell replacement therapy holds significant potential. Common retinal degenerative diseases, including Age-related Macular Degeneration, are frequently characterized by damage to the unit comprising photoreceptors, retinal pigment epithelium, and Bruch's membrane. The selection of appropriate tissue engineering materials, in conjunction with retinal pigment epithelial cells, for graft preparation, can offer an effective treatment for retinal degenerative diseases. This article presents an overview of the research conducted on retinal pigment epithelial cell tissue engineering, outlining the challenges and future prospects.

Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma.

BACKGROUND: Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP. METHODS: RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors. RESULTS: In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP. CONCLUSIONS: We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.

Impact of tumor multiplicity on the prognosis of patients with primary renal cell carcinoma: a SEER database analysis.

To compare clinical characteristics and survival outcomes of patients with multiple renal cell carcinoma versus single renal cell carcinoma. Develop a prognostic model for predicting prognosis in patients with multiple tumors and analyze prognostic factors. Patients with primary multiple renal cell carcinoma were selected from the Surveillance, Epidemiology, and End Results database (2004-2015). They were divided into single-tumor and multiple-tumor groups. Survival analysis was conducted using the Kaplan-Meier method and log-rank test. A Cox regression model was used to identify potential prognostic factors. A total of 19,489 renal cell carcinoma cases were included, with 947 in the multiple-tumor group and 18,542 in the single-tumor group. The multiple-tumor group had lower cancer-specific survival (P = 0.03, HR = 1.431). Cox regression identified risk factors for the multiple-tumor group including number of tumors, gender, combined summary stage, T stage, N stage, tumor size, and type of surgery. The predicted probabilities showed acceptable agreement with the actual observations at 3-, 5-, and 8-years area under the curve values in both the training and validation cohorts (0.831 vs. 0.605; 0.775 vs. 0.672; and 0.797 vs. 0.699, respectively). Compared with single renal cell carcinoma, multiple renal cell carcinoma is associated with decreased cancer-specific survival. Additionally, we identified several prognostic factors including the number of tumors, T stage, tumor size, and type of surgery. These findings offer valuable insights for selecting appropriate treatment strategies for patients diagnosed with multiple renal cell carcinomas.

Advances in sequencing and omics studies in prostate cancer: unveiling molecular pathogenesis and clinical applications.

Background: Prostate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field. Methods: We assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field. Results: 3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, 'the molecular pathogenesis of PCa' and 'the clinical application of sequencing and omics studies in PCa' were summarized as two research hotspots in the field. Conclusion: Sequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.

Ultrasound-Based Deep Learning Radiomics Nomogram for the Assessment of Lymphovascular Invasion in Invasive Breast Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: The aim of this study was to develop a deep learning radiomics nomogram (DLRN) based on B-mode ultrasound (BMUS) and color doppler flow imaging (CDFI) images for preoperative assessment of lymphovascular invasion (LVI) status in invasive breast cancer (IBC). MATERIALS AND METHODS: In this multicenter, retrospective study, 832 pathologically confirmed IBC patients were recruited from eight hospitals. The samples were divided into training, internal test, and external test sets. Deep learning and handcrafted radiomics features reflecting tumor phenotypes on BMUS and CDFI images were extracted. The BMUS score and CDFI score were calculated after radiomics feature selection. Subsequently, a DLRN was developed based on the scores and independent clinic-ultrasonic risk variables. The performance of the DLRN was evaluated for calibration, discrimination, and clinical usefulness. RESULTS: The DLRN predicted the LVI with accuracy, achieving an area under the receiver operating characteristic curve of 0.93 (95% CI 0.90-0.95), 0.91 (95% CI 0.87-0.95), and 0.91 (95% CI 0.86-0.94) in the training, internal test, and external test sets, respectively, with good calibration. The DLRN demonstrated superior performance compared to the clinical model and single scores across all three sets (p < 0.05). Decision curve analysis and clinical impact curve confirmed the clinical utility of the model. Furthermore, significant enhancements in net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indicated that the two scores could serve as highly valuable biomarkers for assessing LVI. CONCLUSION: The DLRN exhibited strong predictive value for LVI in IBC, providing valuable information for individualized treatment decisions.

Preoperative neoadjuvant targeted therapy remodels intra-tumoral heterogeneity of clear-cell renal cell carcinoma and ferroptosis inhibition induces resistance progression.

Neoadjuvant tyrosine kinase inhibitor (TKI) therapy is an important treatment option for advanced renal cell carcinoma (RCC). Many RCC patients may fail to respond or be resistant to TKI therapy. We aimed to explore the key mechanisms of neoadjuvant therapy résistance. We obtained tumor samples from matched pre-treatment biopsy and post-treatment surgical samples and performed single-cell RNA sequencing. Sunitinib-resistant ccRCC cell lines were established. Ferroptosis was detected by ferrous ion and lipid peroxidation levels. Tumor growth and resistance to Sunitinib was validated in vitro and vivo. Immunohistochemistry was used to validate the levels key genes and lipid peroxidation. Multi-center cohorts were included, including TCGA, ICGC, Checkmate-025 and IMmotion151 clinical trial. Survival analysis was performed to identify the associated clinical and genomic variables. Intratumoral heterogeneity was first described in the whole neoadjuvant management. The signature of endothelial cells was correlated with drug sensitivity and progression-free survival. Ferroptosis was shown to be the key biological program in malignant cell resistance. We observed tissue lipid peroxidation was negatively correlated with IL6 and tumor response. TKI-resistant cell line was established. SLC7A11 knockdown promoted cell growth and lipid peroxidation, increased the ferroptosis level, and suppressed the growth of tumor xenografts significantly (P < 0.01). IL6 could reverse the ferroptosis and malignant behavior caused by SLC7A11 (-) via JAK2/STAT3 pathway, which was rescued by the ferroptosis inducer Erastin. Our data indicate that ferroptosis is a novel strategy for advanced RCC treatment, which activated by IL6, providing a new idea for resistance to TKIs.

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems.

Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.

Integrated analysis of tertiary lymphoid structures and immune infiltration in ccRCC microenvironment revealed their clinical significances: a multicenter cohort study.

BACKGROUND: Tertiary lymphoid structures (TLSs) serve as organized lymphoid aggregates that influence immune responses within the tumor microenvironment. This study aims to investigate the characteristics and clinical significance of TLSs and tumor-infiltrating lymphocytes (TILs) in clear cell renal cell carcinoma (ccRCC). METHODS: TLSs and TILs were analyzed comprehensively in 754 ccRCC patients from 6 academic centers and 532 patients from The Cancer Genome Atlas. Integrated analysis was performed based on single-cell RNA-sequencing datasets from 21 ccRCC patients to investigate TLS heterogeneity in ccRCC. Immunohistochemistry and multiplex immunofluorescence were applied. Cox regression and Kaplan-Meier analyses were used to reveal the prognostic significance. RESULTS: The study demonstrated the existence of TLSs and TILs heterogeneities in the ccRCC microenvironment. TLSs were identified in 16% of the tumor tissues in 113 patients. High density (>0.6/mm2) and maturation of TLSs predicted good overall survival (OS) (p<0.01) in ccRCC patients. However, high infiltration (>151) of scattered TILs was an independent risk factor of poor ccRCC prognosis (HR=14.818, p<0.001). The presence of TLSs was correlated with improved progression-free survival (p=0.002) and responsiveness to therapy (p<0.001). Interestingly, the combination of age and TLSs abundance had an impact on OS (p<0.001). Higher senescence scores were detected in individuals with immature TLSs (p=0.003). CONCLUSIONS: The study revealed the contradictory features of intratumoral TLSs and TILs in the ccRCC microenvironment and their impact on clinical prognosis, suggesting that abundant and mature intratumoral TLSs were associated with decreased risks of postoperative ccRCC relapse and death as well as favorable therapeutic response. Distinct spatial distributions of immune infiltration could reflect effective antitumor or protumor immunity in ccRCC.

DEPDC1 as a metabolic target regulates glycolysis in renal cell carcinoma through AKT/mTOR/HIF1α pathway.

Renal cell carcinoma (RCC) is considered a "metabolic disease" characterized by elevated glycolysis in patients with advanced RCC. Tyrosine kinase inhibitor (TKI) therapy is currently an important treatment option for advanced RCC, but drug resistance may develop in some patients. Combining TKI with targeted metabolic therapy may provide a more effective approach for patients with advanced RCC. An analysis of 14 RCC patients (including three needle biopsy samples with TKI resistance) revealed by sing-cell RNA sequencing (scRNA-seq) that glycolysis played a crucial role in poor prognosis and drug resistance in RCC. TCGA-KIRC and glycolysis gene set analysis identified DEPDC1 as a target associated with malignant progression and drug resistance in KIRC. Subsequent experiments demonstrated that DEPDC1 promoted malignant progression and glycolysis of RCC, and knockdown DEPDC1 could reverse TKI resistance in RCC cell lines. Bulk RNA sequencing (RNA-seq) and non-targeted metabolomics sequencing suggested that DEPDC1 may regulate RCC glycolysis via AKT/mTOR/HIF1α pathway, a finding supported by protein-level analysis. Clinical tissue samples from 98 RCC patients demonstrated that DEPDC1 was associated with poor prognosis and predicted RCC metastasis. In conclusion, this multi-omics analysis suggests that DEPDC1 could serve as a novel target for TKI combined with targeted metabolic therapy in advanced RCC patients with TKI resistance.

Breaking solvation dominance of ethylene carbonate via molecular charge engineering enables lower temperature battery.

Low temperatures severely impair the performance of lithium-ion batteries, which demand powerful electrolytes with wide liquidity ranges, facilitated ion diffusion, and lower desolvation energy. The keys lie in establishing mild interactions between Li+ and solvent molecules internally, which are hard to achieve in commercial ethylene-carbonate based electrolytes. Herein, we tailor the solvation structure with low-ε solvent-dominated coordination, and unlock ethylene-carbonate via electronegativity regulation of carbonyl oxygen. The modified electrolyte exhibits high ion conductivity (1.46 mS·cm-1) at -90 °C, and remains liquid at -110 °C. Consequently, 4.5 V graphite-based pouch cells achieve ~98% capacity over 200 cycles at -10 °C without lithium dendrite. These cells also retain ~60% of their room-temperature discharge capacity at -70 °C, and miraculously retain discharge functionality even at ~-100 °C after being fully charged at 25 °C. This strategy of disrupting solvation dominance of ethylene-carbonate through molecular charge engineering, opens new avenues for advanced electrolyte design.