What enlightenment has the development of lung cancer bone metastasis brought in the last 22 years.

BACKGROUND: Lung cancer bone metastasis (LCBM) is a disease with a poor prognosis, high risk and large patient population. Although considerable scientific output has accumulated on LCBM, problems have emerged, such as confusing research structures. AIM: To organize the research frontiers and body of knowledge of the studies on LCBM from the last 22 years according to their basic research and translation, clinical treatment, and clinical diagnosis to provide a reference for the development of new LCBM clinical and basic research. METHODS: We used tools, including R, VOSviewer and CiteSpace software, to measure and visualize the keywords and other metrics of 1903 articles from the Web of Science Core Collection. We also performed enrichment and protein-protein interaction analyses of gene expression datasets from LCBM cases worldwide. RESULTS: Research on LCBM has received extensive attention from scholars worldwide over the last 20 years. Targeted therapies and immunotherapies have evolved into the mainstream basic and clinical research directions. The basic aspects of drug resistance mechanisms and parathyroid hormone-related protein may provide new ideas for mechanistic study and improvements in LCBM prognosis. The produced molecular map showed that ribosomes and focal adhesion are possible pathways that promote LCBM occurrence. CONCLUSION: Novel therapies for LCBM face animal testing and drug resistance issues. Future focus should centre on advancing clinical therapies and researching drug resistance mechanisms and ribosome-related pathways.

Association of tumor immune infiltration and prognosis with homologous recombination repair genes mutations in early triple-negative breast cancer.

The aim of this study was to evaluate the mutation spectrum of homologous recombination repair (HRR) genes and its association with tumor immune infiltration and prognosis in triple-negative breast cancer (TNBC). TNBC patients (434 patients from Ruijin cohort) were evaluated with targeted next-generating sequencing for mutations in HRR genes. The frequencies of mutations were compared with public reference cohorts (320 TNBC patients from METABRIC, 105 from TCGA, and 225 from MSKCC 2018). Associations between mutation status and tumor immune infiltration and prognosis were analyzed. HRR genes mutations were seen in 21.89% patients, with BRCA1/2 mutations significantly enriched in tumors with breast/ovarian cancer family history (P = 0.025) and high Ki-67 levels (P = 0.018). HRR genes mutations were not related with recurrence-free survival (RFS) (adjusted P = 0.070) and overall survival (OS) (adjusted P = 0.318) for TNBC patients, regardless of carboplatin treatment (P > 0.05). Moreover, tumor immune infiltration and PD-L1 expression was positively associated with HRR or BRCA1/2 mutation (all P < 0.001). Patients with both HRR mutation and high CD8+ T cell counts had the best RFS and OS, whereas patients with no HRR mutation and low CD8+ T cell counts had the worst outcomes (RFS P < 0.001, OS P = 0.019). High frequency of HRR gene mutations was found in early TNBC, with no prognostic significance. Immune infiltration and PD-L1 expression was positively associated with HRR mutation, and both HRR mutation and high CD8+ T cell infiltration levels were associated with superior disease outcome.

Improving both performance and stability of n-type organic semiconductors by vitamin C.

Organic semiconductors (OSCs) are one of the most promising candidates for flexible, wearable and large-area electronics. However, the development of n-type OSCs has been severely held back due to the poor stability of their most candidates, that is, the intrinsically high reactivity of negatively charged polarons to oxygen and water. Here we demonstrate a general strategy based on vitamin C to stabilize n-type OSCs, remarkably improving the performance and stability of their device, for example, organic field-effect transistors. Vitamin C scavenges reactive oxygen species and inhibits their generation by sacrificial oxidation and non-sacrificial triplet quenching in a cascade process, which not only lastingly prevents molecular structure from oxidation damage but also passivates the latent electron traps to stabilize electron transport. This study presents a way to overcome the long-standing stability problem of n-type OSCs and devices.

Eigen microstates in self-organized criticality.

We employ the eigen microstates approach to explore the self-organized criticality (SOC) in two celebrated sandpile models, namely the BTW model and the Manna model. In both models, phase transitions from the absorbing state to the critical state can be understood by the emergence of dominant eigen microstates with significantly increased weights. Spatial eigen microstates of avalanches can be uniformly characterized by a linear system size rescaling. The first temporal eigen microstates reveal scaling relations in both models. Furthermore, by finite-size scaling analysis of the first eigen microstates, we numerically estimate critical exponents, i.e., sqrt[σ_{0}w_{1}]/v[over ̃]_{1}∝L^{D} and v[over ̃]_{1}∝L^{D(1-τ_{s})/2}. Our findings could provide profound insights into eigen microstates of the universality and phase transition in nonequilibrium complex systems governed by self-organized criticality.

The 21-Gene Recurrence Score Assay Improved Multidisciplinary Treatment Compliance in Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer Patients: An Analysis of 2,323 Patients.

PURPOSE: The 21-gene recurrence score (RS) can guide adjuvant chemotherapy decisions in the multidisciplinary treatment (MDT) of patients with early breast cancer. This study aimed to evaluate the influence of the 21-gene RS assay on patient' compliance with MDT and its association with disease outcomes. METHODS: Patients diagnosed with pN0-1, hormone receptor-positive, human epidermal growth factor receptor-2-negative breast cancer between January 2013 and June 2019 were enrolled. A logistic regression model was used to identify parameters associated with treatment adherence. Prognostic indicators were evaluated using the Cox proportional hazard models. RESULTS: After the assay, patients were less likely to violate the treatment plan (14.9% vs. 23.1%, p < 0.001), and higher compliance rates were observed for chemotherapy (p = 0.042), radiotherapy (p = 0.012), and endocrine therapy (p < 0.001). Multivariable analysis demonstrated that the 21-gene RS assay (odds ratio [OR], 1.43; 95% confidence interval [CI], 1.09-1.88; p = 0.009) was independently associated with MDT compliance. Moreover, compliance with MDT was independently associated with better disease-free survival (hazard ratio, 0.43; 95% CI, 0.29-0.64; p < 0.001), regardless of the 21-gene RS assay (interaction p = 0.842). CONCLUSION: The 21-gene RS assay improved the MDT compliance rate in patients with early breast cancer. Adherence to MDT is associated with a better prognosis.

Overexpressed KCNK1 regulates potassium channels affecting molecular mechanisms and biological pathways in bladder cancer.

BACKGROUND: This study aimed to explore the expression, molecular mechanism and its biological function of potassium two pore domain channel subfamily K member 1 (KCNK1) in bladder cancer (BC). METHODS: We integrated large numbers of external samples (n = 1486) to assess KCNK1 mRNA expression levels and collected in-house samples (n = 245) for immunohistochemistry (IHC) experiments to validate at the KCNK1 protein level. Single-cell RNA sequencing (scRNA-seq) analysis was performed to further assess KCNK1 expression and cellular communication. The transcriptional regulatory mechanisms of KCNK1 expression were explored by ChIP-seq, ATAC-seq and ChIA-PET data. Highly expressed co-expressed genes (HECEGs) of KCNK1 were used to explore potential signalling pathways. Furthermore, the immunoassay, clinical significance and molecular docking of KCNK1 were calculated. RESULTS: KCNK1 mRNA was significantly overexpressed in BC (SMD = 0.58, 95% CI [0.05; 1.11]), validated at the protein level (p < 0.0001). Upregulated KCNK1 mRNA exhibited highly distinguishing ability between BC and control samples (AUC = 0.82 [0.78-0.85]). Further, scRNA-seq analysis revealed that KCNK1 expression was predominantly clustered in BC epithelial cells and tended to increase with cellular differentiation. BC epithelial cells were involved in cellular communication mainly through the MK signalling pathway. Secondly, the KCNK1 transcription start site (TSS) showed promoter-enhancer interactions in three-dimensional space, while being transcriptionally regulated by GRHL2 and FOXA1. Most of the KCNK1 HECEGs were enriched in cell cycle-related signalling pathways. KCNK1 was mainly involved in cellular metabolism-related pathways and regulated cell membrane potassium channel activity. KCNK1 expression was associated with the level of infiltration of various immune cells. Immunotherapy and chemotherapy (docetaxel, paclitaxel and vinblastine) were more effective in BC patients in the high KCNK1 expression group. KCNK1 expression correlated with age, pathology grade and pathologic_M in BC patients. CONCLUSIONS: KCNK1 was significantly overexpressed in BC. A complex and sophisticated three-dimensional spatial transcriptional regulatory network existed in the KCNK1 TSS and promoted the upregulated of KCNK1 expression. The high expression of KCNK1 might be involved in the cell cycle, cellular metabolism, and tumour microenvironment through the regulation of potassium channels, and ultimately contributed to the deterioration of BC.

Transketolase promotes MAFLD by limiting inosine-induced mitochondrial activity.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has a global prevalence of about 25% and no approved therapy. Using metabolomic and proteomic analyses, we identified high expression of hepatic transketolase (TKT), a metabolic enzyme of the pentose phosphate pathway, in human and mouse MAFLD. Hyperinsulinemia promoted TKT expression through the insulin receptor-CCAAT/enhancer-binding protein alpha axis. Utilizing liver-specific TKT overexpression and knockout mouse models, we demonstrated that TKT was sufficient and required for MAFLD progression. Further metabolic flux analysis revealed that Tkt deletion increased hepatic inosine levels to activate the protein kinase A-cAMP response element binding protein cascade, promote phosphatidylcholine synthesis, and improve mitochondrial function. Moreover, insulin induced hepatic TKT to limit inosine-dependent mitochondrial activity. Importantly, N-acetylgalactosamine (GalNAc)-siRNA conjugates targeting hepatic TKT showed promising therapeutic effects on mouse MAFLD. Our study uncovers how hyperinsulinemia regulates TKT-orchestrated inosine metabolism and mitochondrial function and provides a novel therapeutic strategy for MAFLD prevention and treatment.

Interplay Between Intracellular Transport Dynamics and Liquid‒Liquid Phase Separation.

Liquid‒liquid phase separation (LLPS) is a ubiquitous process in which proteins, RNA, and biomolecules assemble into membrane-less compartments, playing important roles in many biological functions and diseases. The current knowledge on the biophysical and biochemical principles of LLPS is largely from in vitro studies; however, the physiological environment in living cells is complex and not at equilibrium. The characteristics of intracellular dynamics and their roles in physiological LLPS remain to be resolved. Here, by using single-particle tracking of quantum dots and dynamic monitoring of the formation of stress granules (SGs) in single cells, the spatiotemporal dynamics of intracellular transport in cells undergoing LLPS are quantified. It is shown that intracellular diffusion and active transport are both reduced. Furthermore, the formation of SG droplets contributes to increased spatial heterogeneity within the cell. More importantly, the study demonstrated that the LLPS of SGs can be regulated by intracellular dynamics in two stages: the reduced intracellular diffusion promotes SG assembly and the microtubule-associated transport facilitates SG coalescences. The work on intracellular dynamics not only improves the understanding of the mechanism of physiology phase separations occurring in nonequilibrium environments but also reveals an interplay between intracellular dynamics and LLPS.

Achieving Zero-Temperature Coefficient Point Behavior by Defect Passivation for Temperature-Immune Organic Field-Effect Transistors.

Organic field-effect transistors (OFETs) have broad prospects in biomedical, sensor, and aerospace applications. However, obtaining temperature-immune OFETs is difficult because the electrical properties of organic semiconductors (OSCs) are temperature-sensitive. The zero-temperature coefficient (ZTC) point behavior can be used to achieve a temperature-immune output current; however, it is difficult to achieve in organic devices with thermal activation characteristics, according to the existing ZTC point theory. Here, the Fermi pinning in OSCs is eliminated using the defect passivation strategy, making the Fermi level closer to the tail state at low temperatures; thus threshold voltage (VT) is negatively correlated with temperature. ZTC point behaviors in OFETs are achieved by compensation between VT and mobility at different temperatures to improve its temperature immunity. A temperature-immune output current can be realized in a variable-temperature bias voltage test over 50000 s by biasing the device at the ZTC point. This study provides an effective solution for temperature-immune OFETs and inspiration for their practical application.

Order parameter dynamics in complex systems: From models to data.

Collective ordering behaviors are typical macroscopic manifestations embedded in complex systems and can be ubiquitously observed across various physical backgrounds. Elements in complex systems may self-organize via mutual or external couplings to achieve diverse spatiotemporal coordinations. The order parameter, as a powerful quantity in describing the transition to collective states, may emerge spontaneously from large numbers of degrees of freedom through competitions. In this minireview, we extensively discussed the collective dynamics of complex systems from the viewpoint of order-parameter dynamics. A synergetic theory is adopted as the foundation of order-parameter dynamics, and it focuses on the self-organization and collective behaviors of complex systems. At the onset of macroscopic transitions, slow modes are distinguished from fast modes and act as order parameters, whose evolution can be established in terms of the slaving principle. We explore order-parameter dynamics in both model-based and data-based scenarios. For situations where microscopic dynamics modeling is available, as prototype examples, synchronization of coupled phase oscillators, chimera states, and neuron network dynamics are analytically studied, and the order-parameter dynamics is constructed in terms of reduction procedures such as the Ott-Antonsen ansatz, the Lorentz ansatz, and so on. For complicated systems highly challenging to be well modeled, we proposed the eigen-microstate approach (EMP) to reconstruct the macroscopic order-parameter dynamics, where the spatiotemporal evolution brought by big data can be well decomposed into eigenmodes, and the macroscopic collective behavior can be traced by Bose-Einstein condensation-like transitions and the emergence of dominant eigenmodes. The EMP is successfully applied to some typical examples, such as phase transitions in the Ising model, climate dynamics in earth systems, fluctuation patterns in stock markets, and collective motion in living systems.

Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model.

OBJECTIVES: Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy. METHODS: A total of 726 HER2 + cases who received no/single/dual anti-HER2 targeted therapies were split into three respective cohorts. A deep learning model (DeepTEPP) based on preoperative breast magnetic resonance (MR) was developed. Patients were scored and categorized into low-, moderate-, and high-risk groups. Recurrence-free survival (RFS) was compared in patients with different risk groups according to the anti-HER2 treatment they received, to validate the value of DeepTEPP in predicting treatment efficacy and guiding anti-HER2 strategy. RESULTS: DeepTEPP was capable of risk stratification and guiding anti-HER2 treatment strategy: DeepTEPP-Low patients (60.5%) did not derive significant RFS benefit from trastuzumab (p = 0.144), proposing an anti-HER2 de-escalation. DeepTEPP-Moderate patients (19.8%) significantly benefited from trastuzumab (p = 0.048), but did not obtain additional improvements from pertuzumab (p = 0.125). DeepTEPP-High patients (19.7%) significantly benefited from dual HER2 blockade (p = 0.045), suggesting an anti-HER2 escalation. CONCLUSIONS: DeepTEPP represents a pioneering MR-based deep learning model that enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thereby providing valuable guidance for anti-HER2 (de-)escalation strategies. DeepTEPP provides an important reference for choosing the appropriate individualized treatment in HER2 + breast cancer patients, warranting prospective validation. CLINICAL RELEVANCE STATEMENT: We built an MR-based deep learning model DeepTEPP, which enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thus guiding anti-HER2 (de-)escalation strategies in early HER2-positive breast cancer patients. KEY POINTS: • DeepTEPP is able to predict anti-HER2 effectiveness and to guide treatment (de-)escalation. • DeepTEPP demonstrated an impressive prognostic efficacy for recurrence-free survival and overall survival. • To our knowledge, this is one of the very few, also the largest study to test the efficacy of a deep learning model extracted from breast MR images on HER2-positive breast cancer survival and anti-HER2 therapy effectiveness prediction.

Predictive nomogram using multimodal ultrasonographic features for axillary lymph node metastasis in early­stage invasive breast cancer.

Axillary lymph node (ALN) status is a key prognostic factor in patients with early-stage invasive breast cancer (IBC). The present study aimed to develop and validate a nomogram based on multimodal ultrasonographic (MMUS) features for early prediction of axillary lymph node metastasis (ALNM). A total of 342 patients with early-stage IBC (240 in the training cohort and 102 in the validation cohort) who underwent preoperative conventional ultrasound (US), strain elastography, shear wave elastography and contrast-enhanced US examination were included between August 2021 and March 2022. Pathological ALN status was used as the reference standard. The clinicopathological factors and MMUS features were analyzed with uni- and multivariate logistic regression to construct a clinicopathological and conventional US model and a MMUS-based nomogram. The MMUS nomogram was validated with respect to discrimination, calibration, reclassification and clinical usefulness. US features of tumor size, echogenicity, stiff rim sign, perfusion defect, radial vessel and US Breast Imaging Reporting and Data System category 5 were independent risk predictors for ALNM. MMUS nomogram based on these factors demonstrated an improved calibration and favorable performance [area under the receiver operator characteristic curve (AUC), 0.927 and 0.922 in the training and validation cohorts, respectively] compared with the clinicopathological model (AUC, 0.681 and 0.670, respectively), US-depicted ALN status (AUC, 0.710 and 0.716, respectively) and the conventional US model (AUC, 0.867 and 0.894, respectively). MMUS nomogram improved the reclassification ability of the conventional US model for ALNM prediction (net reclassification improvement, 0.296 and 0.288 in the training and validation cohorts, respectively; both P<0.001). Taken together, the findings of the present study suggested that the MMUS nomogram may be a promising, non-invasive and reliable approach for predicting ALNM.

Unraveling the crucial role of trace oxygen in organic semiconductors.

Optoelectronic properties of semiconductors are significantly modified by impurities at trace level. Oxygen, a prevalent impurity in organic semiconductors (OSCs), has long been considered charge-carrier traps, leading to mobility degradation and stability problems. However, this understanding relies on the conventional deoxygenation methods, by which oxygen residues in OSCs are inevitable. It implies that the current understanding is questionable. Here, we develop a non-destructive deoxygenation method (i.e., de-doping) for OSCs by a soft plasma treatment, and thus reveal that trace oxygen significantly pre-empties the donor-like traps in OSCs, which is the origin of p-type characteristics exhibited by the majority of these materials. This insight is completely opposite to the previously reported carrier trapping and can clarify some previously unexplained organic electronics phenomena. Furthermore, the de-doping results in the disappearance of p-type behaviors and significant increase of n-type properties, while re-doping (under light irradiation in O2) can controllably reverse the process. Benefiting from this, the key electronic characteristics (e.g., polarity, conductivity, threshold voltage, and mobility) can be precisely modulated in a nondestructive way, expanding the explorable property space for all known OSC materials.

Serum level of galectin-9 as a potential biomarker for high risk of malignancy in dermatomyositis.

OBJECTIVES: Galectin-9, as immune checkpoint protein, plays a role in regulating autoimmunity and tumour immunity. Therefore, we explored the pathophysiological link between galectin-9 and malignancy in cancer-related DM (CRDM). METHODS: Serum galectin-9 were quantified via enzyme-linked immunosorbent assay, and its association with serological indices was evaluated using Spearman analysis. Receiver operating characteristic (ROC) analysis was utilized to determine the cut-off value of galectin-9. RESULTS: Serum levels of galectin-9 were significantly higher in DM patients [23.38 (13.85-32.57) ng/ml] than those in healthy controls (HCs) [6.81 (5.42-7.89) ng/ml, P < 0.0001], and were positively correlated with the cutaneous dermatomyositis disease area severity index activity (CDASI-A) scores (rs=0.3065, P = 0.0172). DM patients with new-onset and untreated cancer (new-CRDM) [31.58 (23.85-38.84) ng/ml] had higher levels of galectin-9 than those with stable and treated cancer (stable-CRDM) [17.49 (10.23-27.91) ng/ml, P = 0.0288], non-cancer-related DM (non-CRDM) [21.05 (11.97-28.02) ng/ml, P = 0.0258], and tumour patients without DM [7.46 (4.90-8.51) ng/ml, P < 0.0001]. Serum galectin-9 levels significantly decreased [27.79 (17.04-41.43) ng/ml vs 13.88 (5.15-20.37) ng/ml, P = 0.002] after anti-cancer treatment in CRDM patients. The combination of serum galectin-9 and anti-transcriptional intermediary factor 1-γ (anti-TIF1-γ) antibody (AUC = 0.889, 95% CI 0.803-0.977) showed the highest predictive value for the presence of cancer in DM. CONCLUSION: Increased galectin-9 levels were related to tumor progression in CRDM, and galectin-9 was downregulated upon cancer treatment. Monitoring serum galectin-9 levels and anti-TIF1-γ antibodies might be an attractive strategy to achieve tumour diagnosis and predict CRDM outcome.

Machine Learning-Based Breast Tumor Ultrasound Radiomics for Pre-operative Prediction of Axillary Sentinel Lymph Node Metastasis Burden in Early-Stage Invasive Breast Cancer.

OBJECTIVE: The aim of the work described here was to assess the application of ultrasound (US) radiomics with machine learning (ML) classifiers to the prediction of axillary sentinel lymph node metastasis (SLNM) burden in early-stage invasive breast cancer (IBC). METHODS: In this study, 278 early-stage IBC patients with at least one SLNM (195 in the training set and 83 in the test set) were studied at our institution. Pathologic SLNM burden was used as the reference standard. The US radiomics features of breast tumors were extracted by using 3D-Slicer and PyRadiomics software. Four ML classifiers-linear discriminant analysis (LDA), support vector machine (SVM), random forest (RF) and decision tree (DT)-were used to construct radiomics models for the prediction of SLNM burden. The combined clinicopathologic-radiomics models were also assessed with respect to sensitivity, specificity, accuracy and areas under the curve (AUCs). RESULTS: Among the US radiomics models, the SVM classifier achieved better predictive performance with an AUC of 0.920 compared with RF (AUC = 0.874), LDA (AUC = 0.835) and DT (AUC = 0.800) in the test set. The clinicopathologic model had low efficacy, with AUCs of 0.678 and 0.710 in the training and test sets, respectively. The combined clinicopathologic (C) factors and SVM classifier (C + SVM) model improved the predictive ability with an AUC of 0.934, sensitivity of 86.7%, specificity of 89.9% and accuracy of 91.0% in the test set. CONCLUSION: ML-based US radiomics analysis, as a novel and promising predictive tool, is conducive to a precise clinical treatment strategy.

Decitabine induces IRF7-mediated immune responses in p53-mutated triple-negative breast cancer: a clinical and translational study.

p53 is mutated in half of cancer cases. However, no p53-targeting drugs have been approved. Here, we reposition decitabine for triple-negative breast cancer (TNBC), a subtype with frequent p53 mutations and extremely poor prognosis. In a retrospective study on tissue microarrays with 132 TNBC cases, DNMT1 overexpression was associated with p53 mutations (P = 0.037) and poor overall survival (OS) (P = 0.010). In a prospective DEciTabinE and Carboplatin in TNBC (DETECT) trial (NCT03295552), decitabine with carboplatin produced an objective response rate (ORR) of 42% in 12 patients with stage IV TNBC. Among the 9 trialed patients with available TP53 sequencing results, the 6 patients with p53 mutations had higher ORR (3/6 vs. 0/3) and better OS (16.0 vs. 4.0 months) than the patients with wild-type p53. In a mechanistic study, isogenic TNBC cell lines harboring DETECT-derived p53 mutations exhibited higher DNMT1 expression and decitabine sensitivity than the cell line with wild-type p53. In the DETECT trial, decitabine induced strong immune responses featuring the striking upregulation of the innate immune player IRF7 in the p53-mutated TNBC cell line (upregulation by 16-fold) and the most responsive patient with TNBC. Our integrative studies reveal the potential of repurposing decitabine for the treatment of p53-mutated TNBC and suggest IRF7 as a potential biomarker for decitabine-based treatments.

Ultrahigh-gain organic transistors based on van der Waals metal-barrier interlayer-semiconductor junction.

Intrinsic gain is a vital figure of merit in transistors, closely related to signal amplification, operation voltage, power consumption, and circuit simplification. However, organic thin-film transistors (OTFTs) targeted at high gain have suffered from challenges such as narrow subthreshold operating voltage, low-quality interface, and uncontrollable barrier. Here, we report a van der Waals metal-barrier interlayer-semiconductor junction-based OTFT, which shows ultrahigh performance including ultrahigh gain of ~104, low saturation voltage, negligible hysteresis, and good stability. The high-quality van der Waals-contacted junctions are mainly attributed to patterning EGaIn liquid metal electrodes by low-energy microfluidic processes. The wide-bandgap semiconductor Ga2O3 as barrier interlayer is achieved by in situ surface oxidation of EGaIn electrodes, allowing for an adjustable barrier height and expected thermionic emission properties. The organic inverters with a high gain of 5130 and a simplified current stabilizer are further demonstrated, paving a way for high-gain and low-power organic electronics.

An exosome-based specific transcriptomic signature for profiling regulation patterns and modifying tumor immune microenvironment infiltration in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a highly heterogeneous tumor that lacks effective treatment and has a poor prognosis. Exosomes carry abundant genomic information and have a significant role in tumorigenesis, metastasis, and drug resistance. However, further exploration is needed to investigate the relationship between exosome-related genes and the heterogeneity and tumor immune microenvironment of TNBC. Based on the exosome-related gene sets, multiple machine learning algorithms, such as Cox boost, were used to screen the risk score model with the highest C-index. A 9-gene risk score model was constructed, and the TNBC population was divided into high- and low-risk groups. The effectiveness of this model was verified in multiple datasets. Compared with the low-risk group, the high-risk group exhibited a poorer prognosis, which may be related to lower levels of immune infiltration and immune response rates. The gene mutation profiles and drug sensitivity of the two groups were also compared. By screening for genes with the most prognostic value, the hub gene, CLDN7, was identified, and thus, its potential role in predicting prognosis, as well as providing ideas for the clinical diagnosis, treatment, and risk assessment of TNBC, was also discussed. This study demonstrates that exosome-related genes can be used for risk stratification in TNBC, identifying patients with a worse prognosis. The high-risk group exhibited a poorer prognosis and required more aggressive treatment strategies. Analysis of the genomic information in patient exosomes may help to develop personalized treatment decisions and improve their prognosis. CLDN7 has potential value in prognostic prediction in the TNBC population.

Safety analysis of immediate breast reconstruction with a deep inferior epigastric perforator (DIEP) flap in the post-COVID-19 era: a comparison between pre- and post-pandemic cohorts.

Background: The demand for immediate breast reconstruction with a deep inferior epigastric perforator (DIEP) flap is recovering as coronavirus disease 2019 (COVID-19) transitions from a pandemic to an endemic. This study sought to evaluate the safety of resuming DIEP flap reconstruction in the post-COVID-19 era. Methods: Consecutive breast cancer patients who underwent immediate breast reconstruction with a DIEP flap at the Comprehensive Breast Health Center, Ruijin Hospital were retrospectively included in the study. The patients were divided into a post-pandemic group (Group A) and a pre-pandemic group (Group B). The clinicopathological factors, surgical procedures, and rates of post-operative complications were compared between the two groups using the Mann-Whitney U test and Chi-squared test. Results: A total of 167 patients were included in the study, of whom 119 (71.3%) were in Group A and 48 (28.7%) were in Group B. The two groups had similar clinicopathological features, including age (P=0.988), body mass index (P=0.504), and tumor, node, metastasis (TNM) stage (P=0.932). The Group A patients were more likely to receive single perforator DIEP flap transplantation than the Group B patients (n=28, 22.8% vs. n=3, 5.8%, P=0.007). There was a numerical decrease in the mean operating time of Group A patients compared to Group B patients (9.82 vs. 10.12 hours, P=0.172). The mean length of stay after the surgery was significantly shorter after the pandemic than before the pandemic (11.2 vs. 14.3 days, P<0.001). The complication rates between the two groups were similar. Conclusions: This study provides evidence that resuming DIEP reconstruction is safe in the post-COVID-19 era.