Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has high relapse and low 5-year survival rates. Single-cell profiling in relapsed HCC may aid in the design of effective anticancer therapies, including immunotherapies. We profiled the transcriptomes of ∼17,000 cells from 18 primary or early-relapse HCC cases. Early-relapse tumors have reduced levels of regulatory T cells, increased dendritic cells (DCs), and increased infiltrated CD8+ T cells, compared with primary tumors, in two independent cohorts. Remarkably, CD8+ T cells in recurrent tumors overexpressed KLRB1 (CD161) and displayed an innate-like low cytotoxic state, with low clonal expansion, unlike the classical exhausted state observed in primary HCC. The enrichment of these cells was associated with a worse prognosis. Differential gene expression and interaction analyses revealed potential immune evasion mechanisms in recurrent tumor cells that dampen DC antigen presentation and recruit innate-like CD8+ T cells. Our comprehensive picture of the HCC ecosystem provides deeper insights into immune evasion mechanisms associated with tumor relapse.

GLP-1 in the Hypothalamic Paraventricular Nucleus Promotes Sympathetic Activation and Hypertension.

Glucagon-like peptide-1 (GLP-1) and its analogs are widely used for diabetes treatment. The paraventricular nucleus (PVN) is crucial for regulating cardiovascular activity. This study aims to determine the roles of GLP-1 and its receptors (GLP-1R) in the PVN in regulating sympathetic outflow and blood pressure. Experiments were carried out in male normotensive rats and spontaneously hypertensive rats (SHR). Renal sympathetic nerve activity (RSNA) and mean arterial pressure (MAP) were recorded. GLP-1 and GLP-1R expressions were present in the PVN. PVN microinjection of GLP-1R agonist recombinant human GLP-1 (rhGLP-1) or EX-4 increased RSNA and MAP, which were prevented by GLP-1R antagonist exendin 9-39 (EX9-39) or GLP-1R antagonist 1, superoxide scavenger tempol, antioxidant N-acetylcysteine, NADPH oxidase (NOX) inhibitor apocynin, adenylyl cyclase (AC) inhibitor SQ22536 or protein kinase A (PKA) inhibitor H89. PVN microinjection of rhGLP-1 increased superoxide production, NADPH oxidase activity, cAMP level, AC, and PKA activity, which were prevented by SQ22536 or H89. GLP-1 and GLP-1R were upregulated in the PVN of SHR. PVN microinjection of GLP-1 agonist increased RSNA and MAP in both WKY and SHR, but GLP-1 antagonists caused greater effects in reducing RSNA and MAP in SHR than in WKY. The increased superoxide production and NADPH oxidase activity in the PVN of SHR were augmented by GLP-1R agonists but attenuated by GLP-1R antagonists. These results indicate that activation of GLP-1R in the PVN increased sympathetic outflow and blood pressure via cAMP-PKA-mediated NADPH oxidase activation and subsequent superoxide production. GLP-1 and GLP-1R upregulation in the PVN partially contributes to sympathetic overactivity and hypertension.

Methylation of GPRC5A promotes liver metastasis and docetaxel resistance through activating mTOR signaling pathway in triple negative breast cancer.

AIMS: This study aims to explore the function and mechanism of G Protein-coupled receptor class C group 5 member A (GPRC5A) in docetaxel-resistance and liver metastasis of breast cancer. METHODS: Single-cell RNA transcriptomic analysis and bioinformatic analysis are used to screen relevant genes in breast cancer metastatic hepatic specimens. MeRIP, dual-luciferase analysis and bioinformation were used to detect m6A modulation. Mass spectrometry (MS), co-inmunoprecipitation (co-IP) and immunofluorescence colocalization were executed to explore the mechanism of GPRC5A in breast cancer cells. RESULT: GPRC5A was upregulated in triple-negative breast cancer (TNBC) and was associated with a poor prognosis. In vitro and in vivo experiments demonstrated that knockdown of GPRC5A alleviated metastasis and resistance to docetaxel in TNBC. Overexpression of GPRC5A had the opposite effects. The m6A methylation of GPRC5A mRNA was modulated by METTL3 and YTHDF1, which facilitates its translation. GPRC5A inhibited the ubiquitination-dependent degradation of LAMTOR1, resulting in the recruitment of mTORC1 to lysosomes and activating the mTORC1/p70s6k signaling pathway. CONCLUSION: METTL3/YTHDF1 axis up-regulates GPRC5A expression by m6A methylation. GPRC5A activates mTORC1/p70s6k signaling pathway by recruiting mTORC1 to lysosomes, consequently promotes docetaxel-resistance and liver metastasis.

Nanoarchitectonic Engineering of Thermal-Responsive Magnetic Nanorobot Collectives for Intracranial Aneurysm Therapy.

Stent-assisted coiling is a main treatment modality for intracranial aneurysms (IAs) in clinics, but critical challenges remain to be overcome, such as exogenous implant-induced stenosis and reliance on antiplatelet agents. Herein, an endovascular approach is reported for IA therapy without stent grafting or microcatheter shaping, enabled by active delivery of thrombin (Th) to target aneurysms using innovative phase-change material (PCM)-coated magnetite-thrombin (Fe3O4-Th@PCM) FTP nanorobots. The nanorobots are controlled by an integrated actuation system of dynamic torque-force hybrid magnetic fields. With robust intravascular navigation guided by real-time ultrasound imaging, nanorobotic collectives can effectively accumulate and retain in model aneurysms constructed in vivo, followed by controlled release of the encapsulated Th for rapid occlusion of the aneurysm upon melting the protective PCM (thermally responsive in a tunable manner) through focused magnetic hyperthermia. Complete and stable aneurysm embolization is confirmed by postoperative examination and 2-week postembolization follow-up using digital subtraction angiography (DSA), contrast-enhanced ultrasound (CEUS), and histological analysis. The safety of the embolization therapy is assessed through biocompatibility evaluation and histopathology assays. This strategy, seamlessly integrating secure drug packaging, agile magnetic actuation, and clinical interventional imaging, avoids possible exogenous implant rejection, circumvents cumbersome microcatheter shaping, and offers a promising option for IA therapy.

Impact of NDUFAF6 on breast cancer prognosis: linking mitochondrial regulation to immune response and PD-L1 expression.

BACKGROUND: Breast cancer is a major global health concern, and there is a continuous search for novel biomarkers to predict its prognosis. The mitochondrial protein NDUFAF6, previously studied in liver cancer, is now being investigated for its role in breast cancer. This study aims to explore the expression and functional significance of NDUFAF6 in breast cancer using various databases and experimental models. METHODS: We analyzed breast cancer samples from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA) databases, supplemented with immunohistochemistry (IHC) staining to assess NDUFAF6 expression. A breast cancer cell xenograft mouse model was used to evaluate tumor growth, apoptosis, and NDUFAF6 expression. Survival probabilities were estimated through Kaplan-Meier plots and Cox regression analysis. A Protein-Protein Interaction (PPI) network was constructed, and differentially expressed genes related to NDUFAF6 were analyzed using GO, KEGG, and GSEA. The relationship between NDUFAF6 expression, immune checkpoints, and immune infiltration was also evaluated. RESULTS: NDUFAF6 was found to be overexpressed in breast cancer patients and in the xenograft mouse model. Its expression correlated with worse clinical features and prognosis. NDUFAF6 expression was an independent predictor of breast cancer outcomes in both univariate and multivariate analyses. Functionally, NDUFAF6 is implicated in several immune-related pathways. Crucially, NDUFAF6 expression correlated with various immune infiltrating cells and checkpoints, particularly promoting PD-L1 expression by inhibiting the NRF2 signaling pathway. CONCLUSION: The study establishes NDUFAF6 as a potential prognostic biomarker in breast cancer. Its mechanism of action, involving the inhibition of NRF2 to upregulate PD-L1, highlights its significance in the disease's progression and potential as a target for immunotherapy.

Associations of MRI-Derived Glymphatic System Impairment With Global White Matter Damage and Cognitive Impairment in Mild Traumatic Brain Injury: A DTI-ALPS Study.

BACKGROUND: Assessing the glymphatic function using diffusion tensor image analysis along the perivascular space (DTI-ALPS) may be helpful for mild traumatic brain injury (mTBI) management. PURPOSE: To assess glymphatic function using DTI-ALPS and its associations with global white matter damage and cognitive impairment in mTBI. STUDY TYPE: Prospective. POPULATION: Thirty-four controls (44.1% female, mean age 49.2 years) and 58 mTBI subjects (43.1% female, mean age 48.7 years), including uncomplicated mTBI (N = 32) and complicated mTBI (N = 26). FIELD STRENGTH/SEQUENCE: 3-T, single-shot echo-planar imaging sequence. ASSESSMENT: Magnetic resonance imaging (MRI) was done within 1 month since injury. DTI-ALPS was performed to assess glymphatic function, and peak width of skeletonized mean diffusivity (PSMD) was used to assess global white matter damage. Cognitive tests included Auditory Verbal Learning Test and Digit Span Test (forward and backward). STATISTICAL TESTS: Neuroimaging findings comparisons were done between mTBI and control groups. Partial correlation and multivariable linear regression assessed the associations between DTI-ALPS, PSMD, and cognitive impairment. Mediation effects of PSMD on the relationship between DTI-ALPS and cognitive impairment were explored. P-value <0.05 was considered statistically significant, except for cognitive correlational analyses with a Bonferroni-corrected P-value set at 0.05/3 ≈ 0.017. RESULTS: mTBI showed lower DTI-ALPS and higher PSMD, especially in complicated mTBI. DTI-ALPS was significantly correlated with verbal memory (r = 0.566), attention abilities (r = 0.792), executive function (r = 0.618), and PSMD (r = -0.533). DTI-ALPS was associated with verbal memory (ß = 8.77, 95% confidence interval [CI] 5.00, 12.54), attention abilities (ß = 5.67, 95% CI 4.56, 6.97), executive function (ß = 2.34, 95% CI 1.49, 3.20), and PSMD (ß = -0.79, 95% CI -1.15, -0.43). PSMD mediated 46.29%, 20.46%, and 24.36% of the effects for the relationship between DTI-ALPS and verbal memory, attention abilities, and executive function. DATA CONCLUSION: Glymphatic function may be impaired in mTBI reflected by DTI-ALPS. Glymphatic dysfunction may cause cognitive impairment related to global white matter damage after mTBI. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Cardiomyocyte-specific Peli1 contributes to the pressure overload-induced cardiac fibrosis through miR-494-3p-dependent exosomal communication.

Cardiac fibrosis is an essential pathological process in pressure overload (PO)-induced heart failure. Recently, myocyte-fibroblast communication is proven to be critical in heart failure, in which, pathological growth of cardiomyocytes (CMs) may promote fibrosis via miRNAs-containing exosomes (Exos). Peli1 regulates the activation of NF-κB and AP-1, which has been demonstrated to engage in miRNA transcription in cardiomyocytes. Therefore, we hypothesized that Peli1 in CMs regulates the activation of cardiac fibroblasts (CFs) through an exosomal miRNA-mediated paracrine mechanism, thereby promoting cardiac fibrosis. We found that CM-conditional deletion of Peli1 improved PO-induced cardiac fibrosis. Moreover, Exos from mechanical stretch (MS)-induced WT CMs (WT MS-Exos) promote activation of CFs, Peli1-/- MS-Exos reversed it. Furthermore, miRNA microarray and qPCR analysis showed that miR-494-3p was increased in WT MS-Exos while being down regulated in Peli1-/- MS-Exos. Mechanistically, Peli1 promoted miR-494-3p expression via NF-κB/AP-1 in CMs, and then miR-494-3p induced CFs activation by inhibiting PTEN and amplifying the phosphorylation of AKT, SMAD2/3, and ERK. Collectively, our study suggests that CMs Peli1 contributes to myocardial fibrosis via CMs-derived miR-494-3p-enriched exosomes under PO, and provides a potential exosomal miRNA-based therapy for cardiac fibrosis.

Evaluating Oral Probiotic Supplements as Complementary Treatment in Advanced Lung Cancer Patients Receiving ICIs: A Prospective Real-World Study.

OBJECTIVE: To evaluate the effectiveness of oral probiotic supplements in patients undergoing immune checkpoint inhibitors (ICIs) for the treatment of advanced lung cancer. METHODS: This prospective real-world study enrolled patients with advanced lung cancer who were receiving ICIs as part of their treatment. The patients were divided into 2 groups: Group OPS received oral probiotic supplements along with ICIs, while Group C did not. The primary endpoint was progression-free survival (PFS). The secondary outcome measure was the objective response rate (ORR). RESULTS: A total of 253 patients were included in the study, with 71 patients in Group OPS and 182 patients in the control group (Group C). No significant differences were observed in the median PFS between the 2 groups for all patients. However, for small cell lung cancer (SCLC) patients, the median PFS was significantly better in the Group OPS compared to the Group C (11.1 months vs 7.0 months, P = .049). No significant differences were observed in median PFS for the non-small cell lung cancer (NSCLC) cohort between the 2 groups, but a trend towards better median PFS in Group OPS was noticed (16.5 months vs 12.3 months, P = .56). The ORR for the entire cohort was 58.0%. CONCLUSION: Oral probiotics supplements in combination with ICIs included regimen may improve the outcome in patients with advanced SCLC. The above points should be proved by further study.

This study examined whether the addition of oral probiotic supplements to ICIs could enhance the treatment of advanced lung cancer. A total of 253 patients with advanced lung cancer were involved in the study, with some receiving probiotics in combination with ICIs and others not. The findings revealed that patients with SCLC who took probiotics had significantly better PFS compared to those who did not. Additionally, there was a tendency towards enhanced PFS in NSCLC patients who received probiotics. In conclusion, the study indicates that incorporating oral probiotics with ICIs may lead to better outcomes for patients with advanced SCLC, although further research is necessary to validate these results.This real world study explores whether oral probiotic supplements along with immune checkpoint inhibitors (ICIs) can help treat advanced lung cancer. The study included 253 patients with advanced lung cancer receiving ICIs treatment, part of them taking probiotics along with ICIs. The results showed that patients with small cell lung cancer (SCLC) who took probiotics had better progression-free survival (PFS) compared to those who didn't. There was also a trend towards better PFS in non-small cell lung cancer (NSCLC) patients who took probiotics. Overall, the study suggests that taking oral probiotics along with ICIs may improve outcomes for patients with advanced SCLC, but more research is needed to confirm these findings.

A dual-energy computed tomography-based radiomics nomogram for predicting time since stroke onset: a multicenter study.

OBJECTIVES: We aimed to develop and validate a radiomics nomogram based on dual-energy computed tomography (DECT) images and clinical features to classify the time since stroke (TSS), which could facilitate stroke decision-making. MATERIALS AND METHODS: This retrospective three-center study consecutively included 488 stroke patients who underwent DECT between August 2016 and August 2022. The eligible patients were divided into training, test, and validation cohorts according to the center. The patients were classified into two groups based on an estimated TSS threshold of ≤ 4.5 h. Virtual images optimized the visibility of early ischemic lesions with more CT attenuation. A total of 535 radiomics features were extracted from polyenergetic, iodine concentration, virtual monoenergetic, and non-contrast images reconstructed using DECT. Demographic factors were assessed to build a clinical model. A radiomics nomogram was a tool that the Rad score and clinical factors to classify the TSS using multivariate logistic regression analysis. Predictive performance was evaluated using receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA) was used to compare the clinical utility and benefits of different models. RESULTS: Twelve features were used to build the radiomics model. The nomogram incorporating both clinical and radiomics features showed favorable predictive value for TSS. In the validation cohort, the nomogram showed a higher AUC than the radiomics-only and clinical-only models (AUC: 0.936 vs 0.905 vs 0.824). DCA demonstrated the clinical utility of the radiomics nomogram model. CONCLUSIONS: The DECT-based radiomics nomogram provides a promising approach to predicting the TSS of patients. CLINICAL RELEVANCE STATEMENT: The findings support the potential clinical use of DECT-based radiomics nomograms for predicting the TSS. KEY POINTS: Accurately determining the TSS onset is crucial in deciding a treatment approach. The radiomics-clinical nomogram showed the best performance for predicting the TSS. Using the developed model to identify patients at different times since stroke can facilitate individualized management.

Clot-based time attenuation curve as a novel imaging predictor of mechanical thrombectomy functional outcome in acute ischemia stroke.

OBJECTIVES: To investigate whether a novel assessment of thrombus permeability obtained from perfusion computed tomography (CTP) can act as a more accurate predictor of clinical response to mechanical thrombectomy (MT) in acute ischemic stroke (AIS). MATERIALS AND METHODS: We performed a study including two cohorts of AIS patients who underwent MT admitted to a single-center between April 2018 and February 2022: a retrospective development cohort (n = 71) and a prospective independent validation cohort (n = 96). Thrombus permeability was determined in terms of entire thrombus time-attenuation curve (TAC) on CTP. Association between thrombus TAC distributions and histopathological results was analyzed in the development cohort. Logistic regression was used to assess the performance of the TAC for predicting 90-day modified Rankin Scale (mRS) score, and good outcome was defined as a mRS score of ≤ 2. Basic clinical characteristics was used to build a routine clinical model. A combined model gathered TAC and basic clinical characteristics was also developed. The performance of the three models is compared on the independent validation set. RESULTS: Two TAC distributions were observed-unimodal (uTAC) and linear (lTAC). TAC distributions achieved strong correlations (|r|= 0.627, p < 0.001) with histopathological results, in which uTAC associated with fibrin- and platelet-rich clot while lTAC associated with red blood cell-rich clot. The uTAC was independently associated with poor outcome (odds ratio, 0.08 [95% confidence interval (CI), 0.02-0.31]; p < 0.001). TAC distributions yielded an AUC of 0.78 (95% CI, 0.70-0.87) for predicting clinical outcome. When combined clinical characteristics, the performance was significantly improved (AUC, 0.85 [95% CI, 0.76-0.93]; p < 0.001) and higher than routine clinical model (AUC, 0.69 [95% CI, 0.59-0.83]; p < 0.001). CONCLUSIONS: Thrombus TAC on CTP were found to be a promising new imaging biomarker to predict the outcomes of MT in AIS. CLINICAL RELEVANCE STATEMENT: This study revealed that clot-based time attenuation curve based on admission perfusion CT could reflect the permeability and composition of thrombus and, also, provide valuable information to predict the clinical outcomes of mechanical thrombectomy in patients with acute ischemia stroke. KEY POINTS: • Two time-attenuation curves distributions achieved strong correlations (|r|= 0.627, p < 0.001) with histopathological results. • The unimodal time-attenuation curve was independently associated with poor outcome (odds ratio, 0.08 [0.02-0.31]; p < 0.001). • The time-attenuation curve distributions yielded a higher performance for detecting clinical outcome than routine clinical model (AUC, 0.78 [0.70-0.87] vs 0.69 [0.59-0.83]; p < 0.001).

SPACA6P-AS: a trailblazer in breast cancer pathobiology and therapeutics.

OBJECTIVE: The primary objective of this investigation is to delve into the involvement of the long noncoding RNA (lncRNA) SPACA6P-AS in breast cancer (BC) development, focusing on its expression pattern, association with clinical-pathological features, impact on prognosis, as well as its molecular and immunological implications. METHODS: Bioinformatics analysis was conducted utilizing RNA sequencing data of 1083 BC patients from the TCGA database. Functional exploration of SPACA6P-AS was carried out through the construction of survival curves, GO and KEGG enrichment analysis, and single-sample gene set enrichment analysis (ssGSEA). Furthermore, its functionality was validated through in vitro cell experiments and in vivo nude mouse model experiments. RESULTS: SPACA6P-AS showed a remarkable increase in expression levels in BC tissues (p < 0.001) and demonstrated a close relationship to poor prognosis (overall survival HR = 1.616, progression-free interval HR = 1.40, disease-specific survival HR = 1.54). Enrichment analysis revealed that SPACA6P-AS could impact biological functions such as protease regulation, endopeptidase inhibitor activity, taste receptor activity, taste transduction, and maturity-onset diabetes of the young pathway. ssGSEA analysis indicated a negative correlation between SPACA6P-AS expression and immune cell infiltration like dendritic cells and neutrophils, while a positive correlation was observed with central memory T cells and T helper 2 cells. Results from in vitro and in vivo experiments illustrated that silencing SPACA6P-AS significantly inhibited the proliferation, migration, and invasion capabilities of BC cells. In vitro experiments also highlighted that dendritic cells with silenced SPACA6P-AS exhibited enhanced capabilities in promoting the proliferation of autologous CD3 + T cells and cytokine secretion. These discoveries elucidate the potential multifaceted roles of SPACA6P-AS in BC, including its potential involvement in modulating immune cell infiltration in the tumor microenvironment. CONCLUSION: The high expression of lncRNA SPACA6P-AS in BC is closely linked to poor prognosis and may facilitate tumor progression by influencing specific biological processes, signaling pathways, and the immune microenvironment. The regulatory role of SPACA6P-AS positions it as a prospective biomarker and target for therapeutic approaches for BC diagnosis and intervention.

Relationship between muscle and subcutaneous adipose tissue size and density and proximal femur bone in elderly women with hip fracture.

BACKGROUND: Both osteoporosis and sarcopenia are associated with aging, increasing the likelihood of falls in older adults and consequently raising the risk of hip fractures (HF). AIMS: To explore the relationship between the size and density of muscle and subcutaneous adipose tissue (SAT) and the bone mineral density (BMD) of the proximal femur in elderly women with HF. METHODS: Quantitative computed tomography (QCT) was conducted on the hips of 661 female participants who experienced low-energy acute HFs to measure both areal BMD (aBMD) and volume BMD (vBMD). Measurements were taken for the cross-sectional area (CSA) and density of the muscle around the hip and adjacent SAT. Multivariable linear regression models were applied to assess the relationship between these parameters. RESULTS: Most increases in the density of the gluteus medius and minimus muscle (G.Med/MinM) were correlated with higher BMD in the femoral neck fracture (FNF) group with osteoporosis. In the FNF group, gluteus maximus muscle (G.MaxM) density was negatively associated with the BMD parameters of the proximal femur in individuals with osteoporosis, while they were positively associated with nonosteoporosis. In the intertrochanteric fracture (ITF) group without osteoporosis, both FN aBMD and FN vBMD showed significant correlations with G.Med/MinM density. DISCUSSION: In women with HFs, bone and muscle are closely related. CONCLUSIONS: In older women with HFs, density but not CSA of the G.Med/MinM were associated with BMD parameters of the proximal femur. Osteoporosis may influence the relationship between G.MaxM density and proximal femur BMD in elderly women with FNF.

How Integrated Digital Tools Can Improve Tuberculosis Medication Adherence: A Longitudinal Study in China.

Background: Poor medication adherence remains one of the major problems in the treatment of tuberculosis (TB) patients, while digital technologies have been proven effective to improve the treatment results. However, reports on the effectiveness of comprehensive practice integrating different intervention methods and technologies are limited. The aim of this study is to evaluate the effectiveness of an integrated digital adherence intervention for TB patients. Methods: We developed a digital adherence intervention platform integrating instant WeChat message, electronic medication monitors (EMMs), and manual reminders. The primary goal of the platform was to improve the accessibility of digital adherence technologies, and thus improve treatment adherence. TB patients were newly diagnosed at 10 TB-designated hospitals and came from 220 communities, from January to June 2022. The basic characteristics and treatment adherence of TB patients in WeChat, EMM, and conventional groups were compared, and the influencing factors of high medication adherence were analyzed by logistic regression. Results: A total of 2,498 TB patients were enrolled in the study, 14.5% were managed by digital technologies, 9.5% by WeChat, and 5.0% by EMM, respectively. After intervention, the median medication rate of TB patients was significantly higher in the WeChat group (95.3%) and EMM group (95.7%) compared with that of the conventional group (83.8%). On the contrary, the median number of missed medications among patients of the conventional group (nine times) was significantly higher than that in the WeChat (three times) group and EMM (three times) group. The proportion of high adherence (adherence medication rate ≥90%) among TB patients was 64.7%, 64.5%, and 43.2% in WeChat, EMM, and conventional group, respectively. Conclusions: The application of the integrated digital adherence intervention platform could significantly improve medication adherence among TB patients. The accessibility of digital adherence technologies could be improved by integrating complementary technologies in practice.

[Ischemic stroke infarct segmentation model based on depthwise separable convolution for multimodal magnetic resonance imaging].

Magnetic resonance imaging (MRI) plays a crucial role in the diagnosis of ischemic stroke. Accurate segmentation of the infarct is of great significance for selecting intervention treatment methods and evaluating the prognosis of patients. To address the issue of poor segmentation accuracy of existing methods for multiscale stroke lesions, a novel encoder-decoder architecture network based on depthwise separable convolution is proposed. Firstly, this network replaces the convolutional layer modules of the U-Net with redesigned depthwise separable convolution modules. Secondly, an modified Atrous spatial pyramid pooling (MASPP) is introduced to enlarge the receptive field and enhance the extraction of multiscale features. Thirdly, an attention gate (AG) structure is incorporated at the skip connections of the network to further enhance the segmentation accuracy of multiscale targets. Finally, Experimental evaluations are conducted using the ischemic stroke lesion segmentation 2022 challenge (ISLES2022) dataset. The proposed algorithm in this paper achieves Dice similarity coefficient (DSC), Hausdorff distance (HD), sensitivity (SEN), and precision (PRE) scores of 0.816 5, 3.668 1, 0.889 2, and 0.894 6, respectively, outperforming other mainstream segmentation algorithms. The experimental results demonstrate that the method in this paper effectively improves the segmentation of infarct lesions, and is expected to provide a reliable support for clinical diagnosis and treatment.

Identification of the novel markers of PPAR signalling affecting immune microenvironment and immunotherapy response of lung adenocarcinoma patients.

Peroxisome proliferator-activated receptors (PPARs) are essential for cellular physiological processes. However, there is less research on the PPAR-related genes in lung adenocarcinoma (LUAD). Open-access data were get from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases. All the analysis were conducted in the R software based on different R packages. In this study, we gauged the PPAR score employing a set of 72 PPAR-associated genes and probed the biological impact of this score on lung adenocarcinoma (LUAD). Subsequently, we established a unique signature composed of eight PPAR-related genes (ANGPTL4, ACSL3, ADIPOQ, FABP1, SLC27A1, ACOX2, PPARD and OLR1) to forecast the prognosis of LUAD. The signature's effectiveness in predicting survival was validated through the receiver operating characteristic curve in the TCGA-LUAD cohort. As per the pathway enrichment analysis, several crucial oncogenic pathways and metabolic processes were enriched in high-risk individuals. Further, we observed that these high-risk patients exhibited heightened genomic instability. Additionally, compared to the low-risk cohort, high-risk patients demonstrated diminished immune components and function. Intriguingly, high-risk patients exhibited a potential heightened sensitivity to immunotherapy and certain drugs, including Gefitinib, Afatinib, Erlotinib, IAP_5620, Sapitinib, LCL161, Lapatinib and AZD3759. The prognosis model based on eight PPAR-related genes has satisfactory prognosis prediction efficiency. Meanwhile, our results can provide direction for future studies in the relevant aspects.

Advancements in clinical aspects of targeted therapy and immunotherapy in breast cancer.

Breast cancer is the second leading cause of death for women worldwide. The heterogeneity of this disease presents a big challenge in its therapeutic management. However, recent advances in molecular biology and immunology enable to develop highly targeted therapies for many forms of breast cancer. The primary objective of targeted therapy is to inhibit a specific target/molecule that supports tumor progression. Ak strain transforming, cyclin-dependent kinases, poly (ADP-ribose) polymerase, and different growth factors have emerged as potential therapeutic targets for specific breast cancer subtypes. Many targeted drugs are currently undergoing clinical trials, and some have already received the FDA approval as monotherapy or in combination with other drugs for the treatment of different forms of breast cancer. However, the targeted drugs have yet to achieve therapeutic promise against triple-negative breast cancer (TNBC). In this aspect, immune therapy has come up as a promising therapeutic approach specifically for TNBC patients. Different immunotherapeutic modalities including immune-checkpoint blockade, vaccination, and adoptive cell transfer have been extensively studied in the clinical setting of breast cancer, especially in TNBC patients. The FDA has already approved some immune-checkpoint blockers in combination with chemotherapeutic drugs to treat TNBC and several trials are ongoing. This review provides an overview of clinical developments and recent advancements in targeted therapies and immunotherapies for breast cancer treatment. The successes, challenges, and prospects were critically discussed to portray their profound prospects.

Stabilizing Zn Metal Anode Through Regulation of Zn Ion Transfer and Interfacial Behavior with a Fast Ion Conductor Protective Layer.

Aqueous Zn-ion batteries (AZIBs) attract intensive attention owing to their environmental friendliness, cost-effectiveness, innate safety, and high specific capacity. However, the practical applications of AZIBs are hindered by several adverse phenomena, including corrosion, Zn dendrites, and hydrogen evolution. Herein, a Zn anode decorated with a 3D porous-structured Na3 V2 (PO4)3 (NVP@Zn) is obtained, where the NVP reconstruct the electrolyte/anode interface. The resulting NVP@Zn anode can provide a large quantity of fast and stable channels, facilitating enhanced Zn ion deposition kinetics and regulating the Zn ions transport process through the ion confinement effect. The NASICON-type NVP protective layer promote the desolvation process due to its nanopore structure, thus effectively avoiding side reactions. Theoretical calculations indicate that the NVP@Zn electrode has a higher Zn ion binding energy and a higher migration barrier, which demonstrates that NVP protective layer can enhance Zn ion deposition kinetics and prevent the unfettered 2D diffusion of Zn ions. Therefore, the results show that NVP@Zn/MnO2 full cell can maintain a high specific discharge capacity of 168 mAh g-1 and a high-capacity retention rate of 74.6% after cycling. The extraordinary results obtained with this strategy have confirmed the promising applications of NVP in high-performance AZIBs.

Assessment of automatic rib fracture detection on chest CT using a deep learning algorithm.

OBJECTIVES: To evaluate deep neural networks for automatic rib fracture detection on thoracic CT scans and to compare its performance with that of attending-level radiologists using a large amount of datasets from multiple medical institutions. METHODS: In this retrospective study, an internal dataset of 12,208 emergency room (ER) trauma patients and an external dataset of 1613 ER trauma patients taking chest CT scans were recruited. Two cascaded deep neural networks based on an extended U-Net architecture were developed to segment ribs and detect rib fractures respectively. Model performance was evaluated with a 95% confidence interval (CI) on both the internal and external dataset, and compared with attending-level radiologist readings using t test. RESULTS: On the internal dataset, the AUC of the model for detecting fractures at per-rib level was 0.970 (95% CI: 0.968, 0.972) with sensitivity of 93.3% (95% CI: 92.0%, 94.4%) at a specificity of 98.4% (95% CI: 98.3%, 98.5%). On the external dataset, the model obtained an AUC of 0.943 (95% CI: 0.941, 0.945) with sensitivity of 86.2% (95% CI: 85.0%, 87.3%) at a specificity of 98.8% (95% CI: 98.7%, 98.9%), compared to the sensitivity of 70.5% (95% CI: 69.3%, 71.8%) (p < .0001) and specificity of 98.8% (95% CI: 98.7%, 98.9%) (p = 0.175) by attending radiologists. CONCLUSIONS: The proposed DL model is a feasible approach to identify rib fractures on chest CT scans, at the very least, reaching a level on par with attending-level radiologists. KEY POINTS: • Deep learning-based algorithms automatically detected rib fractures with high sensitivity and reasonable specificity on chest CT scans. • The performance of deep learning-based algorithms reached comparable diagnostic measures with attending level radiologists for rib fracture detection on chest CT scans. • The deep learning models, similar to human readers, were susceptible to the inconspicuity and ambiguity of target lesions. More training data was required for subtle lesions to achieve comparable detection performance.

Benign vs malignant vertebral compression fractures with MRI: a comparison between automatic deep learning network and radiologist's assessment.

OBJECTIVE: To test the diagnostic performance of a deep-learning Two-Stream Compare and Contrast Network (TSCCN) model for differentiating benign and malignant vertebral compression fractures (VCFs) based on MRI. METHODS: We tested a deep-learning system in 123 benign and 86 malignant VCFs. The median sagittal T1-weighted images (T1WI), T2-weighted images with fat suppression (T2WI-FS), and a combination of both (thereafter, T1WI/T2WI-FS) were used to validate TSCCN. The receiver operator characteristic (ROC) curve was analyzed to evaluate the performance of TSCCN. The accuracy, sensitivity, and specificity of TSCCN in differentiating benign and malignant VCFs were calculated and compared with radiologists' assessments. Intraclass correlation coefficients (ICCs) were tested to find intra- and inter-observer agreement of radiologists in differentiating malignant from benign VCFs. RESULTS: The AUC of the ROC plots of TSCCN according to T1WI, T2WI-FS, and T1WI/T2WI-FS images were 99.2%, 91.7%, and 98.2%, respectively. The accuracy of T1W, T2WI-FS, and T1W/T2WI-FS based on TSCCN was 95.2%, 90.4%, and 96.2%, respectively, greater than that achieved by radiologists. Further, the specificity of T1W, T2WI-FS, and T1W/T2WI-FS based on TSCCN was higher at 98.4%, 94.3%, and 99.2% than that achieved by radiologists. The intra- and inter-observer agreements of radiologists were 0.79-0.85 and 0.79-0.80 for T1WI, 0.65-0.72 and 0.70-0.74 for T2WI-FS, and 0.83-0.88 and 0.83-0.84 for T1WI/T2WI-FS. CONCLUSION: The TSCCN model showed better diagnostic performance than radiologists for automatically identifying benign or malignant VCFs, and is a potentially helpful tool for future clinical application. CLINICAL RELEVANCE STATEMENT: TSCCN-assisted MRI has shown superior performance in distinguishing benign and malignant vertebral compression fractures compared to radiologists. This technology has the value to enhance diagnostic accuracy, sensitivity, and specificity. Further integration into clinical practice is required to optimize patient management. KEY POINTS: • The Two-Stream Compare and Contrast Network (TSCCN) model showed better diagnostic performance than radiologists for identifying benign vs malignant vertebral compression fractures. • The processing of TSCCN is fast and stable, better than the subjective evaluation by radiologists in diagnosing vertebral compression fractures. • The TSCCN model provides options for developing a fully automated, streamlined artificial intelligence diagnostic tool.

Financial and clinical outcomes of CT myocardial perfusion imaging and coronary CT angiography-guided versus coronary CT angiography-guided strategy.

OBJECTIVES: To compare the financial and clinical outcomes of CT myocardial perfusion imaging (CT-MPI) + coronary CT angiography (CCTA)-guided versus CCTA-guided strategy in patients suspected of chronic coronary syndrome (CCS). MATERIALS AND METHODS: This study retrospectively included consecutive patients suspected of CCS and referred for CT-MPI+CCTA-guided and CCTA-guided treatment. The details of medical costs within 3 months after index imaging, including downstream invasive procedures, hospitalization, and medications, were recorded. All patients were followed up for major adverse cardiac events (MACE) at a median time of 22 months. RESULTS: A total of 1335 patients (559 in the CT-MPI+CCTA group and 776 in the CCTA group) were finally included. In the CT-MPI+CCTA group, 129 patients (23.1%) underwent ICA and 95 patients (17.0%) received revascularization. In the CCTA group, 325 patients (41.9%) underwent ICA whereas 194 patients (25.0%) received revascularization. An addition of CT-MPI in the evaluation strategy remarkably reduced the healthcare expenditure, compared with CCTA-guided strategy (USD 1441.36 vs. USD 232.91, p < 0.001). After adjustment for potential cofounders after inverse probability weighting, the CT-MPI+CCTA strategy was significantly associated with lower medical expenditure [adjusted cost ratio (95% CI) for total costs: 0.77 (0.65-0.91), p < 0.001]. In addition, there was no significant difference regarding the clinical outcome between the two groups (adjusted HR= 0.97; p = 0.878). CONCLUSIONS: CT-MPI+CCTA considerably reduced medical expenditures in patients suspected of CCS, compared to the CCTA strategy alone. Moreover, CT-MPI+CCTA led to a lower rate of invasive procedures with a similar long-term prognosis. CLINICAL RELEVANCE STATEMENT: CT myocardial perfusion imaging + coronary CT angiography-guided strategy reduced medical expenditure and invasive procedure rate. KEY POINTS: • CT-MPI+CCTA strategy yielded significantly lower medical expenditure than did the CCTA strategy alone in patients with suspected CCS. • After adjustment for potential confounders, the CT-MPI+CCTA strategy was significantly associated with lower medical expenditure. • No significant difference was observed regarding the long-term clinical outcome between the two groups.