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.

Stabilizing Zinc Anode through Ion Selection Sieving for Aqueous Zn-Ion Batteries.

Uncontrollable dendrite growth and corrosion induced by reactive water molecules and sulfate ions (SO42-) seriously hindered the practical application of aqueous zinc ion batteries (AZIBs). Here we construct artificial solid electrolyte interfaces (SEIs) realized by sodium and calcium bentonite with a layered structure anchored to anodes (NB@Zn and CB@Zn). This artificial SEI layer functioning as a protective coating to isolate activated water molecules, provides high-speed transport channels for Zn2+, and serves as an ionic sieve to repel negatively charged anions while attracting positively charged cations. The theoretical results show that the bentonite electrodes exhibit a higher binding energy for Zn2+. This demonstrates that the bentonite protective layer enhances the Zn-ion deposition kinetics. Consequently, the NB@Zn//MnO2 and CB@Zn//MnO2 full-battery capacities are 96.7 and 70.4 mAh g-1 at 2.0 A g-1 after 1000 cycles, respectively. This study aims to stabilize Zn anodes and improve the electrochemical performance of AZIBs by ion-selection sieving.

Deciphering the role of cuproptosis-related lncRNAs in shaping the lung cancer immune microenvironment: A comprehensive prognostic model.

Cuproptosis plays an important role in cancer, but its role in lung cancer remains unknown. Transcriptional profiles, clinical details and mutation data were acquired from the Cancer Genome Atlas database through a variety of methods. The analysis of this publicly available data was comprehensively performed using R software along with its relevant packages, ensuring a thorough examination of the information. In this study, we conducted a detailed analysis of cuproptosis-related genes and lncRNA co-expression, identifying 129 relevant lncRNAs and establishing a prognostic model with four key lncRNAs (LINC00996, RPARP-AS1, SND1-IT1, TMPO-AS1). Utilizing data from TCGA and GEO databases, the model effectively categorized patients into high- and low-risk groups, showing significant survival differences. Correlation analysis highlighted specific relationships between individual lncRNAs and cuproptosis genes. Our survival analysis indicated a higher survival rate in the low-risk group across various cohorts. Additionally, the model's predictive accuracy was confirmed through independent prognostic analysis and ROC curve evaluations. Functional enrichment analysis revealed distinct biological pathways and immune functions between risk groups. Tumour mutation load analysis differentiated high- and low-risk groups by their mutation profiles. Drug sensitivity analysis and immune infiltration studies using the CIBERSORT algorithm further elucidated the potential treatment responses in different risk groups. This comprehensive evaluation underscores the significance of lncRNAs in cuproptosis and their potential as biomarkers for lung cancer prognosis and immune microenvironment.

Chemerin in caudal division of nucleus tractus solitarius increases sympathetic activity and blood pressure.

Chemerin is an adipokine that contributes to metabolism regulation. Nucleus tractus solitarius (NTS) is the first relay station in the brain for accepting various visceral afferent activities for regulating cardiovascular activity. However, the roles of chemerin in the NTS in regulating sympathetic activity and blood pressure are almost unknown. This study aimed to determine the role and potential mechanism of chemerin in the NTS in modulating sympathetic outflow and blood pressure. Bilateral NTS microinjections were performed in anaesthetized adult male Sprague-Dawley rats. Renal sympathetic nerve activity (RSNA), mean arterial pressure (MAP) and heart rate (HR) were continuously recorded. Chemerin and its receptor chemokine-like receptor 1 (CMKLR1) were highly expressed in caudal NTS (cNTS). Microinjection of chemerin-9 to the cNTS increased RSNA, MAP and HR, which were prevented by CMKLR1 antagonist α-NETA, superoxide scavenger tempol or N-acetyl cysteine, nicotinamide adenine dinucleotide phosphate (NADPH) oxidase inhibitors diphenyleneiodonium or apocynin. Chemerin-9 increased superoxide production and NADPH oxidase activity in the cNTS. The increased superoxide production induced by chemerin-9 was inhibited by α-NETA. The effects of cNTS microinjection of chemerin-9 on the RSNA, MAP and HR were attenuated by the pretreatment with paraventricular nucleus (PVN) microinjection of NMDA receptor antagonist MK-801 rather than AMPA/kainate receptor antagonist CNQX. These results indicate that chemerin-9 in the NTS increases sympathetic outflow, blood pressure and HR via CMKLR1-mediated NADPH oxidase activation and subsequent superoxide production in anaesthetized normotensive rats. Glutamatergic inputs in the PVN are needed for the chemerin-9-induced responses.

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).

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing ischemic changes in acute ischemic stroke using non-contrast computed tomography (NCCT), is often interpreted relying on expert experience and can vary between readers. This study aimed to develop a clinically applicable automatic ASPECTS system employing deep learning (DL). METHODS: This study enrolled 1987 NCCT scans that were retrospectively collected from four centers between January 2017 and October 2021. A DL-based system for automated ASPECTS assessment was trained on a development cohort (N = 1767) and validated on an independent test cohort (N = 220). The consensus of experienced physicians was regarded as a reference standard. The validity and reliability of the proposed system were assessed against physicians' readings. A real-world prospective application study with 13,399 patients was used for system validation in clinical contexts. RESULTS: The DL-based system achieved an area under the receiver operating characteristic curve (AUC) of 84.97% and an intraclass correlation coefficient (ICC) of 0.84 for overall-level analysis on the test cohort. The system's diagnostic sensitivity was 94.61% for patients with dichotomized ASPECTS at a threshold of ≥ 6, with substantial agreement (ICC = 0.65) with expert ratings. Combining the system with physicians improved AUC from 67.43 to 89.76%, reducing diagnosis time from 130.6 ± 66.3 s to 33.3 ± 8.3 s (p < 0.001). During the application in clinical contexts, 94.0% (12,591) of scans successfully processed by the system were utilized by clinicians, and 96% of physicians acknowledged significant improvement in work efficiency. CONCLUSION: The proposed DL-based system could accurately and rapidly determine ASPECTS, which might facilitate clinical workflow for early intervention. CLINICAL RELEVANCE STATEMENT: The deep learning-based automated ASPECTS evaluation system can accurately and rapidly determine ASPECTS for early intervention in clinical workflows, reducing processing time for physicians by 74.8%, but still requires validation by physicians when in clinical applications. KEY POINTS: The deep learning-based system for ASPECTS quantification has been shown to be non-inferior to expert-rated ASPECTS. This system improved the consistency of ASPECTS evaluation and reduced processing time to 33.3 seconds per scan. 94.0% of scans successfully processed by the system were utilized by clinicians during the prospective clinical application.

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.

Adaptive Weighted Data Fusion for Line Structured Light and Photometric Stereo Measurement System.

Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.

Deep learning reconstruction for coronary CT angiography in patients with origin anomaly, stent or bypass graft.

PURPOSE: To develop and validate a deep learning (DL)-model for automatic reconstruction for coronary CT angiography (CCTA) in patients with origin anomaly, stent or bypass graft. MATERIAL AND METHODS: In this retrospective study, a DL model for automatic CCTA reconstruction was developed with training and validation sets from 6063 and 1962 patients. The algorithm was evaluated on an independent external test set of 812 patients (357 with origin anomaly or revascularization, 455 without). The image quality of DL reconstruction and manual reconstruction (using dedicated cardiac reconstruction software provided by CT vendors) was compared using a 5-point scale. The successful reconstruction rates and post-processing time for two methods were recorded. RESULTS: In the external test set, 812 patients (mean age, 64.0 ± 11.6, 100 with origin anomalies, 152 with stents, 105 with bypass grafts) were evaluated. The successful rates for automatic reconstruction were 100% (455/455), 97% (97/100), 100% (152/152), and 76.2% (80/105) in patients with native vessel, origin anomaly, stent, and bypass graft, respectively. The image quality scores were significantly higher for DL reconstruction than those for manual approach in all subgroups (4 vs. 3 for native vessel, 4 vs. 4 for origin anomaly, 4 vs. 3 for stent and 4 vs. 3 for bypass graft, all p < 0.001). The overall post-processing time was remarkably reduced for DL reconstruction compared to manual method (11 s vs. 465 s, p < 0.001). CONCLUSIONS: The developed DL model enabled accurate automatic CCTA reconstruction of bypass graft, stent and origin anomaly. It significantly reduced post-processing time and improved clinical workflow.

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.