Large-scale kinetic simulations of colliding plasmas within a hohlraum of indirect-drive inertial confinement fusion.

The National Ignition Facility has recently achieved successful burning plasma and ignition using the inertial confinement fusion (ICF) approach. However, there are still many fundamental physics phenomena that are not well understood, including the kinetic processes in the hohlraum. Shan et al. [Phys. Rev. Lett. 120, 195001 (2018)0031-900710.1103/PhysRevLett.120.195001] utilized the energy spectra of neutrons to investigate the kinetic colliding plasma in a hohlraum of indirect drive ICF. However, due to the typical large spatial-temporal scales, this experiment could not be well simulated by using available codes at that time. Utilizing our advanced high-order implicit PIC code, LAPINS, we were able to successfully reproduce the experiment on a large scale of both spatial and temporal dimensions, in which the original computational scale was increased by approximately seven to eight orders of magnitude. Not only is the validity of the explanation of the experiment confirmed by our simulations, i.e., the abnormally large width of neutron spectra comes from beam-target nuclear fusions, but also a different physical insight into the source of energetic deuterium ions is provided. The acceleration of deuterium ions can be categorized into two components: one is propelled by a sheath electric field created by the charge separation at the onset, while the other is a result of the reflection of the potential of the shock wave. The robustness of the acceleration mechanism is analyzed with varying initial conditions, e.g., temperatures, drifting velocity, and ion components. This paper might serve as a reference for benchmark simulations of upcoming simulation codes and may be relevant for future research on mixtures and entropy increments at plasma interfaces.

Analysis of clinicopathologic and imaging features of dual-phenotype hepatocellular carcinoma.

Dual-phenotype hepatocellular carcinoma (DPHCC) is a new subtype of hepatocellular carcinoma (HCC). This study aimed to investigate the relationship between the computerized tomography scan (CT) imaging and clinicopathologic features of DPHCC. The CT imaging and clinicopathologic data of 97 HCC cases who underwent radical resection were collected retrospectively. The CT imaging feature was evaluated by the ratio of the average CT value of tumor to liver (TLR) in the plain scan, arterial, portal vein and delayed phases. The association between CT imaging and clinicopathologic features was analyzed using the t-test or chi-square test. Univariate and multivariate recurrence-free survival (RFS) analysis and overall survival (OS) were performed. The positive rates of cytokeratin 7 (CK7) and CK19 were 35.1% and 20.6% respectively. The positive rate of CK19 was significantly higher in cases with age < 47 years (P = 0.005), tumor diameter > 4 cm (P = 0.016) or AFP ≥ 400 ng/ml (P = 0.007). The TLR in the portal vein phase was significantly lower in CK19 positive group (P = 0.024). The recurrence risk was significantly higher in cases with CK19 positive (HR: 2.17, 95% CI 1.16 to 4.04, P = 0.013), tumor diameter > 4 cm (HR: 2.05, 95% CI 1.11 to 3.78, P = 0.019), AFP ≥ 400 ng/ml (HR: 2.50, 95% CI 1.37 to 4.54, P = 0.002) or CA199 ≥ 37 U/ml (HR: 2.23, 95% CI 1.12 to 4.42, P = 0.020). However, imaging features, pathological subtype, CK7 or CK19 expression were not significantly related to HCC OS in the univariate and multivariate analysis (all P > 0.05). The expression of CK19 may be associated with the enhancement feature of the portal vein phase CT image, and CK19 positive may suggest a worse RFS.

Promoting Personalized Reminiscence Among Cognitively Intact Older Adults Through an AI-Driven Interactive Multimodal Photo Album: Development and Usability Study.

BACKGROUND: Reminiscence, a therapy that uses stimulating materials such as old photos and videos to stimulate long-term memory, can improve the emotional well-being and life satisfaction of older adults, including those who are cognitively intact. However, providing personalized reminiscence therapy can be challenging for caregivers and family members. OBJECTIVE: This study aimed to achieve three objectives: (1) design and develop the GoodTimes app, an interactive multimodal photo album that uses artificial intelligence (AI) to engage users in personalized conversations and storytelling about their pictures, encompassing family, friends, and special moments; (2) examine the app's functionalities in various scenarios using use-case studies and assess the app's usability and user experience through the user study; and (3) investigate the app's potential as a supplementary tool for reminiscence therapy among cognitively intact older adults, aiming to enhance their psychological well-being by facilitating the recollection of past experiences. METHODS: We used state-of-the-art AI technologies, including image recognition, natural language processing, knowledge graph, logic, and machine learning, to develop GoodTimes. First, we constructed a comprehensive knowledge graph that models the information required for effective communication, including photos, people, locations, time, and stories related to the photos. Next, we developed a voice assistant that interacts with users by leveraging the knowledge graph and machine learning techniques. Then, we created various use cases to examine the functions of the system in different scenarios. Finally, to evaluate GoodTimes' usability, we conducted a study with older adults (N=13; age range 58-84, mean 65.8 years). The study period started from January to March 2023. RESULTS: The use-case tests demonstrated the performance of GoodTimes in handling a variety of scenarios, highlighting its versatility and adaptability. For the user study, the feedback from our participants was highly positive, with 92% (12/13) reporting a positive experience conversing with GoodTimes. All participants mentioned that the app invoked pleasant memories and aided in recollecting loved ones, resulting in a sense of happiness for the majority (11/13, 85%). Additionally, a significant majority found GoodTimes to be helpful (11/13, 85%) and user-friendly (12/13, 92%). Most participants (9/13, 69%) expressed a desire to use the app frequently, although some (4/13, 31%) indicated a need for technical support to navigate the system effectively. CONCLUSIONS: Our AI-based interactive photo album, GoodTimes, was able to engage users in browsing their photos and conversing about them. Preliminary evidence supports GoodTimes' usability and benefits cognitively intact older adults. Future work is needed to explore its potential positive effects among older adults with cognitive impairment.

A radiomics model based on magnetic resonance imaging to predict cytokeratin 7/19 expression and liver fluke infection of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. HCC with liver fluke infection could harbor unique biological behaviors. This study was aimed at investigating radiomics features of HCC with liver fluke infection and establishing a model to predict the expression of cytokeratin 7 (CK7) and cytokeratin 19 (CK19) as well as prognosis at the same time. A total of 134 HCC patients were included. Gadoxetic acid-enhanced magnetic resonance imaging (MRI) images of all patients were acquired. Radiomics features of the tumor were extracted and then data dimensionality was reduced. The radiomics model was established to predict liver fluke infection and the radiomics score (Radscore) was calculated. There were 11 features in the four-phase combined model. The efficiency of the combined model increased significantly compared to each single-phase MRI model. Radscore was an independent predictor of liver fluke infection. It was also significantly different between different expression of CK7/ CK19. Meanwhile, liver fluke infection was associated with CK7/CK19 expression. A cut-off value was set up and all patients were divided into high risk and low risk groups of CK7/CK19 positive expression. Radscore was also an independent predictor of these two biomarkers. Overall survival (OS) and recurrence free survival (RFS) of negative liver fluke infection group were significantly better than the positive group. OS and RFS of negative CK7 and CK19 expression were also better, though not significantly. Positive liver fluke infection and CK19 expression prediction groups harbored significantly worse OS and RFS, survival of positive CK7 expression prediction was unsatisfying as well. A radiomics model was established to predict liver fluke infection among HCC patients. This model could also predict CK7 and CK19 expression. OS and RFS could be foreseen by this model at the same time.

The association of sickle cell disorder with adverse outcomes in COVID-19 patients: A meta-analysis.

The aim is to elucidate the relationship between sickle cell disorder and severe COVID-19. We systematically searched the required articles in three electronic databases, extracting and pooling effect sizes (ES) and 95% confidence interval (CI) from each eligible study to evaluate the effect of combined sickle cell disorder on adverse consequences in patients with COVID-19. This meta-analysis included 21 studies. Sickle cell disease (SCD) was a risk factor for mortality (pooled ES = 1.70, 95% CI: 1.00-2.92, p = 0.001), hospitalization (pooled ES = 6.21, 95% CI: 3.60-10.70, p = 0.000) and intensive care unit (ICU) admission (pooled ES = 2.29, 95% CI: 1.61-3.24, p = 0.099) in COVID-19 patients. Patients with SCD had an increased risk of respiratory failure/mechanical ventilation, but a statistical association was not found (pooled ES = 1.21, 95%CI: 0.74-1.98, p = 0.036). There was significant heterogeneity between SCD and death, hospitalization, and respiratory failure/mechanical ventilation. The results of meta-regression of SCD and hospitalization suggested that the tested variables including Area (p = 0.642), study design (p = 0.739), sample size (p = 0.397), proportion of males (p = 0.708), effect type (p = 0.723), whether confounding factors are adjusted (p = 0.606) might not be the source of heterogeneity. In addition, sickle cell trait (SCT) was significantly associated with the mortality (pooled ES = 1.54, 95% CI: 1.28-1.85, p = 0.771) and hospitalization (pooled ES = 1.20, 95% CI: 1.07-1.35，p = 0.519) in patients with COVID-19. But any increased risk of ICU admission/severe (pooled ES = 1.24, 95% CI: 0.95-1.62, p = 0.520) and mechanical ventilation (OR = 1.00, 95%CI:0.59-1.69) in COVID-19 patients with SCT was not observed. Sensitivity analysis demonstrated that the results were robust. The results of the funnel plot and Egger's test did not support the existence of publication bias. Current meta-analysis indicated that sickle cell disorder has a meaningful impact on COVID-19 progression to severe cases and associated deaths. However, further investigations and research to validate the current findings is indispensable.

ZXDC enhances cervical cancer metastasis through IGF2BP3-mediated activation of RhoA/ROCK signaling.

Metastasis in cervical cancer (CC) has a significant negative impact on patient survival, highlighting the urgent need for investigation in this area. In this study, we identified significant overexpression of zinc finger, X-linked, duplicated family member C (ZXDC) in CC tissue with metastasis, which correlates with poor outcomes for CC patients. We observed that overexpression of ZXDC promotes, while silencing of ZXDC inhibits the metastasis of CC cells both in vitro and in vivo. Additionally, our research demonstrated that ZXDC activated RhoA/ROCK signaling pathway, leading to enhanced cytoskeleton remodeling in CC cells. Besides, we found that IGF2BP3 plays an essential role in the activation of ZXDC on the RhoA/ROCK signaling pathway by stabilizing RhoA mRNA. These findings reveal a mechanism whereby ZXDC promotes the cervical cancer metastasis by targeting IGF2BP3/RhoA/ROCK pathway.

Correlation between ABO blood group and prognosis of hepatectomy for hepatitis B virus-associated hepatocellular carcinoma.

BACKGROUND: The relationship between ABO blood group and prognosis of patients with hepatocellular carcinoma (HCC) remains unclear. We investigated the relationship between prognosis and ABO blood group in patients with hepatitis B-associated HCC after radical hepatectomy. METHODS: The medical records of 874 patients with hepatitis B-associated HCC who underwent radical liver tumor resection were retrospectively collected. Cox proportional risk models were constructed for analysis, and the patient data were further balanced using propensity score matching (PSM) analysis to assess the impact of ABO blood group on the prognosis of patients with hepatitis B-associated HCC. RESULTS: In univariate Cox regression analysis, the overall survival (OS) of non-A blood type group vs. A blood type group [hazard ratio (HR) (95% confidence interval [CI]) = 1.504 (1.003-2.255), P = 0.048], in multivariate Cox regression analysis the OS of non-A blood type group versus A blood type group [HR (95% CI) = 1.596 (1.054-2.417), P = 0.027]. After PSM, the baseline information was more balanced between the two groups, yielding the same results as above [HR (95% CI) = 1.550 (1.012-2.373), P = 0.044]. CONCLUSION: The difference in OS after radical hepatectomy in patients with hepatitis B-associated HCC was statistically significant in terms of ABO blood group, OS was lower in patients with non-A blood group than in patients with A blood group.

Deep learn-based computer-assisted transthoracic echocardiography: approach to the diagnosis of cardiac amyloidosis.

Myocardial amyloidosis (CA) differs from other etiological pathologies of left ventricular hypertrophy in that transthoracic echocardiography is challenging to assess the texture features based on human visual observation. There are few studies on myocardial texture based on echocardiography. Therefore, this paper proposes an adaptive machine learning method based on ultrasonic image texture features to identify CA. In this retrospective study, a total of 289 participants (50 cases of myocardial amyloidosis; Hypertrophic cardiomyopathy: 70 cases; Uremic cardiomyopathy: 92 cases; Hypertensive heart disease: 77 cases). We extracted the myocardial ultrasonic imaging features of these patients and screened the features, and four models of random forest (RF), support vector machine (SVM), logistic regression (LR) and gradient decision-making lifting tree (GBDT) were established to distinguish myocardial amyloidosis from other diseases. Finally, the diagnostic efficiency of the model was evaluated and compared with the traditional ultrasonic diagnostic methods. In the overall population, the four machine learning models we established could effectively distinguish CA from nonCA diseases, AUC (RF 0.77, SVM 0.81, LR 0.81, GBDT 0.71). The LR model had the best diagnostic efficiency with recall, F1-score, sensitivity and specificity of 0.21, 0.34, 0.21 and 1.0, respectively. Slightly better than the traditional ultrasonic diagnosis model. In further subgroup analysis, the myocardial amyloidosis group was compared one-by-one with the patients with hypertrophic cardiomyopathy, uremic cardiomyopathy, and hypertensive heart disease groups, and the same method was used for feature extraction and data modeling. The diagnostic efficiency of the model was further improved. Notably, in identifying of the CA group and HHD group, AUC values reached more than 0.92, accuracy reached more than 0.87, sensitivity equal to or greater than 0.81, specificity 0.91, and F1 score higher than 0.84. This novel method based on echocardiography combined with machine learning may have the potential to be used in the diagnosis of CA.

Comprehensive analysis of LILR family genes expression and tumour-infiltrating immune cells in early-stage pancreatic ductal adenocarcinoma.

Leucocyte immunoglobulin-like receptors (LILRs) are closely related to tumourigenesis, but their clinical value in early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy remains unknown. Kaplan-Meier and Cox proportional hazards regression models is used to investigate the association between LILR expression and prognosis in tumour biopsies and peripheral blood mononuclear cells. Risk score was calculated for each patient based on the prognostic model. DAVID, STRING, GeneMANIA, and GSEA were used to conduct pathway and functional analyses. The CIBERSORT algorithm is used to analyse tumour-infiltrating immune cells. Survival analysis showed that high levels of LILRA4 (p = 0.006) and LILRB4 (p = 0.04) were significantly associated with better overall survival. High levels of LILRA2 (p = 0.008) and LILRB4 (p = 0.038) were significantly associated with better relapse-free survival. JAK-STAT signalling pathway, regulation of T cell activation, regulation of the immune effector process, and tumour necrosis factor superfamily cytokine production were involved in molecular mechanisms that affected poor prognoses in the high-risk group in GSEA. CIBERSORT demonstrated that the high-risk group had significantly higher infiltrating fraction of memory-activated CD4 T cells and activated NK cells and lower fraction of resting dendritic cells and neutrophils. LILRB4 plays crucial roles in affecting the clinical outcomes of early-stage PDAC.

Recurrence of Early Hepatocellular Carcinoma after Surgery May Be Related to Intestinal Oxidative Stress and the Development of a Predictive Model.

Background: Early stage hepatocellular carcinoma (HCC) has a high recurrence rate after surgery and lacks reliable predictive tools. We explored the potential of combining enhanced CT with gut microbiome to develop a predictive model for recurrence after early HCC surgery. Methods: A total of 112 patients with early HCC who underwent hepatectomy from September 2018 to December 2020 were included in this study, and the machine learning method was divided into a training group (N = 71) and a test group (N = 41) with the observed endpoint of recurrence-free survival (RFS). Features were extracted from the arterial and portal phases of enhanced computed tomography (CT) images and gut microbiome, and features with minimum absolute contraction and selection operator regression were created, and the extracted features were scored to create a preoperative prediction model by using the multivariate Cox regression analysis with risk stratification analysis. Results: In the study cohort, the model constructed by combining radiological and gut flora features provided good predictive performance (C index, 0.811 (0.650-0.972)). The combined radiology and gut flora-based model constructed risk strata with high, intermediate, or low risk of recurrence and different characteristics of recurrent tumor imaging and gut flora. Recurrence of early stage hepatocellular carcinoma may be associated with oxidative stress in the intestinal flora. Conclusions: This study successfully constructs a risk model integrating enhanced CT and gut microbiome characteristics that can be used for the risk of postoperative recurrence in patients with early HCC. In addition, intestinal flora associated with HCC recurrence may be involved in oxidative stress.

Biomimetic cytomembrane-coated ZIF-8-loaded DMDD nanoparticle and sonodynamic co-therapy for cancer.

Background: Breast cancer (BC) is the most common type of cancer affecting females. It is also a leading cause of cancer-related death in women worldwide. Methods: Sonodynamic therapy (SDT) is an emerging therapeutic strategy for cancer treatment. SDT ensures non-invasive penetration of deep tumors and results in activation of non-toxic sonosensitizers administered in deep tumor sites to become cytotoxic. It has been reported that 2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione (DMDD) has a significant anti-tumor effect against various cancer types including BC. However, DMDD is hydrophobic. Therefore, a one-step encapsulation method was used in the current study to construct zeolitic imidazole frameworks-8 (ZIF-8) loaded with DMDD and sonosensitizer chlorin e6 (Ce6). ZIF-8 was further modified by coating it with a biomimetic cell membrane to improve targeted delivery. Results: In vitro and in vivo results indicated that the nanomedicines had great biocompatibility properties and targeting ability. The nanocomposite exhibited a higher release rate under an acidic tumor microenvironment. The tumor killing effect of reactive oxygen species (ROS) generated from Ce6 and inhibition of tumor growth was enhanced after ultrasound (US) treatment, which might be caused by the increase in apoptosis rate. Conclusions: These findings show that the combination of nanomedicine and SDT provides a potential therapeutic method for BC.

A novel Peng's test in reducing bile leakage after partial hepatectomy for hepatocellular carcinoma: From an animal study to a clinical cohort Propensity score matching comparative study.

BACKGROUND: Bile leakage (BL) is a common complication of partial hepatectomy for hepatocellular carcinoma (HCC). However, various intraoperative approaches to detect BL have not been widely accepted owing to uncertainty in their treatment effectiveness and complexity of use. MATERIALS AND METHODS: A novel BL-detection approach (Peng's test) was developed in a swine model to determine the pressures generated in the gallbladder and common bile duct (CBD) during the test. A comparative study was then conducted on a prospective cohort of patients using Peng's test versus a retrospective historical cohort patient group using the White Gauze test in partial hepatectomy for HCC. Propensity score matching (PSM) was performed in a 1:1 ratio to balance confounding factors. RESULTS: The maximum pressures with methylene blue injection in the gallbladder and CBD without Pringle's maneuver in the four swines were 103.8 ± 11.8 and 42.3 ± 6.1, respectively. After Pringle's maneuver, 32.0 ± 6.8 mL methylene blue injection led to a maximum pressure in the CBD of 85.3 ± 9.5 cmH2O. The pressures in CBD were 25.8 ± 3.3 and 86.0 ± 9.9 cmH2O when BL appeared at small bile ducts and around the ligation sites, respectively. Of the 206 patients enrolled in the historical control group, 31 (15.0%) developed BL, while of the 54 patients in the study group, only 1 developed grade A BL. The number of BL detected by the routine white gauze test in the control group was significantly lower than that in the study group (Z = -3.002, P = 0.003). After PSM, the incidence of BL in the control group and grade B/C BL was 20.4% and 11.1%, respectively. The corresponding incidences in the study group were 1.9% (χ2 = 7.594, P = 0.006) and 0% (P = 0.027), respectively. The length of hospital stay in the study group was significantly reduced (Z = -6.048, P < 0.001). CONCLUSION: Peng's test for intraoperative BL detection is safe and effective in reducing BL after hepatectomy.

Effects of 2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione on autophagy and the PI3K/AKT/mTOR signaling pathway in human cholangiocarcinoma QBC939 cells.

Background: 2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione (DMDD) has been reported to have good antitumor effects. The aim of this study was to investigate whether DMDD induces apoptosis and autophagy in human cholangiocarcinoma (CCA) QBC939 cells and determine its effect on the PI3K/AKT/mTOR signaling pathway. Methods: QBC939 cells were cultured in vitro and changes in cell viability were detected by the Cell Counting Kit (CCK8) assay after treatment with different concentrations of DMDD for 24, 48, and 72 h. The cells were divided into control and DMDD-treated groups (treated concentrations were 10, 15, and 20 µM/L), and the cell cycle, apoptosis, and autophagic vesicles were assessed. The expression levels of PI3K, AKT, mTOR, microtubule-associated protein 1 light chain 3 beta (LC3-II)/I, Beclin-1, and P62 were detected by Western blot. A xenograft mouse model was constructed to detect the effect of DMDD on CCA. Results: The experimental results showed that DMDD was able to inhibit proliferation, migration, and invasion and induce cell cycle arrest and autophagy of QBC939 cells. In addition, DMDD decreased the protein expression of PI3K, AKT, and mTOR and increased the expression of LC3-II/I, Beclin-1, and P62. In mice, DMDD was able to inhibit the growth of tumors. Conclusions: DMDD inhibits CCA cell viability and induces cell cycle arrest and autophagy by a mechanism that may be related to the downregulation of the PI3K/AKT/mTOR signaling pathway.

Graft versus host disease after liver transplantation following radiotherapy for the treatment of hepatocellular carcinoma: A case report and literature review.

Graft versus host disease after solid organ transplantation is very rare. This article reports a case of graft versus host disease after liver transplantation following targeted therapy and radiotherapy for the treatment of hepatocellular carcinoma. The patient developed a symptomatic skin rash and pancytopenia 13 days after surgery, which was confirmed as graft versus host disease after liver transplantation by histopathology and fluorescence in situ hybridization. Early diagnosis of graft versus host disease after solid organ transplantation is difficult and often delayed due to nonspecific manifestations that overlap with other diseases. Currently, the treatment of graft versus host disease after liver transplantation occurs by either strengthening the immune suppression or weakening the immune suppression; however, there is no unified standard treatment strategy. We found that in addition to age, gender, and human leukocyte antigen type, preoperative radiotherapy is a likely risk factor for graft versus host disease after liver transplantation.

Prognostic nomograms to predict overall survival and cause specific death in vulvar squamous cell carcinoma.

OBJECTIVE: The incidence of vulvar squamous cell carcinoma has been rising in recent decades. The prognosis of patients with vulvar squamous cell carcinoma was explored, and nomograms were constructed to predict survival rates. METHODS: Vulvar squamous cell carcinoma patient data were downloaded from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into a training dataset and testing dataset. Univariable and multivariable Cox regression were used to identify risk factors affecting vulvar squamous cell carcinoma overall survival in the training dataset. Cumulative incidence function and Fine-Gray regression were used to analyze cancer specific death in the training dataset. Overall survival and cancer specific death nomograms were constructed and validated in the testing and whole datasets. Receiver operating characteristic and calibration were used to verify the predictive value and clinical applicability of the models. RESULTS: Age ≥60 years, grade 3, American Joint Committee on Cancer stages III and IV, TNM (tumor, nodes, metastasis) stages T2, T3, N1, and M1 had a negative effect on overall survival in vulvar cancer patients. Surgery (hazard ratio (HR)=0.416, 95% confidence interval (CI) 0.349 to 0.496, p<0.001) and chemotherapy (HR=0.637, 95% CI 0.544 to 0.746, p<0.001) may improve overall survival. Age, tumor grade, American Joint Committee on Cancer stage, T stage, N stage, M stage, surgery, and chemotherapy significantly affected vulvar cancer specific death. For area under the receiver operating characteristic curve, the predictive ability of the nomograms for overall survival and cancer specific death for 1 year (area under the curve (AUC)=0.862), 3 years (AUC=0.832), and 5 years (AUC=0.808) were all >0.800. CONCLUSION: The nomograms established in our study had an excellent predictive ability for overall survival and cancer specific death in vulvar cancer patients.

Acyl-CoA Binding Domain Containing 4 Polymorphism rs4986172 and Expression Can Serve as Overall Survival Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma Patients After Hepatectomy.

Background: The aim of our study was to evaluate the potential of expression and single nucleotide polymorphism of Acyl-CoA binding domain containing 4 (ACBD4) gene as prognosis biomarkers in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after hepatectomy. Methods: HBV-related HCC patients from the First Affiliated Hospital of Guangxi Medical University and GSE14520 were included in the current study, as well as The Cancer Genome Atlas (TCGA) HCC verification cohort. Prognostic analysis and multiple functional enrichment analysis methods were used to evaluate the prognostic value and potential biological functions of the ACBD4 gene in HBV-related HCC. Results: We found that ACBD4 gene is highly expressed in normal liver tissues and markedly down-regulated in HBV-related HCC tissues. ACBD4 gene was significantly related to overall survival (OS) of HCC in TCGA and GSE14520 cohorts, and patients with low ACBD4 expression were markedly related to poor OS. Rs4986172 was observed as an OS biomarker after hepatectomy in the Guangxi HBV-related HCC cohort. The OS of rs4986172 GG genotype was worse than that of HCC patients with A allele (AA and AG genotypes). Multifunctional enrichment analysis suggested that ACBD4 gene is closely related to the metabolic, peroxisome proliferator-activated receptor and cytochrome P450 pathway. Through connectivity map, we also identified eight compounds that may be used as targeted therapeutic agents for ACBD4 gene in HBV-related HCC; these compounds were scopoletin, alfaxalone, bephenium hydroxynaphthoate, apramycin, 4,5-dianilinophthalimide, DL-thiorphan, aminohippuric acid and quinidine. Immune microenvironment analysis revealed that there were significant differences in immune scores of HBV-related HCC tumor tissues with different ACBD4 expression levels. Conclusion: Our study reveals that ACBD4 expression and rs4986172 can be serve as biomarkers of OS in HBV-related HCC patients after hepatectomy.

A comprehensive analysis of the diagnostic and prognostic value associated with the SLC7A family members in breast cancer.

Background: The solute carrier (SLC) 7 family genes play central roles in cancer cell metabolism as glucose and glutamate transporters. However, their expression and prognostic value in breast cancer (BC) remains to be elucidated. Methods: Clinical data from BC patients were downloaded from The Cancer Genome Atlas (TCGA) and the Kaplan-Meier (KM) plotter database. The mechanisms underlying the association between SLC7A expression and overall survival (OS) were explored using Cox regression and log-rank tests. ESTIMATE gives a measure of the immune-cell infiltrates. Single-sample (ss) Gene Set Enrichment Analysis (GSEA) was conducted to quantify immune cell infiltration. Results: High SLC7A5 expression was associated with a poorer survival time in BC patients according to the TCGA and KM plotter data. SLC7A4 was associated with good progression-free interval (PFI) and disease-specific survival (DSS) according to the TCGA data. Furthermore, SLC7A4 was correlated with good prognosis of OS, distant metastasis-free survival (DMFS), relapse-free survival (RFS), and post-progression survival (PPS) according to the KM plotter data. SLC7A3 expression was positively associated with OS, but was not strongly associated with PFI nor DSS in the TCGA data. However, SLC7A3 was positively correlated with DMFS and RFS in the KM database analysis. SLC7A had excellent diagnostic value in BC patients and was strongly correlated with tumor infiltration. T helper 2 (Th2) cells, CD56 bright natural killer (NK) cells, and NK cells were the most strongly correlated with the SLC7A family genes, suggesting that these genes play a crucial role in BC partly by modulating immune infiltration. Conclusions: SLC7A4 and SLC7A5 expression levels may be sensitive biomarkers for predicting BC outcomes. SLC7A3 may be a potential diagnostic and prognostic biomarker in BC, but further studies are warranted to verify these results.

Down regulated oncogene KIF2C inhibits growth, invasion, and metastasis of hepatocellular carcinoma through the Ras/MAPK signaling pathway and epithelial-to-mesenchymal transition.

Background: Hepatocellular carcinoma (HCC) is the leading cause of cancer death. Kinesin family member 2C (KIF2C) has been shown as oncogene in a variety of tumors. However, its role in HCC remains unclear. Methods: In this study, the expression level of KIF2C in HCC was detected by immunohistochemical staining and RT-PCR, and verified by Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and Oncomine database. A curve was established to evaluate the diagnostic efficiency of KIF2C. The effect of KIF2C on HCC was investigated by flow cytometry, Cell Counting Kit-8, Transwell, and the wound-healing assay. We explored the underlying mechanism through epithelial-to-mesenchymal transition (EMT) and transcriptome sequences analysis. Results: KIF2C was overexpression in HCC tissue and related to neoplasm histologic grade (P<0.001), pathology stage (P=0.001), and a dismal prognosis (overall, recurrence-free, and disease-free survival). The diagnostic efficacy of KIF2C was >90% in diagnosing HCC. The HCC cell function experiments showed that KIF2C promoted HCC cell proliferation, migration, invasion, and an accelerated cell cycle, and inhibited apoptosis. Based on western blot analysis and RT-PCR, we found that KIF2C promoted HCC invasion and metastasis through activation of the EMT. Based on transcriptome sequences, we showed that KIF2C promoted HCC through the Ras/MAPK and PI3K/Akt signaling pathway. Conclusions: KIF2C was found to promote the progression of HCC and is anticipated to serve as a biomarker for HCC diagnosis, prognosis, and targeted therapy.

Gender disparity in hepatocellular carcinoma recurrence after curative hepatectomy.

INTRODUCTION AND OBJECTIVES: Whether there is gender disparity in the recurrence of hepatocellular carcinoma (HCC) has been not fully addressed. This study aimed to investigate the impact of gender on HCC recurrence following curative hepatectomy. PATIENTS AND METHODS: This retrospective cohort study included 1087 patients with HCC (917 males, 170 females) who underwent curative hepatectomy. Cox regression models were constructed to estimate the hazard ratio (HR) and 95% confidence interval (CI) of the risk parameters associated with HCC recurrence. In the sensitivity analysis, subgroup analysis, and propensity score matching (PSM) analysis were used. Logistic regression models were used to assess the odds ratio (OR) and 95% CI of the risk parameters related to early and late recurrence. RESULTS: Male patients showed significantly higher risk for HCC recurrence than females, in both multivariate Cox regression analysis (HR [95% CI] = 1.480 [1.084-2.020], P = 0.014) and PSM analysis (HR [95% CI] = 1.589 [1.093-2.312], P = 0.015). Higher risk of HCC recurrence was again found in males in the subgroup analysis, but the effect of male versus female gender on HCC recurrence did not depend on any selected subgroups (all P for interaction > 0.05). Gender was an independent risk factor for early recurrence (OR [95% CI] = 1.864 [1.215-2.936], P = 0.006), but not for late recurrence. CONCLUSIONS: There is gender disparity in the recurrence of patients with HCC after curative hepatectomy: males had a higher risk for HCC recurrence than females.

A Closer Look at the Joint Training of Object Detection and Re-identification in Multi-Object Tracking.

Unifying object detection and re-identification (ReID) into a single network enables faster multi-object tracking (MOT), while this multi-task setting poses challenges for training. In this work, we dissect the joint training of detection and ReID from two dimensions: label assignment and loss function. We find previous works generally overlook them and directly borrow the practices from object detection, inevitably causing inferior performance. Specifically, we identify a qualified label assignment for MOT should: 1) have the assignment cost aware of ReID cost, not just detection cost; 2) provide sufficient positive samples for robust feature learning while avoiding ambiguous positives (i.e., the positives shared by different ground-truth objects). To achieve the above goals, we first propose Identity-aware Label Assignment, which jointly considers the assignment cost of detection and ReID to select positive samples for each instance without ambiguities. Moreover, we advance a novel Discriminative Focal Loss that integrates ReID predictions with Focal Loss to focus the training on the discriminative samples. Finally, we upgrade the strong baseline FairMOT with our techniques and achieve up to 7.0 MOTA / 54.1% IDs improvements on MOT16/17/20 benchmarks under favorable inference speed, which verifies our tailored label assignment and loss function for MOT are superior to those inherited from object detection.