The role of serum thymidine kinase 1 activity in neoadjuvant-treated HER2-positive breast cancer: biomarker analysis from the Swedish phase II randomized PREDIX HER2 trial.

BACKGROUND: Thymidine kinase 1 (TK1) plays a pivotal role in DNA synthesis and cellular proliferation. TK1 has been studied as a prognostic marker and as an early indicator of treatment response in human epidermal growth factor 2 (HER2)-negative early and metastatic breast cancer (BC). However, the prognostic and predictive value of serial TK1 activity in HER2-positive BC remains unknown. METHODS: In the PREDIX HER2 trial, 197 HER2-positive BC patients were randomized to neoadjuvant trastuzumab, pertuzumab, and docetaxel (DPH) or trastuzumab emtansine (T-DM1), followed by surgery and adjuvant epirubicin and cyclophosphamide. Serum samples were prospectively collected from all participants at multiple timepoints: at baseline, after cycle 1, 2, 4, and 6, at end of adjuvant therapy, annually for a total period of 5 years and/or at the time of recurrence. The associations of sTK1 activity with baseline characteristics, pathologic complete response (pCR), event-free survival (EFS), and disease-free survival (DFS) were evaluated. RESULTS: No association was detected between baseline sTK1 levels and all the baseline clinicopathologic characteristics. An increase of TK1 activity from baseline to cycle 2 was seen in all cases. sTK1 level at baseline, after 2 and 4 cycles was not associated with pCR status. After a median follow-up of 58 months, 23 patients had EFS events. There was no significant effect between baseline or cycle 2 sTK1 activity and time to event. A non-significant trend was noted among patents with residual disease (non-pCR) and high sTK1 activity at the end of treatment visit, indicating a potentially worse long-term prognosis. CONCLUSION: sTK1 activity increased following neoadjuvant therapy for HER2-positive BC but was not associated with patient outcomes or treatment benefit. However, the post-surgery prognostic value in patients that have not attained pCR warrants further investigation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02568839. Registered on 6 October 2015.

Autophagy dysfunction contributes to NLRP1 inflammasome-linked depressive-like behaviors in mice.

BACKGROUND: Major depressive disorder (MDD) is a common but severe psychiatric illness characterized by depressive mood and diminished interest. Both nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain-containing 1 (NLRP1) inflammasome and autophagy have been reported to implicate in the pathological processes of depression. However, the mechanistic interplay between NLRP1 inflammasome, autophagy, and depression is still poorly known. METHODS: Animal model of depression was established by chronic social defeat stress (CSDS). Depressive-like behaviors were determined by social interaction test (SIT), sucrose preference test (SPT), open field test (OFT), forced swim test (FST), and tail-suspension test (TST). The protein expression levels of NLRP1 inflammasome complexes, pro-inflammatory cytokines, phosphorylated-phosphatidylinositol 3-kinase (p-PI3K)/PI3K, phosphorylated-AKT (p-AKT)/AKT, phosphorylated-mechanistic target of rapamycin (p-mTOR)/mTOR, brain-derived neurotrophic factor (BDNF), phosphorylated-tyrosine kinase receptor B (p-TrkB)/TrkB, Bcl-2-associated X protein (Bax)/B-cell lymphoma-2 (Bcl2) and cleaved cysteinyl aspartate-specific proteinase-3 (caspase-3) were examined by western blotting. The mRNA expression levels of pro-inflammatory cytokines were tested by quantitative real-time PCR. The interaction between proteins was detected by immunofluorescence and coimmunoprecipitation. Neuronal injury was assessed by Nissl staining. The autophagosomes were visualized by transmission electron microscopy. Nlrp1a knockdown was performed using an adeno-associated virus (AAV) vector containing Nlrp1a-shRNA-eGFP infusion. RESULTS: CSDS exposure caused a bidirectional change in hippocampal autophagy function, which was activated in the initial period but impaired at the later stage. In addition, CSDS exposure increased the expression levels of hippocampal NLRP1 inflammasome complexes, pro-inflammatory cytokines, p-PI3K, p-AKT and p-mTOR in a time-dependent manner. Interestingly, NLRP1 is immunoprecipitated with mTOR but not PI3K/AKT and CSDS exposure facilitated the immunoprecipitation between them. Hippocampal Nlrp1a knockdown inhibited the activity of PI3K/AKT/mTOR signaling, rescued the impaired autophagy and ameliorated depressive-like behavior induced by CSDS. In addition, rapamycin, an autophagy inducer, abolished NLRP1 inflammasome-driven inflammatory reactions, alleviated depressive-like behavior and exerted a neuroprotective effect. CONCLUSIONS: Autophagy dysfunction contributes to NLRP1 inflammasome-linked depressive-like behavior in mice and the regulation of autophagy could be a valuable therapeutic strategy for the management of depression.

The relationship between psychological distress and the nursing humanistic care demands in postoperative cancer inpatients: a cross-sectional study.

PURPOSE: We aimed to investigate cancer patients' experiences of psychological distress after surgery and the factors that influence it, and to analyze the relationship between this and the nursing humanistic care demands. METHODS: This study used a convenience sampling method to survey 432 cancer patients undergoing surgical treatment in the specialized cancer hospital in Beijing. The survey used socio-demographic information, the Distress Management Screening Measures, and the Nursing Humanistic Care Demands questionnaire. Questionnaire Star was used to collect data online. SPSS24.0 software was used to test the relationship between psychological distress and nursing humanistic care demands. RESULTS: The mean scores for psychological distress and nursing humanistic care demands were 3.95 ± 2.71 and 147.02 ± 19.88, respectively, and showed a moderately positive correlation. The main issues that caused psychological distress in patients were: worry, financial problems, surroundings, nervousness, sleep, and pain. Regression analysis showed that gender, financial burden, personality trait, and need for humanistic care in nursing explained 24.5% of the total variance in the model and were independent predictors of psychological distress. CONCLUSION: Cancer inpatients have significant psychological distress after surgery and exhibit high levels of nursing humanistic care demands. This study fills the research gap on humanistic care for psychological distress management, nursing humanistic care demands positively predicted psychological distress. Nursing staff should pay attention to the psychological suffering of patients and develop individualized care measures to alleviate their psychological suffering by accurately identifying their nursing humanistic care demands.

Mediating effects of core competence between the transition shock and work readiness of newly graduated nurses in cancer hospitals: A cross-sectional study.

BACKGROUND: Newly graduated nurses face a dilemma of transitioning from student to clinical nurse roles, resulting in a low level of work readiness. The special professional environment of oncology hospitals requires newly graduated nurses to have specialized and novel theoretical knowledge and nursing skills. Therefore, they are constantly expected to develop better core competence. However, whether the core competence of newly graduated nurses mediates the relationship between transition shock and work readiness has not been investigated. OBJECTIVE: This study examined the relationship among transition shock, core competence, and work readiness of newly graduated nurses in cancer hospitals. DESIGN: A descriptive, cross-sectional study design. SETTING: This study was conducted at a tertiary cancer hospital in Beijing. PARTICIPATIONS: A convenience sample of 188 newly graduated nurses was studied from July to August 2022. METHODS: Sociodemographic data and Transition Shock Scale for Newly Graduated Nurses, Work Readiness Scale for Newly Graduated Nurses, and Core Competence Scale scores were collected using the online Questionnaire Star support platform. Pearson correlation and multiple regression analysis were applied using the Statistical Package for the Social Sciences version 24 to test the relationship among transition shock, core competencies, and work readiness. The Analysis of Moment Structures version 24.0 software was used to construct structural equation models. This report followed the Strengthening the Reporting of Observational studies in Epidemiology checklist. RESULTS: The transition shock of newly graduated nurses was negatively correlated with work readiness and core competence, whereas core competence was positively correlated with work readiness. Core competence partially mediated the effect between transition shock and work readiness, accounting for 19 % of the total effect. CONCLUSION: Core competence is the mediating variable between transition shock and work readiness of newly graduated nurses in oncology hospitals. During the transition period of newly graduated nurses, clinical nursing managers and teachers should pay attention to cultivating the core competence of newly graduated nurses to improve their work readiness.

Applicability of multidimensional convolutional neural networks on automated detection of diverse focal liver lesions in multiphase CT images.

PURPOSE: To investigate the applicability of multidimensional convolutional neural networks (CNNs) together with multiphase contrast-enhanced CT images on automated detection of diverse focal liver lesions (FLLs). METHODS: We trained detection models based on 2.5D and 3D CNN frameworks using 567 patients with 3892 FLLs and validated on a relatively large independent cohort of 1436 patients with 4723 lesions. The detection performance across different phases (arterial, portal venous [PV], and combined phases) was assessed for the 2.5D model. The lesions were divided into two groups with a cutoff size of 20 mm, and further subdivided into four subgroups of <10, 10-20, 20-50, and ≥50 mm, to verify the detection rates for lesions of different sizes for the 2.5D and 3D models. McNemar's test was used to compare the detection sensitivities among different methods. In addition, sensitivity with 95% confidence intervals and free-response receiver operating characteristics (FROC) curves were plotted for visualization of the detectability. RESULTS: In the 2.5D model, the detection rate of PV phase outperformed arterial phase, and a combination of the two phases further improved the performance over a single phase. The detection sensitivities in the arterial, PV, and combined phases were 0.737 versus 0.802 versus 0.832 for all lesions. The 3D model was superior to the 2.5D model for detecting benign lesions (0.896 vs. 0.807, p < 0.001), malignant lesions (0.940 vs. 0.918, p = 0.013), and all lesions (0.902 vs. 0.832, p < 0.001) regardless of size division. Particularly, the 3D model showed higher sensitivity than the 2.5D model in detecting lesions smaller than 20 mm (0.868 vs. 0.759, p < 0.001). For lesions larger than 20 mm, both the 3D and the 2.5D models achieved excellent detection performance. CONCLUSIONS: The proposed CNN detection model was demonstrated to adaptively learn the feature representations of diverse FLLs and generalize well to a large-scale validation dataset. The use of multiphase significantly improved the detectability of FLLs compared to single phase. 3D CNN framework showed an enhanced capability over the 2.5D in the detection of FLLs, particularly small lesions. The promising performance shows that the proposed CNN detection system could be a powerful clinical tool for the early detection of hepatic tumors.

A novel multimodal deep learning model for preoperative prediction of microvascular invasion and outcome in hepatocellular carcinoma.

BACKGROUND: Accurate preoperative identification of the microvascular invasion (MVI) can relieve the pressure from personalized treatment adaptation and improve the poor prognosis for hepatocellular carcinoma (HCC). This study aimed to develop and validate a novel multimodal deep learning (DL) model for predicting MVI based on multi-parameter magnetic resonance imaging (MRI) and contrast-enhanced computed tomography (CT). METHODS: A total of 397 HCC patients underwent both CT and MRI examinations before surgery. We established the radiological models (RCT, RMRI) by support vector machine (SVM), DL models (DLCT_ALL, DLMRI_ALL, DLCT + MRI) by ResNet18. The comprehensive model (CALL) involving multi-modality DL features and clinical and radiological features was constructed using SVM. Model performance was quantified by the area under the receiver operating characteristic curve (AUC) and compared by net reclassification index (NRI) and integrated discrimination improvement (IDI). RESULTS: The DLCT + MRI model exhibited superior predicted efficiency over single-modality models, especially over the DLCT_ALL model (AUC: 0.819 vs. 0.742, NRI > 0, IDI > 0). The DLMRI_ALL model improved the performance over the RMRI model (AUC: 0.794 vs. 0.766, NRI > 0, IDI < 0), but no such difference was found between the DLCT_ALL model and RCT model (AUC: 0.742 vs. 0.710, NRI < 0, IDI < 0). Furthermore, both the DLCT + MRI and CALL models revealed the prognostic power in recurrence-free survival stratification (P < 0.001). CONCLUSION: The proposed DLCT + MRI model showed robust capability in predicting MVI and outcomes for HCC. Besides, the identification ability of the multi-modality DL model was better than any single modality, especially for CT.

Expression patterns and prognostic implications of tumor-infiltrating lymphocytes dynamics in early breast cancer patients receiving neoadjuvant therapy: A systematic review and meta-analysis.

Purpose: High levels of tumor-infiltrating lymphocytes (TILs) are associated with better outcomes in early breast cancer and higher pathological response rates to neoadjuvant chemotherapy especially in the triple-negative (TNBC) and HER2+ subtypes. However, the dynamic changes in TILs levels after neoadjuvant treatment (NAT) are less studied. This systematic review and meta-analysis aimed to investigate the patterns and role of TILs dynamics change in early breast cancer patients receiving NAT. Methods: Medline, Embase, Web of Science Core Collection and PubMed Central databases were searched for eligible studies. Data were extracted independently by two researchers and discordances were resolved by a third. Pooled TILs rates pre- & post-treatment (overall and per subtype), pooled rates of ΔTILs and direction of change after NAT as well as correlation of ΔTILs with survival outcomes were generated in the outcome analysis. Results: Of 2116 identified entries, 34 studies fulfilled the criteria and provided adequate data for the outcomes of interest. A decreased level of TILs was observed after NAT in paired samples across all subtypes. The effect of NAT on TILs was most prominent in TNBC subtype with a substantial change, either increase or decrease, in 79.3% (95% CI 61.7-92.6%) of the patients as well as in HER2+ disease (14.4% increased vs 46.2% decreased). An increase in ΔTILs in TNBC was associated with better disease-free/relapse-free survival in pooled analysis (univariate HR = 0.59, 95% CI: 0.37-0.95, p = 0.03). Conclusion: This meta-analysis illustrates the TILs dynamics during NAT for breast cancer and indicates prognostic implications of ΔTILs in TNBC. The potential clinical utility of the longitudinal assessment of TILs during neoadjuvant therapy warrants further validation.

Influencing Factors of Physical Activity in Patients with Lung Cancer Surgery and Its Correlation with Exercise Self-Efficacy and Perceived Social Support.

Purpose: The aim of the study is to understand the current status of physical activity in patients with lung cancer surgery, explore its influencing factors, and analyze the correlation between physical activity and exercise self-efficacy and perception of social support. Methods: The General Information Questionnaire was designed for 145 patients, Chinese version of EPIC-PAQ physical activity scale for lung cancer patients. The Exercise Self-Efficacy Scale (SEE) is used to evaluate the ability of people to organize and execute motor behaviors in various difficult situations. The Perceived Social Support Scale (PSSS) was used to emphasize individual self-understanding and self-feeling. Results: The median and quartile of total physical activity scores in lung cancer surgery patients were 73.0 (34.8, 129.7) points; univariate analysis showed that there were statistically significant differences in physical activity levels among lung cancer surgery patients with different ages, work status before hospitalization, and perceived disease severity. The results of multivariate analysis showed that age, perceived disease severity, exercise self-efficacy, and total score of perceived social support affected the physical activity level of patients (P < 0.05). Efficacy were positively correlated with perceived social support (P < 0.01). Conclusion: The level of physical activity of patients undergoing lung cancer surgery needs to be further improved. Physical activity is affected by patient age, perceived disease severity, exercise self-efficacy, and perceived social support and is positively correlated with exercise self-efficacy and perceived social support. Medical staff should provide targeted activity guidance according to the age and other characteristics of patients undergoing lung cancer surgery, enhance patients' exercise self-efficacy and comprehend social support, and improve their physical activity level, thereby promoting patients' early recovery.

CT-Based Radiomics for the Recurrence Prediction of Hepatocellular Carcinoma After Surgical Resection.

Purpose: To explore the effectiveness of radiomics signature in predicting the recurrence of hepatocellular carcinoma (HCC) and the benefit of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE). Patients and Methods: In this multicenter retrospective study, 364 consecutive patients with multi-phase computed tomography (CT) images were included. Recurrence-related radiomics features of intra- and peritumoral regions were extracted from the pre-contrast, arterial and portal venous phase, respectively. The radiomics model was established in the training cohort (n = 187) using random survival forests analysis to output prediction probability as "Rad-score" and validated by the internal (n = 92) and external validation cohorts (n = 85). Besides, the Clinical nomogram was developed by clinical-radiologic-pathologic characteristics, and the Combined nomogram was further constructed to evaluate the added value of the Rad-score for individualized recurrence-free survival (RFS) prediction, which is our primary and only endpoint. The performance of the three models was assessed by the concordance index (C-index). Furthermore, all the patients were stratified into high- and low-risk groups of recurrence by the median value of the Rad-score to analyze the benefit of PA-TACE. Results: The model built using radiomics signature demonstrated favorable prediction of HCC recurrence across all datasets, with C-index of 0.892, 0.812, 0.809, separately in the training, the internal and external validation cohorts. Univariate and multivariate analysis revealed that the Rad-score was an independent prognostic factor. Significant differences were found between the high- and low-risk group in RFS prediction in all three cohorts. Further analysis showed that compared with the low-risk group, patients with the high-risk received more benefits from PA-TACE. Conclusion: The newly developed Rad-score was not only a powerful biomarker in predicting the RFS of HCC but also a strong stratification basis to explore the high-risk patients who could benefit from PA-TACE.

Automatic discrimination of different sequences and phases of liver MRI using a dense feature fusion neural network: a preliminary study.

PURPOSE: To develop and validate a dense feature fusion neural network (DFuNN) to automatically recognize different sequences and phases of liver magnetic resonance imaging (MRI). MATERIALS AND METHODS: In total, 3869 sequences and phases from 384 liver MRI examinations, divided into training/validation (n = 2886 sequences from 287 patients) and test (n = 983 sequences from 97 patients) sets, were used in this retrospective study. Ten unenhanced sequences and enhanced phases were included. Manual sequence recognition, performed by two radiologists (20 and 10 years of experience) in a consensus reading, was used as the reference standard. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of the DFuNN on an identical unseen test set. Finally, we evaluated the factors impacting the model precision. RESULTS: A fusion block improved the performance of the DFuNN. DFuNN with a fusion block achieved good recognition performance for both complete and incomplete sequences and phases in the test set. The average sensitivity of recognition performance for complete sequence and phase inputs ranged from 88.06 to 100%, the average specificity ranged from 99.12 to 99.94%, and the median accuracy ranged from 98.02 to 99.95%. The DFuNN prediction accuracy for patients without cirrhosis were significantly higher than those for patients with cirrhosis (P = 0.0153). No significant difference was found in the accuracy across other factors. CONCLUSION: DFuNN can automatically and accurately identify specific unenhanced MRI sequences and enhanced MRI phases.

Multimorbidity Patterns and Memory Trajectories in Older Adults: Evidence From the English Longitudinal Study of Aging.

BACKGROUND: We aimed to examine the multimorbidity patterns within a representative sample of UK older adults and their association with concurrent and subsequent memory. METHODS: Our sample consisted of 11 449 respondents (mean age at baseline was 65.02) from the English Longitudinal Study of Aging (ELSA). We used 14 health conditions and immediate and delayed recall scores (IMRC and DLRC) over 7 waves (14 years of follow-up). Latent class analyses were performed to identify the multimorbidity patterns and linear mixed models were estimated to explore their association with their memory trajectories. Models were adjusted by sociodemographics, body mass index (BMI), and health behaviors. RESULTS: Results showed 8 classes: Class 1: Heart Disease/Stroke (26%), Class 2: Asthma/Lung Disease (16%), Class 3: Arthritis/Hypertension (13%), Class 4: Depression/Arthritis (12%), Class 5: Hypertension/Cataracts/Diabetes (10%), Class 6: Psychiatric Problems/Depression (10%), Class 7: Cancer (7%), and Class 8: Arthritis/Cataracts (6%). At baseline, Class 4 was found to have lower IMRC and DLRC scores and Class 5 in DLRC, compared to the no multimorbidity group (n = 6380, 55.72% of total cohort). For both tasks, in unadjusted models, we found an accelerated decline in Classes 1, 3, and 8; and, for DLRC, also in Classes 2 and 5. However, it was fully attenuated after adjustments. CONCLUSIONS: These findings suggest that individuals with certain combinations of health conditions are more likely to have lower levels of memory compared to those with no multimorbidity and their memory scores tend to differ between combinations. Sociodemographics and health behaviors have a key role to understand who is more likely to be at risk of an accelerated decline.

Dynamic individual vital sign trajectory early warning score (DyniEWS) versus snapshot national early warning score (NEWS) for predicting postoperative deterioration.

AIMS: International early warning scores (EWS) including the additive National Early Warning Score (NEWS) and logistic EWS currently utilise physiological snapshots to predict clinical deterioration. We hypothesised that a dynamic score including vital sign trajectory would improve discriminatory power. METHODS: Multicentre retrospective analysis of electronic health record data from postoperative patients admitted to cardiac surgical wards in four UK hospitals. Least absolute shrinkage and selection operator-type regression (LASSO) was used to develop a dynamic model (DyniEWS) to predict a composite adverse event of cardiac arrest, unplanned intensive care re-admission or in-hospital death within 24 h. RESULTS: A total of 13,319 postoperative adult cardiac patients contributed 442,461 observations of which 4234 (0.96%) adverse events in 24 h were recorded. The new dynamic model (AUC = 0.80 [95% CI 0.78-0.83], AUPRC = 0.12 [0.10-0.14]) outperforms both an updated snapshot logistic model (AUC = 0.76 [0.73-0.79], AUPRC = 0.08 [0.60-0.10]) and the additive National Early Warning Score (AUC = 0.73 [0.70-0.76], AUPRC = 0.05 [0.02-0.08]). Controlling for the false alarm rates to be at current levels using NEWS cut-offs of 5 and 7, DyniEWS delivers a 7% improvement in balanced accuracy and increased sensitivities from 41% to 54% at NEWS 5 and 18% to -30% at NEWS 7. CONCLUSIONS: Using an advanced statistical approach, we created a model that can detect dynamic changes in risk of unplanned readmission to intensive care, cardiac arrest or in-hospital mortality and can be used in real time to risk-prioritise clinical workload.

NLRP1 inflammasome contributes to chronic stress-induced depressive-like behaviors in mice.

BACKGROUND: Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, and inflammation has been considered crucial components of the pathogenesis of depression. NLRP1 inflammasome-driven inflammatory response is believed to participate in many neurological disorders. However, it is unclear whether NLRP1 inflammasome is implicated in the development of depression. METHODS: Animal models of depression were established by four different chronic stress stimuli including chronic unpredictable mild stress (CUMS), chronic restrain stress (CRS), chronic social defeat stress (CSDS), and repeat social defeat stress (RSDS). Depressive-like behaviors were determined by sucrose preference test (SPT), forced swim test (FST), tail-suspension test (TST), open-field test (OFT), social interaction test (SIT), and light-dark test (LDT). The expression of NLRP1 inflammasome complexes, BDNF, and CXCL1/CXCR2 were tested by western blot and quantitative real-time PCR. The levels of inflammatory cytokines were tested by enzyme-linked immunosorbent assay (ELISA) kits. Nlrp1a knockdown was performed by an adeno-associated virus (AAV) vector containing Nlrp1a-shRNA-eGFP infusion. RESULTS: Chronic stress stimuli activated hippocampal NLRP1 inflammasome and promoted the release of pro-inflammatory cytokines IL-1ß, IL-18, IL-6, and TNF-α in mice. Hippocampal Nlrp1a knockdown prevented NLRP1 inflammasome-driven inflammatory response and ameliorated stress-induced depressive-like behaviors. Also, chronic stress stimuli caused the increase in hippocampal CXCL1/CXCR2 expression and low BDNF levels in mice. Interestingly, Nlrp1a knockdown inhibited the up-regulation of CXCL1/CXCR2 expression and restored BDNF levels in the hippocampus. CONCLUSIONS: NLRP1 inflammasome-driven inflammatory response contributes to chronic stress induced depressive-like behaviors and the mechanism may be related to CXCL1/CXCR2/BDNF signaling pathway. Thus, NLRP1 inflammasome could become a potential antidepressant target.

Spinal cord NLRP1 inflammasome contributes to dry skin induced chronic itch in mice.

BACKGROUND: Dry skin itch is one of the most common skin diseases and elderly people are believed to be particularly prone to it. The inflammasome has been suggested to play an important role in chronic inflammatory disorders including inflammatory skin diseases such as psoriasis. However, little is known about the role of NLRP1 inflammasome in dry skin-induced chronic itch. METHODS: Dry skin-induced chronic itch model was established by acetone-ether-water (AEW) treatment. Spontaneous scratching behavior was recorded by video monitoring. The expression of nucleotide oligomerization domain (NOD)-like receptor protein 1 (NLRP1) inflammasome complexes, transient receptor potential vanilloid type 1 (TRPV1), and the level of inflammatory cytokines were determined by western blot, quantitative real-time PCR, and enzyme-linked immunosorbent assay (ELISA) kits. Nlrp1a knockdown was performed by an adeno-associated virus (AAV) vector containing Nlrp1a-shRNA-eGFP infusion. H.E. staining was used to evaluate skin lesion. RESULTS: AEW treatment triggers spontaneous scratching and significantly increases the expression of NLRP1, ASC, and caspase-1 and the levels of IL-1ß, IL-18, IL-6, and TNF-α in the spinal cord and the skin of mice. Spinal cord Nlrp1a knockdown prevents AEW-induced NLRP1 inflammasome assembly, TRPV1 channel activation, and spontaneous scratching behavior. Capsazepine, a specific antagonist of TRPV1, can also inhibit AEW-induced inflammatory response and scratching behavior. Furthermore, elderly mice and female mice exhibited more significant AEW-induced scratching behavior than young mice and male mice, respectively. Interestingly, AEW-induced increases in the expression of NLRP1 inflammasome complex and the levels of inflammatory cytokines were more remarkable in elderly mice and female mice than in young mice and male mice, respectively. CONCLUSIONS: Spinal cord NLRP1 inflammasome-mediated inflammatory response contributes to dry skin-induced chronic itch by TRPV1 channel, and it is also involved in age and sex differences of chronic itch. Inhibition of NLRP1 inflammasome may offer a new therapy for dry skin itch.

Deep learning assisted differentiation of hepatocellular carcinoma from focal liver lesions: choice of four-phase and three-phase CT imaging protocol.

PURPOSE: To evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in differentiating hepatocellular carcinoma (HCC) from other focal liver lesions (FLLs) compared with a four-phase protocol. METHODS: Three hundred and forty-two patients (mean age 49.1 ± 10.5 years, range 19-86 years, 65.8% male) scanned with a four-phase CT protocol (precontrast, arterial, portal-venous and delayed phases) were retrospectively enrolled. A total of 449 FLLs were categorized into HCC and non-HCC groups based on the best available reference standard. Three convolutional dense networks (CDNs) with the input of four-phase CT images (model A), three-phase images without portal-venous phase (model B) and three-phase images without precontrast phase (model C) were trained on 80% of lesions and evaluated in the other 20% by receiver operating characteristics (ROC) and confusion matrix analysis. The DeLong test was performed to compare the areas under the ROC curves (AUCs) of A with B, B with C, and A with C. RESULTS: The diagnostic accuracy in differentiating HCC from other FLLs on test sets was 83.3% for model A, 81.1% for model B and 85.6% for model C, and the AUCs were 0.925, 0.862 and 0.920, respectively. The AUCs of models A and C did not differ significantly (p = 0.765), but the AUCs of models A and B (p = 0.038) and of models B and C (p = 0.028) did. CONCLUSIONS: When combined with a CDN, a three-phase CT protocol without precontrast showed similar diagnostic accuracy as a four-phase protocol in differentiating HCC from other FLLs, suggesting that the multiphase CT protocol for HCC diagnosis might be optimized by removing the precontrast phase to reduce radiation dose.

Joint use of the radiomics method and frozen sections should be considered in the prediction of the final classification of peripheral lung adenocarcinoma manifesting as ground-glass nodules.

OBJECTIVES: To evaluate the diagnostic accuracy of radiomics method and frozen sections (FS) for the pathological classification of peripheral lung adenocarcinoma manifesting as ground-glass nodules (GGNs) in computer tomography (CT). MATERIALS AND METHODS: A dataset of 831 peripheral lung adenocarcinoma manifesting as GGNs in CT were divided into two cohorts: training cohort (n = 581) and validation cohort (n = 250). Combined with clinical features, the radiomics classifier was trained and validated to distinguish the pathological classification of these nodules. FS diagnoses in the validation cohort were collected. Diagnostic performance of the FS and radiomics methods was compared in the validation cohort. The predictive factors for the misdiagnosis of FS were determined via univariate and multivariate analyses. RESULTS: The accuracy of radiomics method in the training and validation cohorts was 72.5 % and 68.8 % respectively. The overall accuracy of FS in the validation cohort was 70.0 %. The concordance rate between FS and final pathology when FS had a different diagnosis from radiomics classifier was significantly lower than when FS had the same diagnosis as radiomics classifier (46 vs. 87 %, P < 0.001). Univariate and Multivariate analyses showed that different diagnosis between FS and radiomics classifier was the independent predictive factor for the misdiagnosis of FS (OR: 7.46; 95%CI: 4.00-13.91; P < 0.001). CONCLUSIONS: Radiomics classifier predictions may be a reliable reference for the classification of peripheral lung adenocarcinoma manifesting as GGNs when FS cannot provide a timely diagnosis. Intraoperative diagnoses of the cases where FS had a different diagnosis from radiomics method should be considered cautiously due to the higher misdiagnosis rate.

FoxO3a inhibiting expression of EPS8 to prevent progression of NSCLC: A new negative loop of EGFR signaling.

BACKGROUND: The resistance to EGF receptor (EGFR) tyrosine kinase inhibitors (TKI) is a major challenge in the treatment of non-small cell lung cancer (NSCLC). Understanding the molecular mechanisms behind resistance is therefore an important issue. Here we assessed the role of EGFR pathway substrate 8 (EPS8) and Forkhead box O 3a (FoxO3a) as potentially valuable targets in the resistance of NSCLC . METHODS: The expression levels of EPS8 and FoxO3a in patients with NSCLC (n = 75) were examined by immunohistochemistry staining, while in cells were detected by qPCR and western blot. The effects of EPS8 and FoxO3a on resistance, migration and invasion, cell cycle arrest were detected by MTT, transwell and flow cytometry, respectively. Chromatin immunoprecipitation and luciferase reporter assays were performed to determine the mechanisms of EPS8 expression and FoxO3a regulation. FINDINGS: We observed that the expression of EPS8 inversely correlated with FoxO3a in NSCLC cell lines and NSCLC patients. FoxO3a levels were significantly decreased in tumor tissues compared with para-carcinoma tissues, while EPS8 is opposite. Besides, they play reverse roles in the resistance to gefitinib, the migration and invasion abilities, the cell cycle arrest in vitro and the tumor growth in vivo. Mechanistically, FoxO3a inhibits EPS8 levels by directly binding its gene promoter and they form a negative loop in EGFR pathway. INTERPRETATION: Targeting FoxO3a and EPS8 in EGFR signaling pathway prevents the progression of NSCLC, which implied that the negative loop they formed could served as a therapeutic target for overcoming resistance in NSCLC. FUNDS: National Natural Science Foundation of China, Science and Technology Project of Henan, Outstanding Young Talent Research Fund of Zhengzhou University and the National Scholarship Fund.

Anterior thalamic radiation structural and metabolic changes in obsessive-compulsive disorder: A combined DTI-MRS study.

Numerous studies indicate the cortico-striato-thalamo-cortical (CSTC) circuit plays an important role in the pathophysiology of obsessive-compulsive disorder (OCD). The anterior thalamic radiation (ATR), as a major fiber in the fronto-thalamic circuitry, contributes to symptomology of OCD. However, the underlying biochemical mechanism in relation with its structural alteration remains not understood. This study investigated the structural abnormality of ATR and its correlation with thalamic metabolic alteration in OCD, using diffusion tensor image (DTI) and proton magnetic resonance spectroscopy (1H-MRS). Twenty-six unmedicated adult OCD patients and twenty-six matched healthy controls participated in DTI study. Thirteen OCD patients and thirteen healthy controls, a subset of DTI participants, took part in MRS study. The results showed that mean fiber length of right ATR negatively correlated with ipsilateral thalamic choline (Cho) level in OCD patients. Additionally, significantly higher Cho concentration was detected in right thalamus of OCD patients compared to healthy controls. Moreover, the mean fractional anisotropy (FA) value of right ATR positively correlated with patients Yale-Brown Obsessive Compulsive Scale (YBOCS) total score, as well as YBOCS compulsion score. These results suggested the coupling of structural and metabolic changes in right ATR, which might serve as a multi-modal biomarker contributing to the pathogenesis of OCD.

Enhanced Immunological Tolerance by HLA-G1 from Neural Progenitor Cells (NPCs) Derived from Human Embryonic Stem Cells (hESCs).

BACKGROUND: Despite the great potential of utilizing human embryonic stem cells (hESCs)-derived cells as cell source for transplantation, these cells were often rejected during engraftment by the immune system due to adaptive immune response. METHODS: We first evaluated HLA-G expression level in both hESCs and differentiated progenitor cells. After that, we generated modified hESC lines that over-express HLA-G1 using lentiviral infection with the construct contains both HLA-G1 and GFP tag. The lentivirus was first produced by co-transfecting HLA-G1 expressing lentiviral vector together with packaging vectors into packaging cell line 293T. Then the produced virus was used for the infection of selected hESC lines. We characterized the generated cell lines phenotype, including pluripotency and self-renewal abilities, as well as immune tolerance ability by mixed lymphocyte reaction (MLR) and cytotoxicity assays. RESULTS: Although the hESCs do not express high levels of HLA-G1, over-expression of HLA-G1 in hESCs still retains their stem cell characteristics as determined by retaining the expression levels of OCT4 and SOX2, two critical transcriptional factors for stem cell function. Furthermore, the HLA-G1 overexpressing hESCs retain the self-renewal and pluripotency characteristics of stem cells, which can differentiate into different types of cells, including pigment cells, smooth muscle cells, epithelia-like cells, and NPCs. After differentiation, the differentiated cells including NPCs retain the high levels of HLA-G1 protein. In comparison with conventional NPCs, these HLA-G1 positive NPCs have enhanced immune tolerance ability. CONCLUSIONS: Ectopic expression of HLA-G1, a non-classical major histocompatibility complex class I (MHC I) antigen that was originally discovered involving in engraftment tolerance during pregnancy, can enhance the immunological tolerance in differentiated neural progenitor cells (NPCs). Our study shows that stably overexpressing HLA-G1 in hESCs might be a feasible strategy for enhancing the engraftment of NPCs during transplantation.

Overexpression of sphingosine kinase 1 is predictive of poor prognosis in human breast cancer.

Sphingosine kinase 1 (SPHK1) is a bioactive lipid mediator that has been identified as a biomarker in various cancers and is considered to play an important role in tumor progression. In the present study, the expression level of SPHK1 was examined in breast cancer clinical specimens, and its association with patient survival was investigated to clarify the clinical significance of SPHK1 in breast cancer. SPHK1 mRNA expression was increased in breast cancer tissues compared with that in matched adjacent breast tissues in 19 of 32 paired tissue specimens (59.4%). Immunohistochemical analysis of 122 breast cancer cases revealed that the expression levels of SPHK1 were upregulated in 64 tumor tissues (52.5%), and increased expression levels of the protein were significantly associated with the presence of lymph node metastasis (P=0.0016), number of positive lymph nodes (P=0.0268) and presence of distant metastasis (P=0.0097). Increased SPHK1 protein expression was also associated with human epidermal growth factor receptor 2 status (P=0.0100), initial symptoms (P=0.0025) and tumor location (P=0.0457). Patients with increased SPHK1 protein expression had shorter overall survival and disease-free survival times compared with patients with lower SPHK1. Univariate and multivariate analyses indicated that high SPHK1 expression may be a poor prognostic factor. These results indicated that SPHK1 may perform an important role in breast cancer and may be a predictive factor in patients with breast cancer.