Uncovering the Molecular Composition and Architecture of the Bacillus subtilis Biofilm via Solid-State NMR Spectroscopy.

The complex and dynamic compositions of biofilms, along with their sophisticated structural assembly mechanisms, endow them with exceptional capabilities to thrive in diverse conditions that are typically unfavorable for individual cells. Characterizing biofilms in their native state is significantly challenging due to their intrinsic complexities and the limited availability of noninvasive techniques. Here, we utilized solid-state nuclear magnetic resonance (NMR) spectroscopy to analyze Bacillus subtilis biofilms in-depth. Our data uncover a dynamically distinct organization within the biofilm: a dominant, hydrophilic, and mobile framework interspersed with minor, rigid cores of limited water accessibility. In these heterogeneous rigid cores, the major components are largely self-assembled. TasA fibers, the most robust elements, further provide a degree of mechanical support for the cell aggregates and some lipid vesicles. Notably, rigid cell aggregates can persist even without the major extracellular polymeric substance (EPS) polymers, although this leads to slight variations in their rigidity and water accessibility. Exopolysaccharides are exclusively present in the mobile domain, playing a pivotal role in its water retention property. Specifically, all water molecules are tightly bound within the biofilm matrix. These findings reveal a dual-layered defensive strategy within the biofilm: a diffusion barrier through limited water mobility in the mobile phase and a physical barrier posed by limited water accessibility in the rigid phase. Complementing these discoveries, our comprehensive, in situ compositional analysis is not only essential for delineating the sophisticated biofilm architecture but also reveals the presence of alternative genetic mechanisms for synthesizing exopolysaccharides beyond the known pathway.

New Diterpenes and Diterpene Glycosides with Antibacterial Activity from Soft Coral Lemnalia bournei.

Five new biflorane-type diterpenoids, biofloranates E-I (1-5), and two new bicyclic diterpene glycosides, lemnaboursides H-I (6-7), along with the known lemnabourside, were isolated from the South China Sea soft coral Lemnalia bournei. Their chemical structures and stereochemistry were determined based on extensive spectroscopic methods, including time-dependent density functional theory (TDDFT) ECD calculations, as well as a comparison of them with the reported values. The antibacterial activities of the isolated compounds were evaluated against five pathogenic bacteria, and all of these diterpenes and diterpene glycosides showed antibacterial activities against Staphylococcus aureus and Bacillus subtilis, with MICs ranging from 4 to 64 µg/mL. In addition, these compounds did not exhibit noticeable cytotoxicities on A549, Hela, and HepG2 cancer cell lines, at 20 µM.

Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma.

BACKGROUND: Magnetic resonance imaging (MRI) performs well in the locoregional assessment of extranodal nasal-type NK/T-cell lymphoma (ENKTCL). It's important to assess the value of multi-modal MRI-based radiomics for estimating overall survival (OS) in patients with ENKTCL. METHODS: Patients with ENKTCL in a prospectively cohort were systemically reviewed and all the pretreatment MRI were acquisitioned. An unsupervised spectral clustering method was used to identify risk groups of patients and radiomic features. A nomogram-revised risk index (NRI) plus MRI radiomics signature (NRI-M) was developed, and compared with the NRI. RESULTS: The 2 distinct type I and II groups of the MRI radiomics signatures were identified. The 5-year OS rates between the type I and type II groups were 87.2% versus 67.3% (P = 0.002) in all patients, and 88.8% versus 69.2% (P = 0.003) in early-stage patients. The discrimination and calibration of the NRI-M for OS prediction demonstrated a better performance than that of either MRI radiomics or NRI, with a mean area under curve (AUC) of 0.748 and 0.717 for predicting the 5-year OS in all-stages and early-stage patients. CONCLUSIONS: The NRI-M model has good performance for predicting the prognosis of ENKTCL and may help design clinical trials and improve clinical decision making.

Three New Cembranoids from a Xisha Soft Coral Sarcophyton sp.

Chemical investigation of the Xisha soft coral Sarcophyton sp. has led to the isolation of eight cembrane-type diterpenoids, including three new compounds, namely sarcophynoids A-C (1-3), and five known analog compounds (4-8). Their structures were clarified based on spectroscopic analysis, and computer-assisted methods including TDDFT-ECD calculation and the quantum mechanical-nuclear magnetic resonance (QM-NMR) method. All the above compounds were tested for their antibacterial activities. Among them, compounds 4-7 and 8 exhibited antibacterial activities against S. aureus, B. subtilis, and P. aeruginosa, with MIC of 4-64 µg/mL.

Enhanced Antibacterial Ability of Electrospun PCL Scaffolds Incorporating ZnO Nanowires.

The infection of implanted biomaterial scaffolds presents a major challenge. Existing therapeutic solutions, such as antibiotic treatment and silver nanoparticle-containing scaffolds are becoming increasingly impractical because of the growth of antibiotic resistance and the toxicity of silver nanoparticles. We present here a novel concept to overcome these limitations, an electrospun polycaprolactone (PCL) scaffold functionalised with zinc oxide nanowires (ZnO NWs). This study assessed the antibacterial capabilities and biocompatibility of PCL/ZnO scaffolds. The fabricated scaffolds were characterised by SEM and EDX, which showed that the ZnO NWs were successfully incorporated and distributed in the electrospun PCL scaffolds. The antibacterial properties were investigated by co-culturing PCL/ZnO scaffolds with Staphylococcus aureus. Bacterial colonisation was reduced to 51.3% compared to a PCL-only scaffold. The biocompatibility of the PCL/ZnO scaffolds was assessed by culturing them with HaCaT cells. The PCL scaffolds exhibited no changes in cell metabolic activity with the addition of the ZnO nanowires. The antibacterial and biocompatibility properties make PCL/ZnO a good choice for implanted scaffolds, and this work lays a foundation for ZnO NWs-infused PCL scaffolds in the potential clinical application of tissue engineering.

Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics.

BACKGROUND: Histopathologic evaluation after surgery is the gold standard to evaluate treatment response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). However, it cannot be used to guide organ-preserving strategies due to poor timeliness. PURPOSE: To develop and validate a multiscale model incorporating radiomics and pathomics features for predicting pathological good response (pGR) of down-staging to stage ypT0-1N0 after nCRT. STUDY TYPE: Retrospective. POPULATION: A total of 153 patients (median age, 55 years; 109 men; 107 training group; 46 validation group) with clinicopathologically confirmed LARC. FIELD STRENGTH/SEQUENCE: A 3.0-T; fast spin echo T2 -weighted and single-shot EPI diffusion-weighted images. ASSESSMENT: The differences in clinicoradiological variables between pGR and non-pGR groups were assessed. Pretreatment and posttreatment radiomics signatures, and pathomics signature were constructed. A multiscale pGR prediction model was established. The predictive performance of the model was evaluated and compared to that of the clinicoradiological model. STATISTICAL TESTS: The χ2 test, Fisher's exact test, t-test, the minimum redundancy maximum relevance algorithm, the least absolute shrinkage and selection operator logistic regression algorithm, regression analysis, receiver operating characteristic curve (ROC) analysis, Delong method. P < 0.05 indicated a significant difference. RESULTS: Pretreatment radiomics signature (odds ratio [OR] = 2.53; 95% CI: 1.58-4.66), posttreatment radiomics signature (OR = 9.59; 95% CI: 3.04-41.46), and pathomics signature (OR = 3.14; 95% CI: 1.40-8.31) were independent factors for predicting pGR. The multiscale model presented good predictive performance with areas under the curve (AUC) of 0.93 (95% CI: 0.88-0.98) and 0.90 (95% CI: 0.78-1.00) in the training and validation groups, those were significantly higher than that of the clinicoradiological model with AUCs of 0.69 (95% CI: 0.55-0.82) and 0.68 (95% CI: 0.46-0.91) in both groups. DATA CONCLUSION: A model incorporating radiomics and pathomics features effectively predicted pGR after nCRT in patients with LARC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 4.

Added-value of dynamic contrast-enhanced MRI on prediction of tumor recurrence in locally advanced cervical cancer treated with chemoradiotherapy.

OBJECTIVES: To evaluate whether the DCE-MRI derived parameters integrated into clinical and conventional imaging variables may improve the prediction of tumor recurrence for locally advanced cervical cancer (LACC) patients following concurrent chemoradiotherapy (CCRT). METHODS: Between March 2014 and November 2019, 79 consecutive LACC patients who underwent pelvic MRI examinations with DCE-MRI sequence before treatment were prospectively enrolled. The primary outcome was disease-free survival (DFS). DCE-MRI derived parameters, conventional imaging, and clinical factors were collected. Univariate and multivariate Cox hazard regression analyses were performed to evaluate these parameters in the prediction of DFS. The independent and prognostic interested variables were combined to build a prediction model compared with the clinical International Federation of Gynecological (FIGO) staging system. RESULTS: Lymph node metastasis (LNM) and the mean value of ve (ve_mean) were independently associated with tumor recurrence (all p < 0.05). The prediction model based on T stage, LNM, and ve_mean demonstrated a moderate predictive capability in identifying LACC patients with a high risk of tumor recurrence; the model was more accurate than the FIGO staging system alone (c-index: 0.735 vs. 0.661) and the combination of ve_mean and the FIGO staging system (c-index: 0.735 vs. 0.688). Moreover, patients were grouped into low-, medial-, and high-risk levels based on the advanced T stage, positive LNM, and ve_mean < 0.361, with which the 2-year DFS was significantly stratified (p < 0.001). CONCLUSIONS: The ve_mean from DCE-MRI could be used as a useful biomarker to predict DFS in LACC patients treated with CCRT as an assistant of LNM and T stage. KEY POINTS: Lower ve_mean is an independent predictor of poor prognosis for disease-free survival in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (hazard ratio [HR]: 0.016, p<0.023). A combined prediction model based on advanced T stage, LNM, and ve_mean performed better than the FIGO staging system alone.

Sinuscalide A: An Antiviral Norcembranoid with an 8/8-Fused Carbon Scaffold from the South China Sea Soft Coral Sinularia scabra.

Sinuscalide A (1), featuring an uncommon 8/8-fused carbon scaffold, three new norditerpenes, sinuscalides B-D (2-4), and sinuscatone A (5), with a 5/4/9 tricyclic carbon ring system, along with four known compounds were isolated from the South China Sea soft coral Sinularia scabra. The structures of the new compounds were established by extensive spectroscopic analysis, X-ray diffraction, and electronic circular dichroism (ECD). A plausible biosynthetic pathway for 1 was proposed. In a bioassay, compound 1 showed antiviral activity against human enterovirus EV71 (IC50 = 5.0 µM) and an inhibitory effect against RANKL-induced osteoclastogenesis (92.3% inhibition at 10 µM). Compound 5 exhibited mild inhibition against Streptococcus pneumoniae and Salmonella paratyph (MIC 16 µg/mL).

Whole-lesion apparent diffusion coefficient (ADC) histogram as a quantitative biomarker to preoperatively differentiate stage IA endometrial carcinoma from benign endometrial lesions.

BACKGROUND: To assess the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in differentiating stage IA endometrial carcinoma (EC) from benign endometrial lesions (BELs) and characterizing histopathologic features of stage IA EC preoperatively. METHODS: One hundred and six BEL and 126 stage IA EC patients were retrospectively enrolled. Eighteen volumetric histogram parameters were extracted from the ADC map of each lesion. The Mann-Whitney U or Student's t-test was used to compare the differences between the two groups. Models based on clinical parameters and histogram features were established using multivariate logistic regression. Receiver operating characteristic (ROC) analysis and calibration curves were used to assess the models. RESULTS: Stage IA EC showed lower ADC10th, ADC90th, ADCmin, ADCmax, ADCmean, ADCmedian, interquartile range, mean absolute deviation, robust mean absolute deviation (rMAD), root mean squared, energy, total energy, entropy, variance, and higher skewness, kurtosis and uniformity than BELs (all p < 0.05). ADCmedian yielded the highest area under the ROC curve (AUC) of 0.928 (95% confidence interval [CI] 0.895-0.960; cut-off value = 1.161 × 10-3 mm2/s) for differentiating stage IA EC from BELs. Moreover, multivariate analysis demonstrated that ADC-score (ADC10th + skewness + rMAD + total energy) was the only significant independent predictor (OR = 2.641, 95% CI 2.045-3.411; p < 0.001) for stage IA EC when considering clinical parameters. This ADC histogram model (ADC-score) achieved an AUC of 0.941 and a bias-corrected AUC of 0.937 after bootstrap resampling. The model performed well for both premenopausal (accuracy = 0.871) and postmenopausal (accuracy = 0.905) patients. Besides, ADCmin and ADC10th were significantly lower in Grade 3 than in Grade 1/2 stage IA EC (p = 0.022 and 0.047). At the same time, no correlation was found between ADC histogram parameters and the expression of Ki-67 in stage IA EC (all p > 0.05). CONCLUSIONS: Whole-lesion ADC histogram analysis could serve as an imaging biomarker for differentiating stage IA EC from BELs and assisting in tumor grading of stage IA EC, thus facilitating personalized clinical management for premenopausal and postmenopausal patients.

Development and validation of a nomogram for predicting the 6-months survival rate of patients undergoing incident hemodialysis in China.

BACKGROUND: The all-cause mortality of patients undergoing hemodialysis (HD) is higher than in the general population. The first 6 months after dialysis are important for new patients. The aim of this study was to develop and validate a nomogram for predicting the 6-month survival rate of HD patients. METHODS: A prediction model was constructed using a training cohort of 679 HD patients. Multivariate Cox regression analyses were performed to identify predictive factors. The identified factors were used to establish a nomogram. The performance of the nomogram was assessed using the C-index and calibration plots. The nomogram was validated by performing discrimination and calibration tests on an additional cohort of 173 HD patients. RESULTS: During a follow-up period of six months, 47 and 16 deaths occurred in the training cohort and validation cohort, respectively, representing a mortality rate of 7.3% and 9.2%, respectively. The nomogram comprised five commonly available predictors: age, temporary dialysis catheter, intradialytic hypotension, use of ACEi or ARB, and use of loop diuretics. The nomogram showed good discrimination in the training cohort [C-index 0.775(0.693-0.857)] and validation cohort [C-index 0.758(0.677-0.836)], as well as good calibration, indicating that the performance of the nomogram was good. The total score point was then divided into two risk classifications: low risk (0-90 points) and high risk (≥ 91 points). Further analysis showed that all-cause mortality was significantly different between the high-risk group and the low-risk group. CONCLUSIONS: The constructed nomogram accurately predicted the 6-month survival rate of HD patients, and thus it can be used in clinical decision-making.

Submucosal Enhancing Stripe as a Contrast Material-enhanced MRI-based Imaging Feature for the Differentiation of Stage T0-T1 from Early T2 Rectal Cancers.

Background Accurate differentiation of stage T0-T1 rectal tumors from stage T2 rectal tumors facilitates the selection of appropriate surgical treatment. MRI is a recommended technique for local staging, but its ability to distinguish T1 from T2 tumors is poor. Purpose To explore the value of a submucosal enhancing stripe (SES), an uninterrupted enhancing band between the rectal tumor and the muscular layer on contrast material-enhanced T1-weighted images, as a potential imaging feature to differentiate T0-T1 from T2 rectal tumors. Materials and Methods This retrospective study included patients with pT0-T1 and pT2 rectal tumors who underwent pretreatment MRI and rectal tumor resection between January 2012 and November 2019. Two radiologists independently evaluated tumor characteristics (SES; status of muscularis propria [SMP]; and tumor shape, location, and size) at MRI. The associations of clinical and imaging characteristics with stage T0-T1 or T2 tumors were assessed, ß values were calculated, and predictive models were built. The diagnostic accuracies for the differentiation of T0-T1 tumors from T2 tumors with SES and SMP were compared. Results Data from 431 patients (mean age, 60 years ± 10 [standard deviation]; 261 men) were evaluated. SES (ß = 3.9; 95% CI: 3.1, 4.7; P < .001), SMP (ß = 1.3; 95% CI: 0.7, 1.9; P < .001), and carpetlike shape (ß = 1.6; 95% CI: 0.5, 2.8; P = .01) were independent factors distinguishing T0-T1 tumors from T2 tumors. The diagnostic accuracy was 87% (95% CI: 84, 90; 376 of 431) for SES and 67% (95% CI: 63, 72; 290 of 431) for SMP (P < .001). Conclusion Submucosal enhancing stripe (SES) at contrasted-enhanced MRI, status of muscularis propria (SMP) on T2-weighted images, and tumor shape can serve as independent imaging features to differentiate stage T0-T1 rectal tumors from stage T2 rectal tumors. Moreover, SES is a more accurate feature than is SMP. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Whole-tumor texture model based on diffusion kurtosis imaging for assessing cervical cancer: a preliminary study.

OBJECTIVES: To evaluate the diagnostic potential of diffusion kurtosis imaging (DKI) functional maps with whole-tumor texture analysis in differentiating cervical cancer (CC) subtype and grade. METHODS: Seventy-six patients with CC were enrolled. First-order texture features of the whole tumor were extracted from DKI and DWI functional maps, including apparent kurtosis coefficient averaged over all directions (MK), kurtosis along the axial direction (Ka), kurtosis along the radial direction (Kr), mean diffusivity (MD), fractional anisotropy (FA), and ADC maps, respectively. The Mann-Whitney U test and ROC curve were used to select the most representative texture features. Models based on each individual and combined functional maps were established using multivariate logistic regression analysis. Conventional parameters-the average values of ADC and DKI parameters derived from the conventional ROI method-were also evaluated. RESULTS: The combined model based on Ka, Kr, MD, and FA maps yielded the best diagnostic performance in discrimination of cervical squamous cell cancer (SCC) and cervical adenocarcinoma (CAC) with the highest AUC (0.932). Among individual functional map derived models, Kr map-derived model showed the best performance when differentiating tumor subtypes (AUC = 0.828). MK_90th percentile was useful for distinguishing high-grade and low-grade in SCC tumors with an AUC of 0.701. The average values of MD, FA, and ADC were significantly different between SCC and CAC, but no conventional parameters were useful for tumor grading. CONCLUSIONS: The whole-tumor texture analysis applied to DKI functional maps can be used for differential diagnosis of cervical cancer subtypes and grading SCC. KEY POINTS: • The whole-tumor texture analysis applied to DKI functional maps allows accurate differential diagnosis of CC subtype and grade. • The combined model derived from multiple functional maps performs significantly better than the single models when differentiating tumor subtypes. • MK_90th percentile was useful for distinguishing poorly and well-/moderately differentiated SCC tumors with an AUC of 0.701.

Prognostic risk factors and survival models for T3 locally advanced rectal cancer: what can we learn from the baseline MRI?

OBJECTIVES: To evaluate the baseline MRI characteristics for predicting survival outcomes and construct survival models for risk stratification to facilitate personalized treatment and follow-up strategies in patients with MRI-defined T3 (mrT3) locally advanced rectal cancer (LARC). METHODS: We retrospectively reviewed 256 mrT3 LARC patients evaluated between 2008 and 2012 in our institution, with an average follow-up period of 6.8 ± 1.2 years. The baseline MRI characteristics, clinical data, and follow-up information were evaluated. The patients were randomized into a training cohort (TC, 186 patients) and validation cohort (VC, 70 patients). The TC dataset was used to develop multivariate nomograms for disease-free survival (DFS) and overall survival (OS), while the VC dataset was used for independent validation of the models. Harrell concordance (C) indices and Hosmer-Lemeshow calibration were used to evaluate the performances of the models. RESULTS: Baseline mrT3 substage, extramural venous invasion (EMVI) grading, mucinous adenocarcinoma, mesorectal fascia involvement, elevated pretreatment carcinoembryonic antigen level, and neoadjuvant chemoradiotherapy (NCRT) were independent predictors of DFS. T3 substage, EMVI grading, and NCRT were also independent predictors of OS. The nomograms constructed permitted the individualized prediction of 3-year and 5-year DFS and 5-year OS with high discrimination (C-index range, 0.833-0.892) and good calibration in the TC and VC. CONCLUSIONS: We have identified baseline MRI characteristics that help independently predict survival outcomes in patients with mrT3 LARC. The survival models based on these characteristics allow for the individualized pretreatment risk stratification in patients with mrT3 LARC. KEY POINTS: • Baseline MRI characteristics can independently stratify risk and predict survival outcomes in patients with mrT3 LARC. • The nomograms built using selected baseline MRI characteristics facilitate the individualized pretreatment risk stratification and help with clinical decision-making in patients with mrT3 LARC. • MR-defined risk factors should, therefore, be carefully reported in the baseline MRI evaluation.

Chemical Diversity and Biological Activity of Secondary Metabolites from Soft Coral Genus Sinularia since 2013.

Sinularia is one of the conspicuous soft coral species widely distributed in the world's oceans at a depth of about 12 m. Secondary metabolites from the genus Sinularia show great chemical diversity. More than 700 secondary metabolites have been reported to date, including terpenoids, norterpenoids, steroids/steroidal glycosides, and other types. They showed a broad range of potent biological activities. There were detailed reviews on the terpenoids from Sinularia in 2013, and now, it still plays a vital role in the innovation of lead compounds for drug development. The structures, names, and pharmacological activities of compounds isolated from the genus Sinularia from 2013 to March 2021 are summarized in this review.

Antimicrobial Terpenoids from South China Sea Soft Coral Lemnalia sp.

Chemical investigation of the South China Sea soft coral Lemnalia sp. afforded 13 structurally diverse terpenoids, including three new neolemnane sesquiterpene lineolemnene, E-G (1-3); a new aristolane-type sesquiterpenoid, 2-acetoxy-aristolane (4); four new decalin-type bicyclic diterpenes, named biofloranate A-D (5-8); a new serrulatane, named euplexaurene D (9); and a new aromadendrane-type diterpenoid cneorubin K (10), together with three known related compounds (11-13). The structures of the new compounds were elucidated by NMR spectroscopy, the Mosher's method, and ECD analysis. Compounds 1-13 were tested in a wide panel of biological assays. Lineolemnene J (3) showed weak cytotoxicity against the CCRF-CEM cancer cell line. The isolated new diterpenes, except euplexaurene D (9), demonstrated moderate antimicrobial activity against Bacillus subtilis and Staphylococcus aureus with a MIC of 4-64 µg/mL. Compound 2 exhibited a mild inhibitory effect against influenza A H1N1 virus (IC50 = 5.9 µM).

Six New Diterpene Glycosides from the Soft Coral Lemnaliabournei.

A chemical study on the extracts of soft coral Lemnalia bournei resulted in the isolation and identification of six new bicyclic diterpene glycosides including three new lemnaboursides E-G (1-3), and three new lemnadiolboursides A-C (4-6), along with three known lemnaboursides (7-9). Their structures were elucidated by detailed spectroscopic analysis, ECD analysis, chemical methods, and comparison with the literature data. Lemnadiolboursides A-C (4-6) contained a lemnal-1(10)-ene-7,12-diol moiety compared with the lemnaboursides. All these compounds were evaluated for antibacterial activity; cell growth inhibition of A549, Hela, HepG2, and CCRF-CEM cancer cell lines; and inhibition of LPS-induced NO production in RAW264.7 macrophages. The results indicated that compounds 1, 2, and 4-6 exhibited antibacterial activity against Staphylococcus aureus and Bacillus subtilis (MIC 4-16 µg/mL); compounds 1-9 displayed low cytotoxicity on the CCRF-CEM cell lines (IC50 10.44-27.40 µM); and compounds 1, 2, and 5 showed weak inhibition against LPS-induced NO production (IC50 21.56-28.06 µM).

Nomogram for predicting 1-, 5-, and 10-year survival in hemodialysis (HD) patients: a single center retrospective study.

OBJECTIVES: Risk of death is high for hemodialysis (HD) patients but it varies considerably among individuals. There is few clinical tool to predict long-term survival rates for HD patients yet. The aim of this study was to develop and validate a easy-to-use nomogram for prediction of 1-, 5-, and 10-year survival among HD patients. METHODS: This study retrospectively enrolled 643 adult HD patients who was randomly assigned to two cohorts: the training cohort (n = 438) and validation cohort (n = 205), univariate survival analyses were performed using Kaplan-Meier's curve with log-rank test and multivariate Cox regression analyses were performed to identify predictive factors, and a easy-to-use nomogram was established. The performance was assessed using the area under the curve (AUC), calibration plots, and decision curve analysis. RESULTS: The score included seven commonly available predictors: age, diabetes, use of arteriovenous fistula (AVF), history of emergency temporary dialysis catheter placement, cardiovascular disease (CVD), hemoglobin (Hgl), and no caregiver. The score revealed good discrimination in the training and validation cohort (AUC 0.779 and 0.758, respectively) and the calibration plots showed well calibration, indicating suitable performance of the nomogram model. Decision curve analysis showed that the nomogram added more net benefit compared with the treat-all strategy or treat-none strategy with a threshold probability of 10% or greater. CONCLUSIONS: This easy-to-use nomogram can accurately predict 1-, 5-, and 10-year survival for HD patients, which could be used in clinical decision-making and clinical care.

Genome-wide CRISPR knockout screens identify NCAPG as an essential oncogene for hepatocellular carcinoma tumor growth.

Hepatocellular carcinoma (HCC) is a common and deadly cancer with limited treatment options. Through genome-wide growth depletion screens using clustered regularly interspaced short palindromic repeats and expression profiling of primary HCC tumors, we identified 13 clinically relevant target genes with therapeutic potential. Subsequent functional annotation analysis revealed significant enrichment of these 13 genes in the cell cycle, cell death, and survival pathways. Non-structural maintenance of chromosomes condensin I complex subunit G (NCAPG) was ranked the highest among the depletion screens and multiple HCC expression datasets. Transient inhibition of NCAPG using specific small interfering RNAs resulted in a significant reduction in cell growth, migration, and the down-regulation of mitochondrial gene expression in vitro. Small homologous RNA-mediated knockdown of NCAPG significantly impaired cell viability, caused aberrant mitotic division, fragmented the mitochondrial network, and increased cell death in vitro. HCC cells with a reduced expression of NCAPG formed significantly smaller xenograft tumors in vivo. Importantly, high NCAPG expression was significantly associated with poorer overall and disease-free survival in HCC patients. High NCAPG expression is a novel prognostic biomarker to predict HCC early recurrence after surgical resection. In conclusion, NCAPG is an essential gene for HCC tumor cell survival. It represents a promising novel target for treating HCC and a prognostic biomarker for clinical management of HCC.-Wang, Y., Gao, B., Tan, P. Y., Handoko, Y. A., Sekar, K., Deivasigamani, A., Seshachalam, V. P., OuYang, H.-Y., Shi, M., Xie, C., Goh, B. K. P., Ooi, L. L., Hui, K. M. Genome-wide CRISPR knockout screens identify NCAPG as an essential oncogene for hepatocellular carcinoma tumor growth.

Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma.

OBJECTIVE: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) using histogram analysis of apparent diffusion coefficients (ADC). METHODS: Breath-hold diffusion weighted imaging (DWI) was performed in 64 patients (33 progressive and 31 stable) with biopsy-proven HCC prior to RFA. All patients had pre-treatment magnetic resonance imaging (MRI) and follow-up computed tomography (CT) or MRI. The ADC values (ADC10, ADC30, ADCmedian and ADCmax) were obtained from the histogram's 10th, 30th, 50th and 100th percentiles. The ratios of ADC10, ADC30, ADCmedian and ADCmax to the mean non-lesion area-ADC (RADC10, RADC30, RADCmedian, and RADCmax) were calculated. The two patient groups were compared. Key predictive factors for survival were determined using the univariate and multivariate analysis of the Cox model. The Kaplan-Meier survival analysis was performed, and pairs of survival curves based on the key factors were compared using the log-rank test. RESULTS: The ADC30, ADCmedian, ADCmax, RADC30, RADCmedian, and RADCmax were significantly larger in the progressive group than in the stable group (P<0.05). The median progression-free survival (PFS) was 22.9 months for all patients. The mean PFS for the stable and progressive groups were 47.7±1.3 and 9.8±1.3 months, respectively. Univariate analysis indicated that RADC10, RADC30, and RADCmedian were significantly correlated with the PFS [hazard ratio (HR)=31.02, 43.84, and 44.29, respectively, P<0.05 for all]. Multivariate analysis showed that RADCmedian was the only independent predictor of tumor progression (P=0.04). And the cutoff value of RADCmedian was 0.71. CONCLUSIONS: Pre-RFA ADC histogram analysis might serve as a useful biomarker for predicting tumor progression and survival in patients with HCC treated with RFA.

Bulleyaconitine A attenuates hyperexcitability of dorsal root ganglion neurons induced by spared nerve injury: The role of preferably blocking Nav1.7 and Nav1.3 channels.

Background Oral administration of Bulleyaconitine A, an extracted diterpenoid alkaloid from Aconitum bulleyanum plants, is effective for treating chronic pain in rats and in human patients, but the underlying mechanisms are poorly understood. Results As the hyperexcitability of dorsal root ganglion neurons resulting from the upregulation of voltage-gated sodium (Nav) channels has been proved critical for development of chronic pain, we tested the effects of Bulleyaconitine A on Nav channels in rat spared nerve injury model of neuropathic pain. We found that Bulleyaconitine A at 5 nM increased the threshold of action potentials and reduced the firing rate of dorsal root ganglion neurons in spared nerve injury rats but not in sham rats. Bulleyaconitine A preferably blocked tetrodotoxin-sensitive Nav channels over tetrodotoxin-resistant ones in dorsal root ganglion neurons of spared nerve injury rats. Bulleyaconitine A was more potent for blocking Nav1.3 and Nav1.7 than Nav1.8 in cell lines. The half maximal inhibitory concentration (IC50) values for resting Nav1.3, Nav1.7, and Nav1.8 were 995.6 ± 139.1 nM, 125.7 ± 18.6 nM, and 151.2 ± 15.4 µM, respectively, which were much higher than those for inactivated Nav1.3 (20.3 ± 3.4 pM), Nav1.7 (132.9 ± 25.5 pM), and Nav1.8 (18.0 ± 2.5 µM). The most profound use-dependent blocking effect of Bulleyaconitine A was observed on Nav1.7, less on Nav1.3, and least on Nav1.8 at IC50 concentrations. Bulleyaconitine A facilitated the inactivation of Nav channels in each subtype. Conclusions Preferably blocking tetrodotoxin-sensitive Nav1.7 and Nav1.3 in dorsal root ganglion neurons may contribute to Bulleyaconitine A's antineuropathic pain effect.