Multiparametric MRI-based intratumoral and peritumoral radiomics for predicting the pathological differentiation of hepatocellular carcinoma.

PURPOSE: To explore the predictive potential of intratumoral and multiregion peritumoral radiomics features extracted from multiparametric MRI for predicting pathological differentiation in hepatocellular carcinoma (HCC) patients. METHODS: A total of 265 patients with 277 HCCs (training cohort n = 193, validation cohort n = 84) who underwent preoperative MRI were retrospectively analyzed. The risk factors identified through stepwise regression analysis were utilized to construct a clinical model. Radiomics models based on MRI (arterial phase, portal venous phase, delayed phase) across various regions (entire tumor, Peri_5mm, Peri_10mm, Peri_20mm) were developed using the LASSO approach. The features obtained from the intratumoral region and the optimal peritumoral region were combined to design the IntraPeri fusion model. Model performance was assessed using the area under the curve (AUC). RESULTS: Larger size, non-smooth margins, and mosaic architecture were risk factors for poorly differentiated HCC (pHCC). The clinical model achieved AUCs of 0.77 and 0.73 in the training and validation cohorts, respectively, while the intratumoral model achieved corresponding AUC values of 0.92 and 0.82. The Peri_10mm model demonstrated superior performance to the Peri_5mm and Peri_20mm models, with AUC values of 0.87 vs. 0.84 vs. 0.73 in the training cohort and 0.80 vs. 0.77 vs. 0.68 in the validation cohort, respectively. The IntraPeri model exhibited remarkable AUC values of 0.95 and 0.86 in predicting pHCC in the training and validation cohorts, respectively. CONCLUSIONS: Our study highlights the potential of a multiparametric MRI-based radiomic model that integrates intratumoral and peritumoral features as a tool for predicting HCC differentiation. CRITICAL RELEVANCE STATEMENT: Both clinical and multiparametric MRI-based radiomic models, particularly the intratumoral radiomic model, are non-invasive tools for predicting HCC differentiation. Importantly, the IntraPeri fusion model exhibited remarkable predictiveness for individualized HCC differentiation. KEY POINTS: • Both the intratumoral radiomics model and clinical features were useful for predicting HCC differentiation. • The Peri_10mm radiomics model demonstrated better diagnostic ability than other peritumoral region-based models. • The IntraPeri radiomics fusion model outperformed the other models for predicting HCC differentiation.

Machine Learning-Based CEMRI Radiomics Integrating LI-RADS Features Achieves Optimal Evaluation of Hepatocellular Carcinoma Differentiation.

Purpose: To develop and compare various machine learning (ML) classifiers that employ radiomics extracted from contrast-enhanced magnetic resonance imaging (CEMRI) for diagnosing pathological differentiation of hepatocellular carcinoma (HCC), and validate the performance of the best model. Methods: A total of 251 patients with HCCs (n = 262) were assigned to a training (n = 200) cohort and a validation (n = 62) cohort. A collection of 5502 radiomics signatures were extracted from the CEMRI images for each HCC nodule. To reduce redundancy and dimensionality, Spearman rank correlation, minimum redundancy maximum relevance (mRMR), and the least absolute shrinkage and selection operator (LASSO) approach were employed. Eight ML classifiers were trained to obtain the best radiomics model. The performance of each model was evaluated based on the area under the receiver operating characteristic curve (AUC). The radiomics model was integrated with liver imaging reporting and data system (LI-RADS) features to design a combined model. Results: The eXtreme Gradient Boosting (XGBoost)-based radiomics model outperformed other ML classifiers in evaluating pHCC, achieving an AUC of 1.00 and accuracy of 1.00 in the training cohort. The LI-RADS model demonstrated an AUC value of 0.77 and 0.82 in the training and validation cohorts. The combined model exhibited best performance in both the training and validation cohorts, with AUCs of 1.00 and 0.86 for evaluating HCC differentiation, respectively. Conclusion: CEMRI radiomics integrating LI-RADS features demonstrated excellent performance in evaluating HCC differentiation, suggesting an optimal clinical decision tool for individualized diagnosis of HCC differentiation.

CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning.

RATIONALE AND OBJECTIVES: To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on contrast-enhanced magnetic resonance imaging (CEMRI) and validate its efficiency for predicting microvascular invasion (MVI) and pathological differentiation in hepatocellular carcinoma (HCC). METHODS: CEMRI images were retrospectively obtained from 277 HCCs in 265 patients. Habitat analysis and DL features were extracted from the CEMRI images and selected with the least absolute shrinkage and selection operator approach to develop ITH and DL models, respectively, and these robust features were then integrated to design a fusion model for predicting MVI and poorly differentiated HCC (pHCC). The predictive value of the three models was assessed using the area under the receiver operating characteristic curve (AUC). RESULTS: The training and validation sets comprised 221 HCCs and 56 HCCs, respectively. The ITH and DL models presented AUC values of (0.90 vs. 0.87) for predicting MVI in the training set, with AUC values of 0.86 and 0.83 in the validation set. The AUC values of the ITH model to predict pHCC were 0.90 and 0.86 in the two sets, respectively; they were 0.84 and 0.80 for the DL model. The fusion model yielded the best performance for predicting MVI and pHCC in the training set (AUC=0.95, 0.90) and in the validation set (AUC=0.89, 0.87), respectively. CONCLUSION: A fusion model integrating ITH and DL features derived from CEMRI images can serve as an excellent imaging biomarker for predicting aggressive characteristics in HCC.

Magnolol alleviates pulmonary fibrosis inchronic obstructive pulmonary disease by targeting transient receptor potential vanilloid 4-ankyrin repeat domain.

Transient receptor potential vanilloid 4 (TRPV4) plays a role in regulating pulmonary fibrosis (PF). While several TRPV4 antagonists including magnolol (MAG), have been discovered, the mechanism of action is not fully understood. This study aimed to investigate the effect of MAG on alleviating fibrosis in chronic obstructive pulmonary disease (COPD) based on TRPV4, and to further analyze its mechanism of action on TRPV4. COPD was induced using cigarette smoke and LPS. The therapeutic effect of MAG on COPD-induced fibrosis was evaluated. TRPV4 was identified as the main target protein of MAG using target protein capture with MAG probe and drug affinity response target stability assay. The binding sites of MAG at TRPV4 were analyzed using molecular docking and small molecule interaction with TRPV4-ankyrin repeat domain (ARD). The effects of MAG on TRPV4 membrane distribution and channel activity were analyzed by co-immunoprecipitation, fluorescence co-localization, and living cell assay of calcium levels. By targeting TRPV4-ARD, MAG disrupted the binding between phosphatidylinositol 3 kinase γ and TRPV4, leading to hampered membrane distribution on fibroblasts. Additionally, MAG competitively impaired ATP binding to TRPV4-ARD, inhibiting TRPV4 channel opening activity. MAG effectively blocked the fibrotic process caused by mechanical or inflammatory signals, thus alleviating PF in COPD. Targeting TRPV4-ARD presents a novel treatment strategy for PF in COPD.

Cerebral Gray Matter Volume Changes in Patients with Neuropathic Pain from Total Brachial Plexus Injury.

INTRODUCTION: Total brachial plexus injury not only significantly affects the motor and sensory function of the affected upper limbs but also causes further physical and mental damage to patients with long-term intractable pain. Previous studies mainly focused on the surgical treatment, while only a few paid attention to the intractable neuropathic pain caused by this injury. Changes in the volume of gray matter in the brain are thought to be associated with chronic neuropathic pain. METHODS: Voxel-based morphometry analysis was used to compare the difference in cerebral gray matter volume between total brachial plexus injury patients with neuropathic pain and healthy controls. Correlations between pain duration, pain severity, and GM changes were analyzed. RESULTS: The volume of cerebral gray matter in the patient group was decreased significantly in multiple regions, including the parahippocampal gyrus, paracentric lobule, inferior frontal gyrus, auxiliary motor cortex, middle occipital gyrus, right middle temporal gyrus, while it was increased in the insular, pons, middle frontal gyrus, cingulate gyrus, inferior parietal lobule, bilateral thalamus, and globus pallidus. There were no significant correlations between pain duration and rGMV changes, while a positive correlation was observed between pain severity and rGMV changes in one specific region, involving the anterior cingulate cortex. CONCLUSION: Total brachial plexus injury patients with chronic pain have widespread regions of gray matter atrophy and hypertrophy. The only positive correlation was observed between pain severity and rGMV changes in one specific region, suggesting that nociceptive stimuli trigger a variety of nonpain-specific processes, which confirms the multidimensional nature of pain.

Involvement of Methoprene-tolerant and Krüppel homolog 1 in juvenile hormone-mediated vitellogenesis of female Liposcelis entomophila (End.) (Psocoptera: Liposcelididae).

Methoprene-tolerant (Met) as an intracellular receptor of juvenile hormone (JH) and the Krüppel-homolog 1 (Kr-h1) as a JH-inducible transcription factor had been proved to contribute to insect reproduction. Their functions vary in different insect orders, however, they are not clear in Psocoptera. In this study, LeMet and LeKr-h1 were identified and their roles in vitellogenesis and ovarian development were investigated in Liposcelis entomophila (Enderlein). Treatment with exogenous JH III significantly induced the expression of LeKr-h1, LeVg, and LeVgR. Furthermore, silencing LeMet and LeKr-h1 remarkably reduced the transcription of LeVg and LeVgR, disrupted the production of Vg in fat body and the uptake of Vg by oocytes, and ultimately led to a decline in fecundity. The results indicated that the JH signaling pathway was essential to the reproductive process of this species. Interestingly, knockdown of LeMet or LeKr-h1 also resulted in fluctuations in the expression of FoxO, indicating the complex regulatory interactions between different hormone factors. Besides, knockdown of both LeMet and LeKr-h1 significantly increased L. entomophila mortality. Our study provides initial insight into the roles of JH signaling in the female reproduction of psocids and provided evidence that RNAi-mediated knockdown of Met or Kr-h1 is a potential pest control strategy.

Ligustilide attenuates airway remodeling in COPD mice by covalently binding to MH2 domain of Smad3 in pulmonary epithelium, disrupting the Smad3-SARA interaction.

Airway remodeling is one of the hallmarks of chronic obstructive pulmonary disease (COPD) and is closely related to the dysregulation of epithelial-mesenchymal transition (EMT). Smad3, an important transcriptional regulator responsible for transducing TGF-ß1 signals, is a promising target for EMT modulation. We found that ligustilide (Lig), a novel Smad3 covalent inhibitor, effectively inhibited airway remodeling in cigarette smoke (CS) combined with lipopolysaccharide (LPS)-induced COPD mice. Oral administration of an alkynyl-modified Lig probe was used to capture and trace target proteins in mouse lung tissue, revealing Smad3 in airway epithelium as a key target of Lig. Protein mass spectrometry and Smad3 mutation analysis via in-gel imaging indicated that the epoxidized metabolite of Lig covalently binds to the MH2 domain of Smad3 at Cys331/337. This irreversible bonding destroys the interaction of Smad3-SARA, prevents Smad3 phosphorylation activation, and subsequently suppresses the nuclear transfer of p-Smad3, the EMT process, and collagen deposition in TGF-ß1-stimulated BEAS-2B cells and COPD mice. These findings provide experimental support that Lig attenuates COPD by repressing airway remodeling which is attributed to its suppression on the activation of EMT process in the airway epithelium via targeting Smad3 and inhibiting the recruitment of the Smad3-SARA heterodimer in the TGF-ß1/Smad3 pathway.

Matrix-Directed Mineralization for Bulk Structural Materials.

Mineral-based bulk structural materials (MBSMs) are known for their long history and extensive range of usage. The inherent brittleness of minerals poses a major problem to the performance of MBSMs. To overcome this problem, design principles have been extracted from natural biominerals, in which the extraordinary mechanical performance is achieved via the hierarchical organization of minerals and organics. Nevertheless, precise and efficient fabrication of MBSMs with bioinspired hierarchical structures under mild conditions has long been a big challenge. This Perspective provides a panoramic view of an emerging fabrication strategy, matrix-directed mineralization, which imitates the in vivo growth of some biominerals. The advantages of the strategy are revealed by comparatively analyzing the conventional fabrication techniques of artificial hierarchically structured MBSMs and the biomineral growth processes. By introducing recent advances, we demonstrate that this strategy can be used to fabricate artificial MBSMs with hierarchical structures. Particular attention is paid to the mass transport and the precursors that are involved in the mineralization process. We hope this Perspective can provide some inspiring viewpoints on the importance of biomimetic mineralization in material fabrication and thereby spur the biomimetic fabrication of high-performance MBSMs.

Spread of Carbapenem-Resistant Klebsiella pneumoniae Clinical Isolates Producing NDM-Type Metallo-ß-Lactamase in Myanmar.

A total of 38 isolates of carbapenem-resistant Klebsiella pneumoniae harboring blaNDM were obtained during surveillance of 10 hospitals in Myanmar. Of these 38 isolates, 19 (50%) harbored genes encoding 16S rRNA methylases, such as armA or rmtB. The K. pneumoniae strains tested belonged to 17 sequence types (STs), including the high-risk clonal lineages ST101 and ST147. The ST101 and ST147 isolates carried IncFII plasmids harboring blaNDM-5 and IncFIB(pQil) plasmids harboring blaNDM-1, respectively. These results indicate that IncFII plasmids harboring blaNDM-5 and IncFIB(pQil) plasmids harboring blaNDM-1 have been spreading in K. pneumoniae ST101 and ST147 isolates, respectively, in Myanmar. IMPORTANCE The emergence of carbapenem-resistant K. pneumoniae has become a serious problem in medical settings worldwide. The present study demonstrated that carbapenem-resistant K. pneumoniae strains have been spreading in medical settings in Myanmar. In particular, plasmid genes encoding NDMs and 16S rRNA methylases have been spreading in K. pneumoniae high-risk clones.

Construction of ceRNA networks with different types of IDH1 mutation status in low-grade glioma patients.

Background: Isocitrate dehydrogenase 1 (IDH1) mutation status is related to the prognosis and immune microenvironment of glioma. Long non-coding ribonucleic acids (lncRNAs) interact with microRNAs (miRNAs), and play roles in the competitive endogenous RNA (ceRNA) network and tumor progression. Methods: Data on low-grade glioma (LGG) IDH1 mutation was acquired from The Cancer Genome Atlas (TCGA). An empirical analysis of differential gene expression was conducted to identify differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed lncRNAs (DElncRNAs). Survival-associated genes were identified by a univariate Cox regression analysis. An enrichment analysis was conducted to explore the gene ontology and pathways of the DEmRNAs. Results: Eighty-eight DEIDH1mRNAs, 88 DEIDH1lncRNAs, and 6 DEIDH1miRNAs were identified to construct a ceRNA network of LGG patients. Validated by Chinese Glioma Genome Atlas and our LGG patients of gene expression and survival, and the colorectal neoplasia differentially expressed (CRNDE), HOXA transcript antisense RNA, myeloid-specific 1 (HOTAIRM1)/miRNA-206a/hepatocyte nuclear factor 4 (HNF4G) axis was determined. Conclusions: We established a ceRNA network by integrating the different IDH1 mutation statuses of LGG patients, and identified HNF4G, CRNDE, and HOTAIRM1 as genes related to the prognosis of and immune infiltration in LGG patients. Our findings suggest that these genes may be targets for LGG treatment, especially for patients with the wild-type IDH1 gene variants.

The prognostic significance of a novel ferroptosis-related gene model in breast cancer.

Background: Breast cancer (BRCA) is the most common malignancy with high heterogeneity in women, and the prognostic prediction for BRCA has remained poor. Ferroptosis, a recently identified iron-dependent form of programmed cell death, plays a significant role in BRCA treatment. Some BRCA cell lines are proven to be sensitive to ferroptosis, and some ferroptosis-related genes have been identified as divers or suppressors in the progress of BRCA. This study aimed to explore the prognostic value of ferroptosis-related genes in BRCA. Methods: A ferroptosis-related gene list, messenger RNA (mRNA) gene expression of BRCA patients, and corresponding clinicopathological data were collected from public databases. The patients of the Cancer Genome Atlas (TCGA) were identified as the training cohort, and the ones of the Gene Expression Omnibus (GEO) were looked as the validation cohort. Univariate Cox regression analysis was utilized to identify prognostic ferroptosis-related genes, and subsequent multivariate analysis further screened out important genes to establish a prognostic model. Receiver operating characteristic (ROC) curves were used to validate the model in both internal and external cohorts. Functional analysis was generated to evaluate the potential correlation between tumor immunity and ferroptosis-related genes in BRCA. Results: A ferroptosis-related gene signature stratifying patients into 2 risk score groups was established based on the TCGA cohort, and validated in the GEO cohort. Patients with lower risk scores had better overall survival (OS) compared to those with higher risk scores (P<0.001, TCGA cohort; P<0.05, GEO cohort). The risk score was independently associated with the OS of BRCA patients (P<0.001, TCGA cohort; P<0.05, GEO cohort). The area under the curves (AUCs) of the model in the training and validation cohorts were all around 0.7. Immune-related biological pathways and immune status were significantly different between the 2 divided risk groups. Conclusions: The novel prognostic model composed of 9 ferroptosis-related genes accurately predicts the survival of BRCA patients. It might provide a new sight for ferroptosis-related BRCA therapy.

Microencapsulation of Capsaicin in Chitosan Microcapsules: Characterization, Release Behavior, and Pesticidal Properties against Tribolium castaneum (Herbst).

Capsaicin is a capsaicinoid in hot chili peppers, with excellent antibacterial and antimicrobial activities and a good safety profile, but its poor solubility and instability restrict its effectiveness. This limitation may be mitigated by encapsulation. Herein, capsaicin microcapsules (CCMs) were prepared through layer-by-layer self-assembly, using chitosan and carboxymethyl chitosan as shell materials. The chemical and microstructure structural characterization was evaluated by the methods of Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The SEM indicated the microcapsules were irregular in shape with an average size of about 100 µm. The encapsulation had a high loading efficiency of 64.31%. FTIR and XRD revealed the absence of the interaction between the core and shell materials and the amorphous nature of the CCMs. The analysis results of the microcapsules' release behavior showed the burst release of capsaicin in 7 days and a slow progression afterward in three solutions, with the highest release properties in a basic solution, followed by acidic and neutral salt solutions. The entomotoxicity of CCMs was conducted against Tribolium castaneum (Herbst), and its efficacy was compared with pure capsaicin. The CCMs were found to be highly effective against this pest. The LC50 value for capsaicin and its microcapsules was 31.37 and 29.75 mg/kg on adults, respectively. According to these values, T. castaneum's development and reproduction were significantly inhibited compared with the control group. The excellent physicochemical characteristics and insecticidal performance show a high application value for integrated pest control.

Artificial Nacre with High Toughness Amplification Factor: Residual Stress-Engineering Sparks Enhanced Extrinsic Toughening Mechanisms.

The high fracture toughness of mollusk nacre is predominantly attributed to the structure-associated extrinsic mechanisms such as platelet sliding and crack deflection. While the nacre-mimetic structures are widely adopted in artificial ceramics, the extrinsic mechanisms are often weakened by the relatively low tensile strength of the platelets with a large aspect ratio, which makes the fracture toughness of these materials much lower than expected. Here, it is demonstrated that the fracture toughness of artificial nacre materials with high inorganic contents can be improved by residual stress-induced platelet strengthening, which can catalyze more effective extrinsic toughening mechanisms that are specific to the nacre-mimetic structures. Thereby, while the absolute fracture toughness of the materials is not comparable with advanced ceramic-based composites, the toughness amplification factor of the material reaches 16.1 ± 1.1, outperforming the state-of-the-art biomimetic ceramics. The results reveal that, with the merit of nacre-mimetic structural designs, the overall fracture toughness of the artificial nacre can be improved by the platelet strengthening through extrinsic toughening mechanisms, although the intrinsic fracture toughness may decrease at platelet level due to the strengthening. It is anticipated that advanced structural ceramics with exceeding performance can be fabricated through these unconventional strategies.

DCE-MRI of esophageal carcinoma using star-VIBE compared with conventional 3D-VIBE.

To investigate the value of the star-VIBE sequence in dynamic contrast-enhanced magnetic resonance imaging of esophageal carcinoma under free breathing conditions. From February 2019 to June 2020, 60 patients with esophageal carcinoma were prospectively enrolled to undergo dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with the K-space golden-angle radial stack-of-star acquisition scheme (star-VIBE) sequence (Group A) or conventional 3D volumetric-interpolated breath-hold examination (3D-VIBE) sequence (Group B), completely randomized grouping. The image quality of DCE-MRI was subjectively evaluated at five levels and objectively evaluated according to the image signal-to-noise ratio (SNR) and contrast-noise ratio (CNR). The DCE-MRI parameters of volume transfer constant (Ktrans), rate constant (Kep) and vascular extracellular volume fraction (Ve) were calculated using the standard Tofts double-compartment model in the post-perfusion treatment software TISSUE 4D (Siemens). Each group included 30 randomly selected cases. There was a significant difference in subjective classification between the groups (35.90 vs 25.10, p = 0.009). The study showed that both the SNR and CNR of group A were significantly higher than those of group B (p = 0.004 and < 0.001, respectively). There was no significant difference in Ktrans, Kep or Ve between the groups (all p > 0.05). The star-VIBE sequence can be applied in DCE-MRI examination of esophageal carcinoma, which can provide higher image quality than the conventional 3D-VIBE sequence in the free breathing state.

Nicotine Oral Administration Attenuates DSS-Induced Colitis Through Upregulation of Indole in the Distal Colon and Rectum in Mice.

Nicotine affects the gastrointestinal environment and modulates ulcerative colitis (UC). However, the associations among nicotine, gut metabolites, and UC are still largely unknown. We investigated whether orally administered nicotine affected gut metabolites and dextran sodium sulfate (DSS)-induced colitis. C57BL/6 male mice were orally administered nicotine solution in drinking water prior to inducing DSS-induced colitis. Short-chain fatty acids (SCFAs) and indole in gut contents and fecal samples were measured by GC-MS and hydroxylamine-based indole assays, respectively. Oral administration of nicotine increased indole concentration in feces, but, in contrast, SCFA values did not differ with nicotine administration. Indole levels were increased in the distal colon and rectum but not in the cecum and proximal colon. DSS-induced colitis was less severe clinically and histological changes were minimal in the rectum of orally nicotine-administered mice compared to mice drinking only water. 16S rRNA microbiome on the feces revealed an increasing in Clostridium and Porphyromonas in nicotine-administered mice. In conclusion, nicotine administration was associated with increased indole levels in the distal colon and rectum and attenuated DSS-induced colitis. Oral administration of nicotine may play a potential role in indole upregulation and prevention of UC.

Current trends in optimal medical therapy after PCI and its influence on clinical outcomes in China.

BACKGROUND: Limited data were available on the current trends in optimal medical therapy (OMT) after PCI and its influence on clinical outcomes in China. We aimed to evaluate the utilization and impact of OMT on the main adverse cardiovascular and cerebrovascular events (MACCEs) in post-PCI patients and analyzed the factors predictive of OMT after discharge. METHODS: We collected data from 3812 individuals from 2016.10 to 2017.09 at TEDA International Cardiovascular Hospital. They were classified into an OMT group and a non-OMT group according to their OMT status, which was defined as the combination of dual antiplatelet therapy, statins, ß-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers after PCI. Multivariable Cox regression models were developed to assess the association between OMT and MACCEs, defined as all-cause mortality, nonfatal myocardial infarction, stroke, and target vessel revascularization. A logistic regression model was established to analyze the factors predictive of OMT. RESULTS: Our results revealed that the proportion of patients receiving OMT and its component drugs decreased over time. A total of 36.0% of patients were still adherent to OMT at the end of follow-up. Binary logistic regression analysis revealed that baseline OMT (P < 0.001, OR = 52.868) was the strongest predictor of OMT after PCI. The Cox hazard model suggested that smoking after PCI was associated with the 1-year risk of MACCE (P = 0.001, HR = 2.060, 95% CI 1.346-3.151), while OMT (P = 0.001, HR = 0.486, 95% CI 0.312-0.756) was an independent protective factor against postoperative MACCEs. CONCLUSIONS: There was still a gap between OMT utilization after PCI and the recommendations in the evidence-based guidelines. Sociodemographic and clinical factors influence the application of OMT. The management of OMT and smoking cessation after PCI should be emphasized.

Pseudomonas allokribbensis sp. nov. and Pseudomonas gozinkensis sp. nov., Two New Species Isolated from a Volcanic Island, Izu Oshima, Japan.

The genomes of two Pseudomonas strains, IzPS23T and IzPS32dT isolated from soil samples of Izu Oshima were compared to Pseudomonas type strains. Whole-genome sequence analysis revealed both belong to the Pseudomonas fluorescens lineage. The average nucleotide identity values of the whole-genome sequences of IzPS23T and IzPS32dT compared with other type strains showed high correlations with Pseudomonas kribbensis (93.1%) and Pseudomonas glycinae (93.5%), respectively. Genome-to-genome distances between the whole-genome sequences of IzPS23T and IzPS32dT showed correlations with Pseudomonas kribbensis (51.0%) and Pseudomonas glycinae (53.2%), respectively. Genotypic and phenotypic analysis indicated the two strains were novel species, and were named Pseudomonas allokribbensis (IzPS23T = CECT 9961T, = LMG 31525T) and Pseudomonas gozinkensis (IzPS32dT = CECT 9962T, = LMG 31526T), respectively.

Establishment and validation of a novel predictive model to quantify the risk of bone metastasis in patients with prostate cancer.

BACKGROUND: Patients with prostate cancer (PCa) commonly suffer from bone metastasis during disease progression. This study aims to construct and validate a nomogram to quantify bone metastasis risk in patients with PCa. METHODS: Clinicopathological data of patients diagnosed with PCa between 2010 and 2015 were retrospectively retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Predictors for bone metastasis were identified by logistic regression analyses to establish a nomogram. The concordance index (c-index) and calibration plots were generated to assess the nomogram's discrimination, and the area under the receiver operating characteristic curve (AUC) was used to compare the precision of the nomogram with routine staging systems. The nomogram's clinical performance was evaluated by decision curve analysis (DCA) and clinical impact curves (CIC). Independent prognostic factors were identified by Cox regression analysis. RESULTS: A total of 168,414 eligible cases were randomly assigned to the training cohort or validation cohort at a ratio of 1:1. The nomogram, which was established based on independent factors, showed good accuracy, with c-indexes of 0.911 in the training set and 0.910 in the validation set. Calibration plots also approached 45 degrees. After other distant metastatic sites were included in the predictive model, the new nomogram displayed superior prediction performance. The AUCs and net benefit of the nomograms were both higher than those of other routine staging systems. Furthermore, bone metastasis prediction points were shown to be a new risk factor for overall survival. CONCLUSIONS: Novel validated nomograms can effectively predict the risk of bone metastasis in patients with PCa and help clinicians improve cancer management.

Prior Local or Systemic Treatment: A Predictive Model Could Guide Clinical Decision-Making for Locoregional Recurrent Breast Cancer.

INTRODUCTION: Locoregional recurrent breast cancer indicates poor prognosis. No solid prediction model is available to predict prognosis and guide clinical management. Prior local treatment or systemic treatment remains controversial. METHODS: Locoregional recurrent breast cancer patients operated in Fudan University Shanghai Cancer Center were enrolled as a training cohort. An external validation cohort included breast cancer patients after locoregional recurrence from Ruijin Hospital, Shanghai Jiaotong University. A nomogram predicting overall survival after locoregional recurrence was established using multivariable Cox regression analysis while internal and external validation were performed to evaluate its calibration and discrimination. RESULTS: Overall, 346 and 96 breast cancer patients were included in the training cohort and the validation cohort separately. A nomogram was developed, including age, neoadjuvant chemotherapy, breast surgery, pathology type, tumor size, lymph node status, hormonal receptor and Her-2 status, disease-free interval, and sites of locoregional recurrence. It had modest calibration and discrimination in the training cohort, internal validation and external validation (concordance index: 0.751, 0.734 and 0.722, respectively). The nomogram classified 266 and 80 patients into low and high-risk subgroups with distinctive prognosis. Local treatment after locoregional recurrence was associated with improved overall survival in low-risk group (P = 0.011), while systemic therapies correlated with better outcomes only in high-risk group (P < 0.001). CONCLUSION: A nomogram based on clinicopathological factors can predict prognosis and identify low and high-risk patients. Local treatment is a prior choice for low-risk patients whereas systemic treatment needs to be considered for high-risk patients, warranting further validation and exploration.