Metagenomic and culture-dependent analysis of Rhinopithecius bieti gut microbiota and characterization of a novel genus of Sphingobacteriaceae.

Culture-dependent and metagenomic binning techniques were employed to gain an insight into the diversification of gut bacteria in Rhinopithecius bieti, a highly endangered primate endemic to China. Our analyses revealed that Bacillota_A and Bacteroidota were the dominant phyla. These two phyla species are rich in carbohydrate active enzymes, which could provide nutrients and energy for their own or hosts' survival under different circumstances. Among the culturable bacteria, one novel bacterium, designated as WQ 2009T, formed a distinct branch that had a low similarity to the known species in the family Sphingobacteriaceae, based on the phylogenetic analysis of its 16S rRNA gene sequence or phylogenomic analysis. The ANI, dDDH and AAI values between WQ 2009T and its most closely related strains S. kitahiroshimense 10CT, S. pakistanense NCCP-246T and S. faecium DSM 11690T were significantly lower than the accepted cut-off values for microbial species delineation. All results demonstrated that WQ 2009T represent a novel genus, for which names Rhinopithecimicrobium gen. nov. and Rhinopithecimicrobium faecis sp. nov. (Type strain WQ 2009T = CCTCC AA 2021153T = KCTC 82941T) are proposed.

A radiomics signature derived from CT imaging to predict MSI status and immunotherapy outcomes in gastric cancer: a multi-cohort study.

BACKGROUND: Accurate microsatellite instability (MSI) testing is essential for identifying gastric cancer (GC) patients eligible for immunotherapy. We aimed to develop and validate a CT-based radiomics signature to predict MSI and immunotherapy outcomes in GC. METHODS: This retrospective multicohort study included a total of 457 GC patients from two independent medical centers in China and The Cancer Imaging Archive (TCIA) databases. The primary cohort (n = 201, center 1, 2017-2022), was used for signature development via Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression analysis. Two independent immunotherapy cohorts, one from center 1 (n = 184, 2018-2021) and another from center 2 (n = 43, 2020-2021), were utilized to assess the signature's association with immunotherapy response and survival. Diagnostic efficiency was evaluated using the area under the receiver operating characteristic curve (AUC), and survival outcomes were analyzed via the Kaplan-Meier method. The TCIA cohort (n = 29) was included to evaluate the immune infiltration landscape of the radiomics signature subgroups using both CT images and mRNA sequencing data. RESULTS: Nine radiomics features were identified for signature development, exhibiting excellent discriminative performance in both the training (AUC: 0.851, 95%CI: 0.782, 0.919) and validation cohorts (AUC: 0.816, 95%CI: 0.706, 0.926). The radscore, calculated using the signature, demonstrated strong predictive abilities for objective response in immunotherapy cohorts (AUC: 0.734, 95%CI: 0.662, 0.806; AUC: 0.724, 95%CI: 0.572, 0.877). Additionally, the radscore showed a significant association with PFS and OS, with GC patients with a low radscore experiencing a significant survival benefit from immunotherapy. Immune infiltration analysis revealed significantly higher levels of CD8 + T cells, activated CD4 + B cells, and TNFRSF18 expression in the low radscore group, while the high radscore group exhibited higher levels of T cells regulatory and HHLA2 expression. CONCLUSION: This study developed a robust radiomics signature with the potential to serve as a non-invasive biomarker for GC's MSI status and immunotherapy response, demonstrating notable links to post-immunotherapy PFS and OS. Additionally, distinct immune profiles were observed between low and high radscore groups, highlighting their potential clinical implications.

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR). METHODS: In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images. RESULTS: Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates. CONCLUSION: DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT. CLINICAL RELEVANCE STATEMENT: Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose. KEY POINTS: • The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.

Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI.

OBJECTIVE: This study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared with standard image reconstruction algorithms on abdominal enhanced computed tomography (CT) scanning with a wide range of body mass indexes (BMIs). METHODS: A total of 112 participants who underwent contrast-enhanced abdominal CT scans were divided into three groups according to BMIs: the 80-kVp group (BMI ≤ 23.9 kg/m2), 100-kVp group (BMI 24-28.9 kg/m2), and 120-kVp group (BMI ≥ 29 kg/m2). All images were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction-V of 50% level (IR), and DLIR at low, medium, and high levels (DL, DM, and DH, respectively). Subjective noise, artifact, overall image quality, and low- and high-contrast hepatic lesion conspicuity were all graded on a 5-point scale. The CT attenuation value (in HU), image noise, and contrast-to-noise ratio (CNR) were quantified and compared. RESULTS: DM and DH improved the qualitative and quantitative parameters compared with FBP and IR for all three BMI groups. DH had the lowest image noise and highest CNR value, while DM had the highest subjective overall image quality and low- and high-contrast lesion conspicuity scores for the three BMI groups. Based on the FBP, the improvement in image quality and lesion conspicuity of DM and DH images was greater in the 80-kVp group than in the 100-kVp and 120-kVp groups. CONCLUSION: For all BMIs, DLIR improves both image quality and hepatic lesion conspicuity, of which DM would be the best choice to balance both. CLINICAL RELEVANCE STATEMENT: The study suggests that utilizing DLIR, particularly at the medium level, can significantly enhance image quality and lesion visibility on abdominal CT scans across a wide range of BMIs. KEY POINTS: • DLIR improved the image quality and lesion conspicuity across a wide range of BMIs. • DLIR at medium level had the highest subjective parameters and lesion conspicuity scores among all reconstruction levels. • On the basis of the FBP, the 80-kVp group had improved image quality and lesion conspicuity more than the 100-kVp and 120-kVp groups.

Radiomics using CT images for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma: a multi-centric study.

OBJECTIVES: To develop a CT-based radiomics model for preoperative prediction of lymph node (LN) metastasis in perihilar cholangiocarcinoma (pCCA). METHODS: The study enrolled consecutive pCCA patients from three independent Chinese medical centers. The Boruta algorithm was applied to build the radiomics signature for the primary tumor and LN. The k-means algorithm was employed to cluster the selected LNs based on the radiomics signature LN. Support vector machines were used to construct the prediction models. The diagnostic efficiency was measured by the area under the receiver operating characteristic curve (AUC). The optimal model was evaluated in terms of calibration, clinical usefulness, and prognostic value. RESULTS: A total of 214 patients were included in the study (mean age: 61.6 years ± 9.4; 130 male). The selected LNs were classified into two clusters, which were significantly correlated with LN metastasis in all cohorts (p < 0.001). The model incorporated the clinical risk factors, radiomics signature primary tumor, and the LN cluster obtained the best discrimination, with AUC values of 0.981 (95% CI: 0.962-1), 0.896 (95% CI: 0.810-0.982), and 0.865 (95% CI: 0.768-0.961) in the training, internal validation, and external validation cohorts, respectively. High-risk patients predicted by the optimal model had shorter overall survival than low-risk patients (median, 13.7 vs. 27.3 months, p < 0.001). CONCLUSIONS: The study proposed a radiomics model with good performance to predict LN metastasis in pCCA. As a noninvasive preoperative prediction tool, this model may help in patient risk stratification and personalized treatment. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics model accurately predicts lymph node metastasis in perihilar cholangiocarcinoma patients. This noninvasive preoperative tool can aid in patient risk stratification and personalized treatment, potentially improving patient outcomes. KEY POINTS: • The radiomics model based on contrast-enhanced CT is a useful tool for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma. • Radiomics features extracted from lymph nodes show great potential for predicting lymph node metastasis. • The study is the first to identify a lymph node phenotype with a high probability of metastasis based on radiomics.

Survival prediction of hepatocellular carcinoma by measuring the extracellular volume fraction with single-phase contrast-enhanced dual-energy CT imaging.

Purpose: This study aimed to investigate the value of quantified extracellular volume fraction (fECV) derived from dual-energy CT (DECT) for predicting the survival outcomes of patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE). Materials and methods: A total of 63 patients with HCC who underwent DECT before treatment were retrospectively included. Virtual monochromatic images (VMI) (70 keV) and iodine density images (IDI) during the equilibrium phase (EP) were generated. The tumor VMI-fECV and IDI-fECV were measured and calculated on the whole tumor (Whole) and maximum enhancement of the tumor (Maximum), respectively. Univariate and multivariate Cox models were used to evaluate the effects of clinical and imaging predictors on overall survival (OS) and progression-free survival (PFS). Results: The correlation between tumor VMI-fECV and IDI-fECV was strong (both p< 0.001). The Bland-Altman plot between VMI-fECV and IDI-fECV showed a bias of 5.16% for the Whole and 6.89% for the Maximum modalities, respectively. Increasing tumor VMI-fECV and IDI-fECV were positively related to the effects on OS and PFS (both p< 0.05). The tumor IDI-fECV-Maximum was the only congruent independent predictor in patients with HCC after TACE in the multivariate analysis on OS (p = 0.000) and PFS (p = 0.028). Patients with higher IDI-fECV-Maximum values had better survival rates above the optimal cutoff values, which were 35.42% for OS and 29.37% for PFS. Conclusion: The quantified fECV determined by the equilibrium-phase contrast-enhanced DECT can potentially predict the survival outcomes of patients with HCC following TACE treatment.

Comparative genomic analysis and proposal of Clostridium yunnanense sp. nov., Clostridium rhizosphaerae sp. nov., and Clostridium paridis sp. nov., three novel Clostridium sensu stricto endophytes with diverse capabilities of acetic acid and ethanol production.

OBJECTIVES: Genus Clostridium sensu stricto is generally regarded as the true Clostridium genus, which includes important human and animal pathogens and industrially relevant microorganisms. Besides, it is also a prominent member of plant-associated endophytes. However, our knowledge of endophytic Clostridium is limited. METHODS: In this study, the endophytes were isolated under anaerobic condition from the roots of Paris polyphylla Smith var. yunnanensis. Subsequently, a polyphasic taxonomic approach was used to clarify their taxonomic positions. The fermentation products were measured in the isolates with HPLC analysis. Comparative genomics was performed on these new strains and other relatives. RESULTS: In total, nine endophytic strains belonging to the genus Clostridium sensu stricto were isolated, and three of them were identified as new species. Seven of nine strains could produce acetate, propionate, and butyrate. Only two strains could produce ethanol, although genomics analysis suggested that only two of them were without genes for solventogenesis. Different from the endophytic strains, the phylogenetically closely related non-endophytic strains showed significant enrichment effects on some metabolic pathways involving environmental information processing, carbohydrate, and amino acid metabolisms, etc. It suggests that the genomes of these endophytic strains had undergone subtle changes associated with environmental adaptations. CONCLUSION: Consequently, strains YIM B02505T, YIM B02515T, and YIM B02565T are proposed to represent a new species of the genus Clostridium sensu stricto, for which the names Clostridium yunnanense sp. nov., Clostridium rhizosphaerae sp. nov., and Clostridium paridis sp. nov. are suggested.

Azospirillum Endophyticum sp. nov., an Endophyte of Paris Polyphylla Smith var. Yunnanensis.

A Gram-negative, facultative anaerobic bacterial strain, designated YIM B02556T, was isolated from the root of Paris polyphylla Smith var. yunnanensis collected from Yunnan Province, southwest China. By using a polyphasic approach, its taxonomic position was investigated. Phylogenetic analysis based on 16S rRNA gene sequences revealed that strain YIM B02556T belonged to the genus Azospirillum and the 16S rRNA gene sequence similarity values of strain YIM B02556T to the type strains of members of this genus ranged from 94.9 to 98.3%. Overall genome relatedness index (OGRI) analysis estimated based on average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) between YIM B02556T and other Azospirillum species type strains were <90.8% and <37.8%, lower than the limit of species circumscription. Cells of the strain were characterized as oxidase- and catalase-positive, with motility provided by flagella. The growth conditions of the strain were found to occur at 20-40 °C (optimum, 35 °C), and pH 6.0-9.5 (optimum, pH 7.5). Strain YIM B02556T can tolerate 2% NaCl concentration. Strain YIM B02556T contained Q-10 as the major ubiquinone. The major fatty acids were C18:1 ω7c and summed feature three (C16:1 ω7c and/or C16:1 ω6c). The major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, and phosphatidylethanolamine. Based on polyphasic analysis, strain YIM B02556T could be differentiated genotypically and phenotypically from recognized species of the genus Azospirillum. Therefore, the isolate represents a novel species, for which the name Azospirillum endophyticum is proposed. The type strain is YIM B02556T (=JCM 34631T=CGMCC 1.18654T).

A creatinine-based model for predicting recurrent bleeding after modified percutaneous transhepatic variceal embolization in patients with cirrhosis.

Background: Patients who survive initial esophagogastric variceal bleeding (EVB) are at an increased risk of recurrent bleeding and death; however, a reliable predictive model is lacking. We aimed to develop a model for rebleeding prediction in patients with EVB after modified percutaneous transhepatic variceal embolization (PTVE) with cyanoacrylate. Methods: A total of 122 patients with EVB who underwent PTVE from January 2015 to November 2020 were enrolled. Multivariate logistic analyses were conducted to determine independent risk factors for nomogram construction. The discrimination, calibration, and clinical utility of the nomogram were compared with the Model for End-stage Liver Disease score (MELD) and the Child-Pugh model. Risk stratification was performed according to the nomogram. Results: Rebleeding within 3 months of PTVE occurred in 32 patients (26.2%). Independent rebleeding indicators included prior history of endoscopic therapy, Child-Pugh score, partial splenic embolization, and creatinine level. The nomogram incorporating these four predictors achieved excellent calibration and discriminatory abilities, with a concordance index of 0.85, which was confirmed to be 0.83 through bootstrapping validation. The nomogram demonstrated superior discrimination and clinical applicability than the MELD and Child-Pugh models. As shown in the Kaplan-Meier curves, high-risk patients had a high probability of rebleeding (P â€‹< â€‹0.001). Conclusions: The creatinine-based nomogram had a superior ability to predict rebleeding after PTVE in patients with EVB. Risk stratification may help identify high-risk patients and lead to the earlier implementation of aggressive treatments and formulation of intensive follow-up plans.

Enhanced CT-based radiomics predicts pathological complete response after neoadjuvant chemotherapy for advanced adenocarcinoma of the esophagogastric junction: a two-center study.

PURPOSE: This study aimed to develop and validate CT-based models to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric junction (AEG). METHODS: Pre-NAC clinical and imaging data of AEG patients who underwent surgical resection after preoperative-NAC at two centers were retrospectively collected from November 2014 to September 2020. The dataset included training (n = 60) and external validation groups (n = 32). Three models, including CT-based radiomics, clinical and radiomics-clinical combined models, were established to differentiate pCR (tumor regression grade (TRG) = grade 0) and nonpCR (TRG = grade 1-3) patients. For the radiomics model, tumor-region-based radiomics features in the arterial and venous phases were extracted and selected. The naïve Bayes classifier was used to establish arterial- and venous-phase radiomics models. The selected candidate clinical factors were used to establish a clinical model, which was further incorporated into the radiomics-clinical combined model. ROC analysis, calibration and decision curves were used to assess the model performance. RESULTS: For the radiomics model, the AUC values obtained using the venous data were higher than those obtained using the arterial data (training: 0.751 vs. 0.736; validation: 0.768 vs. 0.750). Borrmann typing, tumor thickness and degree of differentiation were utilized to establish the clinical model (AUC-training: 0.753; AUC-validation: 0.848). The combination of arterial- and venous-phase radiomics and clinical factors further improved the discriminatory performance of the model (AUC-training: 0.838; AUC-validation: 0.902). The decision curve reflects the higher net benefit of the combined model. CONCLUSION: The combination of CT imaging and clinical factors pre-NAC for advanced AEG could help stratify potential responsiveness to NAC.

CT-Based Radiomics Analysis for Noninvasive Prediction of Perineural Invasion of Perihilar Cholangiocarcinoma.

Purpose: The study aimed to construct and evaluate a CT-Based radiomics model for noninvasive detecting perineural invasion (PNI) of perihilar cholangiocarcinoma (pCCA) preoperatively. Materials and Methods: From February 2012 to October 2021, a total of 161 patients with pCCA who underwent resection were retrospectively enrolled in this study. Patients were allocated into the training cohort and the validation cohort according to the diagnostic time. Venous phase images of contrast-enhanced CT were used for radiomics analysis. The intraclass correlation efficient (ICC), the correlation analysis, and the least absolute shrinkage and selection operator (LASSO) regression were applied to select radiomics features and built radiomics signature. Logistic regression analyses were performed to establish a clinical model, a radiomics model, and a combined model. The performance of the predictive models was measured by area under the receiver operating characteristic curve (AUC), and pairwise ROC comparisons between models were tested using the Delong method. Finally, the model with the best performance was presented as a nomogram, and its calibration and clinical usefulness were assessed. Results: Finally, 15 radiomics features were selected to build a radiomics signature, and three models were developed through logistic regression. In the training cohort, the combined model showed a higher predictive capability (AUC = 0.950) than the radiomics model and the clinical model (AUC: radiomics = 0.914, clinical = 0.756). However, in the validation cohort, the AUC of the radiomics model (AUC = 0.885) was significantly higher than the other two models (AUC: combined = 0.791, clinical = 0.567). After comprehensive consideration, the radiomics model was chosen to develop the nomogram. The calibration curve and decision curve analysis (DCA) suggested that the nomogram had a good consistency and clinical utility. Conclusion: We developed a CT-based radiomics model with good performance to noninvasively predict PNI of pCCA preoperatively.

Tumor Response and Nomogram-Based Prognostic Stratification for Hepatocellular Carcinoma After Drug-Eluting Beads Transarterial Chemoembolization.

Purpose: To explore the tumor response and propose a nomogram-based prognostic stratification for hepatocellular carcinoma (HCC) after drug-eluting beads transarterial chemoembolization (DEB-TACE). Patients and Methods: From the database of two centers, patients who received DEB-TACE as an initial treatment were enrolled and divided into the training and validation sets. The tumor response after DEB-TACE was estimated according to the Modified Response Evaluation Criteria in Solid Tumors. Using the independent survival predictors in the training set, a nomogram was constructed and validated internally and externally by measuring concordance index (C-index) and calibration. A prognostic stratification based on the nomogram was established. Results: A total of 335 patients met the inclusion criteria for the study. Alkaline phosphatase level, tumor maximum diameter, tumor capsule and portal vein invasion were interrelated with the achievement of complete release after DEB-TACE. Alpha-fetoprotein level, Child-Pugh class, tumor maximum diameter, tumor number, tumor extent and portal vein invasion were integrated into the nomogram. The nomogram demonstrated good calibration and discrimination, with C-indexes of 0.735 and 0.854 and higher area under the curve (AUC) than BCLC and CNLC staging systems in the internal and external validation sets. The prognostic stratification classified patients into three different risk groups, which had significant differences in survival, complete release and objective response rate between any two groups (P < 0.05). Conclusion: The nomogram-based prognostic stratification has a good distinction and may help to identify the patients benefiting from DEB-TACE.

A Nomogram to Predict the Risk of Stent Dysfunction After TIPS in Patients with Hepatitis B Cirrhosis.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram for the prediction of stent dysfunction after transjugular intrahepatic portosystemic shunt (TIPS) placement in patients with hepatitis B cirrhosis. MATERIALS AND METHODS: From 2012 to 2020, 355 patients with hepatitis B cirrhosis who underwent TIPS placements were enrolled in this study. A multivariable logistic regression analysis was applied to determine independent risk factors for the nomogram construction. Discrimination, calibration, and clinical usefulness of the prediction model were assessed by using receiver operating characteristic curves, calibration scatter plots, and a decision curve analysis (DCA). RESULTS: Independent factors for TIPS stent dysfunction included diabetes, previous splenectomy, the shunting branch of the portal vein, and stent position, which were used to construct the nomogram. The AUC values in the training and validation cohorts were 0.817 (95% CI: 0.731-0.903) and 0.804 (95% CI: 0.673-0.935), respectively, which suggested a good predictive ability. The calibration curves in both cohorts revealed good agreement between the predictions and actual observations. The DCA curve indicated that when the threshold probability ranged from 2% to 88%, the nomogram could provide clinical usefulness and a net benefit. CONCLUSION: The nomogram that we developed could be conveniently used to predict TIPS stent dysfunction in patients with hepatitis B cirrhosis.

Neobacillus paridis sp. nov., an endophyte of Paris polyphylla Smith var. yunnanensis.

A novel endophytic strain, designated YIM B02564T, was isolated from the root of Paris polyphylla Smith var. yunnanensis obtained from Yunnan Province, southwest China. By using a polyphasic approach, cells of the strain were characterized as facultative anaerobic, Gram-positive and rod-shaped. The growth conditions of the strain were found to occur at 20-55 °C (optimum, 30 °C), pH 6.0-9.0 (optimum, pH 7.0). Strain YIM B02564T can tolerate 2% NaCl concentration. Phylogenetic analysis based on 16S rRNA gene sequences revealed that strain YIM B02564T belonged to the genus Neobacillus and the 16S rRNA gene sequence similarity values of strain YIM B02564T to the type strains of members of this genus ranged from 95.6 to 97.8%. The DNA G+C content of strain YIM B02564T calculated from the whole genome sequence was 41.6 mol%. Values of the ANI and the dDDH between strain YIM B02564T and its closely related Neobacillus species were below 77.9% and 21.5%. Strain YIM B02564T contained MK-7 as the major menaquinone, iso-C15:0 and anteiso-C15:0 as the major fatty acids. The major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, an unidentified aminophospholipid and four unidentified lipids. It contained meso-diaminopimelic acid in the cell-wall peptidoglycan. On the basis of polyphasic analysis, strain YIM B02564T could be differentiated genotypically and phenotypically from recognized species of the genus Neobacillus. The isolate therefore represents a novel species, for which the name Neobacillus paridis is proposed. The type strain is YIM B02564T (= JCM 34668T = CGMCC 1.18655T).

A novel application of drug-eluting transarterial chemoembolization in treating non-liver cancers.

This case series aimed to preliminarily evaluate the efficacy and safety of drug-eluting beads transarterial chemoembolization (DEB-TACE) in patients with lung, renal, gastric, and other non-liver cancers.Twenty-four patients who underwent DEB-TACE or DEB-TACE combined with other therapies were reviewed in this case series. Treatment responses were assessed at 1 month after treatment according to the modified Response Evaluation Criteria in Solid Tumors. Overall survival (OS) and adverse events were recorded.In the total patients, the objective response and disease control rate were 79.2% and 87.5%, respectively. And the mean OS in total patients was 14.7 months (95% confidence interval: 9.6-19.9 months). The number of patients who had generalized aches, nausea, vomit, fever, abdominal discomfort, chest discomfort, elevated blood pressure, cough, loss of appetite, and headache in total patients were 7 (29.2%), 11 (45.8%), 6 (25.0%), 2 (8.3%), 3 (12.5%), 3 (12.5%), 1 (4.2%), 1 (4.2%), 1 (4.2%), and 1 (4.2%), respectively. The objective response rates in patients with lung, renal, gastric, and other non-liver cancer were 70.0%, 85.7%, 100.0%, and 80.0%, respectively. In patients with lung, renal, gastric, and other non-liver cancers, the mean values of the OSs were 13.4 months, 12.4 months, 7.6 months, and 20.3 months, respectively. And the most common adverse events in lung cancer patients, renal carcinoma patients, gastric cancer patients, and patients with other non-liver cancers were post-embolization syndrome.DEB-TACE may be an effective and safe therapeutic option in patients with lung, renal, gastric, and other non-liver cancers.

Early recurrence detected in hepatocellular carcinoma patients after transcatheter arterial chemoembolization treatment with plasma cell-free DNA.

OBJECTIVE: Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide with poor prognosis due to the high incidence of recurrence. For patients with advanced HCC, transcatheter arterial chemoembolization (TACE) is the preferred treatment option owing to the minimal invasive clinical treatment with optimum therapeutic outcomes. But, there is a paucity of studies on early detection of residual cancer and relapse that result in the bottleneck of long-term effects after TACE therapy. PATIENTS AND METHODS: Using next-generation sequencing platform targeting a panel of 622 cancer-associated genes, we prospectively evaluated the predictive significance of plasma cell-free DNA (cfDNA) to detect minimal residual disease in plasma cfDNA in comparison with DNA obtained from tumor tissue and blood cells of three eligible cases with HCC following TACE therapy. RESULTS: The results indicated that the mutational spectrum from plasma cfDNA was consistent with tumor-derived DNA and potentially suggested disease progression. Next, we determined if the dynamic variation of plasma cfDNA could indicate treatment response, the findings suggested that the mutation burden of plasma cfDNA could reveal relapse before alterations in conventional computed tomography imaging and serum α-fetoprotein values. CONCLUSION: The mutation burden in plasma cfDNA may serve as a novel prognostic biomarker by providing early evidence of residual disease and identifying high risk of recurrence in patients with HCC following TACE therapy.