[Efficacy and safety of generic azacitidine in Chinese patients with higher-risk myelodysplastic syndromes: a multicenter, prospective, single-arm study]

Objective: To evaluate the efficacy, safety, and pharmacokinetics of the generic azacitidine in Chinese patients with higher-risk myelodysplastic syndromes(MDS). Methods: Between October 2013 and 2016, 72 patients were eligible for enrollment at 9 sites from China received generic subcutaneous azacitidine 75 mg·m(-2)·d(-1) for 7 days per 28-day cycle, for ≥6 cycles. Pharmacokinetic blood samples were collected on day 1 of a single-dose. Results: For each patient at cycle 6 or at the time of study discontinuation, whichever came first, the overall response rate, which included complete remission (CR)and partial remission(PR), was 6.9%(5/72), the rate of patients who had the best effect with CR or PR during the treatment was 12.5%(9/72). Patients who were dependent on red-blood-cell transfusions and platelet transfusions at baseline became transfusion independent were 46.3%(19/41)and 41.2% (7/17), respectively. The median time of treatment was 6 cycles, and the median OS was 16.1 months (95%CI 10.9-20.6 months). For 36 patients(50%)received treatment at ≥6 cycles, and the median OS was 22.3 months(95%CI 16.1- not evaluative). Most common grade Ⅲ-Ⅳ hematologic treatment-emergent adverse events were neutropenia(55%), leukopenia(47%), and thrombocytopenia(61%). Pharmacokinetic profiles were similar for generic and original azacitidine in Chinese patients. Conclusion: Generic azacitidine treatment was favorable and safe and can be used as a standard treatment for patients with higher-risk MDS.

Deep learning-based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre study

Background

Accurate lymph nodes (LNs) assessment is important for rectal cancer (RC) staging in multiparametric magnetic resonance imaging (mpMRI). However, it is incredibly time-consumming to identify all the LNs in scan region. This study aims to develop and validate a deep-learning-based, fully-automated lymph node detection and segmentation (auto-LNDS) model based on mpMRI.

Methods

In total, 5789 annotated LNs (diameter ≥ 3 mm) in mpMRI from 293 patients with RC in a single center were enrolled. Fused T2-weighted images (T2WI) and diffusion-weighted images (DWI) provided input for the deep learning framework Mask R-CNN through transfer learning to generate the auto-LNDS model. The model was then validated both on the internal and external datasets consisting of 935 LNs and 1198 LNs, respectively. The performance for LNs detection was evaluated using sensitivity, positive predictive value (PPV), and false positive rate per case (FP/vol), and segmentation performance was evaluated using the Dice similarity coefficient (DSC).

Findings

For LNs detection, auto-LNDS achieved sensitivity, PPV, and FP/vol of 80.0%, 73.5% and 8.6 in internal testing, and 62.6%, 64.5%, and 8.2 in external testing, respectively, significantly better than the performance of junior radiologists. The time taken for model detection and segmentation was 1.3 s/case, compared with 200 s/case for the radiologists. For LNs segmentation, the DSC of the model was in the range of 0.81–0.82.

Interpretation

This deep learning–based auto-LNDS model can achieve pelvic LNseffectively based on mpMRI for RC, and holds great potential for facilitating N-staging in clinical practice.

[Quick community survey on the impact of COVID-19 outbreak for the healthcare of people living with HIV]

Objective: To collect the current status and healthcare needs of people living with HIV (PLHIV) in China during the COVID-19 outbreak to inform quick response from government and communities. Methods: During February 5(th) to 10(th), 2020, a national anonymous survey was conducted using an online questionnaire among PLHIV at least 18 years of age and had started antiretroviral treatment (ART) to collect the information on COVID-19 prevention, HIV-related health services and the needs on psychosocial support. Current status and needs of people living with HIV were analyzed in Hubei and other regions. Results: A total of 1 014 valid questionnaires were collected, with PLHIV respondents cross the country. The survey revealed that 93.79% of the respondents could obtain information regarding the prevention of COVID-19 from their communities or villages. Respondents were concerned with HIV-specific protective measures and personal protective equipment shortage. 32.64% of all respondents were not carrying sufficient antiretroviral medicines (ARVs) to meet the needs under traffic and travel restrictions, and some could face stock-outs in the coming month. In Hubei province where 53 respondents needed ARV refill, 64.15% reported difficulty accessing ARV due to the "blockage" . 28.93% respondents were in need of sociopsychological support, and 85.31% anticipated further improvement of the out-of-town ARV refill process from the government. Conclusion: PLHIV wants to know HIV-specific protective measures against COVID-19 outbreak. PLHIV who returned to their home-towns and affected by the lock-downs reported challenges with refills. We should undertake a more systematic study on impacts of the COVID-19 on PLHIV to develop preparedness capacity for future public health emergency.

Short communication: Menaquinone-4 (vitamin K2) induces proliferation responses in bovine peripheral blood mononuclear cells

The effects of vitamin K (VK) on immune cells in ruminants are yet to be fully investigated. The objective of this study was to examine the effects of VK on peripheral blood mononuclear cells (PBMC) in Holstein dairy cows. A cell proliferation assay was performed to evaluate the effect of menaquinone-4 (MK-4, the biologically active form of VK) on immune response of PBMC. The proliferation of PBMC stimulated by MK-4 was significantly higher than that of nonstimulated controls. The expression of T cell-related genes in PBMC, stimulated with MK-4, was assessed by quantitative PCR. No significant changes were observed in the mRNA expression levels of both CD4 and CD8 as helper T cell and cytotoxic T cell markers, respectively. The present study demonstrated that MK-4 positively influenced cow PBMC proliferation and suggested the possibility of bovine-specific immune cell activation. The present study lays a foundation for understanding the physiological role of VK in cattle.

[Individualized treatment recommendations for lung cancer patients at different stages of treatment during the outbreak of 2019 novel coronavirus disease]

In order to achieve the overall victory over 2019 novel coronavirus disease epidemic, especially to prevent the disease recurrence from rebounding during the resumption of labor, the government has not loosened any control of personnel mobility, which has obviously affected the normal examination and treatment of lung cancer patients under the influence of this epidemic. During the epidemic period, cancer patients with low immunity levels face the double ordeals of disease and epidemic situation. Compared with the general population, they are more likely to be infected with the new coronavirus. Among the infected cancer patients, lung cancer is the most common type. It is necessary to provide more appropriate individualized treatment recommendations for patients with lung cancer based on the epidemic situation of the patient's location and in combination with the patient's own condition. Through active prevention of infection, timely conversion of treatment strategies, online and offline joint control, and positive psychological counseling, we do our best to help patients with lung cancer to survive this difficult period.

A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma

OBJECTIVES

The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the risk of complications. This study aims to develop a cross-modal 3D neural network based on CT images and prior clinical knowledge for accurate prediction of LN metastasis in clinical stage T1 lung adenocarcinoma.

PATIENTS AND METHODS

Five hundred one lung adenocarcinoma patients with clinical stage T1 were enrolled. Data including: corresponding 3D nodule-centered patches of CT; prior clinical features; and pathological labels of LN status were obtained. We proposed a cross-modal deep learning system, which can successfully incorporate prior clinical knowledge and CT images into a 3D neural network to predict LN metastasis. We trained and validated our system with 401 cases and tested its performance with 100 cases. The result was compared with that of the logistic regression integration model, the single deep learning model without prior clinical knowledge integration, radiomics method, and manual evaluation by radiologists.

RESULTS

The model proposed DensePriNet achieved an AUC of 0.926, which is significantly higher than the logistic regression integration model (0.904) single deep learning model (0.880), and radiomics method (0.891). The Matthews Correlation Coefficient (MCC) of DensePriNet (0.705) was significantly higher than manual classification by one senior radiologist (0.534) and one junior radiologist (0.416), respectively.

CONCLUSION

The performance of the single deep learning method is significantly higher than the radiomics method and the radiologists, and integration of prior clinical knowledge into the deep learning model enhance the diagnostic precision of LN status and facilitate the application of precision medicine.

Predicting the Outcome of Transcatheter Arterial Embolization Therapy for Unresectable Hepatocellular Carcinoma Based on Radiomics of Preoperative Multiparameter MRI

BACKGROUND

In unresectable hepatocellular carcinoma (HCC), methods to predict patients at increased risk of progression are required.

PURPOSE

To investigate the feasibility of radiomics model in predicting early progression of unresectable HCC after transcatheter arterial chemoembolization (TACE) therapy using preoperative multiparametric magnetic resonance imaging (MP-MRI).

STUDY TYPE

Retrospective.

POPULATION

A total of 84 patients with BCLC B stage HCC from one medical center. According to the modified response evaluation criteria in solid tumors, patients who progressed at 6 months after TACE therapy were assigned as the progressive disease (PD) group (n = 32). Patients whose MRI was performed on four devices were divided into a training cohort (n = 67). Patients whose MRI was performed on other than the previous four devices were used as the testing set (n = 17).

FIELD STRENGTH/SEQUENCE

3.0T, 1.5T axial T₂ -weighted imaging (T₂ WI), diffusion-weighted imaging (DWI, b = 0, 500 s/mm² ), and apparent diffusion coefficient (ADC) ASSESSMENT: PD was confirmed via imaging studies with MRI. Risk factors, including age, alpha fetoprotein (AFP), size, and radiomic-related features of PD were assessed. In addition, the discrimination ability of each radiomics signature was tested on an independent testing set.

STATISTICAL TESTS

The area under the receiver-operator characteristic (ROC) curve (AUC) was used to evaluate the predictive accuracy of the radiomic signature in both the training and testing sets. The results indicated that the MP-MRI model achieved the greatest benefit.

RESULTS

In the testing set, the model based on DWI features presented an AUC of (b = 0, 0.786; b = 500, 0.729), followed by T₂ WI features (0.729) and ADC (0.714). The AUC of the MP-MRI signature was increased to 0.800 compared to any single MRI signature. The multivariate logistic analysis identified the radiomics signature as independent parameters of PD, while clinical information such as age, AFP, size, etc., had no significance in the PD group.

DATA CONCLUSION

Preoperative MP-MRI has the potential to predict the outcome of TACE therapy for unresectable HCC. In addition, these image features may be complementary to the current staging systems of HCC patients.

LEVEL OF EVIDENCE

2.

TECHNICAL EFFICACY STAGE

3. J. Magn. Reson. Imaging 2020;52:1083-1090.

Research Note: Effects of the rearing method and stocking density on carcass traits and proximate composition of meat in small-sized meat ducks

The present study was conducted to evaluate the effects of different rearing methods and stocking densities on carcass yield and proximate composition of meat in small-sized meat ducks. A total of 555 one-day-old birds were randomly allocated to six treatment groups (three replicates per treatment, sex ratio 1/1) with a 2 × 3 factorial arrangement of two rearing methods (reared in cage or net) and three stocking densities (5 [low], 7 [medium], or 9 [high] birds/m²) until day 70. Five male and five female birds from each replicate were randomly selected and processed to determine the carcass yield. Proximate composition was determined by proximate analysis using the breast and thigh muscles. There was no interaction effect between the rearing method and stocking density on carcass yield. The rearing method affected the thigh muscle rate, which was higher in the cage groups (P < 0.05). The final BW and abdominal fat rate decreased with increasing density (P < 0.05), whereas the thigh muscle rate increased (P < 0.05). There were significant interaction effects (P < 0.05) between the rearing method and stocking density on the content of protein, fat, and collagen. The content of fat and moisture was greater and lower, respectively, in the cage groups (P < 0.05). The content of moisture, fat, and collagen with a medium density was higher (P < 0.05). In addition, the content of protein and fat was lower in the ducks fed in nets at low and high densities (P < 0.05), respectively; the collagen content of breast and thigh muscle was lower in the ducks fed in cages and nets, respectively, at a low density (P < 0.05). Our findings provide valuable insights into the single and interactive effects of the rearing method and stocking density on duck slaughter performance and proximate composition of meat. The results indicate that a rearing system with a cage pattern and a medium density is better than other arrangements for small-sized meat ducks.

Parent-of-origin has no detectable effect on survival days of Marek's disease virus infected White Leghorns

Marek's Disease (MD) is a neoplastic disease of chickens and remains as a chronic infectious disease that threatens the poultry industry. Improving genetic resistance to MD in poultry is an important long-term goal, which would significantly augment the current control measures against MD and eventually reduce the annual economic loss. In this study, survival patterns of F2 birds from 2 reciprocal crosses were compared to examine possible difference in survival between the reciprocal crosses in response to MD virus (MDV) challenge. A total of 246 and 224 F2 chicks derived from reciprocal crosses of lines 63 × 72 and lines 72 × 63, respectively, were sampled from an MDV challenge trial and survival days were recorded from the MDV-inoculation date to the end of experiment. Statistical analyses, including Principal Component Analysis (PCA) followed by a cox-regression model, showed there was no significant difference in survival days between reciprocal crosses (P > 0.05). To the best of our knowledge, this is the first MD survival study on reciprocal crosses of 2 genetically diversified lines of chickens differing in MD resistance. This report documented the experimental evidence that the genetic lineage of grandparental (maternal or paternal) effect on survival days was minimal, if present at all.