Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer. MATERIALS AND METHODS: In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA). RESULTS: The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models. CONCLUSION: The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

Role of magnetic resonance imaging features in diagnosing and localization of disc rupture related to cervical spinal cord injury without radiographic abnormalities.

STUDY DESIGN: A retrospective study. OBJECTIVE: Traumatic cervical spinal cord injury (TSCI) is often associated with disc rupture. It was reported that high signal of disc and anterior longitudinal ligament (ALL) rupture on magnetic resonance imaging (MRI) were the typical signs of ruptured disc. However, for TSCI with no fracture or dislocation, there is still difficult to diagnose disc rupture. The purpose of this study was to investigate the diagnostic efficiency and localization method of different MRI features for cervical disc rupture in patient with TSCI but no any signs of fracture or dislocation. SETTING: Affiliated hospital of University in Nanchang, China. METHODS: Patients who had TSCI and underwent anterior cervical surgery between June 2016 and December 2021 in our hospital were included. All patients received X-ray, CT scan, and MRI examinations before surgery. MRI findings such as prevertebral hematoma, high-signal SCI, high-signal posterior ligamentous complex (PLC), were recorded. The correlation between preoperative MRI features and intraoperative findings was analyzed. Also, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of these MRI features in diagnosing the disc rupture were calculated. RESULTS: A total of 140 consecutive patients, 120 males and 20 females with an average age of 53 years were included in this study. Of these patients, 98 (134 cervical discs) were intraoperatively confirmed with cervical disc rupture, but 59.1% (58 patients) of them had no definite evidence of an injured disc on preoperative MRI (high-signal disc or ALL rupture signal). For these patients, the high-signal PLC on preoperative MRI had the highest diagnostic rate for disc rupture based on intraoperative findings, with a sensitivity of 97%, specificity of 72%, PPV of 84% and NPV of 93%. Combined high-signal SCI with high-signal PLC had higher specificity (97%) and PPV (98%), and a lower FPR (3%) and FNR (9%) for the diagnosis of disc rupture. And combination of three MRI features (prevertebral hematoma, high-signal SCI and PLC) had the highest accuracy in diagnosing traumatic disc rupture. For the localization of the ruptured disc, the level of the high-signal SCI had the highest consistency with the segment of the ruptured disc. CONCLUSION: MRI features, such as prevertebral hematoma, high-signal SCI and PLC, demonstrated high sensitivities for diagnosing cervical disc rupture. High-signal SCI on preoperative MRI could be used to locate the segment of ruptured disc.

A practical dynamic nomogram model for predicting bone metastasis in patients with thyroid cancer.

Purpose: The aim of this study was to established a dynamic nomogram for assessing the risk of bone metastasis in patients with thyroid cancer (TC) and assist physicians to make accurate clinical decisions. Methods: The clinical data of patients with TC admitted to the First Affiliated hospital of Nanchang University from January 2006 to November 2016 were included in this study. Demographic and clinicopathological parameters of all patients at primary diagnosis were analyzed. Univariate and multivariate logistic regression analysis was applied to build a predictive model incorporating parameters. The discrimination, calibration, and clinical usefulness of the nomogram were evaluated using the C-index, ROC curve, calibration plot, and decision curve analysis. Internal validation was evaluated using the bootstrapping method. Results: A total of 565 patients were enrolled in this study, of whom 25 (4.21%) developed bone metastases. Based on logistic regression analysis, age (OR=1.040, P=0.019), hemoglobin (HB) (OR=0.947, P<0.001) and alkaline phosphatase (ALP) (OR=1.006, P=0.002) levels were used to construct the nomogram. The model exhibited good discrimination, with a C-index of 0.825 and good calibration. A C-index value of 0.815 was achieved on interval validation analysis. Decision curve analysis showed that the nomogram was clinically useful when intervention was decided at a bone metastases possibility threshold of 1%. Conclusions: This dynamic nomogram, with relatively good accuracy, incorporating age, HB, and ALP, could be conveniently used to facilitate the prediction of bone metastasis risk in patients with TC.

Trend of unplanned reoperation rates after lumbar degenerative surgery from 2011 to 2019: a large patient population study.

BACKGROUND: Unplanned reoperation is commonly performed due to postoperative complications. Previous studies have reported the incidence of unplanned reoperation following lumbar spinal surgery. But few study focused on the trend of reoperation rates, and the reasons of unplanned reoperation were not clear. In this study, we conducted a retrospective study to determine the trend of unplanned reoperation rates after degenerative lumbar spinal surgery from 2011 to 2019, and the reasons and risk factors of unplanned reoperation were also determined. METHODS: Data of patients who were diagnosed with degenerative lumbar spinal disease and underwent posterior lumbar spinal fusion surgery in our institution from January 2011 to December 2019 were reviewed. Those who received unplanned reoperation during the primary admission were identified. The demographics, diagnosis, surgical segments and postoperative complications of these patients were recorded. The rates of unplanned reoperation from 2011 to 2019 were calculated, and the reasons of unplanned reoperation were statistically analysed. RESULTS: A total of 5289 patients were reviewed. Of them, 1.91% (n = 101) received unplanned reoperation during the primary admission. The unplanned reoperation rates of degenerative lumbar spinal surgery firstly increased from 2011 to 2014, with a peak rate in 2014 (2.53%). Then, the rates decreased from 2014 to 2019, with the lowest one in 2019 (1.46%). Patients with lumbar spinal stenosis have a higher rate of unplanned reoperation (2.67%) compared with those diagnosed as lumbar disc herniation (1.50%) and lumbar spondylolisthesis (2.04%) (P < 0.05). The main reasons for unplanned reoperation were wound infection (42.57%), followed by wound hematoma (23.76%). Patients who underwent 2-segment spinal surgery had a higher unplanned reoperation rate (3.79%) than those receiving other segments surgery (P < 0.001). And different spine surgeons had different reoperation rates. CONCLUSIONS: The rates of unplanned reoperation after lumbar degenerative surgery increased at first and then decreased during past 9 years. Wound infection was the major reason for unplanned reoperation. 2-segment surgery and surgeon's surgical skills were related to the reoperation rate.

Arthroscopic Repair Benefits Reparable Rotator Cuff Tear Patients Aged 65 Years or Older With a History of Traumatic Events.

PURPOSE: To evaluate the clinical outcomes of arthroscopic rotator cuff repair at 2-year follow-up in patients aged 65 years or older with a history of traumatic events divided into groups based on symptom duration (<3 months, 3-6 months, and >6 months from injury to surgery) and to compared patient-reported outcomes among the 3 groups. METHODS: Between 2015 and 2020, 110 patients who met the inclusion criteria were enrolled in this study; these patients were divided into 3 groups according to symptom duration: less than 3 months (group A), 3 to 6 months (group B) and more than 6 months (group C). Preoperative and 2-year postoperative clinical outcomes were compared, including American Shoulder and Elbow Surgeons, Constant-Murley, University of California, Los Angeles, Simple Shoulder Test, and visual analog scale scores; forward elevation; external rotation; and internal rotation. The minimal clinically important difference (MCID), patient acceptable symptom state, substantial clinical benefit, and maximum outcome improvement were also compared among the groups. RESULTS: The American Shoulder and Elbow Surgeons score, as the primary outcome, improved significantly from 41.0 ± 18.5 to 85.4 ± 8.1 in group A, from 53.7 ± 14.3 to 86.3 ± 11.7 in group B, and from 49.7 ± 18.5 to 83.9 ± 11.9 in group C. All the other parameters showed statistically significant improvements at 2-year follow-up in each group (all P < .05). There was no significant difference in each parameter among the 3 groups except the visual analog scale score, which did not achieve the MCID. Overall, 86 patients (78.2%) exceeded the MCID, 87 patients (79.1%) achieved the patient acceptable symptom state, 77 patients (70.0%) achieved substantial clinical benefit, and 62 patients (56.4%) achieved maximum outcome improvement without significant differences among the 3 groups. CONCLUSIONS: In rotator cuff tear patients aged 65 years or older with a history of traumatic events, arthroscopic rotator cuff repair significantly improves clinical outcomes at 2-year follow-up regardless of symptom duration if the tear is fully reparable. LEVEL OF EVIDENCE: Level III, prognostic retrospective study.

Variability in the minimum temperature over two centuries in the overlap region between the fringe of the Asian westerly region and the temperate continental-monsoon climate transition zone.

The overlap region between the eastern fringe of the Asian westerly region and the temperate continental-monsoon climate transition zone is sensitive to climate changes and is characterized by fragile ecosystems. Uncovering the long-term historical climate variability patterns in this region is necessary. A standardized tree-ring width chronology was constructed based on the tree-ring samples collected from four representative tree species in four typical areas in the overlap region, and the 203- to 343-year annual mean minimum temperature series in the overlap region were reconstructed. The reconstructed series overlapped well with extreme climate events and low-temperature periods recorded in historical data. Therefore, the reconstructed model is stable and reliable. As suggested by the reconstructed series, the annual average minimum temperature in the overlap region changes sharply from east to west, and the periodicity change in the overlap region shows a trend of gradually weakening from the east and west ends to the middle. In the nineteenth century, the high-latitude area was in the high-temperature period, and the entire overlap region experienced significant low-temperature periods lasting 20-45 years until the 1950s. The western part had an earlier low-temperature period start time, a longer cooling duration, and a slower cooling rate than the central part. The overlap region experienced a significant warming period in approximately the last half-century, with temperatures increasing faster in the western and eastern parts than in the central part. The temperature variability in the overlap region was more intense in the last two centuries, with shorter periodicities and a larger proportion of cold periods. The central and western parts of the Asian westerly region, the mid- to high-latitude regions of the transition zone, and the overlap region experienced significant low-temperature periods or drastic cooling trends (the Little Ice Age) in the first half of the nineteenth century and significant warming trends afterwards due to global warming. The influences of these changes may have been exacerbated by the westerly circulation. The results of this study provide new insights into the use of dendroclimatology to extract temperature series in the Asian westerly region and the transition zone and a reference for research on global climate change.

Modulation of ZnO Nanostructure for Efficient Photocatalytic Performance.

Structure has been considered to play an important role in photocatalytic performance of the semiconductors, but the intrinsic factors were rarely revealed. Herein, ZnO nanomaterials in the structures of thin film, nanowire array and nanosheet array were synthesized, and their structural characteristics, optical properties, photocurrent response and photocatalytic efficiency were compared with each other for illustrating the issue. The photoluminescence intensity decreased in the order of nanosheets, thin film and nanowires for improved lifetime of the photoexcited charges. The absorption of the nanosheets and nanowires improved obviously in the visible range with a redshift of the absorption edge than that of the thin film. The nanowires possessed the highest response current of 82.65 µA at a response time of 2.0 ms in a sensitivity of 87.93 at the light frequency of 1 Hz, and gained the largest catalytic efficiency of 2.45 µg/cm2 h for the methylene blue degradation in UV light. Nevertheless, the improvement of catalytic efficiency of the nanosheets (up to 42.4%) was much larger than that of nanowires (5.7%) and thin film (2.6%) for the Au coating. The analysis revealed that the photocatalytic efficiency of the ZnO nanomaterials was modulated by the structure as it contained different surface area, roughness, defect and doping states, vacancies, polar and non-polar crystalline faces, which would provide structural design of semiconductor nanomaterials for the photoelectric and photocatalytic applications.

LRIG2 regulates cell proliferation, migration and apoptosis of osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is one of the malignant bone tumors with strong aggressiveness and poor prognosis. Leucine-rich repeats and immunoglobulin-like domains2 (LRIG2) is closely associated with the poor prognosis of a variety of tumors, but the role of LRIG2 in osteosarcoma and the underlying molecular mechanism remains unclear. OBJECTIVE: The aim of this study was to determine the function of LRIG2 in OS and the related molecular mechanism on cell proliferation, apoptosis and migration of OS. METHODS: The mRNA and protein expression of LRIG2 in OS tissues and cells was detected by qRT-PCR, western blot (WB) assay and immunohistochemistry (IHC). The cell counting Kit-8 (CCK-8), clone formation, transwell, TdT-mediated dUTP Nick-End Labeling (TUNEL) and WB assay were applied to determine the proliferation, migration and apoptosis abilities of OS cells and its molecular mechanisms. Spontaneous metastasis xenografts were established to confirm the role of LRIG2 in vivo. RESULTS: LRIG2 exhibited high expression in OS tissues and OS cell lines and the expression of which was significantly correlated with Enneking stage of patients, knockdown LRIG2 expression significantly inhibited OS cell proliferation, migration and enhanced apoptosis. Silencing LRIG2 also suppressed the growth of subcutaneous transplanted tumor in nude mice. Further, the mechanism investigation revealed that the protein level of cell proapoptotic proteins (Bax, caspase9 and caspase3) all increased attributed to LRIG2 deficiency, whereas expression of anti-apoptotic protein BCL2 decreased. LRIG2 silencing led to the decrease phosphorylation of AKT signaling, a decrease expression of vimentin and N-cadherin. Additionally, silencing LRIG2 significantly decreased the rate of tumor growth and tumor size. CONCLUSIONS: LRIG2 acts as an oncogene in osteosarcoma, and it might become a novel target in the treatment of human OS.

Using Machine Learning Methods to Predict Bone Metastases in Breast Infiltrating Ductal Carcinoma Patients.

Breast cancer (BC) was the most common malignant tumor in women, and breast infiltrating ductal carcinoma (IDC) accounted for about 80% of all BC cases. BC patients who had bone metastases (BM) were more likely to have poor prognosis and bad quality of life, and earlier attention to patients at a high risk of BM was important. This study aimed to develop a predictive model based on machine learning to predict risk of BM in patients with IDC. Six different machine learning algorithms, including Logistic regression (LR), Naive Bayes classifiers (NBC), Decision tree (DT), Random Forest (RF), Gradient Boosting Machine (GBM), and Extreme gradient boosting (XGB), were used to build prediction models. The XGB model offered the best predictive performance among these 6 models in internal and external validation sets (AUC: 0.888, accuracy: 0.803, sensitivity: 0.801, and specificity: 0.837). Finally, an XGB model-based web predictor was developed to predict risk of BM in IDC patients, which may help physicians make personalized clinical decisions and treatment plans for IDC patients.

Using Preoperative and Intraoperative Factors to Predict the Risk of Surgical Site Infections After Lumbar Spinal Surgery: A Machine Learning-Based Study.

OBJECTIVE: To develop a model based on machine learning to predict surgical site infection (SSI) risk in patients after lumbar spinal surgery (LSS). METHODS: Patients who developed postoperative SSI after LSS in the First Affiliated Hospital of Nanchang University between December 2010 and December 2019 were retrospectively reviewed. Preoperative and intraoperative variables, including age, diabetes mellitus, hypertension, body mass index, previous spinal surgery history, surgical duration, number of fused segments, blood loss, and surgical procedure were analyzed. Six machine learning algorithms-logistic regression, multilayer perceptron, decision tree, random forest, gradient boosting machine, and extreme gradient boosting-were used to build prediction models. The performance of the models was evaluated using the area under the curve, accuracy, precision, sensitivity, and F1 score. A web predictor was developed based on the best-performing model. RESULTS: The study included 288 patients who underwent LSS, of whom 144 developed SSI and 144 did not develop SSI. The extreme gradient boosting model offers the best predictive performance among these 6 models (area under the curve = 0.923, accuracy = 0.860, precision = 0.900, sensitivity = 0.834, F1 score = 0.864). An extreme gradient boosting model-based web predictor was developed to predict SSI in patients after LSS. CONCLUSIONS: This study developed a machine learning model and a web predictor for predicting SSI in patients after LSS, which may help clinicians screen high-risk patients, provide personalized treatment, and reduce the incidence of SSI after LSS.

Prediction of bone metastasis in non-small cell lung cancer based on machine learning.

Objective: The purpose of this paper was to develop a machine learning algorithm with good performance in predicting bone metastasis (BM) in non-small cell lung cancer (NSCLC) and establish a simple web predictor based on the algorithm. Methods: Patients who diagnosed with NSCLC between 2010 and 2018 in the Surveillance, Epidemiology and End Results (SEER) database were involved. To increase the extensibility of the research, data of patients who first diagnosed with NSCLC at the First Affiliated Hospital of Nanchang University between January 2007 and December 2016 were also included in this study. Independent risk factors for BM in NSCLC were screened by univariate and multivariate logistic regression. At this basis, we chose six commonly machine learning algorithms to build predictive models, including Logistic Regression (LR), Decision tree (DT), Random Forest (RF), Gradient Boosting Machine (GBM), Naive Bayes classifiers (NBC) and eXtreme gradient boosting (XGB). Then, the best model was identified to build the web-predictor for predicting BM of NSCLC patients. Finally, area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity were used to evaluate the performance of these models. Results: A total of 50581 NSCLC patients were included in this study, and 5087(10.06%) of them developed BM. The sex, grade, laterality, histology, T stage, N stage, and chemotherapy were independent risk factors for NSCLC. Of these six models, the machine learning model built by the XGB algorithm performed best in both internal and external data setting validation, with AUC scores of 0.808 and 0.841, respectively. Then, the XGB algorithm was used to build a web predictor of BM from NSCLC. Conclusion: This study developed a web predictor based XGB algorithm for predicting the risk of BM in NSCLC patients, which may assist doctors for clinical decision making.

Short-segment fixation and transpedicular bone grafting for the treatment of thoracolumbar spine fracture.

Purpose: Thoracolumbar fracture is one of the most common fractures of spine. And short-segment posterior fixation including the fractured vertebra (SSPFI) is usually used for the surgical treatment of it. However, the outcomes of SSPFI for different types of thoracolumbar fractures are not clear, and whether it is necessary to perform transpedicular bone grafting is still controversial. This study was conducted to determine the clinical efficacy of SSPFI for the treatment of different types of single-level thoracolumbar fracture, and make clear what kind of fractures need transpedicular bone grafting during the surgery. Methods: Patients with single-level thoracolumbar fracture undergoing SSPFI surgery between January 2013 and June 2020 were included in this study. The operative duration, intraoperative blood loss, anterior vertebral height ratio (AVHR) and anterior vertebral height compressive ratio (AVHC) of the fractured vertebra, local kyphotic Cobb angle (LKA), vertebral wedge angle (VWA) and correction loss during follow up period were recorded. Outcomes between unilateral and bilateral pedicle screw fixation for fractured vertebra, between SSPFI with and without transpedicular bone grafting (TBG), and among different compressive degrees of fractured vertebrae were compared, respectively. Results: A total of 161 patients were included in this study. All the patients were followed up, and the mean follow-upped duration was 25.2 ± 3.1 months (6-52 months). At the final follow-up, the AVHR was greater, and the LKA and VWA were smaller in patients with bilateral fixation (6-screw fixation) than those with unilateral fixation (5-screw fixation) of AO type A3/A4 fractures (P < 0.001). The correction loss of AVHR, LKA and VWA in fractured vertebra were significantly great when preoperative AVHC was >50% (P < 0.05). For patients with AVHC >50%, the correction loss in patients with TBG were less than those without TBG at the final follow-up (P < 0.05). Conclusions: SSPFI using bilateral fixation was more effective than unilateral fixation in maintaining the fractured vertebral height for AO type A3/A4 fractures. For patients with AVHC >50%, the loss of correction was more obvious and it can be decreased by transpedicular bone grafting.

Response relationships between abrupt seasonal temperature changes/warming (cooling) hiatuses in China and their influencing factors.

The mechanisms of abrupt seasonal temperature changes and warming (cooling) hiatuses remain unclear. Clarifying how they respond to various influencing factors is critically important to understanding their mechanisms. In this study, the influencing factors to which the abrupt changes in Tav, Tnav, and Txav were most sensitive followed the order of (AGG and CO2) > SR > WS > AMO > PDO > MEI > AO > AP > RH. Seasonal Tav had the greatest sensitivity to all influencing factors, followed by seasonal Tav and lastly by seasonal Txav. An abrupt temperature change occurred when AGG, AMO, or SR increased continuously to a certain value, when PDO was in a positive phase (warm phase) and increased continuously to a certain value, when MEI changed abruptly, when WS and RH continued to decline for a certain time and reached a certain tendency rate, or when AP continued to decline for a certain time and reached a certain value. During the period before and after the warming (cooling) hiatuses, the temperature at most of the stations only had a significant relationship with a few influencing factors, and the hiatuses in seasonal Tav, Tnav, and Txav were overall most sensitive to changes in WS, followed by changes in RH and lastly by changes in AP. The occurrence of warming (cooling) hiatuses was highly consistent with the variation trend of some influencing factors, which to some extent affected the warming (cooling) hiatuses. Abrupt seasonal temperature changes/warming (cooling) hiatuses are the combined effects of multiple influencing factors.

Evaluating the phytotoxicity of dissolved organic matter derived from black carbon.

Dissolved organic matter (DOM) derived from black carbon (BC) can migrate from soil to river by rainfall or snow melting in nature. Because of the incomplete biomass combustion, BC produced at various temperatures is mixed, which is hard to divide the DOM at single temperature. Then it is difficult to explore the properties and risks of DOM in detail. Therefore, corn straws were selected to prepare BC under different heating temperature (200 °C, 250 °C, 300 °C, 350 °C, 400 °C and 450 °C). Germination index combined the excitation-emission matrix-parallel factor (PARAFAC) and two-dimensional correlation spectra was employed to clarify the phytotoxicity and the PARAFAC components of DOM derived from BC at single temperature. Results showed that BC was hard to dissolve in water, but most of its DOM were toxic. Heating temperature promoted the formation of simple and complex fluorescent components. Combined with volume integration, it is the complex peaks of fluorescent components to determine the phytotoxicity of DOM derived from BC. These results would help to build a deep understanding of the fluorescence characteristics and toxicity of BC at different temperatures and emphasize the importance of reducing straw by burning.

Identification of differentially expressed genes involved in amino acid and lipid accumulation of winter turnip rape (Brassica rapa L.) in response to cold stress.

Winter turnip rape (Brassica rapa L.) is an important overwintering oil crop that is widely planted in northwestern China. It considered to be a good genetic resource for cold-tolerant research because its roots can survive harsh winter conditions. Here, we performed comparative transcriptomics analysis of the roots of two winter turnip rape varieties, Longyou7 (L7, strong cold tolerance) and Tianyou2 (T2, low cold tolerance), under normal condition (CK) and cold stress (CT) condition. A total of 8,366 differentially expressed genes (DEGs) were detected between the two L7 root groups (L7CK_VS_L7CT), and 8,106 DEGs were detected for T2CK_VS_T2CT. Among the DEGs, two ω-3 fatty acid desaturase (FAD3), two delta-9 acyl-lipid desaturase 2 (ADS2), one diacylglycerol kinase (DGK), and one 3-ketoacyl-CoA synthase 2 (KCS2) were differentially expressed in the two varieties and identified to be related to fatty acid synthesis. Four glutamine synthetase cytosolic isozymes (GLN), serine acetyltransferase 1 (SAT1), and serine acetyltransferase 3 (SAT3) were down-regulated under cold stress, while S-adenosylmethionine decarboxylase proenzyme 1 (AMD1) had an up-regulation tendency in response to cold stress in the two samples. Moreover, the delta-1-pyrroline-5-carboxylate synthase (P5CS), δ-ornithine aminotransferase (δ-OAT), alanine-glyoxylate transaminase (AGXT), branched-chain-amino-acid transaminase (ilvE), alpha-aminoadipic semialdehyde synthase (AASS), Tyrosine aminotransferase (TAT) and arginine decarboxylase related to amino acid metabolism were identified in two cultivars variously expressed under cold stress. The above DEGs related to amino acid metabolism were suspected to the reason for amino acids content change. The RNA-seq data were validated by real-time quantitative RT-PCR of 19 randomly selected genes. The findings of our study provide the gene expression profile between two varieties of winter turnip rape, which lay the foundation for a deeper understanding of the highly complex regulatory mechanisms in plants during cold treatment.

Diagnostic Value of Quantitative Gray-Scale Analysis of Contrast-Enhanced Spectral Mammography for Benign and Malignant Breast Lesions.

OBJECTIVE: The aim of the study was to quantitatively analyze the enhancement of breast lesions by contrast-enhanced spectral mammography to improve the differential diagnosis ability of contrast-enhanced spectral mammography. METHODS: A total of 283 patients with breast lesions admitted from August 2017 to May 2018 were retrospectively analyzed. Quantitative analysis of all enhancing lesions was performed to measure the gray values of the lesion region of interest (ROI), the area close to the lesion (ROI1), the area close to the chest wall (ROI2), and the chest wall (ROI3). Differences in gray values between different ROIs of benign and malignant lesions were compared. Taking the pathological results as the criterion standard, we used the receiver operating characteristic curve to evaluate the diagnostic efficacy of the ROI gray value and relative gray value (rROI) for the lesions. RESULTS: A total of 299 lesions were found in 283 patients, including 101 benign lesions and 198 malignant lesions. The ROI gray value, rROI1, rROI2, and rROI3 of malignant lesions were all significantly greater than those of benign lesions. The areas under the ROC curve of ROI, rROI1, rROI2, and rROI3 gray values of benign and malignant lesions were 0.795, 0.833, 0.812, and 0.741, respectively. The statistically significant difference in the area under the ROC curve was only found between rROI1 and ROI gray value and rROI1 had the greatest diagnostic value. CONCLUSIONS: The gray value of malignant breast lesions was higher than that of benign lesions. The quantitative analysis of the gray value will help in the differential diagnosis of benign and malignant breast lesions.

Protein and carbohydrate drive microbial responses in diverse ways during different animal manures composting.

The aim of this study was to assess the roles of bacteria in degrading protein and carbohydrate during chicken and bovine manures composting. The results showed that protein and carbohydrate degraded greatly, especially during the thermophilic phase of composting. This was mainly caused by the abundant bacteria communities that related with protein and carbohydrate transformation in the thermophilic phase, which identified by the network analysis. Besides, the microbial degradation of nutrient substances performed specificity and universality. "Specificity" and "Universality" meant protein and carbohydrate degraded by certain bacteria and diverse groups of bacteria, respectively. "Specific" bacteria transformed protein and carbohydrate during chicken manure composting, whereas the transformation characteristic of bacteria to protein and carbohydrate in bovine manure was "universality". Structural equation models also verified these results, and they showed that more than 79% of protein and carbohydrate changes were transformed by bacteria.

Diagnostic Value of Contrast-Enhanced Spectral Mammography in Comparison to Magnetic Resonance Imaging in Breast Lesions.

OBJECTIVE: The aim of this study was to evaluate the diagnostic value between contrast-enhanced spectral mammography (CESM) and breast magnetic resonance imaging (MRI) in breast disease. METHODS: Two hundred thirty-five patients who were suspected of having breast abnormalities by clinical examination or mammography underwent CESM and MRI examination. Using histopathologic results as the criterion standard, the diagnostic performance of CESM and MRI was investigated. The areas under receiver operating characteristic curves were applied to analyze diagnostic efficiency. The Pearson correlation coefficients between CESM versus pathology and MRI versus pathology were calculated. RESULTS: Two hundred sixty-three breast lesions were found in 235 patients, in which 177 were malignant and 86 were benign. By evaluating the diagnostic value, sensitivity, positive predictive value, negative predictive value, and false-negative rate from CESM examination were comparable to those from MRI (91.5%, 94.7%, 83.7%, and 8.5% vs 91.5%, 90.5%, 82.1%, and 8.5%). Importantly, the accuracy and the specificity were higher for CESM than those for MRI (81% and 89.5% vs 80.2% and 71.7%), whereas the false-positive rate was lower (10.5% vs 19.8%). The areas under receiver operating characteristic curves of CESM and MRI were 0.950 and 0.939, displaying the equivalent diagnostic efficiency (P = 0.48).For the agreement between measurements, mean tumor sizes were 3.1 cm for CESM and 3.4 cm for MRI compared with 3.2 cm on histopathologic results. The Pearson correlation coefficient of CESM versus histopathology (r = 0.774, P = 0.000) was consistent with MRI versus histopathology (r = 0.771, P = 0.000). CONCLUSIONS: Our results show better accuracy, specificity, and false-positive rate of CESM in breast cancer detection than MRI. Contrast-enhanced spectral mammography displayed a good correlation with histopathology in assessing the lesion size of breast cancer, which is consistent with MRI.

Imaging performance and clinical value of contrast-enhanced ultrasonography and computed tomography in the diagnosis of liver cancer.

The imaging performance and clinical value of contrast-enhanced ultrasonography (CEUS) combined with CT in diagnosis of liver cancer were investigated. A total of 426 liver cancer patients treated in Yuhuangding Hospital (Yantai, China) from February 2011 to May 2016 were selected. Among them, 222 patients underwent CEUS examination, 204 patients underwent CT examination, and 102 patients underwent CEUS combined with CT examination. Sensitivity and specificity of the three methods were examined. CT showed a low density in 92.6% of patients (189 patients) and a high-low hybrid density in 6.4% (13 patients), with calcification seen in 2.5% of patients (5 patients) and bleeding in 3.4% (7 patients). Lesions: 76.5% (156 cases) of patients with multiple type, 23.5% (48 cases) with single type. CEUS showed overall enhancement in 53.2% patients (118 cases), heterogenous enhancement in 16.7% (37 cases), peripheral enhancement in 18.9% of patients (42 cases), necrosis of liquefaction in 11.3% (25 cases). In 65.3% (145 cases) of patients, the portal venous phase and the delayed phase showed a low enhancement, while 34.7% (77 cases) showed no enhancement. The sensitivity and specificity rates of CEUS combined with CT detection of liver cancer were 87.8, 88.2 and 94.1%, respectively. The ROC curve analysis showed that the sensitivity and specificity of CEUS in the diagnosis of liver cancer were 76.8 and 78.9%, respectively. The sensitivity and specificity of CT were 81.2 and 85.5%, respectively. The sensitivity and specificity of CEUS combined with CT were 90.4 and 92.7%, respectively. CEUS combined with CT detection can make-up for the deficiencies of each other and effectively improve the coincidence rate of liver cancer diagnosis, which can be used as an effective examination method for the diagnosis of liver cancer.

Regulatory effect of microRNA-34a on osteogenesis and angiogenesis in glucocorticoid-induced osteonecrosis of the femoral head.

Glucocorticoid-induced osteonecrosis of the femoral head (GIOFH) is a common and devastating orthopedic disease, and its underlying mechanism remains unclear. The aim of this study was to determine the role of microRNA-34a (mir-34a) in GIOFH. C57 mouse mesenchymal stem cells (mMSCs) and human umbilical vein endothelial cells (HUVECs) were cultured with dexamethasone (Dex). A total of 48 adult rats were treated with glucocorticoids, and after the onset of GIOFH, each femoral head was removed. Mir-34a mimics, an inhibitor and over-expressing lentivirus were used in vitro and in vivo, respectively. Real-time PCR, immunohistochemistry, ELISA, cell proliferation assays, osteoblastic differentiation, and endothelial activity assays were employed to evaluate the effect of mir-34a on mMSCs, osteoblasts, and vascular endothelial cells in glucocorticoid-treated mice. We found that Dex inhibited mMSC proliferation and osteoblastic differentiation, as well as the viability and activity of endothelial cells. Dex also caused osteonecrosis and decreased new vessel formation in vivo. Mir-34a alleviated the inhibitory effects of Dex on mMSCs and osteoblasts, while facilitating its inhibitory effects on endothelial cells. Mir-34a is an important regulator in osteogenesis and angiogenesis, and it might be useful as a therapeutic target for GIOFH. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:417-424, 2018.