A Single-Center Prospective Study of 116 Women with Osteoporosis Treated with Zoledronic Acid Monitored by Electrocardiography for the Development of Cardiac Arrhythmia During the Acute Phase in China.

BACKGROUND Concerns have been raised among clinicians and patients about the cardiovascular risks of bisphosphonates used in the treatment of osteoporosis. The goal of this study was to investigate the acute effect of zoledronic acid (ZA) infusion on arrhythmia development using an electrocardiograph (ECG). MATERIAL AND METHODS This prospective study was a self-controlled case series study that recruited 116 female patients with osteoporosis. The patients underwent standard 12-lead electrocardiography before and 1 day after zoledronic acid intravenous infusion to evaluate cardiac adverse effects and the change in ECG parameters after the infusion. Heart rhythm, atrial and ventricular premature contractions, atrial fibrillation, P wave, and QTc parameters were measured using an ECG. A blood biochemical examination was performed for all patients before the ZA infusion. Body temperature was measured twice per day. RESULTS Before ZA administration, ECG findings were normal in 47 patients and abnormal in 69 patients. After ZA administration, ECG findings were normal in 35 patients and abnormal in 81 patients. New onsets of premature atrial contractions and atrial fibrillation were observed in 1 patient each, and new onsets of premature ventricular contractions were observed in 2 patients. The heart rate was obviously higher, and the QT interval was obviously shorter after ZA administration, compared with before administration. No significant differences in P wave and QTc parameters were found between the 2 ECG measurements. CONCLUSIONS During the acute phase, 116 women with osteoporosis who were treated with zoledronic acid infusion did not develop significantly abnormal ECG changes.

Repression of let-7b-5p prevents the development of multifidus muscle dysfunction by promoting vitamin D accumulation via upregulation of electron transfer flavoprotein alpha subunit in a rat model of multifidus muscle injury.

Multifidus muscle dysfunction is associated with the multifidus muscle injury (MMI), which ultimately result in the low-back pain. Increasing evidence shows that microRNAs (miRs) may be involved in multifidus muscle dysfunction. In this study, we tested the hypothesis that downregulation of let-7b-5p may inhibit the multifidus muscle dysfunction development and progression. The target prediction program and luciferase activity determination confirmed electron transfer flavoprotein alpha subunit (ETFA) as a direct target gene of let-7b-5p. To study the mechanisms and functions of let-7b-5p in relation to ETFA in MMI progression, we prepared rats with experimental MMI, and a lentivirus-based packaging system was designed to upregulate expressions of let-7b-5p, and downregulate the expression of ETFA. ETFA was identified as a target gene of let-7b-5p. Older age, a longer duration of pain, and higher visual analog scale and Oswestry disability index scores for the patients with chronic low-back pain were linked to a more severe degree of degenerative muscle atrophy and fatty infiltration. Increased expression of let-7b-5p and decreased expression of ETFA and vitamin D receptor (VDR) were positively correlated with multifidus muscle dysfunction. Downregulated let-7b-5p could inhibit infiltration of collagen fibers, reverse the ultrastructural changes of multifidus muscle, and induce the VDR expression, thereby repair the MMI. The results provided a potential basis for let-7b-5p that could support targeted intervention in multifidus muscle dysfunction. Collectively, this study confirmed that downregulation of let-7b-5p has a potential inhibitory effect on the development of the function of the musculus myocytes by upregulating ETFA.

Influence of bone densitometry on the anti-osteoporosis treatment after fragility hip fracture.

BACKGROUND: Fragility fracture significantly increases risk of future fracture. The fragility fracture cycle should be disrupted. The secondary fracture prevention is important for the patients with fragility hip fracture. The pharmacotherapy for osteoporosis is important for prevention of new fracture. However, many patients with hip fracture do not receive osteoporosis treatment. This retrospective study investigates the influence of bone mineral density (BMD) assessment on the initiation of anti-osteoporosis medications in the hospitalized patients with fragility hip fracture. METHODS: This retrospective research enrolled 1211 patients with fragility hip fracture 50 years of age and older. Among 1211 patients aged from 50 to 103 years with the average age of 77.83 ± 9.95 years, there were 807 females and 404 males. There were 634 fractures of femoral neck and 577 intertrochanteric fractures of femur. We examined whether patients had received bone mineral density assessment and received anti-osteoporosis therapy during the period of hospitalization. The patients were divided into BMD assessment group and no BMD assessment group. Measurement data were expressed as mean ± standard deviation and compared with t test. All parameters of groups were compared with Chi-square test. RESULTS: Of 1211 patients, 331 (27.33%) had received BMD assessment and 925 (76.38%) had received anti-osteoporosis drugs during the period of hospitalization. The rate of bisphosphonate use was lower and only 11.31% in the total patients. The anti-osteoporosis treatment rate was 93.66% in the patients receiving BMD assessment and 69.89% in the patients without BMD assessment (p < 0.01). The zoledronate use significantly increased from 6.7% in the patients without BMD assessment to 23.56% in the patients receiving BMD assessment (p < 0.01). CONCLUSIONS: BMD assessment is a good basis for communication between patients and orthopedic surgeons. BMD assessment significantly increases the initiation of osteoporosis treatment and bisphosphonate use in the patients with hip fracture during the period of hospitalization.

Land Use Classification of the Deep Convolutional Neural Network Method Reducing the Loss of Spatial Features.

Land use classification is a fundamental task of information extraction from remote sensing imagery. Semantic segmentation based on deep convolutional neural networks (DCNNs) has shown outstanding performance in this task. However, these methods are still affected by the loss of spatial features. In this study, we proposed a new network, called the dense-coordconv network (DCCN), to reduce the loss of spatial features and strengthen object boundaries. In this network, the coordconv module is introduced into the improved DenseNet architecture to improve spatial information by putting coordinate information into feature maps. The proposed DCCN achieved an obvious performance in terms of the public ISPRS (International Society for Photogrammetry and Remote Sensing) 2D semantic labeling benchmark dataset. Compared with the results of other deep convolutional neural networks (U-net, SegNet, Deeplab-V3), the results of the DCCN method improved a lot and the OA (overall accuracy) and mean F1 score reached 89.48% and 86.89%, respectively. This indicates that the DCCN method can effectively reduce the loss of spatial features and improve the accuracy of semantic segmentation in high resolution remote sensing imagery.

Overexpression of Long Non-Coding RNA NNT-AS1 Correlates with Tumor Progression and Poor Prognosis in Osteosarcoma.

BACKGROUND/AIMS: Increasing evidence demonstrates that long non-coding RNAs (lncRNAs) play critical regulatory roles in cancers, including osteosarcoma. A previous study showed that Nicotinamide Nucleotide Transhydrogenase-antisense RNA1 (NNT-AS1) was aberrantly expressed in several types of cancer. However, the potential biological roles and regulatory mechanisms of NNT-AS1 in osteosarcoma progression remain unknown. METHODS: Quantitative RT-PCR was performed to examine the expression of NNT-AS1 in human tissues and cells. The biological functions of NNT-AS1 were determined by CCK-8, colony formation, Flow cytometry and Transwell assays in vitro. A mouse xenograft model was performed to investigate the effect of NNT-AS1 on tumor growth in vivo. RESULTS: In this study, we found the expression of NNT-AS1 was significantly increased in tumor tissues compared to adjacent normal tissues. Furthermore, upregulated NNT-AS1 expression predicted poor prognosis and was an independent and significant risk factor for osteosarcoma patient survival. Further experiments revealed that NNT-AS1 knockdown significantly inhibited cell proliferation by inducing cell cycle arrest and promoting apoptosis in osteosarcoma cells. Moreover, NNT-AS1 silencing suppressed cell migration and invasion in vitro. In a tumor xenograft model, knockdown of NNT-AS1 suppressed tumor growth of OS-732 cells in vivo. CONCLUSIONS: Taken together, these findings indicate that NNT-AS1 functions as an oncogene in osteosarcoma and could be a novel diagnostic and therapeutic target for osteosarcoma.

LncRNA DLX6-AS1/miR-129-5p/DLK1 axis aggravates stemness of osteosarcoma through Wnt signaling.

Osteosarcoma is the most common primary bone tumor and occurs most frequently in adolescents. Cancer stem cells (CSCs) are resistant to chemotherapy and radiotherapy, and can drive cancer recurrence. In this study, we aimed to investigate the effect of Long noncoding RNAs (lncRNAs) DLX6-AS1 on osteosarcoma stemness and the underlying mechanism involved. DLX6-AS1 enhanced osteosarcoma stemness in vitro and in vivo. Moreover, DLX6-AS1 competitively interacted with miR-129-5p to DLK1, resulting in activation of Wnt signaling and promotion of stemness in osteosarcoma. DLX6-AS1 functionally interplayed with miR-129-5p to form a reciprocal feedback loop to activate Wnt signaling. High DLX6-AS1 expression was observed in osteosarcoma tissues, and predicted a poor prognosis for osteosarcoma patients. Our study suggests that DLX6-AS1, combined with miR-129-5p and DLK1, can be utilized as factors for the clinical diagnosis and prognosis of osteosarcoma, and may be potential targets for the treatment of osteosarcoma.

The Use of Cryotherapy for the Prevention of Wound Complications in the Treatment of Calcaneal Fractures.

We analyzed the risk factors for skin infection and necrosis after calcaneal fracture surgery and evaluated the effect of cryotherapy in preventing postoperative skin infections and necrosis. We studied 129 calcaneal fracture patients (148 feet) who had undergone open reduction and internal fixation from January 2008 to December 2010. Three groups included were: control (44 patients; 49 feet), preoperative cryotherapy (43 patients; 48 feet), and perioperative cryotherapy (42 patients; 51 feet). The wound infection rate, Maryland foot score, and postoperative visual analog scale (VAS) score were compared. Risk factors for infection were analyzed using multinomial logistic regression. Both cryotherapy groups had lower infection rates, higher Maryland foot scores, lower VAS scores, and shorter hospitalizations than the control group (p < .05). The perioperative cryotherapy group had a lower infection rate, higher Maryland foot score, and shorter hospitalization (p < .05) but similar VAS score compared with the preoperative cryotherapy group (p > .05). Pre- and postoperative cryotherapy, postoperative drainage, surgical timing, smoking index, alcoholism, and suture method were risk factors for postoperative infection and necrosis. The risk of these can be largely reduced by patients not smoking and drinking alcohol and surgeons choosing the appropriate surgical timing, improving the suturing method, and performing postoperative drainage. Perioperative cryotherapy might be an effective method to decrease the postoperative infection rate, shorten the hospital stay, and reduce postoperative pain. Our findings require further validation in well-designed randomized controlled trials.

Cortical thickness in the intertrochanteric region may be relevant to hip fracture type.

BACKGROUND: This study assessed the differences in femoral geometry and bone mineral density between femoral neck fragility fractures and trochanteric fractures. METHODS: One hundred and seventeen patients were divided into femoral neck and trochanteric fracture groups. There were 69 patients with femoral neck fractures, 20 men and 49 women with an average age of 75.1 ± 9.6 years and an average body mass index (BMI) value of 21.6 ± 4.1 kg/m2. The trochanteric group consisted of 48 patients, 16 men and 32 women with an average age of 78.1 ± 9.1 years and an average BMI value of 21.5 ± 4.3 kg/m2. All patients underwent dual-energy X-ray absorptiometry (DXA) of the contralateral hip; hip structural analysis (HSA) software was used to analyze the femoral geometry parameters, including hip axis length (HAL), neck-shaft angle (NSA), cross-sectional area (CSA), the cross-sectional moment of inertia (CSMI), the buckling ratio (BR), and cortical thickness. RESULTS: The cortical thickness in the intertrochanteric region was reduced in the trochanteric fractures group compared to the femoral neck fracture group (P < 0.05). There were no statistically significant differences (P > 0.05) in gender, age, height, weight, or BMI between the two groups. In addition, no statistically significant differences (P > 0.05) were found in the CSA, CSMI, or BR of the femoral neck or the intertrochanteric region between the two groups. There were no statistically significant differences (P > 0.05) in femoral neck cortical thickness between the two groups. CONCLUSIONS: Cortical thickness thinning in the intertrochanteric region may be one of the relevant factors causing different types of hip fractures, especially in elderly patients.

Hyperspectral Imaging Detection of Total Viable Count from Vacuum Packing Cooling Mutton Based on GA and CARS Algorithms.

In the process of spectral modeling, spectral extraction of characteristic bands with different variable screening algorithms is an important step for improving the model effects. Total viable count of cooling mutton under vacuum packing condition was chosen as the research index in this paper, while the influence of 2 variable screening algorithms on its hyperspectral PLS model effects was compared. Mutton muscle spectra of Regions of interest (ROIs) were extracted and preprocessed. Subsequently, Genetic Algorithm (GA) and Competitive Adaptive Reweighted Sampling (CARS) were applied to extract characteristic bands from preprocessed spectra at full band range of 473～1 000 nm. Model effects of GA-PLS, CARS-PLS and W-PLS with corresponding bands selection were contrasted and analyzed. The results indicated that both model effects of GA-PLS, CARS-PLS were better than that of W-PLS, and CARS-PLS model effect was optimal. As for the CARS-PLS model, the determination coefficient (R2c) and root mean square error (RMSEC) of calibration set was 0.96 and 0.29, and the determination coefficient (R2cv) and root mean square error (RMSECV) of leave-one-out cross validation was 0.92 and 0.46, respectively. Meanwhile, the determination coefficient (R2p), root mean square error of prediction (RMSEP) and the ratio of standard deviation to standard error of prediction (RPD) of prediction set was 0.92 and 0.47 and 3.58, respectively. Therefore, hyperspectral imaging (HSI) technology combined with CARS-PLS can achieve quick, non-destructive and accurate detection of mutton total viable count.

[Study on the Rapid Evaluation of Total Volatile Basic Nitrogen (TVB-N) of Mutton by Hyperspectral Imaging Technique].

Total Volatile Basic Nitrogen (TVB-N) was usually taken as the physicochemical reference value to evaluate the mutton freshness. In order to explore the feasibility of hyperspectral (HSI) imaging technique to detect mutton freshness, 71 representative mutton samples were collected and scanned using a diffuse reflectance hyperspectral imaging (HSI) system in the Visible-Near infrared (NIR) spectral region (400-1 000 nm), and the chemical values of TVB-N content were determined using the semimicro Kjeldahl method according to the modified Chinese national standard. The representative spectra of mutton samples were extracted and obtained after selection of the region of interests (ROIs). The samples of calibration set and prediction set were divided at the ratio of 3 : 1 according to the content gradient method. Optimum HSI calibration models of the mutton (TVB-N) were established and evaluated by comparing different spectral preprocessing methods and modeling methods, which included Stepwise Multiple Linear Regression (SMLR), Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR) methods. The results are that through the utilization of Multiplicative Scatter Correction (MSC), first derivative, Savitzky-Golay (S-G) smoothing and mean-centering together, both PLSR and PCR were able to achieve quantitative detection of mutton TVB-N. As for the PLSR model of mutton TVB-N established, the spectral pretreatment methods chosen included MSC, first derivative, S-G (15,2) smoothing and mean-centering, and the latent variables (LVs) number used was 11. As for the calibration set of PLSR model of mutton TVB-N, the correlation coefficient (r) and root mean square error of calibration (RMSEC) were 0.92 and 3.00 mg x (100 g)(-1), respectively. As for the prediction set of PLSR model of mutton TVB-N, the correlation coefficient (r), Root Mean Square Error of Prediction (RMSEP), and ratio of standard deviation to standard error of prediction (RPD) were 0.92, 3.46 mg x (100 g)(-1) and 2.35, respectively. The study demonstrated that the rapid and accurate analysis of TVB-N, the key freshness attribute, could be implemented by using the hyperspectral imaging (HSI) technique. The study provides the basis for further rapid and non-destructive detection of other mutton freshness attributes by using the hyperspectral imaging (HSI) technique, the improvement of current modeling effect of TVB-N content and the application involved of the technique in the practical production.

[Study on Characteristic Bands Selection of Lamb pH Value Based on Hyperspectral Imaging and Partial Least Squares(PLS)].

Characteristic bands method selection and subsequent spectral extraction has a great influence on the hyperspectral model performance. For rapid and accurate detection of mutton pH value, the effects of 2 band-selection methods on PLS models of mutton pH based on HSI technique were carried out and discussed. Initially, the preprocessing method of second derivative (2D), multiplicative scatter correction (MSC) and mean-centering together was implemented on the representative spectra of mutton muscle portion. Then, 2 methods of synergy interval partial least square (siPLS) and the combination of synergy interval partial least squares with genetic algorithm (siPLS-GA) were used to extract the characteristic bands in the spectral range of 473～1 000 nm. Finally, 2 PLS models of lamb pH value were established with the corresponding characteristic bands, and were also compared with the effect of full-band PLS model. The results indicated that the effect of siPLS-GA-PLS model was the best. As for the siPLS-GA-PLS model, 56 characteristic wavelength points were chosen, the correlation coefficient(Rcal) and root mean square error(RMSEC) of calibration set was 0.96 and 0.043 respectively, and the correlation coefficient(Rp) and root mean square error(RMSEP) of prediction set was 0.96 and 0.048 respectively. Spectral variables were reduced and model accuracy was improved. It can be concluded that characteristic bands selection and rapid and accurate detection of lamb pH can be achieved using hyperspectral imaging technique combined with siPLS-GA method.

Significance of proximal femoral computed tomography scanning in the prediction of femoral prosthesis before total hip arthroplasty.

Femoral prosthesis before total hip arthroplasty (THA) predicted by Proximal Femoral CT scanning. Prior to THA, 61 hip bones in 52 cases were scanned by CT to measure the minimum inner diameter of cavum medullare in femur isthmus. The corresponding type of femoral prosthesis was selected according to the size of the cavum medullares. The conventional template measuring method was used as a contrast. The minimum inner diameter of cavum medullare in femur isthmus and the medial diameter of cavum medullare of resected femur had strong correlation with the type of femoral prosthesis (r = 0.97-0.99, P < 0.05). In terms of pre-operative femoral prosthesis selection, the CT-based isthmus-measuring method had an excellence rate of 47.5%. This method had an excellence rate of 52.5%. The CT-based resected-femur-measuring method had better accuracy in pre-operative femoral prosthesis selection for the patients.

Synergetic application of thermal imaging and CCD imaging techniques to detect mutton adulteration based on data-level fusion and deep residual network.

To improve the performance of single thermal imaging and single CCD imaging in detecting unknown adulterated meat samples, these two imaging techniques combined with a deep residual network were synergistically applied to detect mutton adulteration. Considering the importance of spatial and detailed information in improving stability and accuracy, three data-level fusion methods, namely, colour image stitching, grey image stitching and grey channel stacking, were proposed for the fusion of thermal images and CCD images. Classification and prediction models were further developed based on fusion images. The results showed that the models with colour image stitching achieved the best performance. For the external validation set, the accuracy of the best classification model in discriminating five categories was 99.30%. In predicting pork proportions, the R2, RMSE, RPD and RER of the best prediction model were 0.9717, 0.0238, 7.8696 and 21.28, respectively. The best prediction model for duck proportions had a R2 of 0.9616, RMSE of 0.0277, RPD of 5.1015, and RER of 14.44. Therefore, the synergetic application of thermal imaging and CCD imaging can provide a novel and promising tool to detect mutton adulteration and the quality of other food items.

Drying Temperature Precision Control System Based on Improved Neural Network PID Controller and Variable-Temperature Drying Experiment of Cantaloupe Slices.

A drying temperature precision control system was studied to provide technical support for developing and further proving the superiority of the variable-temperature drying process. In this study, an improved neural network (INN) proportional-integral-derivative (PID) controller (INN-PID) was designed. The dynamic performance of the PID, neural network PID (NN-PID) and INN-PID controllers was simulated with unit step signals as an input in MATLAB software. A drying temperature precision control system was set up in an air impingement dryer, and the drying temperature control experiment was carried out to verify the performance of the three controllers. Linear variable-temperature (LVT) and constant-temperature drying experiments of cantaloupe slices were carried out based on the system. Moreover, the experimental results were evaluated comprehensively with the brightness (L value), colour difference (ΔE), vitamin C content, chewiness, drying time and energy consumption (EC) as evaluation indexes. The simulation results show that the INN-PID controller outperforms the other two controllers in terms of control accuracy and regulation time. In the drying temperature control experiment at 50 °C-55 °C, the peak time of the INN-PID controller is 237.37 s, the regulation time is 134.91 s and the maximum overshoot is 4.74%. The INN-PID controller can quickly and effectively regulate the temperature of the inner chamber of the air impingement dryer. Compared with constant-temperature drying, LVT is a more effective drying mode as it ensures the quality of the material and reduces the drying time and EC. The drying temperature precision control system based on the INN-PID controller meets the temperature control requirements of the variable-temperature drying process. This system provides practical and effective technical support for the variable-temperature drying process and lays the foundation for further research. The LVT drying experiments of cantaloupe slices also show that variable-temperature drying is a better process than constant-temperature drying and is worthy of further study to be applied in production.

Simulated and Verification of Mass and Heat Transfer Coupled Model of Jujube Slices Dried by Hot Air Combined with Radio Frequency Heat Treatment at Different Drying Stages.

This study investigates the impact of radio frequency (RF) heat treatment on heat and mass transfer during the hot air drying of jujube slices. Experiments were conducted at different drying stages, comparing single-hot air drying with hot air combined with RF treatment. Numerical models using COMSOL Multiphysics® were developed to simulate the process, and the results were compared to validate the models. The maximum difference between the simulated value of the center temperature and the experimental value was 6.9 °C, while the minimum difference was 0.1 °C. The maximum difference in average surface temperature was 1.7 °C, with a minimum of 0.3 °C. The determination coefficient (R2) between the simulated experimental values of HA and the early (E-HA + RF), middle (M-HA + RF), and later (L-HA + RF) groups was 0.964, 0.987, 0.961, and 0.977, respectively. The study demonstrates that RF treatment reduces drying time, enhances internal temperature, promotes consistent heat and mass transfer, and accelerates moisture diffusion in jujube slices. Furthermore, the later the RF treatment is applied, the greater the increase in internal temperature and the faster the decrease in moisture content. This research elucidates the mechanism by which RF heat treatment influences heat transfer in hot air-dried jujube slices.

Artificial Neural Network Modeling and Genetic Algorithm Multiobjective Optimization of Process of Drying-Assisted Walnut Breaking.

This study combined an artificial neural network (ANN) with a genetic algorithm (GA) to obtain the model and optimal process parameters of drying-assisted walnut breaking. Walnuts were dried at different IR temperatures (40 °C, 45 °C, 50 °C, and 55 °C) and air velocities (1, 2, 3, and 4 m/s) to different moisture contents (10%, 15%, 20%, and 25%) by using air-impingement technology. Subsequently, the dried walnuts were broken in different loading directions (sutural, longitudinal, and vertical). The drying time (DT), specific energy consumption (SEC), high kernel rate (HR), whole kernel rate (WR), and shell-breaking rate (SR) were determined as response variables. An ANN optimized by a GA was applied to simulate the influence of IR temperature, air velocity, moisture content, and loading direction on the five response variables, from which the objective functions of DT, SEC, HR, WR, and SR were developed. A GA was applied for the simultaneous maximization of HR, WR, and SR and minimization of DT and SEC to determine the optimized process parameters. The ANN model had a satisfactory prediction ability, with the coefficients of determination of 0.996, 0.998, 0.990, 0.991, and 0.993 for DT, SEC, HR, WR, and SR, respectively. The optimized process parameters were found to be 54.9 °C of IR temperature, 3.66 m/s of air velocity, 10.9% of moisture content, and vertical loading direction. The model combining an ANN and a GA was proven to be an effective method for predicting and optimizing the process parameters of walnut breaking. The predicted values under optimized process parameters fitted the experimental data well, with a low relative error value of 2.51-3.96%. This study can help improve the quality of walnut breaking, processing efficiency, and energy conservation. The ANN modeling and GA multiobjective optimization method developed in this study provide references for the process optimization of walnut and other similar commodities.

Discrimination of Minced Mutton Adulteration Based on Sized-Adaptive Online NIRS Information and 2D Conventional Neural Network.

Single-probe near-infrared spectroscopy (NIRS) usually uses different spectral information for modelling, but there are few reports about its influence on model performance. Based on sized-adaptive online NIRS information and the 2D conventional neural network (CNN), minced samples of pure mutton, pork, duck, and adulterated mutton with pork/duck were classified in this study. The influence of spectral information, convolution kernel sizes, and classifiers on model performance was separately explored. The results showed that spectral information had a great influence on model accuracy, of which the maximum difference could reach up to 12.06% for the same validation set. The convolution kernel sizes and classifiers had little effect on model accuracy but had significant influence on classification speed. For all datasets, the accuracy of the CNN model with mean spectral information per direction, extreme learning machine (ELM) classifier, and 7 × 7 convolution kernel was higher than 99.56%. Considering the rapidity and practicality, this study provides a fast and accurate method for online classification of adulterated mutton.

Microstructure Analysis and Quality Evaluation of Jujube Slices Dried by Hot Air Combined with Radio Frequency Heat Treatment at Different Drying Stages.

Jujubes have been favored by consumers because of their rich nutrition and wide use. Hot air drying has been commercially and typically used to prolong shelf life and acquire the dried produce. Jujube slices were dried with hot air combined with radio frequency (RF) at different drying stages, namely, early (0-2 h, E-HA + RF), middle (2-4 h, M-HA + RF), later (4-6 h, L-HA + RF), and whole (0-6 h, W-HA + RF) stages. This study aimed to investigate the effects of different RF application stages on the microstructure, moisture absorption rate, color, and ascorbic acid of jujube slices. Compared with the hot air drying (HA) group, the E-HA + RF group obtained the best results among the experimental groups because it reduced the cells with a roundness of less than 0.4 by 5%. Moreover, the M-HA + RF group showed better results than those of other groups, with an 18.6% and 48.8% reduction in cells for a cross-sectional area less than 200 µm2 and a perimeter less than 25 µm, respectively. The minimum total color difference (ΔE = 9.21 ± 0.31) and maximum retention of ascorbic acid (285.06 mg/100 g) were also observed in this group. Therefore, the method of hot air drying assisted by phased RF is viable in the drying industry to improve the quality of dried agricultural products and reduce energy consumption.

Evaluation of Mutton Adulteration under the Effect of Mutton Flavour Essence Using Hyperspectral Imaging Combined with Machine Learning and Sparrow Search Algorithm.

The evaluation of mutton adulteration faces new challenges because of mutton flavour essence, which achieves a similar flavour between the adulterant and mutton. Hence, methods for classifying and quantifying the adulterated mutton under the effect of mutton flavour essence, based on near-infrared hyperspectral imaging (NIR-HSI, 1000-2500 nm) combined with machine learning (ML) and sparrow search algorithm (SSA), were proposed in this study. After spectral preprocessing via first derivative combined with multiple scattering correction (1D + MSC), classification and quantification models were established using back propagation neural network (BP), extreme learning machine (ELM) and support vector machine/regression (SVM/SVR). SSA was further used to explore the global optimal parameters of these models. Results showed that the performance of models improves after optimisation via the SSA. SSA-SVM achieved the optimal discrimination result, with an accuracy of 99.79% in the prediction set; SSA-SVR achieved the optimal prediction result, with an RP2 of 0.9304 and an RMSEP of 0.0458 g·g-1. Hence, NIR-HSI combined with ML and SSA is feasible for classification and quantification of mutton adulteration under the effect of mutton flavour essence. This study can provide a theoretical and practical reference for the evaluation and supervision of food quality under complex conditions.

Mortality and Related Risk Factors of Fragile Hip Fracture.

OBJECTIVE: To explore the mortality of patients with fragile hip fractures and assess the death-associated risk factors. METHODS: A total of 690 patients with osteoporotic hip fractures (age, 50-103 years) that were treated from January 2010 to December 2015 were enrolled and followed-up in this study and the clinical data were retrospectively collected. Three months, 1 year, and the total mortality were measured. Mortality-related risk factors were assessed including age, gender, surgery, the duration from injury to operation, pulmonary infection, and the number and type of complications. The mortality of each group was compared by chi-square test or corrected chi-square test for univariate analysis, and the factors with statistically significant mortality difference confirmed by univariate analysis were analyzed by binary logistic multivariate analysis. RESULTS: The 3-month mortality was 7.69%, the 1-year mortality was 15.60%, and the total mortality of the follow-up time was 24.06%. The 1-year and total mortality during the follow-up of the patients were higher in the >75-year-old group than those in the ≤75-year-old group (p = 0.000, respectively); were higher in the male patients than that in the female patients (p = 0.042; p = 0.017, respectively); were significantly lower in the operation group than that in the non-operation group (p = 0.000, respectively); were significantly lower in the patients that underwent the operation in ≤5 days than the patients that underwent the operation within >5 days (p = 0.008; p = 0.000, respectively); were significantly lower in patients with >2 kinds of combined medical diseases than those with ≥2 kinds of chronic diseases (p = 0.000, respectively); were significantly lower in patients receiving anti-osteoporosis treatment than in patients not receiving anti-osteoporosis treatment (p = 0.000, p = 0.002, respectively). Binary logistic regression analysis showed that the independent risk factors affecting mortality included advanced age >75-years-old (OR = 5.653, p = 0.000), male (OR = 1.998, p = 0.001), non-surgical treatment (OR = 9.909, p = 0.000), the number of combined medical diseases ≥2 (OR = 1.522, p = 0.042), and non-anti-osteoporosis treatment (OR = 1.796, p = 0.002). CONCLUSION: Age, whether or not surgical treatment was performed, the number of medical diseases, and whether or not anti-osteoporosis treatment was performed were independent risk factors for 3-month and 1-year mortality in patients with fragile hip fractures.