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Abstract Background Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength. However, current anti‐resorptive drugs carry a risk of various complications. The deep learning‐based efficacy prediction system (DLEPS) is a forecasting tool that can effectively compete in drug screening and prediction based on gene expression changes. This study aimed to explore the protective effect and potential mechanisms of cinobufotalin (CB), a traditional Chinese medicine (TCM), on bone loss. Methods DLEPS was employed for screening anti‐osteoporotic agents according to gene profile changes in primary osteoporosis. Micro‐CT, histological and morphological analysis were applied for the bone protective detection of CB, and the osteogenic differentiation/function in human bone marrow mesenchymal stem cells (hBMMSCs) were also investigated. The underlying mechanism was verified using qRT‐PCR, Western blot (WB), immunofluorescence (IF), etc. Results A safe concentration (0.25 mg/kg in vivo, 0.05 μM in vitro) of CB could effectively preserve bone mass in estrogen deficiency‐induced bone loss and promote osteogenic differentiation/function of hBMMSCs. Both BMPs/SMAD and Wnt/β‐catenin signaling pathways participated in CB‐induced osteogenic differentiation, further regulating the expression of osteogenesis‐associated factors, and ultimately promoting osteogenesis. Conclusion Our study demonstrated that CB could significantly reverse estrogen deficiency‐induced bone loss, further promoting osteogenic differentiation/function of hBMMSCs, with BMPs/SMAD and Wnt/β‐catenin signaling pathways involved.

Abstract Background Breast cancer (BC) metastasis is the common cause of high mortality. Conventional prognostic criteria cannot accurately predict the BC metastasis risk. The machine learning technologies can overcome the disadvantage of conventional models. Aim We developed a model to predict BC metastasis using the random survival forest (RSF) method. Methods Based on demographic data and routine clinical data, we used RSF‐recursive feature elimination to identify the predictive variables and developed a model to predict metastasis using RSF method. The area under the receiver operating characteristic curve (AUROC) and Kaplan–Meier survival (KM) analyses were plotted to validate the predictive effect when C‐index was plotted to assess the discrimination and Brier scores was plotted to assess the calibration of the predictive model. Results We developed a metastasis prediction model comprising three variables (pathological stage, aspartate aminotransferase, and neutrophil count) selected by RSF‐recursive feature elimination. The model was reliable and stable when assessed by the AUROC (0.932 in training set and 0.905 in validation set) and KM survival analyses (p

Abstract Recently, relaxation linear regression has received increasing attention in image analysis. However, the current relaxation linear regression methods fail to consider the local geometrical structure and spatial information while they are applied for hyperspectral image (HSI) classification. To address the above problems, this letter proposes a novel relaxation linear regression with spectral–spatial constrained locality adaptive regularization (SSLA‐RLR) method for HSI classification. The SSLA‐RLR method not only integrates the locality adaptive graph with relaxation linear regression to adaptively exploit the local geometrical structure for relieving the side effects of noise corruptions, but also takes the spatial correlations between each data point and its neighbours into consideration via spectral–spatial constraint. Finally, extensive experiments are conducted on three benchmark HSI datasets to demonstrate the effectiveness of the proposed method.

Objective To assess a safe surgical approach for intertransverse process lower thoracic intervertebral body fusion (ITIF) based on measurements from enhanced three‐dimensional CT reconstruction, cadaver simulated operation, and patient operation. Methods Enhanced three‐dimensional CT image reconstruction was performed for 20 healthy volunteers on thoracic segments T8–T12. The length of the transverse process (LTP), distance between the upper and lower transverse processes (DULTP), remote distance of the transverse process (RDTP), height of the extraforaminal intervertebral space (HEIS), and oblique diameter of the intervertebral space (ODIS) were measured and recorded. The blood vessels of the intertransverse lower thoracic region were observed, and their internal diameters were measured. The rib‐intervertebral space relationship for T10/11 and T11/12 was measured in 104 patients of the thoracic skeleton. Then, based on the data from the CT measurements, simulated surgery was performed on six human cadavers at the T11/12 level. An ankylosing spondylitis (AS) patient with a fracture of the T10/11 level was eventually operated on with the ITIF technique. Results No significant difference was found between the lengths of the left and right thoracic transverse processes. The relationship of the values of the LTP and RDTP for the measured vertebrae were found to be as follows:T8 > T9 > T10 > T11 > T12. For HEIS and DULTP, T8–9 < T9–10 < T10–11 < T11–12. The results for the ODIS were as follows: T8–T9 < T9–T10 < T10–T11 < T11–T12. The blood vessel inner diameter of T11–12 was less than that of T10–11, while there was no significant difference between the diameters for T8–9 and T11–12. Almost half of the volunteer's T10/11 intervertebral spaces were covered posteriorly by the 11th rib (45.19% on left and 41.35% on right), while for most patients, the T11/12 intervertebral space was not covered by the 12th rib (98.08%). According to the cadaver experiments, intervertebral bone grafting and ipsilateral pedicle screw fixation were performed to simulate the operation. One patient with a combined AS and T10/11 fracture was then operated on with the ITIF technique and followed up for 3 years with satisfactory results. Conclusion As verified by 3D CT reconstruction measurements, cadaver simulation surgery and patient operation with follow‐up, the intertransverse process approach for some T10/T11 and almost all T11/T12 segments is a safe surgical pathway for operations such as ITIF, fracture bone grafting, clearance of focal lesions.

Background. The aim of this study was to establish a hepatitis B virus (HBV) vaccination protocol among orthotopic liver transplantation (OLT) recipients under the coverage of a low-dose hepatitis B immunoglobulin (HBIG) combined with an antiviral agent prophylaxis protocol. Method. Two hundred OLT recipients were included in this study. The vaccine was injected at months 0, 1, 2, and 6. Low-dose HBIG combined with antiviral agent prophylaxis protocol was continued before reestablishment of active immunity against HBV in order to maintain a steady anti-HBs titer. Results. Active immunity against HBV was reestablished in 50 patients, for an overall response rate of 25%. Of the 50 patients, 24 discontinued HBIG without any HBV graft reinfection during a follow-up period of 26.13 ± 7.05 months. 21 patients discontinued both HBIG and antiviral agents during a follow-up period of 39.86 ± 15.47 months, and 4 patients among them appeared to be HBsAg positive. There was no recipient death or graft loss because of HBV reinfection. Conclusions. Vaccination preventing HBV reinfection for OLT recipients is feasible. The strategy withdrawal of HBIG with induction of active immunity against hepatitis B is reasonable for long-term survivors of OLT; however, discontinuation nucleoside analogues should be cautious.

Regarding the tracking of moving target in the large-scale fixed scene, a new routing algorithm of LAODV in the principle of TOA localization is proposed. Then, the participation field of the fixed node based on the node location information is properly controlled, while the routing request area is reduced through combination of AODV and LAR during transmission of the location information. Simulation results show that the proposed algorithm renders satisfactory performance in terms of average delay reduction from end to end, packet loss rate, and routing overhead. As a result, the delay and system overhead during localization could be minimized.