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Doxorubicin (DOX) is one of the most commonly used anticancer drugs; however, its clinical application is greatly limited due to its toxicity and chemotherapy resistance. The delivery of DOX by liposomes (Lipos) can improve the blood circulation time in vivo and reduce toxic side effects, but the drug’s accumulation in the tumor is often insufficient for effective treatment. In this study, we present a calcium cross-linked liposome gel for the encapsulation of DOX, demonstrating its superior long-term release capabilities compared to conventional Lipos. By leveraging this enhanced long-term release, we can enhance drug accumulation within tumors, ultimately leading to improved antitumor efficacy. Lipos were prepared using the thin-film dispersion method in this study. We utilized the ion-responsiveness of glutathione-gelatin (GSH-GG) to form the gel outside the Lipos and named the nanoparticles coated with GSH-GG on the outside of Lipos as Lipos@GSH-GG. The average size of Lipos@GSH-GG was around 342.9 nm, with a negative charge of -25.6 mV. The in vitro experiments revealed that Lipos@GSH-GG exhibited excellent biocompatibility and slower drug release compared to conventional Lipos. Further analysis of cellular uptake and cytotoxicity demonstrated that Lipos@GSH-GG loading DOX (DOX&Lipos@GSH-GG) exhibited superior long-term release effects and lower toxic side effects compared to Lipos loading DOX (DOX&Lipos). Additionally, the findings regarding the long-term release effect in vivo and the tumor accumulation within tumor-bearing mice of Lipos@GSH-GG suggested that, compared to Lipos, it demonstrated superior long-term release capabilities and achieved greater drug accumulation within tumors. In vivo antitumor efficacy experiments showed that DOX&Lipos@GSH-GG demonstrated superior antitumor efficacy to DOX&Lipos. Our study highlights Lipos@GSH-GG as a promising nanocarrier with the potential to enhance efficacy and safety by means of long-term release effects and may offer an alternative approach for effective antitumor therapy in the future.

In this letter, we investigate the joint beamspace waveform design and beam selection problem for lens antenna array (LAA)-assisted integrated sensing and communication (ISAC) systems. The LAA effectively reduces the number of required radio frequency (RF) chains by transforming the dense spatial domain channel into a sparse beamspace channel. We adopt a more practical power consumption model and aim to minimize the system power consumption while guaranteeing the communication and sensing performance. The system power consumption involves the $\ell _{0}$ norm of the transmitting signal, which makes the objective intractable. To address this issue, we propose an iterative reweighting successive convex approximation (IR-SCA) algorithm, which sequentially relaxes the $\ell _{0}$ norm to a reweighted $\ell _{1}$ norm, and approximates the non-convex quadratic form using its first-order Taylor expansion. Simulation results convincingly demonstrate that the proposed method outperforms fully digital systems in terms of energy efficiency.

Background: Evaluating the risk of metastasis and recurrence of a cervical cancer patient iscritical for appropriate adjuvant therapy. However, current risk assessment models usually involve thetesting of tens to thousands of genes from patients tissue samples, which is expensive and timeconsuming.Therefore, computer-aided diagnosis and prognosis prediction based on Hematoxylin and Eosin(H&E) pathological images have received much attention recently. Objective: The prognosis of whether patients will have metastasis and recurrence can support accuratetreatment for patients in advance and help reduce patient loss. It is also important for guiding treatmentafter surgery to be able to quickly and accurately predict the risk of metastasis and recurrence of a cervicalcancer patient. Methods: To address this problem, we propose a hybrid method. Transfer learning is used to extract features,and it is combined with traditional machine learning in order to analyze and determine whetherpatients have the risks of metastasis and recurrence. First, the proposed model retrieved relevant patchesusing a color-based method from H&E pathological images, which were then subjected to image preprocessingsteps such as image normalization and color homogenization. Based on the labeled patchedimages, the Xception model with good classification performance was selected, and deep features ofpatched pathological images were automatically extracted with transfer learning. After that, the extractedfeatures were combined to train a random forest model to predict the label of a new patched image.Finally, a majority voting method was developed to predict the metastasis and recurrence risk of a patientbased on the predictions of patched images from the whole-slide H&E image. Results: In our experiment, the proposed model yielded an area under the receiver operating characteristiccurve of 0.82 for the whole-slide image. The experimental results showed that the high-level featuresextracted by the deep convolutional neural network from the whole-slide image can be used to predictthe risk of recurrence and metastasis after surgical resection and help identify patients who might receiveadditional benefit from adjuvant therapy. Conclusion: This paper explored the feasibility of predicting the risk of metastasis and recurrence fromcervical cancer whole slide H&E images through deep learning and random forest methods.

A total of 18 male New Zealand white rabbits aged 3 months were selected for operation by using horse serum combined with Dimi rabbit femoral head necrosis model. After finishing the modelling, the rabbits that were successfully modelled were randomly divided into equal groups and divided into the following three groups: the autogenous bone group (group A), the stent group (group B), and the right-guidance combined stent group (Group C), there are six animals in each group. At the same time, they were treated with femoral head necrosis and hip-sparing surgery, and they were all located on the right side. Group A had autologous patella repair material, group B tricalcium phosphate scaffold, and group C right-guiding gavage combined with phosphate implantation. Three calcium scaffolds. From the beginning of the surgery, rabbits in each group were sacrificed on the 5th, 10th, and 15th weeks by over-anaesthesia, and the three groups were examined by histology and immunohistochemistry. Through research, Youguiyin combined with stent has a significant effect on the repair of wrist and femoral head necrotic bone, promotes osteogenesis and inhibits osteoclastic activity, and significantly improves the ability of bone repair in the head. Youguiyin can further improve the stent implantation. Stent osseointegration ability is a good alternative to autologous bone, and it provides some ideas for exploring new methods of integrated traditional Chinese and Western medicine for repairing wrist ligament damage.

Background. Knee osteoarthritis (KOA) is a high incidence chronic joint disease that seriously affects patients’ quality of life, and current treatment methods have limited efficacy. Self-management may be an effective strategy for KOA, and clinicians have been showing increased interest recently. However, the effectiveness of self-management for KOA remains controversial. Purpose. This study aims to systematically evaluate the effectiveness of self-management for KOA. Methods. We screened articles published in MEDLINE, Cochrane Library, EMBASE, and Web of Science until September 17, 2021. The main outcomes included pain, knee function, stiffness, WOMAC (total), physical function, arthritis self-efficacy (ASE-pain), arthritis self-efficacy (ASE-other symptoms), mental health, and quality of life. Results. Thirteen randomized controlled trials (RCTs) were finally included (n = 1610). Meta-analysis showed differences in pain, knee function, stiffness, ASE-pain, ASE-other symptoms, mental health, and quality of life between the self-management and control groups. Of the nine outcomes evaluated, four were highly heterogeneous, and the quality of evidence ranged from very low to moderate. Conclusion. The meta-analysis results showed that self-management might help improve the pain, knee function, stiffness, ASE, mental health, and quality of life in patients with KOA. However, it has no significant effect on WOMAC (total) and physical function. Considering that this study has some limitations, we cannot draw clear conclusions based on the results of this study. Nevertheless, we offer much needed insight and encourage more rigorously designed and implemented RCTs in the future to substantiate our conclusions.