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Background: The area of computational pathology has made huge progresses due to advances in artificial intelligence (AI) and machine learning technologies. It has been applied to many research and translational tasks which provide great improvement on medical diagnosis and treatment. Cancer stem-like cells (CSC) have been consistently reported for its key role in Triple negative breast cancer (TNBC) . Given the large amount of existing H&E stained histological slides of TNBC, digital identification of CSC could benefit the evaluation of tumor status and prediction of patients’ response to chemotherapy. Here we proposed an AI framework based on Convolutional Neural Network (CNN) to predict CSC from the histological images of TNBC patient. And our preliminary work suggested that chromosome 17p loss, a common genetic variations in breast cancer, is linked to cancer stemness. Methods: A modified GoogleNet model was adopted as our CNN classifier. Consecutive breast cancer tissue microarrays (TMA), which stained with H&E ,SOX2, OCT4 and NANOG antibodies respectively by IHC, were used as training dataset for the CNN model. Gene expression data from the TCGA and METABRIC datasets were used to identify gene signatures associated with CSC. The connectivity map (CMAP) and Cancer Cell Line Encyclopedia (CCLE) were used for screening compounds that target stemness in cancer cell lines with chromosomal 17p loss. HS578T and EO771 cells with or without heterozygous 17p loss (11b in EO771) were used for in vitro experiments. Female immunodeficient nude (Nu/J) mice were used for animal studies. Results: The well trained GoogleNet model was applied to TNBC patient diagnosis images in TCGA BRCA dataset. By analyzing patient genomic alteration on chromosomal level, we found that loss of chromosome 17p associate with high cancer stemness in TNBC. Flow cytometry assays also demonstrated higher ALDH1 activity and higher CD44+/CD24−/low cell population in HS578T cells with 17p loss. RNA-seq of HS578T cells revealed that most CSC marker genes were located in the unregulated differentially expressed genes (DEGs) of 17p loss cells. We next compared the cytotoxicity of chemotherapy drugs including doxorubicin, paclitaxel, docetaxel and cisplatin on 17p loss and 17p intact HS578T cells, 11b loss and 11b intact EO771 cells, in terms of IC50 value. The IC50 value of indicated drug on 17p loss HS578T cells with were 3-6 fold higher than their IC50 on 17p intact HS578T cells. Similar result was observed in EO771 cells. Next, 17p loss and 17p intact HS578T cells were orthotopically implanted into the Nu/J mice. Under the doxorubicin treatment, mice bearing 17p loss HS578T derived tumors had larger and heavier tumors in compare to mice bearing 17p intact tumors. Next, we did a computational drug screening to identify compounds that can target the cancer stemness in 17p loss cells. Screened out compounds were tested for their cytotoxicity on 17p loss and 17p intact HS578T cells and FK866 showed the most pronounced efficacy on inhibiting the viability of 17p loss cells, compared to 17p intact cells. Followup experiments demonstrated that FK866 can decrease the CSC features induced by doxorubicin, both in vitro and in vivo. FK866 also potentiates the effect of doxorubicin on treating TNBC cells with 17p loss, which provide a drug combination potential for TNBC patient with 17p loss. Conclusions: A CNN based model was developed to identify CSC from TNBC histopathology images. The images analysis combined with patient genomic data revealed that chromosome 17p loss associated with cancer stemness in TNBC. This result was confirmed using assays on TNBC cells with or without 17p loss. A computational drug screening was performed to identify candidates that targeting stemness in 17p loss cells. FK866 was identified and it potentiates the anti-tumor effect of doxorubicin on treating TNBC cells with 17p loss. Our study provides a novel strategy on applying AI to precision treatment for cancers. Citation Format: tianhan dong, jiannan liu, yuanzhang Fang, Ziyu Liu, Xiongbin Lu, kun huang. Machine learning based histopathology images analysis reveals cancer stemness in TNBC patient with 17p loss [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-14-08.

Purpose: For patients who need to reconstruct the mandible with the fibula, this article gives an automated design scheme to save the doctor's time. Methods: First, perform the initial registration by analyzing the characteristic points of the fibula and jaw defect, cut the fibula and move it to the approximate location. Then optimize and adjust, and finally give a plan. Results The average operating time is about 10s for each reconstruction planning. Six surgeons at different levels were invited to rate the output of our method and manual operations by expert and novice, the evaluation of our method is even higher than that of the experts. Conclusions: The proposed method can automatically accomplish the task. At the same time, it is self-defining, allowing doctors to select the required feature points based on their own experience. This design has application value in the design of surgical plan.

Free fibula flap is the first choice for jaw reconstruction in head and neck oncology, but postoperative complications in donor site are ignored always. The main purpose of this study was to investigate the long-term complications and potential risk factors of donor site after vascularized fibular transplantation, and to explore the precautions of preparing vascularized fibular flap and the measures of preventing donor site complications.Data were retrospectively collected on 31 patients who had undergone immediate mandibular reconstruction with a fibular flap after segmental mandibulectomy from 2013 to 2018 in Shanghai Ninth People's Hospital. Thirty-one patients (24 male, 7 female) were available for the long-term complications in donor site analysis from 25 to 96 months after surgery. The data were collected and analyzed, including age at time of operation, early postoperative complications, incidence of dorsiflexion weakness of hallux, donor site missing fibula length, proximal and distal stump fibula length, and subjective evaluation of foot function (AOFAS-hallux, AOFAS-ankle hindfoot, Enneking lower limb function score). In the single-factor analysis in this study, the correlation between related factors and long-term complications was statistically analyzed. For inter-group comparisons of quantitative data, if the normal distribution was satisfied, two independent sample t-tests were used; p 0.05 was statistical significant. If the normal distribution was not satisfied, Wilcoxon rank-sum test was used, and p 0.05 was considered statistically significant. For qualitative data, the Fisher exact probability method was compared between group differences, and p 0.05 was statistically significant.The most commonly encountered complication in our series was dorsiflexion disorder, flexion deformity, numbness of the lateral side of the lower leg, and dorsum of the foot. Ten patients (32.26%) developed hallux flexion deformity after operation, 17 patients (54.84%) had hallux dorsiflexion dysfunction after operation, and 10 patients (32.26%) had numbness of the lateral side of the lower leg and dorsum of the foot. The incidence of hallux dorsiflexion dysfunction, thumb flexion deformity, and sensory disturbance was higher than that of other long-term complications in the donor area. The residual length of fibular distal was related to the dorsiflexion dysfunction and flexion deformity of hallux (p 0.05). The early complications of donor site were correlated with the hallux dorsiflexion dysfunction (p 0.05).The incidence of dorsiflexion disorder and flexion deformity is higher in patients after fibula transplantation. The less the residual length of fibular distal, the more obvious the long-term complications in the donor site, and the higher the incidence of dorsiflexion dysfunction and flexion deformity of hallux.The long-term complications of donor site after fibular transplantation seriously affect the quality of life of patients and provide clinical reference for further reducing the occurrence of donor site complications.

Sports events are an indispensable part of popularization and strong entertainment and can promote the physical and mental health of the people and the construction of cultural and spiritual civilization. Therefore, it is necessary to use a timer to record and analyze data during the game. In the traditional sense, the game timer is a fixed system. And now we can design sports event timer operations through mobile phones, computers, and other equipment to assist in the calculation of game time and competition. Ferroelectric memory is a kind of random access memory, which combines the fast read and write access of dynamic random access memory with the ability to retain data. Based on this, the ferroelectric memory timer proposed in this paper is intended to improve the accuracy and fairness of sports events. Therefore, this article has tested the function of the timer designed in this article by studying the ferroelectric memory and experimental construction and testing methods and finally concluded that the design is reasonable, but there is still a problem of data susceptibility. The experimental results show that there is a certain gap between the time interval measurement level of the timer and SR, the difference is 47 ps, the pulse width difference is controlled at 0.004, and the measurement uncertainty of timer interval is better than 60 ps. This shows that the timer can be applied, but it needs further improvement.

Periodontal disease (PD) is one of the most prevalent dental diseases. Fortunately, it can be prevented if identified early, especially for high-risk patients. Dental electronic health records (EHRs) could help develop a data-driven personalized prediction model using advanced machine learning development of clinical decision support system (CDSS) as in our Phase I, II AMIA-AI showcase. In phase II, we created a CDSS, the Perio-Risk Scoring system (PRSS), to help clinicians generate perio-scores and diagnoses and identify the influential factors. In Phase III (this study), we implemented and compared the patient’s risk factors information in five periodontal risk assessment tools [periodontal risk assessment (PRA), PreViser, Sonicare, Cigna, and Periodontal Risk Scoring System (PRSS)]. We examined 1) agreement between the risk scores provided by each of the five risk assessment tools of 20 patients’ information and 2) compare the risk scores provided by each tool to the original outcomes (five years outcomes). Fleiss Kappa, Cohen’s Kappa, and percentage agreements were performed to determine the agreements between risk scores and original outcomes. We found a -1.24 Kappa value which indicates disagreement between the risk scores provided by five risk assessment tools. Compared to the original outcomes (five-year disease outcomes), PRSS provided the most accurate prediction (70%), followed by Previser (55%), PRA (35%), Phillips (35%), and Cigna (25%). We conclude that using advanced state-of-the-art informatics methods could help us utilize EHR data optimally to represent the current patient populations and their risk factors to provide the most accurate disease risk score. This may promote preventive strategies at the chairside, hoping to reduce PD prevalence, improve quality of life, and reduce healthcare costs.

Anaerobic exercise capacity and neuromuscular activity research is an important content and an emerging research field in sports training research. At present, the understanding of anaerobic exercise ability in academia is still at the general and overall cognitive level, and the understanding and application of anaerobic exercise ability cannot fully meet the needs of competitive sports practice. In order to solve these problems, this paper proposes a cyclic anaerobic exercise performance and neuromuscular activity based on artificial intelligence genetic algorithm, aimed at studying the theory and application mechanism of anaerobic exercise capacity and neuromuscular activity and its application characteristics in competitive sports practice. The approach in this paper is to design genetic operators, compare artificial intelligence genetic algorithms, and test neuromuscular movements. The purpose of these methods is to provide exercisers with a feasible and more effective new method of daily training and to investigate whether this new training method can optimize anaerobic exercise in humans. In this paper, by studying the kinematic basis of anaerobic exercise capacity and the mechanism of neuromuscular regulation, a model of muscle neuron population in anaerobic exercise is established. The results showed that the CMC of the beta band was significantly higher than that of the alpha band at the same strength level, with a difference of 0.03.

Multiagent technology, as a conceptual model commonly used in intelligent systems, has now had a lot of related research, and it is also widely used in sports training simulation systems. This paper mainly studies the development of the sports training simulation system based on agent technology. This paper proposes the motion perception system of multiagent technology in sports training. In the research, this paper introduces the related concepts and methods of agent in detail. In order to better simulate the changes of human joints during exercise with the system, this article uses a variety of comparison methods. Among them, the experiment of the imaging analysis module is carried out through the simulation of the simulation system. The experimental results show that the role of multiagent in the simulation system is huge. In linear motion, the accuracy of joint extraction has reached more than 95%. The extraction of joints in the curve movement reached more than 80%, indicating that it can not only complete the relevant processing adaptively but also predict and correct the exercise process of the trainer. Therefore, in the research of sports training simulation system, more attention should be paid to the research of curve motion.

Heuristic and machine learning models for rank-ordering reaction templates comprise an important basis for computer-aided organic synthesis regarding both product prediction and retrosynthetic pathway planning. Their viability relies heavily on the quality and characteristics of the underlying template database. With the advent of automated reaction and template extraction software and consequently the creation of template databases too large for manual curation, a data-driven approach to assess and improve the quality of template sets is needed. We therefore systematically studied the influence of template generality, canonicalization, and exclusivity on the performance of different template ranking models. We find that duplicate and nonexclusive templates, i.e., templates which describe the same chemical transformation on identical or overlapping sets of molecules, decrease both the accuracy of the ranking algorithm and the applicability of the respective top-ranked templates significantly. To remedy the negative effects of nonexclusivity, we developed a general and computationally efficient framework to deduplicate and hierarchically correct templates. As a result, performance improved considerably for both heuristic and machine learning template ranking models, as well as multistep retrosynthetic planning models. The canonicalization and correction code is made freely available.

Aedes aegypti is a crucial vector of many diseases that cause millions of deaths worldwide. Cry11Aa display high toxicity to the larvae of Ae.aegypti. And the Galectins are a family of β-galactoside binding proteins that play a role in immune responses and may also affect Cry11Aa toxin activity. In our previous work, Galectin 6 and Galectin 14 were found to affect toxicity of Bt toxins. However, there are also some other galectin genes expressed in the gut of Ae.aegypti, such as Galectin 8, whose function is still not confirmed yet. In order to further understand its function and molecular mechanism, Ae.aegypti galectin 8 gene was cloned, expressed the recombinant protein and purified in this study. The bioassays results indicated that Galectin 8 is similar to Galectin 6 to reduce the toxicity of Cry11Aa. In order to determine interactions among Galectin8, Cry11Aa and toxin receptors, Octet Red System, Western blot, far-western blot assay were also performed. Octet Red System result showed that Galectin 8 could also bind to BBMVs of Ae.aegypti, but the kDa value is smaller than that of Galectin 6, indicating that Galectin 8 had a stronger binding ability to BBMVs than Galectin 6. Western blot and far-western blot analyses also demonstrated that Galectin 8 could bind to Ae.aegypti receptor ALP1 and APN2, similar to result of protein docking simulation. All of these results support the conclusion that Galectin 8 may increase block Cry11Aa from binding to ALP1 and APN2 than Galectin 6, which might decrease the toxicity of Cry11Aa for Ae.aegypti.

The process of basketball is often accompanied by physical injury, serious fractures of limbs will also occur. At present, the most common treatment for limb fracture is surgery, which can repair t...

BackgroundTremendous research efforts have been made in the Alzheimer’s disease (AD) field to understand the disease etiology, progression and discover treatments for AD. Many mechanistic hypotheses, therapeutic targets and treatment strategies have been proposed in the last few decades. Reviewing previous work and staying current on this ever-growing body of AD publications is an essential yet difficult task for AD researchers.MethodsIn this study, we designed and implemented a natural language processing (NLP) pipeline to extract gene-specific neurodegenerative disease (ND) -focused information from the PubMed database. The collected publication information was filtered and cleaned to construct AD-related gene-specific publication profiles. Six categories of AD-related information are extracted from the processed publication data: publication trend by year, dementia type occurrence, brain region occurrence, mouse model information, keywords occurrence, and co-occurring genes. A user-friendly web portal is then developed using Django framework to provide gene query functions and data visualizations for the generalized and summarized publication information.ResultsBy implementing the NLP pipeline, we extracted gene-specific ND-related publication information from the abstracts of the publications in the PubMed database. The results are summarized and visualized through an interactive web query portal. Multiple visualization windows display the ND publication trends, mouse models used, dementia types, involved brain regions, keywords to major AD-related biological processes, and co-occurring genes. Direct links to PubMed sites are provided for all recorded publications on the query result page of the web portal.ConclusionThe resulting portal is a valuable tool and data source for quick querying and displaying AD publications tailored to users’ interested research areas and gene targets, which is especially convenient for users without informatic mining skills. Our study will not only keep AD field researchers updated with the progress of AD research, assist them in conducting preliminary examinations efficiently, but also offers additional support for hypothesis generation and validation which will contribute significantly to the communication, dissimilation and progress of AD research.

In this study, we fabricated a super-hydrophilic (θ < 5°) hierarchical reticular porous structure on the surface of Ti–24Nb–4Zr–8Sn (Ti2448) by combining sandblasting, dual acid-etching, and alkali...

Purpose The differentiation of the ameloblastoma and odontogenic keratocyst directly affects the formulation of surgical plans, while the results of differential diagnosis by imaging alone are not satisfactory. This paper aimed to propose an algorithm based on convolutional neural networks (CNN) structure to significantly improve the classification accuracy of these two tumors. Methods A total of 420 digital panoramic radiographs provided by 401 patients were acquired from the Shanghai Ninth People’s Hospital. Each of them was cropped to a patch as a region of interest by radiologists. Furthermore, inverse logarithm transformation and histogram equalization were employed to increase the contrast of the region of interest (ROI). To alleviate overfitting, random rotation and flip transform as data augmentation algorithms were adopted to the training dataset. We provided a CNN structure based on a transfer learning algorithm, which consists of two branches in parallel. The output of the network is a two-dimensional vector representing the predicted scores of ameloblastoma and odontogenic keratocyst, respectively. Results The proposed network achieved an accuracy of 90.36% (AUC = 0.946), while sensitivity and specificity were 92.88% and 87.80%, respectively. Two other networks named VGG-19 and ResNet-50 and a network trained from scratch were also used in the experiment, which achieved accuracy of 80.72%, 78.31%, and 69.88%, respectively. Conclusions We proposed an algorithm that significantly improves the differential diagnosis accuracy of ameloblastoma and odontogenic keratocyst and has the utility to provide a reliable recommendation to the oral maxillofacial specialists before surgery.

Purpose. To report a technique for performing sutureless intrascleral fixation of a posterior chamber intraocular lens (PC-IOL) and analyzing the clinical outcomes and postoperative complications. Study Design. 68 eyes of 66 patients who received the technique were studied retrospectively. Methods. The best-corrected visual acuity (BCVA), intraocular pressure (IOP), anterior chamber depth (ACD), IOL tilt and decentration, corneal topography (K1 and K2), and postoperative complications were determined at 3 months. Results. The mean preoperative BCVA was 1.63 ± 1.24 logMAR units, and the mean postoperative BCVA was 0.74 ± 0.59 logMAR units at 3 months (P<0.05). The mean preoperative IOP was 21.9 ± 12.6 mmHg, and the mean postoperative IOP was 16.9 ± 4.5 mmHg at 3 months (P = 0.001). The mean preoperative corneal topography (K1 and K2) was K1 = 42.14 ± 1.91 and K2 = 43.54 ± 1.51; the mean postoperative corneal topography (K1 and K2) was K1 = 43.03 ± 2.18 and K2 = 43.40 ± 1.71 at 3 months (P = 0.678 and 0.468, respectively). The mean preoperative spherical equivalent was +11.00 ± 13.19 diopters (D), and the mean postoperative spherical equivalent was +0.06 ± 0.86 D (P<0.005). The mean IOL tilt was 2.4 ± 1.7°, and the mean decentration was 0.35 ± 0.21 mm. The mean ACD was 4.31 ± 0.29 mm. Conclusions. The 27-gauge sutureless intrascleral PC-IOL implantation technique minimizes intraoperative injury, simplifies procedure, and provides good PC-IOL fixation with few postoperative complications.

Of all pathological types of renal cell cancer (RCC), clear cell renal cell carcinoma (ccRCC) has the highest incidence. Cyclovirobuxine (CVB), a triterpenoid alkaloid isolated from Buxus microphylla, exhibits antitumour activity against gastric cancer and breast cancer; however, the mechanism by which CVB inhibits ccRCC remains unclear. The aim of our study was to explore the antitumour effects of CVB on ccRCC and to elucidate its exact mechanism. Cell viability, proliferation, cell cycle distribution, apoptosis, wound healing and invasion were evaluated. Furthermore, Western blotting, immunofluorescence staining, immunohistochemical staining, and bioinformatics analyses were utilized to comprehensively probe the molecular mechanisms. The in vivo curative effect of CVB was explored using a 786-O xenograft model established in nude mice. CVB reduced cell viability, proliferation, angiogenesis, the epithelial-mesenchymal transition (EMT), migration and invasion. In addition, CVB induced cell cycle arrest in S phase and promoted apoptosis. The expression of the EMT-related transcription factor Snail was significantly downregulated by CVB via the inhibition of the AKT, STAT3 and MAPK pathways. We revealed that insulin-like growth factor binding protein 3 (IGFBP3) was the true therapeutic target of CVB. CVB exerted anti-ccRCC effects by blocking the IGFBP3-AKT/STAT3/MAPK-Snail pathway. Targeted inhibition of IGFBP3 with CVB treatment may become a promising therapeutic regimen for ccRCC.

Background Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. Molecular level characters, such as gene expression levels and mutations, may provide profound information for precision treatment apart from pathological indicators. Transcription factors function as critical regulators in all aspects of cell life, but transcription factors-based biomarkers for colon cancer prognosis were still rare and necessary. Methods We implemented an innovative process to select the transcription factors variables and evaluate the prognostic prediction power by combining the Cox PH model with the random forest algorithm. We picked five top-ranked transcription factors and built a prediction model by using Cox PH regression. Using Kaplan-Meier analysis, we validated our predictive model on four independent publicly available datasets (GSE39582, GSE17536, GSE37892, and GSE17537) from the GEO database, consisting of 925 colon cancer patients. Results A five-transcription-factors based predictive model for colon cancer prognosis has been developed by using TCGA colon cancer patient data. Five transcription factors identified for the predictive model is HOXC9, ZNF556, HEYL, HOXC4 and HOXC6. The prediction power of the model is validated with four GEO datasets consisting of 1584 patient samples. Kaplan-Meier curve and log-rank tests were conducted on both training and validation datasets, the difference of overall survival time between predicted low and high-risk groups can be clearly observed. Gene set enrichment analysis was performed to further investigate the difference between low and high-risk groups in the gene pathway level. The biological meaning was interpreted. Overall, our results prove our prediction model has a strong prediction power on colon cancer prognosis. Conclusions Transcription factors can be used to construct colon cancer prognostic signatures with strong prediction power. The variable selection process used in this study has the potential to be implemented in the prognostic signature discovery of other cancer types. Our five TF-based predictive model would help with understanding the hidden relationship between colon cancer patient survival and transcription factor activities. It will also provide more insights into the precision treatment of colon cancer patients from a genomic information perspective.

The analysis of the maxillary sinus (MS) can provide an assessment for many clinical diagnoses, so accurate CT image segmentation of the MS is essential. However, common segmentation methods are mainly done by experienced doctors manually, and there are some challenges such as low efficiency and precision. As for automatic methods, the initial seed points and adjustment of various parameters are required, which will affect the segmentation efficiency. Thus, accurate, efficient, and automatic segmentation method of MS is critical to promote the clinical application. This paper proposed an automatic CT image segmentation method of MS based on VGG network and improved V-Net. The VGG network was established to classify CT slices, which can avoid the failure of CT slice segmentation without MS. Then, we proposed the improved V-Net based on edge supervision for segmenting MS regions more effectively. The edge loss was integrated into the loss of the improved V-Net, which could reduce region misjudgment and improve the automatic segmentation performance. For the classification of CT slices with MS and without MS, the VGG network had a classification accuracy of 97.04 ± 2.03%. In the segmentation, our method obtained a better result, in which the segmentation Dice reached 94.40 ± 2.07%, the Iou (intersection over union) was 90.05 ± 3.26%, and the precision was 94.72 ± 2.64%. Compared with U-Net and V-Net, it reduced region misjudgment significantly and improved the segmentation accuracy. By analyzing the error map of 3D reconstruction, it was mainly distributed in ± 1 mm, which demonstrated that our result was quite close to the ground truth. The segmentation of the MS can be realized efficiently, accurately, and automatically by our method. Meanwhile, it not only has a better segmentation result, but also improves the doctor’s work efficiency, which will have significant impact on clinical applications in the future.

Background While several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes. Methods Gene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-expressed targets in TCGA using a nonlinear approach. We then used this information to predict breast cancer patient survival outcome. Result We built a multiple regulator-based prediction model for breast cancer. This model was validated in more than 5000 breast cancer patients from the Gene Expression Omnibus (GEO) databases. We demonstrated our regulator model was significantly associated with clinical stage and that cell cycle and DNA replication related pathways were significantly enriched in high regulator risk patients. Conclusion Our findings demonstrate that transcriptional regulator activities can predict patient survival. This finding provides additional biological insights into the mechanisms of breast cancer progression.

Purpose Various reports found a relationship between lymphocyte-related blood parameters (LRBP), including absolute lymphocyte counts (ALC), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) and prognosis of breast cancer. Most of the studies focused on LRBP pre-treatment. Seldom have studies focused on LRBP during radiotherapy. We intended to perform a retrospective cohort study on the prognostic value of LRBP at the time point of lowest ALC during radiotherapy for breast cancer. Patients and methods A total of 158 female patients were included in radiotherapy group because of the strict limitation standards of complete routine blood test results at pre-treatment and pre-operation, and at least once a week during radiotherapy. Besides 221 patients, including the 158 patients of radiotherapy group, were adopted in pre-treatment group and pre-operation group. Results ALC and PLR at the time point of lowest ALC during radiotherapy are prognostic predictors of breast cancer, and lower ALC and higher PLR are independent significant predictors of poor DFS. Besides, lower ALC, higher NLR and higher PLR at both pre-treatment and pre-operation were found to be independent variables for predicting poor DFS. Conclusion LRBP at pre-treatment, pre-operation, and during radiotherapy may serve as predictors of outcomes of breast cancer.

Cryptotanshinone (CTT), extracted from the root of Salvia miltiorrhiza Bunge (Danshen), exhibits activities against a variety of human cancers in vitro and in vivo. The purpose of this study was to investigate the potential inhibitory effect of CTT on bladder cancer. In this study, we found that CTT inhibited bladder cancer cell proliferation, migration, and invasion and promoted apoptosis. In addition, CTT modulated the expression of proteins via the PI3K/AKT pathway, and the inhibition of PI3K/AKT signalling was due to induction of PTEN expression. Taken together, the results of the present study demonstrated the anticancer effect of CTT on bladder cancer cells, which might be associated with the downregulation of PI3K/AKT/mTOR and NF-κB signalling pathway proteins, and this inhibition was mediated by the induction of PTEN.

Buccal titanium plate fixation is a common method for repairing mandibular defects. However, the method presents certain problems: the requirement of a large volume of titanium plate, a large number of fixation screws, a lengthy duration of the surgical operation, and exposure of the fixation plate which easily causes wound infection. In this study, a new base-fixation system was designed. Mandibular reconstruction was performed using the three-dimensional reconstruction package Mimics. In order to compare the newly designed base-fixation system and the common buccal-fixation system, the stress distributions and the displacement distributions of the whole model under two loading conditions were studied, based on the finite element analysis package ANSYS. The safety of the base-fixation titanium plate was evaluated. The results showed that although the maximum stress of the base-fixation titanium plate was higher than that of the buccal-fixation titanium plate, it was still less than the yield strength of titanium. Therefore, under the condition of applying 300 N of vertical occlusal loading, the base-fixation titanium plate displayed superior fixation ability without permanent deformation (and concomitant fixation failure). The results of the fatigue simulation analysis showed that the safety factor of the base-fixation titanium plate in the working state was 3.8 (1.0), indicating that its fatigue performance met the application requirements. Compared with traditional buccal fixation, the novel base-fixation system has obvious advantages, suggesting its suitability as a new treatment method for clinical mandibular defect reconstruction.

Free fibula flap is the gold standard for the treatment of mandibular defects. However, the existing preoperative planning protocol is cumbersome to execute, costly to learn, and poorly collaborative with the robot-assisted cutting of the fibular osteotomy plane.A surgical planning system for robotic assisted mandibular reconstruction with fibula free flap is proposed in this study. A fibular osteotomy planning algorithm is presented so that the virtual surgical planning of the fibular osteotomy segments can be obtained automatically with selected mandibular anatomical landmarks. The planned osteotomy planes are then converted into the motion path of the robotic arm, and the automatic fibula osteotomy is completed under optical navigation.Surgical planning was performed on 35 patients to verify the feasibility of our system's virtual surgical planning module, with an average time of 13 min. Phantom experiments were performed to evaluate the reliability and stability of this system. The average distance and angular deviations of the osteotomy planes are 1.04 ± 0.68 mm and 1.56 ±1.10°, respectively.Our system can achieve not only precise and convenient preoperative planning, but also safe and reliable osteotomy trajectory. The clinical applications of our system for mandibular reconstruction surgery are expected soon.

Large-scale jaw reconstruction can hardly achieve satisfactory results only by relying on doctors' experience. In this study, we assessed a new approach using a machine learning algorithm based on jaw feature points to assist complex jaw reconstruction in patients with maxillary and mandibular defects.One hundred and two computed tomography (CT) data on the jaw were collected and 16 skeletal marker points on the jaw were selected. The machine learning algorithm learned the positional relationship between points and built a model, which was used to predict the coordinate position of an unknown point. Then the model was used for a surgical plan in clinical cases.The linear regression model based on machine learning can control the error within 3 mm. In linear models, Lasso has a slight advantage over the others. We used Lasso to predict the missing points for two patients with maxillary and mandibular defect, respectively. The operation was carried out as planned, and the defects were successfully repaired.The restoration of jaw feature points based on a machine learning algorithm is expected to solve large-scale jaw defects without contralateral reference.

The growth and development of skeletal muscle is a physiological process regulated by a variety of genes and signaling pathways. As a posttranscriptional regulatory factor, circRNA plays a certain regulatory role in the development of animal skeletal muscle in the form of a miRNA sponge. However, the role of circRNAs in muscle development and growth in goats is still unclear. In our study, apparent differences in muscle fibers in Wu'an goats of different ages was firstly detected by hematoxylin-eosin (HE) staining, the circRNA expression profiles of longissimus dorsi muscles from 1-month-old (mon1) and 9-month-old (mon9) goats were screened by RNA-seq and verified by RT–qPCR. The host genes of differentially expressed (DE) circRNAs were predicted, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses (KEGG) of host genes with DE circRNAs were performed to explore the functions of circRNAs. The circRNA-miRNA-mRNA networks were then constructed using Cytoscape software. Ten significantly differentially expressed circRNAs were also verified in the mon1 and mon9 groups by RT–qPCR. Luciferase Reporter Assay was used to verify the binding site between circRNA and its targeted miRNA. The results showed that a total of 686 DE circRNAs were identified between the mon9 and mon1 groups, of which 357 were upregulated and 329 were downregulated. Subsequently, the 467 host genes of DE circRNAs were predicted using Find_circ and CIRI software. The circRNA-miRNA-mRNA network contained 201 circRNAs, 85 miRNAs, and 581 mRNAs; the host mRNAs were associated with “muscle fiber development” and “AMPK signaling pathway” and were enriched in the FoxO signaling pathway. Competing endogenous RNA (ceRNA) network analysis showed that novel_circ_0005314, novel_circ_0005319, novel_circ_0009256, novel_circ_0009845, novel_circ_0005934 and novel_circ_0000134 may play important roles in skeletal muscle growth and development between the mon9 and mon1 groups. Luciferase Reporter Assay confirmed the combination between novel_circ_0005319 and chi-miR-199a-5p, novel_circ_0005934 and chi-miR-450-3p and novel_circ_0000134 and chi-miR-655. Our results provide specific information related to goat muscle development and a reference for the goat circRNA profile.

Age-related macular degeneration (AMD) is the main cause of blindness in elderly individuals. As a metabolic regulator, fibroblast growth factor 21 (FGF-21) has been proven indicated to have an effect on wet AMD, but whether this cytokine has a therapeutic effect on dry AMD is unclear. The current study aimed to evaluate the preventive effects of FGF-21 against retinal degeneration in mice and provide mechanistic insights. FGF-21-/- mice were raised to 10 months of age. Then, the morphological changes in the retinal pigment epithelium (RPE)/choroid of the mice were observed by transmission electron microscopy (TEM), and iTRAQ was used to detect the variations in the protein profile. Next, FGF-21-/- and wild-type mice of the same age were fed hydroquinone to generate a dry AMD mouse model to examine whether exogenous FGF-21 can interfere with the occurrence and development of dry AMD. In vivo studies revealed that following FGF-21 knockout, there was an increase in the expression of complement in the RPE/choroid concomitant with the occurrence of dry AMD-like pathological changes. Furthermore, exogenous FGF-21 administration effectively reversed this phenomenon. FGF-21 also demonstrated strong anti-inflammatory effects in the RPE/choroid by inhibiting the NF-κB pathway. In conclusion, the present study demonstrates that FGF-21 treatment presents a novel therapeutic approach for the prevention and development of dry AMD by reducing complement.

To assure complete tumor removal, frozen section analysis is the most common procedure for intraoperative pathological assessment of resected tumor margins. However, during one operation, multiple biopsies may be sent for examination, but only few of them are made into cryosections because of the complex preparation protocols and time-consuming pathological analysis, which potentially increases the risk of overlooking tumor involvement. Here, we propose a fluorescence-based pre-screening strategy that allows high-throughput, convenient, and fast gross assessment of resected tumor margins. A dual-activatable cationic fluorescent molecular rotor was developed to specifically illuminate live tumor cells’ cytoplasm by emitting two different fluorescence signals in response to elevations in hypoxia-induced nitroreductase (a biochemical marker) and cytoplasmic viscosity (a biophysical marker), two characteristics of cancer cells. The ability of the fluorescent molecular rotor in detecting tumor cells was evaluated in mouse and human specimens of multiple tissues by comparing with hematoxylin and eosin staining. Importantly, the fluorescent molecular rotor achieved 100 % specificity in discriminating lung and liver cancers from normal tissue, allowing pre-screening of the tumor-free surgical margins and promoting clinical decision. Altogether, this type of fluorescent molecular rotor and the proposed strategy may serve as a new option to facilitate intraoperative assessment of resected tumor margins.

Heuristic and machine learning models for rank-ordering reaction templates comprise an important basis for computer-aided organic synthesis regarding both product prediction and retrosynthetic pathway planning. Their viability relies heavily on the quality and characteristics of the underlying template database. With the advent of automated reaction and template extraction software and consequently the creation of template databases too large to be curated manually, a data-driven approach to assess and improve the quality of template sets is needed. We therefore systematically studied the influence of template generality, canonicalization and exclusivity on the performance of different template ranking models. We find that duplicate and non-exclusive templates, \textit{i.e.} templates which describe the same chemical transformation on identical or overlapping sets of molecules, decrease both the accuracy of the ranking algorithm and the applicability of the respective top-ranked templates significantly. To remedy the negative effects of non-exclusivity, we developed a general and computationally efficient framework to deduplicate and hierarchically correct templates. As a result, performance improved for both heuristic and machine learning template ranking algorithms across different template sizes. The canonicalization and correction code was made freely available.