Effectiveness and safety of Governor vessel acupuncture therapy for post-stroke cognitive impairment: A meta-analysis of randomized controlled trials.

OBJECTIVE: The purpose of this study was to evaluate the effectiveness of Governor vessel acupuncture (GV Ac) in treating post-stroke cognitive impairment (PSCI). METHODS: There was a total of seven databases examined. Four English databases (Cochrane Library, PubMed, Embase, and Medline) and three Chinese databases (Chinese National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Databases (VIP), and Wan Fang Database) contain all randomized controlled trials (RCTs) comparing Governor vessel acupuncture to other treatments or none acupuncture for PSCI. The exact dates for the search period are from January 1, 2000, to January 1, 2023.Two researchers independently reviewed the literature, gathered RCT data, and performed statistical analysis. All data were analyzed using Review Manager software (Rev Man) 5.3. RESULTS: This meta-analysis includes a total of 39 trials with 2044 patients. There were 1022 participants in each of the test and control groups. Following 12-120 days of acupuncture treatment, a meta-analysis revealed that the treatment groups (GV Ac combined with conventional treatment groups) significantly increased their scores on the Curative ratio (OR = 3.00, 95 %CI = 2.37-3.79, P = 0.98, I² = 0 %), Montreal Cognitive Assessment (MoCA)(MD = 1.82, 95 %CI = 1.60-2.03, P = 0.11, I² = 25 %), Mini-Mental State Examination (MMSE)(MD = 2.18, 95 %CI = 1.64-2.72, P<0.005, I² = 92 %), and Activity of Daily Living (ADL)(MD = 5.99, 95 %CI = 5.33-6.64, P = 0.19, I² = 26 %). CONCLUSION: The results suggested that acupuncture on points of the Governor vessel enhanced cognitive function in stroke survivors.

[Mechanism of Shikonin on spinal cord injury in rats based on TNFR/RIPK1 pathway].

OBJECTIVE: To explore the effect of shikonin on the recovery of nerve function after acute spinal cord injury(SCI) in rats. METHODS: 96 male Sprague-Dawley(SD)rats were divided into 4 groups randomly:sham operation group (Group A), sham operation+shikonin group (Group B), SCI+ DMSO(Group C), SCI+shikonin group (Group D).The acute SCI model of rats was made by clamp method in groups C and D . After subdural catheterization, no drug was given in group A. rats in groups B and D were injected with 100 mg·kg-1 of shikonin through catheter 30 min after modeling, and rats in group C were given with the same amount of DMSO, once a day until the time point of collection tissue. Basso-Beattie-Bresnahan(BBB) scores were performed on 8 rats in each group at 6, 12, and 3 d after moneling, and oblique plate tests were performed on 1, 3, 7 and 14 d after modeling, and then spinal cord tissues were collected. Eight rats were intraperitoneally injected with propidine iodide(PI) 1 h before sacrificed to detection PI positive cells at 24 h in each group. Eight rats were sacrificed in each group at 24 h after modeling, the spinal cord injury was observed by HE staining.The Nissl staining was used to observe survivor number of nerve cells. Western-blot technique was used to detect the expression levels of Bcl-2 protein and apoptosis related protein RIPK1. RESULTS: After modeling, BBB scores were normal in group A and B, but in group C and D were significantly higher than those in group A and B. And the scores in group D were higher than those in group C in each time point (P<0.05). At 12 h after modeling, the PI red stained cells in group D were significantly reduced compared with that in group C, and the disintegration of neurons was alleviated(P<0.05). HE and Nissl staining showed nerve cells with normal morphology in group A and B at 24h after operation. The degree of SCI and the number of neuronal survival in group D were better than those in group C, the difference was statistically significant at 24h (P<0.05). The expression of Bcl-2 and RIPK1 proteins was very low in group A and B;The expression of RIPK1 was significantly increased in Group C and decreased in Group D, with a statistically significant difference (P<0.05);The expression of Bcl-2 protein in group D was significantly higher than that in group C (P<0.05). CONCLUSION: Shikonin can alleviate the pathological changes after acute SCI in rats, improve the behavioral score, and promote the recovery of spinal nerve function. The specific mechanism may be related to the inhibition of TNFR/RIPK1 signaling pathway mediated necrotic apoptosis.

Mechanism of Shikonin on spinal cord injury in rats based on TNFR/RIPK1 pathway / 中国骨伤

OBJECTIVE@#To explore the effect of shikonin on the recovery of nerve function after acute spinal cord injury(SCI) in rats.@*METHODS@#96 male Sprague-Dawley(SD)rats were divided into 4 groups randomly:sham operation group (Group A), sham operation+shikonin group (Group B), SCI+ DMSO(Group C), SCI+shikonin group (Group D).The acute SCI model of rats was made by clamp method in groups C and D . After subdural catheterization, no drug was given in group A. rats in groups B and D were injected with 100 mg·kg-1 of shikonin through catheter 30 min after modeling, and rats in group C were given with the same amount of DMSO, once a day until the time point of collection tissue. Basso-Beattie-Bresnahan(BBB) scores were performed on 8 rats in each group at 6, 12, and 3 d after moneling, and oblique plate tests were performed on 1, 3, 7 and 14 d after modeling, and then spinal cord tissues were collected. Eight rats were intraperitoneally injected with propidine iodide(PI) 1 h before sacrificed to detection PI positive cells at 24 h in each group. Eight rats were sacrificed in each group at 24 h after modeling, the spinal cord injury was observed by HE staining.The Nissl staining was used to observe survivor number of nerve cells. Western-blot technique was used to detect the expression levels of Bcl-2 protein and apoptosis related protein RIPK1.@*RESULTS@#After modeling, BBB scores were normal in group A and B, but in group C and D were significantly higher than those in group A and B. And the scores in group D were higher than those in group C in each time point (P<0.05). At 12 h after modeling, the PI red stained cells in group D were significantly reduced compared with that in group C, and the disintegration of neurons was alleviated(P<0.05). HE and Nissl staining showed nerve cells with normal morphology in group A and B at 24h after operation. The degree of SCI and the number of neuronal survival in group D were better than those in group C, the difference was statistically significant at 24h (P<0.05). The expression of Bcl-2 and RIPK1 proteins was very low in group A and B;The expression of RIPK1 was significantly increased in Group C and decreased in Group D, with a statistically significant difference (P<0.05);The expression of Bcl-2 protein in group D was significantly higher than that in group C (P<0.05).@*CONCLUSION@#Shikonin can alleviate the pathological changes after acute SCI in rats, improve the behavioral score, and promote the recovery of spinal nerve function. The specific mechanism may be related to the inhibition of TNFR/RIPK1 signaling pathway mediated necrotic apoptosis.

Deep Reinforcement Learning With Explicit Context Representation.

Though reinforcement learning (RL) has shown an outstanding capability for solving complex computational problems, most RL algorithms lack an explicit method that would allow learning from contextual information. On the other hand, humans often use context to identify patterns and relations among elements in the environment, along with how to avoid making wrong actions. However, what may seem like an obviously wrong decision from a human perspective could take hundreds of steps for an RL agent to learn to avoid. This article proposes a framework for discrete environments called Iota explicit context representation (IECR). The framework involves representing each state using contextual key frames (CKFs), which can then be used to extract a function that represents the affordances of the state; in addition, two loss functions are introduced with respect to the affordances of the state. The novelty of the IECR framework lies in its capacity to extract contextual information from the environment and learn from the CKFs' representation. We validate the framework by developing four new algorithms that learn using context: Iota deep Q-network (IDQN), Iota double deep Q-network (IDDQN), Iota dueling deep Q-network (IDuDQN), and Iota dueling double deep Q-network (IDDDQN). Furthermore, we evaluate the framework and the new algorithms in five discrete environments. We show that all the algorithms, which use contextual information, converge in around 40 000 training steps of the neural networks, significantly outperforming their state-of-the-art equivalents.

FCOS-LSC: A Novel Model for Green Fruit Detection in a Complex Orchard Environment.

To better address the difficulties in designing green fruit recognition techniques in machine vision systems, a new fruit detection model is proposed. This model is an optimization of the FCOS (full convolution one-stage object detection) algorithm, incorporating LSC (level scales, spaces, channels) attention blocks in the network structure, and named FCOS-LSC. The method achieves efficient recognition and localization of green fruit images affected by overlapping occlusions, lighting conditions, and capture angles. Specifically, the improved feature extraction network ResNet50 with added deformable convolution is used to fully extract green fruit feature information. The feature pyramid network (FPN) is employed to fully fuse low-level detail information and high-level semantic information in a cross-connected and top-down connected way. Next, the attention mechanisms are added to each of the 3 dimensions of scale, space (including the height and width of the feature map), and channel of the generated multiscale feature map to improve the feature perception capability of the network. Finally, the classification and regression subnetworks of the model are applied to predict the fruit category and bounding box. In the classification branch, a new positive and negative sample selection strategy is applied to better distinguish supervised signals by designing weights in the loss function to achieve more accurate fruit detection. The proposed FCOS-LSC model has 38.65M parameters, 38.72G floating point operations, and mean average precision of 63.0% and 75.2% for detecting green apples and green persimmons, respectively. In summary, FCOS-LSC outperforms the state-of-the-art models in terms of precision and complexity to meet the accurate and efficient requirements of green fruit recognition using intelligent agricultural equipment. Correspondingly, FCOS-LSC can be used to improve the robustness and generalization of the green fruit detection models.

BFP Net: Balanced Feature Pyramid Network for Small Apple Detection in Complex Orchard Environment.

Despite of significant achievements made in the detection of target fruits, small fruit detection remains a great challenge, especially for immature small green fruits with a few pixels. The closeness of color between the fruit skin and the background greatly increases the difficulty of locating small target fruits in the natural orchard environment. In this paper, we propose a balanced feature pyramid network (BFP Net) for small apple detection. This network can balance information mapped to small apples from two perspectives: multiple-scale fruits on the different layers of FPN and a characteristic of a new extended feature from the output of ResNet50 conv1. Specifically, we design a weight-like feature fusion architecture on the lateral connection and top-down structure to alleviate the small-scale information imbalance on the different layers of FPN. Moreover, a new extended layer from ResNet50 conv1 is embedded into the lowest layer of standard FPN, and a decoupled-aggregated module is devised on this new extended layer of FPN to complement spatial location information and relieve the problem of locating small apple. In addition, a feature Kullback-Leibler distillation loss is introduced to transfer favorable knowledge from the teacher model to the student model. Experimental results show that APS of our method reaches 47.0%, 42.2%, and 35.6% on the benchmark of the GreenApple, MinneApple, and Pascal VOC, respectively. Overall, our method is not only slightly better than some state-of-the-art methods but also has a good generalization performance.

Follicular carcinoma of the thyroid with a single metastatic lesion in the lumbar spine: A case report.

BACKGROUND: The bone is the second most common site of thyroid cancer metastasis, after the lung. Treatment options for bone metastasis of thyroid cancer include surgery, radioiodine therapy (RAIT), external radiation therapy, thyroid-stimulating hormone (TSH) inhibition, bisphosphonates, and small-molecule targeted therapies. In most cases, thyroid carcinoma is found in the thyroid tissue; reports of follicular thyroid carcinoma with a single metastasis to the lumbar spine are rare. CASE SUMMARY: We report a case of bone metastasis as the only clinical manifestation of thyroid cancer. The patient was a 67-year-old woman with lumbar pain for 7 years and aggravation with intermittent claudication who had previously undergone partial thyroidectomy of a benign thyroid lesion. No abnormal nodules were found in the bilateral thyroid glands. However, imaging studies were consistent with a spinal tumor, and the lesion was diagnosed as a metastatic follicular carcinoma of thyroid origin. We adopted a multidisciplinary collaboration and comprehensive treatment approach. The patient underwent lumbar spine surgery, total resection of the thyroid, postoperative TSH suppression therapy, and RAIT. There were no complications associated with the operation, and the patient had good postoperative recovery. She has experienced no recurrence. CONCLUSION: Follicular thyroid carcinoma is associated with early hematogenous metastasis, and the bone is a typical site of metastasis. Single bone metastasis is not a contraindication to medical procedures, and providing the appropriate therapy can result in better outcomes and quality of life for these patients.

Hierarchical Reinforcement Learning With Universal Policies for Multistep Robotic Manipulation.

Multistep tasks, such as block stacking or parts (dis)assembly, are complex for autonomous robotic manipulation. A robotic system for such tasks would need to hierarchically combine motion control at a lower level and symbolic planning at a higher level. Recently, reinforcement learning (RL)-based methods have been shown to handle robotic motion control with better flexibility and generalizability. However, these methods have limited capability to handle such complex tasks involving planning and control with many intermediate steps over a long time horizon. First, current RL systems cannot achieve varied outcomes by planning over intermediate steps (e.g., stacking blocks in different orders). Second, the exploration efficiency of learning multistep tasks is low, especially when rewards are sparse. To address these limitations, we develop a unified hierarchical reinforcement learning framework, named Universal Option Framework (UOF), to enable the agent to learn varied outcomes in multistep tasks. To improve learning efficiency, we train both symbolic planning and kinematic control policies in parallel, aided by two proposed techniques: 1) an auto-adjusting exploration strategy (AAES) at the low level to stabilize the parallel training, and 2) abstract demonstrations at the high level to accelerate convergence. To evaluate its performance, we performed experiments on various multistep block-stacking tasks with blocks of different shapes and combinations and with different degrees of freedom for robot control. The results demonstrate that our method can accomplish multistep manipulation tasks more efficiently and stably, and with significantly less memory consumption.

Efficiency comparison with fovea-sparing internal limiting membrane peeling and complete internal limiting membrane peeling for treating myopic traction maculopathy.

PURPOSE: To explore whether the efficacy of fovea-sparing internal limiting membrane peeling (FS-ILMP) is better than that of complete internal limiting membrane peeling (ILMP). METHODS: This retrospective clinical study included 34 cases (34 eyes) with myopic traction maculopathy collected from June 2017 to February 2019. Twenty-three-gauge (23-G) pars plana vitrectomy (23G PPV) was performed on all patients. In the FS-ILMP group, 18 eyes retained the internal limiting membrane (ILM) of about 1 to 1.5 papillary diameter centered on fovea centralis, while in the standard ILMP group, the ILM was completely removed from 16 eyes. The best corrected visual acuity (BCVA), central foveal thickness (CFT), and other indexes were collected before and 6 months after surgery. RESULTS: There was no significant difference in baseline clinical characteristics between the two groups. CFT and BCVA were significantly improved in both FS-ILMP and standard ILMP group, but the postoperative BCVA of the FS-ILMP group was significantly better than that of the standard ILMP group (P < 0.001). Two cases of subretinal effusion in macula were recorded in the FS-ILMP group, and three eyes in the standard ILMP group developed macular holes after surgery. Although both treatments relieved the mechanical traction of macular fovea, the patients in the FS-ILMP group showed better clinical outcomes in various aspects. CONCLUSION: These results improved our understanding of the clinical application of vitrectomy combined with preservation of ILM upon the fovea centralis, which might lay a foundation for in-depth study on the treatment of myopic traction maculopathy.

Serum albumin and the risk of contrast-induced acute kidney injury after percutaneous coronary intervention.

Serum creatinine and serum albumin levels were measured prior to surgery, and serum creatinine level was also measured at 72 hours following percutaneous coronary intervention in 819 (January 1st, 2015 and December 31th, 2018). According to whether patients developed contrast-induced acute kidney injury or not, they were assigned to either a contrast-induced acute kidney injury group (72 cases, 8.8%) or a non-contrast-induced acute kidney injury group (747 cases; control). Serum albumin was significantly lower in the contrast-induced acute kidney injury group than control (39.33 ± 5.09 g/l and 42.69 ± 5.19 g/l, respectively, P < 0.001). The results of a receiver-operating curve analysis indicated a serum albumin level of 40.5 g/L was the optimal cut-off value for prediction of contrast-induced acute kidney injury and according to a multivariate logistic regression analysis, serum albumin was an independent biomarker for prediction of (95% confidence interval: 0.836-0.935, odds ratio: 0.884, P < 0.001). Serum albumin, a low-cost and easily assessable laboratory protein, was independently related to a greater risk of contrast-induced acute kidney injury among patients that received percutaneous coronary intervention. It is proposed that under these circumstances SA is a potential biomarker for contrast-induced acute kidney injury.

KIF18B as a regulator in microtubule movement accelerates tumor progression and triggers poor outcome in lung adenocarcinoma.

KIF18B is involved in several tumor progression and exerts critical effects on microtubule growth during mitosis, but its role in lung adenocarcinoma still remains rare. Hence, we attempted to explore the biological function of KIF18B in lung adenocarcinoma. We first analyzed the expressional pattern of KIF18B in lung adenocarcinoma, and detected the correlation between KIF18B expression and clinical characteristics in lung adenocarcinoma based on The Cancer Genome Atlas (TCGA) database and Oncomine dataset. Subsequently, cell counting kit-8 (CCK-8) assay, wound-healing analysis, and transwell method were performed to assess the effects of KIF18B in lung adenocarcinoma cells. Quantitative real-time reverse transcription-PCR (qRT-PCR) and western blotting were utilized to measure the mRNA and protein expression levels. Our results illustrated that KIF18B expression was significantly up-regulated in lung adenocarcinoma samples compared to normal specimens. High levels of KIF18B were associated with unfavorable prognosis of lung adenocarcinoma patients. Down-regulation of KIF18B in lung adenocarcinoma cells inhibited cell prolifartion, migration, and invasion. Western blot assay demonstrated that KIF18B knockdown markedly decreased Rac1-GTP expression, an important marker of migration and invasion in tumors. Moreover, the phosphorylation of AKT and mTOR expression levels were attenuated after KIF18B knockdown. Taken together, these data enhanced the point that KIF18B might promote lung adenocarcinoma cell proliferation, migration, and invasion by activating Rac1 and mediating the AKT/mTOR signaling pathway.

Feature extraction of four-class motor imagery EEG signals based on functional brain network.

OBJECTIVE: A motor-imagery-based brain-computer interface (MI-BCI) provides an alternative way for people to interface with the outside world. However, the classification accuracy of MI signals remains challenging, especially with an increased number of classes and the presence of high variations with data from multiple individual people. This work investigates electroencephalogram (EEG) signal processing techniques, aiming to enhance the classification performance of multiple MI tasks in terms of tackling the challenges caused by the vast variety of subjects. APPROACH: This work introduces a novel method to extract discriminative features by combining the features of functional brain networks with two other feature extraction algorithms: common spatial pattern (CSP) and local characteristic-scale decomposition (LCD). After functional brain networks are established from the MI EEG signals of the subjects, the measures of degree in the binary networks are extracted as additional features and fused with features in the frequency and spatial domains extracted by the CSP and LCD algorithms. A real-time BCI robot control system is designed and implemented with the proposed method. Subjects can control the movement of the robot through four classes of MI tasks. Both the BCI competition IV dataset 2a and real-time data acquired in our designed system are used to validate the performance of the proposed method. MAIN RESULTS: As for the offline data experiment results, the average classification accuracy of the proposed method reaches 79.7%, outperforming the majority of popular algorithms. Experimental results with real-time data also prove the proposed method to be highly promising in its real-time performance. SIGNIFICANCE: The experimental results show that our proposed method is robust in extracting discriminative brain activity features when performing different MI tasks, hence improving the classification accuracy in four-class MI tasks. The high classification accuracy and low computational demand show a considerable practicality for real-time rehabilitation systems.

Correlation study on mobile phone addiction and sleep quality of military medical students / 第二军医大学学报

Objective: To investigate the relationship between mobile phone addiction and sleep quality of military medical students, so as to provide evidence for improving their mental health. Methods: A total of 237 cadets from freshman to senior majored in medicine were tested by the Pittsburgh sleep quality index (PSQI) scale and mobile phone addiction tendency scale (MPATS). Results: Eventually, 227 valid questionnaires were collected, with the effective response rate being 95.8%. The mean score of PSQI was 5.78±2.26, and the mean score of MPATS was 38.65±11.32. Females had a worse sleep quality than male military medical students (6.12±2.11 vs 5.49±2.35, P < 0.05). Junior cadets had the highest MPATS score (42.51 ± 10.81). The score of PSQI was positively correlated with the score of MPATS among military medical students (r 0.280, P<0.01). Regression analysis showed that mobile phone addiction had significant impact on sleep quality of military medical students (P < 0.01). Conclusion: Mobile phone overuse has a negative impact on sleep quality among military medical students, especially in females. It is necessary to strengthen the management mobile phone use among junior cadets.

Sh-MARCH8 Inhibits Tumorigenesis via PI3K Pathway in Gastric Cancer.

BACKGROUND/AIMS: To identify new treatment strategies for gastric cancer and to elucidate the mechanism underlying its pathophysiology, we transfected sh-MARCH8 into the human gastric cancer cell lines MKN-45 and AGS to investigate the roles of MARCH8 in gastric cancer. METHODS: We used genetic engineering to construct the sh-MARCH8 interference plasmid and transfected it into gastric cancer cells. Colony formation assays and cell viability measurements were performed to detect the viability and proliferation of cancer cells. Wound healing assays were performed to estimate the migration and proliferation rates of the cells. Cell invasion assays were used to estimate the invasive abilities of the cells. Cell apoptosis analysis was performed by using flowing cytometry. Western blot analysis was performed to estimate the expression levels of proteins. Statistical analysis was performed using the SPSS 18.0 software. Student's t-test was used to determine the significance of all pairwise comparisons of interest. RESULTS: We observed that the transfection of sh-MARCH8 inhibited the survival and proliferation of MKN-45 and AGS cells. The migration and invasion of the MKN-45 and AGS cells were significantly decreased, and apoptosis was induced in comparison with the control cells. These results were further confirmed by data showing that sh-MARCH8 increased the BAX/BCL2 ratio in MKN-45 and AGS cells. We also observed that sh-MARCH8 inactivated the PI3K and ß-catenin stat3 signaling pathways by changing protein expression levels or the phosphorylation of related proteins. CONCLUSION: These data suggested that sh-March8 reduced viability and induced apoptosis of the MKN-45 and AGS cells through the PI3K and ß-catenin stat3 signaling pathways. Taken together, our data revealed that transfection of sh-MARCH8 into the MKN-45 and AGS gastric cancer cell lines inhibited their growth, and this approach may be useful as a novel strategy for gastric cancer therapy.

Strengthening Gastric Cancer Therapy by Trastuzumab-Conjugated Nanoparticles with Simultaneous Encapsulation of Anti-MiR-21 and 5-Fluorouridine.

BACKGROUND/AIMS: MicroRNA-21 is an oncogenic miR (oncomiR) frequently elevated in gastric cancer (GC). Overexpression of miR-21 decreases the sensitivity of GC cells to 5-fluorouridine (5-Fu) and trastuzumab, a humanized monoclonal antibody targeting human epidermal growth factor receptor 2 (HER2). Receptor-mediated endocytosis plays a crucial role in the delivery of biotherapeutics including anti-miRNA oligonucleotides (AMOs). This study is a continuation of earlier findings involving poly(ε-caprolactone) (PCL)-poly (ethylene glycol) (PEG) nanoparticles (PEG-PCL NPs), which were coated with trastuzumab to target GC with HER2 receptor over-expression using anti-miRNA-21 (AMO-21) and 5-Fu. METHODS: HER-PEG-PCL NPs were prepared by one-step carbodiimide coupling using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDAc) and Sulfo-NHS in aqueous phase. Covalent coupling of amino groups at the surface of PEG-PCL with the carboxyl groups of trastuzumab was analyzed by X-ray photoelectron spectroscopy (XPS). AMO-21/5-Fu NPs were formulated by a double-emulsion solvent evaporation technique. The cell line specificity, cellular uptake and AMO-21 delivery were investigated through the rhodamine-B-labeled 6-carboxyfluorescein (FAM)-AMO-21-PEG-PCL NPs coated with or without the antibody in both Her2-positive (NUGC4) and negative GC cells (SGC7901) visualized by fluorescence microscopy. The cytotoxicity of the HER-PEG-PCL NPs encapsulating AMO-21 was evaluated by MTT and apoptosis. Real-time reverse-transcription polymerase chain reaction (RT-PCR) was used to examine miR-21 and phosphatase and tensin homolog (PTEN) and Sprouty2 expression in GC cell lines. The antitumor effects of AMO-21/5-Fu NPs were compared with other groups in xenograft gastric cancer mice. RESULTS: The antibody conjugates significantly enhanced the cellular uptake of NPs. The AMO-21/5-Fu NPs effectively suppressed the target miRNA expression in GC cells, which further up-regulated PTEN and Sprouty2. As a result, the sensitivity of HER2-expressing gastric cancer to trastuzumab and 5-Fu were enhanced both in vitro and in vivo. The approach enhanced the targeting by trastuzumab as well as antibody-dependent cellular cytotoxicity (ADCC) of immune effector cells Conclusions: Taken together, the results provide insight into the biological and clinical potential of targeted AMO-21 and 5-Fu co-delivery using modified trastuzumab for GC treatment.

iTRAQ-based quantitative proteomic analysis of longissimus muscle from growing pigs with dietary supplementation of non-starch polysaccharide enzymes.

Non-starch polysaccharide enzymes (NSPEs) have long been used in the feed production of monogastric animals to degrade non-starch polysaccharide to oligosaccharides and promote growth performance. However, few studies have been conducted on the effect of such enzymes on skeletal muscle in monogastric animals. To elucidate the mechanism of the effect of NSPEs on skeletal muscle, an isobaric tag for relative and absolute quantification (iTRAQ) for differential proteomic quantitation was applied to investigate alterations in the proteome in the longissimus muscle (LM) of growing pigs after a 50-d period of supplementation with 0.6% NSPEs in the diet. A total of 51 proteins were found to be differentially expressed in the LM between a control group and the NSPE group. Functional analysis of the differentially expressed protein species showed an increased abundance of proteins related to energy production, protein synthesis, muscular differentiation, immunity, oxidation resistance and detoxification, and a decreased abundance of proteins related to inflammation in the LM of the pigs fed NSPEs. These findings have important implications for understanding the mechanisms whereby dietary supplementation with NSPEs enzymes can promote growth performance and improve muscular metabolism in growing pigs.

A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image.

A modified possibilistic fuzzy c-means clustering algorithm is presented for fuzzy segmentation of magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities and noise. By introducing a novel adaptive method to compute the weights of local spatial in the objective function, the new adaptive fuzzy clustering algorithm is capable of utilizing local contextual information to impose local spatial continuity, thus allowing the suppression of noise and helping to resolve classification ambiguity. To estimate the intensity inhomogeneity, the global intensity is introduced into the coherent local intensity clustering algorithm and takes the local and global intensity information into account. The segmentation target therefore is driven by two forces to smooth the derived optimal bias field and improve the accuracy of the segmentation task. The proposed method has been successfully applied to 3 T, 7 T, synthetic and real MR images with desirable results. Comparisons with other approaches demonstrate the superior performance of the proposed algorithm. Moreover, the proposed algorithm is robust to initialization, thereby allowing fully automatic applications.