Image retrieval based on colour and improved NMI texture features

This paper proposes an improved method for extracting NMI features. This method uses Particle Swarm Optimization in advance to optimize the two-dimensional maximum class-to-class variance (2OTSU) in advance. Afterwards, the optimized 2OUSU is introduced into the Pulse Coupled Neural Network (PCNN) to automatically obtain the number of iterations of the loop. We use an improved PCNN method to extract the NMI features of the image. For the problem of low accuracy of single feature, this paper proposes a new method of multi-feature fusion based on image retrieval. It uses HSV colour features and texture features, where, the texture feature extraction methods include: Grey Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) and Improved PCNN. The experimental results show that: on the Corel-1k dataset, compared with similar algorithms, the retrieval accuracy of this method is improved by 13.6%; On the AT&T dataset, the retrieval accuracy is improved by 13.4% compared with the similar algorithm; on the FD-XJ dataset, the retrieval accuracy is improved by 17.7% compared with the similar algorithm. Therefore, the proposed algorithm has better retrieval performance and robustness compared with the existing image retrieval algorithms based on multi-feature fusion

Effects of transcranial combined with peripheral repetitive magnetic stimulation on limb spasticity and resting-state brain activity in stroke patients

Background and objectiveTranscranial magnetic stimulation and peripheral repetitive magnetic stimulation (rPMS), as non-invasive neuromodulation techniques, can promote functional recovery in patients with post-stroke spasticity (PSS), but the effects of transcranial magnetic stimulation combined with peripheral magnetic stimulation on PSS remain largely unknown. Therefore, we examined the effects of low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) combined with rPMS on PSS patients and its potential neural correlates to behavioral improvements.MethodsForty-nine PSS patients were divided randomly into three groups: a combined group (n = 20), a LF-rTMS group (n = 15), and a control group (n = 14). The combined group received LF-rTMS and rPMS treatment, the rTMS group received LF-rTMS treatment, and the control group received only routine rehabilitation. All patients underwent Ashworth Spasm Scale (MAS), upper extremity Fugl-Meyer (FMA-UE), and modified Barthel Index (MBI) assessments before and after intervention. In addition, resting-state functional magnetic resonance imaging data were collected pre- and post-treatment to observe changes in the amplitude of low-frequency fluctuation (ALFF).ResultsThe MAS score was decreased, FMA-UE score and MBI scores were increased in the three groups after therapy than before therapy (all P < 0.05). In particular, the combined group showed significant effect on improved motor function and relieved spasticity in PSS (P < 0.01). Moreover, the combined treatment increased ALFF values mainly in the right supplementary motor area, right middle frontal gyrus, and right cerebellum, while reduced ALFF values mainly in the right post-central gyrus compared with pre-treatment. Compared with the LF-rTMS and control groups, the combined treatment increased ALFF values in the right cerebellum and reduced ALFF values mainly in the frontoparietal cortex. Improvements in the MAS score were positively correlated with the change in ALFF values in the right cerebellum (r = 0.698, P = 0.001) and the right supplementary motor area (r = 0.700, P = 0.001) after combined treatment.ConclusionTranscranial combined with peripheral repetitive magnetic stimulation could improve spastic state and motor function in PSS patients, and this effect may be associated with altered cerebellar and frontoparietal cortical activity.Clinical trial registrationhttp://www.chictr.org.cn/index.aspx, identifier ChiCTR1800019452

Case Report: A long-term survival case of diffuse large B-cell lymphoma with left ventricular infiltration and spinal cord compression

BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma and may occur with lymph node and/or extranodal involvement. However, DLBCL with intracardiac mass is exceedingly rare. In the reported literature, the intracardiac infiltration of DLBCL mostly involves the right ventricle. Lymphoma that invades the heart has an aggressive nature, with symptoms that are easily ignored initially and can lead to multiple complications in severe cases, resulting in a poor prognosis. Early screening and diagnosis may significantly improve the survival rate. Early diagnosis may significantly improve outcomes.Case summaryWe presented a 68-year-old woman with back pain. PET/CT suggested increased FDG metabolism in the left ventricle, right adrenal gland, right erector spinae intramuscularis, multiple bones and multiple lymph nodes. Contrast-enhanced ultrasound showed a left ventricular apical mass with ventricular septum thickening. Cardiac MRI suggested a 1.6*1.1*2.1 cm mass in the apical-central portion of the left ventricle. Biopsy of the right neck mass confirmed the pathologic diagnosis of diffuse large B-cell lymphoma. However, before the pathologic diagnosis was confirmed, the patient was paralyzed due to spinal cord compression caused by the progression of bone metastases. Subsequently, pathology confirmed the diagnosis of diffuse large B-cell lymphoma, and rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) was treated immediately as first-line therapy. In addition, glucocorticoids and mannitol dehydration were administered to relieve the symptoms of spinal cord compression. After 8 cycles of R-CHOP, the tumor at all sites had almost complete regression. The patient was able to walk normally and had no tumor-related symptoms.ConclusionsWe present a case of DLBCL with a very high tumor load that involved multiple organs, including the left ventricle, but exhibited no cardiac-related symptoms. The combination of various imaging modalities is valuable for the diagnosis of cardiac infiltration. The mass in the left ventricle almost completely regressed after R-CHOP treatment, and no recurrence has occurred in the 5 years of follow-up so far

miR-221 Mediates Chemoresistance of Esophageal Adenocarcinoma by Direct Targeting of DKK2 Expression

Background:Chemoresistance is a main obstacle to effective esophageal cancer (EC) therapy. We hypothesize that altered expression of microRNAs (miRNAs) play a role in EC cancer progression and resistance to 5-fluorouracil (5-FU) based chemotherapeutic strategies.Methods:Four pairs of esophageal adenocarcinoma (EAC) cell lines and corresponding 5-FU resistant variants were established. The expression levels of miRNAs previously shown to be involved in the general regulation of stem cell pathways were analyzed by qRT-PCR. The effects of selected miRNAs on proliferation, apoptosis, and chemosensitivity were evaluated both in vitro and in vivo. We identified a particular miRNA and analyzed its putative target genes in 14 pairs of human EC tumor specimens with surrounding normal tissue by qRT-PCR as well as Wnt pathway associated genes by immunohistochemistry in another 45 EAC tumor samples.Results:MiR-221 was overexpressed in 5-FU resistant EC cell lines as well as in human EAC tissue. DKK2 was identified as a target gene for miR-221. Knockdown of miR-221 in 5-FU resistant cells resulted in reduced cell proliferation, increased apoptosis, restored chemosensitivity, and led to inactivation of the Wnt/-catenin pathway mediated by alteration in DKK2 expression. Moreover, miR-221 reduction resulted in alteration of EMT-associated genes such as E-cadherin and vimentin as well as significantly slower xenograft tumor growth in nude mice. RT2 profiler analysis identified a substantial dysregulation of 4 Wnt/-catenin signaling and chemoresistance target genes as a result of miR-221 modulation: CDH1, CD44, MYC, and ABCG2.Conclusion:MiR-221 controls 5-FU resistance of EC partly via modulation of Wnt/-catenin-EMT pathways by direct targeting of DKK2 expression. MiR-221 may serve as a prognostic marker and therapeutic target for patients with 5-FU resistant EAC

Twenty Novel Disease Group-Specific and 12 New Shared Macrophage Pathways in Eight Groups of 34 Diseases Including 24 Inflammatory Organ Diseases and 10 Types of Tumors.

The mechanisms underlying pathophysiological regulation of tissue macrophage (Mφ) subsets remain poorly understood. From the expression of 207 Mφ genes comprising 31 markers for 10 subsets, 45 transcription factors (TFs), 56 immunometabolism enzymes, 23 trained immunity (innate immune memory) enzymes, and 52 other genes in microarray data, we made the following findings. (1) When 34 inflammation diseases and tumor types were grouped into eight categories, there was differential expression of the 31 Mφ markers and 45 Mφ TFs, highlighted by 12 shared and 20 group-specific disease pathways. (2) Mφ in lung, liver, spleen, and intestine (LLSI-Mφ) express higher M1 Mφ markers than lean adipose tissue Mφ (ATMφ) physiologically. (3) Pro-adipogenic TFs C/EBPα and PPARγ and proinflammatory adipokine leptin upregulate the expression of M1 Mφ markers. (4) Among 10 immune checkpoint receptors (ICRs), LLSI-Mφ and bone marrow (BM) Mφ express higher levels of CD274 (PDL-1) than ATMφ, presumably to counteract the M1 dominant status via its reverse signaling behavior. (5) Among 24 intercellular communication exosome mediators, LLSI- and BM- Mφ prefer to use RAB27A and STX3 than RAB31 and YKT6, suggesting new inflammatory exosome mediators for propagating inflammation. (6) Mφ in peritoneal tissue and LLSI-Mφ upregulate higher levels of immunometabolism enzymes than does ATMφ. (7) Mφ from peritoneum and LLSI-Mφ upregulate more trained immunity enzyme genes than does ATMφ. Our results suggest that multiple new mechanisms including the cell surface, intracellular immunometabolism, trained immunity, and TFs may be responsible for disease group-specific and shared pathways. Our findings have provided novel insights on the pathophysiological regulation of tissue Mφ, the disease group-specific and shared pathways of Mφ, and novel therapeutic targets for cancers and inflammations

A List-Ranking Framework Based on Linear and Non-Linear Fusion for Recommendation from Implicit Feedback

Although most list-ranking frameworks are based on multilayer perceptrons (MLP), they still face limitations within the method itself in the field of recommender systems in two respects: (1) MLP suffer from overfitting when dealing with sparse vectors. At the same time, the model itself tends to learn in-depth features of user–item interaction behavior but ignores some low-rank and shallow information present in the matrix. (2) Existing ranking methods cannot effectively deal with the problem of ranking between items with the same rating value and the problem of inconsistent independence in reality. We propose a list ranking framework based on linear and non-linear fusion for recommendation from implicit feedback, named RBLF. First, the model uses dense vectors to represent users and items through one-hot encoding and embedding. Second, to jointly learn shallow and deep user–item interaction, we use the interaction grabbing layer to capture the user–item interaction behavior through dense vectors of users and items. Finally, RBLF uses the Bayesian collaborative ranking to better fit the characteristics of implicit feedback. Eventually, the experiments show that the performance of RBLF obtains a significant improvement