Abnormal Nodes Research Articles

Characteristics of her2-positive breast cancer, and the current use of anti-her2 therapy and its related factors

ABSTRACT Objective: To describe the characteristics of patients with HER2-positive breast cancer and to identify the proportion of patients using anti-HER2 therapy, and treatment-making related factors. Methods: An analytical cross-sectional study was conducted on 79 patients with BC and HER2-positive diagnosed by immunohistochemistry (IHC) or with FISH at the Oncology Department of Hue University of Medicine and Pharmacy Hospital and Oncology Center of Hue Central Hospital from 1/2021 to 12/2022. Clinical and pathological features, type of drug, number of cycles using anti-Her2 therapy were recorded using medical documents. The decision-making related factors were recorded by questionnaire interviewing patients and relatives. Exclusion criteria included recurrent or previously treated tumors; having contraindications with anti-HER2 therapy; not being willing to participate in the study. SPSS 22.0 was used for the analysis. Results: Mean age was 54.14 ± 11.03. Patients with right-sided BC accounted for 53.1%. 60.8% of tumors were located in the upper right quadrant of the breast. Patient’s self-report of lumps was the most common cause of hospitalization (77.2%). By ultrasound, 60.2% of participants had a tumor size of 2 - 5cm. Abnormal lymph nodes were identified in 40.8% of patients. Histopathologically, invasive ductal carcinoma was found in the majority of tumors (75.9%). Stage II was predominant with 59.5% and 7.6% of patients with stage IV. The rate of treatment with Trastuzumab in our study was 27.8%. The main reason that patients refused anti-HER-2 therapy was financial problems (96.5%). The awareness of anti-HER2 therapy among patients and their relatives was significantly associated with the treatment decision (p = 0.007). Conclusion: Regarding the positive-HER2 BC patients, invasive ductal carcinoma was the major histopathological finding. More than half of the patients were classified as stage II of the disease. The rate of patients undergoing antiHER2 therapy was 27.8%. Financial problems were found to be the main reason for refusal of treatment. Awareness of anti-HER2 therapy is significantly associated with the patient’s decision on treatment.

Current axillary management of patients with early breast cancer and low-volume nodal disease undergoing primary surgery: results of a United Kingdom national practice survey

PurposeUK NICE guidelines recommend axillary node clearance (ANC) should be performed in all patients with biopsy-proven node-positive breast cancer having primary surgery. There is, however, increasing evidence such extensive surgery may not always be necessary. Targeted axillary dissection (TAD) may be an effective alternative in patients with low-volume nodal disease who are clinically node negative (cN0) but have abnormal nodes detected radiologically. This survey aimed to explore current management of this group to inform feasibility of a future trial.MethodsAn online survey was developed to explore current UK management of patients with low-volume axillary disease and attitudes to a future trial. The survey was distributed via breast surgery professional associations and social media from September to November 2022. One survey was completed per unit and simple descriptive statistics used to summarise the results.Results51 UK breast units completed the survey of whom 78.5% (n = 40) reported performing ANC for all patients with biopsy-proven axillary nodal disease having primary surgery. Only 15.7% of units currently performed TAD either routinely (n = 6, 11.8%) or selectively (n = 2, 3.9%). There was significant uncertainty (83.7%, n = 36/43) about the optimal surgical management of these patients. Two-thirds (n = 27/42) of units felt an RCT comparing TAD and ANC would be feasible.ConclusionsANC remains standard of care for patients with low-volume node-positive breast cancer having primary surgery in the UK, but considerable uncertainty exists regarding optimal management of this group. This survey suggests an RCT comparing the outcomes of TAD and ANC may be feasible.

Use of ultrasound and MRI to stage the axilla for breast cancer before and after neoadjuvant chemotherapy prior to targeted sentinel lymphadenectomy

PurposePrior data from this Center demonstrated that for patients who had biopsy-proven axillary metastases, were ycN0 after neoadjuvant chemotherapy (NAC), and had a wire-directed (targeted) sentinel lymphadenectomy (WD-SLND), 60% were node negative. The hypothesis of this study was that results of axillary imaging either before or after NAC would be predictive of final pathologic status after WD-SLND.MethodsFor patients treated with NAC between 2015 and 2023, ultrasound and MRI images of the axilla were retrospectively reviewed by radiologists specializing in breast imaging, who were blinded to the surgical and pathology results.ResultsOf 113 patients who fit the clinical criteria, 66 (58%) were ypN0 at WD-SLND and 34 (30%) had a pathologic complete response to NAC. There was no correlation between the number of abnormal lymph nodes on pre-NAC ultrasound or MRI imaging and the final pathologic status of the lymph nodes. The positive predictive value (PPV) of abnormal post-NAC axillary imaging was 48% for ultrasound and 53% for MRI. The negative predictive value (NPV) for normal post-NAC axillary imaging was 67% for ultrasound and 68% for MRI.ConclusionThe results of axillary imaging were not adequate to identify lymph nodes after NAC that were persistently pathologically node positive or those which had become pathologically node negative.

An Adaptive Trust Evaluation Model for Detecting Abnormal Nodes in Underwater Acoustic Sensor Networks.

Underwater acoustic sensor networks have a wide range of applications in both civil and military fields, but the complex and changing underwater environment makes them vulnerable to multiple security threats. Trust mechanisms are effective ways to enhance network security and reliability. In order to improve the accuracy of trust evaluation and the detection rate of abnormal nodes, this paper proposes an adaptive trust evaluation model based on fuzzy logic. This model adopts a variable weight fuzzy comprehensive evaluation algorithm to dynamically adjust the weights of three direct trust indicators to ensure the accuracy of direct trust evaluation. Then, it uses fuzzy closeness to eliminate unreliable recommendation trust and adjusts the weight of recommendation trust through deviation to improve the accuracy of indirect trust. The simulation results show that the model can effectively improve the accuracy of trust evaluation and the detection rate of abnormal nodes. Especially when the link quality is unstable, the success rate of detecting abnormal nodes in this model is improved by more than 10% compared with the existing trust model.

Targeted axillary dissection after neoadjuvant chemotherapy for highly selective patients with initial cN1 breast cancer: A single-center prospective trial.

Sentinel lymph node (SLN) biopsy is gradually accepted as the standard of care in breast cancer patients with down-staged axillary disease after neoadjuvant chemotherapy (NAC). However, it is still difficult to precisely define pre-NAC clinical node-positive (cN1) and post-NAC clinical node-negative (ycN0). This prospective single-center trial was designed to evaluate the feasibility and accuracy of standard targeted axillary dissection (TAD) after NAC in highly selective pre-NAC cN1 patients (not considering ultrasound-based axillary ycN staging). This prospective trial included patients with initial pre-NAC cT1-3N1M0 invasive breast cancer but with a rigorous definition of cN1 from the Affiliated Cancer Hospital of Zhengzhou University. When NAC was effective (including complete and partial responses) and preoperative axillary palpation was negative, preoperative ultrasound-based axillary staging was not considered, and all patients underwent TAD followed by axillary lymph node (LN) dissection. The detection rate (DR) and false-negative rate (FNR) of TAD were calculated. A total of 82 patients were included, and 77 of them were eligible for data analysis. The DR for TAD was 94.8% (73/77). There were 26 patients with one abnormal LN at the time of diagnosis based on ultrasound, 45 patients with two, and 2 patients with three. One patient had one TAD LN, four patients had two TAD LNs, and 68 patients had three or more TAD LNs. Preoperative axillary palpation yielded negative results for all 73 patients who successfully underwent TAD. Preoperative ultrasound-based ycN0 and ycN+ conditions were detected for 52 and 21 cases, respectively. The FNR was 7.4% (2/27) for standard TAD (≥3 SLNs), which was lower than that of all successful TAD (≥1 SLN; 10.0%, 3/30). In rigorously defined pre-NAC cN1 breast cancer patients, standard TAD is feasible for those with negative axillary palpation after NAC, and FNR is also less than 10%. chictr.org.cn , ChiCTR2100049093.

P16, p53 and EGFR expression in head and neck squamous cell carcinoma and their correlation with clinicopathological parameters.

Oral squamous cell carcinoma is a major cause of death throughout the developed world. Human papillomavirus (HPV) type 16 has also been suggested to play a role in etiology of head and neck squamous cell carcinoma (HNSCC). p16 expression is now being used as a surrogate marker of HPV infection in squamous cell carcinoma. Dysfunction in the p53 tumor suppressor gene is implicated in many cancers, including head and neck cancer. Overexpression or mutation of EGFR is found in 80%-100% of the patients with HNSCC, and is associated with poor prognosis and decreased survival. In this cross-sectional observation study, total of 100 cases of HNSCC were taken. p16, p53, and EGFR expression was determined by immunohistochemical staining and correlated with clinicopathological parameters. p16 expression was also correlated with expression of p53 and EGFR. The obtained results were analyzed and evaluated using Chi-square test, value of P < 0.05 was taken significant. p16, p53, and EGFR were positive in 60%, 44%, and 58% cases, respectively. A statistically significant association was observed between p16 with age, site of the tumor, abnormal sexual habits and lymph node involvement. Significant expression also seen between p53 with age and abnormal sexual habits and immunohistochemical expression of p16 with p53 and EGFR. Immunohistochemical expression of p16 can be used as a surrogate marker of HPV. Study of p16, p53, and EGFR expression may provide clinicians with more exact information in order to evaluate tumor aggressiveness and treatment modalities.

106 Characteristics of Cognitive Impairment in Moyamoya Disease

INTRODUCTION: Cognitive impairment in adult moyamoya disease (MMD) is thought to be the result of ischemic stroke; however, the presence and extent of cognitive decline in asymptomatic patients remain largely unknown. METHODS: After classification using T2-weighted fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), a total of 19 MMD patients with a history of cerebral infarction, 21 asymptomatic MMD patients, and 20 healthy controls matched for age, sex, and years of education were prospectively included in this study. A detailed neuropsychological evaluation of two moyamoya subgroups and normal controls was conducted. In addition, participants underwent arterial spin labeling and resting state fMRI sequences. RESULTS: Asymptomatic patients showed varying degrees of decline in intelligence (Raven’s Standard Progressive Matrices, P = 0.001), spatial imagination (mental rotation, P = 0.014), working memory (verbal working memory-backward digit span, P = 0.011), and computational ability (simple subtraction, P = 0.014; complex subtraction, P &lt; 0.001) compared with normal controls. MMD patients with cerebral infarction had more severe impairment in complex arithmetic (P = 0.027) and word short-term memory (P = 0.01) than those without symptoms. The asymptomatic MMD group also showed decreased CBF in the left anterior central and left inferior frontal gyri of the island fap with multiple node abnormalities in the brain network and reduced network connectivity. There was a significant association of these changes with cognitive decline in the MMD group. CONCLUSIONS: In asymptomatic MMD patients, a variety of cognitive impairments precedes the onset of clinical symptoms such as cerebral infarction, which may be a long-term complication of conservative treatment. Besides, disturbance of CBF and impaired brain network connections may be important causes of cognitive decline.

Internal mammary node abnormality in imaging studies and treatment outcomes in patients with breast cancer.

The clinical significance of mild internal mammary node (IMN) enlargement (Mild-IMN) is uncertain. This study aimed to evaluate the relationship between treatment outcomes and IMN status in patients with breast cancer who underwent postmastectomy radiation therapy between January 2010 and December 2018. Overall, 250 patients were categorized based on IMN status: Clinically normal IMN (Normal-IMN; n=172), Mild-IMN (n=39) and clinically metastatic IMN (cMet-IMN; n=39). None of the patients in the Normal- or Mild-IMN groups received IMN irradiation. In the cMet-IMN group, 25 patients underwent IMN irradiation with an IMN boost (10 Gy in 5 fractions), while 14 patients did not. The median follow-up time was 80.0 months (range, 7.2-147.6 months). The 7-year overall survival (OS), disease-free survival (DFS) and IMN recurrence-free survival (IRF) rates were 80.2, 73.0 and 93.4%, respectively. Multivariate analyses indicated that only cMet-IMN had a significant impact on OS [hazard ratio (HR), 1.66; 95% CI, 1.01-3.68; P=0.05] and DFS (HR, 1.91; 95% CI, 1.08-3.39; P=0.03), while cMet-IMN did not have a significant impact on IRF (HR, 1.66; 95% CI, 0.41-6.78; P=0.48). Additionally, receiving an IMN boost had no influence on OS (HR, 1.11; 95% CI, 0.37-2.34; P=0.84), DFS (HR, 1.28; 95% CI, 0.51-3.22; P=0.60) or IRF (HR, 1.94; 95% CI, 0.22-17.47; P=0.55). In conclusion, the impact of Mild-IMN on clinical outcomes was small. Although irradiation for cMet-IMN is important, the impact of the cMet-IMN boost with 10 Gy in 5 fractions on clinical outcomes may also be limited.

Use of axillary ultrasound to guide breast cancer management in the genomic assay era.

Chemotherapy is conventionally offered to non-stage IV breast cancer patients with metastatic nodes. However, the RxPONDER trial showed that chemotherapy can be omitted in selected patients with 1-3 metastatic nodes if the 21-gene assay recurrence score is ≤25. We aimed to investigate if axillary ultrasound can identify this group of patients with limited nodal burden so that they can undergo upfront surgery followed by gene assay testing, to potentially avoid chemotherapy. T1-3, node positive, hormone receptor-positive and HER2-negative breast cancer patients ≥50 years old with axillary lymph node dissection (ALND) were reviewed from 2 centres. Patients with neoadjuvant chemotherapy and bilateral cancers were excluded. Number of ultrasound-detected abnormal axillary nodes, demographic and histological parameters were correlated with the number of metastatic nodes found on ALND. 138 patients were included, 59 (42.8%) and 79 (57.2%) patients had 1-3 and >3 metastatic nodes on ALND respectively. On logistic regression and ROC analysis, the number of ultrasound-detected abnormal nodes was significant (p <0.001) for predicting limited nodal burden (ROC AUC = 0.7135). Probabilities of <4 metastatic nodes with ultrasound cut-offs of 5, 6 and 8 abnormal nodes were 0.057, 0.026 and 0.005 respectively, with 100% specificity. A cut-off of ≤5 ultrasound-detected abnormal nodes can distinguish between patients with limited versus high nodal burden, with high specificity. Hence, incorporating the number of abnormal ultrasound-detected nodes into clinical practice may prove useful in guiding between upfront surgery and gene assay testing or neoadjuvant chemotherapy in this group of patients.

Evaluation of traditional targeted axillary dissection eligibility criteria for node-positive breast cancer after neoadjuvant chemotherapy in a prospective multicenter registry

IntroductionTargeted axillary dissection (TAD) is performed after neoadjuvant systemic therapy (NST) to decrease the rate of non-therapeutic axillary dissection (ALND) for patients with node-positive breast cancer. In order to ensure the oncologic safety of TAD, eligibility criteria resulting in a low false negative rate (FNR) have been proposed. The purpose of this study was to evaluate the utility of the traditional criteria. MethodsData was collected from a prospective multicenter registry. In order to ascertain FNRs, pathologic findings in the sentinel lymph nodes (LN)s, malignant clipped LN, and axillary contents were determined. The FNRs within TAD eligibility criterion groups were compared. ResultsA total of 110 patients underwent TAD and ALND, and were therefore eligible for analysis. TAD retained a low FNR in advanced clinical T-N stage compared with earlier disease (T stage: 95% CI 0.00–11.93, p = 0.42; N stage: 95% CI 0.00–8.76, p = 0.31). Presentation with ≥4 abnormal LNs on axillary ultrasound did not predict a high TAD FNR (95% CI 0.00–5.37, p = 0.16). No significant differences were noted in TAD FNR when single was compared with dual tracer (blue dye vs dual tracer 95% CI 0.72–52.49, p = 0.13; radiotracer vs dual tracer 0.04–20.11, p = 0.51). Excision of the clipped LN and only one SLN was as accurate as excision of the clipped LN and ≥2 SLNs (95% CI 0.00–10.61, p = 0.38). ConclusionsTAD retained a low FNR among patients traditionally considered ineligible for this technique. However, excision of the clipped LN and at least one SLN remained essential to a low FNR.

A Framework for Detecting False Data Injection Attacks in Large-Scale Wireless Sensor Networks.

False data injection attacks (FDIAs) on sensor networks involve injecting deceptive or malicious data into the sensor readings that cause decision-makers to make incorrect decisions, leading to serious consequences. With the ever-increasing volume of data in large-scale sensor networks, detecting FDIAs in large-scale sensor networks becomes more challenging. In this paper, we propose a framework for the distributed detection of FDIAs in large-scale sensor networks. By extracting the spatiotemporal correlation information from sensor data, the large-scale sensors are categorized into multiple correlation groups. Within each correlation group, an autoregressive integrated moving average (ARIMA) is built to learn the temporal correlation of cross-correlation, and a consistency criterion is established to identify abnormal sensor nodes. The effectiveness of the proposed detection framework is validated based on a real dataset from the U.S. smart grid and simulated under both the simple FDIA and the stealthy FDIA strategies.

Anomaly attribute mining method for topological nodes of power system based on graph theory

Due to the large scale, high dimension and time series characteristics of power system data, and the normal samples far exceed the abnormal samples, the sample imbalance phenomenon occurs, and it is difficult to mine the abnormal attributes of nodes. Therefore, a method of mining abnormal attributes of topological nodes of power systems based on graph theory is developed. The logical relation between nodes is analyzed by graph theory, and directed graph and undirected graph are obtained. The topology structure of the power system is constructed, the noise in data is removed by the adaptive clustering algorithm, the weight of topological nodes is set, and the abnormal malicious attacks of topological nodes are discovered by the double threshold method. The experimental results show that the proposed method can accurately detect the abnormal topological nodes in the network, perform better in the energy consumption of the neighbor topological nodes, and greatly reduce the energy consumption of the neighbor topological nodes during mining.

Incidental Axillary Lymphadenopathy Found on Radiation Planning Computed Tomography

AimThe aim of this study was to evaluate the rate of axillary node positive disease in early breast cancer patients who had a suspicious axillary lymph node on radiation planning CT. Methods and MaterialsA retrospective review of the medical records of all breast cancer patients who were referred for axillary ultrasound from the radiation unit to the breast imaging unit at the Meirav Breast Center, Sheba Medical Center, during 2012-2022. Ethics approval was obtained. Only the records of patients who were referred due to an abnormal axillary lymph node seen on radiation planning-CT were further evaluated. ResultsDuring the study period, a total of 21 patients were referred to the breast imaging unit for evaluation of suspicious nodes seen on radiation planning CT. Of these, 3 cases were excluded. A total of 15 out of the 18 (83%) patients included had an abnormal lymph node in the ultrasound and an ultrasound guided biopsy was recommended (BI-RADS 4). Of these, 3 (out of 15, 20%) had a positive biopsy for tumor cells from axillary lymph node. Two were cases after primary systemic therapy without complete pathologic response. Thickening of the lymph node cortex and complete loss of the central fatty hilum were associated with pathologic lymph node. ConclusionThe sonar had limited ability to differentiate reactive nodes from involved nodes. The presence of lymph nodes with loss of cortical-hilum differentiation on ultrasound together with clinical features are parameters that can help guiding the need of further biopsy. Histopathology evaluation is important to make the diagnosis of residual axillary disease. Future studies and guidelines are needed to improve the diagnostic abilities and reduce the number of patients who are undergoing biopsy for non-involved nodes.

Preoperative factors that predict pathologic nodal involvement in early-stage HER2+ breast cancer: selecting cT1cN0 patients for treatment with neoadjuvant chemotherapy versus upfront surgery.

The goal of this study was to identify the preoperative predictors of pathologic nodal metastases (pN+) in cT1cN0 HER2+ breast cancer undergoing upfront surgery. We retrospectively reviewed data from women with cT1-T2N0 HER2+ breast cancer treated with neoadjuvant therapy (NAC) or upfront surgery at our institution between 2012 and 2023. Factors associated with management strategy were evaluated, and in those undergoing upfront surgery, univariate analyses were performed to identify the clinicopathologic factors associated with nodal metastases. Overall, 255 women with cT1-T2N0 HER2+ breast cancer met inclusion criteria, including 170 (68.6%) upfront surgery patients and 85 (31.4%) who underwent NAC. The median age at diagnosis was 59years (range, 27-90years). Younger age, larger clinical tumor size, high-grade disease, ER-PR-HER2+ subtype, and year of diagnosis after 2019 were significantly associated with receipt of NAC (p < 0.05). In those undergoing upfront surgery, 25.3% were pN+ , including 32.5% of cT1cN0 tumors. Factors associated with nodal involvement included age under 50, larger clinical tumor size, lymphovascular invasion (LVI), multifocality/multicentricity, and abnormal lymph nodes on axillary ultrasound (p < 0.05). In subset analysis of cT1cN0 HER2+ cases, LVI remained the strongest predictor of pN + disease (73.3% vs. 22.6%, p < 0.001). Patients with cT1cN0 HER2+ breast cancer under 50years had a 47.1% likelihood of pN+ disease. Patients with cT1cN0 breast cancer have a 32.5% likelihood of nodal metastases, with higher incidence with younger age, LVI, multifocality/multicentricity, and abnormal axillary ultrasound. The presence of these factors may identify the patients who would benefit from treatment with neoadjuvant chemotherapy.

Gold nanoshells for prostate cancer treatment: evidence for deposition in abdominal organs.

Gold-silica nanoshell therapy [AuroShells with subsequent focal laser therapy (AuroLase)] is an emerging targeted treatment modality for prostate cancer. We reviewed pre- and post-treatment unenhanced CT imaging to assess for retained gold-silica nanoshells in the abdomen and pelvis. This single-institution retrospective study identified patients in the AuroLase pilot who underwent pre- and post-treatment unenhanced abdominopelvic CT. The attenuation, before and after gold-silica nanoshell administration, of the liver, spleen, pancreas, kidneys, prostate, blood pool, paraspinal musculature, and abnormal lymph nodes were manually measured by two readers. After inter-reader agreement was calculated using intraclass correlation (ICC), a permutation test was used to assess pre- and post-therapy attenuation differences. Four patients met the inclusion criteria. Mean age was 72.3 ± 5.9years. Median time interval between pre-treatment CT and treatment, and between treatment and post-treatment CT, was 232days and 236.5days, respectively. The two readers' attenuation measurements had very high agreement (ICC = 0.99, p < 0.001). The highest differences in organ attenuation between pre- and post-therapy scans were seen in all four patients in the liver and spleen (liver increased by an average of 28.9 HU, p = 0.010; spleen increased by an average of 63.7 HU, p = 0.012). A single measured lymph node increased by an average of 58.9 HU. In the remainder of the measured sites, the change in attenuation from pre- to post-therapy scans ranged from -0.1 to 3.8 HU (p > 0.05). Increased attenuation of liver and spleen at CT can be an expected finding in patients who have received gold-silica nanoshell therapy.

Development and Validation of Deep Learning-Based Automated Detection of Cervical Lymphadenopathy in Patients with Lymphoma for Treatment Response Assessment: A Bi-institutional Feasibility Study.

The purpose is to train and evaluate a deep learning (DL) model for the accurate detection and segmentation of abnormal cervical lymph nodes (LN) on head and neck contrast-enhanced CT scans in patients diagnosed with lymphoma and evaluate the clinical utility of the DL model in response assessment. This retrospective study included patients who underwent CT for abnormal cervical LN and lymphoma assessment between January 2021 and July 2022. Patients were grouped into the development (n = 76), internal test 1 (n = 27), internal test 2 (n = 87), and external test (n = 26) cohorts. A 3D SegResNet model was used to train the CT images. The volume change rates of cervical LN across longitudinal CT scans were compared among patients with different treatment outcomes (stable, response, and progression). Dice similarity coefficient (DSC) and the Bland-Altman plot were used to assess the model's segmentation performance and reliability, respectively. No significant differences in baseline clinical characteristics were found across cohorts (age, P = 0.55; sex, P = 0.13; diagnoses, P = 0.06). The mean DSC was 0.39 ± 0.2 with a precision and recall of 60.9% and 57.0%, respectively. Most LN volumes were within the limits of agreement on the Bland-Altman plot. The volume change rates among the three groups differed significantly (progression (n = 74), 342.2%; response (n = 8), - 79.2%; stable (n = 5), - 8.1%; all P < 0.01). Our proposed DL segmentation model showed modest performance in quantifying the cervical LN burden on CT in patients with lymphoma. Longitudinal changes in cervical LN volume, as predicted by the DL model, were useful for treatment response assessment.

SRC family kinase inhibition rescues molecular and behavioral phenotypes, but not protein interaction network dynamics, in a mouse model of Fragile X syndrome.

Glutamatergic synapses encode information from extracellular inputs using dynamic protein interaction networks (PINs) that undergo widespread reorganization following synaptic activity, allowing cells to distinguish between signaling inputs and generate coordinated cellular responses. Here, we investigate how Fragile X Messenger Ribonucleoprotein (FMRP) deficiency disrupts signal transduction through a glutamatergic synapse PIN downstream of NMDA receptor or metabotropic glutamate receptor (mGluR) stimulation. In cultured cortical neurons or acute cortical slices from P7, P17 and P60 FMR1-/y mice, the unstimulated protein interaction network state resembled that of wildtype littermates stimulated with mGluR agonists, demonstrating resting state pre-activation of mGluR signaling networks. In contrast, interactions downstream of NMDAR stimulation were similar to WT. We identified the Src family kinase (SFK) Fyn as a network hub, because many interactions involving Fyn were pre-activated in FMR1-/y animals. We tested whether targeting SFKs in FMR1-/y mice could modify disease phenotypes, and found that Saracatinib (SCB), an SFK inhibitor, normalized elevated basal protein synthesis, novel object recognition memory and social behavior in FMR1-/y mice. However, SCB treatment did not normalize the PIN to a wild-type-like state in vitro or in vivo, but rather induced extensive changes to protein complexes containing Shank3, NMDARs and Fyn. We conclude that targeting abnormal nodes of a PIN can identify potential disease-modifying drugs, but behavioral rescue does not correlate with PIN normalization.

Leptin Receptor Deficiency Impairs Lymph Node Development and Adaptive Immune Response.

Activation and clonal expansion of the Ag-specific adaptive immune response in the draining lymph node is essential to clearing influenza A virus infections. Activation sufficient for virus clearance is dependent on the lymph node's architectural organization that is maintained by stromal cells, chiefly fibroblastic reticular cells. During an analysis of influenza A virus clearance in leptin receptor knockout (DB/DB) mice, we observed that the DB/DB mice have markedly reduced numbers of lymph node fibroblastic reticular cells at the steady state. The reduction in lymph node fibroblastic reticular cells resulted in abnormal lymph node organization and diminished numbers of adaptive immune cells in the lymph nodes under homeostatic conditions. As a consequence, the DB/DB mice were impaired in their ability to generate an effective influenza-specific adaptive immune response, which prevented virus clearance. Using leptin receptor mutant mice with point mutations at distinct signaling sites in the leptin receptor, we were able to link the leptin receptor's signaling domain tyrosine 985, which does not contribute to obesity, to lymph node fibroblastic reticular cell development and function. These results demonstrate a novel role for leptin receptor signaling in regulating lymph node development in a manner that is crucial to the generation of Ag-specific adaptive immune responses.

Graph autoencoder with mirror temporal convolutional networks for traffic anomaly detection

Traffic time series anomaly detection has been intensively studied for years because of its potential applications in intelligent transportation. However, classical traffic anomaly detection methods often overlook the evolving dynamic associations between road network nodes, which leads to challenges in capturing the long-term temporal correlations, spatial characteristics, and abnormal node behaviors in datasets with high periodicity and trends, such as morning peak travel periods. In this paper, we propose a mirror temporal graph autoencoder (MTGAE) framework to explore anomalies and capture unseen nodes and the spatiotemporal correlation between nodes in the traffic network. Specifically, we propose the mirror temporal convolutional module to enhance feature extraction capabilities and capture hidden node-to-node features in the traffic network. Morever, we propose the graph convolutional gate recurrent unit cell (GCGRU CELL) module. This module uses Gaussian kernel functions to map data into a high-dimensional space, and enables the identification of anomalous information and potential anomalies within the complex interdependencies of the traffic network, based on prior knowledge and input data. We compared our work with several other advanced deep-learning anomaly detection models. Experimental results on the NYC dataset illustrate that our model works best compared to other models for traffic anomaly detection.

CaCo: Attributed Network Anomaly Detection via Canonical Correlation Analysis

Capturing the complex interaction between the node attribute and the network structure is important for attributed network embedding and anomaly detection. However, there are few methods to explicitly model the correlation between these two views of the node attribute and the network structure. In this paper, we propose an attributed network anomaly detection (CaCo) method based on canonical correlation analysis, which assumes that there should be a strong correlation between the attribute and structure features of normal nodes, and a weak correlation ones between those abnormal nodes, in the attributed networks. Consequently, a joint learning mechanism is designed in CaCo to explicitly measure the correlation between two views in the latent space. Specifically, the backbone of a weight-sharing graph convolutional network is employed to encode the node feature from two views of attribute and structure in the latent space, respectively. Then, a Kullback-Leibler (KL) divergence regularization is used to align the distributions of the two views. Finally, the parameters of CaCo are optimized by maximizing the correlation between attribute and structure features of normal nodes in the training phase, and anomalies can be detected by measuring the correlation between two views in the testing phase. Extensive experiments on six real-world datasets demonstrate the effectiveness of the proposed method compared to the state-of-art techniques.