Miracle-dz/UniFAR-FTUs huggingface dataset:
Global transcriptional analysis identifies a novel role for SOX4 in tumor-induced angiogenesis

The expression of the transcription factor SOX4 is increased in many human cancers, however, the pro-oncogenic capacity of SOX4 can vary greatly depending on the type of tumor. Both the contextual nature and the mechanisms underlying the pro-oncogenic SOX4 response remain unexplored. Here, we demonstrate that in mammary tumorigenesis, the SOX4 transcriptional network is dictated by the epigenome and is enriched for pro-angiogenic processes. We show that SOX4 directly regulates endothelin-1 (ET-1) expression and can thereby promote tumor-induced angiogenesis both in vitro and in vivo. Furthermore, in breast tumors, SOX4 expression correlates with blood vessel density and size, and predicts poor-prognosis in patients with breast cancer. Our data provide novel mechanistic insights into context-dependent SOX4 target gene selection, and uncover a novel pro-oncogenic role for this transcription factor in promoting tumor-induced angiogenesis. These findings establish a key role for SOX4 in promoting metastasis through exploiting diverse pro-tumorigenic pathways.
A Hybrid Particle Swarm Optimization and Differential Evolution Based Test Data Generation Algorithm for Data-Flow Coverage Using Neighbourhood Search Strategy

Meta-heuristic search techniques, mainly Genetic Algorithm (GA), have been widely applied for automated test data generation according to a structural test adequacy criterion . However, it remains a challenging task for more robust adequacy criterion such as data-flow coverage of a program. Now, focus is on the use of other highly-adaptive meta-heuristic search techniques such as Particle Swarm Optimization (PSO) and Differential Evolution (DE). In this paper, a hybrid (adaptive PSO and DE) algorithm is proposed to generate test data for data-flow dependencies of a program with a neighbourhood search strategy to improve the search capability of the hybrid algorithm. The fitness function is based on the concepts of dominance relations and branch distance. The measures considered are mean number of generations and mean percentage coverage. The performance of the hybrid algorithm is compared with that of DE, PSO, GA, and random search. Over several experiments on a set of benchmark programs, it is shown that the hybrid algorithm performed significantly better than DE, PSO, GA and random search in data-flow test data generation with respect to the measures collected.
Language-Eloquent White Matter Pathway Tractography and the Course of Language Function in Glioma Patients

Object: As various recent studies show, damage to white matter pathways leads to permanent functional deficits in a high percentage of patients. Particularly the subcortical language network is complex, and its visualization has a tremendous relevance for neurosurgeons. This pilot study aims to correlate language-eloquent white matter pathways with the course of language function after the resection of left-sided perisylvian gliomas. Methods: We included 10 patients who underwent resection of highly language-eloquent high- (9 pts) and low-grade gliomas (1 pts). We performed navigated repetitive transcranial magnetic stimulation (nrTMS)-based tractography via diffusion tensor imaging fiber trackings (DTI FT) preoperatively (PRE-1), postoperatively (POST-1), and at long-term follow up or tumor recurrence (PRE-2). We separately tracked the inferior fronto-occipital fascicle (IFOF), the frontal aslant tract (FAT), and the superior longitudinal (SLF), and arcuate fascicle (AF), and correlated the amount of visualized fibers to the patients' language function at each date. Results: The changes of nrTMS-based DTI FTs of single white matter pathways correlated with the according status of language function for any of the pathways in 80% of patients and in 19 of 30 (63%) single pathway comparisons between PRE-1 and POST-1. Between POST-1 and PRE-2 the nrTMS-based DTI FTs correlated with the status of language function for any of the pathways in all patients and in 24 of 30 (80%) single pathway comparisons. Single FT results correlated with the according status of language function at POST-1 in 60, 70, and 60% of cases, and with the according status of language function at PRE-2 in 60, 90, and 90% of cases for the tracking of the IFOF, FAT, and SLF/AF, respectively. Conclusion: By the present results we were able to show that nrTMS-based DTI FT of the IFOF, FAT, and SLF/AF mainly correlates with the according status of language function preoperatively, postoperatively, and at long-term follow up after the resection of left-sided perisylvian gliomas.
Learning Saliency Maps for Adversarial Point-Cloud Generation

3D point-cloud recognition with deep neural network (DNN) has received remarkable progress on obtaining both highaccuracy recognition and robustness to random point missing (or dropping). However, the robustness of DNNs to maliciously-manipulated point missing is still unclear. In this paper, we show that point-missing can be a critical security concern by proposing a malicious point-dropping method to generate adversarial point clouds to fool DNNs. Our method is based on learning a saliency map for a whole point cloud, which assigns each point a score reflecting its contribution to the model-recognition loss, i.e., the difference between the losses with and without the specific point respectively. The saliency map is learnt by approximating the nondifferentiable point-dropping process with a differentiable procedure of shifting points towards the cloud center. In this way, the loss difference, i.e., the saliency score for each point in the map, can be measured by the corresponding gradient of the loss w.r. t the point under the spherical coordinates. Based on the learned saliency map, maliciously point-dropping attack can be achieved by dropping points with the highest scores, leading to significant increase of model loss and thus inferior classification performance. Extensive evaluations on several state-of-the-art point-cloud recognition models, including PointNet, PointNet++ and DGCNN, demonstrate the efficacy and generality of our proposed saliencymap-based point-dropping scheme. Code for experiments is released on https://github.com/tianzheng4/ Learning-PointCloud-Saliency-Maps.
A Study of Fronthaul Networks in CRANs - Requirements and Recent Advancements

One of the most innovative paradigms for the next-generation of wireless cellular networks is the cloud-radio access networks (C-RANs). In C-RANs, base station functions are distributed between the remote radio heads (RHHs) and base band unit (BBU) pool, and a communication link is defined between them which is referred as the fronthaul. This leveraging link is expected to reduce the CAPEX (capital expenditure) and OPEX (operating expense) of envisioned cellular architectures as well as improves the spectral and energy efficiencies, provides the high scalability, and efficient mobility management capabilities. The fronthaul link carries the baseband signals between the RRHs and BBU pool using the digital radio over fiber (RoF) based common public radio interface (CPRI). CPRI based optical links imposed stringent synchronization, latency and throughput requirements on the fronthaul. As a result, fronthaul becomes a hinder in commercial deployments of C-RANs and is seen as one of a major bottleneck for backbone networks. The optimization of fronthaul is still a challenging issue and requires further exploration at industrial and academic levels. This paper comprehensively summarized the current challenges and requirements of fronthaul networks, and discusses the recently proposed system architectures, virtualization techniques, key transport technologies and compression schemes to carry the time-sensitive traffic in fronthaul networks.
Performance Analysis of Uplink Cellular IoT Using Different Deployments of Data Aggregators

Data aggregation is an effective solution to enable cellular support of Internet-of-things (IoT) communications. Indeed, it helps alleviate channel congestion, reduce the communication range, and extend battery-lifetime. In this paper, we use stochastic geometry to analyze the performance of uplink cellular IoT using different deployment strategies of aggregators, including terrestrial and aerial ones, e.g., drones or unmanned aerial vehicles. We focus on IoT-specific performance metrics, that are typically used by 3GPP. Specifically, we derive closed-form expressions of the average transmit power consumption, which is key to determine the lifetime of IoT devices, as well as the maximum coupling loss, which is essential to determine the maximum coverage the cellular system can support. Simulation results are presented to validate the derived theoretical expressions. It is shown that aerial aggregators can significantly extend the device lifetime and provide superior coverage compared to other deployment strategies. In addition, random deployment performs well when aggregators are densely deployed, whereas optimizing the location of a single terrestrial aggregator is beneficial when devices are more clustered.
SAG/RBX2 E3 Ubiquitin Ligase Differentially Regulates Inflammatory Responses of Myeloid Cell Subsets

Macrophages form an important component of the innate immune system and serve as first responders against invading pathogens. While pathways critical for initiation of inflammatory responses between macrophages and other LysM+ myeloid cells are largely similar, it remains unknown whether a specific pathway has differential effects on inflammatory responses mediated between these cells. Recent studies demonstrated that depletion of SAG (Sensitive to Apoptosis Gene), an E3 ubiquitin ligase, blocked inflammatory responses generated by macrophages and dendritic cells in response to LPS in cell culture settings. However, the in vivo role of Sag on modulation of macrophages and neutrophil is not known. Here we generated LysM-Cre/Sagfl/fl mice with selective Sag deletion in myeloid lineage, and found that in contrast to in vitro observations, LysM-Cre/Sagfl/fl mice showed increased serum levels of proinflammatory cytokines and enhanced mortality in response to LPS. Interestingly, while Sag−/− macrophages released less proinflammatory cytokines, Sag−/− neutrophils released more. Mechanistically, expression of a list of genes response to LPS was significantly altered in bone marrow cells from LysM-Cre+/Sagfl/fl mice after LPS challenge. Specifically, induction by LPS of myeloperoxidase (Mpo), a key neutrophil enzyme, and Elane, neutrophil expressed elastase, was significantly decreased upon Sag depletion. Collectively, our study revealed that Sag plays a differential role in the activation of macrophages and neutrophils.
Involving “authentic” cancer patients, their caregivers, and multidisciplinary professionals in a quality improvement trajectory in a hospital cancer pathway: a study protocol

Introduction The implementation of oncology care pathways that standardize organizational procedures has improved cancer care in recent years. However, the involvement of “authentic” patients and caregivers in quality improvement of these predetermined pathways is in its infancy, especially the scholarly reflection on this process. We, therefore, aim to explore the multidisciplinary challenges both in practice, when cancer patients, their caregivers, and a multidisciplinary team of professionals work together on quality improvement, as well as in our research team, in which a social scientist, health care professionals, health care researchers, and experience experts design a research project together. Methods and design Experience-based co-design will be used to involve cancer patients and their caregivers in a qualitative research design. In-depth open discovery interviews with 12 colorectal cancer patients, 12 breast cancer patients, and seven patients with cancer-associated thrombosis and their caregivers, and focus group discussions with professionals from various disciplines will be conducted. During the subsequent prioritization events and various co-design quality improvement meetings, observational field notes will be made on the multidisciplinary challenges these participants face in the process of co-design, and evaluation interviews will be done afterwards. Similar data will be collected during the monthly meetings of our multidisciplinary research team. The data will be analyzed according to the constant comparative method. Discussion This study may facilitate quality improvement programs in oncologic care pathways, by increasing our real-world knowledge about the challenges of involving “experience experts” together with a team of multidisciplinary professionals in the implementation process of quality improvement. Such co-creation might be challenging due to the traditional paternalistic relationship, actual disease-/treatment-related constraints, and a lack of shared language and culture between patients, caregivers, and professionals and between professionals from various disciplines. These challenges have to be met in order to establish equality, respect, team spirit, and eventual meaningful participation.
Matching game based resource allocation algorithm for energy-harvesting small cells network with NOMA

In order to increase the capacity and improve the spectrum efficiency of wireless communication systems, this paper proposes a rate-based two-sided many-to-one matching game algorithm for energy-harvesting small cells with non-orthogonal multiple access (NOMA) in heterogeneous cellular networks (HCN). First, we use a heuristic clustering based channel allocation algorithm to assign channels to small cells and manage the interference. Then, aiming at addressing the user access problem, this issue is modeled as a many-to-one matching game with the rate as its utility. Finally, considering externality in the matching game, we propose an algorithm that involves swap-matchings to find the optimal matching and to prove its stability. Simulation results show that this algorithm outperforms the comparing algorithm in efficiency and rate, in addition to improving the spectrum efficiency.
The complementarity of IT and HRM capabilities for competitive performance: a configurational analysis of manufacturing and industrial service SMEs

ABSTRACT Building on the resource-based view (RBV) perspective, we analyse the combined effects of two highly-valued organizational resources, namely information technology (IT) capabilities and human resource management (HRM) capabilities, on the competitive performance of small and medium-sized enterprises (SMEs). Three resource configurations are derived from data on 227 SMEs (121 from the manufacturing sector and 106 from the industrial services sector) through a cluster analysis. These resource configurations are labelled IT Capabilities-dominant Configuration (ITC), e-Business Capabilities-dominant Configuration (e-BC), and HRM Capabilities-dominant Configuration (HRC). This last configuration is the best-performing, followed by the e-BC, with the ITC as the worst-performing. The results also show that manufacturing and service firms are very unevenly distributed within HRC and ITC configurations, suggesting notable differences between the two sectors regarding their respective IT and non-IT capability-building. The fact that service SMEs are overwhelmingly represented (93%) in the worst-performing configuration and completely absent (0%) in the most effective configuration while displaying the strongest IT infrastructure capabilities confirms that the IT productivity paradox is aggravated in service SMEs and calls for further research on this issue.
Analysis of drug utilization and health care resource consumption in patients with psoriasis and psoriatic arthritis before and after treatment with biological therapies

Objectives To describe the therapeutic pathways of patients with psoriasis (PSO) and psoriatic arthritis (PsA) before and after treatment with biological therapies in a real-world setting and to determine the relative consumption of health care resources. Design Retrospective observational study. Setting Real-life clinical setting in 5 Italian local health units. Participants A total of 351 male and female patients with at least 1 prescription for a biological drug from January 1, 2010 to December 31, 2013; patients with concomitant rheumatoid arthritis, ankylosing spondylitis, or Crohn’s disease were excluded. Results The major health care cost (excluding drug costs) was represented by hospitalizations, mainly related to PSO /PsA-associated disorders and cardiometabolic disorders. Use of conventional drugs among biologics-naïve patients reached 50% in PSO and 80% in PsA; their use decreased following initiation of biological therapy. After the start of biological treatment, the incidence of hospitalization decreased both for PSO (from 12.3% to 3.2% in day hospital regimen and from 2.4% to 0.4% for conventional admission) and for PsA (from 11.1% to 8.1% and from 10.1% to 3.0%, respectively). Mean annual costs for hospitalization before biological treatment were €217 and €537 for PSO and PsA, respectively, while mean annual cost for concomitant drugs slightly increased after biologics initiation: from €249.8 to €269.4 for PSO and from €331.8 to €346.9 for PsA. The major consumption of health care resources occurred in the quarter preceding the beginning of biological treatment. Conclusion The consumption of health resources is mostly related to hospitalization, seems to peak during the quarter before the beginning of biologics therapies, and subsequently decreases after biologics initiation. Further studies should focus on prescription scheme and economic burden of PSO and PsA in Italy to help optimize health care resources and potentiate services for patients.
A Quasi-Polynomial Algorithm for Submodular Tree Orienteering in Directed Graphs

We consider the following general network design problem on directed graphs. The input is an asymmetric metric $(V,c)$, root $r\in V$, monotone submodular function $f:2^V \xrightarrow{} \mathbb{R}_+$ and budget $B$. The goal is to find an $r$-rooted arborescence $T$ of cost at most $B$ that maximizes $f(T)$. Our main result is a quasi-polynomial time $O(\frac{\log k}{\log\log k})$-approximation algorithm for this problem, where $k\le |V|$ is the number of vertices in an optimal solution. To the best of our knowledge, this is the first non-trivial approximation ratio for this problem. As a consequence we obtain a simple $O(\frac{\log^2 k}{\log\log k})$-approximation algorithm for directed (polymatroid) Steiner tree in quasi-polynomial time. For the usual directed Steiner tree problem, this matches the best previous result known. For the polymatroid generalization, our result improves prior results by a logarithmic factor. Our approximation ratio is tight for quasi-polynomial algorithms under certain complexity assumptions.
Anomaly Detection for Network Connection Logs

We leverage a streaming architecture based on ELK, Spark and Hadoop in order to collect, store, and analyse database connection logs in near real-time. The proposed system investigates outliers using unsupervised learning; widely adopted clustering and classification algorithms for log data, highlighting the subtle variances in each model by visualisation of outliers. Arriving at a novel solution to evaluate untagged, unfiltered connection logs, we propose an approach that can be extrapolated to a generalised system of analysing connection logs across a large infrastructure comprising thousands of individual nodes and generating hundreds of lines in logs per second.
The Efficacy and Safety of Anti-epidermal Growth Factor Receptor Monoclonal Antibodies in Nasopharyngeal Carcinoma: Literature-based Meta-analyses

Background: Anti-epidermal growth factor receptor monoclonal antibodies (anti-EGFR mAbs), such as cetuximab and nimotuzumab have been used in the treatment of nasopharyngeal carcinoma (NPC), yet their efficacy and safety are undetermined. Materials and Methods: We performed two meta-analyses based on systematic searches of PubMed, EMBASE, the Cochrane Library and SinoMed: comparison 1 (standard therapy plus mAbs vs. standard therapy) and comparison 2 (radiotherapy plus concurrent mAbs vs. concurrent chemoradiotherapy) to explore the treatment value of anti-EGFR mAbs in NPC. Primary outcomes were overall survival (OS) and disease-free survival (DFS); secondary outcomes, locoregional recurrence-free survival (LRFS), distant metastasis-free survival (DMFS) and grade 3 and above acute adverse events. Results: Four randomized controlled trials and thirteen observational studies were eligible. Comparison 1 (twelve studies): adding mAbs to standard therapy (radiotherapy or chemoradiotherapy) significantly improved OS (HR, 0.51; 95% CI, 0.39-0.66) and DFS (HR, 0.68; 95% CI, 0.54-0.86), but increased the frequency of skin rashes and mucositis. Comparison 2 (six studies): OS (HR, 1.17; 95% CI, 0.81-1.70) and DFS (HR, 1.16; 95% CI, 0.86-1.57) were not significantly different when mAbs replaced conventional cytotoxic chemotherapy concurrently with radiotherapy, with fewer hematological, gastrointestinal and renal toxicities and more skin rashes in the mAb group. Conclusion: We recommend anti-EGFR mAbs enhance—but should not replace—current treatment paradigms for locoregionally advanced NPC. Further evidence from phase III clinical trials is required.
Induction of Proinflammatory Multiple Sclerosis-Associated Retrovirus Envelope Protein by Human Herpesvirus-6A and CD46 Receptor Engagement

The aberrant expression of human endogenous retrovirus (HERV) elements of the HERV-W family has been associated with different diseases, including multiple sclerosis (MS). In particular, the expression of the envelope protein (Env) from the multiple sclerosis-associated retrovirus (MSRV), a member of HERV-W family and known for its potent proinflammatory activity, is repeatedly detected in the brain lesions and blood of MS patients. Furthermore, human herpesvirus 6 (HHV-6) infection has long been suspected to play a role in the pathogenesis of MS and neuroinflammation. We show here that both HHV-6A and stimulation of its receptor, transmembrane glycoprotein CD46, induce the expression of MSRV-Env. The engagement of extracellular domains SCR3 and SCR4 of CD46-Cyt1 isoform was required for MSRV-env transactivation, limiting thus the MSRV-Env induction to the CD46 ligands binding these domains, including C3b component of complement, specific monoclonal antibodies, and both infectious and UV-inactivated HHV-6A, but neither HHV-6B nor measles virus vaccine strain. Induction of MSRV-Env required CD46 Cyt-1 singling and was abolished by the inhibitors of protein kinase C. Finally, both membrane-expressed and secreted MSRV-Env trigger TLR4 signaling, displaying thus a proinflammatory potential, characteristic for this viral protein. These data expand the specter of HHV-6A effects in the modulation of the immune response and support the hypothesis that cross-talks between exogenous and endogenous viruses may contribute to inflammatory diseases and participate in neuroinflammation. Furthermore, they reveal a new function of CD46, known as an inhibitor of complement activation and receptor for several pathogens, in transactivation of HERV env genes, which may play an important role in the pathogenesis of inflammatory diseases.