Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine Learning: Basic Principles

This tutorial introduces some main concepts of machine learning (ML). From an engineering point of view, the field of ML revolves around developing software that implements the scientific principle: (i) formulate a hypothesis (choose a model) about some phenomenon, (ii) collect data to test the hypothesis (validate the model) and (iii) refine the hypothesis (iterate). One important class of algorithms based on this principle are gradient descent methods which aim at iteratively refining a model which is parametrized by some (``weight'') vector. A plethora of ML methods is obtained by combining different choices for the hypothesis space (model), the quality measure (loss) and the computational implementation of the model refinement (optimization method). %Many of the current systems, which are considered as (artificially) intelligent, are based on %combinations of few basic machine learning methods. After formalizing the main building blocks of an ML problem, some popular algorithmic design patterns for ML methods are discussed. This tutorial grew out of the lecture notes developed for the courses ``Machine Learning: Basic Principles'' and ``Artificial Intelligence'', which I have co-taught since 2015 at Aalto University.
Learning and Generating Distributed Routing Protocols Using Graph-Based Deep Learning

Automated network control and management has been a long standing target of network protocols. We address in this paper the question of automated protocol design, where distributed networked nodes have to cooperate to achieve a common goal without a priori knowledge on which information to exchange or the network topology. While reinforcement learning has often been proposed for this task, we propose here to apply recent methods from semi-supervised deep neural networks which are focused on graphs. Our main contribution is an approach for applying graph-based deep learning on distributed routing protocols via a novel neural network architecture named Graph-Query Neural Network. We apply our approach to the tasks of shortest path and max-min routing. We evaluate the learned protocols in cold-start and also in case of topology changes. Numerical results show that our approach is able to automatically develop efficient routing protocols for those two use-cases with accuracies larger than 95%. We also show that specific properties of network protocols, such as resilience to packet loss, can be explicitly included in the learned protocol.
The Impact of Insulin Resistance and Chronic Kidney Disease on Inflammation and Cardiovascular Disease

There is extensive evidence showing that insulin resistance (IR) is associated with chronic low-grade inflammation. Furthermore, IR has been shown to increase the risk for cardiovascular disease (CVD), even in nondiabetic patients, and is currently considered as a “nontraditional” risk factor contributing to CVD by promoting hypertension, oxidative stress, endothelial dysfunction, dyslipidemia, and type 2 diabetes mellitus. However, chronic kidney disease (CKD) is also considered a state of low-grade inflammation. In addition, CKD is considered an IR state and has been described as an independent risk factor for the development of CVD, as even early-stage CKD is associated with an estimated 40% to 100% increase in CVD risk. There is also strong evidence indicating that inflammation per se plays a crucial role in both the initiation and progression of CVD. Given the above, the combined effect of IR and CKD may significantly increase the risk of inflammation and CVD. This review aims to focus on the complex interplay between IR, CKD, inflammation, and CVD and will present and discuss the current clinical and scientific data pertaining to the impact of IR and CKD on inflammation and CVD.
Tumor rupture of gastric gastrointestinal stromal tumors during endoscopic resection: a risk factor for peritoneal metastasis?

Abstract Background and study aims Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors in the gastrointestinal tract. Up to the present time, complete surgical excision has been the standard treatment for primary GISTs greater than 2 cm. It is well known that tumor rupture during surgery is an independent risk factor for peritoneal metastasis; however, it is not known whether the risk of peritoneal metastasis increases in cases where the tumor is ruptured during endoscopic resection. Patients and methods A total of 195 patients treated for GIST between January 2014 and December 2016 in our hospital were enrolled in this study. They were divided into two groups according to whether the tumor was ruptured during endoscopic resection. The rate of peritoneal metastasis in patients in the two groups who also suffered perforation was investigated from the follow-up results. Results Approximately 55.4 % of all patients were female and the average age of the study group was 59.0 ± 10.3 years. Of the 195 patients, the tumors in 27 were ruptured and the remaining 168 patients underwent en bloc resection. There was no statistically significant difference in gender or age between the two groups. The median tumor size (maximum diameter) in all patients was 1.5 cm (0.3 – 5.0 cm): 2.5 cm (0.8 – 5.0 cm) and 1.4 cm (0.3 – 4.0 cm) in the tumor rupture group and en bloc resection group, respectively (P < 0.001). Most of the tumors were located in the gastric fundus. At a median follow-up of 18.7 ± 10.2 months, neither tumor recurrence (liver metastasis, peritoneal metastasis, local recurrence) nor mortality related to GISTs were detected. Conclusions Tumor rupture during endoscopic resection of gastric GISTs may not be a risk factor for peritoneal metastasis.
Inotuzumab ozogamicin: a CD22 mAb–drug conjugate for adult relapsed or refractory B-cell precursor acute lymphoblastic leukemia

Despite improved rates of remission and cure in newly diagnosed adult acute lymphoblastic leukemia (ALL), the prognosis for patients with relapsed or refractory disease remains poor and the 5-year overall survival rate after relapse is under 10%. A recent paradigm shift has focused on the promise of targeted immunotherapy rather than standard chemotherapy, as ALL blast cells express a variety of antigens, and monoclonal antibodies may be developed to identify and destroy the leukemic cells. Inotuzumab ozogamicin is a CD22 monoclonal antibody conjugated to the cytotoxic antibiotic calicheamicin. CD22 expression is detected on leukemic blasts in over 90% of patients with ALL. Based on promising results from preclinical studies, inotuzumab ozogamicin was tested in Phase 1/2 and Phase 3 clinical trials and it demonstrated improved complete remission rates, progression-free survival and overall survival in relapsed or refractory adult ALL compared to standard therapy. Ongoing studies are evaluating the value of inotuzumab ozogamicin when given in combination with chemotherapy as part of upfront treatment. This review discusses the drug’s biochemical properties and mechanism of action, preclinical research outcomes, clinical trial results, adverse events and toxicities, drug approval and ongoing investigations.
Effects of Magnesium Supplementation on Unipolar Depression: A Placebo-Controlled Study and Review of the Importance of Dosing and Magnesium Status in the Therapeutic Response

Animal studies using tests and models have demonstrated that magnesium exerts an antidepressant effect. The literature contains few studies in humans involving attempts to augment antidepressant therapy with magnesium ions. The purpose of our study was to assess the efficacy and safety of antidepressant treatment, in combination with magnesium ions. A total of 37 participants with recurrent depressive disorder who developed a depressive episode were included in this study. As part of this double-blind study, treatment with the antidepressant fluoxetine was accompanied with either magnesium ions (120 mg/day as magnesium aspartate) or placebo. During an 8-week treatment period, each patient was monitored for any clinical abnormalities. Moreover, serum fluoxetine and magnesium levels were measured, and pharmaco-electroencephalography was performed. The fluoxetine + magnesium and fluoxetine + placebo groups showed no significant differences in either Hamilton Depression Rating Scale (HDRS) scores or serum magnesium levels at any stage of treatment. Multivariate statistical analysis of the whole investigated group showed that the following parameters increased the odds of effective treatment: lower baseline HDRS scores, female gender, smoking, and treatment augmentation with magnesium. The parameters that increased the odds of remission were lower baseline HDRS scores, shorter history of disease, the presence of antidepressant-induced changes in the pharmaco-EEG profile at 6 h after treatment, and the fact of receiving treatment augmented with magnesium ions. The limitation of this study is a small sample size.
Antimycobacterial susceptibility evaluation of rifampicin and isoniazid benz-hydrazone in biodegradable polymeric nanoparticles against Mycobacterium tuberculosis H37Rv strain

Introduction Tuberculosis (TB) is the single largest infectious disease which requires a prolonged treatment regime with multiple drugs. The present treatment for TB includes frequent administration of a combination of four drugs for a duration of 6 months. This leads to patient’s noncompliance, in addition to developing drug-resistant strains which makes treatment more difficult. The formulation of drugs with biodegradable polymeric nanoparticles (NPs) promises to overcome this problem. Materials and methods In this study, we focus on two important drugs used for TB treatment – rifampicin (RIF) and isoniazid (INH) – and report a detailed study of RIF-loaded poly lactic-co-glycolic acid (PLGA) NPs and INH modified as INH benz-hydrazone (IH2) which gives the same therapeutic effect as INH but is more stable and enhances the drug loading in PLGA NPs by 15-fold compared to INH. The optimized formulation was characterized using particle size analyzer, scanning electron microscopy and transmission electron microscopy. The drug release from NPs and stability of drug were tested in different pH conditions. Results It was found that RIF and IH2 loaded in NPs release in a slow and sustained manner over a period of 1 month and they are more stable in NPs formulation compared to the free form. RIF- and IH2-loaded NPs were tested for antimicrobial susceptibility against Mycobacterium tuberculosis H37Rv strain. RIF loaded in PLGA NPs consistently inhibited the growth at 70% of the minimum inhibitory concentration (MIC) of pure RIF (MIC level 1 µg/mL), and pure IH2 and IH2-loaded NPs showed inhibition at MIC equivalent to the MIC of INH (0.1 µg/mL). Conclusion These results show that NP formulations will improve the efficacy of drug delivery for TB treatment.
Aircraft Noise and Psychological Ill-Health: The Results of a Cross-Sectional Study in France

Background: The effects of aircraft noise on psychological ill-health have not been largely investigated and remain to be discussed. No study has been performed in France on the health effects of aircraft noise. Objectives: The present study aimed to investigate the relationship between aircraft noise in dB and in terms of annoyance and psychological ill-health in populations living near airports in France. Methods: A total of 1244 individuals older than 18 and living near three French airports (Paris–Charles de Gaulle, Lyon–Saint-Exupéry and Toulouse–Blagnac) were randomly selected to participate in the study. Information about their personal medical history and socioeconomic and lifestyle factors was collected by means of a face-to-face questionnaire performed at their place of residence by an interviewer. Psychological ill-health was evaluated with the 12-item version of the General Heath Questionnaire (GHQ-12). For each participant, outdoor aircraft noise exposure in dB was estimated by linking their home address to noise maps. Objective noise exposure in dB was considered to be the primary exposure of interest. Four noise indicators referring to three different periods of the day were derived and used for the statistical analyses: Lden, LAeq,24hr, LAeq,6hr–22hr, and Lnight. Noise annoyance and noise sensitivity were the secondary risk factors of interest. Logistic regression models were used with adjustment for potential confounders. Results: The participation rate in the study was 30%. Approximately 22% of the participants were considered to have psychological ill-health according to the GHQ-12. No direct association was found between exposure to aircraft noise in dB and psychological ill-health. However, annoyance due to aircraft noise and noise sensitivity were both significantly associated with psychological ill-health. Moreover, a gradient was evidenced between annoyance and psychological ill-health, with increasing ORs from 1.79 (95% CI 1.06–3.03) for people who were not all annoyed to 4.00 (95% CI 1.67–9.55) for extremely annoyed people. Conclusions: These findings confirm the results of previous studies, suggesting there is no direct association between aircraft noise exposure in dB and psychological ill-health, but there is a significant relationship between noise sensitivity or annoyance due to aircraft noise and psychological ill-health. This supports the hypothesis that psychological aspects, such as noise annoyance and noise sensitivity, play important roles in the association between environmental noise and adverse effects on health. However, further studies are necessary in order to better understand the links between these variables.
Knowledge of and attitudes toward HIV/AIDS among Iranian women

OBJECTIVES This study investigated the knowledge of Iranian women about HIV/AIDS and whether they had accepting attitudes towards people living with human immunodeficiency virus (HIV), and sought to identify factors correlated with their knowledge and attitudes. METHODS The data analyzed in the present study were taken from Iran’s Multiple Indicator Demographic and Health Survey, a national survey conducted in 2015. In total, 42,630 women aged 15-49 years were identified through multi-stage stratified cluster random sampling and interviewed. Associations of the socio-demographic characteristics of participants with their knowledge and attitudes were examined using multiple logistic regression analysis. RESULTS The majority (79.0%) of Iranian women had heard about HIV/AIDS, but only 19.1% had a comprehensive knowledge. In addition, only 15.4% of women had accepting attitudes toward people with HIV. Being older, married, more highly educated, and wealthier were factors associated with having more comprehensive knowledge of HIV/AIDS, and living in urban areas was associated with having more positive attitudes toward people with HIV. CONCLUSIONS The relatively poor knowledge of Iranian women and the low prevalence of accepting attitudes toward people living with HIV highlight the need to develop policies and interventions to overcome this issue, which would be a basis for further prevention of HIV/AIDS in Iran.
Combustion Behaviors of CIGS Thin-Film Solar Modules from Cone Calorimeter Tests

As is well known, building integrated photovoltaic (BIPV) technology is becoming more commonly used in residential and commercial buildings. Fire assessment of photovoltaic (PV) modules as a whole is still insufficient. This work focuses on the thermal properties and combustion behavior of CIGS (copper, indium, gallium and selenium) thin-film modules. Cone calorimeter experiments were conducted at different external heat flux of 25, 30, 35, 40 and 45 kW m−2. Several parameters are discussed, including surface temperature, ignition time, heat release rate (HRR), mass loss rate, carbon monoxide (CO) and carbon dioxide (CO2) concentrations. The results show that CIGS thin-film solar modules are inflammable at intermediate or high flashover risk. A correction calculation for the gas toxicity index has been used to reduce the well-ventilation condition effect. Compared with the uncorrected calculation, peak fractional effective dose (FED) and lethal concentration for 50% of the population (LC50) are almost double. This work will help to determine a more stringent fire safety provision for PV modules.
Consensus on Molecular Subtypes of High-Grade Serous Ovarian Carcinoma

Purpose: The majority of ovarian carcinomas are of high-grade serous histology, which is associated with poor prognosis. Surgery and chemotherapy are the mainstay of treatment, and molecular characterization is necessary to lead the way to targeted therapeutic options. To this end, various computational methods for gene expression–based subtyping of high-grade serous ovarian carcinoma (HGSOC) have been proposed, but their overlap and robustness remain unknown. Experimental Design: We assess three major subtype classifiers by meta-analysis of publicly available expression data, and assess statistical criteria of subtype robustness and classifier concordance. We develop a consensus classifier that represents the subtype classifications of tumors based on the consensus of multiple methods, and outputs a confidence score. Using our compendium of expression data, we examine the possibility that a subset of tumors is unclassifiable based on currently proposed subtypes. Results: HGSOC subtyping classifiers exhibit moderate pairwise concordance across our data compendium (58.9%–70.9%; P < 10−5) and are associated with overall survival in a meta-analysis across datasets (P < 10−5). Current subtypes do not meet statistical criteria for robustness to reclustering across multiple datasets (prediction strength < 0.6). A new subtype classifier is trained on concordantly classified samples to yield a consensus classification of patient tumors that correlates with patient age, survival, tumor purity, and lymphocyte infiltration. Conclusions: A new consensus ovarian subtype classifier represents the consensus of methods and demonstrates the importance of classification approaches for cancer that do not require all tumors to be assigned to a distinct subtype. Clin Cancer Res; 24(20); 5037–47. ©2018 AACR.
Deep Neural Network for Analysis of DNA Methylation Data

Many researches demonstrated that the DNA methylation, which occurs in the context of a CpG, has strong correlation with diseases, including cancer. There is a strong interest in analyzing the DNA methylation data to find how to distinguish different subtypes of the tumor. However, the conventional statistical methods are not suitable for analyzing the highly dimensional DNA methylation data with bounded support. In order to explicitly capture the properties of the data, we design a deep neural network, which composes of several stacked binary restricted Boltzmann machines, to learn the low dimensional deep features of the DNA methylation data. Experiments show these features perform best in breast cancer DNA methylation data cluster analysis, comparing with some state-of-the-art methods.
On Optimizing Deep Convolutional Neural Networks by Evolutionary Computing

Optimization for deep networks is currently a very active area of research. As neural networks become deeper, the ability in manually optimizing the network becomes harder. Mini-batch normalization, identification of effective respective fields, momentum updates, introduction of residual blocks, learning rate adoption, etc. have been proposed to speed up the rate of convergent in manual training process while keeping the higher accuracy level. However, the problem of finding optimal topological structure for a given problem is becoming a challenging task need to be addressed immediately. Few researchers have attempted to optimize the network structure using evolutionary computing approaches. Among them, few have successfully evolved networks with reinforcement learning and long-short-term memory. A very few has applied evolutionary programming into deep convolution neural networks. These attempts are mainly evolved the network structure and then subsequently optimized the hyper-parameters of the network. However, a mechanism to evolve the deep network structure under the techniques currently being practiced in manual process is still absent. Incorporation of such techniques into chromosomes level of evolutionary computing, certainly can take us to better topological deep structures. The paper concludes by identifying the gap between evolutionary based deep neural networks and deep neural networks. Further, it proposes some insights for optimizing deep neural networks using evolutionary computing techniques.
HSP40 co-chaperone protein Tid1 suppresses metastasis of head and neck cancer by inhibiting Galectin-7-TCF3-MMP9 axis signaling

Human tumorous imaginal disc (Tid1), a DnaJ co-chaperone protein, is classified as a tumor suppressor. Previously, we demonstrated that Tid1 reduces head and neck squamous cell carcinoma (HNSCC) malignancy. However, the molecular details of Tid1-mediated anti-metastasis remain elusive. Methods: We used affinity chromatography and systemic mass spectrometry to identify Tid1-interacting client proteins. Immunohistochemical staining of Tid1 in HNSCC patient tissues was examined to evaluate the association between the expression profile of Tid1-interacting client proteins with pathologic features and prognosis. The roles of Tid1-interacting client proteins in metastasis were validated both in vitro and in vivo. The interacting partner and downstream target of Tid1-interacting client protein were determined. Results: Herein, we first revealed that Galectin-7 was one of the Tid1-interacting client proteins. An inverse association of protein expression profile between Tid1 and Galectin-7 was determined in HNSCC patients. Low Tid1 and high Galectin-7 expression predicted poor overall survival in HNSCC. Furthermore, Tid1 abolished the nuclear translocation of Galectin-7 and suppressed Galectin-7-induced tumorigenesis and metastasis. Keratinocyte-specific Tid1-deficient mice with 4-nitroquinoline-1-oxide (4NQO) treatment exhibited increased protein levels of Galectin-7 and had a poor survival rate. Tid1 interacted with Galectin-7 through its N-linked glycosylation to promote Tid1-mediated ubiquitination and proteasomal degradation of Galectin-7. Additionally, Galectin-7 played a critical role in promoting tumorigenesis and metastatic progression by enhancing the transcriptional activity of TCF3 transcription factor through elevating MMP-9 expression. Conclusions: Overall, future treatments through activating Tid1 expression or inversely repressing the oncogenic function of Galectin-7 may exhibit great potential in targeting HNSCC progression.
PIP2 depletion promotes TRPV4 channel activity in mouse brain capillary endothelial cells

We recently reported that the inward-rectifier Kir2.1 channel in brain capillary endothelial cells (cECs) plays a major role in neurovascular coupling (NVC) by mediating a neuronal activity-dependent, propagating vasodilatory (hyperpolarizing) signal. We further demonstrated that Kir2.1 activity is suppressed by depletion of plasma membrane phosphatidylinositol 4,5-bisphosphate (PIP2). Whether cECs express depolarizing channels that intersect with Kir2.1-mediated signaling remains unknown. Here, we report that Ca2+/Na+-permeable TRPV4 (transient receptor potential vanilloid 4) channels are expressed in cECs and are tonically inhibited by PIP2. We further demonstrate that depletion of PIP2 by agonists, including putative NVC mediators, that promote PIP2 hydrolysis by signaling through Gq-protein-coupled receptors (GqPCRs) caused simultaneous disinhibition of TRPV4 channels and suppression of Kir2.1 channels. These findings collectively support the concept that GqPCR activation functions as a molecular switch to favor capillary TRPV4 activity over Kir2.1 signaling, an observation with potentially profound significance for the control of cerebral blood flow.