Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene Expression Profiling of Olfactory Neuroblastoma Helps Identify Prognostic Pathways and Define Potentially Therapeutic Targets

Simple Summary The gene expression profile of ONB defines a group of patients with a dismal prognosis and identifies potentially targetable pathways. Better prognostic stratification may offer new tailored approaches for the treatment and follow-up of ONB. The integration of new therapeutic agents with standard surgical and RT strategies may improve the outcomes in cases with worse prognoses. Furthermore, the ontogenesis of ONB in basal and neural subtypes is mirrored by different transcriptional pathways, paving the way towards different therapeutic approaches. Abstract Olfactory neuroblastoma (ONB) is a rare sinonasal neoplasm with a peculiar behavior, for which limited prognostic factors are available. Herein, we investigate the transcriptional pathways altered in ONB and correlate them with pathological features and clinical outcomes. We analyze 32 ONB patients treated with curative intent at two independent institutions from 2001 to 2019 for whom there is available pathologic and clinical data. We perform gene expression profiling on primary ONB samples and carry out functional enrichment analysis to investigate the key pathways associated with disease-free survival (DFS). The median age is 53.5 years; all patients undergo surgery and a pure endoscopic approach is adopted in the majority of cases (81.2%). Most patients have advanced disease (stages III–IV, 81.2%) and 84.4% undergo adjuvant (chemo)radiotherapy. The median follow-up is 35 months; 11 (26.8%) patients relapse. Clinical characteristics (gender, stage and Hyams’ grade) are not associated with the outcomes. In contrast, TGF-beta binding, EMT, IFN-alpha response, angiogenesis, IL2-STAT5 and IL6-JAK-STAT3 signaling pathways are enriched in patients experiencing recurrence, and significantly associated with shorter DFS. Clustering of transcriptional profiles according to pathological features indicates two distinct molecular groups, defined by either cytokeratin-positive or -negative immunostaining. Definition of the characterizing ONB transcriptomic pathways may pave the way towards tailored treatment approaches.
Self-reported memory and executive function in adult non-clinical hoarders

Abstract Hoarding is the excessive acquisition of, and failure to discard of, large numbers of items, leading to personal distress. Impairments on memory and executive functions have been systematically associated with hoarding behavior, predominantly focusing upon clinical (mainly middle-aged-elderly) patients with hoarding and/or PTSD. We were interested in hoarding-related memory and executive problems in younger non-clinical hoarders or non-hoarders, based on their Saving Inventory-Revised scores. In total, 113 young adults (aged 18–35 years) were assigned to either a hoarder group (N = 40) or non-hoarder group (N = 73) determined by their scores on the Saving Inventory-Revised (SI-R). Working memory (WM) and inhibition control (IC) were measured using the Adult Executive Functioning Inventory (ADEXI) and the Dysexecutive Questionnaire Revised (DEX-R) measured general executive function (EF). The Hospital Anxiety and Depression Scale measured anxiety and depression. After controlling for gender and anxiety, the analysis revealed that the hoarders reported significantly more problems than the non-hoarders on both the IC and general EF. There was no significant between-group difference on the WM sub-scale ADEXI. Self-reported deficits in IC and EF are associated with hoarding behavior. The IC deficits cold explain hoarders’ inability to resist urges to buy, and general EF deficits suggest other domains are involved.
GWAS Links New Variant in Long Non-Coding RNA LINC02006 with Colorectal Cancer Susceptibility

Simple Summary Identifying risk factors for cancer development can allow for appropriate stratification and surveillance of individuals at risk, increasing their chances of benefiting from early disease detection; however, most of the genetic factors contributing to the risk of colorectal cancer (CRC) remain undetermined. Here, we adopted a new approach for selecting index polymorphism for further validation in combination with a genome-wide association study of pooled DNA samples for CRC susceptibility variants in the Polish population. This study, including 2013 patients and controls, uncovered five susceptibility loci not previously reported for CRC. Four of identified variants were located within genes likely involved in tumor invasiveness and metastasis, suggesting that they could be markers of poor prognosis in CRC patients. Our results provide evidence that conducting association studies on small but homogenous populations can help us discover new common risk variants specific to the studied population. Abstract Despite great efforts, most of the genetic factors contributing to the risk of colorectal cancer (CRC) remain undetermined. Including small but homogenous populations in genome-wide association studies (GWAS) can help us discover new common risk variants specific to the studied population. In this study, including 465 CRC patients and 1548 controls, a pooled DNA samples-based GWAS was conducted in search of genetic variants associated with CRC in a Polish population. Combined with a new method of selecting single-nucleotide polymorphisms (SNPs) for verification in individual DNA samples, this approach allowed the detection of five new susceptibility loci not previously reported for CRC. The discovered loci were found to explain 10% of the overall risk of developing CRC. The strongest association was observed for rs10935945 in long non-coding RNA LINC02006 (3q25.2). Three other SNPs were also located within genes (rs17575184 in NEGR1, rs11060839 in PIWIL1, rs12935896 in BCAS3), while one was intergenic (rs9927668 at 16p13.2). An expression quantitative trait locus (eQTL) bioinformatic analysis suggested that these polymorphisms may affect transcription factor binding sites. In conclusion, four of the identified variants were located within genes likely involved in tumor invasiveness and metastasis. Therefore, they could possibly be markers of poor prognosis in CRC patients.
Effect of Plasma-Enhanced Atomic Layer Deposition on Oxygen Overabundance and Its Influence on the Morphological, Optical, Structural, and Mechanical Properties of Al-Doped TiO2 Coating

The chemical, structural, morphological, and optical properties of Al-doped TiO2 thin films, called TiO2/Al2O3 nanolaminates, grown by plasma-enhanced atomic layer deposition (PEALD) on p-type Si <100> and commercial SLG glass were discussed. High-quality PEALD TiO2/Al2O3 nanolaminates were produced in the amorphous and crystalline phases. All crystalline nanolaminates have an overabundance of oxygen, while amorphous ones lack oxygen. The superabundance of oxygen on the crystalline film surface was illustrated by a schematic representation that described this phenomenon observed for PEALD TiO2/Al2O3 nanolaminates. The transition from crystalline to amorphous phase increased the surface hardness and the optical gap and decreased the refractive index. Therefore, the doping effect of TiO2 by the insertion of Al2O3 monolayers showed that it is possible to adjust different parameters of the thin-film material and to control, for example, the mobility of the hole-electron pair in the metal-insulator-devices semiconductors, corrosion protection, and optical properties, which are crucial for application in a wide range of technological areas, such as those used to manufacture fluorescence biosensors, photodetectors, and solar cells, among other devices.
Rational Design Method Based on Techno-Economic Principles for Integration of Organic/Organic Pervaporation with Lipase Catalyzed Transesterification

An engineering foundation is developed in this manuscript to allow the rational design of enzymatic transesterifications integrated with organic–organic pervaporation for the removal of methanol. In the first part, enzyme kinetics are elucidated for the solventless transesterification of two monoterpene alcohols with methyl acetate catalyzed by Novozym 435. Nonlinear regression revealed that three parameters (enzyme loading, forward and backward second-order reaction rate) sufficed to describe the entire conversion as a function of time. In the second part, a mathematical model for acetate ester production, integrated with organic–organic pervaporation, was developed based on a set of ordinary differential equations. To this end, empirical formulae for the pervaporation performance (of a PERVAP 2255-30 membrane and a standard HybSi® membrane) were established, relating methyl acetate and methanol flux to the methanol concentration in the reactor. The resulting digital twin, “PervApp”, allows us to study the influence of the key design parameters “enzyme loading” and “membrane surface” on, e.g., catalyst productivity. Finally, a techno-economic assessment is made for an annual production of 100 tons of geranyl acetate. The described methodology allows producers to shift from laborious, expensive and often disappointing trial-and-error approaches to the rational design of such integrated units.
Tumor Extracellular Matrix Stiffness Promptly Modulates the Phenotype and Gene Expression of Infiltrating T Lymphocytes

The immune system is a fine modulator of the tumor biology supporting or inhibiting its progression, growth, invasion and conveys the pharmacological treatment effect. Tumors, on their side, have developed escaping mechanisms from the immune system action ranging from the direct secretion of biochemical signals to an indirect reaction, in which the cellular actors of the tumor microenvironment (TME) collaborate to mechanically condition the extracellular matrix (ECM) making it inhospitable to immune cells. TME is composed of several cell lines besides cancer cells, including tumor-associated macrophages, cancer-associated fibroblasts, CD4+ and CD8+ lymphocytes, and innate immunity cells. These populations interface with each other to prepare a conservative response, capable of evading the defense mechanisms implemented by the host’s immune system. The presence or absence, in particular, of cytotoxic CD8+ cells in the vicinity of the main tumor mass, is able to predict, respectively, the success or failure of drug therapy. Among various mechanisms of immunescaping, in this study, we characterized the modulation of the phenotypic profile of CD4+ and CD8+ cells in resting and activated states, in response to the mechanical pressure exerted by a three-dimensional in vitro system, able to recapitulate the rheological and stiffness properties of the tumor ECM.
Novel Methodological Tools for Behavioral Interventions: The Case of HRV-Biofeedback. Sham Control and Quantitative Physiology-Based Assessment of Training Quality and Fidelity

Scientific research on heart rate variability (HRV) biofeedback is burdened by certain methodological issues, such as lack of consistent training quality and fidelity assessment or control conditions that would mimic the intervention. In the present study, a novel sham HRV-biofeedback training was proposed as a credible control condition, indistinguishable from the real training. The Yield Efficiency of Training Index (YETI), a quantitative measure based on the spectral distribution of heart rate during training, was suggested for training quality assessment. A training fidelity criterion derived from a two-step classification process based on the average YETI index and its standard deviation (YETISD) was suggested. We divided 57 young, healthy volunteers into two groups, each subjected to 20 sessions of either real or sham HRV-biofeedback. Five standard HRV measures (standard deviation of the NN (SDNN), root mean square of the standard deviation of the NN (RMSSD), total power, low-frequency (LF), and high-frequency (HF) power) collected at baseline, after 10 and 20 sessions were subjected to analysis of variance. Application of a training fidelity criterion improved sample homogeneity, resulting in a substantial gain in effect sizes of the group and training interactions for all considered HRV indices. Application of methodological amendments, including proper control conditions (such as sham training) and quantitative assessment of training quality and fidelity, substantially improves the analysis of training effects. Although presented on the example of HRV-biofeedback, this approach should similarly benefit other behavioral training procedures that interact with any of the many psychophysiological mechanisms in the human body.
How Trust in Information Sources Influences Preventative Measures Compliance during the COVID-19 Pandemic

This paper explores how trust in formal information sources (government and media) and informal information sources (interpersonal) about COVID-19 influences compliance with preventive measures. This cross-sectional study uses convenience sampling of 478 adult participants. Data analyses using structural equation modeling with multigroup comparisons examine hypothesized relationships between trust in information sources and preventative behaviors and social distancing. Results suggest that understanding of COVID-19 causes is related to trust in formal information sources, but not to trust in informal information. Self-efficacy for prevention is related to trust in informal information sources, but not to trust in formal information sources. Worry about contracting COVID-19 is related to trust in formal information sources, but not to informal ones. Engaging in preventive measures is linked to both self-efficacy for prevention and worry, while social distancing was related only to worry. These findings have important implications for public health policy guidelines centered on clear and truthful media messages. The findings also facilitate comparative analyses of reactions to information sources across a decade of evolving attitudes toward media and government, between two cultures (Hong Kong vs. the USA), and between two different global pandemics.
The Efficacy of Transcranial Direct Current Stimulation in Enhancing Surgical Skill Acquisition: A Preliminary Meta-Analysis of Randomized Controlled Trials

The application of transcranial direct current stimulation (tDCS) to targeted cortices has been found to improve in skill acquisition; however, these beneficial effects remained unclear in fine and complicated skill. The aim of the current meta-analysis was to investigate the association between tDCS application and the efficacy of surgical performance during surgical skill training. We included randomized controlled trials (RCTs) investigating the efficacy of tDCS in enhancing surgical skill acquisition. This meta-analysis was conducted under a random-effect model. Six RCTs with 198 participants were included. The main result revealed that tDCS was associated with significantly better improvement in surgical performance than the sham control (Hedges’ g = 0.659, 95% confidence intervals (95%CIs) = 0.383 to 0.935, p < 0.001). The subgroups of tDCS over the bilateral prefrontal cortex (Hedges’ g = 0.900, 95%CIs = 0.419 to 1.382, p < 0.001) and the primary motor cortex (Hedges’ g = 0.599, 95%CIs = 0.245 to 0.953, p = 0.001) were both associated with significantly better improvements in surgical performance. The tDCS application was not associated with significant differences in error scores or rates of local discomfort compared with a sham control. This meta-analysis supported the rationale for the tDCS application in surgical training programs to improve surgical skill acquisition.
Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response and brain oscillation activity was investigated using the concurrent recording of fNIRS and EEG during ankle joint movements. Twenty subjects participated in this experiment. The EEG was recorded using 20 electrodes and hemodynamic responses were recorded using 32 optodes positioned over the motor cortex areas. The event-related desynchronization (ERD) feature was extracted from the EEG signal in the alpha band (8–11) Hz, and the concentration change of the oxy-hemoglobin (oxyHb) was evaluated from the hemodynamics response. During the motor execution of the ankle joint movements, a decrease in the alpha (8–11) Hz amplitude (desynchronization) was found to be correlated with an increase of the oxyHb (r = −0.64061, p < 0.00001) observed on the Cz electrode and the average of the fNIRS channels (ch28, ch25, ch32, ch35) close to the foot area representation. Then, the correlated channels in both modalities were used for ankle joint movement classification. The result demonstrates that the integrated modality based on the correlated channels provides a substantial enhancement in ankle joint classification accuracy of 93.01 ± 5.60% (p < 0.01) compared with single modality. These results highlight the potential of the bimodal fNIR–EEG approach for the development of future BCI for lower limb rehabilitation.
Collision Avoidance and Stability Study of a Self-Reconfigurable Drainage Robot

The inspection and maintenance of drains with varying heights necessitates a drain mapping robot with trained labour to maintain community hygiene and prevent the spread of diseases. For adapting to level changes and navigating in the narrow confined environments of drains, we developed a self-configurable hybrid robot, named Tarantula-II. The platform is a quadruped robot with hybrid locomotion and the ability to reconfigure to achieve variable height and width. It has four legs, and each leg is made of linear actuators and modular rolling wheel mechanisms with bi-directional movement. The platform has a fuzzy logic system for collision avoidance of the side wall in the drain environment. During level shifting, the platform achieves stability by using the pitch angle as the feedback from the inertial measuring unit (IMU) mounted on the platform. This feedback helps to adjust the accurate height of the platform. In this paper, we describe the detailed mechanical design and system architecture, kinematic models, control architecture, and stability of the platform. We deployed the platform both in a lab setting and in a real-time drain environment to demonstrate the wall collision avoidance, stability, and level shifting capabilities of the platform.
Early Detection of Exposure to Toxic Chemicals Using Continuously Recorded Multi-Sensor Physiology

Early detection of exposure to a toxic chemical, e.g., in a military context, can be life-saving. We propose to use machine learning techniques and multiple continuously measured physiological signals to detect exposure, and to identify the chemical agent. Such detection and identification could be used to alert individuals to take appropriate medical counter measures in time. As a first step, we evaluated whether exposure to an opioid (fentanyl) or a nerve agent (VX) could be detected in freely moving guinea pigs using features from respiration, electrocardiography (ECG) and electroencephalography (EEG), where machine learning models were trained and tested on different sets (across subject classification). Results showed this to be possible with close to perfect accuracy, where respiratory features were most relevant. Exposure detection accuracy rose steeply to over 95% correct during the first five minutes after exposure. Additional models were trained to correctly classify an exposed state as being induced either by fentanyl or VX. This was possible with an accuracy of almost 95%, where EEG features proved to be most relevant. Exposure detection models that were trained on subsets of animals generalized to subsets of animals that were exposed to other dosages of different chemicals. While future work is required to validate the principle in other species and to assess the robustness of the approach under different, realistic circumstances, our results indicate that utilizing different continuously measured physiological signals for early detection and identification of toxic agents is promising.
Functional lignin-SiO2 hybrids as potential fillers for phenolic binders

Abstract Functional lignin-SiO2 hybrid fillers were synthesized and characterized with a view to their potential application in binders for phenolic resins. The properties of these fillers and of composites obtained from them with phenolic resin were compared with those of systems with lignin or silica alone. The chemical structure of the materials was investigated by Fourier transform infrared spectroscopy. Surface properties of lignin-SiO2 fillers were tested using inverse gas chromatography (IGC). IGC was used for determination of surface energy and surface heterogeneity of the studied fillers. IGC made it possible to assess the adhesion between the tested fillers and phenolic resins. Interactions of functional fillers with phenolic resins were also evaluated by IGC. The results indicated that lignin-SiO2 interacted strongly with the phenolic resin, more strongly than pure lignin. This was proved by SEM observations: thanks to the stronger interactions of lignin-SiO2 hybrid with phenolic resins, a more homogeneous composite was obtained. Thermo-mechanical properties of lignin–silica and resin systems were investigated by DMTA. DMTA results showed that phenolic binders with lignin-SiO2 fillers have better thermo-mechanical properties than systems with lignin or silica alone: higher glass transition temperature and a smaller decrease in storage modulus. Lignin fillers can thus provide new, promising properties for a phenolic binder combining the good properties of lignin as a plasticizer and of silica as a filler improving mechanical properties.
Reconstruction, analysis and interpretation of posterior probability distributions of PET images, using the posterior bootstrap

The uncertainty of reconstructed PET images remains difficult to assess and to interpret for the use in diagnostic and quantification tasks. Here we provide (1) an easy-to-use methodology for uncertainty assessment for almost any Bayesian model in PET reconstruction from single datasets and (2) a detailed analysis and interpretation of produced posterior image distributions. We apply a recent posterior bootstrap framework to the PET image reconstruction inverse problem and obtain simple parallelizable algorithms based on random weights and on existing maximum a posteriori (MAP) (posterior maximum) optimization-based algorithms. Posterior distributions are produced, analyzed and interpreted for several common Bayesian models. Their relationship with the distribution of the MAP image estimate over multiple dataset realizations is exposed. The coverage properties of posterior distributions are validated. More insight is obtained for the interpretation of posterior distributions in order to open the way for including uncertainty information into diagnostic and quantification tasks.