Miracle-dz/UniFAR-FTUs huggingface dataset:
Correspondence between Monkey Visual Cortices and Layers of a Saliency Map Model Based on a Deep Convolutional Neural Network for Representations of Natural Images

Abstract Attentional selection is a function that allocates the brain’s computational resources to the most important part of a visual scene at a specific moment. Saliency map models have been proposed as computational models to predict attentional selection within a spatial location. Recent saliency map models based on deep convolutional neural networks (DCNNs) exhibit the highest performance for predicting the location of attentional selection and human gaze, which reflect overt attention. Trained DCNNs potentially provide insight into the perceptual mechanisms of biological visual systems. However, the relationship between artificial and neural representations used for determining attentional selection and gaze location remains unknown. To understand the mechanism underlying saliency map models based on DCNNs and the neural system of attentional selection, we investigated the correspondence between layers of a DCNN saliency map model and monkey visual areas for natural image representations. We compared the characteristics of the responses in each layer of the model with those of the neural representation in the primary visual (V1), intermediate visual (V4), and inferior temporal (IT) cortices. Regardless of the DCNN layer level, the characteristics of the responses were consistent with that of the neural representation in V1. We found marked peaks of correspondence between V1 and the early level and higher-intermediate-level layers of the model. These results provide insight into the mechanism of the trained DCNN saliency map model and suggest that the neural representations in V1 play an important role in computing the saliency that mediates attentional selection, which supports the V1 saliency hypothesis.
Circulating Bile Acids Profiles in Obese Children and Adolescents: A Possible Role of Sex, Puberty and Liver Steatosis

Background. Childhood obesity is becoming a major health issue and contributes to increasing the risk of cardiovascular disease in adulthood. Since dysregulated metabolism of bile acids (BAs) plays a role in progression of obesity-related disorders, including steatosis and hypertension, this study aimed to investigate BAs profiles in obese children with and without steatosis and hypertension, as well as exploring the interplay between BAs profile and vascular function. Methods. BAs concentrations were quantified with liquid chromatography-tandem mass spectrometry in 69 overweight/obese children and adolescents (mean age, 11.6 ± 2.5 years; 30 females). Liver steatosis was defined with abdomen ultrasonography, whilst hypertension was defined according to the current European guidelines. Vascular function was assessed with ultrasound technique, by measuring carotid intima media thickness (cIMT) and common carotid artery distensibility (cDC). Results. Total and individual glycine-conjugated BAs concentrations were found to be significantly higher in males compared to females, as well as in pre-pubertal compared to pubertal stage (p < 0.05 for both). No difference in BAs concentration was observed between hypertensive and normotensive subjects. Total BAs and glycine conjugated BAs were significantly higher in participants with steatosis compared to those without (p = 0.004 for both). The values of total glycine-conjugate acids were positively correlated with cDC and this association remained significant in linear regression after adjusting for sex, age, pubertal stage, body mass index and aspartate aminotransferase. Conclusion. The results suggest a possible role of BAs in the pathogenesis of liver and/or vascular damage in children and adolescent. Further studies are hence needed to validate these preliminary findings.
A systematic review and meta-analysis

Background: This study aimed to assess the effect of hyperglycemia on all-cause mortality in pediatric patients with brain injury, based on currently available evidence. Methods: We systematically searched the PubMed, Embase, and Cochrane Library databases with the keywords “hyperglycemia”, “brain injury”, and “pediatrics”. The retrieved records were screened by title, abstract, and full-text to include original articles assessing the effects of hyperglycemia on pediatric brain injury. The extracted data were assessed by a fixed-effects model. The risk of bias in the eligible studies was evaluated with the Newcastle-Ottawa Scale. Publication bias was visually examined with a funnel plot. Begg and Egger tests, respectively, were used to identify small-study effects. Sensitivity analysis was performed to evaluate the robustness of the original effect size. Results: Nine observational studies were identified from 1439 primary hits. A total of 970 pediatric patients, including 304 with hyperglycemia and brain injury, were included for meta-analysis. Hyperglycemia was strongly associated with a higher risk of all-cause mortality in pediatric patients (odds ratio=11.60, 95% confidence interval [CI] 7.88–17.08; I=0%). The overall quality of eligible studies was low, but the funnel plot indicated no publication bias. Conclusions:Hyperglycemia is significantly associated with high all-causemortality in pediatric patients with brain injury. However, the relationship should be confirmed by larger-scale observational studies and randomized controlled trials. Abbreviations: CI= confidence interval, GCS=Glasgow Coma Scale, NOS=Newcastle-Ottawa Quality Assessment Scale, OR = odds ratio.
“Benign” tremor? A serial case report of 2.5 year progression from mild cognitive impairment to amnestic dementia following deep brain stimulator placement for essential tremor

Abstract Essential tremor (ET) is a prevalent neurological disorder with associated neuropsychological sequalae. Although cognitive deficits associated with ET are traditionally conceptualized as attention, processing speed, and executive impairments attributed to underlying frontal-subcortical dysfunction, emerging literature highlights the elevated frequency of progressive amnestic memory impairments in patients with ET. This case study centers around a 75-year-old woman with a 15-year history of ET who underwent deep brain stimulation (DBS) as well as three neuropsychological evaluations, one pre-surgically and two post-surgically at one and two-years post successful DBS surgery. Neuropsychological evaluation results revealed circumscribed mild and variable memory deficits pre-surgically and one-year post-surgically, However, two-years post-DBS, reliable change indices revealed significant declines in verbal/visual memory, consistent with an amnestic presentation, in addition to executive functions, aspects of higher-level language abilities, and overall IQ. This case study adds to a growing literature identifying a subset of ET patients with a neurodegenerative cognitive trajectory characterized by progressive, amnestic memory impairment. The case also highlights the importance of serial monitoring of cognition beyond the pre-surgical DBS workup to monitor for clinically significant decline(s).
Neural H₂ Control Using Continuous-Time Reinforcement Learning

In this article, we discuss continuous-time <inline-formula> <tex-math notation="LaTeX">$\mathcal {H}_{2}$ </tex-math></inline-formula> control for the unknown nonlinear system. We use differential neural networks to model the system, then apply the <inline-formula> <tex-math notation="LaTeX">$\mathcal {H}_{2}$ </tex-math></inline-formula> tracking control based on the neural model. Since the neural <inline-formula> <tex-math notation="LaTeX">$\mathcal {H}_{2}$ </tex-math></inline-formula> control is very sensitive to the neural modeling error, we use reinforcement learning to improve the control performance. The stabilities of the neural modeling and the <inline-formula> <tex-math notation="LaTeX">$\mathcal {H}_{2}$ </tex-math></inline-formula> tracking control are proven. The convergence of the approach is also given. The proposed method is validated with two benchmark control problems.
A Real-Time Movement Artifact Removal Method for Ambulatory Brain-Computer Interfaces

Recently, practical brain-computer interfaces (BCIs) have been widely investigated for detecting human intentions in real world. However, performance differences still exist between the laboratory and the real world environments. One of the main reasons for such differences comes from the user’s unstable physical states (e.g., human movements are not strictly controlled), which produce unexpected signal artifacts. Hence, to minimize the performance degradation of electroencephalography (EEG)-based BCIs, we present a novel artifact removal method named constrained independent component analysis with online learning (cIOL). The cIOL can find and reject the noise-like components related to human body movements (i.e., movement artifacts) in the EEG signals. To obtain movement information, isolated electrodes are used to block electrical signals from the brain using high-resistance materials. We estimate artifacts with movement information using constrained independent component analysis from EEG signals and then extract artifact-free signals using online learning in each sample. In addition, the cIOL is evaluated by signal processing under 16 different experimental conditions (two types of EEG devices $\times $ two BCI paradigms $\times $ four different walking speeds). The experimental results show that the cIOL has the highest accuracy in both scalp- and ear-EEG, and has the highest signal-to-noise ratio in scalp-EEG among the state-of-the-art methods, except for the case of steady-state visual evoked potential at 2.0 m/s with superposition problem.
Towards a mechanism-based approach for the prediction of nongenotoxic carcinogenic potential of agrochemicals

Abstract Chemical substances are subjected to assessment of genotoxic and carcinogenic effects before being marketed to protect man and the environment from health risks. For agrochemicals, the long-term rodent carcinogenicity study is currently required from a regulatory perspective. Although it is the current mainstay for the detection of nongenotoxic carcinogens, carcinogenicity studies are shown to have prominent weaknesses and are subject to ethical and scientific debate. A transition toward a mechanism-based weight-of-evidence approach is considered a requirement to enhance the prediction of carcinogenic potential for environmental (agro)chemicals. The resulting approach should make optimal use of innovative (computational) tools and be less animal demanding. To identify the various mode of actions (MOAs) underlying the nongenotoxic carcinogenic potential of agrochemicals, we conducted an extensive analysis of 411 unique agrochemicals that have been evaluated for carcinogenicity by the United States Environmental Protection Agency (US EPA) and the European Chemicals Agency (ECHA). About one-third of these substances could be categorized as nongenotoxic carcinogens with an average of approximately two tumor types per substance, observed in a variety of organs. For two-third of the tumor cases, an underlying MOA (network) could be identified. This analysis demonstrates that a limited set of MOA (networks) is underlying nongenotoxic carcinogenicity of agrochemicals, illustrating that the transition toward a MOA-driven approach appears manageable. Ultimately the approach should cover relevant MOAs and its associated key events; this will also facilitate the evaluation of the human relevance. This manuscript describes the results of the analysis while identifying knowledge gaps and necessities to achieve a mechanism-based weight-of-evidence approach.
Ergot and Ergot Alkaloids in Cereal Grains Intended for Animal Feeding Collected in Slovenia: Occurrence, Pattern and Correlations

This four-year study reports the occurrence of ergot alkaloids (EAs) in cereals intended for animal feeding collected in Slovenia. A total of 517 samples of cereals were analysed using liquid chromatography-tandem mass spectrometry for the presence of EAs. The sample set included wheat, rye, triticale, oat, spelt and barley. The study revealed that 17% of the analysed cereal samples were contaminated with at least one ergot alkaloid. EAs have two epimeric forms: -ine and -inine. The incidence rates of the -ine and -inine forms in the analysed samples were 16% and 15%, respectively. The highest contamination rates were observed in rye (54%), oat (50%) and spelt (30%), where the highest mean concentrations of total EAs were also determined (502 µg/kg, 594 µg/kg and 715 µg/kg, respectively). However, the highest concentrations of total EAs were found in wheat and rye (4217 µg/kg and 4114 µg/kg, respectively). The predominant EAs were ergometrine, ergosine and ergocristinine. The occurrence of six or more ergot alkaloids was observed in 49% of the positive samples. A weak correlation (p = 0.284) in the positive samples was found between the mass of sclerotia and the total concentrations of EAs using the Spearman correlation coefficient.
Retroinhibition par l'utp de la proteine carbamylphosphate synthetase-aspartate transcarbamylase chez saccharomyces cerevisiae

La levure saccharomyces cerevisiae est un organisme privilegie pour l'etude de mecanismes de regulation de proteines eucaryotiques. De nombreuses chaines de biosynthese sont regulees, en general au niveau de leur premiere activite enzymatique, par leurs produits finaux, par des mecanismes de retroinhibition ou activation. Ces proteines regulees sont tres souvent des enzymes allosteriques. En particulier, la proteine carbamylphosphate synthetase-aspartate transcarbamylase (cpsase-atcase) de la levure codee par le gene ura2, qui catalyse les deux premieres etapes de la chaine de biosynthese des pyrimidines, est retroinhibee par l'utp, produit final. Dans le but d'etudier ce type de regulation, nous avons developpe un systeme de selection in vivo de mutants du gene ura2 insensibles a la retroinhibition. 18 mutants ont ete selectionnes et sequences: 5 d'entre-eux sont localises dans le domaine cpsase et 13 dans le domaine atcase. Toutes les mutations sont ponctuelles et faux-sens et conduisent au changement d'un seul acide amine. Quelles que soient leurs positions dans la proteine, les deux activites cpsase et atcase ne sont plus retroinhibees, ce qui suggere l'existence d'un mecanisme commun de regulation de ces deux fonctions. Les mutations situees dans la partie atcase sont regroupees dans deux domaines bien definis sur le modele de l'atcase d'e. Coli qui pourraient correspondre soit au site de fixation de l'utp lui-meme, soit a des acides amines de transmission du signal du ou des sites de fixation de l'utp au site catalytique
Optical comparison between micro‐CT and OCT in imaging of marginal composite adaptation: Observational study

Dental composite is the most used aesthetic restorative biomaterial worldwide. However, it undergoes polymerisation shrinkage that could lead to loss of the interfacial seal between tooth and resin in some circumstances. This demands high‐resolution imaging technologies to detect these defects. This study carried out a comparison between microcomputed tomography (micro‐CT; Shimadzu, Japan) and swept‐source optical coherence tomography (SS‐OCT; Santec, Japan) in the detection of marginal adaptation defects at the tooth‐resin interface. Unlike in micro‐CT, it was possible to outline interfacial gaps along with tooth‐resin interfaces with SS‐OCT, which was attributed to the Fresnel diffraction of light. This in vitro comparison demonstrates SS‐OCT has great potential in dental imaging to effectively assess dental composite adaptation and marginal defects when high resolution is desired in real time.
A Guide to Fluorescence Lifetime Microscopy and Förster's Resonance Energy Transfer in Neuroscience

Fluorescence lifetime microscopy (FLIM) and Förster's resonance energy transfer (FRET) are advanced optical tools that neuroscientists can employ to interrogate the structure and function of complex biological systems in vitro and in vivo using light. In neurobiology they are primarily used to study protein‐protein interactions, to study conformational changes in protein complexes, and to monitor genetically encoded FRET‐based biosensors. These methods are ideally suited to optically monitor changes in neurons that are triggered optogenetically. Utilization of this technique by neuroscientists has been limited, since a broad understanding of FLIM and FRET requires familiarity with the interactions of light and matter on a quantum mechanical level, and because the ultra‐fast instrumentation used to measure fluorescent lifetimes and resonance energy transfer are more at home in a physics lab than in a biology lab. In this overview, we aim to help neuroscientists overcome these obstacles and thus feel more comfortable with the FLIM‐FRET method. Our goal is to aid researchers in the neuroscience community to achieve a better understanding of the fundamentals of FLIM‐FRET and encourage them to fully leverage its powerful ability as a research tool. Published 2020. U.S. Government.
Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks

In recent years, growing interest in deep learning neural networks has raised a question on how they can be used for effective processing of high-dimensional datasets produced by hyperspectral imaging (HSI). HSI, traditionally viewed as being within the scope of remote sensing, is used in non-invasive substance classification. One of the areas of potential application is forensic science, where substance classification on the scenes is important. An example problem from that area—blood stain classification—is a case study for the evaluation of methods that process hyperspectral data. To investigate the deep learning classification performance for this problem we have performed experiments on a dataset which has not been previously tested using this kind of model. This dataset consists of several images with blood and blood-like substances like ketchup, tomato concentrate, artificial blood, etc. To test both the classic approach to hyperspectral classification and a more realistic application-oriented scenario, we have prepared two different sets of experiments. In the first one, Hyperspectral Transductive Classification (HTC), both a training and a test set come from the same image. In the second one, Hyperspectral Inductive Classification (HIC), a test set is derived from a different image, which is more challenging for classifiers but more useful from the point of view of forensic investigators. We conducted the study using several architectures like 1D, 2D and 3D convolutional neural networks (CNN), a recurrent neural network (RNN) and a multilayer perceptron (MLP). The performance of the models was compared with baseline results of Support Vector Machine (SVM). We have also presented a model evaluation method based on t-SNE and confusion matrix analysis that allows us to detect and eliminate some cases of model undertraining. Our results show that in the transductive case, all models, including the MLP and the SVM, have comparative performance, with no clear advantage of deep learning models. The Overall Accuracy range across all models is 98–100% for the easier image set, and 74–94% for the more difficult one. However, in a more challenging inductive case, selected deep learning architectures offer a significant advantage; their best Overall Accuracy is in the range of 57–71%, improving the baseline set by the non-deep models by up to 9 percentage points. We have presented a detailed analysis of results and a discussion, including a summary of conclusions for each tested architecture. An analysis of per-class errors shows that the score for each class is highly model-dependent. Considering this and the fact that the best performing models come from two different architecture families (3D CNN and RNN), our results suggest that tailoring the deep neural network architecture to hyperspectral data is still an open problem.
Sigma-2 Receptor—A Potential Target for Cancer/Alzheimer’s Disease Treatment via Its Regulation of Cholesterol Homeostasis

The sigma receptors were classified into sigma-1 and sigma-2 receptor based on their different pharmacological profiles. In the past two decades, our understanding of the biological and pharmacological properties of the sigma-1 receptor is increasing; however, little is known about the sigma-2 receptor. Recently, the molecular identity of the sigma-2 receptor has been identified as TMEM97. Although more and more evidence has showed that sigma-2 ligands have the ability to treat cancer and Alzheimer’s disease (AD), the mechanisms connecting these two diseases are unknown. Data obtained over the past few years from human and animal models indicate that cholesterol homeostasis is altered in AD and cancer, underscoring the importance of cholesterol homeostasis in AD and cancer. In this review, based on accumulated evidence, we proposed that the beneficial roles of sigma-2 ligands in cancer and AD might be mediated by their regulation of cholesterol homeostasis.
Modified quadruple therapy or bismuth-containing quadruple therapy in the first-line treatment of Helicobacter Pylori in Turkey.

AIM Helicobacter pylori (H.pylori) eradication is still an important issue in countries with high antibiotic resistance. In this study, we aimed to compare the efficacy and safety of two bismuth-containing treatment modalities in H pylori treatment, in Turkey. MATERIAL AND METHOD Subjects with H pylori infection who were treated for the first time with either bismuth-containing quadruple therapy (pantoprazole 40 mg BID, tetracycline 500 mg QID, metronidazole 500 mg TID, bismuth subcitrate 262 mg QID daily) (BQT group) or modified quadruple therapy (pantoprazole 40 mg BID, amoxicillin 1 g BID, metronidazole 500 mg TID, bismuth subcitrate 262 mg QID daily) (MBQT group) for 14 days were compared retrospectively. The eradication success rate, adverse events related to the medications, and compliance were investigated. RESULTS Totally 128 patients in the BQT group and 102 patients in the MBQT group completed the treatment. Intention to treat analysis revealed 81.69% (95 % CI: 75.9-88.1%) and 88.23% (95 % CI: 80.8-93.9%) in BQT group and MBQT group, respectively. Per protocol analysis revealed 90.62% (95 % CI: 85.5-95.7%) and 95.74% (95 % CI: 91.5-99.8%) in BQT group and MBQT group, respectively. The overall rate of adverse events was significantly more common in the BQT group compared with the MBQT group (39.4% vs. 18.6%; p:0.001). Among the adverse events, nausea-vomiting and abdominal discomfort were significantly more common in the BQT group than the MBQT group (p:0.001). The adverse events were mild-moderate in both groups and any life-threatening adverse event was not determined in any of the patients. CONCLUSION Both bismuth-containing treatment regimens, quadruple therapy and modified quadruple therapy were highly effective and safe in H. pylori eradication in Turkey. Adverse events were lower in the modified quadruple therapy group. Modified quadruple therapy should be kept in mind in H. Pylori first-line therapy in regions with high resistance of metronidazole and clarithromycin treatment.