Miracle-dz/UniFAR-FTUs huggingface dataset:
Stimulus complexity shapes response correlations in primary visual cortex

Significance Whether the population activity in neuronal networks can be understood as the sum of individual activities or neurons jointly determine the state of populations is a fundamental question of neuroscience. Spike count correlations reflect coordination between pairs of neurons and therefore can be regarded as a signature of joint computations. So far, a majority of experimental and theoretical analyses considered these correlations noise and ignored stimulus-dependent aspects. Based on theoretical considerations, we argue that spike count correlations are stimulus dependent and variations in their structure can be predicted by stimulus content. Recording the activity of neurons from primary visual cortex in task-engaged monkeys, we confirm these predictions. These results provide insight into the computations performed by populations of cortical neurons. Spike count correlations (SCCs) are ubiquitous in sensory cortices, are characterized by rich structure, and arise from structured internal dynamics. However, most theories of visual perception treat contributions of neurons to the representation of stimuli independently and focus on mean responses. Here, we argue that, in a functional model of visual perception, featuring probabilistic inference over a hierarchy of features, inferences about high-level features modulate inferences about low-level features ultimately introducing structured internal dynamics and patterns in SCCs. Specifically, high-level inferences for complex stimuli establish the local context in which neurons in the primary visual cortex (V1) interpret stimuli. Since the local context differentially affects multiple neurons, this conjecture predicts specific modulations in the fine structure of SCCs as stimulus identity and, more importantly, stimulus complexity varies. We designed experiments with natural and synthetic stimuli to measure the fine structure of SCCs in V1 of awake behaving macaques and assessed their dependence on stimulus identity and stimulus statistics. We show that the fine structure of SCCs is specific to the identity of natural stimuli and changes in SCCs are independent of changes in response mean. Critically, we demonstrate that stimulus specificity of SCCs in V1 can be directly manipulated by altering the amount of high-order structure in synthetic stimuli. Finally, we show that simple phenomenological models of V1 activity cannot account for the observed SCC patterns and conclude that the stimulus dependence of SCCs is a natural consequence of structured internal dynamics in a hierarchical probabilistic model of natural images.
Markhasphingolipid A, new phytosphingolipid from the leaves of Markhamia stipulata var. canaense V.S. Dang

Abstract From the leaves of Markhamia stipulata var. canaense V.S. Dang, one new phytosphingolipid, named markhasphingolipid A (6) together with five known compounds, 4’,7-O-dimethylapigenin (1), narigenin (2), tectoquinone (3), mollic acid (4), 1-hexadecanoyl-sn-glycerol (5) were classified by various chromatographic methods. Their structures were designated by IR, UV, HR-ESI-MS, HR-ESI-MS/MS and NMR experiments. All compounds were recognized for the first time from this species. The cytotoxicity of all n-hexane fractions and isolated compounds (5 & 6) against three human cancer cell lines (HeLa, HepG2, and MCF-7) were evaluated by SRB assay. All n-hexane fractions expressed cytotoxic effect on three tested cancer cell lines (at the concentration of 100 μg/mL, percent of cytotoxicity ranged from 55.81% to 95.83%) as well as compound 5 (IC50 ranged from 48.51 to 63.30 μM) whereas fraction H.I and compound 6 did not show activity.
Neural mechanisms of training an auditory event‐related potential task in a brain–computer interface context

Effective use of brain–computer interfaces (BCIs) typically requires training. Improved understanding of the neural mechanisms underlying BCI training will facilitate optimisation of BCIs. The current study examined the neural mechanisms related to training for electroencephalography (EEG)‐based communication with an auditory event‐related potential (ERP) BCI. Neural mechanisms of training in 10 healthy volunteers were assessed with functional magnetic resonance imaging (fMRI) during an auditory ERP‐based BCI task before (t1) and after (t5) three ERP‐BCI training sessions outside the fMRI scanner (t2, t3, and t4). Attended stimuli were contrasted with ignored stimuli in the first‐level fMRI data analysis (t1 and t5); the training effect was verified using the EEG data (t2‐t4); and brain activation was contrasted before and after training in the second‐level fMRI data analysis (t1 vs. t5). Training increased the communication speed from 2.9 bits/min (t2) to 4 bits/min (t4). Strong activation was found in the putamen, supplementary motor area (SMA), and superior temporal gyrus (STG) associated with attention to the stimuli. Training led to decreased activation in the superior frontal gyrus and stronger haemodynamic rebound in the STG and supramarginal gyrus. The neural mechanisms of ERP‐BCI training indicate improved stimulus perception and reduced mental workload. The ERP task used in the current study showed overlapping activations with a motor imagery based BCI task from a previous study on the neural mechanisms of BCI training in the SMA and putamen. This suggests commonalities between the neural mechanisms of training for both BCI paradigms.
Theta resting EEG in the right TPJ is associated with individual differences in implicit intergroup bias

Abstract Why are some people more biased than others in their implicit evaluations during social interaction? The dispositional determinants of individual differences in implicit intergroup bias are poorly understood. Here, we explored whether such variability might be explained by stable neural traits. For that purpose, we used the source‐localized resting electroencephalograms of 83 members of naturalistic social groups to explain their bias in an in‐/outgroup implicit association test. Lower levels of resting theta current density in the right temporo‐parietal junction (TPJ) were associated with stronger implicit intergroup bias and explained unique variability in bias beyond relevant personality questionnaires. These findings demonstrate the added value of the neural trait approach in predicting inter‐individual differences in implicit social cognition. Given that low levels of resting theta current density during wakefulness likely reflect increased cortical activation, our results suggest that individuals with an efficiently working right TPJ possess capacities to mediate specific cognitive processes that predispose them towards stronger implicit intergroup bias. As the human species has evolved living in distinct social groups, the capacity to quickly differentiate friend from foe became highly adaptive and might thus constitute an essential part of human nature.
Diagnostic accuracy of saline contrast sonohysterography in detecting endometrial polyps in women with postmenopausal bleeding: systematic review and meta‐analysis

In women with postmenopausal bleeding, endometrial polyps are a frequent finding and the risk of a focal (pre)malignancy in a polyp is up to 6%. Because of this reported risk, the detection of polyps in these women, preferably by a minimally invasive method, is important. The aim of this systematic review was to assess the accuracy of saline contrast sonohysterography (SCSH) for diagnosis of endometrial polyps in women with postmenopausal bleeding.
Learning Spatio Temporal Tactile Features with a ConvLSTM for the Direction Of Slip Detection

Robotic manipulators have to constantly deal with the complex task of detecting whether a grasp is stable or, in contrast, whether the grasped object is slipping. Recognising the type of slippage—translational, rotational—and its direction is more challenging than detecting only stability, but is simultaneously of greater use as regards correcting the aforementioned grasping issues. In this work, we propose a learning methodology for detecting the direction of a slip (seven categories) using spatio-temporal tactile features learnt from one tactile sensor. Tactile readings are, therefore, pre-processed and fed to a ConvLSTM that learns to detect these directions with just 50 ms of data. We have extensively evaluated the performance of the system and have achieved relatively high results at the detection of the direction of slip on unseen objects with familiar properties (82.56% accuracy).
Metabolic Profiling of Dietary Polyphenols and Methylxanthines in Normal and Malignant Mammary Tissues from Breast Cancer Patients.

SCOPE Dietary polyphenols may protect against breast cancer. However, it is unknown whether polyphenols reach human malignant breast tumors in molecular forms and(or) at concentrations likely to act against cancer. METHODS AND RESULTS Ninteen breast cancer patients consumed three capsules daily from biopsy-confirmed diagnosis to surgery (6 ± 2 days). The capsules contained pomegranate, orange, lemon, olive, cocoa, and grapeseed extracts plus resveratrol, providing 37 different phenolics (473.7 mg), theobromine and caffeine (19.7 mg). A total of 101 metabolites are identified in urine, 69 in plasma, 39 in normal (NT), and 33 in malignant (MT) tissues by UPLC-ESI-QTOF-MS. Eight control patients did not consume extracts. Phenolic-derived metabolites in MT and NT are mainly glucuronidated and(or) sulfated. Some representative metabolites detected in MT (median and range, pmol g-1 ) are urolithin-A-3-O-glucuronide (26.2; 3.2-66.5), 2,5-dihydroxybenzoic acid (40.2; 27.7-52.2), resveratrol-3-O-sulfate (86.4; 7.8-224.4), dihydroresveratrol-3-O-glucuronide (109.9; 10.3-229.4), and theobromine (715.0; 153.9-3,216). Metabolites, as detected in breast tissues, do not exert antiproliferative or estrogenic/antiestrogenic activities in MCF-7 breast cancer cells. CONCLUSION This is the first study that describes the metabolic profiling of dietary phenolics and methylxanthines in MT and NT comprehensively. Although phase-II conjugation might hamper a direct anticancer activity, long-term tumor-senescent chemoprevention cannot be discarded.
Health-related quality of life loss associated with first-time stroke

Objectives This study aimed to quantify health-related quality of life (HRQoL) loss associated with first episode of stroke by comparing patient-reported HRQoL before and after stroke onset. The impact of stroke in local population was also evaluated by comparing the pre- and post-stroke HRQoL with that of the general population. Methods The HRQoL of stroke survivors was assessed with the EQ-5D-3L index score at recruitment, for recalled pre-stroke HRQoL, and at 3 and 12 month post-stroke. Change in HRQoL from pre-stroke to 3 and 12 month was self-reported by 285 and 238 patients, respectively. Mean EQ index score at each time point (baseline: 464 patients; 3 month post-stroke: 306 patients; 12 month post-stroke: 258 patients) was compared with published population norms for EQ-5D-3L. Results There was a significant decrease in HRQoL at 3 (0.25) and 12 month (0.09) post-stroke when compared to the retrospectively recalled patients’ mean pre-stroke HRQoL level (0.87). The reduction at 3 month was associated with the reduction in all EQ-5D-3L health dimensions; reductions remaining at 12 month were limited to dimensions of mobility, self-care, usual activities, and anxiety/depression. Stroke patients had a lower mean EQ index than the general population by 0.07 points pre-stroke (0.87 vs. 0.94), 0.33 points at 3 month (0.61 vs. 0.94) and 0.18 points at 12 month (0.76 vs. 0.94) post-stroke. Conclusions Stroke has a substantial impact on HRQoL in Singapore, especially in the first three months post-stroke. Compared to the general population, stroke survivors have lower HRQoL even before stroke onset. This pre-stroke deficit in HRQoL should be taken into account when quantifying health burden of stroke or setting goals for stroke rehabilitation.
Evaluation of the 15 and 24-loci MIRU-VNTR genotyping tools with spoligotyping in the identification of Mycobacterium tuberculosis strains and their genetic diversity in molecular epidemiology studies

Abstract Background: The transmission dynamics of Mycobacterium tuberculosis (Mtb) using various genotyping tools has been studied globally and a particular tool for genotyping Mtb is the mycobacterial interspersed repetitive units-variable number tandem repeats (MIRU-VNTR). Tuberculosis (TB) remains an important public health problem worldwide and Sri Lanka being a country of tourist destination; because of major development projects undergoing, it has a high proportion of tourists and immigrants from Asia and Europe that are characterized with highest TB incidences and drug-resistant clinical isolates. Hence, in order to address the question of Mtb genetic diversity, we investigated the discriminatory power of both MIRU-VNTR typing of 15 and 24 loci with spoligotyping to differentiate Mtb isolates. Method: Acid-fast bacilli positive sputum samples (n = 150) from first visit patients were collected. Decontamination of sputum and extraction of genomic DNA were carried out using standard techniques. The isolates were characterized by MIRU-VNTR for both the 15 and 24 loci and spoligotyping. Results: In our study population, MIRU-VNTR 15 and 24 loci did not show a significant difference among the identified M. tuberculosis strains. However, MIRU 24 loci yielded an additional strain LAM, which is of T1 origin. 15 loci strain grouping had more clusters of strains grouped together while 24 loci differentiated the same cluster of strains into distinct strain types. Conclusion: We conclude that the use of 15-locus MIRU-VNTR typing is sufficient for a first-line epidemiological study to genotype M. tuberculosis, but the additional discriminatory power of 24 loci MIRU-VNTR has been able to differentiate samples within highly homologous groups.
Cell-Proliferation Imaging for Monitoring Response to CDK4/6 Inhibition Combined with Endocrine-Therapy in Breast Cancer: Comparison of [18F]FLT and [18F]ISO-1 PET/CT

Purpose: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors in combination with endocrine-therapy have emerged as an important regimen of care for estrogen receptor (ER)-positive metastatic breast cancer, although identifying predictive biomarkers remains a challenge. We assessed the ability of two PET-proliferation tracers, [18F]FLT and [18F]ISO-1, for evaluating response to CDK4/6-inhibitor (palbociclib) and ER-antagonist (fulvestrant). Experimental Design: To determine the effect of CDK4/6 inhibition combined with estrogen-blockade, we assessed cell proliferation in six breast cancer cell lines after 1, 3, and 6 days of treatment with palbociclib and/or fulvestrant. These data were correlated to in vitro radiotracer assays and results were verified by longitudinal [18F]FLT and [18F]ISO-1 micro-PET imaging performed in MCF7 tumor-bearing mice. Results: All palbociclib-sensitive cell lines showed decreased [18F]FLT accumulation and S-phase depletion after treatment, with both measures augmented by combination therapy. In contrast, these cells showed changes in [18F]ISO-1 analogue-binding and G0 arrest only after prolonged treatment. MicroPET imaging of MCF7 xenografts showed a significant decrease in [18F]FLT but no changes in [18F]ISO-1 uptake in all treated mice on day 3. On day 14, however, mice treated with combination therapy showed a significant decrease in [18F]ISO-1, corresponding to G0 arrest, while maintaining reduced [18F]FLT uptake, which corresponded to S-phase depletion. Conclusions: Our data suggest complementary roles of [18F]FLT and [18F]ISO-1 PET in evaluating tumor-proliferation after combined CDK4/6 inhibitor and endocrine therapy in breast cancer. [18F]FLT is more sensitive to immediate changes in S-phase, whereas [18F]ISO-1 can assess more delayed changes related to cell-cycle arrest and transition to G0 quiescence from combination therapy. These data suggest a potential role for early prediction of long-term response using these imaging biomarkers.
Twenty‐four‐hour motor activity and body temperature patterns suggest altered central circadian timekeeping in Smith–Magenis syndrome, a neurodevelopmental disorder

Smith–Magenis syndrome (SMS) is a contiguous gene syndrome linked to interstitial microdeletion, or mutation of RAI1, within chromosome 17p11.2. Key behavioral features of SMS include intellectual disability, sleep‐disturbances, maladaptive, aggressive and self‐injurious behaviors, hyperactivity, and sudden changes in mood. A distinguishing feature of this syndrome is an inverted pattern of melatonin characterized by elevated daytime and low nighttime melatonin levels. As the central circadian clock controls the 24‐hr rhythm of melatonin, we hypothesized that the clock itself may contribute to the disrupted pattern of melatonin and sleep. In this report, 24‐hr patterns of body temperature, a surrogate marker of clock‐timing, and continuous wrist activity were collected to examine the links between body temperature, sleep behavior, and the circadian clock. In addition, age‐dependent changes in sleep behavior were explored. Actigraphy‐estimated sleep time for SMS was 1 hr less than expected across all ages studied. The timing of the 24‐hr body temperature (Tb‐24) rhythm was phase advanced, but not inverted. Compared to sibling (SIB) controls, the SMS group had less total night sleep, lower sleep efficiency, earlier sleep onset, earlier final awake times, increased waking after sleep onset (WASO), and increased daytime nap duration. The timing of wake onset varied with age, providing evidence of ongoing developmental sleep changes from childhood through adolescence. Clarification of the circadian and developmental factors that contribute to the disrupted and variable sleep patterns in this syndrome will be helpful in identifying more effective individualized treatments.
Phosphorus and ammonium removal characteristics from aqueous solutions by a newly isolated plant growth-promoting bacterium

ABSTRACT An indigenous plant growth-promoting bacterium isolated from Peganum Harmala rhizosphere in the arid ecosystem was found to solubilize and accumulate phosphates. This isolate was identified as Pseudomonas sp. (PHR6) by partial 16S rRNA gene sequence analysis. Controlled batch experiments on nutrients removal by this isolate in mineral medium showed relatively high efficiencies after 24 h of aerobic incubation with average values of 117.59 and 335.38 mg gVSS−1 for phosphorus (P-PO4) and nitrogen (N-NH4), respectively. Furthermore, the strain performed heterotrophic nitrification ranging from 48.81% to 84.24% of the total removed nitrogen. On the other hand, the experimental results showed that a short idle period (24 h) significantly enhanced P accumulation (up to 95%) and N assimilation (up to 50%) of the total removed amounts. However, long idle period (20 days) revealed firstly aerobic phosphorous release phase succeeded by another removal one within 24 h of incubation. Overall, the idle treatment enhances P removal efficiency from the mineral liquid medium without significant effects on N-NH4 removal performance. The isolated strain showed also significant nutrient removal ability from synthetic wastewater providing an accumulated fraction of 98% from the total removed phosphorus amount. This study highlights the potential contribution of the selected rhizobacterium PHR6 to both environmental nutrient recycling and pollution control especially regarding phosphorus. GRAPHICAL ABSTRACT
Immediate Intervention Effects of Standardized Multicomponent Group Interventions on People with Cognitive Impairment: A Systematic Review

Background: There is no curative medical treatment for dementia. Therefore, researchers turned their attention to non-pharmacological treatment approaches. Many reviews analyzed the efficacy of single-component interventions, but there has been no systematic review of multicomponent interventions so far. Objective: The aim was to systematically review studies using standardized multicomponent group interventions for persons with dementia or persons with mild cognitive impairment (MCI) and to analyze their immediate intervention effects. Methods: The databases PubMed, PsycINFO, PSYNDEX, and CINAHL were systematically searched. We included randomized controlled trials with people with MCI or dementia, which implemented interventions with at least two components that targeted different outcome domains. Additionally, the intervention had to be standardized and in a group setting. Results: Nine studies met the inclusion criteria with a total sample size of N = 513 participants. Six studies applied two, two studies applied three, and one study applied four components. Four studies, which combined at least a physical and a cognitive component, had a positive effect on non-cognitive symptoms of dementia. Two of these interventions additionally had a positive effect on cognitive abilities. One study reported a positive effect on activities of daily living and another study showed an effect on quality of life. Conclusion: In spite of the heterogeneity of the studies, multicomponent interventions suggest a positive effect on non-cognitive symptoms, especially the combination of cognitive and physical components. Single studies had also an effect on additional outcome domains. By trend the effects are dependent on application rate and used assessments.
RGB-D Object Recognition Using Multi-Modal Deep Neural Network and DS Evidence Theory

With the development of low-cost RGB-D (Red Green Blue-Depth) sensors, RGB-D object recognition has attracted more and more researchers’ attention in recent years. The deep learning technique has become popular in the field of image analysis and has achieved competitive results. To make full use of the effective identification information in the RGB and depth images, we propose a multi-modal deep neural network and a DS (Dempster Shafer) evidence theory based RGB-D object recognition method. First, the RGB and depth images are preprocessed and two convolutional neural networks are trained, respectively. Next, we perform multi-modal feature learning using the proposed quadruplet samples based objective function to fine-tune the network parameters. Then, two probability classification results are obtained using two sigmoid SVMs (Support Vector Machines) with the learned RGB and depth features. Finally, the DS evidence theory based decision fusion method is used for integrating the two classification results. Compared with other RGB-D object recognition methods, our proposed method adopts two fusion strategies: Multi-modal feature learning and DS decision fusion. Both the discriminative information of each modality and the correlation information between the two modalities are exploited. Extensive experimental results have validated the effectiveness of the proposed method.