Miracle-dz/UniFAR-FTUs huggingface dataset:
D1/D5 Inverse Agonists Restore Striatal Cholinergic Interneuron Physiology in Dyskinetic Mice

In advanced stages of Parkinson's disease (PD), dyskinesia and motor fluctuations become seriously debilitating and therapeutic options become scarce. Aberrant activity of striatal cholinergic interneurons (SCIN) has been shown to be critical to PD and dyskinesia, but the systemic administration of cholinergic medications can exacerbate extrastriatal‐related symptoms. Thus, targeting the mechanisms causing pathological SCIN activity in severe PD with motor fluctuations and dyskinesia is a promising therapeutic alternative.
A Bayesian latent class model for predicting gestational age in health administrative data

Health administrative data are oftentimes of limited use in epidemiological study on drug safety in pregnancy, due to lacking information on gestational age at birth (GAB). Although several studies have proposed algorithms to estimate GAB using claims database, failing to incorporate the unique distributional shape of GAB, can introduce bias in estimates and subsequent modeling. Hence, we develop a Bayesian latent class model to predict GAB. The model employs a mixture of Gaussian distributions with linear covariates within each class. This approach allows modeling heterogeneity in the population by identifying latent subgroups and estimating class‐specific regression coefficients. We fit this model in a Bayesian framework conducting posterior computation with Markov Chain Monte Carlo methods. The method is illustrated with a dataset of 10,043 Rhode Island Medicaid mother–child pairs. We found that the three‐class and six‐class mixture specifications maximized prediction accuracy. Based on our results, Medicaid women were partitioned into three classes, featured by extreme preterm or preterm birth, preterm or” early” term birth, and” late” term birth. Obstetrical complications appeared to pose a significant influence on class‐membership. Altogether, compared to traditional linear models our approach shows an advantage in predictive accuracy, because of superior flexibility in modeling a skewed response and population heterogeneity.
Traumatic Autobiographical Memories: Preliminary fMRI Findings Among Men With Histories of Childhood Sexual Abuse

Childhood sexual abuse (CSA) is associated with autobiographical memory (AM) disturbances. AM is important for future thinking, sense of self, and coping with negative emotions. CSA is under-researched among men, with research examining long-term neural correlates limited even further. This study explored the neural correlates of re-experiencing traumatic/negative memories to examine the influence of CSA on AM into adulthood. Fifteen males who experienced CSA, with and without posttraumatic stress disorder (PTSD; CSA+PTSD, n = 6; CSA–PTSD, n = 9) and control males without CSA histories nor PTSD (n = 11) completed a script-driven imagery paradigm during functional magnetic resonance imaging (fMRI). Males with CSA histories, with and without PTSD, processed their negative autobiographical memories with less activation compared to control males. The CSA+PTSD group of males had less activation in the left superior occipital, left superior parietal and left parahippocampal gyri compared to control participants. The CSA–PTSD group had reduced activation in the same regions to a lesser extent. This study provides preliminary empirical evidence to suggest CSA impacts AM for traumatic experiences, and the impact is notable even for men who experienced CSA but do not have PTSD. This study highlights the need for more research with men who have experienced CSA, so that, we can fully understand the neural correlates of emotional memories, and better support the mental health and continued wellness of men who experienced CSA.
Evaluation of thresholding methods for activation likelihood estimation meta‐analysis via large‐scale simulations

In recent neuroimaging studies, threshold‐free cluster enhancement (TFCE) gained popularity as a sophisticated thresholding method for statistical inference. It was shown to feature higher sensitivity than the frequently used approach of controlling the cluster‐level family‐wise error (cFWE) and it does not require setting a cluster‐forming threshold at voxel level. Here, we examined the applicability of TFCE to a widely used method for coordinate‐based neuroimaging meta‐analysis, Activation Likelihood Estimation (ALE), by means of large‐scale simulations. We created over 200,000 artificial meta‐analysis datasets by independently varying the total number of experiments included and the amount of spatial convergence across experiments. Next, we applied ALE to all datasets and compared the performance of TFCE to both voxel‐level and cluster‐level FWE correction approaches. All three multiple‐comparison correction methods yielded valid results, with only about 5% of the significant clusters being based on spurious convergence, which corresponds to the nominal level the methods were controlling for. On average, TFCE's sensitivity was comparable to that of cFWE correction, but it was slightly worse for a subset of parameter combinations, even after TFCE parameter optimization. cFWE yielded the largest significant clusters, closely followed by TFCE, while voxel‐level FWE correction yielded substantially smaller clusters, showcasing its high spatial specificity. Given that TFCE does not outperform the standard cFWE correction but is computationally much more expensive, we conclude that employing TFCE for ALE cannot be recommended to the general user.
Is the degree of physiological bone remodeling a predictive factor for peri‐implantitis?

Abstract Background The amount of initial physiological bone remodeling (IPBR) after implant placement varies and the ways it may play a role in peri‐implantitis development remains unknown. The aim of this retrospective study was to investigate the association between the amount of IPBR during the first year of implant placement and incidence of peri‐implantitis as well as the pattern of progressive bone loss. Methods Clinical and radiographic documentation of implants at the time of implant placement (T0), 1 year ± 6 months after crown placement (T1), and at a ≥2‐year follow‐up from implant placement (T2) were retrospectively collected. IPBR was defined as the bone loss occurring from implant placement to the end of the bone remodeling (T1). Cases were grouped into those diagnosed with (test) or without peri‐implantitis (PIm) (control). Linear regression model under generalized estimation equation approach was estimated to assess correlation between marginal bone loss (MBL) rates in both periods (T1‐T0) and (T2‐T1). Receiver operating characteristics curve was estimated to explore an optimal cut‐off point of T1‐T0 MBL to discriminate between PIm and no‐PIm implants. Results A total of 45 patients receiving 57 implants without PIm and 40 with PIm were included. There were no associations between PIm and IPBR (p > 0.05), nor between BML of (T2‐T1) and (T1‐T0). However, arch and total follow‐up showed significant influence on the probability of PIm. Splinted implants showed an MBL rate of 0.60‐mm/year higher than non‐splinted implants (p < 0.001) from T1 to T2. Conclusion No statistically significant association was found between IPBR and incidence of peri‐implantitis.
Time-resolved CMOS SPAD arrays: architectures, applications and perspectives

SPADs (Single-Photon Avalanche Diodes) are the viable photodetectors for most single-photon counting and photontiming applications. Some custom SPAD and many complementary metal-oxide semiconductor (CMOS) SPADs have been reported in literature, with quite different performance and some excelling in just few of them, but often at different operating conditions. Proper performance assessment can be done through figures of merit able to summarize the typical SPAD performance (i.e. photon detection efficiency, dark counting rate, afterpulsing probability, hold-off time, and timing jitter) and to identify a proper metric for SPAD comparisons, when used either as single pixel detectors or in imaging arrays. We present a comparison among some imager architectures and SPAD detectors and arrays in either photon-counting, timing, or imaging applications.
Novel approach to semi‐quantification of tracer accumulation in dopamine transporter scan

Abstract Purpose Accurate tracer accumulation evaluation is difficult owing to the partial volume effect (PVE). We proposed a novel semi‐quantitative approach for measuring the accumulation amount by examining the approximate image. Using a striatal phantom, we verified the validity of a newly proposed method to accurately evaluate the tracer accumulations in the caudate and putamen separately. Moreover, we compared the proposed method with the conventional methods. Methods The left and right caudate/putamen regions and the whole brain region as background were identified in computed tomography (CT) images obtained by single‐photon emission computed tomography (SPECT)/CT and acquired the positional information of each region. SPECT‐like images were generated by assigning assumed accumulation amounts to each region. The SPECT‐like image, approximated to the actual measured SPECT image, was examined by changing the assumed accumulation amounts assigned to each region. When the generated SPECT‐like image most approximated the actual measured SPECT image, the accumulation amounts assumed were determined as the accumulation amounts in each region. We evaluated the correlation between the count density calculated by the proposed method and the actual count density of the 123I solution filled in the phantom. Conventional methods (CT‐guide method, geometric transfer matrix [GTM] method, region‐based voxel‐wise [RBV] method, and Southampton method) were also evaluated. The significance of differences between the correlation coefficients of various methods (except the Southampton method) was evaluated. Results The correlation coefficients between the actual count density and the SPECT count densities were 0.997, 0.973, 0.951, 0.950, and 0.996 for the proposed method, CT‐guide method, GTM method, RBV method, and Southampton method, respectively. The correlation of the proposed method was significantly higher than those of the other methods. Conclusions The proposed method could calculate accurate accumulation amounts in the caudate and putamen separately, considering the PVE.
Pneumococcal Phasevarions Control Multiple Virulence Traits, Including Vaccine Candidate Expression

S. pneumoniae is the world’s foremost bacterial pathogen. S. pneumoniae encodes a phasevarion (phase-variable regulon), that results in differential expression of multiple genes. Previous work demonstrated that the pneumococcal SpnIII phasevarion switches between six different expression states, generating six unique phenotypic variants in a pneumococcal population. ABSTRACT Streptococcus pneumoniae is the most common cause of bacterial illness worldwide. Current vaccines based on the polysaccharide capsule are only effective against a limited number of the >100 capsular serotypes. A universal vaccine based on conserved protein antigens requires a thorough understanding of gene expression in S. pneumoniae. All S. pneumoniae strains encode the SpnIII Restriction-Modification system. This system contains a phase-variable methyltransferase that switches specificity, and controls expression of multiple genes—a phasevarion. We examined the role of this phasevarion during pneumococcal pathobiology, and determined if phase variation resulted in differences in expression of currently investigated conserved protein antigens. Using locked strains that express a single methyltransferase specificity, we found differences in clinically relevant traits, including survival in blood, and adherence to and invasion of human cells. We also observed differences in expression of numerous proteinaceous vaccine candidates, which complicates selection of antigens for inclusion in a universal protein-based pneumococcal vaccine. This study will inform vaccine design against S. pneumoniae by ensuring only stably expressed candidates are included in a rationally designed vaccine. IMPORTANCE S. pneumoniae is the world’s foremost bacterial pathogen. S. pneumoniae encodes a phasevarion (phase-variable regulon), that results in differential expression of multiple genes. Previous work demonstrated that the pneumococcal SpnIII phasevarion switches between six different expression states, generating six unique phenotypic variants in a pneumococcal population. Here, we show that this phasevarion generates multiple phenotypic differences relevant to pathobiology. Importantly, expression of conserved protein antigens varies with phasevarion switching. As capsule expression, a major pneumococcal virulence factor, is also controlled by the phasevarion, our work will inform the selection of the best candidates to include in a rationally designed, universal pneumococcal vaccine.
Multiple socioeconomic circumstances and trajectories of fruit and vegetable consumption: the Helsinki Health Study

Aims: Fruit and vegetable consumption is essential in disease prevention. Socioeconomic differences in consumption have been observed but evidence from longitudinal studies incorporating multiple socioeconomic indicators is lacking. We examined long-term fruit and vegetable consumption trajectories and multiple socioeconomic circumstances as their determinants. Methods: We used survey data from the Helsinki Health Study (phase 1 in 2000–2002, N=8960, response rate 67%; phases 2–4 in 2007, 2012 and 2017) among initially 40- to 60-year-old employees of City of Helsinki, Finland. Fruit and vegetable consumption was measured by a food frequency questionnaire and consumption times per month were calculated. Childhood (parental education, economic difficulties), conventional (own education, occupational class, household income) and material (housing tenure, wealth, current economic difficulties) socioeconomic circumstances were included. We used group-based trajectory modelling for identifying fruit and vegetable consumption trajectories and multinomial logistic regression for examining associations between socioeconomic circumstances and the trajectories. Results: Four fruit and vegetable consumption trajectories were identified: increasing higher (12%), decreasing higher (10%), stable moderate (43%) and stable low (35% of participants). Childhood, conventional and material socioeconomic circumstances were all associated with the trajectories: belonging to a lower socioeconomic group was associated with belonging to the stable low and moderate trajectories. In multivariate models, the strongest associations were found for occupational class and household wealth. Conclusions: Disadvantageous childhood and adulthood socioeconomic circumstances were associated with lower long-term fruit and vegetable consumption. Socioeconomic circumstances should be considered in attempts to promote fruit and vegetable consumption, and people with disadvantageous circumstances need to be targeted in future interventions.
Scalable manufacturing of clinical‐grade differentiated cardiomyocytes derived from human‐induced pluripotent stem cells for regenerative therapy

Basic research on human pluripotent stem cell (hPSC)‐derived cardiomyocytes (CMs) for cardiac regenerative therapy is one of the most active and complex fields to achieve this alternative to heart transplantation and requires the integration of medicine, science, and engineering. Mortality in patients with heart failure remains high worldwide. Although heart transplantation is the sole strategy for treating severe heart failure, the number of donors is limited. Therefore, hPSC‐derived CM (hPSC‐CM) transplantation is expected to replace heart transplantation. To achieve this goal, for basic research, various issues should be considered, including how to induce hPSC proliferation efficiently for cardiac differentiation, induce hPSC‐CMs, eliminate residual undifferentiated hPSCs and non‐CMs, and assess for the presence of residual undifferentiated hPSCs in vitro and in vivo. In this review, we discuss the current stage of resolving these issues and future directions for realizing hPSC‐based cardiac regenerative therapy.
Simulated Leaching of Foliar Applied Copper Bactericides on the Soil Microbiome Utilizing Various Beta Diversity Resemblance Measurements

Nanotechnology-based elemental composites have gained popularity for their potential applications in plant disease management due to their enhanced antimicrobial properties. However, little is known about their potential impact on the environment. ABSTRACT Copper bactericides are routinely used to control Xanthomonas perforans (XP), causal agent of bacterial spot of tomato. Given the widespread tolerance to copper in XP strains in FL, USA, nanotechnology-based elemental composites have gained interest for their potential applications in agriculture in part due to their enhanced antimicrobial properties and toxicity to copper-tolerant strains. However, little is known about the potential impact of conventional copper bactericides as well as nano-based elemental composites on soil microbial communities, as determined by high-throughput sequencing of the 16S rDNA. We compared the effects of 2 and 200 μg/mL of core-shell (CS), a metallic copper composite, and a conventional copper bactericide + mancozeb (Cu+Man) on the soil microbiome. These treatments were compared to three controls, the microbial profile of the soil prior to application of copper products, a water application, and spiking the soil with a soilborne phytobacterium, Ralstonia solanacearum (RS). The RS treatment was included to determine if downstream analysis could detect the artificial inoculation. Utilizing multiple β diversity measurements, each emphasizing various tenets of ecology, provided a greater perspective of the effects the treatments had on the microbiome. Analysis of HTS data revealed that the two treatments containing field applied rates of metallic copper, CS 200 and Cu+Man, had the largest impact on the soil microbiome at seven-days posttreatment compared to water. However, we simulated field applied rates of CS 200 entering the soil by treating soil with CS 2 and determined this concentration had a negligible effect on the soil microbiome. IMPORTANCE Nanotechnology-based elemental composites have gained popularity for their potential applications in plant disease management due to their enhanced antimicrobial properties. However, little is known about their potential impact on the environment. Foliar applications of nano metallic composites upon leaching into the soil have the potential to impact soil microbial populations that in turn influence soil health. Utilizing multiple β diversity measurements, high-throughput sequencing analysis revealed that field applied rates of metallic copper (200 μg/mL) from an advanced copper composite (core-shell [CS]) and a conventional copper bactericide in combination with mancozeb had the largest impact on the soil microbiome compared to water and nontreated control. To simulate leaching from the leaf surface, a lower concentration (2 μg/mL) of CS was also applied to the soil and had a negligible effect on the soil microbiome. Thus, field applied rates of CS may have a minimal effect on soil microbial communities.
Metabolic Synergy between Human Symbionts Bacteroides and Methanobrevibacter

The human gut functions through a complex system of interactions between the host human tissue and the microbes which inhabit it. These diverse interactions are difficult to model or examine under controlled laboratory conditions. ABSTRACT Trophic interactions between microbes are postulated to determine whether a host microbiome is healthy or causes predisposition to disease. Two abundant taxa, the Gram-negative heterotrophic bacterium Bacteroides thetaiotaomicron and the methanogenic archaeon Methanobrevibacter smithii, are proposed to have a synergistic metabolic relationship. Both organisms play vital roles in human gut health; B. thetaiotaomicron assists the host by fermenting dietary polysaccharides, whereas M. smithii consumes end-stage fermentation products and is hypothesized to relieve feedback inhibition of upstream microbes such as B. thetaiotaomicron. To study their metabolic interactions, we defined and optimized a coculture system and used software testing techniques to analyze growth under a range of conditions representing the nutrient environment of the host. We verify that B. thetaiotaomicron fermentation products are sufficient for M. smithii growth and that accumulation of fermentation products alters secretion of metabolites by B. thetaiotaomicron to benefit M. smithii. Studies suggest that B. thetaiotaomicron metabolic efficiency is greater in the absence of fermentation products or in the presence of M. smithii. Under certain conditions, B. thetaiotaomicron and M. smithii form interspecies granules consistent with behavior observed for syntrophic partnerships between microbes in soil or sediment enrichments and anaerobic digesters. Furthermore, when vitamin B12, hematin, and hydrogen gas are abundant, coculture growth is greater than the sum of growth observed for monocultures, suggesting that both organisms benefit from a synergistic mutual metabolic relationship. IMPORTANCE The human gut functions through a complex system of interactions between the host human tissue and the microbes which inhabit it. These diverse interactions are difficult to model or examine under controlled laboratory conditions. We studied the interactions between two dominant human gut microbes, B. thetaiotaomicron and M. smithii, using a seven-component culturing approach that allows the systematic examination of the metabolic complexity of this binary microbial system. By combining high-throughput methods with machine learning techniques, we were able to investigate the interactions between two dominant genera of the gut microbiome in a wide variety of environmental conditions. Our approach can be broadly applied to studying microbial interactions and may be extended to evaluate and curate computational metabolic models. The software tools developed for this study are available as user-friendly tutorials in the Department of Energy KBase.
Supervision, Condition Monitoring and Fault Diagnosis System in a Hybrid Renewable Energy Systems (HRES) Laboratory

Hybrid renewable energy is a good alternative to get a reliable power supply; this idea allows local resources optimization, but, its ideal arrangement depends on available resources and final users’ needs. To explore and evaluates possible solutions, the Institute for Energy Engineering of the Universitat Politècnica de València has assembled different renewable sources and energy storage in a laboratory of distributed renewable resources LabDER. This paper presents the progress in the supervisory system that includes condition monitoring and fault diagnosis.