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Meniere disease is a complex inner ear disorder with significant familial aggregation. A differential prevalence of familial MD (FMD) has been reported, being 9–10% in Europeans compared to 6% in East Asians. A broad genetic heterogeneity in FMD has been described, OTOG being the most common mutated gene, with a compound heterozygous recessive inheritance. We hypothesize that an OTOG-related founder effect may explain the higher prevalence of FMD in the European population. Therefore, the present study aimed to compare the allele frequency (AF) and distribution of OTOG rare variants across different populations. For this purpose, the coding regions with high constraint (low density of rare variants) were retrieved in the OTOG coding sequence in Non-Finnish European (NFE).. Missense variants (AF < 0.01) were selected from a 100 FMD patient cohort, and their population AF was annotated using gnomAD v2.1. A linkage analysis was performed, and odds ratios were calculated to compare AF between NFE and other populations. Thirteen rare missense variants were observed in 13 FMD patients, with 2 variants (rs61978648 and rs61736002) shared by 5 individuals and another variant (rs117315845) shared by two individuals. The results confirm the observed enrichment of OTOG rare missense variants in FMD. Furthermore, eight variants were enriched in the NFE population, and six of them were in constrained regions. Structural modeling predicts five missense variants that could alter the otogelin stability. We conclude that several variants reported in FMD are in constraint regions, and they may have a founder effect and explain the burden of FMD in the European population. [ABSTRACT FROM AUTHOR]

Meniere disease (MD) is a debilitating disorder of the inner ear defined by sensorineural hearing loss (SNHL) associated with episodes of vertigo and tinnitus. Severe tinnitus, which occurs in around 1% of patients, is a multiallelic disorder associated with a burden of rare missense single nucleotide variants in synaptic genes. Rare structural variants (SVs) may also contribute to MD and severe tinnitus. In this study, we analyzed exome sequencing data from 310 MD Spanish patients and selected 75 patients with severe tinnitus based on a Tinnitus Handicap Inventory (THI) score > 68. Three rare deletions were identified in two unrelated individuals overlapping the ERBB3 gene in the positions: NC_000012.12:g.56100028_56100172del, NC_000012.12:g.56100243_56101058del, and NC_000012.12:g.56101359_56101526del. Moreover, an ultra-rare large duplication was found covering the AP4M1, COPS6, MCM7, TAF6, MIR106B, MIR25, and MIR93 genes in another two patients in the NC_000007.14:g.100089053_100112257dup region. All the coding genes exhibited expression in brain and inner ear tissues. These results confirm the contribution of large SVs to severe tinnitus in MD and pinpoint new candidate genes to get a better molecular understanding of the disease. [ABSTRACT FROM AUTHOR]

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein‐peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding. [ABSTRACT FROM AUTHOR]

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein‐peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding. [ABSTRACT FROM AUTHOR]

Food safety is a widespread challenge. Every year it is estimated that almost 1 in 10 people in the world fall ill after eating contaminated food resulting in over 400,000 deaths. The risk of outbreaks is higher when consuming ready‐to‐eat (RTE) products because they are eaten without a further cooking process that could inactivate pathogenic microorganisms. Hence, food processing is essential to increase the safety of RTE products. Microbiological risk assessment (MRA) integrates food science, microbiology and data science to provide a comprehensive understanding of the safety of the food system. MRA provides qualitative and/or quantitative information to decision makers, which might promote the adoption of better food practices. In this contest, this project aims to study and implement tools for quantitative microbial risk assessment (QMRA) of food products along the food chain. A common RTE product (cured ham) from Spain was used as a case study. Following, the exposure assessment model was implemented using mathematical models and statistical software to describe the microbial behaviour along the food chain. The study presents the possibility to identify the risk exposure in different scenarios (e.g. growth during different storage conditions, inactivation induced by traditional or innovative decontamination techniques), showing the flexibility of the predictive tools developed. [ABSTRACT FROM AUTHOR]

Food safety is a widespread challenge. Every year it is estimated that almost 1 in 10 people in the world fall ill after eating contaminated food resulting in over 400,000 deaths. The risk of outbreaks is higher when consuming ready‐to‐eat (RTE) products because they are eaten without a further cooking process that could inactivate pathogenic microorganisms. Hence, food processing is essential to increase the safety of RTE products. Microbiological risk assessment (MRA) integrates food science, microbiology and data science to provide a comprehensive understanding of the safety of the food system. MRA provides qualitative and/or quantitative information to decision makers, which might promote the adoption of better food practices. In this contest, this project aims to study and implement tools for quantitative microbial risk assessment (QMRA) of food products along the food chain. A common RTE product (cured ham) from Spain was used as a case study. Following, the exposure assessment model was implemented using mathematical models and statistical software to describe the microbial behaviour along the food chain. The study presents the possibility to identify the risk exposure in different scenarios (e.g. growth during different storage conditions, inactivation induced by traditional or innovative decontamination techniques), showing the flexibility of the predictive tools developed. [ABSTRACT FROM AUTHOR]

Ports serve as essential nodes for coastal and maritime transportation and are key sources of income and economic activity in coastal zones. This significance, combined with their location in coastal areas, which are prone to climate-driven impacts, makes them highly susceptible to climate change effects. In this work, a climate change risk assessment methodology for port infrastructures that is focused on compound events analysis is presented. This approach is based on a spatial high-resolution probabilistic framework that enables the evaluation of port performance evolution under the effects of climate change. This assessment draws from a multimodel characterization of the evolution of several climate drivers for different emission scenarios and time horizons. It accounts for multiple port infrastructure risks and considers the compound effects of climate drivers and the interdependencies of infrastructures as complex systems. Performance indicators are developed for the physical assets and services at port locations on a highly granular scale, thus allowing port managers and planners to allocate reserves and develop adaptation plans that reduce climate change risks in the operations of maritime transportation nodes based on port performance forecasts. The methodology is implemented in two case studies set in the northern coast of Spain, demonstrating its applicability and replicability among several locations and scales. • Develops a novel framework to assess the climate change risk on coastal and port infrastructures, with a primary emphasis on modeling complex risks. • The framework integrates methods that consider not only the effects on structures and assets but also the ways that harbored uses and services become interrupted. • The framework considers compound effects of diverse climatic drivers on the integrity and performance of the evaluated infrastructures. • The infrastructure component dependencies are evaluated as a unified system. • The study cases output the importance of accounting for complex risk typologies when assessing climate change risk of port and coastal infrastructures. [ABSTRACT FROM AUTHOR]

Adaptation of port infrastructures to climate change and sea level rise effects is highlighted as a key field among transportation systems' lines of action for adaptation, given their highly exposed location in coastal areas and position as critical nodes in logistic chains and local, regional and national economies. The present work proposes an adaptation assessment framework that, based on a high-resolution compound climate risk assessment, identifies the main threats that climate change may pose to port performance, defines a set of optimized adaptation measures and characterizes constraints for implementation, and finally evaluates the applicability and effectiveness of these measures under diverse climate scenarios and different time frames. The framework is applied in a study case located in the northern coast of Spain. It is shown that the proposed methodology enables port managers and planners to develop tailor-fitted adaptation plans, providing tools to make them coherent with actual and future uncertain climate conditions. • The paper develops a novel framework to prepare climate change adaptation plans for port and coastal infrastructures. • It identifies the main needs and limitations for adaptation of port infrastructures based on a compound CC risk assessment. • It identifies and optimizes a set of adaptation measures, considering measure combinations, based on risk-reduction criteria. • It assesses the adaptation options' effectiveness in reducing climate risk for different scenarios and time horizons. • The framework has been applied and validated for a case study located on the Atlantic coast in Spain. [ABSTRACT FROM AUTHOR]

Hydroxytyrosol (HT), the main representative of polyphenols of olive oil, has been described as one of the most powerful natural antioxidants, also showing anti-inflammatory, antimicrobial, cardioprotective and anticancer activity in different type of cancers, but has been little studied in hematological neoplasms. The objective of this work was to evaluate the anticancer potential of HT in acute human leukemia T cells (Jurkat and HL60) and the anti-inflammatory potential in murine macrophages (Raw264.7). For this, cytotoxicity tests were performed for HT, showing IC50 values, at 24 h, for Jurkat, HL60 and Raw264.7 cells, of 27.3 µg·mL−1, 109.8 µg·mL−1 and 45.7 µg·mL−1, respectively. At the same time, HT caused cell arrest in G0/G1 phase in both Jurkat and HL60 cells by increasing G0/G1 phase and significantly decreasing S phase. Apoptosis and cell cycle assays revealed an antiproliferative effect of HT, decreasing the percentage of dividing cells and increasing apoptosis. Furthermore, HT inhibited the PI3K signaling pathway and, consequently, the MAPK pathway was activated. Inflammation tests revealed that HT acts as an anti-inflammatory agent, reducing NO levels in Raw264.7 cells previously stimulated by lipopolysaccharide (LPS). These processes were confirmed by the changes in the expression of the main markers of inflammation and cancer. In conclusion, HT has an anticancer and anti-inflammatory effect in the cell lines studied, which were Raw264.7, Jurkat, and HL60, and could be used as a natural drug in the treatment of liquid cancers, leukemias, myelomas and lymphomas. [ABSTRACT FROM AUTHOR]

In this study, the presence of rare missense variants and frame shift deletions in the I TECTA i gene in six unrelated families with MD suggests a role of this gene in the pathophysiology of the disease. Three rare missense variants (colored in blue) and two short deletions (colored in red) were found in four multicase MD families (arrow shaped) and two additional families with one MD patient and relatives with partial syndromes (diamond shaped). Dear Editor Although there have been considerable advances in recent years, the contribution of genetic factors to Meniere's disease (MD) is not yet fully understood. [Extracted from the article]

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarsegraining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions. [ABSTRACT FROM AUTHOR]

Objectives: Intestinal malrotation is largely a pediatric diagnosis, but initial detection can be made in adulthood. CT colonography (CTC) provides an ideal means for estimating prevalence. Our purpose was to evaluate the prevalence and imaging findings of intestinal malrotation in asymptomatic adults at CTC screening, as well as incomplete optical colonoscopy (OC) referral. Methods: The CTC database of a single academic institution was searched for cases of intestinal malrotation (developmental nonrotation). Prevalence was estimated from 11,176 adults undergoing CTC. Demographic, clinical, imaging (CTC and other abdominal exams), and surgical data were reviewed. Results: 27 cases of malrotation were confirmed (mean age 62 ± 9 years; 15 M/12F), including 17 from the CTC screening cohort (0.17% prevalence) and 10 from incomplete OC (0.75% prevalence; p < 0.001). Most cases (59%; 16/27) were initially diagnosed at CTC. In 67% (12/18); the presence of malrotation was missed on at least one relevant abdominal imaging examination. At least 22% (6/27) had a history of unexplained, chronic intermittent abdominal pain. At CTC, the SMA-SMV relationship was normal in only 11% (3/27). The ileocecal valve was located in the RLQ in only 22% (6/27). Two patients (7%) had associated findings of heterotaxy (polysplenia). Conclusions: The prevalence of intestinal malrotation was four times greater for patients referred from incomplete OC compared with primary screening CTC, likely related to anatomic challenges at endoscopy. Malrotation was frequently missed at other abdominal imaging examinations. CTC can uncover unexpected cases of malrotation in adults, which may be relevant in terms of potential for future complications. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to provide a morphometric description of the bony margins of the interlaminar spaces by level in the cervical spine for guidance of safe posterior cervical surgical dissection and decompression. We also aim to describe the impact of increasing static cervical lordosis on the overlap between the lamina. Methods: Morphometric measurements of the interlaminar space were performed on 100 consecutive cervical spine CT scans of patients ranging in age from 18 to 50 years were selected. Three raters performed measurements of the interlaminar height measured using two techniques (true interlaminar height and surgical interlaminar height), and interlaminar width from C2–C3 to C7–T1. Results: In total, 100 patients were included. The true interlaminar height was greatest at C2–3, C3–4, C4–5 (5.2 ± 1.4–1.8 mm) and smallest at C6–7 (4.4 ± 1.3 mm). Surgical interlaminar height was greatest at C3–4 (4.2 ± 1.7) and smallest at C6–7 (3.0 ± 1.3 mm). The widest interlaminar space was observed at C3–4 (27.1 ± 2.1 mm) and most narrow at C7–T1 (20.9 ± 2.4 mm). Following multivariate regression, male gender was associated with greater interlaminar widths at each cervical level between C4 and T1 (Table 2). While greater patient height was associated with larger interlaminar height (true and surgical) and width at C2–3 and C4–5, weight was not independently associated with the interlaminar measurements. Increasing C2–C7 lordosis was significantly associated with decreasing true and surgical interlaminar heights at all levels except C7–T1, but was not associated with differences between interlaminar width. Conclusion: The study provides a morphometric analysis of interlaminar anatomy in the cervical spine. Surgeons can apply this information in their pre-operative plan to safely approach the posterior cervical spine. [ABSTRACT FROM AUTHOR]

Purpose: Fully automated CT-based algorithms for quantifying bone, muscle, and fat have been validated for unenhanced abdominal scans. The purpose of this study was to determine and correct for the effect of intravenous (IV) contrast on these automated body composition measures. Materials and methods: Initial study cohort consisted of 1211 healthy adults (mean age, 45.2 years; 733 women) undergoing abdominal CT for potential renal donation. Multiphasic CT protocol consisted of pre-contrast, arterial, and parenchymal phases. Fully automated CT-based algorithms for quantifying bone mineral density (BMD, L1 trabecular HU), muscle area and density (L3-level MA and M-HU), and fat (visceral/subcutaneous (V/S) fat ratio) were applied to pre-contrast and parenchymal phases. Effect of IV contrast upon these body composition measures was analyzed. Square of the Pearson correlation coefficient (r2) was generated for each comparison. Results: Mean changes (± SD) in L1 BMD, L3-level MA and M-HU, and V/S fat ratio were 26.7 ± 27.2 HU, 2.9 ± 10.2 cm2, 18.8 ± 6.0 HU, − 0.1 ± 0.2, respectively. Good linear correlation between pre- and post-contrast values was observed for all automated measures: BMD (pre = 0.87 × post; r2 = 0.72), MA (pre = 0.98 × post; r2 = 0.92), M-HU (pre = 0.75 × post + 5.7; r2 = 0.75), and V/S (pre = 1.11 × post; r2 = 0.94); p < 0.001 for all r2 values. There were no significant trends according to patient age or gender that required further correction. Conclusion: Fully automated quantitative tissue measures of bone, muscle, and fat at contrast-enhanced abdominal CT can be correlated with non-contrast equivalents using simple, linear relationships. These findings will facilitate evaluation of mixed CT cohorts involving larger patient populations and could greatly expand the potential for opportunistic screening. [ABSTRACT FROM AUTHOR]

A hydroalcoholic extract was obtained from the petals of the flower of majagua (Talipariti elatum S.W.) rich in anthocyanins, for which the extraction process was optimized according to the total content of polyphenols and anthocyanins, with ethanol as a factor (% v/v) and the extraction time. The optimal extraction conditions corresponded with 79% v/v of ethanol and 12h as the extraction time. The optimized hydroalcoholic extract showed of total polyphenols and anthocyanins of 12034mg gallic acid/L and 10mg/L, respectively. In the optimized extract, metabolites were identified as: terpenes/steroids, reducing sugars, mucilages, polyphenols (anthocyanins, flavonoids and tannins). The extract presented a reddish-orange color in correspondence with the most probable anthocyanins in it: pelargonidin, cyanidin and peonidin, as well as some of its glycosidic variants. [ABSTRACT FROM AUTHOR]

There is a pressing need for new computational tools to integrate data from diverse experimental approaches in structural biology. We present a strategy that combines sparse paramagnetic solid‐state NMR restraints with physics‐based atomistic simulations. Our approach explicitly accounts for uncertainty in the interpretation of experimental data through the use of a semi‐quantitative mapping between the data and the restraint energy that is calibrated by extensive simulations. We apply our approach to solid‐state NMR data for the model protein GB1 labeled with Cu2+‐EDTA at six different sites. We are able to determine the structure to 0.9 Å accuracy within a single day of computation on a GPU cluster. We further show that in some cases, the data from only a single paramagnetic tag are sufficient for accurate folding. [ABSTRACT FROM AUTHOR]

There is a pressing need for new computational tools to integrate data from diverse experimental approaches in structural biology. We present a strategy that combines sparse paramagnetic solid‐state NMR restraints with physics‐based atomistic simulations. Our approach explicitly accounts for uncertainty in the interpretation of experimental data through the use of a semi‐quantitative mapping between the data and the restraint energy that is calibrated by extensive simulations. We apply our approach to solid‐state NMR data for the model protein GB1 labeled with Cu2+‐EDTA at six different sites. We are able to determine the structure to 0.9 Å accuracy within a single day of computation on a GPU cluster. We further show that in some cases, the data from only a single paramagnetic tag are sufficient for accurate folding. [ABSTRACT FROM AUTHOR]

Abstract Background Nephrolithiasis is a classic, treatable manifestation of primary hyperparathyroidism (PHPT). We examined predictors of kidney stone formation in PHPT patients and determined how efficiently the diagnosis of PHPT is made in patients whose initial presentation is with stones. Materials and methods We performed a retrospective analysis of surgically treated PHPT patients, comparing 247 patients who were kidney stone formers and 1047 patients with no kidney stones. We also analyzed 51 stone-forming patients whose stone evaluation and treatment were completed within our health system before PHPT diagnosis. Results Stone-forming patients had higher 24-h urinary calcium (342 versus 304 mg/d, P = 0.005), higher alkaline phosphatase (92 versus 85 IU/L, P = 0.012), and were more likely to be normocalcemic (26.6% versus 16.9%, P = 0.001). Surprisingly, 47.3% of stone formers had normal urinary calcium levels (<300 mg/d). Of the 51 stone-forming patients treated at our institution, serum calcium was measured within 6 mo of stone diagnosis in 37 (72.5%) patients. Only 16 (31.4%) of these patients had elevated calcium levels, and only 10 (62.5%) of these 16 had a serum parathyroid hormone ordered within the following 3 mo. These patients had a significantly shorter time from their first stone to surgical treatment compared to other patients (median 8.5 versus 49.1 mo, P = 0.001). Conclusions Elevated serum and urinary calcium levels are not evaluated in the majority of PHPT patients presenting with kidney stones. In nephrolithiasis patients, provider consideration of PHPT with prompt serum calcium and parathyroid hormone evaluation significantly reduces time to treatment. [ABSTRACT FROM AUTHOR]

Objective Assess automated CT imaging biomarkers in patients who went on to hip fracture, compared with controls. Methods In this retrospective case-control study, 6926 total patients underwent initial abdominal CT over a 20-year interval at one institution. A total of 1308 patients (mean age at initial CT, 70.5 ± 12.0 years; 64.4% female) went on to hip fracture (mean time to fracture, 5.2 years); 5618 were controls (mean age 70.3 ± 12.0 years; 61.2% female; mean follow-up interval 7.6 years). Validated fully automated quantitative CT algorithms for trabecular bone attenuation (at L1), skeletal muscle attenuation (at L3), and subcutaneous adipose tissue area (SAT) (at L3) were applied to all scans. Hazard ratios (HRs) comparing highest to lowest risk quartiles and receiver operating characteristic (ROC) curve analysis including area under the curve (AUC) were derived. Results Hip fracture HRs (95% CI) were 3.18 (2.69-3.76) for low trabecular bone HU, 1.50 (1.28-1.75) for low muscle HU, and 2.18 (1.86-2.56) for low SAT. 10-year ROC AUC values for predicting hip fracture were 0.702, 0.603, and 0.603 for these CT-based biomarkers, respectively. Multivariate combinations of these biomarkers further improved predictive value; the 10-year ROC AUC combining bone/muscle/SAT was 0.733, while combining muscle/SAT was 0.686. Conclusion Opportunistic use of automated CT bone, muscle, and fat measures can identify patients at higher risk for future hip fracture, regardless of the indication for CT imaging. Advances in knowledge CT data can be leveraged opportunistically for further patient evaluation, with early intervention as needed. These novel AI tools analyse CT data to determine a patient's future hip fracture risk. [ABSTRACT FROM AUTHOR]

This work presents a 3D scanner able to reconstruct a complete object without occlusions, including its surface appearance. The technique presents a number of differences in relation to current scanners: it does not require mechanical handling like robot arms or spinning plates, it is free of occlusions since the scanned part is not resting on any surface and, unlike stereo-based methods, the object does not need to have visual singularities on its surface. This system, among other applications, allows its integration in production lines that require the inspection of a large volume of parts or products, especially if there is an important variability of the objects to be inspected, since there is no mechanical manipulation. The scanner consists of a variable number of industrial quality cameras conveniently distributed so that they can capture all the surfaces of the object without any blind spot. The object is dropped through the common visual field of all the cameras, so no surface or tool occludes the views that are captured simultaneously when the part is in the center of the visible volume. A carving procedure that uses the silhouettes segmented from each image gives rise to a volumetric representation and, by means of isosurface generation techniques, to a 3D model. These techniques have certain limitations on the reconstruction of object regions with particular geometric configurations. Estimating the inherent maximum error in each area is important to bound the precision of the reconstruction. A number of experiments are presented reporting the differences between ideal and reconstructed objects in the system. [ABSTRACT FROM AUTHOR]

Free-energy-based simulations are increasingly providing the narratives about the structures, dynamics and biological mechanisms that constitute the fabric of protein science. Here, we review two recent successes. It is becoming practical: first, to fold small proteins with free-energy methods without knowing substructures and second, to compute ligand–protein binding affinities, not just their binding poses. Over the past 40 years, the timescales that can be simulated by atomistic MD are doubling every 1.3 years — which is faster than Moore's law. Thus, these advances are not simply due to the availability of faster computers. Force fields, solvation models and simulation methodology have kept pace with computing advancements, and are now quite good. At the tip of the spear recently are GPU-based computing, improved fast-solvation methods, continued advances in force fields, and conformational sampling methods that harness external information. [ABSTRACT FROM AUTHOR]

This paper presents a Low Noise Amplifier (LNA) for neural spike recording applications. The proposed topology, based on a capacitive feedback network using a two-stage OTA, efficiently solves the triple trade-off between power, area and noise. Additionally, this work introduces a novel transistor-level synthesis methodology for LNAs tailored for the minimization of their noise efficiency factor under area and noise constraints. The proposed LNA has been implemented in a 130 nm CMOS technology and occupies 0.053 mm-sq. Experimental results show that the LNA offers a noise efficiency factor of 2.16 and an input referred noise of 3.8 μVrms for 1.2 V power supply. It provides a gain of 46 dB over a nominal bandwidth of 192 Hz-7.4 kHz and consumes 1.92 μW. The performance of the proposed LNA has been validated through in vivo experiments with animal models. [ABSTRACT FROM AUTHOR]

We numerically investigated the annular electroconvection that takes place in a dielectric liquid lying between two concentric cylinder electrodes. A uniform injection of arbitrary strengths either from the inner or outer cylinder introduces free charge carriers into the system, and the resulting Coulomb force induces electroconvection. The problem is characterized by a linear instability that corresponds to the onset of flow motion. The linear stability criteria were determined from direct numerical results and by linear stability analysis, and the results obtained with the two approaches show an excellent agreement. We focused on the fully developed flow pattern in the finite amplitude regime. We observed very different flow motions that were highly dependent on the injection strength. [ABSTRACT FROM AUTHOR]

More than 100,000 protein structures are now known at atomic detail. However, far more are not yet known, particularly among large or complex proteins. Often, experimental information is only semireliable because it is uncertain, limited, or confusing in important ways. Some experiments give sparse information, some give ambiguous or nonspecific information, and others give uncertain information--where some is right, some is wrong, but we don't know which. We describe a method called Modeling Employing Limited Data (MELD) that can harness such problematic information in a physics-based, Bayesian framework for improved structure determination. We apply MELD to eight proteins of known structure for which such problematic structural data are available, including a sparse NMR dataset, two ambiguous EPR datasets, and four uncertain datasets taken from sequence evolution data. MELD gives excellent structures, indicating its promise for experimental biomolecule structure determination where only semireliable data are available. [ABSTRACT FROM AUTHOR]

Summary: Protein molecules often undergo conformational changes. In order to gain insights into the forces that drive such changes, it would be useful to have a method that computes the per-residue contributions to the conversion free energy. Here, we describe the “confine-convert-release” (CCR) method, which is applicable to large conformational changes. We show that CCR correctly predicts the stable states of several “chameleon” sequences that have previously been challenging for molecular simulations. CCR can often discriminate better from worse predictions of native protein models in critical assessment of protein structure prediction (CASP). We show how the total conversion free energies can be parsed into per-residue free-energy components. Such parsing gives insights into which amino acids are most responsible for given transformations. For example, here we are able to “reverse-engineer” the known design principles of the chameleon proteins. This opens up the possibility for systematic improvements in structure-prediction scoring functions, in the design of protein conformational switches, and in interpreting protein mechanisms at the amino-acid level. [ABSTRACT FROM AUTHOR]

Abstract: Falling film microreactors are ideally suited for fast exothermic reactions due to their large surface to volume ratio (up to 20,000m2/m3) which greatly intensifies mass transfer. Despite the enhanced mass transfer characteristics of these reactors, mass transfer between the phases can still be the rate limiting step. To improve mass transfer, staggered herringbone structures were incorporated on the microchannel floor of falling film microreactors [1]. It was shown experimentally that reactors with herringbone structures increased CO2 absorption in 1M NaOH solution by up to 42%. Modelling of this system can be computationally prohibitive. This is due to its three-dimensional nature and the complexity of incorporating gas/liquid absorption and reaction with chaotic flow. For the CO2 chemical absorption system, a pseudo 3D approach has been implemented to account for such a modelling complexity [2]. In this work, the complexity of modelling the effect of herringbone structures was simplified using an effective diffusion coefficient calculated via an eddy diffusivity approach. Good agreement between the experimental data from Ziegenbalg et al. [1] and the simulations was obtained. The simplification suggested opens the possibility to model complicated systems with minimum computational expenditure. [Copyright &y& Elsevier]

Summary: We estimate the impact of aggregate indicators of “soft” and “hard” infrastructure on the export performance of developing countries. We derive four new indicators for more than 100 countries over the period 2004–07. Estimates show that trade facilitation reforms do improve the export performance of developing countries. This is particularly true with investment in physical infrastructure and regulatory reform to improve the business environment. The findings provide evidence that the marginal effect of the transport efficiency and business environment improvement on exports appears to be decreasing in per capita income. In contrast, the impact of physical infrastructure and information and communications technology on exports appears increasingly important the richer a country becomes. We also find statistical evidence on the complementarity between hard infrastructure and soft infrastructure, as captured by our indicators. Finally, drawing on estimates, we compute illustrative ad-valorem equivalents of improving each indicator halfway to the level of the top performer in the region. [Copyright &y& Elsevier]

Abstract: The high liquid based specific interfacial area, up to ∼20,000m2/m3, of falling film microreactors renders them to be ideally suited to carry out fast exothermic and mass transfer limited reactions. To understand the role of and control this interfacial area, it is important to account for realistic liquid film profiles. Here, we vary the liquid film profile or its velocity profile by two different means – through the (external) shape of a plain microchannel and through in-channel structures within the microchannel (staggered herringbone grooves (SHG) on the microchannel bottom). The variations in the liquid films are evaluated via two computational fluid dynamic (CFD) models. First is the pseudo 3-D which explicitly accounts for the liquid film thicknesses, flow velocities, species transport and reactions. Here, the pseudo 3-D model is used to investigate (1) the effects of five microchannel shapes and (2) three microchannel cross section dimensions; to account for a scale-out through both numbering-up and smart increase in dimensions. The model reaction used is the absorption of CO2 in aqueous NaOH solution. It is found that the mass transfer into the liquid and the reaction conversion depend on the velocity profile and flow pattern. Second CFD model is the full 3-D which is used to evaluate the liquid film in the presence of SHG. The simulations from the full 3-D model indicate that: (1) residence time distribution is narrowed by five times compared to plain microchannels and (2) the penetration depths of particles seeded at the gas/liquid interface are 1.7 times larger in the presence of SHG. Furthermore the effect of SHG on penetration depth is more pronounced at higher flow rates. This is experimentally exploited by increasing the liquid throughput by more than a factor of two while keeping the same reaction conversion, using the SHG microchannels. [Copyright &y& Elsevier]

Abstract: The performance of a consecutive reaction of the type was studied in two reactor configurations. A layered herringbone channel, which consists of two rectangular channels and a middle layer containing machined-through herringbone structures, is compared with an unstructured rectangular channel. It was found that when the reactants are not premixed before the inlet, the layered herringbone configuration shows an improved performance compared to the rectangular channel giving a 40% increase in the maximum amount of intermediate produced. The maximum concentration of intermediate is obtained at lower residence times, which indicates that reactor volume could be decreased compared to the rectangular channel. The maximum amount of intermediate and the conversion at which this maximum occurs is dependent also on the ratio (k 2/k 1) which in this work is 0.05. Good mixing characteristics and narrow residence time distribution (RTD) are responsible for the improved behaviour in the layered herringbone channel. When the reactants are premixed before the inlet the differences are more subtle, indicating that the improved reaction behaviour in the layered herringbone channel is mainly due to good mixing and to a smaller extent to narrow RTDs. Residence time distributions were calculated numerically via CFD and particle tracking methods. The RTDs for the layered herringbone channel were found to be narrower as compared to the rectangular one. The model of axial dispersion exchanging mass with a stagnant zone was used for the modelling of the RTD. It was found that the model parameters could be calculated directly from hydrodynamic data obtained from CFD calculations, without the need of particle tracking algorithms. Concepts from turbulent theory were employed for the calculation of an effective diffusion coefficient that replaced the stirring effect of the herringbones. This procedure greatly simplifies the theoretical calculation of RTDs and reaction conversions. [Copyright &y& Elsevier]

Abstract: Residence time distributions (RTD) have been determined numerically and experimentally for channels with and without herringbone structures. Computational fluid dynamics (CFD) and particle tracking with random walk diffusion were employed for the numerical calculation of the RTD. The axial dispersion exchanging mass with a stagnant zone model was shown to fit the particle tracking data for the channels with staggered herringbone structures. This model provides a simpler method for RTD characterisation. Experimental RTD measurements were performed by monitoring the concentration of a tracer dye by means of a LED-photodiode system. For all cases, the calculations agreed well with experiments. The results show that for low Peclet numbers (Pe<102) the use of herringbone structures does not have an impact on the RTD, however at high Peclet numbers (Pe>102), channels with herringbone structures exhibit a narrower RTD than a plain channel of the same dimensions. Thus, at high Pe, inclusion of herringbones to the bottom floor of rectangular channels allows the increase in channel dimensions without adverse effect on the RTD behaviour or reaction performance. [Copyright &y& Elsevier]

Aequipecten opercularis (Queen scallop) and Mimachlamys ( Chlamys) varia (Black scallop) are important natural resources occurring in Atlantic and Mediterranean coasts. To develop an optimal sustainable exploitation plan, it is important to study the genetic structure of the different populations. In this study, we used polymerase chain reaction-restriction fragment length polymorphisms for the determination of the genetic variation and population structure of these two species in different localities. Ten composite haplotypes were generated for A. opercularis and 15 haplotypes for M. varia. Of these, six and four were unique respectively. The analysis of the distribution of the different haplotypes between the localities showed no clear evidence of subdivision in A. opercularis, while in M. varia the results indicated that the two localities analysed should be managed as separate stocks. [ABSTRACT FROM AUTHOR]

Molecular dynamics is used to investigate the properties of the DNA·RNA hybrid in aqueous solution at room temperature. The structure of the hybrid is intermediate between A and B forms but, in general, closer to the canonical A-type helix. All the riboses exhibit North puckerings, while 2'-deoxyriboses exist in North, East, and South puckerings, the latter being the most populated one. The molecular recognition pattern of the DNA·RNA hybrid is a unique combination of those of normal DNA and RNA duplexes. Finally, the results obtained from essential dynamics and stiffness analysis demonstrate the large and very asymmetric flexibility of the hybrid and the strong predilection that each strand (DNA or RNA) has on the nature of their intrinsic motions in the corresponding homoduplexes. The implications of the unique structural and dynamic properties of the DNA·RNA hybrid on the mechanism of cleavage by RNase H are discussed. [ABSTRACT FROM AUTHOR]

Focuses on a study which examined different conducting balls and liquids, particularly on the dependence on the different paramaters of the ratio charge transferred to the circuit-charge acquired by the ball. Explanation of the theory; Experimental setup; Time of flight and lift-off voltage; Mechanism of electric discharge.

The capability of laser-backscattering imaging technique as a non-destructive method to control the effect of fat on curdling process phases was studied. It was based on capturing images of the diffraction patterns generated by a laser-matrix interaction, from which data were acquired. The studied phases were: raw material inspection; curdling monitoring; fresh curd inspection and curd storage monitoring. Milk was used with three different fat contents (0, 1.5 and 3.5%). An extra category of 1.5% fat without lactose was added to test the effect of modification on other compounds. All the phases were characterised by a destructive analysis (rheology, texture profile analysis, syneresis) to study both the evolution of the physical properties during the process and the relation to imaging data. Images successfully captured the variance generated by fat content and physical modifications. Differences in fat content were distinguished for raw material and fresh curd despite lack of lactose. Curdling monitoring also allowed the fat effect to be characterised and coagulation time to be established. Matrix evolution during storage was modelled from imaging for 24 h and 96 h. Imaging data correlated with syneresis evolution and texture features. The obtained results showed that laser-backscattering imaging was capable of capturing the effect of both fat and physical changes on each processing phase, which implies that this technique can be employed as a common system for independent phase control. • The capability of laser-backscattering imaging to control curd processing was studied. • The phases were: raw material inspection; curdling; curd inspection and storage. • Imaging data correlated with rheology, texture and syneresis of three fat contents. [ABSTRACT FROM AUTHOR]

Recent developments in ultrashort and intense laser systems have enabled the generation of short and brilliant proton sources, which are valuable for studying plasmas under extreme conditions in high-energy-density physics. However, developing sensors for the energy selection, focusing, transport, and detection of these sources remains challenging. This work presents a novel and simple design for an isochronous magnetic selector capable of angular and energy selection of proton sources, significantly reducing temporal spread compared to the current state of the art. The isochronous selector separates the beam based on ion energy, making it a potential component in new energy spectrum sensors for ions. Analytical estimations and Monte Carlo simulations validate the proposed configuration. Due to its low temporal spread, this selector is also useful for studying extreme states of matter, such as proton stopping power in warm dense matter, where short plasma stagnation time (<100 ps) is a critical factor. The proposed selector can also be employed at higher proton energies, achieving final time spreads of a few picoseconds. This has important implications for sensing technologies in the study of coherent energy deposition in biology and medical physics. [ABSTRACT FROM AUTHOR]

Psoriasis is a skin disorder characterized by hyperproliferation of epidermal keratinocytes. 1α,25-Dihydroxyvitamin D3 (1α,25(OH)2D3) and its analogs have been shown to inhibit keratinocyte proliferation in vitro and to be therapeutically effective for the treatment of psoriasis. Some patients with psoriasis, however, do not have a favorable response to 1α,25(OH)2D3 therapy. To evaluate the differential responsiveness to 1α,25(OH)2D3 treatment, we examined the expression of vitamin D receptor mRNA in psoriatic lesions by reverse transcription-polymerase chain reaction using glyceraldehyde-3-phosphate de-hydrogenase as an internal control. In this double- blind clinical trial, we recruited 18 patients who received topical treatment of la,25(OH)2D3 (15 μg/g Vaseline) or placebo on separate psoriatic lesions for 8 weeks. In patients who showed >90% clinical im- provement of their psoriatic lesions treated with 1α,25(OH)2D3 (n = 9), an increase of 130 ± 37% in vitamin D receptor mRNA level was observed in 1α,25(OH)2D3-treated lesions when compared with the corresponding placebo controls. There was no increase in vitamin D receptor mRNA level in the lesions treated with this drug in patients who did not respond to the treatment. These data suggest that the antiproliferative activity of 1α,25(OH)2D3 is closely associated with the expression of its cognate receptor. [ABSTRACT FROM AUTHOR]

Pathologic involvement of the peritoneum can result from a wide variety of conditions, including both neoplastic and non-neoplastic entities. Neoplastic involvement of the peritoneal ligaments, mesenteries, and spaces from malignant spread of epithelial cancers, termed peritoneal carcinomatosis, is frequently encountered at CT evaluation. However, a host of other more unusual benign and malignant neoplasms can manifest with peritoneal disease, including both primary and secondary peritoneal processes, many of which can closely mimic peritoneal carcinomatosis at CT. In this review, we discuss a wide array of unusual peritoneal-based neoplasms that can resemble the more common peritoneal carcinomatosis. Beyond reviewing the salient features for each of these entities, particular emphasis is placed on any specific clinical and CT imaging clues that may allow the interpreting radiologist to appropriately narrow the differential diagnosis and, in some cases, make an imaging-specific diagnosis. [ABSTRACT FROM AUTHOR]

Designing peptide inhibitors of the p53-MDM2 interaction against cancer is of wide interest. Computational modeling and virtual screening are a well established step in the rational design of small molecules. But they face challenges for binding flexible peptide molecules that fold upon binding. We look at the ability of five different peptides, three of which are intrinsically disordered, to bind to MDM2 with a new Bayesian inference approach (MELD × MD). The method is able to capture the folding upon binding mechanism and differentiate binding preferences between the five peptides. Processing the ensembles with statistical mechanics tools depicts the most likely bound conformations and hints at differences in the binding mechanism. Finally, the study shows the importance of capturing two driving forces to binding in this system: the ability of peptides to adopt bound conformations ( Δ G c o n f o r m a t i o n ) and the interaction between interface residues ( Δ G i n t e r a c t i o n ). [ABSTRACT FROM AUTHOR]

• Mass transfer to a reactive-wall was studied for several herringbone channels (HC). • Flow inverter is more efficient at removing the boundary layer than the 1PSHC. • 1-2PeakHC obtained the highest conversion (56 %) compared to other HC configurations. • 1-2PeakHC performance (Sh∼35) is related to a constant boundary layer renewal. • 1PeakHC 3D model may be simplified to 2D with virtual eddy-diffusivity coefficient. In the present study, the flow behaviour through different micro-herringbone channels configurations (1-peak, 2-peak, 1–2 alternated peak herringbone channel and a flow inversion geometry) have been numerically analysed as a mean of intensifying mass transfer to a reactive boundary. Results showed that the mass transfer coefficients were higher for the 1–2 alternated herringbone structure than those with, either, 1-peak or 2-peak structures. Moreover, the flow inversion structure mass transfer coefficients were double those obtained for the staggered herringbone channel. The alternated herringbone channel combines a different set of herringbone structures that are efficient at removing the boundary layer at different parts of the channel. The combination of these structures provide an enhanced mass transfer performance as compared to a standard herringbone channel. The obtained results showed that a 2D simplified model which uses hydrodynamic data from CFD simulations is a reasonable substitute for full 3D particle tracking simulations in terms of the mass transfer behavior of the 1PSHC with a 97.5 % of accuracy related to the asymptotic Sherwood number. The mixing capacity of the herringbones was accounted for by an apparent effective diffusion coefficient. The agreement between the 3D and 2D simulation was reasonable. [ABSTRACT FROM AUTHOR]

Background and aims: Obesity is linked to elevated levels of inflammatory serum markers such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNFa). Adiponectin and resistin are adipokines related to obesity. It has been described that adipose tissue presents a high production and secretion of these diverse pro-inflammatory molecules, which may have local effects on the physiology of fat cells as well as systemic effects on other organs. Our aim was to evaluate the impact that lifestyle modifications, by following a Mediterranean Diet (MedDiet) program and physical activity (PA) training, would have on inflammatory biomarkers and adipokine profile in a Metabolically Healthy Obese (MHO) elderly population from Malaga (Andalusia, Spain). Subjetcs and methods: Subjects aged ≥65 years (65 to 87 years old) with obesity (BMI ≥30 kg/m2) were included in this study if they met ≤1 of the following criteria: systolic blood pressure ≥130 mmHg and/or diastolic blood pressure ≥ 85 mmHg; triglycerides ≥150 mg/dL; HDL-C <40mg/dL in men and <50mg/dL women; and fasting blood glucose ≥100mg/dL. Selected subjects underwent a personalized intensive lifestyle modification. Anthropometric measurements, PA, MedDiet adherence, analytical parameters, and inflammatory biomarkers were analyzed after 12 months of intervention. Results: 166 MHO elderly subjects, 40 (24.1%) male and 126 (75.9%) female (p < 0.0001), aged 71.7±5.2 years old (65 to 87 years old) were included in the study. After 12 months of intervention, only the waist circumference was significantly reduced in all the population (-2.5 cm, p<0.0001), although weight and BMI were maintained. MedDiet adherence increased significantly (p<0.001), but all intensity levels of PA decreased significantly (p<0.001). Concerning inflammatory biomarkers, only TNFa serum increased their levels after the intervention (p<0.001). Regarding the adipokine profile, adiponectin concentrations experienced a significant increment (p<0.001); besides, resistin concentrations decreased significantly (p<0.001). In this sense, only TNFa, adiponectin, and resistin correlated with PA. Adiponectin also correlates with insulin, triglycerides and HDL-c in baseline conditions and after 12 months of intervention; CRP, IL-6, TNFa, adiponectin, and resistin concentrations correlated with anthropometric parameters and some intensities of PA. In addition, adiponectin levels correlates with insulin, triglycerides and HDL-c. In baseline conditions, resistin levels correlated positively with TNFa (p = 0.01) and CRP (p<0.0001) levels. TNFa and IL-6 correlated positively with CRP (p = 0.03 and p<0.0001, respectively). After 12 months of intervention, only IL-6 correlated positively with CRP (p = 0.006). In addition, adipokines levels correlated positively during the process of lifestyle modification. However, during this process, only IL-6 correlated positively with itself (p<0.0001) and with CRP (p = 0.03). Conclusion: Healthy aging is a multifactorial biological process in which lifestyle is essential. The presence of obesity in elderly metabolically healthy population is not a problem necessarily. Elderly MHO population who eat a MedDiet and practice regularly PA are capable to modulate their production of inflammatory cytokines (CRP, IL-6, TNFa) and adipokines profile (adiponectin, resistin), preventing other metabolic disorders. [ABSTRACT FROM AUTHOR]

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High‐throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF‐CBA) to identify proteins that bind a target of interest from a pull‐down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide‐protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF‐CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification. [ABSTRACT FROM AUTHOR]

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High‐throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF‐CBA) to identify proteins that bind a target of interest from a pull‐down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide‐protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF‐CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification. [ABSTRACT FROM AUTHOR]

Point of care ultrasound has emerged as useful tool in cardiac arrest situations in adult population. Despite of these, there is not a protocol for cardiopulmonary resuscitation in the delivery room for newborns. We describe two case were ultrasound helped to rule out the cardiopulmonary arrest case and we propose and algorithm were ultrasound is integrated in the newborn resuscitation and may help to diagnose the cardiac arrest cause. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular (CV) disease is a major public health concern, and automated methods can potentially capture relevant longitudinal changes on CT for opportunistic CV screening purposes. Methods: Fully-automated and validated algorithms that quantify abdominal fat, muscle, bone, liver, and aortic calcium were retrospectively applied to a longitudinal adult screening cohort undergoing serial non-contrast CT examination between 2005 and 2016. Downstream major adverse events (MI/CVA/CHF/death) were identified via algorithmic EHR search. Logistic regression, ROC curve, and Cox survival analyses assessed for associations between changes in CT variables and adverse events. Results: Final cohort included 1949 adults (942 M/1007F; mean age, 56.2 ± 6.2 years at initial CT). Mean interval between CT scans was 5.8 ± 2.0 years. Mean clinical follow-up interval from initial CT was 10.4 ± 2.7 years. Major CV events occurred after follow-up CT in 230 total subjects (11.8%). Mean change in aortic calcium Agatston score was significantly higher in CV(+) cohort (591.6 ± 1095.3 vs. 261.1 ± 764.3), as was annualized Agatston change (120.5 ± 263.6 vs. 46.7 ± 143.9) (p < 0.001 for both). 5-year area under the ROC curve (AUC) for Agatston change was 0.611. Hazard ratio for Agatston score change > 500 was 2.8 (95% CI 1.5–4.0) relative to < 500. Agatston score change was the only significant univariate CT biomarker in the survival analysis. Changes in fat and bone measures added no meaningful prediction. Conclusion: Interval change in automated CT-based abdominal aortic calcium load represents a promising predictive longitudinal tool for assessing cardiovascular and mortality risks. Changes in other body composition measures were less predictive of adverse events. [ABSTRACT FROM AUTHOR]

Purpose: To compare fully automated artificial intelligence body composition measures derived from thin (1.25 mm) and thick (5 mm) slice abdominal CT data. Methods: In this retrospective study, fully automated CT-based body composition algorithms for quantifying bone attenuation, muscle attenuation, muscle area, liver attenuation, liver volume, spleen volume, visceral-to-subcutaneous fat ratio (VSR) and aortic calcium were applied to both thin (1.25 × 0.625 mm) and thick (5 × 3 mm) abdominal CT series from two patient cohorts: unenhanced scans in asymptomatic adults undergoing colorectal cancer screening, and post-contrast scans in patients with colorectal cancer. Body composition measures derived from thin and thick slice data were compared, including correlation coefficients and Bland–Altman analysis. Results: A total of 9882 CT scans (mean age, 57.0 years; 4527 women, 5355 men) were evaluated, including 8947 non-contrast and 935 contrast-enhanced CT exams. Very strong positive correlation was observed for all soft tissue measures: muscle attenuation (r2 = 0.97), muscle area (r2 = 0.98), liver attenuation (r2 = 0.99), liver volume (r2 = 0.98) and spleen volume (r2 = 0.99), VSR (r2 = 0.98), and aortic calcium (r2 = 0.92); (p < 0.001 for all). Moderate positive correlation was observed for bone attenuation (r2 = 0.35). Bland–Altman analysis showed strong agreement for muscle attenuation, muscle area, liver attenuation, liver volume and spleen volume. Mean percentage differences amongst body composition measures were less than 5% for VSR (4.6%), muscle area (− 0.5%), liver attenuation (0.4%) and liver volume (2.7%) and less than 10% for muscle attenuation (− 5.5%) and spleen volume (5.1%). For aortic calcium, thick slice overestimated for Agatston scores between 0 and 100 and > 400 burden in 3.1% and 0.3% relative to thin slice, respectively, but underestimated scores between 100 and 400. Conclusion: Automated body composition measures derived from thin and thick abdominal CT data are strongly correlated and show agreement, particularly for soft tissue applications, making it feasible to use either series for these CT-based body composition algorithms. [ABSTRACT FROM AUTHOR]

Wildlife trafficking creates favorable scenarios for intra- and inter-specific interactions that can lead to parasite spread and disease emergence. Among the fauna affected by this activity, primates are relevant due to their potential to acquire and share zoonoses - infections caused by parasites that can spread between humans and other animals. Though it is known that most primate parasites can affect multiple hosts and that many are zoonotic, comparative studies across different contexts for animal-human interactions are scarce. We conducted a multi-parasite screening targeting the detection of zoonotic infections in wild-caught monkeys in nine Peruvian cities across three contexts: captivity (zoos and rescue centers, n = 187); pet (households, n = 69); and trade (trafficked or recently confiscated, n = 132). We detected 32 parasite taxa including mycobacteria, simian foamyvirus, bacteria, helminths, and protozoa. Monkeys in the trade context had the highest prevalence of hemoparasites (including Plasmodium malariae/brasilianum, Trypanosoma cruzi, and microfilaria) and enteric helminths and protozoa were less common in pet monkeys. However, parasite communities showed overall low variation between the three contexts. Parasite richness (PR) was best explained by host genus and the city where the animal was sampled. Squirrel (genus Saimiri) and wooly (genus Lagothrix) monkeys had the highest PR, which was ~2.2 times the PR found in tufted capuchins (genus Sapajus) and tamarins (genus Saguinus/Leontocebus) in a multivariable model adjusted for context, sex, and age. Our findings illustrate that the threats of wildlife trafficking to One Health encompass exposure to multiple zoonotic parasites well-known to cause disease in humans, monkeys, and other species. We demonstrate these threats continue beyond the markets where wildlife is initially sold; monkeys trafficked for the pet market remain a reservoir for and contribute to the translocation of zoonotic parasites to households and other captive facilities where contact with humans is frequent. Our results have practical applications for the healthcare of rescued monkeys and call for urgent action against wildlife trafficking and ownership of monkeys as pets. [ABSTRACT FROM AUTHOR]

Generative models of protein sequence families are an important tool in the repertoire of protein scientists and engineers alike. However, state-of-the-art generative approaches face inference, accuracy, and overfitting- related obstacles when modeling moderately sized to large proteins and/or protein families with low sequence coverage. Here, we present a simple to learn, tunable, and accurate generative model, GENERALIST: GENERAtive nonLInear tenSor-factorizaTion for protein sequences. GENERALIST accurately captures several high order summary statistics of amino acid covariation. GENERALIST also predicts conservative local optimal sequences which are likely to fold in stable 3D structure. Importantly, unlike current methods, the density of sequences in GENERALIST-modeled sequence ensembles closely resembles the corresponding natural ensembles. Finally, GENERALIST embeds protein sequences in an informative latent space. GENERALIST will be an important tool to study protein sequence variability. Author summary: Protein sequence families show tremendous sequence variation. Yet, it is thought that a large portion of the functional sequence space remains unexplored. Generative models are machine learning methods that allow us to learn what makes proteins functional using sequences of naturally occurring proteins. Here, we present a new type of generative model GENERALIST: GENERAtive nonLInear tenSor-factorizaTion for protein sequences that is accurate, easy to implement, and works with very small datasets. We believe that GENERALIST will be an important tool in the repertoire of protein scientists and engineers alike. [ABSTRACT FROM AUTHOR]

The prevention and control of bacterial contamination on ready‐to‐eat (RTE) fresh produce is an essential task to ensure food safety. Therefore, the development of novel and effective decontamination technologies to ensure microbiological safety of fruits and vegetables has gained considerable attention and new sanitisation methods are needed. The antimicrobial activity of essential oils (EOs) is well documented, but their application in fresh produce remains a challenge due to their hydrophobic nature. Thus, nanoemulsions efficiently contribute to support the use of EOs in foods by enhancing their dispersibility, their contact area and facilitating the introduction into bacterial cells. The combination of these factors ultimately increases their antimicrobial activity. Quantitative microbial risk assessment (QMRA) is gaining more attention as an effective tool to assess and prevent potential risks associated with food‐borne pathogens. In this context, the current project aims to study the effectiveness of different washing methods based on nanoemulsified EOs, comparing them against traditional methods, using a QMRA model for Escherichia coli O157:H7 on cherry tomatoes. Different simulations within a stochastic risk assessment model were implemented using the biorisk package for R, aiming to describe microbial behaviour and biological risk along the Romanian and Spanish food supply chains of RTE fresh produce. Nanoemulsions were prepared using oregano and rosemary EOs, each from Romania and Spain. The four nanoemulsions were evaluated as decontamination treatments to control the growth of E. coli O157:H7 on artificially contaminated cherry tomatoes. The decontamination treatments showed encouraging results, comparable to commonly used chlorine solutions. Therefore, oregano and rosemary nanoemulsions are promising and could be a feasible alternative for chlorine solutions in the reduction of microbiological contaminants. [ABSTRACT FROM AUTHOR]