Sex, cognitive state and falls as factors associated with malnutrition: a cross-sectional study of institutionalized older adults living in a rural area of Portugal

BACKGROUND

Malnutrition is an underestimated geriatric problem, with a high prevalence in institutionalized older adults. The identification of risk factors for malnutrition in elderly individuals must be a priority for governmental organizations worldwide.

METHODS

A total of 98 institutionalized seniors were enrolled in a cross-sectional study. For the assessment of risk factors, sociodemographic characteristics and health-related information were collected. The Mini-Nutritional Assessment Short-Form test was used to assess malnutrition in the sample population.

RESULTS

A significantly greater proportion of women than men were malnourished or at risk of malnutrition. In addition, the comparative analysis revealed that comorbidity, arthritis, balance impairment, dementia and fall episodes with serious injuries were significantly more frequent in the older adults categorized as malnourished or at risk of malnutrition than in those categorized as well-nourished.

CONCLUSIONS

Multivariable regression analysis revealed that being female, having a poor cognitive status and experiencing falls with injuries are the main independent factors influencing nutritional status in institutionalized older adults living in a rural area of Portugal.

Virtual fieldwork on a ship's bridge: virtual reality-reconstructed operation scenarios as contextual substitutes for fieldwork in design education

Designing for professional, high-risk user contexts often implies limited accessibility for interaction designers to conduct field research and field testing, and the measures taken by most universities in Norway in 2020 to prevent COVID-19 spread have further contributed to the problem of achieving the contextual insight needed throughout the design process by severely restricting travel for research purposes. In this paper, we describe the use of virtual reality-reconstructed operation scenarios (VRROS) for Arctic-going vessels implemented in support of and as a substitute for the contextual aspects of fieldwork in the education of master's students studying interaction design. The virtual reality rig contains three scenarios contextualizing ships' bridges and their surroundings originally developed for research on designing navigation and operation applications using augmented reality technology. We evaluate whether aspects of the VRROS can substitute for real fieldwork by evaluating students' use of the VRROS using a student questionnaire. Finally, we discuss the value and potential of using VRROS as a supplement and support when studying how to design for hard-to-reach contexts in the future.

Evaluating recycling fertilizers for tomato cultivation in hydroponics, and their impact on greenhouse gas emissions

Soilless culture systems offer an environmentally friendly and resource-efficient alternative to traditional cultivation systems fitting within the scheme of a circular economy. The objective of this research was to examine the sustainable integration of recycling fertilizers in hydroponic cultivation-creating a nutrient cycling concept for horticultural cultivation. Using the nutrient film technique (NFT), three recycling-based fertilizer variants were tested against standard synthetic mineral fertilization as the control, with 11 tomato plants (Solanum lycopersicum L. cv. Pannovy) per replicate (n = 4) and treatment: two nitrified urine-based fertilizers differing in ammonium/nitrate ratio (NH₄⁺:NO₃^-), namely (1) "Aurin" (AUR) and (2) "Crop" (CRO); as well as (3) an organo-mineral mixture of struvite and vinasse (S+V); and (4) a control (NPK). The closed chamber method was adapted for gas fluxes (N₂O, CH₄, and CO₂) from the root zone. There was no indication in differences of the total shoot biomass fresh matter and uptake of N, P and K between recycling fertilizers and the control. Marketable fruit yield was comparable between NPK, CRO and S+V, whereas lower yields occurred in AUR. The higher NH₄⁺:NO₃^- of AUR was associated with an increased susceptibility of blossom-end-rot, likely due to reduced uptake and translocation of Ca. Highest sugar concentration was found in S+V, which may have been influenced by the presence of organic acids in vinasse. N₂O emissions were highest in S+V, which corresponded to our hypothesis that N₂O emissions positively correlate with organic-C input by the fertilizer amendments. Remaining treatments showed barely detectable GHG emissions. A nitrified urine with a low NH₄⁺:NO₃^- (e.g., CRO) has a high potential as recycling fertilizer in NFT systems for tomato cultivation, and S+V proved to supply sufficient P and K for adequate growth and yield. Alternative cultivation strategies may complement the composition of AUR.

Telehealth and digital developments in society that persons 75 years and older in European countries have been part of: a scoping review

BACKGROUND

Demographic changes are leading to an ageing population in Europe. People are becoming more dependent on digital technologies and health ministries invest increasingly in digitalisation. Societal digital demands impact older people and learning to use new telehealth systems and digital devices are seen as a means of securing their needs.

METHODS

The present study undertakes a scoping review in order to map relevant evidence about telehealth and digital developments in society involving citizens aged 75 and over in European countries. It focuses on their experiences and the main barriers to, and facilitators of, societal digital demands. A framework proposed by Arksey and O`Malley was used to guide the scoping review process. The studies included in the review covered telehealth, digital technology and digital devices, and the context covered participants` own home or surroundings. A comprehensive search on PubMed/MEDLINE, CINAHL, Scopus, Embase and Open Grey was undertaken.

RESULTS

Out of 727 identified citations, 13 sources which met the inclusion criteria (9 original study articles, 2 theses, 1 letter about a product and 1 project report). Few of the studies identified have investigated European citizens 75 years and older separately. The studies included varied in their design, location and focus. Older people have experienced both telehealth and digital devices making life easier and the opposite. The outstanding facilitator found was that technology should be easy to use, and difficulty in remembering the instructions was seen as an important barrier. Interestingly, both social support and lack of social support were found as facilitators of using new devices.

CONCLUSIONS

Telehealth may give a sense of security but learning to use a new device often takes extra effort. Older people were more open to new devices if the possible advantages of the new technology outweighed the effort that would be involved in adopting a new strategy. As technology develops rapidly, and life expectancy in Europe is anticipated to rise continually, there is a need for new and additional research among older European citizens. Future research should cover the technical solutions most relevant to older people today, social support and participants` access to the devices.

Governance models for nature-based solutions: Seventeen cases from Germany

Nature-based solutions (NBS) for mitigating climate change are gaining popularity. The number of NBS is increasing, but research gaps still exist at the governance level. The objectives of this paper are (i) to give an overview of the implemented NBS for flood risk management and mitigation in Germany, (ii) to identify governance models that are applied, and (iii) to explore the differences between these models. The results of a hierarchical clustering procedure and a qualitative analysis show that while no one-size-fits-all governance model exists, polycentricism is an important commonality between the projects. The study concludes by highlighting the need for further research on traditional governance model reconversion and paradigm changes. We expect the findings to identify what has worked in the past, as well as what is important for the implementation of NBS for flood risk management in future projects.

The effect of a cluster-randomized controlled trial on lifestyle behaviors among families at risk for developing type 2 diabetes across Europe: the Feel4Diabetes-study

BACKGROUND

This study investigated the effect of the Feel4Diabetes-intervention, a 2-year multilevel intervention, on energy balance-related behaviors among European families at risk for developing type 2 diabetes. Intervention effects on self-reported physical activity, sedentary behavior and eating behaviors were investigated across and within the participating countries: Belgium, Finland, Greece, Spain, Hungary and Bulgaria.

METHODS

Families were recruited through schools, located in low socio-economic status areas. In total, 4484 families at risk for developing type 2 diabetes were selected using the FINDRISC-questionnaire. Parents' and children's energy balance-related behaviors data were collected by questionnaires at three time points (baseline, mid- and post intervention). Families assigned to the intervention group were invited to participate in a 2-year school-, community-, and family-based intervention to promote a healthier lifestyle, including counseling sessions (first intervention year) and text messages (second intervention year). Families assigned to the control group received standard care, including medical check-up results and recommendations and tips regarding a healthy lifestyle. To assess the intervention-effects, Mixed Models were conducted using the R-Package "lmer "with R v3.2.

RESULTS

Significant intervention effects were found on a certain number of families' lifestyle behaviors. Significant favorable intervention effects were detected on parents' water consumption and consumption of fruit and vegetables, and on children's consumption of sweets and moderate-to-vigorous physical activity. Analyses by country revealed significant favorable intervention effects on water consumption and on moderate-to-vigorous physical activity in Belgian parents and on fruit and vegetable consumption among Belgian children, on sweets consumption among Spanish parents and children, and on moderate-to-vigorous physical activity among Finnish children. Unfavorable intervention effects were found on the consumption of soft drinks and sugar-containing juices among Hungarian children and parents, while when examining the intervention effects for the overall population and per country, 10 from the 112 investigated outcome variables were improved in the intervention group compared to the control group (9%).

CONCLUSIONS

The Feel4Diabetes-intervention managed to improve a certain number of targeted lifestyle behaviors while the intervention was not effective on a large number of targeted lifestyle behaviors. The findings of the current study are encouraging, but further research is needed on how we can further improve effectiveness of lifestyle interventions to prevent type 2 diabetes in families at risk.

TRIAL REGISTRATION

The Feel4Diabetes-study is registered with the clinical trials registry http://clinicaltrials.gov , ID: 643708.

Metabolic cost in healthy fit older adults and young adults during overground and treadmill walking

PURPOSE

The purpose of this study was to determine whether net metabolic cost of walking is affected by age per se.

METHODS

We selected 10 healthy, active older adults (mean age 75 years) and 10 young adults (mean age 26 years), and determined their preferred overground walking speed. On the same day, in a morning and afternoon session, we had them walk at that speed overground and on a treadmill while we measured oxygen consumption rate. From the latter we subtracted the rate in sitting and calculated net metabolic cost.

RESULTS

Anthropometrics were not different between the groups nor was preferred walking speed (1.27 m s^-1 both groups). There was no difference in net metabolic cost of overground walking between older and young adults (e.g., in the morning 2.64 and 2.56 J kg^-1 m^-1, respectively, p > 0.05). In the morning session, net metabolic cost of walking was higher on the treadmill than overground in our older adults by 0.6 J kg^-1 m^-1 (p < 0.05), but not in young adults.

CONCLUSION

First, there is no effect of age per se on metabolic cost of overground walking. Second, older adults tend to have higher metabolic cost of walking on a treadmill than walking overground at preferred speed, and adaptation may take a long time. The commonly reported age-related elevation of metabolic cost of walking may be due to confounding factors causing preferred walking speed to be lower in older adults, and/or due to older adults reacting differently to treadmill walking than young adults.

Adverse cardiovascular magnetic resonance phenotypes are associated with greater likelihood of incident coronavirus disease 2019: findings from the UK Biobank

BACKGROUND

Coronavirus disease 2019 (COVID-19) disproportionately affects older people. Observational studies suggest indolent cardiovascular involvement after recovery from acute COVID-19. However, these findings may reflect pre-existing cardiac phenotypes.

AIMS

We tested the association of baseline cardiovascular magnetic resonance (CMR) phenotypes with incident COVID-19.

METHODS

We studied UK Biobank participants with CMR imaging and COVID-19 testing. We considered left and right ventricular (LV, RV) volumes, ejection fractions, and stroke volumes, LV mass, LV strain, native T1, aortic distensibility, and arterial stiffness index. COVID-19 test results were obtained from Public Health England. Co-morbidities were ascertained from self-report and hospital episode statistics (HES). Critical care admission and death were from HES and death register records. We investigated the association of each cardiovascular measure with COVID-19 test result in multivariable logistic regression models adjusting for age, sex, ethnicity, deprivation, body mass index, smoking, diabetes, hypertension, high cholesterol, and prior myocardial infarction.

RESULTS

We studied 310 participants (n = 70 positive). Median age was 63.8 [57.5, 72.1] years; 51.0% (n = 158) were male. 78.7% (n = 244) were tested in hospital, 3.5% (n = 11) required critical care admission, and 6.1% (n = 19) died. In fully adjusted models, smaller LV/RV end-diastolic volumes, smaller LV stroke volume, and poorer global longitudinal strain were associated with significantly higher odds of COVID-19 positivity.

DISCUSSION

We demonstrate association of pre-existing adverse CMR phenotypes with greater odds of COVID-19 positivity independent of classical cardiovascular risk factors.

CONCLUSIONS

Observational reports of cardiovascular involvement after COVID-19 may, at least partly, reflect pre-existing cardiac status rather than COVID-19 induced alterations.

Functional alterations by a subgroup of neonicotinoid pesticides in human dopaminergic neurons

Neonicotinoid pesticides, originally developed to target the insect nervous system, have been reported to interact with human receptors and to activate rodent neurons. Therefore, we evaluated in how far these compounds may trigger signaling in human neurons, and thus, affect the human adult or developing nervous system. We used SH-SY5Y neuroblastoma cells as established model of nicotinic acetylcholine receptor (nAChR) signaling. In parallel, we profiled dopaminergic neurons, generated from LUHMES neuronal precursor cells, as novel system to study nAChR activation in human post-mitotic neurons. Changes of the free intracellular Ca²⁺ concentration ([Ca²⁺]_i) were used as readout, and key findings were confirmed by patch clamp recordings. Nicotine triggered typical neuronal signaling responses that were blocked by antagonists, such as tubocurarine and mecamylamine. Pharmacological approaches suggested a functional expression of α7 and non-α7 nAChRs on LUHMES cells. In this novel test system, the neonicotinoids acetamiprid, imidacloprid, clothianidin and thiacloprid, but not thiamethoxam and dinotefuran, triggered [Ca²⁺]_i signaling at 10-100 µM. Strong synergy of the active neonicotinoids (at low micromolar concentrations) with the α7 nAChR-positive allosteric modulator PNU-120596 was observed in LUHMES and SH-SY5Y cells, and specific antagonists fully inhibited such signaling. To provide a third line of evidence for neonicotinoid signaling via nAChR, we studied cross-desensitization: pretreatment of LUHMES and SH-SY5Y cells with active neonicotinoids (at 1-10 µM) blunted the signaling response of nicotine. The pesticides (at 3-30 µM) also blunted the response to the non-α7 agonist ABT 594 in LUHMES cells. These data show that human neuronal cells are functionally affected by low micromolar concentrations of several neonicotinoids. An effect of such signals on nervous system development is a toxicological concern.

Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems?

Clinical prediction models (CPMs) have become fundamental for risk stratification across healthcare. The CPM pipeline (development, validation, deployment, and impact assessment) is commonly viewed as a one-time activity, with model updating rarely considered and done in a somewhat ad hoc manner. This fails to address the fact that the performance of a CPM worsens over time as natural changes in populations and care pathways occur. CPMs need constant surveillance to maintain adequate predictive performance. Rather than reactively updating a developed CPM once evidence of deteriorated performance accumulates, it is possible to proactively adapt CPMs whenever new data becomes available. Approaches for validation then need to be changed accordingly, making validation a continuous rather than a discrete effort. As such, "living" (dynamic) CPMs represent a paradigm shift, where the analytical methods dynamically generate updated versions of a model through time; one then needs to validate the system rather than each subsequent model revision.

Variation in hospital admission in febrile children evaluated at the Emergency Department (ED) in Europe: PERFORM, a multicentre prospective observational study

Objectives

Hospitalisation is frequently used as a marker of disease severity in observational Emergency Department (ED) studies. The comparison of ED admission rates is complex in potentially being influenced by the characteristics of the region, ED, physician and patient. We aimed to study variation in ED admission rates of febrile children, to assess whether variation could be explained by disease severity and to identify patient groups with large variation, in order to use this to reduce unnecessary health care utilization that is often due to practice variation.

Design

MOFICHE (Management and Outcome of Fever in children in Europe, part of the PERFORM study, www.perform2020.org), is a prospective cohort study using routinely collected data on febrile children regarding patient characteristics (age, referral, vital signs and clinical alarming signs), diagnostic tests, therapy, diagnosis and hospital admission.

Setting and participants

Data were collected on febrile children aged 0–18 years presenting to 12 European EDs (2017–2018).

Main outcome measures

We compared admission rates between EDs by using standardised admission rates after adjusting for patient characteristics and initiated tests at the ED, where standardised rates >1 demonstrate higher admission rates than expected and rates <1 indicate lower rates than expected based on the ED patient population.

Results

We included 38,120 children. Of those, 9.695 (25.4%) were admitted to a general ward (range EDs 5.1–54.5%). Adjusted standardised admission rates ranged between 0.6 and 1.5. The largest variation was seen in short admission rates (0.1–5.0), PICU admission rates (0.2–2.2), upper respiratory tract infections (0.4–1.7) and fever without focus (0.5–2.7). Variation was small in sepsis/meningitis (0.9–1.1).

Conclusions

Large variation exists in admission rates of febrile children evaluated at European EDs, however, this variation is largely reduced after correcting for patient characteristics and therefore overall admission rates seem to adequately reflect disease severity or a potential for a severe disease course. However, for certain patient groups variation remains high even after adjusting for patient characteristics.

Kemeny-based testing for COVID-19

Testing, tracking and tracing abilities have been identified as pivotal in helping countries to safely reopen activities after the first wave of the COVID-19 virus. Contact tracing apps give the unprecedented possibility to reconstruct graphs of daily contacts, so the question is: who should be tested? As human contact networks are known to exhibit community structure, in this paper we show that the Kemeny constant of a graph can be used to identify and analyze bridges between communities in a graph. Our 'Kemeny indicator' is the value of the Kemeny constant in the new graph that is obtained when a node is removed from the original graph. We show that testing individuals who are associated with large values of the Kemeny indicator can help in efficiently intercepting new virus outbreaks, when they are still in their early stage. Extensive simulations provide promising results in early identification and in blocking the possible 'super-spreaders' links that transmit disease between different communities.

Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer's disease patients

INTRODUCTION

The eye offers potential for the diagnosis of Alzheimer's disease (AD) with retinal imaging techniques being explored to quantify amyloid accumulation and aspects of neurodegeneration. To assess these changes, this proof-of-concept study combined hyperspectral imaging and optical coherence tomography to build a classification model to differentiate between AD patients and controls.

METHODS

In a memory clinic setting, patients with a diagnosis of clinically probable AD (n = 10) or biomarker-proven AD (n = 7) and controls (n = 22) underwent non-invasive retinal imaging with an easy-to-use hyperspectral snapshot camera that collects information from 16 spectral bands (460-620 nm, 10-nm bandwidth) in one capture. The individuals were also imaged using optical coherence tomography for assessing retinal nerve fiber layer thickness (RNFL). Dedicated image preprocessing analysis was followed by machine learning to discriminate between both groups.

RESULTS

Hyperspectral data and retinal nerve fiber layer thickness data were used in a linear discriminant classification model to discriminate between AD patients and controls. Nested leave-one-out cross-validation resulted in a fair accuracy, providing an area under the receiver operating characteristic curve of 0.74 (95% confidence interval [0.60-0.89]). Inner loop results showed that the inclusion of the RNFL features resulted in an improvement of the area under the receiver operating characteristic curve: for the most informative region assessed, the average area under the receiver operating characteristic curve was 0.70 (95% confidence interval [0.55, 0.86]) and 0.79 (95% confidence interval [0.65, 0.93]), respectively. The robust statistics used in this study reduces the risk of overfitting and partly compensates for the limited sample size.

CONCLUSIONS

This study in a memory-clinic-based cohort supports the potential of hyperspectral imaging and suggests an added value of combining retinal imaging modalities. Standardization and longitudinal data on fully amyloid-phenotyped cohorts are required to elucidate the relationship between retinal structure and cognitive function and to evaluate the robustness of the classification model.

1H, 13C and 15N assignment of the paramagnetic high potential iron-sulfur protein (HiPIP) PioC from Rhodopseudomonas palustris TIE-1

High potential iron-sulfur proteins (HiPIPs) are a class of small proteins (50-100 aa residues), containing a 4Fe-4S iron-sulfur cluster. The 4Fe-4S cluster shuttles between the oxidation states [Fe₄S₄]^3+/2+, with a positive redox potential in the range (500-50 mV) throughout the different known HiPIPs. Both oxidation states are paramagnetic at room temperature. HiPIPs are electron transfer proteins, isolated from photosynthetic bacteria and usually provide electrons to the photosynthetic reaction-center. PioC, the HIPIP isolated from Rhodopseudomonas palustris TIE-1, is the smallest among all known HiPIPs. Despite their small dimensions, an extensive NMR assignment is only available for two of them, because paramagnetism prevents the straightforward assignment of all resonances. We report here the complete NMR assignment of ¹H, ¹³C and ¹⁵N signals for the reduced [Fe₄S₄]²⁺ state of the protein. A set of double and triple resonance experiments performed with standardized parameters/datasets provided the assignment of about 72% of the residues. The almost complete resonance assignment (99.5% of backbone and ca. 90% of side chain resonances) was achieved by combining the above information with those obtained using a second set of NMR experiments, in which acquisition and processing parameters, as well as pulse sequences design, were optimized to account for the peculiar features of this paramagnetic protein.

Supply-side options to reduce land requirements of fully renewable electricity in Europe

Renewable electricity can fully decarbonise the European electricity supply, but large land requirements may cause land-use conflicts. Using a dynamic model that captures renewable fluctuations, I explore the relationship between land requirements and total system cost of different supply-side options in the future. Cost-minimal fully renewable electricity requires some 97,000 km2 (2% of total) land for solar and wind power installations, roughly the size of Portugal, and includes large shares of onshore wind. Replacing onshore wind with offshore wind, utility-scale PV, or rooftop PV reduces land requirements drastically with only small cost penalties. Moving wind power offshore is most cost-effective and reduces land requirements by 50% for a cost penalty of only 5%. Wind power can alternatively be replaced by photovoltaics, leading to a cost penalty of 10% for the same effect. My research shows that fully renewable electricity supply can be designed with very different physical appearances and impacts on landscapes and the population, but at similar cost.

Acceptability of genetically engineered algae biofuels in Europe: opinions of experts and stakeholders

BACKGROUND

The development of alternative pathways for sustainable fuel production is a crucial task for politics, industry and research, since the current use of fossil fuels contributes to resource depletion and climate change. Microalgae are a promising option, but the technology readiness level (TRL) is low and cannot compete economically with fossil fuels. Novel genetic engineering technologies are being investigated to improve productivity and reduce the cost of harvesting products extracted from or excreted by microalgae for fuel production. However, high resource efficiency and low costs alone are no guarantee that algae fuels will find their way into the market. Technologies must be accepted by the public to become valuable for society. Despite strong efforts in algae research and development, as well as political commitments at different scales to promote algae biofuels for transport sectors, little is known about public acceptance of this alternative transport fuel. Despite the advantages of algae technology, genetically engineered (GE) microalgae can be controversial in Europe due to risk perception. Therefore, the aim of this study was to investigate, for the first time, the knowledge and views of European experts and stakeholders on the conditions and requirements for acceptability of GE microalgae for next generation biofuel production.

RESULTS

The results of the survey-based study indicate that the majority of the respondents believe that GE algae biofuels could provide strong benefits compared to other fuels. The majority would choose to be final consumers of engineered algae biofuels, if there is clear evidence of their benefits and open communication of potential risks. They believe that closed production systems with high security standards and rigorous risk assessment should be applied to avoid unintended impacts on humans and nature. Some respondents, however, are not convinced about the need to alter natural occurring algae strains to increase productivity, arguing that there is a huge unexplored variety, and that the consequences of using genome editing are still unknown.

CONCLUSIONS

This evaluation of the opinions held by European experts and stakeholders regarding GE algae biofuels provides valuable and differentiated insights, both for future research and for the development of feasible socio-technical algae systems for next generation biofuel production. The identified conditions and requirements for achieving public acceptability can support the (re-)design of this innovative technology and adaptation of the framework conditions towards the implementation of algae biofuels in Europe.

Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets

Gene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.

Double-Gated Nanohelix as a Novel Tunable Binary Superlattice

We theoretically investigate the problem of an electron confined to a nanohelix between two parallel gates modelled as charged wires. The double-gated nanohelix system is a binary superlattice with properties highly sensitive to the gate voltages. In particular, the band structure exhibits energy band crossings for certain combinations of gate voltages, which could lead to quasi-relativistic Dirac-like phenomena. Our analysis for optical transitions induced by linearly and circularly polarized light suggests that a double-gated nanohelix can be used for versatile optoelectronic applications.

KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images

The application of convolutional neural networks (ConvNets) to harness high-content screening images or 2D compound representations is gaining increasing attention in drug discovery. However, existing applications often require large data sets for training, or sophisticated pretraining schemes. Here, we show using 33 IC50 data sets from ChEMBL 23 that the in vitro activity of compounds on cancer cell lines and protein targets can be accurately predicted on a continuous scale from their Kekulé structure representations alone by extending existing architectures (AlexNet, DenseNet-201, ResNet152 and VGG-19), which were pretrained on unrelated image data sets. We show that the predictive power of the generated models, which just require standard 2D compound representations as input, is comparable to that of Random Forest (RF) models and fully-connected Deep Neural Networks trained on circular (Morgan) fingerprints. Notably, including additional fully-connected layers further increases the predictive power of the ConvNets by up to 10%. Analysis of the predictions generated by RF models and ConvNets shows that by simply averaging the output of the RF models and ConvNets we obtain significantly lower errors in prediction for multiple data sets, although the effect size is small, than those obtained with either model alone, indicating that the features extracted by the convolutional layers of the ConvNets provide complementary predictive signal to Morgan fingerprints. Lastly, we show that multi-task ConvNets trained on compound images permit to model COX isoform selectivity on a continuous scale with errors in prediction comparable to the uncertainty of the data. Overall, in this work we present a set of ConvNet architectures for the prediction of compound activity from their Kekulé structure representations with state-of-the-art performance, that require no generation of compound descriptors or use of sophisticated image processing techniques. The code needed to reproduce the results presented in this study and all the data sets are provided at https://github.com/isidroc/kekulescope .

Unraveling essential cellulosomal components of the (Pseudo)Bacteroides cellulosolvens reveals an extensive reservoir of novel catalytic enzymes

BACKGROUND

(Pseudo)Bacteroides cellulosolvens is a cellulolytic bacterium that produces the most extensive and intricate cellulosomal system known in nature. Recently, the elaborate architecture of the B. cellulosolvens cellulosomal system was revealed from analysis of its genome sequence, and the first evidence regarding the interactions between its structural and enzymatic components were detected in vitro. Yet, the understanding of the cellulolytic potential of the bacterium in carbohydrate deconstruction is inextricably linked to its high-molecular-weight protein complexes, which are secreted from the bacterium.

RESULTS

The current proteome-wide work reveals patterns of protein expression of the various cellulosomal components, and explores the signature of differential expression upon growth of the bacterium on two major carbon sources-cellobiose and microcrystalline cellulose. Mass spectrometry analysis of the bacterial secretome revealed the expression of 24 scaffoldin structural units and 166 dockerin-bearing components (mainly enzymes), in addition to free enzymatic subunits. The dockerin-bearing components comprise cell-free and cell-bound cellulosomes for more efficient carbohydrate degradation. Various glycoside hydrolase (GH) family members were represented among 102 carbohydrate-degrading enzymes, including the omnipresent, most abundant GH48 exoglucanase. Specific cellulosomal components were found in different molecular-weight fractions associated with cell growth on different carbon sources. Overall, microcrystalline cellulose-derived cellulosomes showed markedly higher expression levels of the structural and enzymatic components, and exhibited the highest degradation activity on five different cellulosic and/or hemicellulosic carbohydrates. The cellulosomal activity of B. cellulosolvens showed high degradation rates that are very promising in biotechnological terms and were compatible with the activity levels exhibited by Clostridium thermocellum purified cellulosomes.

CONCLUSIONS

The current research demonstrates the involvement of key cellulosomal factors that participate in the mechanism of carbohydrate degradation by B. cellulosolvens. The powerful ability of the bacterium to exhibit different degradation strategies on various carbon sources was revealed. The novel reservoir of cellulolytic components of the cellulosomal degradation machineries may serve as a pool for designing new cellulolytic cocktails for biotechnological purposes.

DNA immunization site determines the level of gene expression and the magnitude, but not the type of the induced immune response

Optimization of DNA vaccine delivery improves the potency of the immune response and is crucial to clinical success. Here, we inquired how such optimization impacts the magnitude of the response, its specificity and type. BALB/c mice were DNA-immunized with two model immunogens, HIV-1 protease and reverse transcriptase by intramuscular or intradermal injections with electroporation. DNA immunogens were co-delivered with DNA encoding luciferase. Delivery and expression were monitored by in vivo bioluminescence imaging (BLI). The endpoint immune responses were assessed by IFN-γ/IL-2 FluoroSpot, multiparametric flow cytometry and antibody ELISA. Expression and immunogenicity were compared in relation to the delivery route. Regardless of the route, protease generated mainly IFN-γ, and reverse transcriptase, IL-2 and antibody response. BLI of mice immunized with protease- or reverse transcriptase/reporter plasmid mixtures, demonstrated significant loss of luminescence over time. The rate of decline of luminescence strongly correlated with the magnitude of immunogen-specific response, and depended on the immunogenicity profile and the immunization route. In vitro and in vivo BLI-based assays demonstrated that intradermal delivery strongly improved the immunogenicity of protease, and to a lesser extent, of reverse transcriptase. Immune response polarization and epitope hierarchy were not affected. Thus, by changing delivery/immunogen expression sites, it is possible to modulate the magnitude, but not the type or fine specificity of the induced immune response.