ExpertosLF: dynamic late fusion of CBIR systems using online learning with relevance feedback

One of the main challenges in CBIR systems is to choose discriminative and compact features, among dozens, to represent the images under comparison. Over the years, a great effort has been made to combine multiple features, mainly using early, late, and hierarchical fusion techniques. Unveiling the perfect combination of features is highly domain-specific and dependent on the type of image. Thus, the process of designing a CBIR system for new datasets or domains involves a huge experimentation overhead, leading to multiple fine-tuned CBIR systems. It would be desirable to dynamically find the best combination of CBIR systems without needing to go through such extensive experimentation and without requiring previous domain knowledge. In this paper, we propose ExpertosLF, a model-agnostic interpretable late fusion technique based on online learning with expert advice, which dynamically combines CBIR systems without knowing a priori which ones are the best for a given domain. At each query, ExpertosLF takes advantage of user's feedback to determine each CBIR contribution in the ensemble for the following queries. ExpertosLF produces an interpretable ensemble that is independent of the dataset and domain. Moreover, ExpertosLF is designed to be modular, and scalable. Experiments on 13 benchmark datasets from the Biomedical, Real, and Sketch domains revealed that: (i) ExpertosLF surpasses the performance of state of the art late-fusion techniques; (ii) it successfully and quickly converges to the performance of the best CBIR sets across domains without any previous domain knowledge (in most cases, fewer than 25 queries need to receive human feedback).

Adverse childhood experiences, bullying, inflammation and BMI in 10-year-old children: The biological embodiment

Exposure to adversity during the first years of life might already be biologically embedded well before adult life. Thus, the impact of different stressful experiences needs to be explored. This study aims to examine if the association between being victimized (adverse childhood experiences—ACEs and bullying) and (hs-) C-Reactive Protein (CRP) is explained by the influence of adversity on the body mass index (BMI) of the child. We included children from the Portuguese birth cohort Generation XXI (n = 3712) that at 10 years of age completed a questionnaire on the exposure to ACEs and bullying victimization, assessed by an adaptation from the original ACEs study and an adaptation of The Bully Scale Survey, respectively. Following an overnight fast, a venous blood sample was collected by trained nurses and hs-CRP was assayed in fresh blood samples. Weight and height were measured with the child in underwear and bare feet. Weight was measured to the nearest one-tenth of a kilogram with the use of a digital scale (Tanita), and height was measured to the nearest one-tenth of a centimetre with the use of a wall stadiometer (seca®). BMI was calculated as the value of weight (kg) over squared height (m), and computed as an age- and sex-specific BMI standard deviation (SD) score (z-score), according to the World Health Organization Child Growth Standards (5–19 years). Regression coefficients and respective 95% Confidence Interval [β(95%CI)] were computed using path analysis. We observed that ACEs had a positive total effect on hs-CRP at the age of 10 years (β = 0.06; 95%CI: -0.02; 0.15). A direct effect (β = 0.02; 95%CI: -0.01; 0.06) accounted for 66.1% of the association between ACEs and hs-CRP. A positive total effect of bullying victimization on hs-CRP (β = 0.20; 95%CI: 0.06; 0.34) was observed. A direct effect (β = 0.08; 95%CI: -0.05; 0.21) accounted for 40.0% of the association, while an indirect effect through BMI (β = 0.12; 95%CI: 0.06; 0.18) explained 60.0% of the pathway between bullying victimization and hs-CRP. Results suggest that there might be different mechanisms involved in the biological embedding of childhood experiences. BMI seems to explain a great part of the association between exposure to bullying victimization and hs-CRP at 10 years of age. Further research is still needed to better understand the mechanisms explaining the emergence and persistence of health poorer outcomes later in life for victims of abuse.

Effects of 2,4,6-Trichlorophenol on Clarias batrachus: a biomarkers approach

2,4,6-Trichlorophenol (2,4,6-TCP) is a common waste among the resulting chlorophenols generated in the production of common products classified as an extremely toxic, mutagenic, carcinogenic and highly persistent xenobiotic in the environment. To evaluate the impact of 2,4,6-TCP in aquatic systems, the catfish species Clarias batrachus has been selected to test its toxicity due to its high market value and consumption in India. Here is presented the impact of this compound on different physiological parameters of fish: haematological parameters (haemoglobin, total erythrocyte count, total leucocyte count and mean corpuscular haemoglobin), biochemical parameters (total serum protein and total serum glucose), growth and reproductive parameters (condition factor, hepatosomatic index, maturity index, specific growth rate, growth hormone, 17β-estradiol and testosterone), exposed to two concentrations of 2,4,6-TCP (0.5 mg/L and 1 mg/L - 1/10th and 1/20th of the LC₅₀) for a period of 15, 30 and 45 days. The results showed that C. batrachus even when exposed to the lower concentration (0.5 mg/L) for the shortest time (15 days) negatively impacted the organism in all the assessed parameters. This was highlighted by the Integrated Biomarker Response index (IBR), showing worse scores for the treatments (up to 20 × worse than the control). This work highlights the importance of continued research on the impact of 2,4,6-TCP, on an important commercial, supported by the high environmental persistence of this compound that can reach the same range of tested concentrations.

A pipeline for the reconstruction and evaluation of context-specific human metabolic models at a large-scale

Constraint-based (CB) metabolic models provide a mathematical framework and scaffold for in silico cell metabolism analysis and manipulation. In the past decade, significant efforts have been done to model human metabolism, enabled by the increased availability of multi-omics datasets and curated genome-scale reconstructions, as well as the development of several algorithms for context-specific model (CSM) reconstruction. Although CSM reconstruction has revealed insights on the deregulated metabolism of several pathologies, the process of reconstructing representative models of human tissues still lacks benchmarks and appropriate integrated software frameworks, since many tools required for this process are still disperse across various software platforms, some of which are proprietary. In this work, we address this challenge by assembling a scalable CSM reconstruction pipeline capable of integrating transcriptomics data in CB models. We combined omics preprocessing methods inspired by previous efforts with in-house implementations of existing CSM algorithms and new model refinement and validation routines, all implemented in the Troppo Python-based open-source framework. The pipeline was validated with multi-omics datasets from the Cancer Cell Line Encyclopedia (CCLE), also including reference fluxomics measurements for the MCF7 cell line. We reconstructed over 6000 models based on the Human-GEM template model for 733 cell lines featured in the CCLE, using MCF7 models as reference to find the best parameter combinations. These reference models outperform earlier studies using the same template by comparing gene essentiality and fluxomics experiments. We also analysed the heterogeneity of breast cancer cell lines, identifying key changes in metabolism related to cancer aggressiveness. Despite the many challenges in CB modelling, we demonstrate using our pipeline that combining transcriptomics data in metabolic models can be used to investigate key metabolic shifts. Significant limitations were found on these models ability for reliable quantitative flux prediction, thus motivating further work in genome-wide phenotype prediction.

Genome-scale models of human metabolism are promising tools capable of contextualising large omics datasets within a framework that enables analysis and manipulation of metabolic phenotypes. Despite various successes in applying these methods to provide mechanistic hypotheses for deregulated metabolism in disease, there is no standardized workflow to extract these models using existing methods and the tools required to do so are mostly implemented using proprietary software. We have assembled a generic pipeline to extract and validate context-specific metabolic models using multi-omics datasets and implemented it using the troppo framework. We first validate our pipeline using MCF7 cell line models and assess their ability to predict lethal gene knockouts as well as flux activity using multi-omics data. We also demonstrate how this approach can be generalized for large-scale transcriptomics datasets and used to generate insights on the metabolic heterogeneity of cancer and relevant features for other data mining approaches. The pipeline is available as part of an open-source framework that is generic for a variety of applications.

Metabolomic signatures after bariatric surgery - a systematic review

Metabolomics emerged as an important tool to gain insights on how the body responds to therapeutic interventions. Bariatric surgery is the most effective treatment for severe obesity and obesity-related co-morbidities. Our aim was to conduct a systematic review of the available data on metabolomics profiles that characterize patients submitted to different bariatric surgery procedures, which could be useful to predict clinical outcomes including weight loss and type 2 diabetes remission. For that, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - PRISMA guidelines were followed. Data from forty-seven original study reports addressing metabolomics profiles induced by bariatric surgery that met eligibility criteria were compiled and summarized. Amino acids, lipids, energy-related and gut microbiota-related were the metabolite classes most influenced by bariatric surgery. Among these, higher pre-operative levels of specific lipids including phospholipids, long-chain fatty acids and bile acids were associated with post-operative T2D remission. As conclusion, metabolite profiling could become a useful tool to predict long term response to different bariatric surgery procedures, allowing more personalized interventions and improved healthcare resources allocation.

A new theropod dinosaur from the early cretaceous (Barremian) of Cabo Espichel, Portugal: Implications for spinosaurid evolution

Spinosaurids are some of the most enigmatic Mesozoic theropod dinosaurs due to their unique adaptations to aquatic environments and their relative scarcity. Their taxonomy has proven to be especially problematic. Recent discoveries from Western Europe in general, specifically Iberia, provide some of the best specimens for the understanding of their phylogeny, leading to the description of the spinosaurid Vallibonavenatrix cani and the recognition of the Iberian dinosaur Camarillasaurus cirugedae as one of them. Portuguese associated spinosaurid remains (ML1190) from the Papo Seco Formation (early Barremian) were previously assigned to Baryonyx walkeri but new material recovered in 2020 along with new phylogenetic analyses suggests a different phylogenetic placement, making their revision necessary. Here we show that these remains are not attributable to Baryonyx walkeri, but to a new genus and species, Iberospinus natarioi, gen. et sp. nov. The new taxon is characterized by the presence of a single Meckelian foramen in the Meckelian sulcus, a straight profile of the ventral surface of the dentary and a distal thickening of the acromion process of the pubis between other characters. Iberospinus natarioi is recovered as a sister taxon of the clade formed by Baryonyx and Suchomimus, and outside Spinosaurinae when Vallibonaventrix cani is excluded from the analysis. The description of this taxon reinforces Iberia as a hotspot for spinosaur biodiversity, with several endemic taxa for the region. As expected for the clade, the dentary displays a highly vascularized neurovascular network. The morphometric analysis of parts of the skeleton (pedal phalanx and caudal vertebrae, among others) shows an intermediate condition between basal tetanurans and spinosaurines.

Becoming a Fraternal Organization: Insights from the Encyclical Fratelli Tutti

We uncover fundamental dimensions of the process through which organizations embed the practice of fraternity through embarking on an organizational journey in the direction of the common good. Building on the latest encyclical of Pope Francis, Fratelli Tutti, about fraternal and social friendship, we offer insight into the understanding of what it means to become a fraternal organization and reflect on the key ethical and paradoxical challenges for organizations aiming at collectively contributing to the common good. We add to previous work by characterizing this journey as a process involving unique ethical challenges that emerge from the paradoxes associated with this process and how this might change the nature of the relationships between organizations and others within the organizational landscape.

Effects of combined training on metabolic profile, lung function, stress and quality of life in sedentary adults: A study protocol for a randomized controlled trial

Background

Both physical inactivity and sedentary behavior are considered modifiable risk factors for chronic diseases and all-cause mortality. Adult office-workers spend most of their working day in sedentary behaviors, so they are particularly at high risk of developed chronic diseases (e.g., cardiovascular diseases, metabolic disorders like diabetes mellitus, …). It seems important to promote behavioral changes that could prevent or delay metabolic disease development. Evidence supports the use of exercise programs, however, to date there are several knowledge gaps and inconsistencies in the literature regarding the effects of Combined Training (i.e., aerobic plus resistance training) in sedentary healthy adults. This paper outlines an RCT designed to evaluate the effects of a 16-week combined training program on biochemical and immune markers of metabolic disease, lung function, salivary stress hormones and subjective quality of life (primary outcomes), as well as on body composition and physical fitness (secondary outcomes) in sedentary middle-aged office-workers. Furthermore, we aimed to assess the associations between the changes promoted by the exercise program and the different variables studied.

Methods and design

This is a single-blinded two-arm RCT with parallel groups. A minimum of healthy 40 office-workers aged 40–64 years will be recruited to engage in a 16-week intervention study. After baseline assessments, participants will be randomized to one of the two groups: (1) combined training group or (2) control group. Baseline assessments will be repeated after 8 weeks of intervention (mid-testing) and upon completion of the intervention (post-testing).

Discussion

This RCT involves a multi-disciplinary approach and seems to be a relevant contribution to understanding the potential role of combined training in improving the metabolic profile, lung function, stress, and quality of life in adults. The results can provide important insights for clinical recommendations and for the optimization of strategies to prevent metabolic disorders in adults with sedentary jobs.

Trial registration

This trial is registered with ClinicalTrials.gov (registration number: NCT04868240; date of registration April 30, 2021).

Multi attribute method implementation using a High Resolution Mass Spectrometry platform: From sample preparation to batch analysis

Quality control of biopharmaceuticals such as monoclonal antibodies (mAbs) has been evolving and becoming more challenging as the requirements of the regulatory agencies increase due to the demanding complexity of products under evaluation. Mass Spectrometry (MS)-based methods such as the multi-attribute method (MAM) are being explored to achieve a deeper understanding of the attributes critical for the safety, efficacy, and quality of these products. MAM uses high mass accuracy/high-resolution MS data that enables the direct and simultaneous monitoring of relevant product quality attributes (PQAs, in particular, chemical modifications) in a single workflow, replacing several orthogonal methods, reducing time and costs associated with these assays. Here we describe a MAM implementation process using a QTOF high resolution platform. Method implementation was accomplished using NIST (National Institute for Standards and Technology) mAb reference material and an in-process mAb sample. PQAs as glycosylation profiles, methionine oxidation, tryptophan dioxidation, asparagine deamidation, pyro-Glu at N-terminal and glycation were monitored. Focusing on applications that require batch analysis and high-throughput, sample preparation and LC-MS parameters troubleshooting are discussed. This MAM workflow was successfully explored as reference analytical tool for comprehensive characterization of a downstream processing (DSP) polishing platform and for a comparability study following technology transfer between different laboratories.

Alternative pathways for hydrogen sink originated from the ruminal fermentation of carbohydrates: Which microorganisms are involved in lowering methane emission?

Agriculture is responsible for a great share of the anthropogenic sources of greenhouse gases that, by warming the earth, threaten its biodiversity. Among greenhouse gas emissions, enteric CH4 from livestock is an important target to slow down climate changes. The CH4 is originated from rumen fermentation and its concentration is affected by several factors, including genetics and nutrition. Ruminants have an extraordinary symbiosis with microorganisms (bacteria, fungi, and protozoa) that ferment otherwise indigestible carbohydrates, from which they obtain energy to grow and continue actively producing, among other products, volatile fatty acids, CO2 and H2. Detrimental ruminal accumulation of H2 is avoided by methanogenesis carried out by Archaea methanogens. Importantly, methanogenesis is not the only H2 sink pathway. In fact, other bacteria can reduce substrates using metabolic hydrogen formed during carbohydrate fermentation, namely propionate production and reductive acetogenesis, thus lowering the CH4 produced. Although the complexity of rumen poses challenges to mitigate CH4 production, the emergence of sequencing techniques that allow the study of microbial communities, gene expression, and metabolome are largely contributing to unravel pathways and key players in the rumen. Indeed, it is now recognized that in vivo emissions of CH4 are correlated to microbial communities, and particularly with the abundance of methanogens, several bacterial groups, and  their genes. The goal of CH4 mitigation is to work in favor of the natural processes, without compromising rumen function, animal health, and productivity. Notwithstanding, the major challenge continues to be the feasibility and affordability of the proposed solutions.

Plant-Based Diet and IGF-1 Modulation on HER2-Positive Breast Cancer: A Lifestyle Medicine Nutrition Approach in Oncology

Breast cancer is the second most common type of cancer in women worldwide, where nutritional intervention should be part of a multidisciplinary lifestyle approach in oncology, promoting therapeutic success. Insulin-like growth factor 1 (IGF-1), along with estrogen, can promote the development of neoplastic cells in breast tissue. Cancers that develop under IGF-1 stimulation are often resistant to therapy. This case report describes a 47-year-old woman, body mass index 27.4 kg/m2, with HER2-positive breast cancer, as well as elevated blood glucose, total cholesterol, and low-density lipoprotein cholesterol. Soon after her breast cancer diagnosis, she transitioned from a Western pattern diet (WPD) to a predominantly whole-food, plant-based diet (PWFPBD) for 1035 days, followed by 232 days of PWFPBD plus night fasting for 16 hours per day. IGF-1 decreased 22.38%, glycemia and total cholesterol decreased by -55.06% and -36.00% at the end of the first intervention and went up by 6.25%, and 3.87%, respectively, at the end of the second intervention. A PWFPBD, with or without 16-hour overnight fasting, seems to modulate plasma levels of IGF-1 on a 47-year-old woman diagnosed with breast cancer, type HER2-positive. Future research, should explore the physiologic and pathophysiological mechanisms and clarify whether this dietary strategy, may be clinically useful in preventing HER2-positive breast cancer.

Momordica balsamina: phytochemistry and pharmacological potential of a gifted species

Momordica balsamina L. (Cucurbitaceae), frequently named balsam apple, southern balsam pear or African pumpkin, is a vegetable with high nutritional value, being mostly used as food in sub-Saharan Africa. It has also been largely used in traditional medicine to treat several diseases, such as malaria fevers and diabetes. As a member of the Cucurbitaceae family, the main constituents are cucurbitane-type triterpenoids, with different oxidation patterns, named cucurbitacins. This review aims at summarizing our contribution to the phytochemical study of M. balsamina and the evaluation of the isolated cucurbitacins and derivatives as multidrug resistance reversers in cancer cells and bacteria. In this way, the selective antiproliferative activity against multidrug resistant cancer cells of cucurbitacins obtained from M. balsamina, their ability as P-glycoprotein inhibitors in cancer cells overexpressing this ABC transporter, as well as efflux pump inhibitors in resistant bacteria strains are reviewed. Moreover, the in vitro antimalarial activity of cucurbitacins and acyl derivatives against the blood and liver-stages of Plasmodium strains, and the in vivo activity of selected compounds is also reviewed. Besides our work, edible and medicinal uses, and other studies mainly reporting the biological activities of M. balsamina extracts, such as antidiabetic, antibacterial, anti-inflammatory, and antioxidant properties are also addressed.

A mathematical model for the dependence of keratin aggregate formation on the quantity of mutant keratin expressed in EGFP-K14 R125P keratinocytes

We examined keratin aggregate formation and the possible mechanisms involved. With this aim, we observed the effect that different ratios between mutant and wild-type keratins expressed in cultured keratinocytes may have on aggregate formation in vitro, as well as how keratin aggregate formation affects the mechanical properties of cells at the cell cortex. To this end we prepared clones with expression rates as close as possible to 25%, 50% and 100% of the EGFP-K14 proteins (either WT or R125P and V270M mutants). Our results showed that only in the case of the 25% EGFP-K14 R125P mutant significant differences could be seen. Namely, we observed in this case the largest accumulation of keratin aggregates and a significant reduction in cell stiffness. To gain insight into the possible mechanisms behind this observation, we extended our previous mathematical model of keratin dynamics by implementing a more complex reaction network that considers the coexistence of wild-type and mutant keratins in the cell. The new model, consisting of a set of coupled, non-linear, ordinary differential equations, allowed us to draw conclusions regarding the relative amounts of intermediate filaments and aggregates in cells, and suggested that aggregate formation by asymmetric binding between wild-type and mutant keratins could explain the data obtained on cells grown in culture.

The role of social connection on the experience of COVID-19 related post-traumatic growth and stress

BACKGROUND

Historically social connection has been an important way through which humans have coped with large-scale threatening events. In the context of the COVID-19 pandemic, lockdowns have deprived people of major sources of social support and coping, with others representing threats. Hence, a major stressor during the pandemic has been a sense of social disconnection and loneliness. This study explores how people's experience of compassion and feeling socially safe and connected, in contrast to feeling socially disconnected, lonely and fearful of compassion, effects the impact of perceived threat of COVID-19 on post-traumatic growth and post-traumatic stress.

METHODS

Adult participants from the general population (N = 4057) across 21 countries worldwide, completed self-report measures of social connection (compassion for self, from others, for others; social safeness), social disconnection (fears of compassion for self, from others, for others; loneliness), perceived threat of COVID-19, post-traumatic growth and traumatic stress.

RESULTS

Perceived threat of COVID-19 predicted increased post-traumatic growth and traumatic stress. Social connection (compassion and social safeness) predicted higher post-traumatic growth and traumatic stress, whereas social disconnection (fears of compassion and loneliness) predicted increased traumatic symptoms only. Social connection heightened the impact of perceived threat of COVID-19 on post-traumatic growth, while social disconnection weakened this impact. Social disconnection magnified the impact of the perceived threat of COVID-19 on traumatic stress. These effects were consistent across all countries.

CONCLUSIONS

Social connection is key to how people adapt and cope with the worldwide COVID-19 crisis and may facilitate post-traumatic growth in the context of the threat experienced during the pandemic. In contrast, social disconnection increases vulnerability to develop post-traumatic stress in this threatening context. Public health and Government organizations could implement interventions to foster compassion and feelings of social safeness and reduce experiences of social disconnection, thus promoting growth, resilience and mental wellbeing during and following the pandemic.

A non-lethal method for studying scorpion venom gland transcriptomes, with a review of potentially suitable taxa to which it can be applied

Scorpion venoms are mixtures of proteins, peptides and small molecular compounds with high specificity for ion channels and are therefore considered to be promising candidates in the venoms-to-drugs pipeline. Transcriptomes are important tools for studying the composition and expression of scorpion venom. Unfortunately, studying the venom gland transcriptome traditionally requires sacrificing the animal and therefore is always a single snapshot in time. This paper describes a new way of generating a scorpion venom gland transcriptome without sacrificing the animal, thereby allowing the study of the transcriptome at various time points within a single individual. By comparing these venom-derived transcriptomes to the traditional whole-telson transcriptomes we show that the relative expression levels of the major toxin classes are similar. We further performed a multi-day extraction using our proposed method to show the possibility of doing a multiple time point transcriptome analysis. This allows for the study of patterns of toxin gene activation over time a single individual, and allows assessment of the effects of diet, season and other factors that are known or likely to influence intraindividual venom composition. We discuss the gland characteristics that may allow this method to be successful in scorpions and provide a review of other venomous taxa to which this method may potentially be successfully applied.

The association of social skills and behaviour problems with bullying engagement in Portuguese adolescents: From aggression to victimization behaviors

This study examines sex differences regarding social skills, behavior problems and bullying engagement, and the association of social skills and behavior problems with bullying engagement, in adolescents. Participants were 447 Portuguese adolescents (252 girls and 195 boys) aged between 12 and 19-years-old. Social skills and behavior problems were assessed using the self-report version of Social Skills Improvement System - Rating Scales. Bullying engagement was assessed using the Scale of Interpersonal Behavior at School. Girls scored higher on social skills and reported more internalizing and fewer externalizing problems than boys, whereas boys reported more aggressive verbal behaviors than girls. Adolescents exhibiting fewer social skills and more internalizing and externalizing problems engage more frequently in bullying aggressive behaviors. In addition, adolescents presenting more internalizing and externalizing problems are more often victimized by bullies. Furthermore, boys more frequently engage in bullying aggressive and victimization behaviors, whereas younger adolescents with more social skills tend to engage less frequently in bullying aggressive behaviors.

Inheritances, social classes, and wealth distribution

We consider a simple theoretical model to investigate the impact of inheritances on the wealth distribution. Wealth is described as a finite resource, which remains constant over different generations and is divided equally among offspring. All other sources of wealth are neglected. We consider different societies characterized by a different offspring probability distribution. We find that, if the population remains constant, the society reaches a stationary wealth distribution. We show that inequality emerges every time the number of children per family is not always the same. For realistic offspring distributions from developed countries, the model predicts a Gini coefficient of G ≈ 0.3. If we divide the society into wealth classes and set the probability of getting married to depend on the distance between classes, the stationary wealth distribution crosses over from an exponential to a power-law regime as the number of wealth classes and the level of class distinction increase.

What is different about social enterprises’ operational practices and capabilities?

The aim of this paper is to identify the main practices and capabilities developed by social enterprises and to explore the relationship between the dual organizational identity of social enterprises and their operational capabilities. A multiple case-study research is conducted comprising five cases representative of the diversity of social enterprise models. The results suggest that the operations strategy in social enterprises is influenced by their dual organizational identity and entails some operational practices and capabilities beyond those traditionally reported in manufacturing companies. They adopt a greater diversity of practices aimed at improvement and cooperation capabilities and their specificities lead to the development of the mobilization of resources capability and the openness capability. Social enterprises with a high social identity show greater evidence of the development of these operational capabilities. This study contributes to the literature on operations strategy by identifying a set of operational practices and capabilities developed by social enterprises and exploring how they are influenced by their dual organizational identity. It responds to the claims that suggest that studying social enterprises would be a fertile ground to advance theoretical and empirical research in the field of service operations. Developing knowledge on the operations management of social enterprises provides valuable insights into improving the performance of such organizations.

Absolute quantitative proteomics using the total protein approach to identify novel clinical immunohistochemical markers in renal neoplasms

BACKGROUND

Renal neoplasms encompass a variety of malignant and benign tumors, including many with shared characteristics. The diagnosis of these renal neoplasms remains challenging with currently available tools. In this work, we demonstrate the total protein approach (TPA) based on high-resolution mass spectrometry (MS) as a tool to improve the accuracy of renal neoplasm diagnosis.

METHODS

Frozen tissue biopsies of human renal tissues [clear cell renal cell carcinoma (n = 7), papillary renal cell carcinoma (n = 5), chromophobe renal cell carcinoma (n = 5), and renal oncocytoma (n = 5)] were collected for proteome analysis. Normal adjacent renal tissue (NAT, n = 5) was used as a control. Proteins were extracted and digested using trypsin, and the digested proteomes were analyzed by label-free high-resolution MS (nanoLC-ESI-HR-MS/MS). Quantitative analysis was performed by comparison between protein abundances of tumors and NAT specimens, and the label-free and standard-free TPA was used to obtain absolute protein concentrations.

RESULTS

A total of 205 differentially expressed proteins with the potential to distinguish the renal neoplasms were found. Of these proteins, a TPA-based panel of 24, including known and new biomarkers, was selected as the best candidates to differentiate the neoplasms. As proof of concept, the diagnostic potential of PLIN2, TUBB3, LAMP1, and HK1 was validated using semi-quantitative immunohistochemistry with a total of 128 samples assessed on tissue micro-arrays.

CONCLUSIONS

We demonstrate the utility of combining high-resolution MS and the TPA as potential new diagnostic tool in the pathology of renal neoplasms. A similar TPA approach may be implemented in any cancer study with solid biopsies.

Bacterial persistence is essential for susceptible cell survival in indirect resistance, mainly for lower cell densities

Antibiotic-susceptible bacteria may survive bactericidal antibiotics if other co-inhabiting bacteria detoxify the medium through antibiotic degradation or modification, a phenomenon denominated as indirect resistance. However, it is unclear how susceptible cells survive while the medium is still toxic. One explanation relies on the speed of detoxification, and another, non-exclusive explanation, relies on persistence, a state of bacterial dormancy where cells with low metabolic activity and growth rates are phenotypically tolerant to antibiotics and other cytotoxic substances. Here we simulated the fate of susceptible cells in laboratory experiments in the context of indirect resistance to understand whether persistence is necessary to explain the survival of susceptible cells. Depending on the strain and experimental conditions, the decay of persister populations may follow an exponential or a power-law distribution. Therefore, we studied the impact of both distributions in the simulations. Moreover, we studied the impact of considering that persister cells have a mechanism to sense the presence of a toxic substance–a mechanism that would enable cells to leave the dormant state when the medium becomes nontoxic. The simulations show that surviving susceptible cells under indirect resistance may originate both from persister and non-persister populations if the density of detoxifying cells is high. However, persistence was necessary when the initial density of detoxifying cells was low, although persister cells remained in that dormancy state for just a few hours. Finally, the results of our simulations are consistent both with exponential and power-law decay of the persistence population. Whether indirect resistance involves persistence should impact antibiotic treatments.

On the Development of a Cutaneous Flavonoid Delivery System: Advances and Limitations

Flavonoids are one of the vital classes of natural polyphenolic compounds abundantly found in plants. Due to their wide range of therapeutic properties, which include antioxidant, anti-inflammatory, photoprotective, and depigmentation effects, flavonoids have been demonstrated to be promising agents in the treatment of several skin disorders. However, their lipophilic nature and poor water solubility invariably lead to limited oral bioavailability. In addition, they are rapidly degraded and metabolized in the human body, hindering their potential contribution to the prevention and treatment of many disorders. Thus, to overcome these challenges, several cutaneous delivery systems have been extensively studied. Topical drug delivery besides offering an alternative administration route also ensures a sustained release of the active compound at the desired site of action. Incorporation into lipid or polymer-based nanoparticles appears to be a highly effective approach for cutaneous delivery of flavonoids with good encapsulation potential and reduced toxicity. This review focuses on currently available formulations used to administer either topically or systemically different classes of flavonoids in the skin, highlighting their potential application as therapeutic and preventive agents.

Balancing Technology, Pedagogy and the New Normal: Post-pandemic Challenges for Higher Education

The Covid-19 pandemic has presented an opportunity for rethinking assumptions about education in general and higher education in particular. In the light of the general crisis the pandemic caused, especially when it comes to the so-called emergency remote teaching (ERT), educators from all grades and contexts experienced the necessity of rethinking their roles, the ways of supporting the students’ learning tasks and the image of students as self-organising learners, active citizens and autonomous social agents. In our first Postdigital Science and Education paper, we sought to distil and share some expert advice for campus-based university teachers to adapt to online teaching and learning. In this sequel paper, we ask ourselves: Now that campus-based university teachers have experienced the unplanned and forced version of Online Learning and Teaching (OLT), how can this experience help bridge the gap between online and in-person teaching in the following years? The four experts, also co-authors of this paper, interviewed aligning towards an emphasis on pedagogisation rather than digitalisation of higher education, with strategic decision-making being in the heart of post-pandemic practices. Our literature review of papers published in the last year and analysis of the expert answers reveal that the ‘forced’ experience of teaching with digital technologies as part of ERT can gradually give place to a harmonious integration of physical and digital tools and methods for the sake of more active, flexible and meaningful learning.

Signatures in SARS-CoV-2 spike protein conferring escape to neutralizing antibodies

Understanding SARS-CoV-2 evolution and host immunity is critical to control COVID-19 pandemics. At the core is an arms-race between SARS-CoV-2 antibody and angiotensin-converting enzyme 2 (ACE2) recognition, a function of the viral protein spike. Mutations in spike impacting antibody and/or ACE2 binding are appearing worldwide, imposing the need to monitor SARS-CoV2 evolution and dynamics in the population. Determining signatures in SARS-CoV-2 that render the virus resistant to neutralizing antibodies is critical. We engineered 25 spike-pseudotyped lentiviruses containing individual and combined mutations in the spike protein, including all defining mutations in the variants of concern, to identify the effect of single and synergic amino acid substitutions in promoting immune escape. We confirmed that E484K evades antibody neutralization elicited by infection or vaccination, a capacity augmented when complemented by K417N and N501Y mutations. In silico analysis provided an explanation for E484K immune evasion. E484 frequently engages in interactions with antibodies but not with ACE2. Importantly, we identified a novel amino acid of concern, S494, which shares a similar pattern. Using the already circulating mutation S494P, we found that it reduces antibody neutralization of convalescent and post-immunization sera, particularly when combined with E484K and with mutations able to increase binding to ACE2, such as N501Y. Our analysis of synergic mutations provides a signature for hotspots for immune evasion and for targets of therapies, vaccines and diagnostics.

Association between respiratory hospital admissions and air quality in Portugal: A count time series approach

Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.

Effects of Different Recovery Times on Internal and External Load During Small-Sided Games in Soccer

BACKGROUND

The ability to maintain a high intensity of exercise over several repetitions depends on recovery from previous exercises. This study aimed to identify the effects of different recovery times on internal and external load during small-sided soccer games.

HYPOTHESIS

An increase in recovery time will increase the external training load and decrease the internal exercise load, which will result in a greater physical impact of the exercise.

STUDY DESIGN

Cross-sectional study.

LEVEL OF EVIDENCE

Level 2.

METHODS

Twenty male semiprofessional soccer players participated in the present study. They performed the same exercise (5-a-side game format) continuously (1 × 18 minutes) and repeatedly/fractionated (3 × 6 minutes) with different recovery times (30 seconds, 1 minute, 1.5 minutes, and 2 minutes). Their internal load (ie, average heart rate (HR) and maximum HR) and external load (ie, total distance, maximum speed, and ratio meters) were measured using an HR band and an inertial device equipped with a global positioning system, respectively.

RESULTS

The manipulation of recovery times induced differences in the internal and external load. For the same total duration, the external and internal load indicators exhibited higher values during the fractionated method, particularly with short recovery periods.

CONCLUSION

The application of small-sided soccer games with different recovery times induced varying responses in training load. To maintain high physical performance and high training load, the fractional method with short recovery periods (ie, 30 seconds) should be used. In contrast, to carefully manage players' efforts and decrease response to training load, continuous or fractional methods with longer recovery periods (ie, 1-2 minutes) should be used.

CLINICAL RELEVANCE

The proper prescription of recovery time between exercises facilitates enhanced training efficiency and optimized performance.

Oxytocin and vasopressin modulation of prisoner's dilemma strategies

BACKGROUND

The neuropeptides oxytocin and vasopressin have been repeatedly implicated in social decision making by enhancing social salience and, generally, cooperation. The iterated and sequential version of the prisoner's dilemma (PD) game is a social dilemma paradigm eliciting strategies of cooperation versus competition.

AIMS

We aimed to characterise the role of PD players' sex, game partner type (computer vs. human) and oxytocin or vasopressin inhalation on the player's strategy preference.

METHODS

Participants (153 men; 151 women) were randomised to intranasal 24 IU oxytocin, 20 IU vasopressin or placebo, double-blind, and played the PD. We examined main and interactive effects of sex, drug and partner type on strategy preference.

RESULTS

We found a pervasive preference for a tit-for-tat strategy (i.e. general sensitivity to the partner's choices) over unconditional cooperation, particularly when against a human rather than a computer partner. Oxytocin doubled this sensitivity in women (i.e. the preference for tit-for-tat over unconditional cooperation strategies) when playing against computers, which suggests a tendency to anthropomorphise them, and doubled women's unconditional cooperation preference when playing against humans. Vasopressin doubled sensitivity to the partner's previous choices (i.e. for tit-for-tat over unconditional cooperation) across sexes and partner types.

CONCLUSIONS

These findings suggest that women may be more sensitive to oxytocin's social effects of anthropomorphism of non-humans and of unconditional cooperation with humans, which may be consistent with evolutionary pressures for maternal care, and that vasopressin, irrespective of sex and partner type, may be generally sensitising humans to others' behaviour.

Machine Learning-Enhanced T Cell Neoepitope Discovery for Immunotherapy Design

Immune responses mediated by T cells are aimed at specific peptides, designated T cell epitopes, that are recognized when bound to human leukocyte antigen (HLA) molecules. The HLA genes are remarkably polymorphic in the human population allowing a broad and fine-tuned capacity to bind a wide array of peptide sequences. Polymorphisms might generate neoepitopes by impacting the HLA-peptide interaction and potentially alter the level and type of generated T cell responses. Multiple algorithms and tools based on machine learning (ML) have been implemented and are able to predict HLA-peptide binding affinity with considerable accuracy. Challenges in this field include the availability of adequate epitope datasets for training and benchmarking and the development of fully integrated pipelines going from next-generation sequencing to neoepitope prediction and quality analysis metrics. Effectively predicting neoepitopes from in silico data is a demanding task that has been facilitated by ML and will be of great value for the future of personalized immunotherapies against cancer and other diseases.