Advances in Food, Bioproducts and Natural Byproducts for a Sustainable Future: From Conventional to Innovative Processes

The world population is expected to reach almost 10,000 million in 2050, which entails the need to focus on sustainability and its three pillars: the economy, the environment, and society. Within this context, it is necessary to use our resources efficiently; for instance, we will need to produce much more food using less land and while polluting less to optimize the production of biomass from diversified resources, along with its subsequent conversion, fractionation, and processing. To achieve this, new approaches and processes, with special emphasis from a biotechnological perspective, may need to be implemented to move towards a circular model that will confer environmental sustainability. Global projections of food losses constitute an abundant pool of complex carbohydrates, proteins, lipids, and functional compounds. Hence, the deployment of food waste streams as raw materials will encompass the formulation of added-value products that will be ideally reintroduced in the food supply chain to close the loop. Therefore, the analysis and optimization of any food and bioproduct process, as well as the development of innovative and emerging food and by-product processing methods, are important as a necessity for the sustainable transition to a bioeconomy era. The valorization, bioprocessing, and biorefining of food-industry-based streams, the role of industrial microorganisms, the isolation of high-added-value compounds, applications of the resulting bio-based chemicals in food manufacturing, novel food formulations, economic policies for food waste management, along with sustainability or techno-economic assessment of processing methods constitute subject areas that need to be addressed. More specifically, bioprocess design to valorize food-industry waste and by-product streams should be initiated by characterizing the composition of the onset raw material with the aim of identifying the target end-products, whereas the generation of multiple high-added-value products is a prerequisite for cost-effective processes to establish economic sustainability. On top of that, the feasibility of innovative processes could be sustained by encompassing food applications, driven by the constantly emerging consumers’ demand for functional foods and beverages with enhanced nutritional value. Equally, a growing awareness for bio-based and natural food components is being developed, thereby imposing challenges on the substitution of chemically derived ingredients with their natural counterparts

Editorial: Acetic acid bacteria

Acetic acid bacteria (ABB) are strictly aerobic organisms that can be found in a wide variety of natural and industrial environments. Their versatility and metabolic adaptability make them microorganisms of high interest to study the optimization of obtaining their multiple products and the essential mechanisms that allow them to grow under extreme conditions. Their metabolism, particularly the role of membrane-bound and soluble dehydrogenases, may offer new opportunities in the development of innovative processes based on their capability for carrying out the incomplete oxidation of several substrates. On the other hand, the resistance of AAB to some extreme conditions, i.e., low pH values, and adaptability to many different habitats make them highly competitive bacteria; so, their interaction with other organisms and plants is a very important topic to be studied. The ability of AAB in producing exopolysaccharides is also of great interest for both research and industrial purposes. They are considered as model organisms for understanding the mechanisms of cellulose synthesis and they are until now the most efficient organisms for producing it, under controlled conditions. Finally, the current state of omic technologies and efficient genetic modification methods can be applied for a greater understanding of the physiological behavior, the recovery of new strains and/or those occurring in complex environments as well as to exploit the full potential of AAB for oxidative bioconversions

Predicting Medical Student Success on Licensure Exams

Many schools seek to predict performance on national exams required for medical school graduation using prematriculation and medical school performance data. The need for targeted intervention strategies for at-risk students has led much of this interest. Assumptions that preadmission data and high stakes in-house medical exams correlate strongly with national standardized exam performance needs to be examined. Looking at prematriculation data for predicting USMLE Step 1 performance, we found that MCAT exam totals and math-science GPA had the best prediction from a set of prematriculation values (adjusted R 2 = 11.7 %) for step 1. The addition of scores from the first medical school exam improved our predictive capabilities with a linear model to 27.9 %. As we added data to the model, we increased our predictive values as expected. However, it was not until we added data from year 2 exams that we started to get step 1 prediction values that exceeded 50 %. Stepwise addition of more exams in year two resulted in much higher predictive values but also led to the exclusion of many early variables. Therefore, our best step 1 predictive value of around 76.7 % consisted of three variables from a total of 37. These data suggest that the preadmission information is a relatively poor predictor of licensure exam performance and that including class exam scores allows for much more accurate determination of students who ultimately proved to be at risk for performance on their licensure exams. The continuous use of this data, as it becomes available, for assisting at-risk students is discussed (251)

Histological and mutational profile of diffuse gastric cancer: current knowledge and future challenges

Gastric cancer (GC) pathogenesis is complex and heterogeneous, reflecting morphological, molecular and genetic diversity. Diffuse gastric cancer (DGC) and intestinal gastric cancer (IGC) are the major histological types. GC may be sporadic or hereditary; sporadic GC is related to environmental and genetic low-risk factors and hereditary GC is caused by inherited high-risk mutations, so far identified only for the diffuse histotype. DGC phenotypic heterogeneity challenges the current understanding of molecular mechanisms underlying carcinogenesis. The definition of a DGC-specific mutational profile remains controversial, possibly reflecting the heterogeneity of DGC-related histological subtypes [signet-ring cell carcinoma (SRCC) and poorly cohesive carcinoma not otherwise specified (PCC-NOS)]. Indeed, DGC and DGC-related subtypes may present specific mutational profiles underlying the particularly aggressive behaviour and dismal prognosis of DGC vs IGC and PCC-NOS vs SRCC. In this systematic review, we revised the histological presentations, molecular classifications and approved therapies for gastric cancer, with a focus on DGC. We then analysed results from the most relevant studies, reporting mutational analysis data specifying mutational frequencies, and their relationship with DGC and IGC histological types, and with specific DGC subtypes (SRCC and PCC-NOS). We aimed at identifying histology-associated mutational profiles with an emphasis in DGC and its subtypes (DGC vs IGC; sporadic vs hereditary DGC; and SRCC vs PCC-NOS). We further used these mutational profiles to identify the most commonly affected molecular pathways and biological functions, and explored the clinical trials directed specifically to patients with DGC. This systematic analysis is expected to expose a DGC-specific molecular profile and shed light into potential targets for therapeutic intervention, which are currently missing.The authors acknowledge the support of the National Infrastructure ‘GenomePT’ – National Laboratory for Genome Sequencing and Analysis (POCI-01-0145-FEDER-022184). J.G-P acknowledges the support of Faculty of Medicine from University of Porto, specifically by the Doctoral Programme in Biomedicine and the Solve-RD Project (H2020-SC1-2017-Single-Stage-RTD) for his PhD fellowship. R.B-M. acknowledges the support of Institute of Biomedical Sciences Abel Salazar from University of Porto, specifically by the Doctoral Programme BiotechHealth and the FCT – Fundação para a Ciência e a Tecnologia for her PhD fellowship (ref. SFRH/BD/145132/2019). This research and its authors were funded by FEDER – Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 – Operacional Programme for Competitiveness and Internationalization (POCI), Portugal 2020, and by Portuguese funds through FCT – Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Inovação in the framework of the project ‘Institute for Research and Innovation in Health Sciences’ (POCI-01-0145-FEDER-007274). This work was also financed by the projects NORTE-01-0145-FEDER-000003 (DOCnet) and NORTE-01-0145-FEDER-000029 (CANCER) – supported by Norte Portugal Regional Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) – project POCI-01-0145-FEDER-016390 (CancelStem) and PTDC/BTM-TEC/30164/2017 (3DChroMe), funded by ERDF, POCI and FCT

A Microbial Co-Culturing System for Producing Cellulose-Hyaluronic Acid Composites

In this study, a co-culture system combining bacterial cellulose (BC) producers and hyaluronic acid (HA) producers was developed for four different combinations. AAB of the genus Komagataeibacter sp. and LAB of the Lactocaseibacillus genus were used to produce BC and HA, respectively. Fourier-transform infrared spectroscopy, scanning electron microscopy, and X-ray diffraction were used to investigate changes in BC-HA composites chemical and morphological structure. Water absorption, uptake, and antibacterial properties were also tested. Outcomes highlighted a higher bacterial cellulose yield and the incorporation of hyaluronic acid into the composite. The presence of hyaluronic acid increased fiber dimension-nearly doubled for some combinations-which led to a decreased crystallinity of the composites. Different results were observed based on the BC producer and HA producer combination. However, water holding capacity (WHC) in all the samples improved with the presence of HA, while water uptake worsened. A thymol-enriched BC-HA composite showed high antibacterial activity against Escherichia coli DSM 30083(T) and Staphylococcus aureus DSM 20231(T). Results could contribute to opening new applications in the cosmetics or pharmaceutical fields

Proteomics analysis of gastric cancer patients with diabetes mellitus

Proteomics is a powerful approach to study the molecular mechanisms of cancer. In this study, we aim to characterize the proteomic profile of gastric cancer (GC) in patients with diabetes mellitus (DM) type 2. Forty GC tissue samples including 19 cases from diabetic patients and 21 cases from individuals without diabetes (control group) were selected for the proteomics analysis. Gastric tissues were processed following the single-pot, solid-phase-enhanced sample preparation approach—SP3 and enzymatic digestion with trypsin. The resulting peptides were analyzed by LC-MS Liquid Chromatography—Mass Spectrometry (LC-MS). The comparison of protein expression levels between GC samples from diabetic and non-diabetic patients was performed by label-free quantification (LFQ). A total of 6599 protein groups were identified in the 40 samples. Thirty-seven proteins were differentially expressed among the two groups, with 16 upregulated and 21 downregulated in the diabetic cohort. Statistical overrepresentation tests were considered for different annotation sets including the Gene Ontology(GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Disease functional databases. Upregulated proteins in the GC samples from diabetic patients were particularly enriched in respiratory electron transport and alcohol metabolic biological processes, while downregulated proteins were associated with epithelial cancers, intestinal diseases, and cell–cell junction cellular components. Taken together, these results support the data already obtained by previous studies that associate diabetes with metabolic disorders and diabetes-associated diseases, such as Alzheimer’s and Parkinson’s, and also provide valuable insights into seven GC-associated protein targets, claudin-3, polymeric immunoglobulin receptor protein, cadherin-17, villin-1, transglutaminase-2, desmoglein-2, and mucin-13, which warrant further investigation.This article is a result of the project DOCnet (NORTE-01-0145-FEDER-000003), supported by the Norte Portugal Regional Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and also by FEDER—Fundo Europeu de Desenvolvimento Regional—funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, as well as by Portuguese funds through FCT—Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Inovação—in the framework of the project “Institute for Research and Innovation in Health Sciences” (POCI-01-0145-FEDER-007274). This work was also financed by the Portuguese Mass Spectrometry Network, integrated in the National Roadmap of Research Infrastructures of Strategic Relevance (ROTEIRO/0028/2013; LISBOA-01-0145-FEDER-022125)