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Synthetic organic compounds (SOCs) are reported as xenobiotics compounds contaminating the environment from various sources including waste from the pulp and paper industries: Since the demand and production of paper is growing increasingly, the release of paper and pulp industrial waste consisting of SOCs is also increasing the SOCs’ pollution in natural reservoirs to create environmental pollution. In pulp and paper industries, the SOCs viz. phenol compounds, furans, dioxins, benzene compounds etc. are produced during bleaching phase of pulp treatment and they are principal components of industrial discharge. This review gives an overview of various biotechnological interventions for paper mill waste effluent management and elimination strategies. Further, the review also gives the insight overview of various ways to restrict SOCs release in natural reservoirs, its limitations and integrated approaches for SOCs bioremediation using engineered microbial approaches. Furthermore, it gives a brief overview of the sustainable remediation of SOCs via genetically modified biological agents, including bioengineering system innovation at industry level before waste discharge.

Reject fines, a waste stream of short lignocellulosic fibers produced from paper linerboard recycling, are a cellulose-rich paper mill byproduct that can be hydrolyzed enzymatically into fermentable sugars. In this study, the use of hydrolyzed reject fines as a carbon source for bacterial biosynthesis of poly(R-3-hydroxyalkanoate) (PHA) and poly(γ-glutamic acid) (PGA) was investigated. Recombinant Escherichia coli harboring PHA biosynthesis genes were cultivated with purified sugars or crude hydrolysate to produce both poly(R-3-hydroxybutyrate) (PHB) homopolymer and medium chain length-containing copolymer (PHB-co-MCL). Wild-type Bacillus licheniformis WX-02 were cultivated with crude hydrolysate to produce PGA. Both PHB and short chain-length-co-medium chain-length (SCL-co-MCL) PHA yields from crude hydrolysate were a 2-fold improvement over purified sugars, and the MCL monomer fraction was decreased slightly in copolymers produced from crude hydrolysate. PGA yield from crude hydrolysate was similarly increased 2-fold. The results suggest that sugars from hydrolyzed reject fines are a viable carbon source for PHA and PGA biosynthesis. The use of crude hydrolysate is not only possible but beneficial for biopolymer production, eliminating the need for costly separation and purification techniques. This study demonstrates the potential to divert a lignocellulosic waste stream into valuable biomaterials, mitigating the environmental impacts of solid waste disposal.

Chemical and biological sensing are crucial tools in science and technology. Plasmonic nanoparticles offer a virtually limitless number of photons for sensing applications, which can be available for visual detection over long periods. Moreover, cellulosic materials, such as paper, represent a versatile building block for implementation of simple, yet valuable, microfluidic analytical devices. This mini review outlines the basic theory of nanoplasmonics and the usability of paper as a nanoplasmonic substrate exploiting its features as a (bio)sensing platform based on different mechanisms depending on localized surface plasmon resonance response. Progress, current trends, challenges and opportunities are also underscored. It is intended for general researchers and technologists who are new to the topic as well as specialist/experts in the field.

In several highly eusocial insect species with morphologically distinct castes, queen-characteristic cuticular hydrocarbons (CHCs) have been shown to act as queen signals that suppress the reproduction of nestmate workers. However, it is not known whether such queen pheromones might also play a role in regulating reproductive division of labour in primitively eusocial insects that lack morphologically defined castes. Here, we experimentally tested whether a blend of CHCs which occurred in higher concentrations in the dominant breeding female act as a queen pheromone, and inhibit reproduction by subordinate females in the primitively eusocial paper wasp Polistes satan. In contrast to earlier findings with highly eusocial species, our results show that although specific compounds were enhanced in dominant, reproductively active females, a blend of five of these compounds did not inhibit development of the ovaries of female nestmates. Instead, the dominant female had to be physically present to prevent subordinate females from reproducing. Our results are in line with earlier evidence suggesting that fertility-linked compounds in primitively eusocial wasps act only as cues and help to regulate reproduction when used in conjunction with aggressive dominance behaviour, meaning the physical presence of the dominant female. Alternatively, our results support the hypothesis that queen pheromones in highly eusocial insects were co-opted from fertility cues that were already present in primitively eusocial ancestors, even when initially, such compounds were merely produced as by-products of ovarian activation, without actually serving to signal reproductive status.

Electrogenicity, or bacterial electron transfer capacity, is an important application which offers environmentally sustainable advances in the fields of biofuels, wastewater treatment, bioremediation, desalination, and biosensing. Significant boosts in this technology can be achieved with the growth of synthetic biology that manipulates microbial electron transfer pathways, thereby potentially significantly improving their electrogenic potential. There is currently a need for a high-throughput, rapid, and highly sensitive test array to evaluate the electrogenic properties of newly discovered and/or genetically engineered bacterial species. In this work, we report a single-sheet, paper-based electrofluidic (incorporating both electronic and fluidic structure) screening platform for rapid, sensitive, and potentially high-throughput characterization of bacterial electrogenicity. This novel screening array uses (i) a commercially available wax printer for hydrophobic wax patterning on a single sheet of paper and (ii) water-dispersed electrically conducting polymer mixture, poly(3,4-ethylenedioxythiophene):polystyrene sulfonate, for full integration of electronic and fluidic components into the paper substrate. The engineered 3-D, microporous, hydrophilic, and conductive paper structure provides a large surface area for efficient electron transfer. This results in rapid and sensitive power assessment of electrogenic bacteria from a microliter sample volume. We validated the effectiveness of the sensor array using hypothesis-driven genetically modified Pseudomonas aeruginosa mutant strains. Within 20 min, we observed that the sensor platform successfully measured the electricity-generating capacities of five isogenic mutants of P. aeruginosa while distinguishing their differences from genetically unmodified bacteria.

The Indian subcontinent with its population density, climatic conditions, means of subsistence, socioeconomic factors as well as travel and tourism presents a fertile ground for thriving of RNA viruses. Despite being pathogens of huge significance, there is very little focus on research into the biology and pathogenesis of RNA viruses in India. Studies on epidemiology and disease burden, risk factors, the immune response to RNA viruses, circulating virus strains and virus evolution, animal models of disease, antivirals and vaccines are strikingly absent. Emerging RNA viruses such as Zika virus, Nipah virus and Crimean-Congo haemorrhagic fever virus are a matter of grave concern to India. Here we summarize the outcome of the India|EMBO symposium on "RNA viruses: immunology, pathogenesis and translational opportunities" organized at Faridabad, National Capital Region, India, on March 28-30, 2018. The meeting focused on RNA viruses (non-HIV), and both national and international experts on RNA viruses covered topics ranging from epidemiology, immune response, virus evolution and vaccine trials concerning RNA viruses. The aim of the symposium was to create a road map for RNA virus research in India. Both concrete and tentative ideas pointing towards short-term and long-term goals were presented with recommendations for follow-up at government level.

Wood is a renewable resource that is mainly composed of lignin and cell wall polysaccharides. The polysaccharide fraction is valuable as it can be converted into pulp and paper, or into fermentable sugars. On the other hand, the lignin fraction is increasingly being considered a valuable source of aromatic building blocks for the chemical industry. The presence of lignin in wood is one of the major recalcitrance factors in woody biomass processing, necessitating the need for harsh chemical treatments to degrade and extract it prior to the valorization of the cell wall polysaccharides, cellulose and hemicellulose. Over the past years, large research efforts have been devoted to engineering lignin amount and composition to reduce biomass recalcitrance toward chemical processing. We review the efforts made in forest trees, and compare results from greenhouse and field trials. Furthermore, we address the value and potential of CRISPR-based gene editing in lignin engineering and its integration in tree breeding programs.

Diatoms are photoautotrophic unicellular algae and are among the most abundant, adaptable, and diverse marine phytoplankton. They are extremely interesting not only for their ecological role but also as potential feedstocks for sustainable biofuels and high-value commodities such as omega fatty acids, because of their capacity to accumulate lipids. However, the cultivation of microalgae on an industrial scale requires higher cell densities and lipid accumulation than those found in nature to make the process economically viable. One of the known ways to induce lipid accumulation in Phaeodactylum tricornutum is nitrogen deprivation, which comes at the expense of growth inhibition and lower cell density. Thus, alternative ways need to be explored to enhance the lipid production as well as biomass density to make them sustainable at industrial scale. In this study, we have used experimental and metabolic modeling approaches to optimize the media composition, in terms of elemental composition, organic and inorganic carbon sources, and light intensity, that boost both biomass quality and quantity of P. tricornutum. Eventually, the optimized conditions were scaled-up to 2 L photobioreactors, where a better system control (temperature, pH, light, aeration/mixing) allowed a further improvement of the biomass capacity of P. tricornutum to 12 g/L.

Lignocellulosic biomass, encompassing cellulose, lignin and hemicellulose in plant secondary cell walls (SCWs), is the most abundant source of renewable materials on earth. Currently, fast-growing woody dicots such as Eucalyptus and Populus trees are major lignocellulosic (wood fiber) feedstocks for bioproducts such as pulp, paper, cellulose, textiles, bioplastics and other biomaterials. Processing wood for these products entails separating the biomass into its three main components as efficiently as possible without compromising yield. Glucuronoxylan (xylan), the main hemicellulose present in the SCWs of hardwood trees carries chemical modifications that are associated with SCW composition and ultrastructure, and affect the recalcitrance of woody biomass to industrial processing. In this review we highlight the importance of xylan properties for industrial wood fiber processing and how gaining a greater understanding of xylan biosynthesis, specifically xylan modification, could yield novel biotechnology approaches to reduce recalcitrance or introduce novel processing traits. Altering xylan modification patterns has recently become a focus of plant SCW studies due to early findings that altered modification patterns can yield beneficial biomass processing traits. Additionally, it has been noted that plants with altered xylan composition display metabolic differences linked to changes in precursor usage. We explore the possibility of using systems biology and systems genetics approaches to gain insight into the coordination of SCW formation with other interdependent biological processes. Acetyl-CoA, s-adenosylmethionine and nucleotide sugars are precursors needed for xylan modification, however, the pathways which produce metabolic pools during different stages of fiber cell wall formation still have to be identified and their co-regulation during SCW formation elucidated. The crucial dependence on precursor metabolism provides an opportunity to alter xylan modification patterns through metabolic engineering of one or more of these interdependent pathways. The complexity of xylan biosynthesis and modification is currently a stumbling point, but it may provide new avenues for woody biomass engineering that are not possible for other biopolymers.

Drill cuttings from petroleum exploration and production sites can cause diverse environmental problems. Total petroleum hydrocarbons (TPHs) are a major pollutant from the use of polyolefin-based mud. As an alternative to incineration, this study investigated the application of surfactant-enhanced washing technology prior to bioremediation. The washing step was necessary because the initial TPH concentrations were quite high at approximately 15% w/w. Washing agents were formulated by varying the concentration of lipopeptide biosurfactant (in foamate or cell-free broth), Dehydol LS7TH (fatty alcohol ethoxylate 7EO, oleochemical surfactant) and butanol (as a lipophilic linker) at different salinities. The most efficient formula produced a Winsor Type I microemulsion (oil-in-water microemulsion) with polyolefin and contained only 20% (v/v) foamate and 2% (v/v) Dehydol LS7TH in water. Due to the synergistic behavior between the anionic lipopeptides and nonionic Dehydol LS7TH, the formula efficiently removed 92% of the TPHs from the drill cuttings when applied in a jar test. To reduce the cost, the concentrations of each surfactant should be reduced; thus, the formula was optimized by the simplex lattice mixture design. In addition, cell-free broth, at a pH of 10, containing 3.0 g/L lipopeptides was applied instead of foamate because it was easy to prepare. The optimized formula removed 81.2% of the TPHs and contained 72.0% cell-free broth and 1.4% Dehydol LS7TH in water. A 20-kg soil washing system was later tested where the petroleum removal efficiency decreased to 70.7% due to polyolefin redeposition during separation of the washing solution. The remaining TPHs (4.5%) in the washed drilled cuttings were further degraded by a mixture of Marinobacter salsuginis RK5, Microbacterium saccharophilum RK15 and Gordonia amicalis JC11. To promote TPH biodegradation, biochar and fertilizer were applied along with bacterial consortia in a microcosm experiment. After 49-day incubation, the TPHs were reduced to 0.9% by both physical and biological mechanisms, while the TPHs in the unamended samples remained unaffected. The treated drill cuttings contained less than 1% TPHs. With the use of the formulated bio-based washing agent and bioremediation approach, the on-site treatment of drill cuttings could be conducted with an acceptable cost and low environmental impacts.

Variable moisture content of biomass during storage is known to compromise feedstock stability, yet a great deal of uncertainty remains on how to manage or mitigate the issue. While moisture contents above 20% risk unacceptable losses in aerobic feed and forage storage, no quantitative relationship exists between corn stover moisture content and rates or extents of degradation for bioenergy use. This work quantifies the relationship between initial moisture content of aerobically stored corn (Zea mays L.) stover biomass and dry matter loss through time. Corn stover with 20% to 52% moisture was stored under aerobic conditions in laboratory reactors while dry matter loss was measured in real time, reaching extents of 8% to 28% by the end of storage. Rates and extents of degradation were proportional to moisture content but were not linearly related. A moisture content “threshold” exists between 36% and 52% above which rates and extents of degradation increase rapidly. Compositional changes included glucan and lignin enrichment resulting from hemicellulose component (xylan and acetyl) biodegradation. Moisture desorption characteristics of the post-storage materials suggest chemical and/or physical changes that increase biomass hydrophilicity. Monomerization of carbohydrates though dilute acid pretreatment and enzymatic hydrolysis resulted in only minor changes, suggesting that degradation does not negatively influence conversion potential of the remaining biomass. Total dry matter preservation remains one of the most significant challenges for a biorefinery.

With the constant accumulation of electronic waste, extracting precious metals contained therein is becoming a major challenge for sustainable development. Bacillus megaterium is currently one of the microbes used for the production of cyanide, which is the main leaching agent for gold recovery. The present study aimed to propose a strategy for metabolic engineering of B. megaterium to overproduce cyanide, and thus ameliorate the bioleaching process. For this, we employed constraint-based modeling, running in silico simulations on iJA1121, the genome-scale metabolic model of B. megaterium DSM319. Flux balance analysis (FBA) was initially used to identify amino acids to be added to the culture medium. Considering cyanide as the desired product, we used growth-coupled methods, constrained minimal cut sets (cMCSs) and OptKnock to identify gene inactivation targets. To identify gene overexpression targets, flux scanning based on enforced objective flux (FSEOF) was performed. Further analysis was carried out on the identified targets to determine compounds with beneficial regulatory effects. We have proposed a chemical-defined medium for accelerating cyanide production on the basis of microplate assays to evaluate the components with the greatest improving effects. Accordingly, the cultivation of B. megaterium DSM319 in a chemically-defined medium with 5.56 mM glucose as the carbon source, and supplemented with 413 μM cysteine, led to the production of considerably increased amounts of cyanide. Bioleaching experiments were successfully performed in this medium to recover gold and copper from telecommunication printed circuit boards. The results of inductively coupled plasma (ICP) analysis confirmed that gold recovery peaked out at around 55% after 4 days, whereas copper recovery continued to increase for several more days, peaking out at around 85%. To further validate the bioleaching results, FESEM, XRD, FTIR, and EDAX mapping analyses were performed. We concluded that the proposed strategy represents a viable route for improving the performance of the bioleaching processes.

Lignocellulosic biomasses are primarily composed of cellulose, hemicelluloses and lignin and these biopolymers are bonded together in a heterogeneous matrix that is highly recalcitrant to chemical or biological conversion processes. Thus, an efficient pretreatment technique must be selected and applied to this type of biomass in order to facilitate its utilization in biorefineries. Classical pretreatment methods tend to operate under severe conditions, leading to sugar losses by dehydration and to the release of inhibitory compounds such as furfural (2-furaldehyde), 5-hydroxy-2-methylfurfural (5-HMF), and organic acids. By contrast, supercritical fluids can pretreat lignocellulosic materials under relatively mild pretreatment conditions, resulting in high sugar yields, low production of fermentation inhibitors and high susceptibilities to enzymatic hydrolysis while reducing the consumption of chemicals, including solvents, reagents, and catalysts. This work presents a review of biomass pretreatment technologies, aiming to deliver a state-of-art compilation of methods and results with emphasis on supercritical processes.

Rising CO2 levels, associated climatic instability, freshwater scarcity and diminishing arable land exacerbate the challenge to maintain food security for the fast growing human population. Although coal-fired power plants generate large amounts of CO2 emissions and wastewater, containing environmentally unsafe concentrations of metals, they ensure energy security. Nitrogen (N2)-fixation by cyanobacteria eliminate nitrogen fertilization costs, making them promising candidates for remediation of waste CO2 and metals from macronutrient-poor ash dam water and the biomass is suitable for phycocyanin and biofertilizer product development. Here, the effects of CO2 and metal mixtures on growth, bioproduct and metal removal potential were investigated for the self-flocculating, N2-fixing freshwater cyanobacterium Tolypothrix sp. Tolypothrix sp. was grown outdoors in simulated ash dam wastewater (SADW) in 500 L vertical bag suspension cultures and as biofilms in modified algal-turf scrubbers. The cultivation systems were aerated with air containing either 15% CO2 (v/v) or not. CO2-fertilization resulted in ∼1.25- and 1.45-fold higher biomass productivities and ∼40 and 27% increased phycocyanin and phycoerythrin contents for biofilm and suspension cultures, respectively. CO2 had no effect on removal of Al, As, Cu, Fe, Sr, and Zn, while Mo removal increased by 37% in both systems. In contrast, Ni removal was reduced in biofilm systems, while Se removal increased by 73% in suspension cultures. Based on biomass yields and biochemical data obtained, net present value (NPV) and sensitivities analyses used four bioproduct scenarios: (1) phycocyanin sole product, (2) biofertilizer sole product, (3) 50% phycocyanin and 50% biofertilizer, and (4) 100% phycocyanin and 100% biofertilizer (residual biomass) for power station co-located and not co-located 10 ha facilities over a 20-year period. Economic feasibility for the production of food-grade phycocyanin either as a sole product or with co-production of biofertilizer was demonstrated for CO2-enriched vertical and raceway suspension cultures raised without nitrogen-fertilization and co-location with power stations significantly increased profit margins, KH acknowledges grant funding by the AdvancedManufacturing Co-operative Research Centre (AMCRC), Melbourne, Australia, grant number 2.3.4

In order to select excellent strains with high CO2 fixation capability on a large scale, nine Spirulina species were cultivated in columnar photobioreactors with the addition of 10% CO2. The two species selected (208 and 220) were optimized for pH value, total dissolved inorganic carbon (DIC), and phosphorus content with intermittent CO2 addition in 4 m2 indoor raceway ponds. On the basis of biomass accumulation and CO2 fixation rate in the present study, the optimum pH, DIC, and phosphate concentration were 9.5, 0.1 mol L-1, and 200 mg L-1 for both strains, respectively. Lastly, the two strains selected were semi-continuously cultivated successfully for CO2 mitigation in 605 m2 raceway ponds aerated with food-grade CO2 purified from a coal chemical flue gas on a large scale. The daily average biomass dry weight of the two stains reached up to 18.7 and 13.2 g m-2 d-1, respectively, suggesting the two Spirulina strains can be utilized for mass production.

Wet storage is synonymous with ensilage, a simple biotechnology that has been used to preserve forage for livestock feed for millennia. In this natural process, organic acids are produced by anaerobic microbial degradation of a small fraction of the biomass, and these acids reduce the pH to levels that minimize further microbial activity and can preserve the biomass for years as long as anaerobic conditions are maintained. These organic acids also result in mild pretreatment with potential to enhance downstream conversion processes, making this an effective storage strategy. However, the degree and significance of this natural pretreatment capability of ensiled storage on downstream processes has not previously been quantified across a range of storage conditions. In this study, the degree of pretreatment was investigated by measuring the reactivity of corn stover fiber to cellulolytic enzymes. Although the results indicated significant improvement in hydrolytic outcomes after wet storage, by a factor of up to 2.4, saccharification of cellulose to sugar monomers was still limited. The results also show that dominance of lactic acid in the ensilage process is key to wet storage [pretreatment] effectiveness as in the livestock feed industry. Lactic acid pKa value is lower than the pKa of other silage acids and lower than typical silage pH. This gives lactic acid the advantage of being in the more dissociated form, with more protons available to facilitate pretreatment hydrolysis. However, unlike the livestock feed industry, where quality feedstock is attainable within very narrow storage moisture range, for biofuel purposes, a wider range of 35 ―65% is appropriate in achieving a similar quality outcome. This is true both for the immediate fiber response to enzymes and with subsequent pretreatment. This wider moisture range implies more flexibility in harvest schedule without sacrificing feedstock quality, thus alleviating concerns over feedstock quality that biomass suppliers or biorefineries may have.

The potent greenhouse gas methane presents a widely accessible resource, being the primary component in natural gas as well as in bio-gas from anaerobic digesters. Given its relatively low heating-value and several issues concerning its storage and transportation, methane upgrading to liquid fuels is of particular interest. Microbial methane conversion/utilization and upgrading is gaining increasing interest due to its high conversion efficiency. In this study we computationally compare aerobic and anaerobic microbial pathways for CH4 oxidation and discuss theoretically achievable biomass yields as well as the possibility for building synthetic biological production platforms for liquid fuels. Specifically, the presented in-silico work investigates the potential of microbial methane upgrading in a metabolic network analysis by means of elementary flux modes. Aerobic fixation of methane via conversion of methane to methanol by a methane monooxygenase (MMO) and different subsequent formaldehyde assimilation pathways (Serine-cycle, RuMP, XMP/DHA-pathway) is compared with anaerobic pathways for oxidation of methane (AOM) by means of reverse-methanogenesis or via a presumed glycyl-radical enzyme, which uses fumarate for activation of methane. The different pathways for aerobic and anaerobic methane oxidation are compared in different central carbon-metabolism envelopes in order to identify highest achievable carbon yields. The capability of efficient CO2 fixation, as well as energy preservation in form of reducing equivalents is identified as crucial to enable high yields, which ranged from 22% to 100%. The potential of the different microbes to grow on these gas streams is assessed by means of the maximum achievable biomass yield and the CO2/CH4 uptake ratio. CO2 co-utilisation, by transferring reducing power between the two co-substrates, is highest, when combining reverse-methanogenesis with the Wood-Ljungdahl pathway, effectively replacing the need for H2 with CH4. Further, the possibility to upgrade methane into liquid (drop-in) bio-fuels is investigated. Established routes to methanol, ethanol, C4-alcoholes and farnesene are evaluated in the most promising substrate-pathway / organism combinations. Stoichiometric, thermodynamic and kinetic limitations are assessed and recommendations regarding potential industrial feasibility are given. The results presented here should guide future research efforts in search for feasible ways of (co)utilizing novel carbon substrates for sustainable production of fuels and chemicals.

Conventional biological nitrogen removal (BNR), comprised of nitrification and denitrification, is traditionally employed in wastewater treatment plants (WWTPs) to prevent eutrophication in receiving water bodies. More recently, the combination of selective ammonia to nitrite oxidation (nitritation) and autotrophic anaerobic ammonia oxidation (anammox), collectively termed deammonification, has also emerged as a possible energy- and cost-effective BNR alternative. Herein, we analyzed microbial diversity and functional potential within 13 BNR processes in the United States, Denmark, and Singapore operated with varying reactor configuration, design, and operational parameters. Using next-generation sequencing and metagenomics, gene-coding regions were aligned against a custom protein database expanded to include all published aerobic ammonia oxidizing bacteria (AOB), nitrite oxidizing bacteria (NOB), anaerobic ammonia oxidizing bacteria (AMX), and complete ammonia oxidizing bacteria (CMX). Overall contributions of these N-cycle bacteria to the total functional potential of each reactor was determined, as well as that of several organisms associated with denitrification and/or structural integrity of microbial aggregates (biofilm or granules). The potential for these engineered processes to foster a broad spectrum of microbial catabolic, anabolic, and carbon assimilation transformations was elucidated. Seeded sidestream DEMON® deammonification systems and single-stage nitritation-anammox moving bed biofilm reactors (MBBRs) and a mainstream Cleargreen reactor designed to enrich in AOB and AMX showed lower enrichment in AMX functionality than an enriched two-stage nitritation-anammox MBBR system treating mainstream wastewater. Conventional BNR systems in Singapore and the United States had distinct metagenomes, especially relating to AOB. A hydrocyclone process designed to recycle biomass granules for mainstream BNR contained almost identical structural and functional characteristics in the overflow, underflow, and inflow of mixed liquor (ALT) rather than the expected selective enrichment of specific nitrifying or AMX organisms. Inoculum used to seed a sidestream deammonification process unexpectedly contained

Gynura procumbens (Lour.) Merr. (Family Asteraceae) is a medicinal plant commonly found in tropical Asia countries such as China, Thailand, Indonesia, Malaysia, and Vietnam. Traditionally, it is widely used in many different countries for the treatment of a wide variety of health ailments such as kidney discomfort, rheumatism, diabetes mellitus, constipation, and hypertension. Based on the traditional uses of G. procumbens, it seems to possess high therapeutic potential for treatment of various diseases making it a target for pharmacological studies aiming to validate and provide scientific evidence for the traditional claims of its efficacy. Although there has been considerable progress in the research on G. procumbens, to date there is no review paper gathering the reported biological activities of G. procumbens. Hence, this review aims to provide an overview of the biological activities of G. procumbens based on reported in vitro and in vivo studies. In brief, G. procumbens has been reported to exhibit antihypertensive, cardioprotective, antihyperglycemic, fertility enhancement, anticancer, antimicrobial, antioxidant, organ protective, and antiinflammatory activity. The commercial applications of G. procumbens have also been summarized in this paper based on existing patents. The data compiled illustrate that G. procumbens is a potential natural source of compounds with various pharmacological actions which can be utilized for the development of novel therapeutic agents.

Background: Oral microbiota are considered major players in the development of periodontal diseases. Thorough knowledge of intact subgingival microbiomes is required to elucidate microbial shifts from health to disease. Aims: This comparative study investigated the subgingival microbiome of healthy children, possible inter- and intra-individual effects of modified sampling, and basic comparability of subgingival microprints. Methods: In five 10-year-old children, biofilm was collected from the upper first premolars and first molars using sterilized, UV-treated paper-points inserted into the subgingival sulcus at eight sites. After supragingival cleaning using an electric toothbrush and water, sampling was performed, firstly, excluding (Mode A) and, secondly, including (Mode B) cleansing with sterile cotton pellets. DNA was extracted from the pooled samples, and primers targeting 16S rRNA hypervariable regions V5 and V6 were used for 454-pyrosequencing. Wilcoxon signed rank test and t-test were applied to compare sampling modes. Principal coordinate analysis (PCoA) and average agglomerative hierarchical clustering were calculated with unweighted UniFrac distance matrices. Sample grouping was tested with permutational MANOVA (Adonis). Results: Data filtering and quality control yielded 67,218 sequences with an average sequence length of 243bp (SD 6.52; range 231–255). Actinobacteria (2.8–24.6%), Bacteroidetes (9.2–25.1%), Proteobacteria (4.9–50.6%), Firmicutes (16.5–57.4%), and Fusobacteria (2.2–17.1%) were the five major phyla found in all samples. Differences in microbial abundances between sampling modes were not evident. High sampling numbers are needed to achieve significance for rare bacterial phyla. Samples taken from one individual using different sampling modes were more similar to each other than to other individuals' samples. PCoA and hierarchical clustering showed a grouping of the paired samples. Permutational MANOVA did not reveal sample grouping by sampling modes (p = 0.914 by R2 = 0.09). Conclusion: A slight modification of sampling mode has minor effects corresponding to a natural variability in the microbiome profiles of healthy children. The inter-individual variability in subgingival microprints is greater than intra-individual differences. Statistical analyses of microbial populations should consider this baseline variability and move beyond mere quantification with input from visual analytics. Comparative results are difficult to summarize as methods for studying huge datasets are still evolving. Advanced approaches are needed for sample size calculations in clinical settings.

International audience; Despite scientific advances, bacterial spores remain a major preoccupation in many different fields, such as the hospital, food, and CBRN-E Defense sector. Although many disinfectant technologies exist, there is a lack for the decontamination of difficult to access areas, outdoor sites, or large interior volumes. This study evaluates the decontamination efficiency of an aqueous foam containing hydrogen peroxide, with the efficiency of disinfectant in the liquid form on vertical surfaces contaminated by Bacillus thurengiensis spores. The decontamination efficiency impact of the surfactant and stabilizer agents in the foam and liquid forms was evaluated. No interferences were observed with these two chemical additives. Our results indicate that the decontamination kinetics of both foam and liquid forms are similar. In addition, while the foam form was as efficient as the liquid solution at 4 degrees C, it was even more so at 30 degrees C. The foam decontamination reaction follows the Arrhenius law, which enables the decontamination kinetic to be predicted with the temperature. Moreover, the foam process used via spraying or filling is more attractive due to the generation of lower quantity of liquid effluents. Our findings highlight the greater suitability of foam to decontaminate difficult to access and high volume facilities compared to liquid solutions.

Activated sludge microbial community composition is a key bio-indicator of the sustainability of wastewater treatment systems. Therefore, a thorough understanding of the activated sludge microbial community dynamics is critical for environmental engineers to effectively manage the wastewater treatment plants (WWTPs). However, fungal communities associated with activated sludge have been poorly elucidated. Here, the activated sludge fungal community in eighteen geographically distributed WWTPs was determined by using Illumina sequencing. The results shown that differences in fungal community structure were observed in samples among all WWTPs and also between oxidation ditch and anaerobic-anoxic-aerobic (A/A/O) systems. While Ascomycota was the largest phyla, followed by Basidiomycota in all samples. Meanwhile, Sporidiobolales and Pezizales were the most abundant order in oxidation ditch and A/A/O systems, respectively. The network analysis indicated cooperative and co-occurrence interactions between fungal taxa in order to accomplish the wastewater treatment process. Hygrocybe sp., Sporobolomyces sp., Rhodotorula sp., Stemphylium sp., Parascedosporium sp., and Cylindrocarpon sp., were found to have statistically significant interactions. Redundancy analysis revealed that total phosphorus, pH, and ammonia nitrogen were significantly affected on the fungal community. This study sheds light on providing the ecological characteristics of activated sludge fungal communities and useful guidance for improving wastewater treatment performance efficiency.

As one of the major biofuels to replace fossil fuel, biodiesel has now attracted more and more attention due to its advantages in higher energy density and overall less greenhouse gas generation. Biodiesel (fatty acid alkyl esters) is produced by chemically or enzymatically catalyzed transesterification of lipids from microbial cells, microalgae, oil crops, or animal fats. Currently, plant oils or waste cooking oils/fats remain the major source for biodiesel production via enzymatic route, but the production capacity is limited either by the uncertain supplement of plant oils or by the low or inconsistent quality of waste oils/fats. In the past decades, significant progresses have been made on synthesis of microalgae oils directly from CO2via a photosynthesis process, but the production cost from any current technologies is still too high to be commercialized due to microalgae's slow growth rate on CO2, inefficiency in photo-bioreactors, lack of efficient contamination control methods, and high cost in downstream recovery. At the same time, many oleaginous microorganisms have been studied to produce lipids via the fatty acid synthesis pathway under aerobic fermentation conditions, among them one of the most studied is the non-conventional yeast, Yarrowia lipolytica, which is able to produce fatty acids at very high titer, rate, and yield from various economical substrates. This review summarizes the recent research progresses in both cellular and bioprocess engineering in Y. lipolytica to produce lipids at a low cost that may lead to commercial-scale biodiesel production. Specific technologies include the strain engineering for using various substrates, metabolic engineering in high-yield lipid synthesis, cell morphology study for efficient substrate uptake and product formation, free fatty acid formation and secretion for improved downstream recovery, and fermentation engineering for higher productivities and less operating cost. To further improve the economics of the microbial oil-based biodiesel, production of lipid-related or -derived high-value products are also discussed.

The scale of data being produced in neuroscience at present and in the future creates new and unheralded challenges, outstripping conventional ways of handling, considering, and analyzing data. As neuroinformatics enters into this big data era, a need for a highly trained and perhaps unique workforce is emerging.To determine the staffing needs created by the impending era of big data, a workshop (iNeuro Project) was convened November 13-14, 2014. Participants included data resource providers, bioinformatics/analytics trainers, computer scientists, library scientists, and neuroscience educators. These individuals provided perspectives on the challenges of big data, the preparation of a workforce to meet these challenges, and the present state of training programs. Participants discussed whether suitable training programs will need to be constructed from scratch or if existing programs can serve as models. Currently, most programs at the undergraduate and graduate levels are located in Europe—participants knew of none in the United States. The skill sets that training programs would need to provide as well as the curriculum necessary to teach them were also discussed. Consistent with Vision and Change in Undergraduate Biology Education: A Call to Action, proposed curricula included authentic, hands-on research experiences. Further discussions revolved around the logistics and barriers to creating such programs. The full white paper, iNeuro Project Workshop Report, is available from iNeuro Project.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms., Legionella is an opportunistic waterborne pathogen of increasing public health significance. Pasteurization, otherwise known as super-heat and flush (increasing water temperature to above 70°C and flushing all outlets), has been identified as an important mechanism for the disinfection of Legionella in manufactured water systems. However, several studies have reported that this procedure was ineffective at remediating water distribution systems as Legionella was able to maintain long term persistent contamination. Up to 25% of L. pneumophila cells survived heat treatment of 70°C, but all of these were in a viable but non-culturable state. This demonstrates the limitations of the culture method of Legionella detection currently used to evaluate disinfection protocols. In addition, it has been demonstrated that pasteurization and nutrient starvation can select for thermal tolerant strains, where L. pneumophila was consistently identified as having greater thermal tolerance compared to other Legionella species. This review demonstrates that further research is needed to investigate the effectiveness of pasteurization as a disinfection method. In particular, it focuses on the potential for pasteurization to select for thermal tolerant L. pneumophila strains which, as the primary causative agent of Legionnaires disease, have greater public health significance compared to other Legionella species.

The aim of the present study was to investigate the potential application of the biosurfactant from Candida lipolytica grown in low-cost substrates, which has previously been produced and characterized under optimized conditions as an adjunct material to enhance the remediation processes of hydrophobic pollutants and heavy metals generated by the oil industry and propose the formulation of a safe and stable remediation agent. In tests carried out with seawater, the crude biosurfactant demonstrated 80% oil spreading efficiency. The dispersion rate was 50% for the biosurfactant at a concentration twice that of the CMC. The biosurfactant removed 70% of motor oil from contaminated cotton cloth in detergency tests. The crude biosurfactant also removed 30–40% of Cu and Pb from standard sand, while the isolated biosurfactant removed ~30% of the heavy metals. The conductivity of solutions containing Cd and Pb was sharply reduced after biosurfactants' addition. A product was prepared through adding 0.2% potassium sorbate as preservative and tested over 120 days. The formulated biosurfactant was analyzed for emulsification and surface tension under different pH values, temperatures, and salt concentrations and tested for toxicity against the fish Poecilia vivipara. The results showed that the formulation had no toxicity and did not cause significant changes in the tensoactive capacity of the biomolecule while maintaining activity demonstrating suitability for potential future commercial product formulation.

The granular sludge process is an effective, low-footprint alternative to conventional activated sludge wastewater treatment. The architecture of the microbial granules allows the co-existence of different functional groups, e.g., nitrifying and denitrifying communities, which permits compact reactor design. However, little is known about the factors influencing community assembly in granular sludge, such as the effects of reactor operation strategies and influent wastewater composition. Here, we analyze the development of the microbiomes in parallel laboratory-scale anoxic/aerobic granular sludge reactors operated at low (0.9 kg m-3d-1), moderate (1.9 kg m-3d-1) and high (3.7 kg m-3d-1) organic loading rates (OLRs) and the same ammonium loading rate (0.2 kg NH4-N m-3d-1) for 84 days. Complete removal of organic carbon and ammonium was achieved in all three reactors after start-up, while the nitrogen removal (denitrification) efficiency increased with the OLR: 0% at low, 38% at moderate, and 66% at high loading rate. The bacterial communities at different loading rates diverged rapidly after start-up and showed less than 50% similarity after 6 days, and below 40% similarity after 84 days. The three reactor microbiomes were dominated by different genera (mainly Meganema, Thauera, Paracoccus, and Zoogloea), but these genera have similar ecosystem functions of EPS production, denitrification and polyhydroxyalkanoate (PHA) storage. Many less abundant but persistent taxa were also detected within these functional groups. The bacterial communities were functionally redundant irrespective of the loading rate applied. At steady-state reactor operation, the identity of the core community members was rather stable, but their relative abundances changed considerably over time. Furthermore, nitrifying bacteria were low in relative abundance and diversity in all reactors, despite their large contribution to nitrogen turnover. The results suggest that the OLR has considerable impact on the composition of the granular sludge communities, but also that the granule communities can be dynamic even at steady-state reactor operation due to high functional redundancy of several key guilds. Knowledge about microbial diversity with specific functional guilds under different operating conditions can be important for engineers to predict the stability of reactor functions during the start-up and continued reactor operation.

Plant cell walls are composed predominantly of cellulose, a range of non-cellulosic polysaccharides and lignin. The walls account for a large proportion not only of crop residues such as wheat straw and sugarcane bagasse, but also of residues of the timber industry and specialist grasses and other plants being grown specifically for biofuel production. The polysaccharide components of plant cell walls have long been recognized as an extraordinarily large source of fermentable sugars that might be used for the production of bioethanol and other renewable liquid transport fuels. Estimates place annual plant cellulose production from captured light energy in the order of hundreds of billions of tonnes. Lignin is synthesised in the same order of magnitude and, as a very large polymer of phenylpropanoid residues, lignin is also an abundant, high energy macromolecule. However, one of the major functions of these cell wall constituents in plants is to provide the extreme tensile and compressive strengths that enable plants to resist the forces of gravity and a broad range of other mechanical forces. Over millions of years these wall constituents have evolved under natural selection to generate extremely tough and resilient biomaterials. The rapid degradation of these tough cell wall composites to fermentable sugars is therefore a difficult task and has significantly slowed the development of a viable lignocellulose-based biofuels industry. However, good progress has been made in overcoming this so-called recalcitrance of lignocellulosic feedstocks for the biofuels industry, through modifications to the lignocellulose itself, innovative pre-treatments of the biomass, improved enzymes and the development of superior yeasts and other microorganisms for the fermentation process. Nevertheless, it has been argued that bioethanol might not be the best or only biofuel that can be generated from lignocellulosic biomass sources and that hydrocarbons with intrinsically higher energy densities might be produced using emerging and continuous flow systems that are capable of converting a broad range of plant and other biomasses to bio-oils through so-called ‘agnostic’ technologies such as hydrothermal liquefaction. Continued attention to regulatory frameworks and ongoing government support will be required for the next phase of development of internationally viable biofuels industries.

To convert wastes into sustainable liquid fuels and chemicals, new resource recovery technologies are required. Chain elongation is a carboxylate-platform bioprocess that converts short-chain carboxylates (SCCs) (e.g., acetate [C2] and n-butyrate [C4]) into medium-chain carboxylates (MCCs) (e.g., n-caprylate [C8] and n-caproate [C6]) with hydrogen gas as a side product. Ethanol or another electron donor (e.g., lactate, carbohydrate) is required. Competitive MCC productivities, yields (product vs. substrate fed), and specificities (product vs. all products) were only achieved previously from an organic waste material when exogenous ethanol had been added. Here, we converted a real organic waste, which inherently comprised of ethanol, into MCCs with n-caprylate as the target product. We used wine lees, which consisted primarily of settled yeast cells and ethanol from wine fermentation, and produced MCCs with a reactor microbiome. We operated the bioreactor at a pH of 5.2 and with continuous in-line extraction and achieved a MCC productivity of 3.9 g COD/L-d at an organic loading rate of 5.8 g COD/L-d, resulting in a promising MCC yield of 67% and specificities of 36% for each n-caprylate and n-caproate (72% for both). Compared to all other studies that used complex organic substrates, we achieved the highest n-caprylate-to-n-caproate product ratio of 1.0 (COD basis), because we used increased broth-recycle rates through the forward membrane contactor, which improved in-line extraction rates. Increased recycle rates also allowed us to achieve the highest reported MCC production flux per membrane surface area thus far (20.1 g COD/m2-d). Through microbial community analyses, we determined that an operational taxonomic unit (OTU) for Bacteroides spp. was dominant and was positively correlated with increased MCC productivities. Our data also suggested that the microbiome may have been shaped for improved MCC production by the high broth-recycle rates. Comparable abiotic studies suggest that further increases in the broth-recycle rates could improve the overall mass transfer coefficient and its corresponding MCC production flux by almost 30 times beyond the maximum that we achieved. With improved in-line extraction, the chain-elongation biotechnology production platform offers new opportunities for resource recovery and sustainable production of liquid fuels and chemicals.

Lignin, a complex aromatic polymer in terrestrial plants, contributes significantly to biomass recalcitrance to microbial and/or enzymatic deconstruction. To reduce biomass recalcitrance, substantial endeavors have been exerted on pretreatment and lignin engineering in the past few decades. Lignin removal and/or alteration of lignin structure have been shown to result in reduced biomass recalcitrance with improved cell wall digestibility. While high lignin content is usually a barrier to a cost-efficient application of bioresources to biofuels, the direct correlation of lignin structure and its concomitant properties with biomass remains unclear due to the complexity of cell wall and lignin structure. Advancement in application of biorefinery to production of biofuels, chemicals, and bio-derived materials necessitates a fundamental understanding of the relationship of lignin structure and biomass recalcitrance. In this mini-review, we focus on recent investigations on the influence of lignin chemical properties on bioprocessability-pretreatment and enzymatic hydrolysis of biomass. Specifically, lignin-enzyme interactions and the effects of lignin compositional units, hydroxycinnamates, and lignin functional groups on biomass recalcitrance have been highlighted, which will be useful not only in addressing biomass recalcitrance but also in deploying renewable lignocelluloses efficiently.

Oil spills in oceans cause irreparable damage to marine life and harm the coastal populations of affected areas. It is therefore fundamental to develop treatment strategies for such spills. Currently, chemical dispersants have been used during oil spills, although these agents have been increasingly restricted due to their toxic potential. Thus, the aim of the present study was to formulate a biodegradable commercial biosurfactant for application as a dispersant. Biosurfactants are scientifically known biomolecules produced by microorganisms capable of allowing water-oil interaction. Thus, a biosurfactant was produced by the yeast Candida bombicola URM 3718 cultivated in industrial waste and formulated with the addition of a potassium sorbate preservative for fractionated sterilization (tyndallization) and the combination of fluent vaporization with the preservative. After formulation, samples were stored for 120 days, followed by surface tension, emulsification and oil dispersant tests in sea water. The results were promising for the biosurfactant formulated with the preservative, which demonstrated stability and an absence of toxicity in experiments with a marine indicator. The commercial biosurfactant was tested at different pH values, temperatures and in the presence of salt, demonstrating potential industrial application at a cost compatible with the environmental field. The formulation process developed in this research was patented in the Brazilian National Intellectual Property Institute (patent number BR1020140179631).

Given the large amount of crude glycerol formed as a by-product in the biodiesel industries and the concomitant decrease in its overall market price, there is a need to add extra value to this biorefinery side stream. Upgrading can be achieved by new biotechnologies dealing with recovery and conversion of glycerol present in wastewaters into value-added products, aiming at a zero-waste policy and developing an economically viable process. In microbial bioelectrochemical systems (BESs), the mixed microbial community growing on the cathode can convert glycerol reductively to 1,3-propanediol (1,3-PDO). However, the product yield is rather limited in BESs compared with classic fermentation processes, and the synthesis of side-products, resulting from oxidation of glycerol, such as organic acids, represents a major burden for recovery of 1,3-PDO. Here, we show that the use of an enriched mixed-microbial community of glycerol degraders and in situ extraction of organic acids positively impacts 1,3-PDO yield and allows additional recovery of propionate from glycerol. We report the highest production yield achieved (0.72 mol1,3-PDO mol−1glycerol) in electricity-driven 1,3-PDO biosynthesis from raw glycerol, which is very close to the 1,3-PDO yield reported thus far for a mixed-microbial culture-based glycerol fermentation process. We also present a combined approach for 1,3-PDO production and propionate extraction in a single three chamber reactor system, which leads to recovery of additional 3-carbon compounds in BESs. This opens up further opportunities for an economical upgrading of biodiesel refinery side or waste streams.

Microbial damages caused by biofilm forming bacteria in the dairy industry are a fundamental threat to safety and quality of dairy products. In order to ensure the optimal level of equipment hygiene in the dairy industry, it is necessary to determine the biofilm removal efficiency of cleaning agents used for cleaning-in-place procedures. However, currently there is no standard method available for evaluating and comparing cleaning agents for use in cleaning-in-place procedures in the dairy industry under realistic conditions. The present study aims to establish a cleaning-in-place model system to evaluate the effectiveness of cleaning agents in removal of biofilm derived spores from the surfaces of stainless steel which is the predominant substrate in milking equipment on dairy farms. The system is based on Bacillus subtilis spores surrounded with exopolymeric substances produced by bacteria during biofilm formation. The spores applied on sampling plates were mounted on T-junctions protruding 1.5 – 11-times the milk pipe diameter from the main loop to resemble different levels of cleaning difficulty. The cleaning tests were conducted using commercial alkaline detergents and caustic soda at conditions which are relevant to actual farm environment. The spores removal effect was evaluated by comparing the number of viable spores (attached to sampling plates) before and after cleaning. Evaluation of the cleaning and disinfecting effect of cleaning agents towards biofilm derived spores was further performed, which indicates whether spores elimination effect of an agent is due to killing the spores or removing them from the surfaces of dairy equipment. Moreover, it was established that the presence of extracellular matrix is an important factor responsible for high level of cleaning difficulty characteristic for surface attached spores. In overall, the results of this study suggest that the developed model system simulates actual farm conditions for quantitative evaluation of the effectiveness of cleaning and disinfecting agents and their cleaning and disinfecting effect on removal of biofilm derived spores.

Even though the main components of all lignocellulosic feedstocks include cellulose, hemicellulose, as well as the protective lignin matrix, there are some differences in structure, such as in hardwoods and softwoods, which may influence the degradability of the materials. Under this view, various types of biomass might require a minimal set of enzymes that has to be tailor-made. Partially defined complex mixtures that are currently commercially used are not adapted to efficiently degrade different materials, so novel enzyme mixtures have to be customized. Development of these cocktails requires better knowledge about the specific activities involved, in order to optimize hydrolysis. The role of filamentous fungus Myceliophthora thermophila and its complete enzymatic repertoire for the bioconversion of complex carbohydrates has been widely proven. In this study, four core cellulases (MtCBH7, MtCBH6, MtEG5, and MtEG7), in the presence of other four “accessory” enzymes (mannanase, lytic polyssacharide monooxygenase MtGH61, xylanase, MtFae1a) and β-glucosidase MtBGL3, were tested as a nine-component cocktail against one model substrate (phosphoric acid swollen cellulose) and four hydrothermally pretreated natural substrates (wheat straw as an agricultural waste, birch, and spruce biomass, as forest residues). Synergistic interactions among different enzymes were determined using a suitable design of experiments methodology. The results suggest that for the hydrolysis of the pure substrate (PASC), high proportions of MtEG7 are needed for efficient yields. MtCBH7 and MtEG7 are enzymes of major importance during the hydrolysis of pretreated wheat straw, while MtCBH7 plays a crucial role in case of spruce. Cellobiohydrolases MtCBH6 and MtCBH7 act in combination and are key enzymes for the hydrolysis of the hardwood (birch). Optimum combinations were predicted from suitable statistical models which were able to further increase hydrolysis yields, suggesting that tailor-made enzyme mixtures targeted toward a particular residual biomass can help maximize hydrolysis yields. The present work demonstrates the change from “one cocktail for all” to “tailor-made cocktails” that are needed for the efficient saccharification of targeted feed stocks prior to the production of biobased products through the biorefinery concept.

We constructed a survey to understand how authors and scientists view the issues around reproducibility, focusing on interactive elements such as interactive figures embedded within online publications, as a solution for enabling the reproducibility of experiments. We report the views of 251 researchers, comprising authors who have published in eLIFE Sciences, and those who work at the Norwich Biosciences Institutes (NBI). The survey also outlines to what extent researchers are occupied with reproducing experiments themselves. Currently, there is an increasing range of tools that attempt to address the production of reproducible research by making code, data, and analyses available to the community for reuse. We wanted to collect information about attitudes around the consumer end of the spectrum, where life scientists interact with research outputs to interpret scientific results. Static plots and figures within articles are a central part of this interpretation, and therefore we asked respondents to consider various features for an interactive figure within a research article that would allow them to better understand and reproduce a published analysis. The majority (91%) of respondents reported that when authors describe their research methodology (methods and analyses) in detail, published research can become more reproducible. The respondents believe that having interactive figures in published papers is a beneficial element to themselves, the papers they read as well as to their readers. Whilst interactive figures are one potential solution for consuming the results of research more effectively to enable reproducibility, we also review the equally pressing technical and cultural demands on researchers that need to be addressed to achieve greater success in reproducibility in the life sciences.

To tackle the challenges in genomic data analysis caused by their tens of thousands of dimensions while having a small number of examples and unbalanced examples between classes, the technique of unsupervised feature selection based on standard deviation and cosine similarity is proposed in this paper. We refer to this idea as SCFS (Standard deviation and Cosine similarity based Feature Selection). It defines the discernibility and independence of a feature to value its distinguishable capability between classes and its redundancy to other features, respectively. A 2-dimensional space is constructed using discernibility as x-axis and independence as y-axis to represent all features where the upper right corner features have both comparatively high discernibility and independence. The importance of a feature is defined as the product of its discernibility and its independence (i.e., the area of the rectangular enclosed by the feature’s coordinate lines and axes). The upper right corner features are by far the most important, comprising the optimal feature subset. Based on different definitions of independence using cosine similarity, there are three feature selection algorithms derived from SCFS. These are SCEFS (Standard deviation and Exponent Cosine similarity based Feature Selection), SCRFS (Standard deviation and Reciprocal Cosine similarity based Feature Selection) and SCAFS (Standard deviation and Anti-Cosine similarity based Feature Selection), respectively. The KNN and SVM classifiers are built based on the optimal feature subsets detected by these feature selection algorithms, respectively. The experimental results on 18 genomic datasets of cancers demonstrate that the proposed unsupervised feature selection algorithms SCEFS, SCRFS and SCAFS can detect the stable biomarkers with strong classification capability. This shows that the idea proposed in this paper is powerful. The functional analysis of these biomarkers show that the occurrence of the cancer is closely related to the biomarker gene regulation level. This fact will benefit cancer pathology research, drug development, early diagnosis, treatment and prevention.

Bananas are an important staple food crop in tropical and subtropical regions in Asia, sub-Saharan Africa, and Central and South America. The plant is affected by numerous diseases, with the fungal leaf disease black Sigatoka, caused by Mycosphaerella fijiensis Morelet [anamorph: Pseudocercospora fijiensis (Morelet) Deighton], considered one of the most economically important phytosanitary problem. Although the development of resistant cultivars is recognized as most effective method for long term control of the disease, the majority of today's cultivars are susceptible. In order to gain insights into this pathosystem, this first systematic literature review on the topic is presented. Utilizing six databases (PubMed Central, Web of Science, Google Academic, Springer, CAPES and Scopus Journals) searches were performed using pre-established inclusion and exclusion criteria. From a total of 3,070 published studies examined, 24 were relevant with regard to the Musa-P. fijiensis pathosystem. Relevant papers highlighted that resistant and susceptible cultivars clearly respond differently to infection by this pathogen. M. acuminata wild diploids such as Calcutta 4 and other diploid cultivars can harbor sources of resistance genes, serving as parentals for the generation of improved diploids and subsequent gene introgression in new cultivars. From the sequenced reference genome of Musa acuminata, although the function of many genes in the genome still require validation, on the basis of transcriptome, proteome and biochemical data, numerous candidate genes and molecules have been identified for further evaluation through genetic transformation and gene editing approaches. Genes identified in the resistance response have included those associated with jasmonic acid and ethylene signaling, transcription factors, phenylpropanoid pathways, antioxidants and pathogenesis-related proteins. Papers in this study also revealed gene-derived markers in Musa applicable for downstream application in marker assisted selection. The information gathered in this review furthers understanding of the immune response in Musa to the pathogen P. fijiensis and is relevant for genetic improvement programs for bananas and plantains for control of black Sigatoka.

IntroductionBesides recurrent infections, a proportion of patients with Common Variable Immunodeficiency Disorders (CVID) may suffer from immune dysregulation such as granulomatous-lymphocytic interstitial lung disease (GLILD). The optimal treatment of this complication is currently unknown. Experienced-based expert opinions have been produced, but a systematic review of published treatment studies is lacking.GoalsTo summarize and synthesize the published literature on the efficacy of treatments for GLILD in CVID.MethodsWe performed a systematic review using the PRISMA guidelines. Papers describing treatment and outcomes in CVID patients with radiographic and/or histologic evidence of GLILD were included. Treatment regimens and outcomes of treatment were summarized.Results6124 papers were identified and 42, reporting information about 233 patients in total, were included for review. These papers described case series or small, uncontrolled studies of monotherapy with glucocorticoids or other immunosuppressants, rituximab monotherapy or rituximab plus azathioprine, abatacept, or hematopoietic stem cell transplantation (HSCT). Treatment response rates varied widely. Cross-study comparisons were complicated because different treatment regimens, follow-up periods, and outcome measures were used. There was a trend towards more frequent GLILD relapses in patients treated with corticosteroid monotherapy when compared to rituximab-containing treatment regimens based on qualitative endpoints. HSCT is a promising alternative to pharmacological treatment of GLILD, because it has the potential to not only contain symptoms, but also to resolve the underlying pathology. However, mortality, especially among immunocompromised patients, is high.ConclusionsWe could not draw definitive conclusions regarding optimal pharmacological treatment for GLILD in CVID from the current literature since quantitative, well-controlled evidence was lacking. While HSCT might be considered a treatment option for GLILD in CVID, the risks related to the procedure are high. Our findings highlight the need for further research with uniform, objective and quantifiable endpoints. This should include international registries with standardized data collection including regular pulmonary function tests (with carbon monoxide-diffusion), uniform high-resolution chest CT radiographic scoring, and uniform treatment regimens, to facilitate comparison of treatment outcomes and ultimately randomized clinical trials.

As anyone who has witnessed firsthand knows, healthcare delivery in low-resource settings is fundamentally different from more affluent settings. Artificial Intelligence, including Machine Learning and more specifically Deep Learning, has made amazing advances over the past decade. Significant resources are now dedicated to problems in the field of medicine, but with the potential to further the digital divide by neglecting underserved areas and their specific context. In the general case, Deep Learning remains a complex technology requiring deep technical expertise. This paper explores advances within the narrower field of deep learning image analysis that reduces barriers to adoption and allows individuals with less specialized software skills to effectively employ these techniques. This enables a next wave of innovation, driven largely by problem domain expertise and the creative application of this technology to unaddressed concerns in LMIC settings. The paper also explores the central role of NGOs in problem identification, data acquisition and curation, and integration of new technologies into healthcare systems.

Despite recent advances in using biologicals that target Th2 pathways, glucocorticoids form the mainstay of asthma treatment. Asthma morbidity and mortality remain high due to the wide variability of treatment responsiveness and complex clinical phenotypes driven by distinct underlying mechanisms. Emerging evidence suggests that inhalation of the toxic air pollutant, ozone, worsens asthma by impairing glucocorticoid responsiveness. This review discusses the role of oxidative stress in glucocorticoid resistance in asthma. The underlying mechanisms point to a central role of oxidative stress pathways. The primary data source for this review consisted of peer-reviewed publications on the impact of ozone on airway inflammation and glucocorticoid responsiveness indexed in PubMed. Our main search strategy focused on cross-referencing “asthma and glucocorticoid resistance” against “ozone, oxidative stress, alarmins, innate lymphoid, NK and γδ T cells, dendritic cells and alveolar type II epithelial cells, glucocorticoid receptor and transcription factors”. Recent work was placed in the context from articles in the last 10 years and older seminal research papers and comprehensive reviews. We excluded papers that did not focus on respiratory injury in the setting of oxidative stress. The pathways discussed here have however wide clinical implications to pathologies associated with inflammation and oxidative stress and in which glucocorticoid treatment is essential.

The gluco-lipostatic theory and its modern variants assume that blood glucose and energy stores are controlled in closed-loop feedback processes. The Selfish Brain theory is based on the same assumptions, but additionally postulates that the brain, as an independent energy compartment, self-regulates its energy concentration with the highest priority. In some clinical situations these two theories make opposite predictions. To investigate one of these situations, namely caloric restriction, we formulated a hypothesis which, if confirmed, would match the predictions of the Selfish Brain theory—but not those of the gluco-lipostatic theory. Hypothesis: Calorie restriction causes minor mass (energy) changes in the brain as opposed to major changes in the body. We conducted a systematic review of caloric-restriction studies to test whether or not the evaluated studies confirmed this hypothesis. We identified 3,157 records, screened 2,804 works by title or abstract, and analyzed 232 by full text. According to strict selection criteria (set out in our PROSPERO preregistration, complying with PRISMA guidelines, and the pre-defined hypothesis-decision algorithm), 8 papers provided enough information to decide on the hypothesis: In animals, high-energy phosphates were measured by 31P-nuclear magnetic resonance, and organ and total body weights were measured by scales, while in humans organ sizes were determined by magnetic resonance imaging. All 8 decidable papers confirmed the hypothesis, none spoke against it. The evidence presented here clearly shows that the most accurate predictions are possible with a theory that regards the brain as independently self-regulating and as occupying a primary position in a hierarchically organized energy metabolism.

Horticultural crops have high economic, and enrich our lives through their aesthetic and nutritional value. Many horticultural species originate from tropical regions and are sensitive to cold at every stage of their lifecycle. Cold stress leads to lower productivity and post-harvest losses in these species, with poor economic and environmental outcomes. Better understanding of the protective mechanisms mediated by hormonal and other signaling pathways (Akhtar et al., 2012) may offer solutions to reduce cold-stress induced losses. The papers included in this collection illustrate this concept, examining natural cold-tolerance mechanisms and practical ways for growers to alleviate chilling stress and to reduce crop losses. The studies were remarkably diverse in terms of the species studied (i.e., tomato, longan, tung tree, lowbush blueberry, and apple), plant organs examined (i.e., seedlings, leaf, and fruit), and approaches used (i.e., reverse genetics, the systems biology, physiology, and biochemistry). The papers encompassed the use of (1) basic science, aimed at identifying key genes and their roles in cold signal transduction and protective pathways in fruit and photosynthetic tissues; (2) reverse genetics for proof-of-concept on the hypothesized role of a cold-tolerance transcription factor cloned from an understudied species; and (3) emerging technologies, by using exogenous hormones and signaling compounds to mitigate the harmful effects of chilling. These studies are described below. Current work at IL's lab was funded by grant AGL2015-64235-R from the Plan Nacional de I+D, Ministry of Education and Science, Spain. DB acknowledges funding from the US-Israeli Binational Agricultural Research Development Grant no. #IS-5196-19. Fund and the AES Hatch Project CA-D-PLS-2404-H. Work at MD's lab was funded by National Research Council and National Agency for the Promotion of Scientific and Technological Activities from Argentina.

Understanding plant growth processes is important for many aspects of biology and food security. Automating the observations of plant development—a process referred to as plant phenotyping—is increasingly important in the plant sciences, and is often a bottleneck. Automated tools are required to analyze the data in microscopy images depicting plant growth, either locating or counting regions of cellular features in images. In this paper, we present to the plant community an introduction to and exploration of two machine learning approaches to address the problem of marker localization in confocal microscopy. First, a comparative study is conducted on the classification accuracy of common conventional machine learning algorithms, as a means to highlight challenges with these methods. Second, a 3D (volumetric) deep learning approach is developed and presented, including consideration of appropriate loss functions and training data. A qualitative and quantitative analysis of all the results produced is performed. Evaluation of all approaches is performed on an unseen time-series sequence comprising several individual 3D volumes, capturing plant growth. The comparative analysis shows that the deep learning approach produces more accurate and robust results than traditional machine learning. To accompany the paper, we are releasing the 4D point annotation tool used to generate the annotations, in the form of a plugin for the popular ImageJ (FIJI) software. Network models and example datasets will also be available online.

Cancer is still a severe health problem globally. The therapy of cancer traditionally involves the use of radiotherapy or anticancer drugs to kill cancer cells, but these methods are quite expensive and have side effects, which will cause great harm to patients. With the find of anticancer peptides (ACPs), significant progress has been achieved in the therapy of tumors. Therefore, it is invaluable to accurately identify anticancer peptides. Although biochemical experiments can solve this work, this method is expensive and time-consuming. To promote the application of anticancer peptides in cancer therapy, machine learning can be used to recognize anticancer peptides by extracting the feature vectors of anticancer peptides. Nevertheless, poor performance usually be found in training the machine learning model to utilizing high-dimensional features in practice. In order to solve the above job, this paper put forward a 19-dimensional feature model based on anticancer peptide sequences, which has lower dimensionality and better performance than some existing methods. In addition, this paper also separated a model with a low number of dimensions and acceptable performance. The few features identified in this study may represent the important features of anticancer peptides.

To understand the function of the neocortex, which is a hierarchical distributed network, it is useful giving meaning to the signals transmitted between these areas from the computational viewpoint. The overall anatomical structure or organs related to this network, including the neocortex, thalamus, and basal ganglia, has been roughly revealed, and much physiological knowledge, though often fragmentary, is being accumulated. The computational theories involving the neocortex have also been developed considerably. By introducing the assumption “The signals transmitted by interarea axonal projections of pyramidal cells in the neocortex carry different meanings for each cell type, common to all areas,” derived from its nature as a distributed network in the neocortex, allows us to specify the computational meanings of interarea signals. In this paper, first, the types of signals exchanged between neocortical areas are investigated, taking into account biological constraints, and employing theories such as predictive coding, reinforcement learning, representation emulation theory, and BDI logic as theoretical starting points, two types of feedforward signals (observation and deviation) and three types of feedback signals (prediction, plan, and intention) are identified. Next, based on the anatomical knowledge of the neocortex and thalamus, the pathways connecting the areas are organized and summarized as three corticocortical pathways and two thalamocortical pathways. Using this summation as preparation, this paper proposes a hypothesis that gives meaning to each type of signals transmitted in the different pathways in the neocortex, from the viewpoint of their functions. This hypothesis reckons that the feedforward corticocortical pathway transmits observation signals, the feedback corticocortical pathway transmits prediction signals, and the corticothalamic pathway mediated by core relay cells transmits deviation signals. The thalamocortical pathway, which is mediated by matrix relay cells, would be responsible for transmitting the signals that activate a part of prediction signals as intentions, due to the reason that the nature of the other available feedback pathways are not sufficient for conveying plans and intentions as signals. The corticocortical pathway, which is projected from various IT cells to the first layer, would be responsible for transmitting signals that activate a part of prediction signals as plans.

Cancer of unknown primary site (CUPS) is a type of metastatic tumor for which the sites of tumor origin cannot be determined. Precise diagnosis of the tissue origin for metastatic CUPS is crucial for developing treatment schemes to improve patient prognosis. Recently, there have been many studies using various cancer biomarkers to predict the tissue-of-origin (TOO) of CUPS. However, only a very few of them use copy number alteration (CNA) to trance TOO. In this paper, a two-step computational framework called CNA_origin is introduced to predict the tissue-of-origin of a tumor from its gene CNA levels. CNA_origin set up an intellectual deep-learning network mainly composed of an autoencoder and a convolution neural network (CNN). Based on real datasets released from the public database, CNA_origin had an overall accuracy of 83.81% on 10-fold cross-validation and 79% on independent datasets for predicting tumor origin, which improved the accuracy by 7.75 and 9.72% compared with the method published in a previous paper. Our results suggested that the autoencoder model can extract key characteristics of CNA and that the CNN classifier model developed in this study can predict the origin of tumors robustly and effectively. CNA_origin was written in Python and can be downloaded from https://github.com/YingLianghnu/CNA_origin.

Acute central nervous system (CNS) injuries, such as stroke, traumatic brain injury (TBI), and spinal cord injury (SCI) present a grave health care challenge worldwide due to high morbidity and mortality, as well as limited clinical therapeutic strategies. Established literature has shown that oxidative stress (OS), inflammation, excitotoxicity, and apoptosis play important roles in the pathophysiological processes of acute CNS injuries. Recently, there have been many studies on the topic of ferroptosis, a form of regulated cell death characterized by the accumulation of iron-dependent lipid peroxidation. Some studies have revealed an emerging connection between acute CNS injuries and ferroptosis. Ferroptosis, induced by the abnormal metabolism of lipids, glutathione (GSH), and iron, can accelerate acute CNS injuries. However, pharmaceutical agents, such as iron chelators, ferrostatin-1 (Fer-1), and liproxstatin-1 (Lip-1), can inhibit ferroptosis and may have neuroprotective effects after acute CNS injuries. However, the specific mechanisms underlying this connection has not yet been clearly elucidated. In this paper, we discuss the general mechanisms of ferroptosis and its role in stroke, TBI, and SCI. We also summarize ferroptosis-related drugs and highlight the potential therapeutic strategies in treating various acute CNS injuries. Additionally, this paper suggests a testable hypothesis that ferroptosis may be a novel direction for further research of acute CNS injuries by providing corresponding evidence.

With the increasing application of orthopedic scaffolds, a dramatically increasing number of requirements for scaffolds are precise. The porous structure has been a fundamental design in the bone tissue engineering or orthopedic clinics because of its low Young's modulus, high compressive strength, and abundant cell accommodation space. The porous structure manufactured by additive manufacturing (AM) technology has controllable pore size, pore shape, and porosity. The single unit can be designed and arrayed with AM, which brings controllable pore characteristics and mechanical properties. This paper presents the current status of porous designs in AM technology. The porous structures are stated from the cellular structure and the whole structure. In the aspect of the cellular structure, non-parametric design and parametric design are discussed here according to whether the algorithm generates the structure or not. The non-parametric design comprises the diamond, the body-centered cubic, and the polyhedral structure, etc. The Voronoi, the Triply Periodic Minimal Surface, and other parametric designs are mainly discussed in parametric design. In the discussion of cellular structures, we emphasize the design, and the resulting biomechanical and biological effects caused by designs. In the aspect of the whole structure, the recent experimental researches are reviewed on uniform design, layered gradient design, and layered gradient design based on topological optimization, etc. These parts are summarized because of the development of technology and the demand for mechanics or bone growth. Finally, the challenges faced by the porous designs and prospects of porous structure in orthopedics are proposed in this paper.

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) and major anatomical structures of interest (ventricles, atria and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across different domains, interpretability) and suggest potential directions for future research., Under review

The current study provides a comprehensive overview and analysis of the lignan literature. Data for the current study were extracted from the electronic Web of Science Core Collection database via the search string TOPIC = (lignan*) and processed by the VOSviewer software. The search yielded 10,742 publications. The ratio of original articles to reviews was 14.6:1. Over 80% of the analyzed papers have been published since the year 2000 and nearly 50% since the year 2010. Many of the publications were focused on pharmacology, chemistry, and plant sciences. The United States and Asian countries, such as China, Japan, South Korea, and India, were the most productive producers of lignan publications. Among the 5 most productive institutions was the University of Helsinki in Finland, the country that ranked 9th. Nineteen journals collectively published 3,607 lignan publications and were considered as core journals. Their impact factor did not correlate with the proportion of uncited papers. Highly cited publications usually mentioned phytoestrogen, isoflavone, daidzein, enterodiol, enterolactone, equol, genistein, and isoflavonoid. Cancer (e.g., breast cancer), cardiovascular disease, and antioxidation were the major themes. Clinical trials were estimated to contribute to 0.21.1% of the analyzed body of literature, so more of them should be conducted in the future to substantiate the beneficial effects and optimal dose of lignan intake in humans. Moreover, researchers can refer to these findings for future research directions and collaborations., AA acknowledges the support by the Polish KNOW (Leading National Research Centre) Scientific Consortium “Healthy Animal—Safe Food,” decision of the Ministry of Science and Higher Education No. 05-1/KNOW2/2015. EN and AS acknowledge the support of the research project Nutraceutica come supporto nutrizionale nel paziente oncologico, CUP: B83D18000140007., info:eu-repo/semantics/publishedVersion