Quantifying the metabolic capabilities of engineered Zymomonas mobilis using linear programming analysis

BACKGROUND: The need for discovery of alternative, renewable, environmentally friendly energy sources and the development of cost-efficient, "clean" methods for their conversion into higher fuels becomes imperative. Ethanol, whose significance as fuel has dramatically increased in the last decade, can be produced from hexoses and pentoses through microbial fermentation. Importantly, plant biomass, if appropriately and effectively decomposed, is a potential inexpensive and highly renewable source of the hexose and pentose mixture. Recently, the engineered (to also catabolize pentoses) anaerobic bacterium Zymomonas mobilis has been widely discussed among the most promising microorganisms for the microbial production of ethanol fuel. However, Z. mobilis genome having been fully sequenced in 2005, there is still a small number of published studies of its in vivo physiology and limited use of the metabolic engineering experimental and computational toolboxes to understand its metabolic pathway interconnectivity and regulation towards the optimization of its hexose and pentose fermentation into ethanol. RESULTS: In this paper, we reconstructed the metabolic network of the engineered Z. mobilis to a level that it could be modelled using the metabolic engineering methodologies. We then used linear programming (LP) analysis and identified the Z. mobilis metabolic boundaries with respect to various biological objectives, these boundaries being determined only by Z. mobilis network's stoichiometric connectivity. This study revealed the essential for bacterial growth reactions and elucidated the association between the metabolic pathways, especially regarding main product and byproduct formation. More specifically, the study indicated that ethanol and biomass production depend directly on anaerobic respiration stoichiometry and activity. Thus, enhanced understanding and improved means for analyzing anaerobic respiration and redox potential in vivo are needed to yield further conclusions for potential genetic targets that may lead to optimized Z. mobilis strains. CONCLUSION: Applying LP to study the Z. mobilis physiology enabled the identification of the main factors influencing the accomplishment of certain biological objectives due to metabolic network connectivity only. This first-level metabolic analysis model forms the basis for the incorporation of more complex regulatory mechanisms and the formation of more realistic models for the accurate simulation of the in vivo Z. mobilis physiology

Coronavirus disease 2019 and future pandemics: Impacts on livestock health and production and possible mitigation measures

The World Health Organization declared coronavirus disease 2019 (COVID-19) a pandemic on March 11, 2020. COVID-19, the current global health emergency, is wreaking havoc on human health systems and, to a lesser degree, on animals globally. The outbreak has continued since the first report of COVID-19 in China in December 2019, and the second and third waves of the outbreak have already begun in several countries. COVID-19 is expected to have adverse effects on crop production, food security, integrated pest control, tourism, the car industry, and other sectors of the global economy. COVID-19 induces a range of effects in livestock that is reflected economically since human health and livelihood are intertwined with animal health. We summarize the potentially harmful effects of COVID-19 on livestock and possible mitigation steps in response to this global outbreak. Mitigation of the negative effects of COVID-19 and future pandemics on livestock requires the implementation of current guidelines

A novel method for furfural recovery via gas stripping assisted vapor permeation by a polydimethylsiloxane membrane

Furfural is an important platform chemical with a wide range of applications. However, due to the low concentration of furfural in the hydrolysate, the conventional methods for furfural recovery are energy-intensive and environmentally unfriendly. Considering the disadvantages of pervaporation (PV) and distillation in furfural separation, a novel energy-efficient ‘green technique’, gas stripping assisted vapor permeation (GSVP), was introduced in this work. In this process, the polydimethylsiloxane (PDMS) membrane was prepared by employing water as solvent. Coking in pipe and membrane fouling was virtually non-existent in this new process. In addition, GSVP was found to achieve the highest pervaporation separation index of 216200 (permeate concentration of 71.1 wt% and furfural flux of 4.09 kgm(−2)h(−1)) so far, which was approximately 2.5 times higher than that found in pervaporation at 95°C for recovering 6.0 wt% furfural from water. Moreover, the evaporation energy required for GSVP decreased by 35% to 44% relative to that of PV process. Finally, GSVP also displayed more promising potential in industrial application than PV, especially when coupled with the hydrolysis process or fermentation in biorefinery industry

Graphene-enabled adaptive infrared textiles

Interactive clothing requires sensing and display functionalities to be embedded on textiles. Despite the significant progress of electronic textiles, the integration of optoelectronic materials on fabrics remains as an outstanding challenge. In this Letter, using the electro-optical tunability of graphene, we report adaptive optical textiles with electrically controlled reflectivity and emissivity covering the infrared and near-infrared wavelengths. We achieve electro-optical modulation by reversible intercalation of ions into graphene layers laminated on fabrics. We demonstrate a new class of infrared textile devices including display, yarn, and stretchable devices using natural and synthetic textiles. To show the promise of our approach, we fabricated an active device directly onto a t-shirt, which enables long-wavelength infrared communication via modulation of the thermal radiation from the human body. The results presented here provide complementary technologies which could leverage the ubiquitous use of functional textiles

Smart and multifunctional fiber‐reinforced composites of 2D heterostructure‐based textiles

Smart and multifunctional fiber reinforced polymer (FRP) composites with energy storage, sensing, and heating capabilities have gained significant interest for automotive, civil, and aerospace applications. However, achieving smart and multifunctional capabilities in an FRP composite while maintaining desired mechanical properties remains challenging. Here, a novel approach for layer‐by‐layer (LBL) deposition of 2D material (graphene and molybdenum disulfide, MoS2)‐based heterostructure onto glass fiber fabric using a highly scalable manufacturing technique at a remarkable speed of ≈150 m min−1 is reported. This process enables the creation of smart textiles with integrated energy storage, sensing, and heating functionalities. This methodology combines gel‐based electrolyte with a vacuum resin infusion technique, resulting in an efficient and stable smart FRP composite with an areal capacitance of up to ≈182 µF cm−2 at 10 mV s−1. The composite exhibits exceptional cyclic stability, maintaining ≈90% capacitance after 1000 cycles. Moreover, the smart composite demonstrates joule heating, reaching from ∼24 to ∼27 °C within 120 s at 25 V.. Additionally, the smart composite displays strain sensitivity by altering electrical resistance with longitudinal strain, enabling structural health monitoring. These findings highlight the potential of smart composites for multifunctional applications and provide an important step toward realizing their actual real‐world applications

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Rh promoted In2O3 as a highly active catalyst for CO2 hydrogenation to methanol

Synthesis of methanol with high selectivity and productivity through hydrogenation of CO2 is highly attractive. This work uses a Rh doped In2O3 catalyst to achieve a high methanol productivity of 1.0 g(MeOH) h(-1) g(cat)(-1) while maintaining the intrinsic high selectivity of pure In2O3. Rh facilitated the dissociation of H-2 leading to creation of oxygen vacancies over the In2O3 surface. In addition, Rh atoms also participated in the activation of CO2 to produce formate species with a low activation barrier as evidenced by DFT calculation. Rh species were atomically dispersed in the In2O3 matrix and were stable during a long term reaction. Under reaction conditions, the surface Rh atoms were reduced and were stabilized by charge transfer from neighbouring In atoms. Our results show that incorporation of atomic Rh species in In2O3 can lead to high methanol productivity by creation of oxygen vacancies as well as Rh centred active sites for CO2 activation

Computational investigation on protein sequence of non-O157 VTEC for potentiality of vaccine production

Computational method can be used for investigation of the protein sequences for developing a vaccine against infections. In this present study, a protein derived from non-O157 Verotoxin-producing E. coli (VTEC) was identified as a potential vaccine candidate that can be used to evaluate their immunogenicity and protective capability against VTEC infections. Identification of potential B-cell epitopes for promising vaccine was carried out by evaluating the protein derived from non-O157 VTEC with the methods of beta turns, hydropathicity, surface accessibility and antigenicity. The methods were implemented in MATLAB. Our test results demonstrated that the VTEC-derived protein has plausible characteristics which provide significant insights for further investigations and will assist in finding potential drug targets/vaccine candidates