148 research outputs found
The landscape of potential health benefits of carotenoids as natural supportive therapeutics in protecting against Coronavirus infection
The Coronavirus Disease-2019 (COVID-19) pandemic urges researching possibilities for prevention and management of the effects of the virus. Carotenoids are natural phytochemicals of anti-oxidant, anti-inflammatory and immunomodulatory properties and may exert potential in aiding in combatting the pandemic. This review presents the direct and indirect evidence of the health benefits of carotenoids and derivatives based on in vitro and in vivo studies, human clinical trials and epidemiological studies and proposes possible mechanisms of action via which carotenoids may have the capacity to protect against COVID-19 effects. The current evidence provides a rationale for considering carotenoids as natural supportive nutrients via antioxidant activities, including scavenging lipid-soluble radicals, reducing hypoxia-associated superoxide by activating antioxidant enzymes, or suppressing enzymes that produce reactive oxygen species (ROS). Carotenoids may regulate COVID-19 induced over-production of pro-inflammatory cytokines, chemokines, pro-inflammatory enzymes and adhesion molecules by nuclear factor kappa B (NF-κB), renin-angiotensin-aldosterone system (RAS) and interleukins-6- Janus kinase-signal transducer and activator of transcription (IL-6-JAK/STAT) pathways and suppress the polarization of pro-inflammatory M1 macrophage. Moreover, carotenoids may modulate the peroxisome proliferator-activated receptors γ by acting as agonists to alleviate COVID-19 symptoms. They also may potentially block the cellular receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), human angiotensin-converting enzyme 2 (ACE2). These activities may reduce the severity of COVID-19 and flu-like diseases. Thus, carotenoid supplementation may aid in combatting the pandemic, as well as seasonal flu. However, further in vitro, in vivo and in particular long-term clinical trials in COVID-19 patients are needed to evaluate this hypothesis
Recovery of Lactobacillus casei strain Shirota (LcS) from faeces of healthy Singapore adults after intake of fermented milk
To validate survival of Lactobacillus casei strain Shirota (LcS) during passage through the gastrointestinal tract of healthy Singaporean young adults, 21 participants (18-25 years old) were asked to consume a 100 ml of fermented milk drink containing 1.0x10(8) cfu/ml of LcS daily for 14 days, and to maintain their dietary habit and life style. During and at the end of the ingestion period, both culture method (identity confirmed by ELISA) and 16s rRNA sequencing results revealed that viable LcS (7.27 and 7.64 log(10) cfu/g of faeces at the ingestion period Day 7 and Day 14, respectively) and Lactobacillus could be recovered from the faeces of all the subjects. The viable LcS count from male and female were comparable for each time point. Before consumption (baseline) and 14 days after cessation of consumption of the fermented milk, LcS was not detected in most of the subjects. In this study condition, the composition of the major gut microbiota (>0.1% in relative abundance of genus) and characteristics of defaecation such as stool consistency and frequency of defecation did not change throughout the study before and after ingestion of LcS. LcS was able to survive passage through the gastrointestinal tract of Singapore adults without sustainable colonisation, but the effect of LcS on microbiota modulation, stool consistency and frequency was not observed under this study condition
Mechanically-Controlled Binary Conductance Switching of a Single-Molecule Junction
Molecular-scale components are expected to be central to nanoscale electronic
devices. While molecular-scale switching has been reported in atomic quantum
point contacts, single-molecule junctions provide the additional flexibility of
tuning the on/off conductance states through molecular design. Thus far,
switching in single-molecule junctions has been attributed to changes in the
conformation or charge state of the molecule. Here, we demonstrate reversible
binary switching in a single-molecule junction by mechanical control of the
metal-molecule contact geometry. We show that 4,4'-bipyridine-gold
single-molecule junctions can be reversibly switched between two conductance
states through repeated junction elongation and compression. Using
first-principles calculations, we attribute the different measured conductance
states to distinct contact geometries at the flexible but stable N-Au bond:
conductance is low when the N-Au bond is perpendicular to the conducting
pi-system, and high otherwise. This switching mechanism, inherent to the
pyridine-gold link, could form the basis of a new class of
mechanically-activated single-molecule switches
A new computational method to split large biochemical networks into coherent subnets
<p>Abstract</p> <p>Background</p> <p>Compared to more general networks, biochemical networks have some special features: while generally sparse, there are a small number of highly connected metabolite nodes; and metabolite nodes can also be divided into two classes: internal nodes with associated mass balance constraints and external ones without. Based on these features, reclassifying selected internal nodes (separators) to external ones can be used to divide a large complex metabolic network into simpler subnetworks. Selection of separators based on node connectivity is commonly used but affords little detailed control and tends to produce excessive fragmentation.</p> <p>The method proposed here (Netsplitter) allows the user to control separator selection. It combines local connection degree partitioning with global connectivity derived from random walks on the network, to produce a more even distribution of subnetwork sizes. Partitioning is performed progressively and the interactive visual matrix presentation used allows the user considerable control over the process, while incorporating special strategies to maintain the network integrity and minimise the information loss due to partitioning.</p> <p>Results</p> <p>Partitioning of a genome scale network of 1348 metabolites and 1468 reactions for <it>Arabidopsis thaliana </it>encapsulates 66% of the network into 10 medium sized subnets. Applied to the flavonoid subnetwork extracted in this way, it is shown that Netsplitter separates this naturally into four subnets with recognisable functionality, namely synthesis of lignin precursors, flavonoids, coumarin and benzenoids. A quantitative quality measure called <it>efficacy </it>is constructed and shows that the new method gives improved partitioning for several metabolic networks, including bacterial, plant and mammal species.</p> <p>Conclusions</p> <p>For the examples studied the Netsplitter method is a considerable improvement on the performance of connection degree partitioning, giving a better balance of subnet sizes with the removal of fewer mass balance constraints. In addition, the user can interactively control which metabolite nodes are selected for cutting and when to stop further partitioning as the desired granularity has been reached. Finally, the blocking transformation at the heart of the procedure provides a powerful visual display of network structure that may be useful for its exploration independent of whether partitioning is required.</p
Observation of Quantum Interference in Molecular Charge Transport
As the dimensions of a conductor approach the nano-scale, quantum effects
will begin to dominate its behavior. This entails the exciting possibility of
controlling the conductance of a device by direct manipulation of the electron
wave function. Such control has been most clearly demonstrated in mesoscopic
semiconductor structures at low temperatures. Indeed, the Aharanov-Bohm effect,
conductance quantization and universal conductance fluctuations are direct
manifestations of the electron wave nature. However, an extension of this
concept to more practical emperatures has not been achieved so far. As
molecules are nano-scale objects with typical energy level spacings (~eV) much
larger than the thermal energy at 300 K (~25 meV), they are natural candidates
to enable such a break-through. Fascinating phenomena including giant
magnetoresistance, Kondo effects and conductance switching, have previously
been demonstrated at the molecular level. Here, we report direct evidence for
destructive quantum interference in charge transport through two-terminal
molecular junctions at room temperature. Furthermore, we show that the degree
of interference can be controlled by simple chemical modifications of the
molecule. Not only does this provide the experimental demonstration of a new
phenomenon in quantum charge transport, it also opens the road for a new type
of molecular devices based on chemical or electrostatic control of quantum
interference
Factors influencing success of clinical genome sequencing across a broad spectrum of disorders
To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges
Factors influencing success of clinical genome sequencing across a broad spectrum of disorders
To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges
Long non-coding RNAs display higher natural expression variation than protein-coding genes in healthy humans
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