Personalizing psychological care for chronic cancer-related fatigue:A case study on symptom dynamics

Approximately 25% of cancer patients suffer from chronic cancer-related fatigue (CCRF), which is a complex, multifactorial condition. While there are evidence-based interventions, it remains unclear what treatment works best for the individual patient. Psychological network models can offer a schematic representation of interrelations among fatigue and protective and perpetuating factors for the individual patient. We explored whether feedback based on these individual fatigue networks can help personalize psychological care for CCRF. A 34-year old woman with CCRF was referred to our mental healthcare institute for psycho-oncology. During the waitlist period, she filled out an experience sampling app for 101 days, including five daily assessments of fatigue, pain, mood, activity and fatigue coping. The interplay between items was visualized in network graphs at the moment-level and day-level, which were discussed with the patient. For example, acceptance of fatigue in the past three hours was associated with less hopelessness and less fatigue in the following moment. At the day-level, acceptance was also being associated with less fatigue, less hopelessness, a better mood, and more motivation to do things. The patient recognized these patterns and explained how unexpected waves of fatigue can make her feel hopeless. This started a dialogue on how cultivating acceptance could potentially help her handle the fatigue. The patient would discuss this with her therapist. Feedback based on individual fatigue networks can provide direct insight into how one copes with CCRF and subsequently offer directions for treatment. Further research is needed in order to implement this in clinical practice

Evaluation of fermented whole crop wheat and barley feeding on growth performance, nutrient digestibility, faecal volatile fatty acid emission, blood constituents, and faecal microbiota in growing pigs

This study was conducted to determine the effects of feeding diets with fermented whole crop wheat (FWW) and fermented whole crop barley (FWB) on growth performance, nutrient digestibility, blood constituents, faecal volatile fatty acid (VFA) emission and faecal microbiota in growing pigs. A total of 200 growing pigs were randomly allotted to five treatments with eight replicates per treatment and five pigs per replicate. Dietary treatments consisted of i) CON (basal diet), ii) 0.5% FWW (CON + 0.5% fermented whole crop wheat), iii) 1.0% FWW (CON + 1.0% fermented whole crop wheat), iv) 0.5% FWB (CON + 0.5% fermented whole crop barley), and v) 1.0% FWB (CON + 1.0% fermented whole crop barley). The digestibility of total dietary fibre was significantly higher in pigs fed FWW diets. The faecal emissions of VFA of pigs fed the fermented treatments was increased significantly compared with CON. Concentrations of cortisol and triglyceride in blood of pigs fed 1.0% FWW were significantly lower than pigs fed CON diets. The pigs fed 1.0% FWB diets had a significantly decreased level of total cholesterol in blood compared with CON. In conclusion, the current results indicated that diets supplemented with FWW and FWB could increase faecal VFA emission and reduce concentration of triglyceride and cortisol, while 0.5% and 1.0% FWW had no negative effects on growth performance, and could increase digestibility of dietary fibre in growing pigs.Keywords: Dietary fibre, faecal short-chain fatty acid emissions, fermented feed, serum parameter, swin

Motif Discovery through Predictive Modeling of Gene Regulation

We present MEDUSA, an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data. We use a modern large-margin machine learning approach, based on boosting, to enable feature selection from the high-dimensional search space of candidate binding sequences while avoiding overfitting. At each iteration of the algorithm, MEDUSA builds a motif model whose presence in the promoter region of a gene, coupled with activity of a regulator in an experiment, is predictive of differential expression. In this way, we learn motifs that are functional and predictive of regulatory response rather than motifs that are simply overrepresented in promoter sequences. Moreover, MEDUSA produces a model of the transcriptional control logic that can predict the expression of any gene in the organism, given the sequence of the promoter region of the target gene and the expression state of a set of known or putative transcription factors and signaling molecules. Each motif model is either a $k$-length sequence, a dimer, or a PSSM that is built by agglomerative probabilistic clustering of sequences with similar boosting loss. By applying MEDUSA to a set of environmental stress response expression data in yeast, we learn motifs whose ability to predict differential expression of target genes outperforms motifs from the TRANSFAC dataset and from a previously published candidate set of PSSMs. We also show that MEDUSA retrieves many experimentally confirmed binding sites associated with environmental stress response from the literature.Comment: RECOMB 200

A facile method for the selective decoration of graphene defects based on a galvanic displacement reaction

Inherent defects, such as grain boundaries (GBs), wrinkles and structural cracks, present on chemical vapor deposition (CVD)-grown graphene are inevitable because of the mechanism used for its synthesis. Because graphene defects are detrimental to electrical transport properties and degrade the performance of graphene-based devices, a defect-healing process is required. We report a simple and effective approach for enhancing the electrical properties of graphene by selective graphene-defect decoration with Pd nanoparticles (Pd NPs) using a wet-chemistry-based galvanic displacement reaction. According to the selective nucleation and growth behaviors of Pd NPs on graphene, several types of defects, such as GBs, wrinkles, graphene regions on Cu fatigue cracks and external edges of multiple graphene layers, were precisely confirmed via spherical aberration correction scanning transmission electron microscopy, field-emission scanning electron microscopy and atomic force microscopy imaging. The resultant Pd-NP-decorated graphene films showed improved sheet resistance. A transparent heater was fabricated using Pd-decorated graphene films and exhibited better heating performance than a heater fabricated using pristine graphene. This simple and novel approach promises the selective decoration of defects in CVD-grown graphene and further exploits the visualization of diverse defects on a graphene surface, which can be a versatile method for improving the properties of graphene.1881sciescopu

Editorial: Advancing our commitment to antiracist scholarship

Social work prides itself as a profession committed to improving the lives of people who are vulnerable, oppressed, and living in poverty. Achieving this mission requires candid conversations about racism as a social justice and public health issue and the role of social work in dismantling white supremacy and promoting racial justice. At its core, research on social work practice and policy should focus on examining how racism and inequality undermine the health, well-being, and social mobility of diverse and marginalized populations. We write this statement as a call to social work researchers to prioritize pursuits that will surface and motivate action to address the causes and consequences of racism. We also call on researchers to renew their commitment to scholarship that alleviates the suffering in Black, Indigenous, and other communities of color

Nucleation of a sodium droplet on C60

We investigate theoretically the progressive coating of C60 by several sodium atoms. Density functional calculations using a nonlocal functional are performed for NaC60 and Na2C60 in various configurations. These data are used to construct an empirical atomistic model in order to treat larger sizes in a statistical and dynamical context. Fluctuating charges are incorporated to account for charge transfer between sodium and carbon atoms. By performing systematic global optimization in the size range 1<=n<=30, we find that Na_nC60 is homogeneously coated at small sizes, and that a growing droplet is formed above n=>8. The separate effects of single ionization and thermalization are also considered, as well as the changes due to a strong external electric field. The present results are discussed in the light of various experimental data.Comment: 17 pages, 10 figure

Dimensional Crossover of Localisation and Delocalisation in a Quantum Hall Bar

The 2-- to 1--dimensional crossover of the localisation length of electrons confined to a disordered quantum wire of finite width $L_y$ is studied in a model of electrons moving in the potential of uncorrelated impurities. An analytical formula for the localisation length is derived, describing the dimensional crossover as function of width $L_y$, conductance $g$ and perpendicular magnetic field $B$ . On the basis of these results, the scaling analysis of the quantum Hall effect in high Landau levels, and the delocalisation transition in a quantum Hall wire are reconsidered.Comment: 12 pages, 7 figure

Next‐Generation Nanopore Sensors Based on Conductive Pulse Sensing for Enhanced Detection of Nanoparticles

Nanopore sensing has been successfully used to characterize biological molecules with single-molecule resolution based on the resistive pulse sensing approach. However, its use in nanoparticle characterization has been constrained by the need to tailor the nanopore aperture size to the size of the analyte, precluding the analysis of heterogeneous samples. Additionally, nanopore sensors often require the use of high salt concentrations to improve the signal-to-noise ratio, which further limits their ability to study a wide range of nanoparticles that are unstable at high ionic strength. Here, a new paradigm in nanopore research that takes advantage of a polymer electrolyte system to comprise a conductive pulse sensing approach is presented. A finite element model is developed to explain the conductive pulse signals observed and compare these results with experiments. This system enables the analytical characterization of heterogeneous nanoparticle mixtures at low ionic strength . Furthermore, the wide applicability of the method is demonstrated by characterizing metallic nanospheres of varied sizes, plasmonic nanostars with various degrees of branching, and protein-based spherical nucleic acids with different oligonucleotide loadings. This system will complement the toolbox of nanomaterials characterization techniques to enable real-time optimization workflow for engineering a wide range of nanomaterials