Miracle-dz/UniFAR-FTUs huggingface dataset:
Perception of affect in unfamiliar musical chords

This study investigates the role of extrinsic and intrinsic predictors in the perception of affect in mostly unfamiliar musical chords from the Bohlen-Pierce microtonal tuning system. Extrinsic predictors are derived, in part, from long-term statistical regularities in music; for example, the prevalence of a chord in a corpus of music that is relevant to a participant. Conversely, intrinsic predictors make no use of long-term statistical regularities in music; for example, psychoacoustic features inherent in the music, such as roughness. Two types of affect were measured for each chord: pleasantness/unpleasantness and happiness/sadness. We modelled the data with a number of novel and well-established intrinsic predictors, namely roughness, harmonicity, spectral entropy and average pitch height; and a single extrinsic predictor, 12-TET Dissimilarity, which was estimated by the chord’s smallest distance to any 12-tone equally tempered chord. Musical sophistication was modelled as a potential moderator of the above predictors. Two experiments were conducted, each using slightly different tunings of the Bohlen-Pierce musical system: a just intonation version and an equal-tempered version. It was found that, across both tunings and across both affective responses, all the tested intrinsic features and 12-TET Dissimilarity have consistent influences in the expected direction. These results contrast with much current music perception research, which tends to assume the dominance of extrinsic over intrinsic predictors. This study highlights the importance of both intrinsic characteristics of the acoustic signal itself, as well as extrinsic factors, such as 12-TET Dissimilarity, on perception of affect in music.
Comparison of Three Measures of Shared Decision Making: SDM Process_4, CollaboRATE, and SURE Scales

Objective. If shared decision making (SDM) is to be part of quality assessment, it is necessary to have good measures of SDM. The purpose of this study is to compare the psychometric performance of 3 short patient-reported measures of SDM. Methods. Patients who met with a specialist to discuss possible surgery for hip or knee osteoarthritis (hips/knees), lumbar herniated disc, or lumbar spinal stenosis (backs) were surveyed shortly after the visit and again 6 months later. Some of the patients saw a patient decision aid (PDA) prior to the meeting. The 3 SDM measures were the SDM Process_4 (SDMP) survey, CollaboRATE, and SURE scale. The follow-up survey included measures of decision regret, satisfaction, and decision quality. Results. Patients in the sample (N = 649) had a mean age of 63.3 years, 51% were female, 60% were college educated, and there were more hip/knee patients than back patients (69% v. 31%). Forty-nine percent had surgery. For hips/knees, the SDMP and SURE scores were significantly associated with viewing all of the PDA compared with those who did not (P < 0.001), but not for CollaboRATE (P = 0.35). For backs, none of the scores were significantly associated with viewing all the PDA. All 3 scores were significantly associated with less regret and higher satisfaction (P < 0.001) for hips/knees. For backs, only SURE and CollaboRATE were significantly associated with less regret, and only SDMP was significantly associated with higher satisfaction. For hips/knees and backs, the SDMP and SURE scales were significantly associated with an informed patient-centered decision (P < 0.001), but this relationship was not significant for CollaboRATE (hips/knees: P = 0.24; backs: P = 0.25). Discussion. Each measure has some evidence of validity. SURE and SDMP better discriminate the use of PDAs and have higher decision quality.
Corona Isolation Method Matters: Capillary Electrophoresis Mass Spectrometry Based Comparison of Protein Corona Compositions Following On-Particle versus In-Solution or In-Gel Digestion

Increased understanding of the role of the nanomaterial protein corona in driving nanomaterial uptake into, and impacts on, cells and organisms, and the consequent need for characterization of the corona, has led to a flourishing of methods for isolation and analysis of the constituent proteins over the past decade. However, despite over 700 corona studies to date, very little is understood in terms of which methods provide the most precise and comprehensive characterization of the corona. With the increasing importance of the modeling of corona formation and its correlation with biological impacts, it is timely to properly characterize and validate the isolation approaches used to determine the protein corona. The current work introduces Capillary Electrophoresis with Electro Spray Ionization Mass Spectrometry (CESI-MS) as a novel method for protein corona characterizations and develops an on-particle tryptic digestion method, comparing peptide solubilization solutions and characterizing the recovery of proteins from the nanomaterial surface. The CESI-MS was compared to the gold standard nano-LC-MS for corona analysis and maintained a high degree of reproducibility, while increasing throughput by >3-fold. The on-particle digestion is compared to an in-solution digestion and an in-gel digestion of the protein corona. Interestingly, a range of different protein classes were found to be recovered to greater or lesser extents among the different methods. Apolipoproteins were detected at lower concentrations when a surfactant was used to solubilize peptides, whereas immunoglobulins in general have a high affinity for nanomaterials, and thus show lower recovery using on-particle digestion. The optimized on-particle digestion was validated using 6 nanomaterials and proved capable of recovering in excess of 97% of the protein corona. These are important factors to consider when designing corona studies and modeling corona formation and impacts, highlighting the significance of a comprehensive validation of nanomaterial corona analysis methods.
Impacts of obesity, maternal obesity and nicotinamide mononucleotide supplementation on sperm quality in mice

Male fertility and sperm quality are negatively impacted by obesity. Furthermore, recent evidence has shown that male offspring from obese rat mothers also have reduced sperm quality and fertility. Here, we extend work in this area by comparing the effects of both maternal obesity and offspring post-weaning diet-induced obesity, as well as their combination, on sperm quality in mice. We additionally tested whether administration of the NAD+-booster nicotinamide mononucleotide (NMN) can ameliorate the negative effects of obesity and maternal obesity on sperm quality. We previously showed that intraperitoneal (i.p.) injection of NMN can reduce the metabolic deficits induced by maternal obesity or post-weaning dietary obesity in mice. In this study, female mice were fed a high-fat diet (HFD) for 6 weeks until they were 18% heavier than a control diet group. Thereafter, HFD and control female mice were mated with control diet males, and male offspring were weaned into groups receiving control or HFD. At 30 weeks of age, mice received 500 mg/kg body weight NMN or vehicle PBS i.p. for 21 days. As expected, adiposity was increased by both maternal and post-weaning HFD but reduced by NMN supplementation. Post-weaning HFD reduced sperm count and motility, while maternal HFD increased offspring sperm DNA fragmentation and levels of aberrant sperm chromatin. There was no evidence that the combination of post-weaning and maternal HFD exacerbated the impacts in sperm quality suggesting that they impact spermatogenesis through different mechanisms. Surprisingly NMN reduced sperm count, vitality and increased sperm oxidative DNA damage, which was associated with increased NAD+ in testes. A subsequent experiment using oral NMN at 400 mg/kg body weight was not associated with reduced sperm viability, oxidative stress, mitochondrial dysfunction or increased NAD+ in testes, suggesting that the negative impacts on sperm could be dependent on dose or mode of administration.
Myocardial blood flow reserve assessed by positron emission tomography myocardial perfusion imaging identifies patients with a survival benefit from early revascularization.

AIMS Positron emission tomography (PET) myocardial perfusion imaging (MPI) can non-invasively measure myocardial blood flow reserve (MBFR). We aimed to examine whether MBFR identifies patients with a survival benefit after revascularization, helping to guide post-test management. METHODS AND RESULTS We examined all-cause mortality in 12 594 consecutive patients undergoing Rb82 rest/stress PET MPI from January 2010 to December 2016, after excluding those with cardiomyopathy, prior coronary artery bypass surgery (CABG), and missing MBFR. Myocardial blood flow reserve was calculated as the ratio of stress to rest absolute myocardial blood flow. A Cox model adjusted for patient and test characteristics, early revascularization (percutaneous coronary intervention or CABG ≤90 days of MPI), and the interaction between MBFR and early revascularization was developed to identify predictors of all-cause mortality. After a median follow-up of 3.2 years, 897 patients (7.1%) underwent early revascularization and 1699 patients (13.5%) died. Ischaemia was present in 4051 (32.3%) patients, with 1413 (11.2%) having ≥10% ischaemia. Mean MBFR was 2.0 ± 1.3, with MBFR <1.8 in 4836 (38.5%). After multivariable adjustment, every 0.1 unit decrease in MBFR was associated with 9% greater hazard of all-cause death (hazard ratio 1.09, 95% confidence interval 1.08-1.10; P < 0.001). There was a significant interaction between MBFR and early revascularization (P < 0.001); such that patients with MBFR ≤1.8 had a survival benefit with early revascularization, regardless of type of revascularization or level of ischaemia. CONCLUSION Myocardial blood flow reserve on PET MPI is associated with all-cause mortality and can identify patients who receive a survival benefit with early revascularization compared to medical therapy. This may be used to guide revascularization, and prospective validation is needed.
Segment-averaged LET concept and analytical calculation from microdosimetric quantities in proton radiation therapy.

PURPOSE This work introduces the concept of segment-averaged linear energy transfer (LET) as a new approach to average distributions of LET of proton beams based on a revisiting of microdosimetry theory. The concept of segment-averaged LET is then used to generate an analytical model from Monte Carlo simulations data to perform fast and accurate calculations of LET distributions for proton beams. METHODS AND MATERIAL The distribution of energy imparted by a proton beam into a representative biological structure or site is influenced by the distributions of (1) LET, (2) segment length, which is the section of the proton track in the site, and (3) energy straggling of the proton beam. The distribution of LET is thus generated by the LET of each component of the beam in the site. However, the situation when the LET of each single proton varies appreciably along its path in the site is not defined. Therefore, a new distribution can be obtained if the particle track segment is decomposed into smaller portions in which LET is roughly constant. We have called "segment distribution" of LET the one generated by the contribution of each portion. The average of that distribution is called segment-averaged LET. This quantity is obtained in the microdosimetry theory from the average and standard deviation of the distributions of energy imparted to the site, segment length and energy imparted per collision. All this information is calculated for protons of clinically relevant energies by means of Geant4-DNA microdosimetric simulations. Finally, a set of analytical functions is proposed for each one of the previous quantities. The presented model functions are fitted to data from Geant4-DNA simulations for monoenergetic beams from 100 keV to 100 MeV and for spherical sites of 1 μm, 5 μm and 10 μm in diameter. RESULTS The average differences along the considered energy range between calculations based on our analytical models and MC for segment-averaged dose-averaged restricted LET are -0.2 ± 0.7 keV/μm for the 1 μm case, 0.0 ± 0.9 keV/μm for the 5 μm case and -0.3 ± 1.1 keV/μm for the 10 μm case, respectively. All average differences are below the average standard deviation (1σ) of the MC calculations. CONCLUSIONS A new way of averaging LET for a proton beam is performed to incorporate the effects produced by the variation of stopping power of each individual proton along microscopic biological structures. An analytical model based on MC simulations allows for fast and accurate calculations of segment-averaged dose-averaged restricted LET for proton beams, which otherwise would need to be calculated from exhaustive MC simulations of clinical plans. This article is protected by copyright. All rights reserved.
Improving infant outcomes through implementation of a family integrated care bundle including a parent supporting mobile application

Objective The aim of the Integrated Family Delivered Care (IFDC) programme was to improve infant health outcomes and parent experience through education and competency-based training. Design In collaboration with veteran parents’ focus groups, we created an experienced co-designed care bundle including IFDC mobile application, which together with staff training programme comprised the IFDC programme. Infant outcomes were compared with retrospective controls in a prepost intervention analysis. Main outcome measures The primary outcome measure was the length of stay (LOS). Results Between April 2017 and May 2018, 89 families were recruited; 37 infants completed their entire care episode in our units with a minimum LOS >14 days. From a gestational age (GA) and birth weight-matched retrospective cohort, 57 control infants were selected. Data were also analysed for subgroup under 30 weeks GA (n=20). Infants in the IFDC group were discharged earlier: median corrected GA (36+0 (IQR 35+0–38+0) vs 37+1 (IQR 36+3–38+4) weeks; p=0.003), with shorter median LOS (41 (32–63) vs 55 (41–73) days; p=0.022). This was also evident in the subgroup <30 weeks GA (61 (39–82) vs 76 (68–84) days; p=0.035). Special care days were significantly lower in the IFDC group (30 (21–41) vs 40 (31–46); p=0.006). The subgroup of infants (<30 weeks) reached full suck feeding earlier (median: 47 (37–76) vs 72 (66–82) days; p=0.006). Conclusion This is the first reported study from a UK tertiary neonatal unit demonstrating significant benefits of family integrated care programme. The IFDC programme has significantly reduced LOS, resulted in the earlier achievement of full enteral and suck feeds.
Antidiabetic Medications and Mortality Risk in Individuals With Pancreatic Cancer–Related Diabetes and Postpancreatitis Diabetes: A Nationwide Cohort Study

OBJECTIVE There are no specific treatment guidelines for diabetes of the exocrine pancreas. High-quality studies are warranted to investigate whether the use of antidiabetic medications has survival benefit in individuals with diabetes of the exocrine pancreas. The objective was to determine the risk of mortality associated with the use of antidiabetic medications in individuals with pancreatic cancer–related diabetes (PCRD) and postpancreatitis diabetes mellitus (PPDM). RESEARCH DESIGN AND METHODS Nationwide pharmaceutical dispensing data (2006–2015) linked to hospital discharge data were used to identify 1,862 individuals with PCRD or PPDM. Multivariable Cox regression analysis was conducted, and the risk was expressed as hazard ratios and 95% CIs. A 6-month lag was used to minimize reverse causality. RESULTS In individuals with PCRD, ever users of metformin (adjusted hazard ratio 0.54; 95% CI 0.46–0.63) and ever users of insulin (adjusted hazard ratio 0.46; 95% CI 0.39–0.55) had significantly lower risks of mortality compared with never users of antidiabetic medications. These associations attenuated toward the null with the use of a 6-month lag. In individuals with PPDM, ever users of metformin had a significantly lower risk of mortality (adjusted hazard ratio 0.51; 95% CI 0.36–0.70), whereas ever-users of insulin did not have a significantly changed risk of mortality (adjusted hazard ratio 0.75; 95% CI 0.49–1.14) compared with never users of antidiabetic medications. The former association remained significant with the use of a 6-month lag. CONCLUSIONS Metformin promotes a survival benefit in individuals with PPDM but not PCRD. Reverse causality may play a role in the association between insulin use and mortality in PCRD.
High-Resolution Encoder–Decoder Networks for Low-Contrast Medical Image Segmentation

Automatic image segmentation is an essential step for many medical image analysis applications, include computer-aided radiation therapy, disease diagnosis, and treatment effect evaluation. One of the major challenges for this task is the blurry nature of medical images (e.g., CT, MR, and microscopic images), which can often result in low-contrast and vanishing boundaries. With the recent advances in convolutional neural networks, vast improvements have been made for image segmentation, mainly based on the skip-connection-linked encoder–decoder deep architectures. However, in many applications (with adjacent targets in blurry images), these models often fail to accurately locate complex boundaries and properly segment tiny isolated parts. In this paper, we aim to provide a method for blurry medical image segmentation and argue that skip connections are not enough to help accurately locate indistinct boundaries. Accordingly, we propose a novel high-resolution multi-scale encoder–decoder network (HMEDN), in which multi-scale dense connections are introduced for the encoder–decoder structure to finely exploit comprehensive semantic information. Besides skip connections, extra deeply supervised high-resolution pathways (comprised of densely connected dilated convolutions) are integrated to collect high-resolution semantic information for accurate boundary localization. These pathways are paired with a difficulty-guided cross-entropy loss function and a contour regression task to enhance the quality of boundary detection. The extensive experiments on a pelvic CT image dataset, a multi-modal brain tumor dataset, and a cell segmentation dataset show the effectiveness of our method for 2D/3D semantic segmentation and 2D instance segmentation, respectively. Our experimental results also show that besides increasing the network complexity, raising the resolution of semantic feature maps can largely affect the overall model performance. For different tasks, finding a balance between these two factors can further improve the performance of the corresponding network.
Marine Microbial Assemblages on Microplastics: Diversity, Adaptation, and Role in Degradation.

We have known for more than 45 years that microplastics in the ocean are carriers of microbially dominated assemblages. However, only recently has the role of microbial interactions with microplastics in marine ecosystems been investigated in detail. Research in this field has focused on three main areas: (a) the establishment of plastic-specific biofilms (the so-called plastisphere); (b) enrichment of pathogenic bacteria, particularly members of the genus Vibrio, coupled to a vector function of microplastics; and (c) the microbial degradation of microplastics in the marine environment. Nevertheless, the relationships between marine microorganisms and microplastics remain unclear. In this review, we deduce from the current literature, new comparative analyses, and considerations of microbial adaptation concerning plastic degradation that interactions between microorganisms and microplastic particles should have rather limited effects on the ocean ecosystems. The majority of microorganisms growing on microplastics seem to belong to opportunistic colonists that do not distinguish between natural and artificial surfaces. Thus, microplastics do not pose a higher risk than natural particles to higher life forms by potentially harboring pathogenic bacteria. On the other hand, microplastics in the ocean represent recalcitrant substances for microorganisms that are insufficient to support prokaryotic metabolism and will probably not be microbially degraded in any period of time relevant to human society. Because we cannot remove microplastics from the ocean, proactive action regarding research on plastic alternatives and strategies to prevent plastic entering the environment should be taken promptly. Expected final online publication date for the Annual Review of Marine Science Volume 12 is January 3, 2020. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Crosshatch nanofiber networks of tunable interfiber spacing induce plasticity in cell migration and cytoskeletal response

Biomechanical cues within tissue microenvironments are critical for maintaining homeostasis, and their disruption can contribute to malignant transformation and metastasis. Once transformed, metastatic cancer cells can migrate persistently by adapting (plasticity) to changes in the local fibrous extracellular matrix, and current strategies to recapitulate persistent migration rely exclusively on the use of aligned geometries. Here, the controlled interfiber spacing in suspended Crosshatch networks of nanofibers induces cells to exhibit plasticity in migratory behavior (persistent and random) and the associated cytoskeletal arrangement. At dense spacing (3 and 6 µm), unexpectedly, elongated cells migrate persistently (in 1 dimension) at high speeds in 3‐dimensional shapes with thick nuclei, and short focal adhesion cluster (FAC) lengths. With increased spacing (18 and 36 µm), cells attain 2‐dimensional morphologies, have flattened nuclei and longer FACs, and migrate randomly by rapidly detaching their trailing edges that strain the nuclei by ∼35%. At 54‐µm spacing, kite‐shaped cells become near stationary. Poorly developed filamentous actin stress fibers are found only in cells on 3‐µm networks. Gene‐expression profiling shows a decrease in transcriptional potential and a differential up‐regulation of metabolic pathways. The consistency in observed phenotypes across cell lines supports using this platform to dissect hallmarks of plasticity in migration in vitro. —Jana, A. , Nookaew, I. , Singh, J., Behkam, B. , Franco, A. T. , Nain, A. S. Crosshatch nanofiber networks of tunable interfiber spacing induce plasticity in cell migration and cytoskeletal response. FA8EB J. 33, 10618–10632 (2019). www.fasebj. org