Miracle-dz/UniFAR-FTUs huggingface dataset:
Use and Reliability of Exposure Assessment Methods in Occupational Case–Control Studies in the General Population: Past, Present, and Future

Introduction Retrospective occupational exposure assessment has been challenging in case-control studies in the general population. We aimed to review (i) trends of different assessment methods used in the last 40 years and (ii) evidence of reliability for various assessment methods. Methods Two separate literature reviews were conducted. We first reviewed all general population cancer case-control studies published from 1975 to 2016 to summarize the exposure assessment approach used. For the second review, we systematically reviewed evidence of reliability for all methods observed in the first review. Results Among the 299 studies included in the first review, the most frequently used assessment methods were self-report/assessment (n = 143 studies), case-by-case expert assessment (n = 139), and job-exposure matrices (JEMs; n = 82). Usage trends for these methods remained relatively stable throughout the last four decades. Other approaches, such as the application of algorithms linking questionnaire responses to expert-assigned exposure estimates and modelling of exposure with historical measurement data, appeared in 21 studies that were published after 2000. The second review retrieved 34 comparison studies examining methodological reliability. Overall, we observed slightly higher median kappa agreement between exposure estimates from different expert assessors (~0.6) than between expert estimates and exposure estimates from self-reports (~0.5) or JEMs (~0.4). However, reported reliability measures were highly variable for different methods and agents. Limited evidence also indicates newer methods, such as assessment using algorithms and measurement-calibrated quantitative JEMs, may be as reliable as traditional methods. Conclusion The majority of current research assesses exposures in the population with similar methods as studies did decades ago. Though there is evidence for the development of newer approaches, more concerted effort is needed to better adopt exposure assessment methods with more transparency, reliability, and efficiency.
Hierarchical Spatial Aggregation for Level-of-Detail Visualization of 3D Thematic Data

Thematic maps are a common tool to visualize semantic data with a spatial reference. Combining thematic data with a geometric representation of their natural reference frame aids the viewer’s ability in gaining an overview, as well as perceiving patterns with respect to location; however, as the amount of data for visualization continues to increase, problems such as information overload and visual clutter impede perception, requiring data aggregation and level-of-detail visualization techniques. While existing aggregation techniques for thematic data operate in a 2D reference frame (i.e., map), we present two aggregation techniques for 3D spatial and spatiotemporal data mapped onto virtual city models that hierarchically aggregate thematic data in real time during rendering to support on-the-fly and on-demand level-of-detail generation. An object-based technique performs aggregation based on scene-specific objects and their hierarchy to facilitate per-object analysis, while the scene-based technique aggregates data solely based on spatial locations, thus supporting visual analysis of data with arbitrary reference geometry. Both techniques can apply different aggregation functions (mean, minimum, and maximum) for ordinal, interval, and ratio-scaled data and can be easily extended with additional functions. Our implementation utilizes the programmable graphics pipeline and requires suitably encoded data, i.e., textures or vertex attributes. We demonstrate the application of both techniques using real-world datasets, including solar potential analyses and the propagation of pressure waves in a virtual city model.
The Combination of Functional and Structural MRI Is a Potential Screening Tool in Alzheimer’s Disease

Introduction: This study aimed to survey the discrimination power of parameters from cerebrospinal fluid (CSF) biomarkers, fluorodeoxyglucose uptake on PET (FDG-PET), structural magnetic resonance imaging (MRI), and functional MRI in high- and low-risk subjects or in converters and stable subjects of normal and mild cognitive impairment (MCI) statuses. Methods: We used baseline resting-state functional MRI (rfMRI) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset to analyze functional networks and recorded subjects’ characteristics and results of the CSF study, FDG-PET, and structural MRI from the ADNI website. All parameters were evaluated based on the between-group difference among normal (NC), MCI, and Alzheimer’s disease (AD) groups. The parameters other than CSF results were included to study the difference between high- and low-AD-risk subjects in NC or MCI groups, based on CSF results. On the basis of two-year follow-up conditions, all parameters were compared between stable subjects and converters in NC and MCI. Results: CSF biomarkers, FDG-PET, structural MRI, and functional MRI are all able to differentiate AD from MCI or NC but not between MCI and NC. As compared with low-AD-risk subjects, high-risk subjects present decreased FDG-PET in both MCI and NC groups but structural MRI change only in MCI status and rfMRI alteration only in NC status. As compared with stable subjects, converters have decreased FDG-PET, functional network changes, and structural changes in both MCI and NC groups. Conclusion: The combination of functional and structural MRI is a safer screening tool but with similar power as FDG-PET to reflect CSF change in the AD pathological process and to identify high-risk subjects and converters in NC and MCI.
The Biomedical Use of Silk: Past, Present, Future

Humans have long appreciated silk for its lustrous appeal and remarkable physical properties, yet as the mysteries of silk are unraveled, it becomes clear that this outstanding biopolymer is more than a high‐tech fiber. This progress report provides a critical but detailed insight into the biomedical use of silk. This journey begins with a historical perspective of silk and its uses, including the long‐standing desire to reverse engineer silk. Selected silk structure–function relationships are then examined to appreciate past and current silk challenges. From this, biocompatibility and biodegradation are reviewed with a specific focus of silk performance in humans. The current clinical uses of silk (e.g., sutures, surgical meshes, and fabrics) are discussed, as well as clinical trials (e.g., wound healing, tissue engineering) and emerging biomedical applications of silk across selected formats, such as silk solution, films, scaffolds, electrospun materials, hydrogels, and particles. The journey finishes with a look at the roadmap of next‐generation recombinant silks, especially the development pipeline of this new industry for clinical use.
Comparative mitogenomic analyses of Amazona parrots and Psittaciformes

Abstract Amazon parrots are long-lived birds with highly developed cognitive skills, including vocal learning. Several parrot mitogenomes have been sequenced, but important aspects of their organization and evolution are not fully understood or have limited experimental support. The main aim of the present study was to describe the mitogenome of the blue-fronted Amazon, Amazona aestiva, and compare it to other mitogenomes from the genus Amazona and the order Psittaciformes. We observed that mitogenomes are highly conserved among Amazon parrots, and a detailed analysis of their duplicated control regions revealed conserved blocks. Population level analyses indicated that the specimen analyzed here seems to be close to A. aestiva individuals from Bahia state. Evolutionary relationships of 41 Psittaciformes species and three outgroups were inferred by BEAST. All relationships were retrieved with high support.
Highly efficient genome editing via CRISPR–Cas9 in human pluripotent stem cells is achieved by transient BCL-XL overexpression

Abstract Genome editing of human induced pluripotent stem cells (iPSCs) is instrumental for functional genomics, disease modeling, and regenerative medicine. However, low editing efficiency has hampered the applications of CRISPR–Cas9 technology in creating knockin (KI) or knockout (KO) iPSC lines, which is largely due to massive cell death after electroporation with editing plasmids. Here, we report that the transient delivery of BCL-XL increases iPSC survival by ∼10-fold after plasmid transfection, leading to a 20- to 100-fold increase in homology-directed repair (HDR) KI efficiency and a 5-fold increase in non-homologous end joining (NHEJ) KO efficiency. Treatment with a BCL inhibitor ABT-263 further improves HDR efficiency by 70% and KO efficiency by 40%. The increased genome editing efficiency is attributed to higher expressions of Cas9 and sgRNA in surviving cells after electroporation. HDR or NHEJ efficiency reaches 95% with dual editing followed by selection of cells with HDR insertion of a selective gene. Moreover, KO efficiency of 100% can be achieved in a bulk population of cells with biallelic HDR KO followed by double selection, abrogating the necessity for single cell cloning. Taken together, these simple yet highly efficient editing strategies provide useful tools for applications ranging from manipulating human iPSC genomes to creating gene-modified animal models.
A shared medication scheme for community dwelling older patients with polypharmacy receiving home health care: role of the community pharmacist

ABSTRACT Background and objective: An accurate medication scheme may be a useful tool to improve medication safety in primary care. This study aimed to identify (1) pharmacists’ alterations to nurse medication schemes and (2) potential improvements to the contribution of the community pharmacist to a shared medication scheme within a multidisciplinary collaboration. Dosing frequency, potentially incorrect moments of intake, drug–drug interactions and medication complexity (quantified by the Medication Regimen Complexity Index, MRCI) were investigated. Setting and method: Observational study in community dwelling older patients (≥70 years) with polypharmacy receiving home health care (i.e. medications being prepared and/or administered by home care nurses). Home care nurses provided the community pharmacist with the original medication scheme (‘nurse medication scheme’), subsequently the community pharmacist generated a standardized ‘pharmacist medication scheme’ which was uploaded on an electronic health platform (Vitalink). The researcher recorded all pharmacists’ alterations and looked for possible additional improvements (‘researcher medication scheme’). Results: Pharmacists made 482 alterations to the nurse medication schemes of 31 patients. Most important alterations included adding indication (61%), generic or brand name (18%) and moment of intake (9%). Pharmacists did not reduce dosing frequency. MRCI scores (median [IQR]) significantly differed between pharmacist (38 [15]) and nurse medication schemes (32 [11]) (p < 0.001) and between nurse (32 [11]) and researcher medication schemes (40 [15]) (p < 0.001). Conclusion: Alterations made by the community pharmacists enable more complete and accurate medication schemes; however, there is room for improvement in optimizing the patient’s medication scheme in a multidisciplinary collaboration.
Antibiotics, Resistome and Resistance Mechanisms: A Bacterial Perspective

History of mankind is regarded as struggle against infectious diseases. Rather than observing the withering away of bacterial diseases, antibiotic resistance has emerged as a serious global health concern. Medium of antibiotic resistance in bacteria varies greatly and comprises of target protection, target substitution, antibiotic detoxification and block of intracellular antibiotic accumulation. Further aggravation to prevailing situation arose on observing bacteria gradually becoming resistant to different classes of antibiotics through acquisition of resistance genes from same and different genera of bacteria. Attributing bacteria with feature of better adaptability, dispersal of antibiotic resistance genes to minimize effects of antibiotics by various means including horizontal gene transfer (conjugation, transformation, and transduction), Mobile genetic elements (plasmids, transposons, insertion sequences, integrons, and integrative-conjugative elements) and bacterial toxin-antitoxin system led to speedy bloom of antibiotic resistance amongst bacteria. Proficiency of bacteria to obtain resistance genes generated an unpleasant situation; a grave, but a lot unacknowledged, feature of resistance gene transfer.
Modeling structure, stability and flexibility of double-stranded RNAs in salt solutions

Double-stranded (ds) RNAs play essential roles in many processes of cell metabolism. The knowledge of three-dimensional (3D) structure, stability and flexibility of dsRNAs in salt solutions is important for understanding their biological functions. In this work, we further developed our previously proposed coarse-grained model to predict 3D structure, stability and flexibility for dsRNAs in monovalent and divalent ion solutions through involving an implicit structure-based electrostatic potential. The model can make reliable predictions for 3D structures of extensive dsRNAs with/without bulge/internal loops from their sequences, and the involvement of the structure-based electrostatic potential and corresponding ion condition can improve the predictions on 3D structures of dsRNAs in ion solutions. Furthermore, the model can make good predictions on thermal stability for extensive dsRNAs over the wide range of monovalent/divalent ion concentrations, and our analyses show that thermally unfolding pathway of a dsRNA is generally dependent on its length as well as its sequence. In addition, the model was employed to examine the salt-dependent flexibility of a dsRNA helix and the calculated salt-dependent persistence lengths are in good accordance with experiments.
Mechanistic insights into high mobility group box-1 (HMGb1)-induced Toll-like receptor 4 (TLR4) dimer formation

Abstract Supplemental data for this article can be accessed here.High mobility group box-1 (HMGb1), an endogenous danger-associated molecular pattern protein (DAMP) whose extracellular release has been associated with sterile injury and various inflammatory diseases and conditions, has been shown to be a valuable clinical drug target. Elucidation of the specific interactions with the HMGb1 receptor, Toll-like receptor 4 (TLR4) and adaptor protein myeloid differentiation factor-2 (MD-2), will lead to more precisely targeted therapeutics. We sought to examine detailed interactions and dynamics of the HMGb1 A-box and B-box fragments, as well as the intact protein using in silico protein–protein docking (ZDOCK, ZRANK) and molecular dynamics (Schrödinger Desmond, New York, NY). Mutagenesis and SPR-binding studies allowed us to draw further conclusions regarding the details of the HMGb1–TLR4–MD2 interaction and shed light on the reasons for the opposing biological activities of HMGb1 A-box and B-box fragments. From our findings, we hypothesize that disulfide A-box fragment binds as an anchor toward the TLR4–MD-2 but does not facilitate the TLR4 dimer formation, thereby competing with the HMGb1-binding site and preventing HMGb1-induced signaling and downstream inflammation, whereas the pro-inflammatory B-box fragment retains the MD-2 active conformation and binds to both TLR4 proteins in the complex to aid TLR4 dimer formation, which activates the intracellular signaling for downstream inflammatory pathways and cytokine release. Communicated by Ramaswamy H. Sarma
Deep HMResNet Model for Human Activity-Aware Robotic Systems

Endowing the robotic systems with cognitive capabilities for recognizing daily activities of humans is an important challenge, which requires sophisticated and novel approaches. Most of the proposed approaches explore pattern recognition techniques which are generally based on hand-crafted features or learned features. In this paper, a novel Hierarchal Multichannel Deep Residual Network (HMResNet) model is proposed for robotic systems to recognize daily human activities in the ambient environments. The introduced model is comprised of multilevel fusion layers. The proposed Multichannel 1D Deep Residual Network model is, at the features level, combined with a Bottleneck MLP neural network to automatically extract robust features regardless of the hardware configuration and, at the decision level, is fully connected with an MLP neural network to recognize daily human activities. Empirical experiments on real-world datasets and an online demonstration are used for validating the proposed model. Results demonstrated that the proposed model outperforms the baseline models in daily human activity recognition.
Male Breast Cancer: Examining gender disparity in diagnosis and treatment

&NA; BACKGROUND: Although men make up a small percentage of those diagnosed with breast cancer, they are usually diagnosed at a later stage than women, increasing their chance of mortality. The reasons for this gender disparity require additional study. OBJECTIVES: This article examines current literature on male breast cancer, including reasons for the gender disparity and interventions that may help to address it. METHODS: An integrative review was conducted, and 12 studies were selected for inclusion. FINDINGS: Study consensus is that male breast cancer is an underresearched subject and that increased research efforts may improve outcomes. In addition, interventions could help to decrease the gender disparity in breast cancer detection.
Secretome of Undifferentiated Neural Progenitor Cells Induces Histological and Motor Improvements in a Rat Model of Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative movement disorder that results from the death of dopamine (DA) neurons. Over recent years, differentiated or undifferentiated neural stem cells (NSCs) transplantation has been widely used as a means of cell replacement therapy. However, compelling evidence has brought attention to the array of bioactive molecules produced by stem cells, defined as secretome. As described in the literature, other cell populations have a high‐neurotrophic activity, but little is known about NSCs. Moreover, the exploration of the stem cell secretome is only in its initial stages, particularly as applied to neurodegenerative diseases. Thus, we have characterized the secretome of human neural progenitor cells (hNPCs) through proteomic analysis and investigated its effects in a 6‐hydroxidopamine (6‐OHDA) rat model of PD in comparison with undifferentiated hNPCs transplantation. Results revealed that the injection of hNPCs secretome potentiated the histological recovery of DA neurons when compared to the untreated group 6‐OHDA and those transplanted with cells (hNPCs), thereby supporting the functional motor amelioration of 6‐OHDA PD animals. Additionally, hNPCs secretome proteomic characterization has revealed that these cells have the capacity to secrete a wide range of important molecules with neuroregulatory actions, which are most likely support the effects observed. Overall, we have concluded that the use of hNPCs secretome partially modulate DA neurons cell survival and ameliorate PD animals’ motor deficits, disclosing improved results when compared to cell transplantation approaches, indicating that the secretome itself could represent a route for new therapeutic options for PD regenerative medicine. Stem Cells Translational Medicine 2018;7:829–838
Neural Underpinnings of the Perception of Emotional States Derived From Biological Human Motion: A Review of Neuroimaging Research

Research on the perception of biological human motion shows that people are able to infer emotional states by observing body movements. This article reviews the methodology applied in fMRI research on the neural representation of such emotion perception. Specifically, we ask how different stimulus qualities of bodily expressions, individual emotional valence, and task instructions may affect the neural representation of an emotional scene. The review demonstrates the involvement of a variety of brain areas, thereby indicating how well the human brain is adjusted to navigate in multiple social situations. All stimulus categories (i.e., full-light body displays, point-light displays, and avatars) can induce an emotional percept and are associated with increased activation in an extensive neural network. This network seems to be organized around areas belonging to the so-called action observation network (PMC, IFG, and IPL) and the mentalizing network (TPJ, TP, dmPFC, and lOFC) as well as areas processing body form and motion (e.g., EBA, FBA, and pSTS). Furthermore, emotion-processing brain sites such as the amygdala and the hypothalamus seem to play an important role during the observation of emotional body expressions. Whereas most brain regions clearly display an increased response to emotional body movements in general, some structures respond selectively to negative valence. Moreover, neural activation seems to depend on task characteristics, indicating that certain structures are activated even when attention is shifted away from emotional body movements.
Characterizing Good Review Practices: A Survey Report Among Agencies of APEC Member Economies

As a first step in the implementation of the Asia-Pacific Economic Cooperation (APEC) Best Regulatory Practice Project, the Centre for Innovation in Regulatory Science conducted a gap analysis survey among regulatory agencies of 14 APEC member economies to assess the current use of good review practices (GRevP) to support transparent, consistent, predictable, and good-quality regulatory decision making. Although the majority of responding agencies have established some form of GRevP, most practices are currently evolving and are applied on an informal basis. Most agencies have developed standard operating procedures and guidelines and use a variety of training methods. The use of a common approach to regulatory review across jurisdictions would help build trust and confidence in each agency’s processes, setting the stage for the possibility of work sharing across resource-constrained agencies and bringing consistency and transparency to the review process.
Motor Control and Sensory Feedback Enhance Prosthesis Embodiment and Reduce Phantom Pain After Long-Term Hand Amputation

We quantified prosthesis embodiment and phantom pain reduction associated with motor control and sensory feedback from a prosthetic hand in one human with a long-term transradial amputation. Microelectrode arrays were implanted in the residual median and ulnar arm nerves and intramuscular electromyography recording leads were implanted in residual limb muscles to enable sensory feedback and motor control. Objective measures (proprioceptive drift) and subjective measures (survey answers) were used to assess prosthesis embodiment. For both measures, there was a significant level of embodiment of the physical prosthetic limb after open-loop motor control of the prosthesis (i.e., without sensory feedback), open-loop sensation from the prosthesis (i.e., without motor control), and closed-loop control of the prosthesis (i.e., motor control with sensory feedback). There was also a statistically significant reduction in reported phantom pain after experimental sessions that included open-loop nerve microstimulation, open-loop prosthesis motor control, or closed-loop prosthesis motor control. The closed-loop condition provided no additional significant improvements in phantom pain reduction or prosthesis embodiment relative to the open-loop sensory condition or the open-loop motor condition. This study represents the first long-term (14-month), systematic report of phantom pain reduction and prosthesis embodiment in a human amputee across a variety of prosthesis use cases.