Miracle-dz/UniFAR-FTUs huggingface dataset:
A Method of Evaluating NV centers Concentration by UV–Vis Transmittance Spectra

The ultraviolet-visible (UV-Vis) spectrum was not generally considered an available method for measuring the concentration of negatively charged nitrogen-vacancy (NV-, NV center). In this study, we propose the idea of evaluating the concentration of NV center by the slope of the UV-Vis spectrum. To establish this new method we synthesized diamonds with different NV center concentrations by the chemical vapor deposition (CVD) method. We then measured the zero-phonon line (ZPL) intensity of PL spectra at 637 nm and estimated the concentration of the NV centers as a baseline for comparison to our new UV-Vis method. The UV-Vis transmission spectra were then measured and transformed to relative absorption coefficient spectra. Slopes of the transformed UV-Vis spectra between 400 nm and 800 nm were calculated and compared with the ZPL intensities. The results show a strong positive correlation between the slopes of the absorption spectra and the ZPL intensities of PL spectra at 637 nm. Therefore, this paper demonstrates the feasibility of estimating the concentration of the NV centers from measuring the transmission UV-Vis spectrum.
Association between Haloperidol use and Risk of Rheumatoid Arthritis

Haloperidol is an anti-psychotic used for the treatment of schizophrenia or Tourette disorder. Here we report, by studying three large administrative health insurance databases, that haloperidol use is associated with a reduced risk of developing rheumatoid arthritis. A meta-analysis revealed a 31% reduced hazard of incident rheumatoid arthritis among individuals with schizophrenia or Tourette disorder treated with haloperidol compared to those treated with other anti-psychotic drugs. These findings suggest a potential benefit of haloperidol in rheumatoid arthritis and provide a rationale for randomized controlled trials to provide causal insights.
Influence of open-source virtual-reality based gaze training on navigation performance in Retinitis pigmentosa patients in a crossover randomized controlled trial

Motivation - People living with tunnel vision caused by Retinitis pigmentosa (RP) oftentimes face challenges navigating and avoiding obstacles due to a severely decreased Visual Field. Previous studies have shown that gaze training - guided tasks to encourage specific gaze behavior - help improve visual performance in patients with limited Visual Field. We propose a Virtual-Reality based, at-home gaze training - to the best of our knowledge the first of its kind - to increase effective eye movements and navigation performance of RP patients in a real-world obstacle course. Methods - A group of RP patients (n=8) participated in a study consisting of two 4-week-phases, both carried out by the same patient group in randomized order: In the 'training phase', participants carried out a Virtual-Reality gaze training for 30 minutes per day; In the 'control phase', no training occurred. Before and after each phase, participants were tasked to move through a randomized real-world obstacle course. Navigation performance in the obstacle course as well as eye-tracking data during the trials were evaluated. The study is registered at the German Clinical Trials Register (DRKS) with the ID DRKS00032628. Results - On average, the time required to move through the obstacle course decreased by 17.0% after the training phase (p<0.001), the number of collisions decreased by 50.0% (p<0.001) and the average visual area observed by participants increased by 4.41% (p<0.001). In comparison, after the control phase, the time required to move through the obstacle course was found to have decreased by 5.9% (p=0.003), collisions decreased by 10.4% (p=0.609) and the observed visual area increased by 2.06% (p=0.0835). Conclusion - The performance increase over the training phase significantly surpasses the natural learning effect found in the control phase, suggesting that Virtual-Reality based gaze training can improve real-world navigation performance and effective gaze movements of patients with RP. The training is available as work-in-progress open-source software.
Decoding biological age from face photographs using deep learning

Because humans age at different rates, a person's physical appearance may yield insights into their biological age and physiological health more reliably than their chronological age. In medicine, however, appearance is incorporated into medical judgments in a subjective and non-standardized fashion. In this study, we developed and validated FaceAge, a deep learning system to estimate biological age from easily obtainable and low-cost face photographs. FaceAge was trained on data from 58,851 healthy individuals, and clinical utility was evaluated on data from 6,196 patients with cancer diagnoses from two institutions in the United States and The Netherlands. To assess the prognostic relevance of FaceAge estimation, we performed Kaplan Meier survival analysis. To test a relevant clinical application of FaceAge, we assessed the performance of FaceAge in end-of-life patients with metastatic cancer who received palliative treatment by incorporating FaceAge into clinical prediction models. We found that, on average, cancer patients look older than their chronological age, and looking older is correlated with worse overall survival. FaceAge demonstrated significant independent prognostic performance in a range of cancer types and stages. We found that FaceAge can improve physicians' survival predictions in incurable patients receiving palliative treatments, highlighting the clinical utility of the algorithm to support end-of-life decision-making. FaceAge was also significantly associated with molecular mechanisms of senescence through gene analysis, while age was not. These findings may extend to diseases beyond cancer, motivating using deep learning algorithms to translate a patient's visual appearance into objective, quantitative, and clinically useful measures.
AI in medical imaging grand challenges: translation from competition to research benefit and patient care

Artificial intelligence (AI), in one form or another, has been a part of medical imaging for decades. The recent evolution of AI into approaches such as deep learning has dramatically accelerated the application of AI across a wide range of radiologic settings. Despite the promises of AI, developers and users of AI technology must be fully aware of its potential biases and pitfalls, and this knowledge must be incorporated throughout the AI system development pipeline that involves training, validation, and testing. Grand challenges offer an opportunity to advance the development of AI methods for targeted applications and provide a mechanism for both directing and facilitating the development of AI systems. In the process, a grand challenge centralizes (with the challenge organizers) the burden of providing a valid benchmark test set to assess performance and generalizability of participants’ models and the collection and curation of image metadata, clinical/demographic information, and the required reference standard. The most relevant grand challenges are those designed to maximize the open-science nature of the competition, with code and trained models deposited for future public access. The ultimate goal of AI grand challenges is to foster the translation of AI systems from competition to research benefit and patient care. Rather than reference the many medical imaging grand challenges that have been organized by groups such as MICCAI, RSNA, AAPM, and grand-challenge.org, this review assesses the role of grand challenges in promoting AI technologies for research advancement and for eventual clinical implementation, including their promises and limitations.
A Fine-Scale and Minimally Invasive Marking Method for Use with Conventional Tungsten Microelectrodes

Visual Abstract In neurophysiology, achieving precise correlation between physiological responses and anatomic structures is a significant challenge. Therefore, the accuracy of the electrode marking method is crucial. In this study, we describe a tungsten-deposition method, in which tungsten oxide is generated by applying biphasic current pulses to conventional tungsten electrodes. The electrical current used was 40–50 μA, which is similar to that used in electrical microstimulation experiments. The size of the markings ranged from 10 to 100 μm, corresponding to the size of the electrode tip, which is smaller than that of existing marking methods. Despite the small size of the markings, detection is easy as the marking appears in bright red under dark-field observation after Nissl staining. This marking technique resulted in low tissue damage and was maintained in vivo for at least two years. The feasibility of this method was tested in mouse and macaque brains.
Notochordal cells: A potential therapeutic option for intervertebral disc degeneration

Abstract Intervertebral disc degeneration (IDD) is a prevalent musculoskeletal degenerative disorder worldwide, and ~40% of chronic low back pain cases are associated with IDD. Although the pathogenesis of IDD remains unclear, the reduction in nucleus pulposus cells (NPCs) and degradation of the extracellular matrix (ECM) are critical factors contributing to IDD. Notochordal cells (NCs), derived from the notochord, which rapidly degrades after birth and is eventually replaced by NPCs, play a crucial role in maintaining ECM homeostasis and preventing NPCs apoptosis. Current treatments for IDD only provide symptomatic relief, while lacking the ability to inhibit or reverse its progression. However, NCs and their secretions possess anti‐inflammatory properties and promote NPCs proliferation, leading to ECM formation. Therefore, in recent years, NCs therapy targeting the underlying cause of IDD has emerged as a novel treatment strategy. This article provides a comprehensive review of the latest research progress on NCs for IDD, covering their biological characteristics, specific markers, possible mechanisms involved in IDD and therapeutic effects. It also highlights significant future directions in this field to facilitate further exploration of the pathogenesis of IDD and the development of new therapies based on NCs strategies.
Stronger evidence for genetic ancestry than environmental conditions in shaping the evolution of a complex signalling trait during biological invasion

Introductions of invasive species to new environments often result in rapid rates of trait evolution. While in some cases these evolutionary transitions are adaptive and driven by natural selection, they can also result from patterns of genetic and phenotypic variation associated with the invasion history. Here, we examined the brown anole (Anolis sagrei), a widespread invasive lizard for which genetic data have helped trace the sources of non‐native populations. We focused on the dewlap, a complex signalling trait known to be subject to multiple selective pressures. We measured dewlap reflectance, pattern and size in 30 non‐native populations across the southeastern United States. As well, we quantified environmental variables known to influence dewlap signal effectiveness, such as canopy openness. Further, we used genome‐wide data to estimate genetic ancestry, perform association mapping and test for signatures of selection. We found that among‐population variation in dewlap characteristics was best explained by genetic ancestry. This result was supported by genome‐wide association mapping, which identified several ancestry‐specific loci associated with dewlap traits. Despite the strong imprint of this aspect of the invasion history on dewlap variation, we also detected significant relationships between dewlap traits and local environmental conditions. However, we found limited evidence that dewlap‐associated genetic variants have been subject to selection. Our study emphasizes the importance of genetic ancestry and admixture in shaping phenotypes during biological invasion, while leaving the role of selection unresolved, likely due to the polygenic genetic architecture of dewlaps and selection acting on many genes of small effect.
Analyse de sensibilité et estimation de paramètres pour la modélisation hydrologique : potentiel et limitations des méthodes variationnelles

Comme tout evenement geophysique, la transformation de la pluie en debit dans les rivieres est caracterisee par la complexite des processus engages et par l'observation partielle, parfois tres limitee, de la reponse hydrologique du bassin versant ainsi que du forcage atmospherique auquel il est soumis. Il est donc essentiel de comprendre, d'analyser et de reduire les incertitudes inherentes a la modelisation hydrologique (analyse de sensibilite, assimilation de donnees, propagation d'incertitudes). Les methodes variationnelles sont tres largement employees au sein d'autres disciplines (ex. meteorologie, oceanographie .) confrontes aux memes challenges. Dans le cadre de ce travail, nous avons applique ce type de methodes a des modeles representant deux types de fonctionnement des hydrosystemes a l'echelle du bassin versant. Le potentiel et les limitations de l'approche variationnelle pour la modelisation hydrologique sont illustres avec un modele faisant du ruissellement par depassement de la capacite d'infiltration le processus preponderant pour la genese des ecoulements superficiels (MARINE) ainsi qu'avec un modele base sur le concept des zones contributives d'aire variable (TOPMODEL). L'analyse de sensibilite par linearisation ou basee sur la methode de l'etat adjoint permet une analyse locale mais approfondie de la relation entre les facteurs d'entree de la modelisation et les variables pronostiques du systeme. De plus, le gradient du critere d'ajustement aux observations calcule par le modele adjoint permet guider de maniere tres efficace un algorithme de descente avec contraintes de bornes pour l'estimation des parametres. Les resultats obtenus sont tres encourageants et plaident pour une utilisation accrue de l'approche variationnelle afin d'aborder les problematiques cles que sont l'analyse de la physique decrite dans les modeles hydrologiques et l'estimation des variables de controle (calibration des parametres et mise a jour de l'etat par assimilation de donnees).
Comprehensive modular analyses of scar subtypes illuminate underlying molecular mechanisms and potential therapeutic targets

Abstract Pathological scarring resulting from traumas and wounds, such as hypertrophic scars and keloids, pose significant aesthetic, functional and psychological challenges. This study provides a comprehensive transcriptomic analysis of these conditions, aiming to illuminate underlying molecular mechanisms and potential therapeutic targets. We employed a co‐expression and module analysis tool to identify significant gene clusters associated with distinct pathophysiological processes and mechanisms, notably lipid metabolism, sebum production, cellular energy metabolism and skin barrier function. This examination yielded critical insights into several skin conditions including folliculitis, skin fibrosis, fibrosarcoma and congenital ichthyosis. Particular attention was paid to Module Cluster (MCluster) 3, encompassing genes like BLK, TRPV1 and GABRD, all displaying high expression and potential implications in immune modulation. Preliminary immunohistochemistry validation supported these findings, showing elevated expression of these genes in non‐fibrotic samples rich in immune activity. The complex interplay of different cell types in scar formation, such as fibroblasts, myofibroblasts, keratinocytes and mast cells, was also explored, revealing promising therapeutic strategies. This study underscores the promise of targeted gene therapy for pathological scars, paving the way for more personalised therapeutic approaches. The results necessitate further research to fully ascertain the roles of these identified genes and pathways in skin disease pathogenesis and potential therapeutics. Nonetheless, our work forms a strong foundation for a new era of personalised medicine for patients suffering from pathological scarring.
Prevalence and correlates of frailty in older hypertensive outpatients according to different tools: the HYPER-FRAIL pilot study

Objectives: To date, few studies have investigated frailty in hypertensive individuals. This study aimed at identifying the prevalence of frailty in a sample of hypertensive older outpatients using six different identification tools. Clinical correlates of frailty and agreement between different frailty definitions were also investigated. Methods: The HYPER-FRAIL pilot study recruited hypertensive patients aged at least 75 years from two geriatric outpatient clinics of Careggi Hospital, Florence, Italy. Four frailty scales [Fried Frailty Phenotype, Frailty Index, Clinical Frailty Scale (CFS), Frailty Postal Score] and two physical performance tests [Short Physical Performance Battery (SPPB) and usual gait speed] were applied. The Cohen's kappa coefficient was calculated to assess agreement between measures. Multiple logistic regression was used to identify clinical features independently associated with frailty. Results: Among 121 participants (mean age 81, 60% women), frailty prevalence varied between 33 and 50% according to the tool used. Moderate agreement was observed between Fried Frailty Phenotype, Frailty Index and SPPB, and between Frailty Index and CFS. Agreement was minimal or weak between the remaining measures (K < 0.60). Use of walking aids and depressive symptoms were independently associated with frailty, regardless of the definition used. Frailty correlates also included dementia, disability and comorbidity burden, but not office and 24-h blood pressure values. Conclusion: Frailty is highly prevalent among older hypertensive outpatients, but agreement between different frailty tools was moderate-to-weak. Longitudinal studies are needed to assess the prognostic role of different frailty tools and their clinical utility in the choice of antihypertensive treatment.
P2Y12 receptor residues crucial for thrombosis regulation

Thrombosis, or the formation of blood clots, can lead to serious medical conditions such as stroke, heart attack, and deep vein thrombosis. The purinoreceptor P2Y12 plays a critical role in the thrombotic pathway and is targeted for therapy to prevent clot formation. However, it is essential to balance the regulation of thrombosis to avoid adverse situations. This study focuses on the P2Y12 receptor and aims to discern the protein residue network and differentiate residues based on their intramolecular interactions. The study utilized a statistical analysis to characterize the significant residues involved in ligand interaction, which helps to identify critical residues that are essential for the function of the receptor. A parametric analysis of interactions of residues in the intraprotein interaction was conducted, which revealed significant residue‐based contacts that facilitate protein interactions. By examining the interactions between residues, the mechanisms underlying protein interactions were studied and the importance of specific residues in facilitating these interactions was determined. This research provides important information on P2Y12, and the findings based on the network based significance of interacting residues may contribute to the development of new therapies that target the receptor to prevent clot formation while maintaining a balance in thrombosis regulation to avoid adverse outcomes. Ultimately, this study could lead to improved treatments for thrombotic disorders and better patient outcomes.
Association Between Child Maltreatment and Aggression in Chinese Early Adolescents: The Mediating Role of Irritability

Child maltreatment (CM) is a major global public health issue, and a strong association exists between CM and aggression. However, the underlying mechanism of this association has not been understood to date. The objective of this study was to explore the mediating role of irritability in the association between CM and aggression in Chinese early adolescents. A cross-sectional study was conducted using a self-report questionnaire to evaluate the levels of CM, aggression, and irritability in 5,724 middle school students from the Anhui Province, China. Structural equation modeling was used to test the hypothesis of the mediating effect of irritability on the relationship between CM and aggression. We further investigated gender differences in this association using multiple group analyses. CM was positively related to both irritability and aggression, and irritability was positively associated with aggression (p < .01). The mediating effects of irritability between CM and aggression were significant (β = .107, 95% confidence intervals [CI]: 0.077–0.133, p < .05). Males had a higher indirect effect size of the pathway from CM to aggression via irritability compared with females. Overall, irritability was a crucial mediator in the relationship between CM and aggression in Chinese adolescents, and males were more prone to engage in aggression compared with females through the pathway of irritability. Therefore, early irritability characteristics should be carefully monitored in adolescents, and they should be provided adequate support to acquire critical emotion regulation skills.
GRECCAR 14 – a multicentric, randomized, phase II–III study evaluating the tailored management of locally advanced rectal carcinoma after a favourable response to induction chemotherapy: Study protocol

Total neoadjuvant treatment (TNT) is becoming standard in patients with locally advanced rectal carcinoma (LARC). Preoperative chemoradiotherapy (CRT) has proven side effects on bowel and genitourinary function. An early tumoral response to induction chemotherapy demonstrates its high prognostic value. Tailored management could be used as an alternative to systematic CRT. The GRECCAR 14 trial will attempt to personalize treatment strategy according to the patient's early tumour response to intensive chemotherapy with the aim of achieving the best toxicity–efficiency ratio.
Detection Capability Enhanced Biosensor Antenna for Portable Electromagnetic Stroke Diagnostic Systems

Low-cost and portable electromagnetic (EM) stroke diagnostic systems are of great interest due to the increasing demand for early on-site detection or long-term bedside monitoring of stroke patients. Biosensor antennas serve as crucial hardware components for EM diagnostic systems. This article presents a detect capability enhanced biosensor antenna with a planar and compact configuration for portable EM stroke detection systems, overcoming the problem of limited detection capability in existing designs for this application. The proposed antenna is developed based on multiple dipoles, exhibiting multi-mode resonances and complementary interaction. In the frequency domain, the simulated and measured results with the presence of head phantoms show that this compact planar antenna achieves improved performance in both impedance bandwidth and near-field radiation inside the head tissues, which all contribute to enhancing its stroke detection capability in radar-based EM diagnosis. An array of 12 elements is numerically and experimentally tested in a lab-setting EM stroke diagnostic system to validate the detection capability of the proposed antenna. The reconstructed 2-D images inside the head demonstrate successful detection of different stroke-affected areas, even as small as 3 mm in radius, significantly smaller than those of reported relevant works under the same validation setting, confirming the enhanced detection capability of the proposed antenna.