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OBJECTIVE: This research aims to extract human gait parameters from floor vibrations. The proposed approach provides an innovative methodology on occupant activity, contributing to a broader understanding of how human movements interact within their built environment. METHODS AND PROCEDURES: A multilevel probabilistic model was developed to estimate cadence and walking speed through the analysis of floor vibrations induced by walking. The model addresses challenges related to missing or incomplete information in the floor acceleration signals. Following the Bayesian Analysis Reporting Guidelines (BARG) for reproducibility, the model was evaluated through twenty-seven walking experiments, capturing floor vibration and data from Ambulatory Parkinson's Disease Monitoring (APDM) wearable sensors. The model was tested in a real-time implementation where ten individuals were recorded walking at their own selected pace. RESULTS: Using a rigorous combined decision criteria of 95% high posterior density (HPD) and the Range of Practical Equivalence (ROPE) following BARG, the results demonstrate satisfactory alignment between estimations and target values for practical purposes. Notably, with over 90% of the 95% HPD falling within the region of practical equivalence, there is a solid basis for accepting the estimations as probabilistically aligned with the estimations using the APDM sensors and video recordings. CONCLUSION: This research validates the probabilistic multilevel model in estimating cadence and walking speed by analyzing floor vibrations, demonstrating its satisfactory comparability with established technologies such as APDM sensors and video recordings. The close alignment between the estimations and target values emphasizes the approach's efficacy. The proposed model effectively tackles prevalent challenges associated with missing or incomplete data in real-world scenarios, enhancing the accuracy of gait parameter estimations derived from floor vibrations. CLINICAL IMPACT: Extracting gait parameters from floor vibrations could provide a non-intrusive and continuous means of monitoring an individual's gait, offering valuable insights into mobility and potential indicators of neurological conditions. The implications of this research extend to the development of advanced gait analysis tools, offering new perspectives on assessing and understanding walking patterns for improved diagnostics and personalized healthcare.Clinical and Translational Impact Statement: This manuscript introduces an innovative approach for unattended gait assessments with potentially significant implications for clinical decision-making. By utilizing floor vibrations to estimate cadence and walking speed, the technology can provide clinicians with valuable insights into their patients' mobility and functional abilities in real-life settings. The strategic installation of accelerometers beneath the flooring of homes or care facilities allows for uninterrupted daily activities during these assessments, reducing the reliance on specialized clinical environments. This technology enables continuous monitoring of gait patterns over time and has the potential for integration into healthcare platforms. Such integration can enhance remote monitoring, leading to timely interventions and personalized care plans, ultimately improving clinical outcomes. The probabilistic nature of our model enables uncertainty quantification in the estimated parameters, providing clinicians with a nuanced understanding of data reliability.
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Vibração , Velocidade de Caminhada , Humanos , Velocidade de Caminhada/fisiologia , Masculino , Teorema de Bayes , Pisos e Cobertura de Pisos , Feminino , Pessoa de Meia-Idade , Modelos Estatísticos , Marcha/fisiologia , Processamento de Sinais Assistido por Computador , Doença de Parkinson/fisiopatologia , Acelerometria/métodos , Acelerometria/instrumentação , Idoso , Caminhada/fisiologia , Adulto , Monitorização Ambulatorial/métodos , Monitorização Ambulatorial/instrumentaçãoRESUMO
PURPOSE: This study aimed to present the institutional experience and algorithm for performing biliary interventions in liver transplant patients using the modified Hutson loop access (MHLA) and the impact of percutaneous endoscopy via the MHLA on these procedures. METHODS: Over 13 years, 201 MHLA procedures were attempted on 52 patients (45 liver transplants; 24 living and 21 deceased donors) for diagnostic (e.g., cholangiography) and therapeutic (e.g., stent/drain insertion and cholangioplasty) purposes. The most common indications for MHLA were biliary strictures (60%) and bile leaks (23%). Percutaneous endoscopy was used to directly visualize the biliary-enteric anastomosis, diagnose pathology (e.g., ischemic cholangiopathy), and help in biliary hygiene (removing debris/casts/stones/stents) in 138/201 (69%) procedures. Technical success was defined as cannulating the biliary-enteric anastomosis and performing diagnostic/therapeutic procedure via the MHLA. RESULTS: The technical success rate was 95% (190/201). The failure rate among procedures performed with and without endoscopy was 2% (3/138) versus 13% (8/63) (P = 0.0024), and the need for new transhepatic access (to aid the procedure) was 12% (16/138) versus 30% (19/63) (P = 0.001). Despite endoscopy, failure in 2% of the cases resulted from inflamed/friable anastomosis (1/3) and high-grade stricture (2/3) obstructing retrograde cannulation of biliary-enteric anastomosis. Major adverse events (bowel perforation and injury) occurred in 1% of the procedures, with no procedure-related mortality. CONCLUSIONS: MHLA-based percutaneous biliary intervention is a safe and effective alternative to managing complications after liver transplant. Percutaneous endoscopy via the MHLA improves success rates and may reduce the need for new transhepatic access. Level of Evidence Level 4.
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Anastomose Cirúrgica , Transplante de Fígado , Humanos , Estudos Retrospectivos , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Adulto , Resultado do Tratamento , Complicações Pós-Operatórias , Algoritmos , Stents , Colangiografia/métodos , Procedimentos Cirúrgicos do Sistema Biliar/métodosRESUMO
Es bien sabido que la forma más común de reducir los efectos del trastorno por déficit de atención con hiperactividad ha sido históricamente a través de productos farmacológicos. Sin embargo, es irrefutable que la influencia del ejercicio físico ha evitado indeseables efectos secundarios y ha logrado cambios favorables significativos en los pacientes. Esta actividad física fue implementada básicamente de forma preventiva, principalmente bajo condiciones médicas, crónicas y discapacidades, también para contribuir a la esfera cognitiva y comportamental. El objetivo de este trabajo consistió en proponer un grupo de recomendaciones metodológicas en la clase de Educación Física para mejorar las condiciones de vida de niños con trastorno por déficit de atención con hiperactividad en la Unidad Educativa Fiscomisional Sagrado Corazón de Esmeraldas, Ecuador. Los métodos empíricos que se utilizaron fueron la observación científica, la encuesta aplicada a estudiantes y la entrevista dirigida a profesores; también se emplea, una vez implementadas estas recomendaciones, una encuesta a ambos componentes del proceso para obtener una valoración preliminar sobre el efecto de esta propuesta, debido a que resultó ser una ayuda metodológica de alto valor para preparar los profesores y estudiantes en sus influencias como orientador en el caso del profesor y como colectivo social académico en el caso del grupo de estudiantes.
É bem sabido que a forma mais comum de reduzir os efeitos do transtorno de déficit de atenção e hiperatividade tem sido historicamente por meio de produtos farmacológicos. Contudo, é irrefutável que a influência do exercício físico evitou efeitos colaterais indesejáveis e alcançou mudanças favoráveis significativas nos pacientes. Essa atividade física foi implementada basicamente de forma preventiva, principalmente em condições médicas, crônicas e deficiências, também para contribuir na esfera cognitiva e comportamental. O objetivo deste trabalho foi propor um conjunto de recomendações metodológicas nas aulas de Educação Física para melhorar as condições de vida de crianças com transtorno de déficit de atenção e hiperatividade na Unidade Educacional Fiscomisional Sagrado Corazón de Esmeraldas, Equador. Os métodos empíricos utilizados foram a observação científica, o inquérito aplicado aos alunos e a entrevista dirigida aos professores; Uma vez implementadas estas recomendações, recorre-se também a um levantamento de ambas as componentes do processo para obter uma avaliação preliminar do efeito desta proposta, porque se revelou uma ajuda metodológica de elevado valor para preparar professores e alunos nas suas influências. como conselheiro no caso do professor e como coletivo social acadêmico no caso do grupo de alunos.
It is well known that the most common way to reduce the effects of Inclusive methodological strategy for teaching - learning football in students with attention deficit hyperactivity disorder in the physical culture class (ADHD) has historically been through pharmacological products. However, it is irrefutable that the influence of physical exercise has avoided undesirable side effects and has achieved significant favorable changes in patients. This physical activity was basically implemented preventively, mainly under medical, chronic conditions and disabilities, also to contribute to the cognitive and behavioral sphere. The objective of this work consisted of proposing a group of methodological recommendations in the Physical Education class to improve the living conditions of children with ADHD in the Sagrado Corazón Fiscomisional Educational Unit of Esmeraldas, Ecuador. The empirical methods used were scientific observation, the survey applied to students and the interview directed to teachers. Once these recommendations were implemented, a survey of both components of the process was also used to obtain a preliminary assessment of the effect of this proposal, because it turned out to be a methodological aid of high value to prepare teachers and students in their influences as a counselor in the case of the teacher and as an academic social collective in the case of the group of students.
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The identification of genetic and chemical perturbations with similar impacts on cell morphology can elucidate compounds' mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here we create such a Resource dataset, CPJUMP1, in which each perturbed gene's product is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same protein encoded by a given gene, and we find that identifying matches between chemical and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling of cellular states, such as uncovering drug mode of action or probing functional genomics.
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Processamento de Imagem Assistida por Computador , Humanos , Processamento de Imagem Assistida por Computador/métodos , Microscopia/métodosRESUMO
Measuring the phenotypic effect of treatments on cells through imaging assays is an efficient and powerful way of studying cell biology, and requires computational methods for transforming images into quantitative data. Here, we present an improved strategy for learning representations of treatment effects from high-throughput imaging, following a causal interpretation. We use weakly supervised learning for modeling associations between images and treatments, and show that it encodes both confounding factors and phenotypic features in the learned representation. To facilitate their separation, we constructed a large training dataset with images from five different studies to maximize experimental diversity, following insights from our causal analysis. Training a model with this dataset successfully improves downstream performance, and produces a reusable convolutional network for image-based profiling, which we call Cell Painting CNN. We evaluated our strategy on three publicly available Cell Painting datasets, and observed that the Cell Painting CNN improves performance in downstream analysis up to 30% with respect to classical features, while also being more computationally efficient.
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Redes Neurais de ComputaçãoRESUMO
Background: Hispanic patients receive disproportionately fewer kidney transplants (KT) than non-Hispanic White (NHW) patients. In this observational study, we evaluated disparities in completing evaluation steps to KT among Hispanic patients. Methods: Using medical records of Hispanic and NHW patients initiating evaluation at 4 transplant centers from January 2011 to March 2020, we performed sequential Cox models to compare Hispanic versus NHW patients reaching each step of the evaluation process until receiving a KT. Results: Among all 5197 patients (Hispanic n = 2473; NHW n = 2724) initiating evaluation, Hispanic patients had 8% lower risk to be approved by the kidney pancreas (KP) committee than NHW patients (adjusted hazard ratio [aHR], 0.92; 95% confidence intervals (CI), 0.86-0.98; P = 0.015). Among 3492 patients approved by the KP committee, Hispanic patients had 13% lower risk to be waitlisted than NHW patients (aHR, 0.87; 95% CI, 0.81-0.94; P = 0.004). Among 3382 patients who were waitlisted, Hispanic patients had 11% lower risk than NHW patients to receive KT (aHR, 0.89; 95% CI, 0.81-0.97; P = 0.011). Among all patients initiating evaluation, Hispanic patients had a 16% lower risk than NHW patients to reach KT (aHR, 0.84; 95% CI, 0.76-0.92; P = 0.0002). Conclusions: Our study found that disproportionately fewer Hispanic patients were approved by the KP committee, were waitlisted, and received a KT, particularly a living donor kidney transplant, than NHW patients. Closer oversight of the evaluation process may help patients overcome challenges in access to KT.
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BACKGROUND: Surgical site drainage is important to prevent hematoma, seroma, and abscess formation. However, the placement of drain placement also predispose patients to several postoperative complications. The aim of this study is to clarify the risk-benefit profile of surgical drain placement. METHODS: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) Procedure-Targeted Databases were used to identify patients who underwent hepatectomy, pancreatectomy, nephrectomy, cystectomy, and prostatectomy. Patients who underwent each procedure were divided into 2 groups based on intraoperative drain placement. Propensity score-matched cohorts of these 2 groups were compared in terms of postoperative adverse events, readmission, reoperation, and length of stay. RESULTS: Hepatectomy patients with drains experienced organ space infections (P < .001), sepsis (P < .001), and readmission (P = .021) more often than patients without drains. Patients who underwent pancreatectomy and had drains placed experienced wound dehiscence less frequently than those without drains (P = .04). For hepatectomy, pancreatectomy, nephrectomy, and prostatectomy populations, patients with drains had longer lengths of stay (P < .05). Matched populations across all procedures did not differ in terms of reoperation rate. DISCUSSION: Prophylactic surgical drain placement may be associated with increased infectious complications and prolonged length of stay. Further studies are needed to elucidate the complete adverse event profile of surgical drains. Nonetheless, outcomes may be improved with better patient selection or advancements in drain technology.
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Drenagem , Hepatectomia , Masculino , Humanos , Hepatectomia/efeitos adversos , Reoperação , Complicações Pós-Operatórias/epidemiologia , Cirurgia de Second-LookRESUMO
Quantitative evaluation of image segmentation algorithms is crucial in the field of bioimage analysis. The most common assessment scores, however, are often misinterpreted and multiple definitions coexist with the same name. Here we present the ambiguities of evaluation metrics for segmentation algorithms and show how these misinterpretations can alter leaderboards of influential competitions. We also propose guidelines for how the currently existing problems could be tackled.
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Algoritmos , Processamento de Imagem Assistida por Computador , Processamento de Imagem Assistida por Computador/métodosRESUMO
Technological advances in high-throughput microscopy have facilitated the acquisition of cell images at a rapid pace, and data pipelines can now extract and process thousands of image-based features from microscopy images. These features represent valuable single-cell phenotypes that contain information about cell state and biological processes. The use of these features for biological discovery is known as image-based or morphological profiling. However, these raw features need processing before use and image-based profiling lacks scalable and reproducible open-source software. Inconsistent processing across studies makes it difficult to compare datasets and processing steps, further delaying the development of optimal pipelines, methods, and analyses. To address these issues, we present Pycytominer, an open-source software package with a vibrant community that establishes an image-based profiling standard. Pycytominer has a simple, user-friendly Application Programming Interface (API) that implements image-based profiling functions for processing high-dimensional morphological features extracted from microscopy images of cells. Establishing Pycytominer as a standard image-based profiling toolkit ensures consistent data processing pipelines with data provenance, therefore minimizing potential inconsistencies and enabling researchers to confidently derive accurate conclusions and discover novel insights from their data, thus driving progress in our field.
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Patients with mitochondrial disorders present with clinically diverse symptoms, largely driven by heterogeneous mutations in mitochondrial-encoded and nuclear-encoded mitochondrial genes. These mutations ultimately lead to complex biochemical disorders with a myriad of clinical manifestations, often accumulating during childhood on into adulthood, contributing to life-altering and sometimes fatal events. It is therefore important to diagnose and characterize the associated disorders for each mitochondrial mutation as early as possible since medical management might be able to improve the quality and longevity of life in mitochondrial disease patients. Here we identify a novel mitochondrial variant in a mitochondrial transfer RNA for histidine (mt-tRNA-his) [m.12148T>C], that is associated with the development of ocular, aural, neurological, renal, and muscular dysfunctions. We provide a detailed account of a family harboring this mutation, as well as the molecular underpinnings contributing to cellular and mitochondrial dysfunction. In conclusion, this investigation provides clinical, biochemical, and morphological evidence of the pathogenicity of m.12148T>C. We highlight the importance of multiple tissue testing and in vitro disease modeling in diagnosing mitochondrial disease.
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Accurately quantifying cellular morphology at scale could substantially empower existing single-cell approaches. However, measuring cell morphology remains an active field of research, which has inspired multiple computer vision algorithms over the years. Here, we show that DINO, a vision-transformer based, self-supervised algorithm, has a remarkable ability for learning rich representations of cellular morphology without manual annotations or any other type of supervision. We evaluate DINO on a wide variety of tasks across three publicly available imaging datasets of diverse specifications and biological focus. We find that DINO encodes meaningful features of cellular morphology at multiple scales, from subcellular and single-cell resolution, to multi-cellular and aggregated experimental groups. Importantly, DINO successfully uncovers a hierarchy of biological and technical factors of variation in imaging datasets. The results show that DINO can support the study of unknown biological variation, including single-cell heterogeneity and relationships between samples, making it an excellent tool for image-based biological discovery.
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This study aimed to establish factors associated with delayed surgery in patients with proximal femoral fracture and to assess patients' health-related quality of life (HRQoL) after surgery including all-cause 6-months mortality. This was a single-center, observational, prospective cohort study that included patients with a proximal femur fracture. We described patients' HRQoL measured by EuroQoL (EQ-5D-5L and EQ-VAS) questionnaire and perioperative complications (including mortality) 6 months after surgery. We included 163 patients with a mean age of 80.5 years, the majority were women and 76.1% reported falling from their own height. The mean time between hospital admission and surgery was 8.3 days (SD 4.9 days) and the mean hospital stay was 13.5 days (SD 10.4 days). After adjustment, the principal factor associated with delayed surgery was adjournment in surgery authorization (3.7 days). EQ-5D-5L index values and the VAS score at 1 month after surgery were 0.489 and 61.1, at 3 months were 0.613 and 65.8, and at 6 months 0.662 and 66.7 respectively. Mortality at 6 months of follow-up was 11% (18 patients). In conclusion, administrative authorization was the strongest associated factor with delayed time from hospital admission to surgery. HRQoL of patients with a proximal femoral fracture improved 6 months after surgery.Trial registration: NCT04217642.
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Fraturas Proximais do Fêmur , Humanos , Feminino , Masculino , Idoso de 80 Anos ou mais , Estudos Prospectivos , Qualidade de Vida , Acidentes por Quedas , HospitalizaçãoRESUMO
Methods for identifying human activity have a wide range of potential applications, including security, event time detection, intelligent building environments, and human health. Current methodologies typically rely on either wave propagation or structural dynamics principles. However, force-based methods, such as the probabilistic force estimation and event localization algorithm (PFEEL), offer advantages over wave propagation methods by avoiding challenges such as multi-path fading. PFEEL utilizes a probabilistic framework to estimate the force of impacts and the event locations in the calibration space, providing a measure of uncertainty in the estimations. This paper presents a new implementation of PFEEL using a data-driven model based on Gaussian process regression (GPR). The new approach was evaluated using experimental data collected on an aluminum plate impacted at eighty-one points, with a separation of five centimeters. The results are presented as an area of localization relative to the actual impact location at different probability levels. These results can aid analysts in determining the required precision for various implementations of PFEEL.
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Predicting assay results for compounds virtually using chemical structures and phenotypic profiles has the potential to reduce the time and resources of screens for drug discovery. Here, we evaluate the relative strength of three high-throughput data sources-chemical structures, imaging (Cell Painting), and gene-expression profiles (L1000)-to predict compound bioactivity using a historical collection of 16,170 compounds tested in 270 assays for a total of 585,439 readouts. All three data modalities can predict compound activity for 6-10% of assays, and in combination they predict 21% of assays with high accuracy, which is a 2 to 3 times higher success rate than using a single modality alone. In practice, the accuracy of predictors could be lower and still be useful, increasing the assays that can be predicted from 37% with chemical structures alone up to 64% when combined with phenotypic data. Our study shows that unbiased phenotypic profiling can be leveraged to enhance compound bioactivity prediction to accelerate the early stages of the drug-discovery process.
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Descoberta de Drogas , Transcriptoma , Descoberta de Drogas/métodos , Bioensaio , Ensaios de Triagem em Larga Escala/métodosRESUMO
PURPOSE: Depression and anxiety have been associated with lower urinary tract symptoms (LUTS) in several studies. In our population, the prevalence of LUTS is high, consequently, it is essential and an objective of this study, to determine the association between anxiety, depression, and LUTS in a large Hispanic population. METHODS: A sub-analysis of a cross-sectional population-based study to estimate LUTS prevalence in the Colombian population was performed (COBaLT study) (Plata et al. in Neurourol Urodyn 38:200-207, 2018). The Hospital Anxiety and Depression Scale (HADS) was used to evaluate mental health. Logistic regression was carried out to estimate the association of depression and anxiety with different LUTS. Variables that proved statistically significant (p < 0.05) were included in a multivariate model. RESULTS: A total of 1060 individuals were assessed. The prevalence of anxiety in women and men was 17.1% and 6.7%, respectively. Depression in women and men was 20.1% and 9.4%, respectively. An association was found between anxiety and overactive bladder (OAB) without urinary incontinence (OR = 3.7) and moderate or severe LUTS in men (OR = 3.8). In women, anxiety was associated with nocturia (OR = 4.2) and stress urinary incontinence (OR = 2.4). For depression, an association was found between sexual dysfunction (OR = 4.3) and moderate or severe LUTS (OR = 4.0) in men; while in women it was associated with stress urinary incontinence (OR = 2.3), the sensation of incomplete emptying (OR = 1.7) and decreased frequency of sexual activity (OR = 1.8). CONCLUSIONS: The associations found are consistent with other reports. It is essential to inquire about possible symptoms related to the mental sphere in the urology consultation to make appropriate referrals and subsequent management.
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Sintomas do Trato Urinário Inferior , Bexiga Urinária Hiperativa , Incontinência Urinária por Estresse , Masculino , Humanos , Feminino , Depressão/epidemiologia , Estudos Transversais , Sintomas do Trato Urinário Inferior/diagnóstico , Bexiga Urinária Hiperativa/epidemiologia , Bexiga Urinária Hiperativa/diagnóstico , Ansiedade/epidemiologia , PrevalênciaRESUMO
Hyperspectral satellite imagery provides highly-resolved spectral information for large areas and can provide vital information. However, only a few imaging spectrometer missions are currently in operation. Aiming to generate synthetic satellite-based hyperspectral imagery potentially covering any region, we explored the possibility of applying statistical learning, i.e. emulation. Based on the relationship of a Sentinel-2 (S2) scene and a hyperspectral HyPlant airborne image, this work demonstrates the possibility to emulate a hyperspectral S2-like image. We tested the role of different machine learning regression algorithms (MLRA) and varied the image-extracted training dataset size. We found superior performance of Neural Network (NN) as opposed to the other algorithms when trained with large datasets (up to 100'000 samples). The developed emulator was then applied to the L2A (bottom-of-atmosphere reflectance) S2 subset, and the obtained S2-like hyperspectral reflectance scene was evaluated. The validation of emulated against reference spectra demonstrated the potential of the technique. R 2 values between 0.75-0.9 and NRMSE between 2-5% across the full 402-2356 nm range were obtained. Moreover, epistemic uncertainty is obtained using the dropout technique, revealing spatial fidelity of the emulated scene. We obtained highest SD values of 0.05 (CV of 8%) in clouds and values below 0.01 (CV of 7%) in vegetation land covers. Finally, the emulator was applied to an entire S2 tile (5490x5490 pixels) to generate a hyperspectral reflectance datacube with the texture of S2 (60Gb, at a speed of 0.14sec/10000pixels). As the emulator can convert any S2 tile into a hyperspectral image, such scenes give perspectives how future satellite imaging spectroscopy will look like.
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A 62-year-old received orthotopic liver transplantation. Three weeks later, thrombotic microangiopathy developed. Testing revealed thrombotic thrombocytopenic purpura (TTP) characterized by low ADAMTS13 (A Disintegrin-like Metallopeptidase with ThromboSpondin type 1 motif 13) activity and no inhibitor of ADAMTS13 protein. Retrospective attainment of donor records revealed a TTP diagnosis, presumably hereditary TTP (hTTP), as an ADAMTS13 protein inhibitor was not mentioned. As the grafted liver does not produce ADAMTS13 protein, the recipient now functionally has hTTP and will likely need plasma transfusions indefinitely. While hTTP is extremely rare, it should be considered a contraindication to liver donation outside of exceptional circumstances. If a potential liver donor has TTP listed on medical history, attempts should be made to determine whether it is autoimmune or hereditary. An accurate medical history is critical as it is the only reliable way to identify hTTP, as outside of acute exacerbations of TTP, donors with hTTP can have normal laboratory values, including normal hemoglobin, platelets, and renal function.