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1.
Ann Am Thorac Soc ; 20(2): 161-195, 2023 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-36723475

RESUMO

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.


Assuntos
Pneumopatias , Enfisema Pulmonar , Humanos , Benchmarking , Pulmão/diagnóstico por imagem , Pneumopatias/diagnóstico por imagem , Respiração , Imageamento por Ressonância Magnética/métodos
2.
Zhongguo Zhong Yao Za Zhi ; 48(2): 382-389, 2023 Jan.
Artigo em Chinês | MEDLINE | ID: mdl-36725228

RESUMO

We prepared 15 batches of Kaixin Powder benchmark samples with the decoction pieces of different batches. Further, we established the specific chromatograms and index component content determination method of Kaixin Powder benchmark samples and analyzed the peaks and similarity of the chromatograms. With sibiricose A5, sibiricose A6, polygalaxanthone Ⅲ, 3,6'-disinapoyl sucrose, ginsenoside Rb_1, ß-asarone, α-asarone, and dehydropachymic acid as index components, the index component content determination method was established and 70%-130% of the mean content of each component was set as the range. The chromatograms of 15 batches of Kaixin Powder benchmark samples had a total of 22 characteristic peaks, among which 8 peaks were identified, which represented sibiricose A5, sibiricose A6, polygalaxanthone Ⅲ, 3,6'-disinapoyl sucrose, ginsenoside Rb_1, ß-asarone, α-asarone, and dehydropachymic acid, respectively. The chromatograms shared the similarity of 0.992-0.999. The 15 batches of benchmark samples had sibiricose A5 of 0.34-0.55 mg·g~(-1), sibiricose A6 of 0.43-0.57 mg·g~(-1), polygalaxanthone Ⅲ of 0.12-0.19 mg·g~(-1), 3,6'-disinapoyl sucrose of 1.08-1.78 mg·g~(-1), ginsenoside Rb_1 of 0.33-0.62 mg·g~(-1), ß-asarone of 2.34-3.72 mg·g~(-1), α-asarone of 0.11-0.22 mg·g~(-1), and dehydropachymic acid of 0.053-0.079 mg·g~(-1). This study established the specific chromatograms and index component content determination method of Kaixin Powder benchmark samples, and the method was simple, feasible, reproducible, and stable. This study provides a scientific basis for further research on the key chemical properties of the benchmark samples and preparations of Kaixin Powder.


Assuntos
Medicamentos de Ervas Chinesas , Ginsenosídeos , Pós , Benchmarking , Medicamentos de Ervas Chinesas/química , Sacarose , Cromatografia Líquida de Alta Pressão/métodos
3.
Indian J Ophthalmol ; 71(2): 385-395, 2023 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-36727324

RESUMO

Purpose: The primary objective of the study was to assess the macular retinal vessel density, subfoveal choroidal thickness, and retinal layer metrics by optical coherence tomography angiography (OCTA), enhanced-depth imaging optical coherence tomography (EDI-OCT), and spectral domain optical coherence tomography (SD-OCT), respectively, in recovered COVID-19 patients and its comparison with the same in control subjects. The secondary objective was to evaluate differences in OCTA parameters in relation with the severity of COVID-19 disease and administration of corticosteroids. Methods: A case-control study was performed that included patients who had recovered from COVID-19 and age-matched healthy controls. Complete ocular examination including OCTA, SD-OCT, and EDI-OCT were performed three months following the diagnosis. Results: Three hundred sixty eyes of 180 subjects were enrolled between the two groups. A decreased mean foveal avascular zone area in both superficial capillary plexuses (P = 0.03) and deep capillary plexuses (P < 0.01), reduced average ganglion cell layer-inner plexiform layer thickness (P = 0.04), and increased subfoveal choroidal thickness (P < 0.001) were observed among cases in comparison to the control group. A significant correlation was found between sectoral macular vessel density in relation to disease severity and a decrease in vessel density with greater severity of the disease. Conclusion: OCTA detected retinal microvascular alterations following SARS-CoV-2 infection in subjects with the absence of any clinical ocular manifestation or systemic thrombotic events. These parameters could be used to help identify patients with a higher incidence of systemic thromboembolism on longer follow-ups and identify the impact of corticosteroids on retinal architecture.


Assuntos
COVID-19 , Tomografia de Coerência Óptica , Humanos , Tomografia de Coerência Óptica/métodos , Angiofluoresceinografia/métodos , Estudos de Casos e Controles , Fóvea Central/irrigação sanguínea , Benchmarking , SARS-CoV-2 , Vasos Retinianos/diagnóstico por imagem
4.
Ann Glob Health ; 89(1): 1, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-36721434

RESUMO

Background: Most Emergency Departments (EDs) in low- and middle-income countries (LMICs), particularly in Pakistan, are staffed by physicians not formally trained in Emergency Medicine (EM). As of January 2022, there were only 13 residency training programs in EM throughout all of Pakistan. Therefore, an intermediate solution-a one-year training program in EM-was developed to build capacity. Objective: To determine the impact of a novel training program in EM on clinical metrics and outcomes. Methods: The first cohort of a novel, one-year training program-the Certification Program in Emergency Medicine (CPEM)-completed the program in June 2019. The program consisted of two arms: CPEM-Clinical (CPEM-C), which included physicians from the Indus Hospital and Health Network (IHHN) ED; and CPEM-Didactic (CPEM-D), which included physicians from EDs across Karachi. Both groups participated in weekly conferences, such as didactics, small group discussions, workshops, and journal clubs. CPEM-C learners also received clinical mentorship from local and international faculty. Mortality, length of stay (LOS), and time-to-evaluation, as well as metrics in four key areas-patients at risk for cardiovascular disease/acute coronary syndrome, sepsis, respiratory illness, and intra-abdominal trauma-were assessed before and after the initial cohort at IHHN and compared with other groups in IHHN. Findings and Conclusions: More than 125,000 patients were seen from July to December 2017 (pre-CPEM) and July to December 2019 (post-CPEM). Overall, there were significant improvements in all clinical metrics and outcomes, with the exception of LOS and time-to-evaluation, and a trend toward improved mortality. In comparing CPEM graduates to other groups in IHHN ED, most metrics and outcomes significantly improved or trended toward improvement, including mortality. Implementation of a medium-duration, intensive EM training program can help improve patient care and the development of EM as a new specialty in lower-resource settings.


Assuntos
Traumatismos Abdominais , Medicina de Emergência , Humanos , Paquistão , Benchmarking
5.
BMC Bioinformatics ; 24(1): 33, 2023 Jan 31.
Artigo em Inglês | MEDLINE | ID: mdl-36721080

RESUMO

BACKGROUND: Whole genome bisulfite sequencing (WGBS), possesses the aptitude to dissect methylation status at the nucleotide-level resolution of 5-methylcytosine (5-mC) on a genome-wide scale. It is a powerful technique for epigenome in various cell types, and tissues. As a recently established next-generation sequencing (NGS) platform, GenoLab M is a promising alternative platform. However, its comprehensive evaluation for WGBS has not been reported. We sequenced two bisulfite-converted mammal DNA in this research using our GenoLab M and NovaSeq 6000, respectively. Then, we systematically compared those data via four widely used WGBS tools (BSMAP, Bismark, BatMeth2, BS-Seeker2) and a new bisulfite-seq tool (BSBolt). We interrogated their computational time, genome depth and coverage, and evaluated their percentage of methylated Cs. RESULT: Here, benchmarking a combination of pre- and post-processing methods, we found that trimming improved the performance of mapping efficiency in eight datasets. The data from two platforms uncovered ~ 80% of CpG sites genome-wide in the human cell line. Those data sequenced by GenoLab M achieved a far lower proportion of duplicates (~ 5.5%). Among pipelines, BSMAP provided an intriguing representation of 5-mC distribution at CpG sites with 5-mC levels > ~ 78% in datasets from human cell lines, especially in the GenoLab M. BSMAP performed more advantages in running time, uniquely mapped reads percentages, genomic coverage, and quantitative accuracy. Finally, compared with the previous methylation pattern of human cell line and mouse tissue, we confirmed that the data from GenoLab M performed similar consistency and accuracy in methylation levels of CpG sites with that from NovaSeq 6000. CONCLUSION: Together we confirmed that GenoLab M was a qualified NGS platform for WGBS with high performance. Our results showed that BSMAP was the suitable pipeline that allowed for WGBS studies on the GenoLab M platform.


Assuntos
Benchmarking , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Animais , Camundongos , Sequenciamento Completo do Genoma , Mamíferos/genética
6.
Global Health ; 19(1): 7, 2023 Jan 31.
Artigo em Inglês | MEDLINE | ID: mdl-36721202

RESUMO

BACKGROUND: Those responding to humanitarian crises have an ethical imperative to respond most where the need is greatest. Metrics are used to estimate the severity of a given crisis. The INFORM Severity Index, one such metric, has become widely used to guide policy makers in humanitarian response decision making. The index, however, has not undergone critical statistical review. If imprecise or incorrect, the quality of decision making for humanitarian response will be affected. This analysis asks, how precise and how well does this index reflect the severity of conditions for people affected by disaster or war? RESULTS: The INFORM Severity Index is calculated from 35 publicly available indicators, which conceptually reflect the severity of each crisis. We used 172 unique global crises from the INFORM Severity Index database that occurred January 1 to November 30, 2019 or were ongoing by this date. We applied exploratory factor analysis (EFA) to determine common factors within the dataset. We then applied a second-order confirmatory factor analysis (CFA) to predict crisis severity as a latent construct. Model fit was assessed via chi-square goodness-of-fit statistic, Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA). The EFA models suggested a 3- or 4- factor solution, with 46 and 53% variance explained in each model, respectively. The final CFA was parsimonious, containing three factors comprised of 11 indicators, with reasonable model fit (Chi-squared = 107, with 40 degrees of freedom, CFI = 0.94, TLI = 0.92, RMSEA = 0.10). In the second-order CFA, the magnitude of standardized factor-loading on the 'societal governance' latent construct had the strongest association with the latent construct of 'crisis severity' (0.73), followed by the 'humanitarian access/safety' construct (0.56). CONCLUSIONS: A metric of crisis-severity is a critical step towards improving humanitarian response, but only when it reflects real life conditions. Our work is a first step in refining an existing framework to better quantify crisis severity.


Assuntos
Pessoal Administrativo , Desastres , Humanos , Benchmarking , Bases de Dados Factuais , Nível de Saúde
7.
Artigo em Inglês | MEDLINE | ID: mdl-36673713

RESUMO

Facebook demotes "engagement bait" content that makes people interact. As a result of this sanctioning, public health content can reach fewer Facebook users. This study aims to determine the negative effect of engagement bait and find alternative techniques. In a three-year period, 791 smoking cessation support content was included (n = 791). The Facebook posts were classified into "engagement bait", "alternative techniques" and control groups. Facebook metrics were compared between the study and control groups. The reach of Facebook page fans was significantly lower in the engagement bait group compared to the control group. On the other hand, the alternative techniques had a significantly lower rate of negative Facebook interactions, as well as significantly higher click rates compared to the control group. This is the first study to reveal the sanctioning of engagement bait on smoking cessation support Facebook posts. "Engagement bait" content has a lower ranking on the Facebook Fans' Newsfeed page. Nevertheless, alternative techniques can circumvent the restrictions on engagement bait. At the same time, alternative techniques can stimulate the click rate and inhibit the rate of negative interactions.


Assuntos
Abandono do Hábito de Fumar , Mídias Sociais , Humanos , Abandono do Hábito de Fumar/métodos , Saúde Pública , Benchmarking , Grupos Controle
8.
J Neuroeng Rehabil ; 20(1): 14, 2023 Jan 27.
Artigo em Inglês | MEDLINE | ID: mdl-36703214

RESUMO

BACKGROUND: Gait training at fast speeds is recommended to reduce walking activity limitations post-stroke. Fast walking may also reduce gait kinematic impairments post-stroke. However, it is unknown if differences in gait kinematics between people post-stroke and neurotypical adults decrease when walking at faster speeds. OBJECTIVE: To determine the effect of faster walking speeds on gait kinematics post-stroke relative to neurotypical adults walking at similar speeds. METHODS: We performed a secondary analysis with data from 28 people post-stroke and 50 neurotypical adults treadmill walking at multiple speeds. We evaluated the effects of speed and group on individual spatiotemporal and kinematic metrics and performed k-means clustering with all metrics at self-selected and fast speeds. RESULTS: People post-stroke decreased step length asymmetry and trailing limb angle impairment, reducing between-group differences at fast speeds. Speed-dependent changes in peak swing knee flexion, hip hiking, and temporal asymmetries exaggerated between-group differences. Our clustering analyses revealed two clusters. One represented neurotypical gait behavior, composed of neurotypical and post-stroke participants. The other characterized stroke gait behavior-comprised entirely of participants post-stroke with smaller lower extremity Fugl-Meyer scores than the post-stroke participants in the neurotypical gait behavior cluster. Cluster composition was largely consistent at both speeds, and the distance between clusters increased at fast speeds. CONCLUSIONS: The biomechanical effect of fast walking post-stroke varied across individual gait metrics. For participants within the stroke gait behavior cluster, walking faster led to an overall gait pattern more different than neurotypical adults compared to the self-selected speed. This suggests that to potentiate the biomechanical benefits of walking at faster speeds and improve the overall gait pattern post-stroke, gait metrics with smaller speed-dependent changes may need to be specifically targeted within the context of fast walking.


Assuntos
Benchmarking , Acidente Vascular Cerebral , Humanos , Adulto , Marcha , Caminhada , Velocidade de Caminhada , Extremidade Inferior , Acidente Vascular Cerebral/complicações , Fenômenos Biomecânicos
9.
Comput Biol Med ; 153: 106453, 2023 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-36603434

RESUMO

Deep learning based medical image segmentation methods have been widely used for thyroid gland segmentation from ultrasound images, which is of great importance for the diagnosis of thyroid disease since it can provide various valuable sonography features. However, existing thyroid gland segmentation models suffer from: (1) low-level features that are significant in depicting thyroid boundaries are gradually lost during the feature encoding process, (2) contextual features reflecting the changes of difference between thyroid and other anatomies in the ultrasound diagnosis process are either omitted by 2D convolutions or weakly represented by 3D convolutions due to high redundancy. In this work, we propose a novel hybrid transformer UNet (H-TUNet) to segment thyroid glands in ultrasound sequences, which consists of two parts: (1) a 2D Transformer UNet is proposed by utilizing a designed multi-scale cross-attention transformer (MSCAT) module on every skipped connection of the UNet, so that the low-level features from different encoding layers are integrated and refined according to the high-level features in the decoding scheme, leading to better representation of differences between anatomies in one ultrasound frame; (2) a 3D Transformer UNet is proposed by applying a 3D self-attention transformer (SAT) module to the very bottom layer of 3D UNet, so that the contextual features representing visual differences between regions and consistencies within regions could be strengthened from successive frames in the video. The learning process of the H-TUNet is formulated as a unified end-to-end network, so the intra-frame feature extraction and inter-frame feature aggregation can be learned and optimized jointly. The proposed method was evaluated on Thyroid Segmentation in Ultrasonography Dataset (TSUD) and TG3k Dataset. Experimental results have demonstrated that our method outperformed other state-of-the-art methods with respect to the certain benchmarks for thyroid gland segmentation.


Assuntos
Benchmarking , Glândula Tireoide , Glândula Tireoide/diagnóstico por imagem , Ultrassonografia , Processamento de Imagem Assistida por Computador
10.
BMJ Open Qual ; 12(1)2023 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-36693674

RESUMO

BACKGROUND: The National Stroke Audit has been used to audit and provide feedback to health professionals and stroke care services in Australia since 2007. The Australian Stroke Clinical Registry was piloted in 2009 and numbers of hospitals participating in the registry are increasing. Considering the changing data landscape in Australia, we designed this study to evaluate the stroke audit and to inform strategic direction. METHODS: We conducted a rapid review of published literature to map features of successful data programmes, followed by a mixed-methods study, comprising national surveys and interviews with clinicians and administrators about the stroke audit. We analysed quantitative data descriptively and analysed open-ended survey responses and interview data using qualitative content analysis. We integrated data from the two sources. RESULTS: We identified 47 Australian data programs, successful programs were usually funded by government sources or professional associations and typically provided twice yearly or yearly reports.106 survey participants, 14 clinician and 5 health administrator interview participants were included in the evaluation. The Stroke Audit was consistently perceived as useful for benchmarking, but there were mixed views about its value for local quality improvement. Time to enter data was the most frequently reported barrier to participation (88% of survey participants), due to the large number of datapoints and features of the audit software.Opportunities to improve the Stroke Audit included refining Audit questions, developing ways to automatically export data from electronic medical records and capturing accurate data for patients who transferred between hospitals. CONCLUSION: While the Stroke Audit was not perceived by all users to be beneficial for traditional quality improvement purposes, the ability to benchmark national stroke services and use these data in advocacy activities was a consistently reported benefit. Modifications were suggested to improve usability and usefulness for participating sites.


Assuntos
Acidente Vascular Cerebral , Humanos , Austrália , Acidente Vascular Cerebral/terapia , Melhoria de Qualidade , Benchmarking , Hospitais
11.
Sci Rep ; 13(1): 1372, 2023 Jan 25.
Artigo em Inglês | MEDLINE | ID: mdl-36697500

RESUMO

Biomolecules undergo continuous conformational motions, a subset of which are functionally relevant. Understanding, and ultimately controlling biomolecular function are predicated on the ability to map continuous conformational motions, and identify the functionally relevant conformational trajectories. For equilibrium and near-equilibrium processes, function proceeds along minimum-energy pathways on one or more energy landscapes, because higher-energy conformations are only weakly occupied. With the growing interest in identifying functional trajectories, the need for reliable mapping of energy landscapes has become paramount. In response, various data-analytical tools for determining structural variability are emerging. A key question concerns the veracity with which each data-analytical tool can extract functionally relevant conformational trajectories from a collection of single-particle cryo-EM snapshots. Using synthetic data as an independently known ground truth, we benchmark the ability of four leading algorithms to determine biomolecular energy landscapes and identify the functionally relevant conformational paths on these landscapes. Such benchmarking is essential for systematic progress toward atomic-level movies of continuous biomolecular function.


Assuntos
Algoritmos , Benchmarking , Conformação Proteica , Microscopia Crioeletrônica , Movimento (Física)
12.
Sci Data ; 10(1): 5, 2023 01 03.
Artigo em Inglês | MEDLINE | ID: mdl-36596792

RESUMO

Multiparametric video-cabled marine observatories are becoming strategic to monitor remotely and in real-time the marine ecosystem. Those platforms can achieve continuous, high-frequency and long-lasting image data sets that require automation in order to extract biological time series. The OBSEA, located at 4 km from Vilanova i la Geltrú at 20 m depth, was used to produce coastal fish time series continuously over the 24-h during 2013-2014. The image content of the photos was extracted via tagging, resulting in 69917 fish tags of 30 taxa identified. We also provided a meteorological and oceanographic dataset filtered by a quality control procedure to define real-world conditions affecting image quality. The tagged fish dataset can be of great importance to develop Artificial Intelligence routines for the automated identification and classification of fishes in extensive time-lapse image sets.


Assuntos
Inteligência Artificial , Ecossistema , Peixes , Animais , Algoritmos , Benchmarking
13.
Sensors (Basel) ; 23(1)2023 Jan 03.
Artigo em Inglês | MEDLINE | ID: mdl-36617127

RESUMO

Predicting the trajectories of surrounding vehicles is an essential task in autonomous driving, especially in a highway setting, where minor deviations in motion can cause serious road accidents. The future trajectory prediction is often not only based on historical trajectories but also on a representation of the interaction between neighbouring vehicles. Current state-of-the-art methods have extensively utilized RNNs, CNNs and GNNs to model this interaction and predict future trajectories, relying on a very popular dataset known as NGSIM, which, however, has been criticized for being noisy and prone to overfitting issues. Moreover, transformers, which gained popularity from their benchmark performance in various NLP tasks, have hardly been explored in this problem, presumably due to the accumulative errors in their autoregressive decoding nature of time-series forecasting. Therefore, we propose MALS-Net, a Multi-Head Attention-based LSTM Sequence-to-Sequence model that makes use of the transformer's mechanism without suffering from accumulative errors by utilizing an attention-based LSTM encoder-decoder architecture. The proposed model was then evaluated in BLVD, a more practical dataset without the overfitting issue of NGSIM. Compared to other relevant approaches, our model exhibits state-of-the-art performance for both short and long-term prediction.


Assuntos
Condução de Veículo , Benchmarking , Fontes de Energia Elétrica , Movimento (Física) , Fatores de Tempo
14.
Nat Commun ; 14(1): 94, 2023 Jan 06.
Artigo em Inglês | MEDLINE | ID: mdl-36609502

RESUMO

A plethora of software suites and multiple classes of spectral libraries have been developed to enhance the depth and robustness of data-independent acquisition (DIA) data processing. However, how the combination of a DIA software tool and a spectral library impacts the outcome of DIA proteomics and phosphoproteomics data analysis has been rarely investigated using benchmark data that mimics biological complexity. In this study, we create DIA benchmark data sets simulating the regulation of thousands of proteins in a complex background, which are collected on both an Orbitrap and a timsTOF instruments. We evaluate four commonly used software suites (DIA-NN, Spectronaut, MaxDIA and Skyline) combined with seven different spectral libraries in global proteome analysis. Moreover, we assess their performances in analyzing phosphopeptide standards and TNF-α-induced phosphoproteome regulation. Our study provides a practical guidance on how to construct a robust data analysis pipeline for different proteomics studies implementing the DIA technique.


Assuntos
Benchmarking , Proteômica , Proteômica/métodos , Benchmarking/métodos , Fluxo de Trabalho , Espectrometria de Massas/métodos , Software , Proteoma/metabolismo
15.
Lancet Oncol ; 24(1): 22-32, 2023 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-36603919

RESUMO

BACKGROUND: Population-based cancer survival is a key measurement of cancer control performance linked to diagnosis and treatment, but benchmarking studies that include lower-income settings and that link results to health systems and human development are scarce. SURVCAN-3 is an international collaboration of population-based cancer registries that aims to benchmark timely and comparable cancer survival estimates in Africa, central and south America, and Asia. METHODS: In SURVCAN-3, population-based cancer registries from Africa, central and south America, and Asia were invited to contribute data. Quality control and data checks were carried out in collaboration with population-based cancer registries and, where applicable, active follow-up was performed at the registry. Patient-level data (sex, age at diagnosis, date of diagnosis, morphology and topography, stage, vital status, and date of death or last contact) were included, comprising patients diagnosed between Jan 1, 2008, and Dec 31, 2012, and followed up for at least 2 years (until Dec 31, 2014). Age-standardised net survival (survival where cancer was the only possible cause of death), with 95% CIs, at 1 year, 3 years, and 5 years after diagnosis were calculated using Pohar-Perme estimators for 15 major cancers. 1-year, 3-year, and 5-year net survival estimates were stratified by countries within continents (Africa, central and south America, and Asia), and countries according to the four-tier Human Development Index (HDI; low, medium, high, and very high). FINDINGS: 1 400 435 cancer cases from 68 population-based cancer registries in 32 countries were included. Net survival varied substantially between countries and world regions, with estimates steadily rising with increasing levels of the HDI. Across the included cancer types, countries within the lowest HDI category (eg, CÔte d'Ivoire) had a maximum 3-year net survival of 54·6% (95% CI 33·3-71·6; prostate cancer), whereas those within the highest HDI categories (eg, Israel) had a maximum survival of 96·8% (96·1-97·3; prostate cancer). Three distinct groups with varying outcomes by country and HDI dependant on cancer type were identified: cancers with low median 3-year net survival (<30%) and small differences by HDI category (eg, lung and stomach), cancers with intermediate median 3-year net survival (30-79%) and moderate difference by HDI (eg, cervix and colorectum), and cancers with high median 3-year net survival (≥80%) and large difference by HDI (eg, breast and prostate). INTERPRETATION: Disparities in cancer survival across countries were linked to a country's developmental position, and the availability and efficiency of health services. These data can inform policy makers on priorities in cancer control to reduce apparent inequality in cancer outcome. FUNDING: Tata Memorial Hospital, the Martin-Luther-University Halle-Wittenberg, and the International Agency for Research on Cancer.


Assuntos
Benchmarking , Neoplasias da Próstata , Masculino , Feminino , Humanos , Mama , Renda , África Central , Sistema de Registros
16.
Sensors (Basel) ; 23(2)2023 Jan 04.
Artigo em Inglês | MEDLINE | ID: mdl-36679371

RESUMO

The improvement of comfort monitoring resources is pivotal for a better understanding of personal perception in indoor and outdoor environments and thus developing personalized comfort models maximizing occupants' well-being while minimizing energy consumption. Different daily routines and their relation to the thermal sensation remain a challenge in long-term monitoring campaigns. This paper presents a new methodology to investigate the correlation between individuals' daily Thermal Sensation Vote (TSV) and environmental exposure. Participants engaged in the long-term campaign were instructed to answer a daily survey about thermal comfort perception and wore a device continuously monitoring temperature and relative humidity in their surroundings. Normalized daily profiles of monitored variables and calculated heat index were clustered to identify common exposure profiles for each participant. The correlation between each cluster and expressed TSV was evaluated through the Kendall tau-b test. Most of the significant correlations were related to the heat index profiles, i.e., 49% of cases, suggesting that a more detailed description of physical boundaries better approximates expressed comfort. This research represents the first step towards personalized comfort models accounting for individual long-term environmental exposure. A longer campaign involving more participants should be organized in future studies, involving also physiological variables for energy-saving purposes.


Assuntos
Benchmarking , Dispositivos Eletrônicos Vestíveis , Humanos , Sensação Térmica , Temperatura , Percepção
17.
Sensors (Basel) ; 23(2)2023 Jan 16.
Artigo em Inglês | MEDLINE | ID: mdl-36679839

RESUMO

Embedded hardware systems, such as wearable devices, are widely used for health status monitoring of ageing people to improve their well-being. In this context, it becomes increasingly important to develop portable, easy-to-use, compact, and energy-efficient hardware-software platforms, to enhance the level of usability and promote their deployment. With this purpose an automatic tri-axial accelerometer-based system for postural recognition has been developed, useful in detecting potential inappropriate behavioral habits for the elderly. Systems in the literature and on the market for this type of analysis mostly use personal computers with high computing resources, which are not easily portable and have high power consumption. To overcome these limitations, a real-time posture recognition Machine Learning algorithm was developed and optimized that could perform highly on platforms with low computational capacity and power consumption. The software was integrated and tested on two low-cost embedded platform (Raspberry Pi 4 and Odroid N2+). The experimentation stage was performed on various Machine Learning pre-trained classifiers using data of seven elderly users. The preliminary results showed an activity classification accuracy of about 98% for the four analyzed postures (Standing, Sitting, Bending, and Lying down), with similar accuracy and a computational load as the state-of-the-art classifiers running on personal computers.


Assuntos
Benchmarking , Dispositivos Eletrônicos Vestíveis , Humanos , Idoso , Postura , Software , Algoritmos , Acelerometria
18.
Sci Rep ; 13(1): 1004, 2023 Jan 18.
Artigo em Inglês | MEDLINE | ID: mdl-36653424

RESUMO

Industrial Internet of Things (IIoT)-based systems have become an important part of industry consortium systems because of their rapid growth and wide-ranging application. Various physical objects that are interconnected in the IIoT network communicate with each other and simplify the process of decision-making by observing and analyzing the surrounding environment. While making such intelligent decisions, devices need to transfer and communicate data with each other. However, as devices involved in IIoT networks grow and the methods of connections diversify, the traditional security frameworks face many shortcomings, including vulnerabilities to attack, lags in data, sharing data, and lack of proper authentication. Blockchain technology has the potential to empower safe data distribution of big data generated by the IIoT. Prevailing data-sharing methods in blockchain only concentrate on the data interchanging among parties, not on the efficiency in sharing, and storing. Hence an element-based K-harmonic means clustering algorithm (CA) is proposed for the effective sharing of data among the entities along with an algorithm named underweight data block (UDB) for overcoming the obstacle of storage space. The performance metrics considered for the evaluation of the proposed framework are the sum of squared error (SSE), time complexity with respect to different m values, and storage complexity with CPU utilization. The results have experimented with MATLAB 2018a simulation environment. The proposed model has better sharing, and storing based on blockchain technology, which is appropriate IIoT.


Assuntos
Blockchain , Indústrias , Algoritmos , Benchmarking , Big Data , Segurança Computacional
19.
Brief Bioinform ; 24(1)2023 Jan 19.
Artigo em Inglês | MEDLINE | ID: mdl-36592056

RESUMO

Circular RNAs (circRNAs) are covalently closed transcripts involved in critical regulatory axes, cancer pathways and disease mechanisms. CircRNA expression measured with RNA-seq has particular characteristics that might hamper the performance of standard biostatistical differential expression assessment methods (DEMs). We compared 38 DEM pipelines configured to fit circRNA expression data's statistical properties, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq) and metagenomics DEMs. The DEMs performed poorly on data sets of typical size. Widely used DEMs, such as DESeq2, edgeR and Limma-Voom, gave scarce results, unreliable predictions or even contravened the expected behaviour with some parameter configurations. Limma-Voom achieved the most consistent performance throughout different benchmark data sets and, as well as SAMseq, reasonably balanced false discovery rate (FDR) and recall rate. Interestingly, a few scRNA-seq DEMs obtained results comparable with the best-performing bulk RNA-seq tools. Almost all DEMs' performance improved when increasing the number of replicates. CircRNA expression studies require careful design, choice of DEM and DEM configuration. This analysis can guide scientists in selecting the appropriate tools to investigate circRNA differential expression with RNA-seq experiments.


Assuntos
Benchmarking , RNA Circular , Benchmarking/métodos , Análise de Sequência de RNA/métodos , RNA-Seq , Metagenômica , RNA/genética
20.
Brief Bioinform ; 24(1)2023 Jan 19.
Artigo em Inglês | MEDLINE | ID: mdl-36592060

RESUMO

Drug-target interaction (DTI) prediction is an essential step in drug repositioning. A few graph neural network (GNN)-based methods have been proposed for DTI prediction using heterogeneous biological data. However, existing GNN-based methods only aggregate information from directly connected nodes restricted in a drug-related or a target-related network and are incapable of capturing high-order dependencies in the biological heterogeneous graph. In this paper, we propose a metapath-aggregated heterogeneous graph neural network (MHGNN) to capture complex structures and rich semantics in the biological heterogeneous graph for DTI prediction. Specifically, MHGNN enhances heterogeneous graph structure learning and high-order semantics learning by modeling high-order relations via metapaths. Additionally, MHGNN enriches high-order correlations between drug-target pairs (DTPs) by constructing a DTP correlation graph with DTPs as nodes. We conduct extensive experiments on three biological heterogeneous datasets. MHGNN favorably surpasses 17 state-of-the-art methods over 6 evaluation metrics, which verifies its efficacy for DTI prediction. The code is available at https://github.com/Zora-LM/MHGNN-DTI.


Assuntos
Benchmarking , Reposicionamento de Medicamentos , Sistemas de Liberação de Medicamentos , Aprendizagem , Redes Neurais de Computação
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