Comparing Video Analysis to Computerized Detection of Limb Position for the Diagnosis of Movement Control during Back Squat Exercise with Overload.

Incorrect limb position while lifting heavy weights might compromise athlete success during weightlifting performance, similar to the way that it increases the risk of muscle injuries during resistance exercises, regardless of the individual's level of experience. However, practitioners might not have the necessary background knowledge for self-supervision of limb position and adjustment of the lifting position when improper movement occurs. Therefore, the computerized analysis of movement patterns might assist people in detecting changes in limb position during exercises with different loads or enhance the analysis of an observer with expertise in weightlifting exercises. In this study, hidden Markov models (HMMs) were employed to automate the detection of joint position and barbell trajectory during back squat exercises. Ten volunteers performed three lift movements each with a 0, 50, and 75% load based on body weight. A smartphone was used to record the movements in the sagittal plane, providing information for the analysis of variance and identifying significant position changes by video analysis (p < 0.05). Data from individuals performing the same movements with no added weight load were used to train the HMMs to identify changes in the pattern. A comparison of HMMs and human experts revealed between 40% and 90% agreement, indicating the reliability of HMMs for identifying changes in the control of movements with added weight load. In addition, the results highlighted that HMMs can detect changes imperceptible to the human visual analysis.

Thermostabilizing mechanisms of canonical single amino acid substitutions at a GH1 ß-glucosidase probed by multiple MD and computational approaches.

ß-glucosidases play a pivotal role in second-generation biofuel (2G-biofuel) production. For this application, thermostable enzymes are essential due to the denaturing conditions on the bioreactors. Random amino acid substitutions have originated new thermostable ß-glucosidases, but without a clear understanding of their molecular mechanisms. Here, we probe by different molecular dynamics simulation approaches with distinct force fields and submitting the results to various computational analyses, the molecular bases of the thermostabilization of the Paenibacillus polymyxa GH1 ß-glucosidase by two-point mutations E96K (TR1) and M416I (TR2). Equilibrium molecular dynamic simulations (eMD) at different temperatures, principal component analysis (PCA), virtual docking, metadynamics (MetaDy), accelerated molecular dynamics (aMD), Poisson-Boltzmann surface analysis, grid inhomogeneous solvation theory and colony method estimation of conformational entropy allow to converge to the idea that the stabilization carried by both substitutions depend on different contributions of three classic mechanisms: (i) electrostatic surface stabilization; (ii) efficient isolation of the hydrophobic core from the solvent, with energetic advantages at the solvation cap; (iii) higher distribution of the protein dynamics at the mobile active site loops than at the protein core, with functional and entropic advantages. Mechanisms i and ii predominate for TR1, while in TR2, mechanism iii is dominant. Loop A integrity and loops A, C, D, and E dynamics play critical roles in such mechanisms. Comparison of the dynamic and topological changes observed between the thermostable mutants and the wildtype protein with amino acid co-evolutive networks and thermostabilizing hotspots from the literature allow inferring that the mechanisms here recovered can be related to the thermostability obtained by different substitutions along the whole family GH1. We hope the results and insights discussed here can be helpful for future rational approaches to the engineering of optimized ß-glucosidases for 2G-biofuel production for industry, biotechnology, and science.

The effect of the exercise environment and the level of involvement on bone mineral health.

INTRODUCTION: This study aimed to compare athletes practicing exercise in different environments with non-active young and elderly men and women regarding bone mineral density (BMD), hypothesizing that BMD values differ between athletes according to the environment of exercise practice, but those training in a low-gravitational environment have no different stimuli to BMD increasing if compared with healthy peers experiencing reduced exercise involvement, whatever the age group and sex. MATERIALS AND METHODS: 104 participants of both sexes were selected according to the environment of exercise practice [swimmers (N = 26) and judo fighters (N = 26)], and exercise level of involvement [non-active young (N = 26) and older adults (N = 26)]. Dual-energy X-ray absorptiometry provided BMD, lean mass, and fat mass (FM) for the whole body (WB), upper (UL), and lower limbs (LL). RESULTS: For the BMD in WB, UL and LL no effects of group and sex were observed (p > 0.05). Post-hoc analyses detected higher values of BMD in UL for female swimmers compared to non-active older adults (p < 0.05), while judo fighters showed higher BMD in WB, UL, and LL than other participants whatever the sex (p < 0.01). Lower FM was observed for WB, UL, and LL when swimmers and judo fighters were compared to non-active young and older female peers (p < 0.01). CONCLUSION: The findings emphasized that BMD stimuli with swimming are reduced when compared to judo, and despite the stimuli in swimming is not distinguishable from that affecting BMD in WB, UL and LL of non-active young, it is effective in differing BMD in UL among non-active older for women.

Performance of the Aktiia optical blood pressure measurement device in the elderly: a comparison with double blinded auscultation in different body positions.

BACKGROUND: Accurate blood pressure (BP) measurement is essential for the correct diagnosis and management of hypertension (HTN) especially in the elderly population. As with of all BP devices, the accuracy of cuffless devices must be verified. This study (NCT04027777) aimed to evaluate the performance of a wrist cuffless optical BP device in an elderly population cohort in different body positions with auscultation as the reference measurement. DESIGN AND METHODS: Patients aged 65-85 years with different BP categories but without diabetes were recruited. After an initial calibration based on auscultatory measurements, BP estimation from the Aktiia Bracelet (Aktiia SA, Switzerland) were compared to reference double-blinded auscultatory measurements in sitting, standing and lying positions on four separate visits distributed over one month. In the absence of a universal standard for cuffless BP device at the time of the study, modified ISO81060-2 criteria were used for performance analysis. RESULTS: Thirty-five participants were included in the analysis fulfilling the inclusion requirements of ISO 81060-2. A total of 469 paired measurements were obtained with overall 83% acceptance rate. Differences (mean ± SD)   between Aktiia Bracelet and auscultation for systolic BP were -0.26 ± 9.96 mmHg for all body positions aggregated (sitting 1.23 ± 7.88 mmHg, standing -1.81 ± 11.11 mmHg, lying -1.8 ± 9.96 mmHg). Similarly, differences for diastolic BP were -0.75 ± 7.0 mmHg (0.2 ± 5.55 mmHg, -5.35 ± 7.75 mmHg and -0.94 ± 7.47 mmHg, respectively). Standard deviation of the averaged differences per subject for systolic/diastolic BP was 3.8/2.5 mmHg in sitting and 4.4/3.7 mmHg for all body positions aggregated. CONCLUSIONS: Overall, this study demonstrates a similar performance of the Aktiia Bracelet compared to auscultation in an elderly population in body positions representative of daily activities. The use of more comfortable, non-invasive, and non-occlusive BP monitors during long periods may facilitate e-health and may contribute to better management of HTN, including diagnosis and treatment of HTN, in the elderly.

Accuracy of blood pressure measurements is essential in the diagnosis and the follow-up of patients with high blood pressure. As with any blood pressure measuring device, a validation is necessary. In this study including a elderly population, we compared values obtained by the cuffless Aktiia Bracelet (Aktiia SA, Switzerland) after an initial calibration with the reference auscultatory method during four separate study days distributed over one month. We show that the accuracy of the Aktiia Bracelet is similar to auscultation. The accuracy varies depending on the position in which the measurement is performed. Overall, the accuracy is not modified by a higher age category. The use of a cuffless device in the elderly population characterized by high prevalence of hypertension may facilitate the follow-up of blood pressure with more comfort and minimal constraints.

Hybrid machine learning to localize atrial flutter substrates using the surface 12-lead electrocardiogram.

AIMS: Atrial flutter (AFlut) is a common re-entrant atrial tachycardia driven by self-sustainable mechanisms that cause excitations to propagate along pathways different from sinus rhythm. Intra-cardiac electrophysiological mapping and catheter ablation are often performed without detailed prior knowledge of the mechanism perpetuating AFlut, likely prolonging the procedure time of these invasive interventions. We sought to discriminate the AFlut location [cavotricuspid isthmus-dependent (CTI), peri-mitral, and other left atrium (LA) AFlut classes] with a machine learning-based algorithm using only the non-invasive signals from the 12-lead electrocardiogram (ECG). METHODS AND RESULTS: Hybrid 12-lead ECG dataset of 1769 signals was used (1424 in silico ECGs, and 345 clinical ECGs from 115 patients-three different ECG segments over time were extracted from each patient corresponding to single AFlut cycles). Seventy-seven features were extracted. A decision tree classifier with a hold-out classification approach was trained, validated, and tested on the dataset randomly split after selecting the most informative features. The clinical test set comprised 38 patients (114 clinical ECGs). The classifier yielded 76.3% accuracy on the clinical test set with a sensitivity of 89.7%, 75.0%, and 64.1% and a positive predictive value of 71.4%, 75.0%, and 86.2% for CTI, peri-mitral, and other LA class, respectively. Considering majority vote of the three segments taken from each patient, the CTI class was correctly classified at 92%. CONCLUSION: Our results show that a machine learning classifier relying only on non-invasive signals can potentially identify the location of AFlut mechanisms. This method could aid in planning and tailoring patient-specific AFlut treatments.

Impact of Delirium and Its Motor Subtypes on Stroke Outcomes.

BACKGROUND AND PURPOSE: Delirium is an acute and fluctuating impairment of attention, cognition, and behavior. Although common in stroke, studies that associate the clinical subtypes of delirium with functional outcome and death are lacking. We aimed to evaluate the influence of delirium occurrence and its different motor subtypes over stroke patients' prognosis. METHODS: Prospective cohort of stroke patients with symptom onset within 72 hours before research admission. Delirium was diagnosed by Confusion Assessment Method for the Intensive Care Unit, and its motor subtypes were defined according to the Richmond Agitation-Sedation Scale. The main outcome was functional dependence or death (modified Rankin Scale>2) at 90 days comparing: delirium versus no delirium patients; and between motor subtypes. Secondary outcomes included modified Rankin Scale score >2 at 30 days and 90-day-mortality. RESULTS: Two hundred twenty-seven patients were enrolled. Delirium occurred in 71 patients (31.3%), with the hypoactive subtype as the most frequent, in 41 subjects (57.8%). Delirium was associated with increased risk of death and functional dependence at 30 and 90 days and higher 90-day mortality. Multivariate analysis showed delirium (odds ratio, 3.28 [95% CI, 1.17-9.22]) as independent predictor of modified Rankin Scale >2 at 90 days. CONCLUSIONS: Delirium is frequent in stroke patients in the acute phase. Its occurrence-specifically in mixed and hypoactive subtypes-seems to predict worse outcomes in this population. To our knowledge, this is the first study to prospectively investigate differences between delirium motor subtypes over functional outcome three months poststroke. Larger studies are needed to elucidate the relationship between motor subtypes of delirium and functional outcomes in the context of acute stroke.

Spectral characteristics of subthalamic nucleus local field potentials in Parkinson's disease: Phenotype and movement matter.

Parkinson's disease (PD) is clinically heterogeneous across patients and may be classified in three motor phenotypes: tremor dominant (TD), postural instability and gait disorder (PIGD), and undetermined. Despite the significant clinical characterization of motor phenotypes, little is known about how electrophysiological data, particularly subthalamic nucleus local field potentials (STN-LFP), differ between TD and PIGD patients. This is relevant since increased STN-LFP bandpower at α-ß range (8-35 Hz) is considered a potential PD biomarker and, therefore, a critical setpoint to drive adaptive deep brain stimulation. Acknowledging STN-LFP differences between phenotypes, mainly in rest and movement states, would better fit DBS to clinical and motor demands. We studied this issue through spectral analyses on 35 STN-LFP in TD and PIGD patients during rest and movement. We demonstrated that higher ß2 activity (22-35 Hz) was observed in PIGD only during rest. Additionally, bandpower differences between rest and movement occurred at the α-ß range, but with different patterns as per phenotypes: movement-induced desynchronization concerned lower frequencies in TD (10-20 Hz) and higher frequencies in PIGD patients (21-28 Hz). Finally, when supervised learning algorithms were employed aiming to discriminate PD phenotypes based on STN-LFP bandpower features, movement information had improved the classification accuracy, achieving peak performances when TD and PIGD movement-induced desynchronization ranges were considered. These results suggest that STN-LFP ß-band encodes phenotype-movement dependent information in PD patients.

[Formula: see text] kinetics and energy contribution in simulated maximal performance during short and middle distance-trials in swimming.

PURPOSE: This study aims to analyze swimmers' oxygen uptake kinetics ([Formula: see text]K) and bioenergetic profiles in 50, 100, and 200 m simulated swimming events and determine which physiological variables relate with performance. METHODS: Twenty-eight well-trained swimmers completed an incremental test for maximal oxygen uptake (Peak-[Formula: see text]) and maximal aerobic velocity (MAV) assessment. Maximal trials (MT) of 50, 100, and 200-m in front crawl swimming were performed for [Formula: see text]K and bioenergetic profile. [Formula: see text]K parameters were calculated through monoexponential modeling and by a new growth rate method. The recovery phase was used along with the blood lactate concentration for bioenergetics profiling. RESULTS: Peak-[Formula: see text] (57.47 ± 5.7 ml kg-1 min-1 for male and 53.53 ± 4.21 ml kg-1 min-1 for female) did not differ from [Formula: see text]peak attained at the 200-MT for female and at the 100 and 200-MT for male. From the 50-MT to 100-MT and to the 200-MT the [Formula: see text]K presented slower time constants (8.6 ± 2.3 s, 11.5 ± 2.4 s and 16.7 ± 5.5 s, respectively), the aerobic contribution increased (~ 34%, 54% and 71%, respectively) and the anaerobic decreased (~ 66%, 46% and 29%, respectively), presenting a cross-over in the 100-MT. Both energy systems, MAV, Peak-[Formula: see text], and [Formula: see text] peak of the MT's were correlated with swimming performance. DISCUSSION: The aerobic energy contribution is an important factor for performance in 50, 100, and 200-m, regardless of the time taken to adjust the absolute oxidative response, when considering the effect on a mixed-group regarding sex. [Formula: see text]K speeding could be explained by a faster initial pacing strategy used in the shorter distances, that contributed for a more rapid increase of the oxidative contribution to the energy turnover.

Characterization of human persistent atrial fibrillation electrograms using recurrence quantification analysis.

Atrial fibrillation (AF) is regarded as a complex arrhythmia, with one or more co-existing mechanisms, resulting in an intricate structure of atrial activations. Fractionated atrial electrograms (AEGs) were thought to represent arrhythmogenic tissue and hence have been suggested as targets for radiofrequency ablation. However, current methods for ablation target identification have resulted in suboptimal outcomes for persistent AF (persAF) treatment, possibly due to the complex spatiotemporal dynamics of these mechanisms. In the present work, we sought to characterize the dynamics of atrial tissue activations from AEGs collected during persAF using recurrence plots (RPs) and recurrence quantification analysis (RQA). 797 bipolar AEGs were collected from 18 persAF patients undergoing pulmonary vein isolation (PVI). Automated AEG classification (normal vs. fractionated) was performed using the CARTO criteria (Biosense Webster). For each AEG, RPs were evaluated in a phase space estimated following Takens' theorem. Seven RQA variables were obtained from the RPs: recurrence rate; determinism; average diagonal line length; Shannon entropy of diagonal length distribution; laminarity; trapping time; and Shannon entropy of vertical length distribution. The results show that the RQA variables were significantly affected by PVI, and that the variables were effective in discriminating normal vs. fractionated AEGs. Additionally, diagonal structures associated with deterministic behavior were still present in the RPs from fractionated AEGs, leading to a high residual determinism, which could be related to unstable periodic orbits and suggesting a possible chaotic behavior. Therefore, these results contribute to a nonlinear perspective of the spatiotemporal dynamics of persAF.

Biocatalytic synthesis of the Green Note trans-2-hexenal in a continuous-flow microreactor.

The biocatalytic preparation of trans-hex-2-enal from trans-hex-2-enol using a novel aryl alcohol oxidase from Pleurotus eryngii (PeAAOx) is reported. As O2-dependent enzyme PeAAOx-dependent reactions are generally plagued by the poor solubility of O2 in aqueous media and mass transfer limitations resulting in poor reaction rates. These limitations were efficiently overcome by conducting the reaction in a flow-reactor setup reaching unpreceded catalytic activities for the enzyme in terms of turnover frequency (up to 38 s-1) and turnover numbers (more than 300000) pointing towards preparative usefulness of the proposed reaction scheme.

Charge carrier transport in defective reduced graphene oxide as quantum dots and nanoplatelets in multilayer films.

Graphene is a breakthrough 2D material due to its unique mechanical, electrical, and thermal properties, with considerable responsiveness in real applications. However, the coverage of large areas with pristine graphene is a challenge and graphene derivatives have been alternatively exploited to produce hybrid and composite materials that allow for new developments, considering also the handling of large areas using distinct methodologies. For electronic applications there is significant interest in the investigation of the electrical properties of graphene derivatives and related composites to determine whether the characteristic 2D charge transport of pristine graphene is preserved. Here, we report a systematic study of the charge transport mechanisms of reduced graphene oxide chemically functionalized with sodium polystyrene sulfonate (PSS), named as GPSS. GPSS was produced either as quantum dots (QDs) or nanoplatelets (NPLs), being further nanostructured with poly(diallyldimethylammonium chloride) through the layer-by-layer (LbL) assembly to produce graphene nanocomposites with molecular level control. Current-voltage (I-V) measurements indicated a meticulous growth of the LbL nanostructures onto gold interdigitated electrodes (IDEs), with a space-charge-limited current dominated by a Mott-variable range hopping mechanism. A 2D intra-planar conduction within the GPSS nanostructure was observed, which resulted in effective charge carrier mobility (µ) of 4.7 cm2 V-1 s-1 for the QDs and 34.7 cm2 V-1 s-1 for the NPLs. The LbL assemblies together with the dimension of the materials (QDs or NPLs) were favorably used for the fine tuning and control of the charge carrier mobility inside the LbL nanostructures. Such 2D charge conduction mechanism and high µ values inside an interlocked multilayered assembly containing graphene-based nanocomposites are of great interest for organic devices and functionalization of interfaces.

Endophytic cultivable bacterial community obtained from the Paullinia cupana seed in Amazonas and Bahia regions and its antagonistic effects against Colletotrichum gloeosporioides.

Guarana (Paullinia cupana var. sorbilis) is a plant from the Amazonas region with socio-economic importance. However, guarana production has been increasingly affected by unfavorable conditions resulting from anthracnose, caused by the Colletotrichum fungal genus, which primarily affects mainly the Amazonas region. The aim of the present study was to isolate bacterial endophytes from the seeds of guarana plants obtained from Amazonas region and the Northeast state of Bahia, a region where this disease is not a problem for guarana plantations. The number of bacterial Colony Forming Units (CFU/g seeds) was 2.4 × 10(4) from the Bahia and 2.9 × 10(4) from the Amazonas region. One hundred and two isolated bacteria were evaluated in vitro against the phytopathogenic strain Colletotrichum gloeosporioides L1. These isolates were also analyzed for the enzymatic production of amylase, cellulase, protease, pectinase, lipase and esterase. Approximately 15% of isolates, showing high antagonistic activity, and the production of at least one enzyme were identified through the partial sequencing of 16S rDNA. The genus Bacillus was the most frequently observed, followed by Paenibacillus, Ochrobactrum, Microbacterium and Stenotrophomonas. Proteolytic activity was observed in 24 isolates followed by amylolytic, pectinolytic and cellulolytic activities. No esterase and lipase production was detected. Most of the isolates, showing antagonistic effects against C. gloeosporioides and high enzymatic activities, were isolated from the anthracnose-affected region. A biocontrol method using the endophytes from guarana seeds could be applied in the future, as these bacteria are vertically transferred to guarana seedlings.

Ventilatory and Physiological Responses in Swimmers Below and Above Their Maximal Lactate Steady State.

The purpose of this study was to understand the ventilatory and physiological responses immediately below and above the maximal lactate steady-state (MLSS) velocity and to determine the relationship of oxygen uptake (VO2) kinetics parameters with performance, in swimmers. Competitive athletes (N = 12) completed in random order and on different days a 400-m all-out test, an incremental step test comprising 5 × 250- and 1 × 200-m stages and 30 minutes at a constant swimming velocity (SV) at 87.5, 90, and 92.5% of the maximal aerobic velocity for MLSS velocity (MLSSv) determination. Two square-wave transitions of 500 m, 2.5% above and below the MLSSv were completed to determine VO2 on-kinetics. End-exercise VO2 at 97.5 and 102.5% of MLSSv represented, respectively, 81 and 97% of VO2max; the latter was not significantly different from maximal VO2 (VO2max). The VO2 at MLSSv (49.3 ± 9.2 ml·kg(-1)·min(-1)) was not significantly different from the second ventilatory threshold (VT2) (51.3 ± 7.6 ml·kg(-1)·min(-1)). The velocity associated with MLSS seems to be accurately estimated by the SV at VT2 (vVT2), and vVO2max also seems to be estimated with accuracy from the central 300-m mean velocity of a 400-m trial, indicators that represent a helpful tool for coaches. The 400-m swimming performance (T400) was correlated with the time constant of the primary phase VO2 kinetics (τp) at 97.5% MLSSv, and T800 was correlated with τp in both 97.5 and 102.5% of MLSSv. The assessment of the VO2 kinetics in swimming can help coaches to build training sets according to a swimmer's individual physiological response.

Optimizing time-in-target-range assessment for blood pressure: insights from a large-scale study with continual cuffless monitoring.

Introduction: Blood pressure (BP) time-in-target-range (TTR) is an emerging predictor of cardiovascular risk. Conventional BP methods are fundamentally unable to provide an optimal assessment of TTR, using irregular measurements separated by lengthy intervals. We investigated the optimal duration and frequency for reliable, practical TTR assessment in clinical settings using continual monitoring. Methods: This retrospective study analyzed 2.3 million BP readings from 5,189 European home users (55 ± 11 years, 82% male, BMI 28.0 ± 5.8) using a cuffless BP monitor (Aktiia SA). Systolic BP (SBP) data over 15 consecutive days were assessed (29 ± 11 readings/subject/24-h; 434 + 132 readings/subject/15-day). Subjects were classified into risk-related TTR groups based on 15-day SBP data (24-h, target 90-125 mmHg; ≥6 daytime readings). Various measurement frequencies and durations (1-14 days; 24-h/daytime; 2, 4 or ≥ 6 readings/day) were compared to this reference. Two specific configurations paralleling ambulatory ("One-Day-24 h") and home ("One-Week-Daytime") BP monitoring were selected for detailed analysis. Results: The reference TTR classified 63.0% of the subjects as high risk, 19.0% intermediate, and 18.0% low. "One-Day-24 h" schedule inaccurately classified 26% of subjects compared to the reference TTR, and "One-Week-Daytime" schedule inaccurately classified 45%. Classification accuracy with both schedules was high for subjects with very low or very high reference TTR, but poor otherwise. Accuracy of ≥90% in TTR classification only occurred with 7 days of continual 24-h monitoring. Discussion: For the first time, with the benefit of a cuffless device that measures BP with sufficient frequency and duration, practical use of TTR is enabled as a potentially enhanced metric to manage hypertension.

Towards discovery: an end-to-end system for uncovering novel biomedical relations.

Biomedical relation extraction is an ongoing challenge within the natural language processing community. Its application is important for understanding scientific biomedical literature, with many use cases, such as drug discovery, precision medicine, disease diagnosis, treatment optimization and biomedical knowledge graph construction. Therefore, the development of a tool capable of effectively addressing this task holds the potential to improve knowledge discovery by automating the extraction of relations from research manuscripts. The first track in the BioCreative VIII competition extended the scope of this challenge by introducing the detection of novel relations within the literature. This paper describes that our participation system initially focused on jointly extracting and classifying novel relations between biomedical entities. We then describe our subsequent advancement to an end-to-end model. Specifically, we enhanced our initial system by incorporating it into a cascading pipeline that includes a tagger and linker module. This integration enables the comprehensive extraction of relations and classification of their novelty directly from raw text. Our experiments yielded promising results, and our tagger module managed to attain state-of-the-art named entity recognition performance, with a micro F1-score of 90.24, while our end-to-end system achieved a competitive novelty F1-score of 24.59. The code to run our system is publicly available at https://github.com/ieeta-pt/BioNExt. Database URL: https://github.com/ieeta-pt/BioNExt.

Multi-head CRF classifier for biomedical multi-class named entity recognition on Spanish clinical notes.

The identification of medical concepts from clinical narratives has a large interest in the biomedical scientific community due to its importance in treatment improvements or drug development research. Biomedical named entity recognition (NER) in clinical texts is crucial for automated information extraction, facilitating patient record analysis, drug development, and medical research. Traditional approaches often focus on single-class NER tasks, yet recent advancements emphasize the necessity of addressing multi-class scenarios, particularly in complex biomedical domains. This paper proposes a strategy to integrate a multi-head conditional random field (CRF) classifier for multi-class NER in Spanish clinical documents. Our methodology overcomes overlapping entity instances of different types, a common challenge in traditional NER methodologies, by using a multi-head CRF model. This architecture enhances computational efficiency and ensures scalability for multi-class NER tasks, maintaining high performance. By combining four diverse datasets, SympTEMIST, MedProcNER, DisTEMIST, and PharmaCoNER, we expand the scope of NER to encompass five classes: symptoms, procedures, diseases, chemicals, and proteins. To the best of our knowledge, these datasets combined create the largest Spanish multi-class dataset focusing on biomedical entity recognition and linking for clinical notes, which is important to train a biomedical model in Spanish. We also provide entity linking to the multi-lingual Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) vocabulary, with the eventual goal of performing biomedical relation extraction. Through experimentation and evaluation of Spanish clinical documents, our strategy provides competitive results against single-class NER models. For NER, our system achieves a combined micro-averaged F1-score of 78.73, with clinical mentions normalized to SNOMED CT with an end-to-end F1-score of 54.51. The code to run our system is publicly available at https://github.com/ieeta-pt/Multi-Head-CRF. Database URL: https://github.com/ieeta-pt/Multi-Head-CRF.

A decision support system to recommend appropriate therapy protocol for AML patients.

Introduction: Acute Myeloid Leukemia (AML) is one of the most aggressive hematological neoplasms, emphasizing the critical need for early detection and strategic treatment planning. The association between prompt intervention and enhanced patient survival rates underscores the pivotal role of therapy decisions. To determine the treatment protocol, specialists heavily rely on prognostic predictions that consider the response to treatment and clinical outcomes. The existing risk classification system categorizes patients into favorable, intermediate, and adverse groups, forming the basis for personalized therapeutic choices. However, accurately assessing the intermediate-risk group poses significant challenges, potentially resulting in treatment delays and deterioration of patient conditions. Methods: This study introduces a decision support system leveraging cutting-edge machine learning techniques to address these issues. The system automatically recommends tailored oncology therapy protocols based on outcome predictions. Results: The proposed approach achieved a high performance close to 0.9 in F1-Score and AUC. The model generated with gene expression data exhibited superior performance. Discussion: Our system can effectively support specialists in making well-informed decisions regarding the most suitable and safe therapy for individual patients. The proposed decision support system has the potential to not only streamline treatment initiation but also contribute to prolonged survival and improved quality of life for individuals diagnosed with AML. This marks a significant stride toward optimizing therapeutic interventions and patient outcomes.

Effects of Resistance Exercise with and without Blood Flow Restriction on Acute Hemodynamic Responses: A Systematic Review and Meta-Analysis.

Low-load intensity resistance exercise with blood flow restriction (BFR) is an alternative method for enhancing strength and muscle mass. However, acute cardiovascular responses to a complete training session remain uncertain compared to high-load intensity resistance exercise (HI). Therefore, the objective of this study to examine acute and post-exercise hemodynamic responses to low-load BFR and HI protocols. This systematic review and meta-analysis (RD42022308697) followed PRISMA guidelines to investigate whether the responses of heart rate (HR), blood systolic (SBP), blood diastolic pressure (DBP), and rate pressure product (RPP) immediately after and up to 60 min post-exercise from BFR were consistent with those reported after resistance exercises performed at HI in healthy individuals. Searches using PICO descriptors were conducted in databases from January 2011 to December 2023, and effect sizes were determined by Hedge's g. The selected studies involved 160 participants in nine articles, for which the responses immediately after BFR and HI exercises showed no differences in HR (p = 0.23) or SBP (p = 0.57), but significantly higher DBP (p < 0.01) and lower RPP (p < 0.01) responses were found when comparing BFR to HI. Furthermore, the BFR and HI protocols showed no differences regarding SBP (p = 0.21) or DBP (p = 0.68) responses during a 15 to 60 min post-exercise period. Thus, these results indicated that hemodynamic responses are similar between BFR and HI, with a similar hypotensive effect up to 60 min following exercise.

Relationship between Femur Mineral Content and Local Muscle Strength and Mass.

Among the stimuli able to prevent early decreases in bone mineralization, exercise has a noticeable role per se as the source of mechanical stimulus or through lean tissue enlargement by its increasing of tensional stimulus. However, prevention strategies, including exercise, generally do not establish the moment in life when attention should begin to be paid to bone integrity, according to age group- and sex-related differences. Thus, this study analyzed the relationship between variables from the diagnosis of total and regional body composition, muscle strength, and bone mineral content (BMC) of femurs in young adult males. Thirty-four young Caucasian men (24.9 ± 8.6 years) had their body composition and bone density assessed by dual X-ray absorptiometry. The subjects performed a one-repetition maximum test (1-RM) in a bench press, front pulley, seated-row, push press, arm curl, triceps pulley, leg flexion, leg extension, and 45° leg press for the assessment of muscle strength in upper and lower limbs in single- and multi-joint exercises. Lean tissue mass in the trunk and upper and lower limbs were related to femoral BMC (Pearson coefficient ranging from 0.55 to 0.72, p < 0.01), and 1-RM values for different exercises involving both upper and lower limbs also correlated with femoral BMC (Pearson coefficients ranging from 0.34 to 0.46, p < 0.05). Taken together, these correlations suggest that muscle mass and strength are positively linked with the magnitude of femoral mass in men, even in early adulthood. Hence, the importance of an enhanced muscle mass and strength to the health of femoral bones in young adults was highlighted.