Mechanical, Durability, and Microstructure Assessment of Wastepaper Fiber-Reinforced Concrete Containing Metakaolin.

This study evaluates the potential use of discarded plasterboard paper as fibers from buildings to reinforce concrete. Various concentrations of wastepaper fibers (0.5%, 1%, 1.5%, 2%, and 2.5% by weight of the binder) were investigated in this research. To mitigate the water absorption effect of the paper fibers, metakaolin was employed as a partial cement replacement. The results demonstrate that the inclusion of the wastepaper fiber enhances the mechanical and durability performance of the concrete. The optimal fiber proportion was identified as 1%, leading to a 29% increase in the compressive strength, a 38% increase in the splitting tensile strength, a 12% decrease in the water absorption, and a 23% decrease in the drying shrinkage with respect to the concrete containing 20% metakaolin. However, exceeding this optimal fiber content results in decreased mechanical and durability properties due to the fiber agglomeration and non-uniform fiber distribution within the concrete matrix. Based on the microstructural analysis, the improved performance of the concrete is ascribed to decreased porosity, more refined pore structure, and reduced propagation of microcracks within the concrete matrix in the presence of wastepaper fiber. According to the results, concrete containing 20% metakaolin and 1% wastepaper fiber exhibits durability and mechanical properties comparable to those of the traditional concrete. This finding highlights the significant promise of reducing dependency on conventional cement and incorporating suitable recycled materials, such as discarded plasterboard, and secondary by-products like metakaolin. Such a strategy encourages the preservation of resources, reduction in carbon dioxide emissions, and a decrease in the ecological footprint resulting from concrete production.

Comparison of Shelf-stable and Conventional Resuscitation Products in a Canine Model of Hemorrhagic Shock.

INTRODUCTION: Treatment of severe hemorrhagic shock typically involves hemostatic resuscitation with blood products. However, logistical constraints often hamper the wide distribution of commonly used blood products like whole blood. Shelf-stable blood products and blood substitutes are poised to be able to effectively resuscitate individuals in hemorrhagic shock when more conventional blood products are not readily available. METHODS: Purpose-bred adult dogs (n = 6) were anesthetized, instrumented, and subjected to hemorrhagic shock (MAP <50 mmHg or 40% blood volume loss). Then each dog was resuscitated with one of five resuscitation products: (1) lactated ringers solution and hetastarch (LRS/heta), (2) canine chilled whole blood (CWB), (3) fresh frozen plasma (FFP) and packed red blood cells (pRBC), (4) canine freeze-dried plasma (FDP) and hemoglobin-based oxygen carrier (HBOC), or (5) HBOC/FDP and canine lyophilized platelets (LyoPLT). Each dog was allowed to recover after the hemorrhage resuscitation event and was then subjected to another hemorrhage event and resuscitated with a different product until each dog was resuscitated with each product. RESULTS: At the time when animals were determined to be out of shock as defined by a shock index <1, MAP (mm Hg) values (mean ± standard error) were higher for FFP/pRBC (n = 5, 83.7 ± 4.5) and FDP/HBOC+LyoPLT (n = 4, 87.8. ± 2.1) as compared to WB (n = 4, 66.0 ± 13.1). A transient increase in creatinine was seen in dogs resuscitated with HBOC and FDP. Albumin and base excess increased in dogs resuscitated with HBOC and FDP products compared to LRS/heta and CWB (p < 0.01). CONCLUSION: Combinations of shelf-stable blood products compared favorably to canine CWB for resolution of shock. Further research is needed to ascertain the reliability and efficacy of these shelf-stable combinations of products in other models of hemorrhage that include a component of tissue damage as well as naturally occurring trauma. LEVEL OF EVIDENCE: This is a Therapeutic/Care management study with Level of Evidence IV.

Impact of Various Concentrations of Low-Dose Atropine on Pupillary Diameter and Accommodative Amplitude in Children with Myopia.

Purpose: To assess over 2 weeks, the effect of 3 different low concentrations of atropine on pupillary diameter and accommodative amplitude in children with myopia. Methods: Fifty-eight children with myopia [spherical equivalent (SE) of -0.50 diopters (D) or worse, astigmatism of less than or equal to 2.00 D] were randomly allocated to 3 groups receiving 0.01%, 0.02%, or 0.03% atropine eye drops, once nightly for 2 weeks. The primary outcome was the change from baseline in pupillary diameter and accommodative amplitude with each of the concentrations. Results: Fifty-seven participants (114 eyes), aged between 6 and 12 years, completed the 2-week trial (mean age 9.3 ± 1.7 years and mean SE -3.53 ± 1.79 D). After 2 weeks of use, all the 3 concentrations were found to have a statistically significant effect on both the pupillary diameter and accommodative amplitude. Accommodative amplitude reduced by an average of 5.23 D, 9.28 D, and 9.32 D, and photopic pupil size increased by an average of 0.95 ± 1.05 mm, 1.65 ± 0.93 mm, and 2.16 ± 0.88 mm with 0.01%, 0.02%, and 0.03%, respectively. Of the eyes, a total of 5.3% and 5.9% of the eyes on 0.02% and 0.03% atropine had a mean residual accommodative amplitude of <5 D. The percentage of eyes having a pupillary dilation >3 mm were 4.8%, 10.5%, and 23.5% for 0.01%, 0.02%, and 0.03% atropine, respectively. Conclusions: Low-dose atropine had an effect on pupillary diameter and accommodative amplitude. With the highest concentration assessed, that is, 0.03% nearly 1 of 4 eyes had pupillary dilation of >3 mm. Clinical Trial Registration number: NCT03699423.

Exploring Nonlinear Dynamics In Brain Functionality Through Phase Portraits And Fuzzy Recurrence Plots.

Much of the complexity and diversity found in nature are driven by nonlinear phenomena, and this holds true for the brain. Nonlinear dynamics theory has been successfully utilized in explaining brain functions from a biophysics standpoint, and the field of statistical physics continues to make substantial progress in understanding brain connectivity and function. This study delves into complex brain functional connectivity using biophysical nonlinear dynamics approaches. We aim to uncover hidden information in high-dimensional and nonlinear neural signals, with the hope of providing a useful tool for analyzing information transitions in functionally complex networks. By utilizing phase portraits and fuzzy recurrence plots, we investigated the latent information in the functional connectivity of complex brain networks. Our numerical experiments, which include synthetic linear dynamics neural time series and a biophysically realistic neural mass model, showed that phase portraits and fuzzy recurrence plots are highly sensitive to changes in neural dynamics, and they can also be used to predict functional connectivity based on structural connectivity. Furthermore, the results showed that phase trajectories of neuronal activity encode low-dimensional dynamics, and the geometric properties of the limit-cycle attractor formed by the phase portraits can be used to explain the neurodynamics. Additionally, our results showed that the phase portrait and fuzzy recurrence plots can be used as functional connectivity descriptors, and both metrics were able to capture and explain nonlinear dynamics behavior during specific cognitive tasks. In conclusion, our findings suggest that phase portraits and fuzzy recurrence plots could be highly effective as functional connectivity descriptors, providing valuable insights into nonlinear dynamics in the brain.

A 15-Year Experience With Total Anomalous Pulmonary Venous Connection in Vietnam.

BACKGROUND: This article aims to demonstrate the morphology of 261 total anomalous pulmonary venous connection (TAPVC) cases operated at Children's Hospital 1 with in-hospital mortality of 19.5% (51/261). METHODS: All the surgical protocols of TAPVC cases repaired between 2008 and June 2023 were reviewed. The descriptions of TAPVC were based on operative findings by surgeons. RESULTS: A total of 261 TAPVC patients were operated, including 124 (47.5%) supra, 83 (31.8%) intra, 41 (15.7%) infra, and 13 (5%) mixed cases. The in-hospital mortality was 19.5% (51/261). Fifteen cases are associated with other anomalies of the heart. Four subtypes of 124 supra TAPVC were found, with 42 (33.9%) obstructed cases. The standard was all pulmonary veins (PVs) forming a common vein (CV) and draining into the innominate veins, then going to the superior vena cava (SVC) (100/124, 80.6%). Eleven supra TAPVC cases were vascular vise type. Ten cases had the vertical vein running from the right of the CV and draining directly into the SVC. Of 83 intracardiac TAPVCs with 9 (10.8%) obstructed cases, the most common was all PVs draining directly into the coronary sinus (60/83, 72.3%). The second was all PVs draining directly into the right atrium (RA) via separated ostia or forming a CV before entering the RA (17/83, 20.5%). Also, there were three cases with rare variants and 100% obstruction when the diagnosis was explored. The in-hospital mortality of intracardiac type was 13.3% (11/83) 41 infra TAPVC with obstructed rate of 61% (25/41) and in-hospital mortality of 29.3% (12/41). Thirteen mixed TAPVCs were repaired, with most cases having three PVs forming a CV. CONCLUSION: This article provides valuable information about the morphology of TAPVC types in Asian patients.

Diagnosis of pathological speech with streamlined features for long short-term memory learning.

BACKGROUND: Pathological speech diagnosis is crucial for identifying and treating various speech disorders. Accurate diagnosis aids in developing targeted intervention strategies, improving patients' communication abilities, and enhancing their overall quality of life. With the rising incidence of speech-related conditions globally, including oral health, the need for efficient and reliable diagnostic tools has become paramount, emphasizing the significance of advanced research in this field. METHODS: This paper introduces novel features for deep learning in the analysis of short voice signals. It proposes the incorporation of time-space and time-frequency features to accurately discern between two distinct groups: Individuals exhibiting normal vocal patterns and those manifesting pathological voice conditions. These advancements aim to enhance the precision and reliability of diagnostic procedures, paving the way for more targeted treatment approaches. RESULTS: Utilizing a publicly available voice database, this study carried out training and validation using long short-term memory (LSTM) networks learning on the combined features, along with a data balancing strategy. The proposed approach yielded promising performance metrics: 90% accuracy, 93% sensitivity, 87% specificity, 88% precision, an F1 score of 0.90, and an area under the receiver operating characteristic curve of 0.96. The results surpassed those obtained by the networks trained using wavelet-time scattering coefficients, as well as several algorithms trained with alternative feature types. CONCLUSIONS: The incorporation of time-frequency and time-space features extracted from short segments of voice signals for LSTM learning demonstrates significant promise as an AI tool for the diagnosis of speech pathology. The proposed approach has the potential to enhance the accuracy and allow for real-time pathological speech assessment, thereby facilitating more targeted and effective therapeutic interventions.

Features and networks of the mandible on computed tomography.

The mandible or lower jaw is the largest and hardest bone in the human facial skeleton. Fractures of the mandible are reported to be a common facial trauma in emergency medicine and gaining insights into mandibular morphology in different facial types can be helpful for trauma treatment. Furthermore, features of the mandible play an important role in forensics and anthropology for identifying gender and individuals. Thus, discovering hidden information of the mandible can benefit interdisciplinary research. Here, for the first time, a method of artificial intelligence-based nonlinear dynamics and network analysis are used for discovering dissimilar and similar radiographic features of mandibles between male and female subjects. Using a public dataset of 10 computed tomography scans of mandibles, the results suggest a difference in the distribution of spatial autocorrelation between genders, uniqueness in network topologies among individuals and shared values in recurrence quantification.

Comparison of Rapid-, Kaolin-, and Native-TEG Parameters in Burn Patient Cohorts With Acute Burn-induced Coagulopathy and Abnormal Fibrinolytic Function.

Although use of thromboelastography (TEG) to diagnose coagulopathy and guide clinical decision-making is increasing, relative performance of different TEG methods has not been well-defined. Rapid-TEG (rTEG), kaolin-TEG (kTEG), and native-TEG (nTEG) were performed on blood samples from burn patients presenting to a regional center from admission to 21 days. Patients were categorized by burn severity, mortality, and fibrinolytic phenotypes (Shutdown [SD], Physiologic [PHYS], and Hyperfibrinolytic [HF]). Manufacturer ranges and published TEG cutoffs were examined. Concordance correlations (Rc) of TEG parameters (R, α-angle, maximum amplitude [MA], LY30) measured agreement and Cohen's Kappa (κ) determined interclass reliability. Patients (n = 121) were mostly male (n = 84; 69.4%), with median age 40 years, median TBSA burn 13%, and mortality 17% (n = 21). Severe burns (≥40% TBSA) were associated with lower admission α-angle for rTEG (P = .03) and lower MA for rTEG (P = .02) and kTEG (P = .01). MA was lower in patients who died (nTEG, P = .04; kTEG, P = .02; rTEG, P = .003). Admission HF was associated with increased mortality (OR, 10.45; 95% CI, 2.54-43.31, P = .001) on rTEG only. Delayed SD was associated with mortality using rTEG and nTEG (OR 9.46; 95% CI, 1.96-45.73; P = .005 and OR, 6.91; 95% CI, 1.35-35.48; P = .02). Admission TEGs showed poor agreement on R-time (Rc, 0.00-0.56) and α-angle (0.40 to 0.55), and moderate agreement on MA (0.67-0.81) and LY30 (0.72-0.93). Interclass reliability was lowest for R-time (κ, -0.07 to 0.01) and α-angle (-0.06 to 0.17) and highest for MA (0.22-0.51) and LY30 (0.29-0.49). Choice of TEG method may impact clinical decision-making. rTEG appeared most sensitive in parameter-specific associations with injury severity, abnormal fibrinolysis, and mortality.

An organismal understanding of C. elegans innate immune responses, from pathogen recognition to multigenerational resistance.

The nematode Caenorhabditis elegans has been a model for studying infection since the early 2000s and many major discoveries have been made regarding its innate immune responses. C. elegans has been found to utilize some key conserved aspects of immune responses and signaling, but new interesting features of innate immunity have also been discovered in the organism that might have broader implications in higher eukaryotes such as mammals. Some of the distinctive features of C. elegans innate immunity involve the mechanisms this bacterivore uses to detect infection and mount specific immune responses to different pathogens, despite lacking putative orthologs of many important innate immune components, including cellular immunity, the inflammasome, complement, or melanization. Even when orthologs of known immune factors exist, there appears to be an absence of canonical functions, most notably the lack of pattern recognition by its sole Toll-like receptor. Instead, recent research suggests that C. elegans senses infection by specific pathogens through contextual information, including unique products produced by the pathogen or infection-induced disruption of host physiology, similar to the proposed detection of patterns of pathogenesis in mammalian systems. Interestingly, C. elegans can also transfer information of past infection to their progeny, providing robust protection for their offspring in face of persisting pathogens, in part through the RNAi pathway as well as potential new mechanisms that remain to be elucidated. Altogether, some of these strategies employed by C. elegans share key conceptual features with vertebrate adaptive immunity, as the animal can differentiate specific microbial features, as well as propagate a form of immune memory to their offspring.

A ß-barrel-like tetramer formed by a ß-hairpin derived from Aß.

ß-Hairpins formed by the ß-amyloid peptide Aß are building blocks of Aß oligomers. Three different alignments of ß-hairpins have been observed in the structures of Aß oligomers or fibrils. Differences in ß-hairpin alignment likely contribute to the heterogeneity of Aß oligomers and thus impede their study at high-resolution. Here, we designed, synthesized, and studied a series of ß-hairpin peptides derived from Aß12-40 in one of these three alignments and investigated their solution-phase assembly and folding. These assays reveal the formation of tetramers and octamers that are stabilized by intermolecular hydrogen bonding interactions between Aß residues 12-14 and 38-40 as part of an extended ß-hairpin conformation. X-ray crystallographic studies of one peptide from this series reveal the formation of ß-barrel-like tetramers and octamers that are stabilized by edge-to-edge hydrogen bonding and hydrophobic packing. Dye-leakage and caspase 3/7 activation assays using tetramer and octamer forming peptides from this series reveal membrane-damaging and apoptotic properties. A molecular dynamics simulation of the ß-barrel-like tetramer embedded in a lipid bilayer shows membrane disruption and water permeation. The tetramers and octamers described herein provide additional models of how Aß may assemble into oligomers and supports the hypothesis that ß-hairpin alignment and topology may contribute directly to oligomer heterogeneity.

Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients.

BACKGROUND: Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistochemical images, to predict the 5-year survival time of two patient groups: one with preoperative radiotherapy and one without. METHODS: The utilization of deep convolutional neural networks in medical research, particularly in clinical cancer studies, has been gaining substantial attention. This success primarily stems from their ability to extract intricate image features that prove invaluable in machine learning. Another innovative method for extracting features at multiple levels is the wavelet-scattering network. Our study combines the strengths of these two convolution-based approaches to robustly extract image features related to protein expression. RESULTS: The efficacy of our approach was evaluated across various tissue types, including tumor, biopsy, metastasis, and adjacent normal tissue. Statistical assessments demonstrated exceptional performance across a range of metrics, including prediction accuracy, classification accuracy, precision, and the area under the receiver operating characteristic curve. CONCLUSION: These results underscore the potential of dual convolutional learning to assist clinical researchers in the timely validation and discovery of cancer biomarkers.

Transforming stress program on medical students' stress mindset and coping strategies: a quasi-experimental study.

OBJECTIVE: Stress is a significant concern in medical education, and identifying effective ways to deal with stress may help with students' mental health and professional development. This study aimed to examine the effects of the Transforming Stress Program (TSP) amongst first-year medical students on their stress mindset and coping strategies when confronted with stressors. METHODS: We conducted a quasi-experimental study at the University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam. A total of 409 first-year students at the Faculty of Medicine were divided into intervention group (205 students) and control group (204 students). The 10-week TSP was delivered as an extra-curricular course. The training adopts psychoeducation based on Dialectical Behavioral Therapy with mindfulness as a fundamental practice incorporated into each component of the program. The intervention group received the training in the first semester; the control group received identical program in the second semester. Stress Mindset Measurement and Brief Coping Orientation to Problems Experienced were measured before the intervention (T0), immediately after intervention on Intervention group (T1), and six months after intervention on Intervention group (T2). RESULTS: At T1, the intervention group showed 65% improvements in stress mindset scores and increases in coping strategies scores in six domains (Problem solving, Social support, Humor, Religion, Venting, and Self-distraction) and decreases in three (Avoidance, Substance use, and Self-blame). The effect sizes were significant in all outcomes (Cohen's d > 0.2). Measurements of the control group did not change significantly in the same period. At T2, effects of the TSP were found decreased in some domains (Avoidance, Substance use, and Self-blame) compared to T1, but largely remained significantly better than T0. CONCLUSIONS: The TSP is a feasible and effective approach that significantly enhanced medical students' stress mindset and coping strategies. Some effects were still observable 6 months after the intervention. The relatively intensive intervention requires support of the school administration and staff.

Genomic and phenotypic evolution of nematode-infecting microsporidia.

Microsporidia are a large phylum of intracellular parasites that can infect most types of animals. Species in the Nematocida genus can infect nematodes including Caenorhabditis elegans, which has become an important model to study mechanisms of microsporidia infection. To understand the genomic properties and evolution of nematode-infecting microsporidia, we sequenced the genomes of nine species of microsporidia, including two genera, Enteropsectra and Pancytospora, without any previously sequenced genomes. Core cellular processes, including metabolic pathways, are mostly conserved across genera of nematode-infecting microsporidia. Each species encodes unique proteins belonging to large gene families that are likely used to interact with host cells. Most strikingly, we observed one such family, NemLGF1, is present in both Nematocida and Pancytospora species, but not any other microsporidia. To understand how Nematocida phenotypic traits evolved, we measured the host range, tissue specificity, spore size, and polar tube length of several species in the genus. Our phylogenetic analysis shows that Nematocida is composed of two groups of species with distinct traits and that species with longer polar tubes infect multiple tissues. Together, our work details both genomic and trait evolution between related microsporidia species and provides a useful resource for further understanding microsporidia evolution and infection mechanisms.

Assessment of ethynylestradiol-3-sulfate on coagulation, metabolism, and survival in pigs with traumatic hemorrhage.

BACKGROUND: The beneficial effects of estrogens on survival from hemorrhage have been suggested in some preclinical models. This study investigated the effects of ethynylestradiol-3-sulfate (EE-3-S) on coagulation, metabolism and survival in pigs following traumatic hemorrhage. METHODS: Twenty-six pigs were randomized into: normal saline group (NS, n = 10), EE-3-S group (EE-3, n = 11) groups, and no resuscitation group (NR, n = 5). Femur fracture was performed in each pig's left leg, followed by hemorrhage of 55% of estimated blood volume and a 10-minute shock period. Afterward, pigs were resuscitated with a small volume of either NS alone (4 mL/kg) or EE-3-S with NS (1 mL/kg at concentration of 1 mg/mL, plus NS solution of 3 mL/kg). Pigs in NR group were not resuscitated with any fluid. All pigs were then monitored for 6 hours or until death, with hemodynamics and survival times recorded. Blood samples were taken during the study for measurements of oxygen metabolism (oxygen delivery, extraction, and consumption) and coagulation function (using Rotem with Extem reagents). RESULTS: All baseline measurements were similar among the three groups. In the NS group, femur fracture and hemorrhage immediately reduced mean arterial pressure (MAP, 74 ± 3 mm Hg to 44 ± 4 mm Hg) and increased heart rate (97 ± 5 bpm to 218 ± 14 bpm, both p < 0.05). Similar changes in MAP and heart rate were observed in the EE-3 and NR groups. There were no differences observed in changes of Rotem ® measurements or oxygen metabolism among the groups during the study. At 6 hours, four pigs in NS, four pigs in EE-3-S, and two pigs in the NR group survived to the end of the study. The mean survival times were similar among the NS (212 ± 43 minutes), EE-3 (212 ± 39 minutes), and NR (223 ± 63 minutes) groups ( p = 0.9845). CONCLUSION: Following severe traumatic hemorrhage, hypotensive resuscitation with EE-3-S did not impact coagulation, metabolism, or survival in pigs.

Inhalation Injury Severity Score on Admission Predicts Overall Survival in Burn Patients.

Inhalation injury is diagnosed in up to one-third of burn patients and is associated with increased morbidity and mortality. There are multiple scoring systems to grade inhalation injury, but no study has evaluated the ability of these scoring systems to predict outcomes of interest such as overall survival. We conducted a prospective, observational study of 99 intubated burn patients who underwent fiberoptic bronchoscopy within 24 hr of admission and graded inhalation injury using three scoring systems: abbreviated injury score (AIS), inhalation injury severity score (I-ISS), and mucosal score (MS). Agreement between scoring systems was assessed with Krippendorff's alpha (KA). Multivariable analyses were conducted to determine if variables were associated with overall survival. At admission, median AIS, I-ISS, and MS scores were 2 for all scoring systems. Patients who died had higher overall injury burden than those who survived and had similar median admission AIS and MS scores, but higher I-ISS scores. There was strong correlation between the inhalation injury grade at admission using the three scoring systems (KA = 0.85). On regression analysis, the only scoring system independently associated with overall survival was I-ISS (score 3 compared to scores 1-2: OR 13.16, 95% CI 1.65-105.07; P = .02). Progression of injury after initial assessment may contribute to the poor correlation between admission score and overall survival for injuries graded with AIS and MS. Repeated assessment may more accurately identify patients at increased risk for mortality.

Superiority of compensatory reserve measurement compared with the Shock index for early and accurate detection of reduced central blood volume status.

BACKGROUND: Shock index (SI) equals the ratio of heart rate (HR) to systolic blood pressure (SBP) with clinical evidence that it is more sensitive for trauma patient status assessment and prediction of outcome compared with either HR or SBP alone. We used lower body negative pressure (LBNP) as a human model of central hypovolemia and compensatory reserve measurement (CRM) validated for accurate tracking of reduced central blood volume to test the hypotheses that SI: (1) presents a late signal of central blood volume status; (2) displays poor sensitivity and specificity for predicting the onset of hemodynamic decompensation; and (3) cannot identify individuals at greatest risk for the onset of circulatory shock. METHODS: We measured HR, SBP, and CRM in 172 human subjects (19-55 years) during progressive LBNP designed to determine tolerance to central hypovolemia as a model of hemorrhage. Subjects were subsequently divided into those with high tolerance (HT) (n = 118) and low tolerance (LT) (n = 54) based on completion of 60 mm Hg LBNP. The time course relationship between SI and CRM was determined and receiver operating characteristic (ROC) area under the curve (AUC) was calculated for sensitivity and specificity of CRM and SI to predict hemodynamic decompensation using clinically defined thresholds of 40% for CRM and 0.9 for SI. RESULTS: The time and level of LBNP required to reach a SI = 0.9 (~60 mm Hg LBNP) was significantly greater ( p < 0.001) compared with CRM that reached 40% at ~40 mm Hg LBNP. Shock index did not differ between HT and LT subjects at 45 mm Hg LBNP levels. ROC AUC for CRM was 0.95 (95% CI = 0.94-0.97) compared with 0.91 (0.89-0.94) for SI ( p = 0.0002). CONCLUSION: Despite high sensitivity and specificity, SI delays time to detect reductions in central blood volume with failure to distinguish individuals with varying tolerances to central hypovolemia. LEVEL OF EVIDENCE: Diagnostic Test or Criteria; Level III.

Prediction of Five-Year Survival Rate for Rectal Cancer Using Markov Models of Convolutional Features of RhoB Expression on Tissue Microarray.

The ability to predict survival in cancer is clinically important because the finding can help patients and physicians make optimal treatment decisions. Artificial intelligence in the context of deep learning has been increasingly realized by the informatics-oriented medical community as a powerful machine-learning technology for cancer research, diagnosis, prediction, and treatment. This paper presents the combination of deep learning, data coding, and probabilistic modeling for predicting five-year survival in a cohort of patients with rectal cancer using images of RhoB expression on biopsies. Using about one-third of the patients' data for testing, the proposed approach achieved 90% prediction accuracy, which is much higher than the direct use of the best pretrained convolutional neural network (70%) and the best coupling of a pretrained model and support vector machines (70%).

Behavioral and Transcriptome Profiling of Heterozygous Rab10 Knock-Out Mice.

A central question in the field of aging research is to identify the cellular and molecular basis of neuroresilience. One potential candidate is the small GTPase, Rab10. Here, we used Rab10+/- mice to investigate the molecular mechanisms underlying Rab10-mediated neuroresilience. Brain expression analysis of 880 genes involved in neurodegeneration showed that Rab10+/- mice have increased activation of pathways associated with neuronal metabolism, structural integrity, neurotransmission, and neuroplasticity compared with their Rab10+/+ littermates. Lower activation was observed for pathways involved in neuroinflammation and aging. We identified and validated several differentially expressed genes (DEGs), including Stx2, Stx1b, Vegfa, and Lrrc25 (downregulated) and Prkaa2, Syt4, and Grin2d (upregulated). Behavioral testing showed that Rab10+/- mice perform better in a hippocampal-dependent spatial task (object in place test), while their performance in a classical conditioning task (trace eyeblink classical conditioning, TECC) was significantly impaired. Therefore, our findings indicate that Rab10 differentially controls the brain circuitry of hippocampal-dependent spatial memory and higher-order behavior that requires intact cortex-hippocampal circuitry. Transcriptome and biochemical characterization of these mice suggest that glutamate ionotropic receptor NMDA type subunit 2D (GRIN2D or GluN2D) is affected by Rab10 signaling. Further work is needed to evaluate whether GRIN2D mediates the behavioral phenotypes of the Rab10+/- mice. We conclude that Rab10+/- mice described here can be a valuable tool to study the mechanisms of resilience in Alzheimer's disease (AD) model mice and to identify novel therapeutical targets to prevent cognitive decline associated with normal and pathologic aging.

Classification of Motor-Imagery Tasks using a Large EEG Dataset by Fusing Classifiers Learning on Wavelet-Scattering Features.

Brain-computer or brain-machine interface technology allows humans to control machines using their thoughts via brain signals. In particular, these interfaces can assist people with neurological diseases for speech understanding or physical disabilities for operating devices such as wheelchairs. Motor-imagery tasks play a basic role in brain-computer interfaces. This study introduces an approach for classifying motor-imagery tasks in a brain-computer interface environment, which remains a challenge for rehabilitation technology using electroencephalogram sensors. Methods used and developed for addressing the classification include wavelet time and image scattering networks, fuzzy recurrence plots, support vector machines, and classifier fusion. The rationale for combining outputs from two classifiers learning on wavelet-time and wavelet-image scattering features of brain signals, respectively, is that they are complementary and can be effectively fused using a novel fuzzy rule-based system. A large-scale challenging electroencephalogram dataset of motor imagery-based brain-computer interface was used to test the efficacy of the proposed approach. Experimental results obtained from within-session classification show the potential application of the new model that achieves an improvement of 7% in classification accuracy over the best existing classifier using state-of-the-art artificial intelligence (76% versus 69%, respectively). For the cross-session experiment, which imposes a more challenging and practical classification task, the proposed fusion model improves the accuracy by 11% (54% versus 65%). The technical novelty presented herein and its further exploration are promising for developing a reliable sensor-based intervention for assisting people with neurodisability to improve their quality of life.