Direct measurement of dynamic attractant gradients reveals breakdown of the Patlak-Keller-Segel chemotaxis model.

Chemotactic bacteria not only navigate chemical gradients, but also shape their environments by consuming and secreting attractants. Investigating how these processes influence the dynamics of bacterial populations has been challenging because of a lack of experimental methods for measuring spatial profiles of chemoattractants in real time. Here, we use a fluorescent sensor for aspartate to directly measure bacterially generated chemoattractant gradients during collective migration. Our measurements show that the standard Patlak-Keller-Segel model for collective chemotactic bacterial migration breaks down at high cell densities. To address this, we propose modifications to the model that consider the impact of cell density on bacterial chemotaxis and attractant consumption. With these changes, the model explains our experimental data across all cell densities, offering insight into chemotactic dynamics. Our findings highlight the significance of considering cell density effects on bacterial behavior, and the potential for fluorescent metabolite sensors to shed light on the complex emergent dynamics of bacterial communities.

Robots as models of evolving systems.

Experimental robobiological physics can bring insights into biological evolution. We present a development of hybrid analog/digital autonomous robots with mutable diploid dominant/recessive 6-byte genomes. The robots are capable of death, rebirth, and breeding. We map the quasi-steady-state surviving local density of the robots onto a multidimensional abstract "survival landscape." We show that robot death in complex, self-adaptive stress landscapes proceeds by a general lowering of the robotic genetic diversity, and that stochastically changing landscapes are the most difficult to survive.

Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back Pain.

Machine learning (ML) algorithms are crucial within the realm of healthcare applications. However, a comprehensive assessment of the effectiveness of regression algorithms in predicting alterations in lifting movement patterns has not been conducted. This research represents a pilot investigation using regression-based machine learning techniques to forecast alterations in trunk, hip, and knee movements subsequent to a 12-week strength training for people who have low back pain (LBP). The system uses a feature extraction algorithm to calculate the range of motion in the sagittal plane for the knee, trunk, and hip and 12 different regression machine learning algorithms. The results show that Ensemble Tree with LSBoost demonstrated the utmost accuracy in prognosticating trunk movement. Meanwhile, the Ensemble Tree approach, specifically LSBoost, exhibited the highest predictive precision for hip movement. The Gaussian regression with the kernel chosen as exponential returned the highest prediction accuracy for knee movement. These regression models hold the potential to significantly enhance the precision of visualisation of the treatment output for individuals afflicted with LBP.

Model-Free Measurement of Local Entropy Production and Extractable Work in Active Matter.

Time-reversal symmetry breaking and entropy production are universal features of nonequilibrium phenomena. Despite its importance in the physics of active and living systems, the entropy production of systems with many degrees of freedom has remained of little practical significance because the high dimensionality of their state space makes it difficult to measure. Here we introduce a local measure of entropy production and a numerical protocol to estimate it. We establish a connection between the entropy production and extractability of work in a given region of the system and show how this quantity depends crucially on the degrees of freedom being tracked. We validate our approach in theory, simulation, and experiments by considering systems of active Brownian particles undergoing motility-induced phase separation, as well as active Brownian particles and E.coli in a rectifying device in which the time-reversal asymmetry of the particle dynamics couples to spatial asymmetry to reveal its effects on a macroscopic scale.

Machine Learning Derived Lifting Techniques and Pain Self-Efficacy in People with Chronic Low Back Pain.

This paper proposes an innovative methodology for finding how many lifting techniques people with chronic low back pain (CLBP) can demonstrate with camera data collected from 115 participants. The system employs a feature extraction algorithm to calculate the knee, trunk and hip range of motion in the sagittal plane, Ward's method, a combination of K-means and Ensemble clustering method for classification algorithm, and Bayesian neural network to validate the result of Ward's method and the combination of K-means and Ensemble clustering method. The classification results and effect size show that Ward clustering is the optimal method where precision and recall percentages of all clusters are above 90, and the overall accuracy of the Bayesian Neural Network is 97.9%. The statistical analysis reported a significant difference in the range of motion of the knee, hip and trunk between each cluster, F (9, 1136) = 195.67, p < 0.0001. The results of this study suggest that there are four different lifting techniques in people with CLBP. Additionally, the results show that even though the clusters demonstrated similar pain levels, one of the clusters, which uses the least amount of trunk and the most knee movement, demonstrates the lowest pain self-efficacy.

Emergent Field-Driven Robot Swarm States.

We present an ecology-inspired form of active matter consisting of a robot swarm. Each robot moves over a planar dynamic resource environment represented by a large light-emitting diode array in search of maximum light intensity; the robots deplete (dim) locally by their presence the local light intensity and seek maximum light intensity. Their movement is directed along the steepest local light intensity gradient; we call this emergent symmetry breaking motion "field drive." We show there emerge dynamic and spatial transitions similar to gas, crystalline, liquid, glass, and jammed states as a function of robot density, resource consumption rates, and resource recovery rates. Paradoxically the nongas states emerge from smooth, flat resource landscapes, not rough ones, and each state can directly move to a glassy state if the resource recovery rate is slow enough, at any robot density.

Emergence of Escherichia coli critically buckled motile helices under stress.

Bacteria under external stress can reveal unexpected emergent phenotypes. We show that the intensely studied bacterium Escherichia coli can transform into long, highly motile helical filaments poized at a torsional buckling criticality when exposed to minimum inhibitory concentrations of several antibiotics. While the highly motile helices are physically either right- or left-handed, the motile helices always rotate with a right-handed angular velocity [Formula: see text], which points in the same direction as the translational velocity [Formula: see text] of the helix. Furthermore, these helical cells do not swim by a "run and tumble" but rather synchronously flip their spin [Formula: see text] and thus translational velocity-backing up rather than tumbling. By increasing the translational persistence length, these dynamics give rise to an effective diffusion coefficient up to 20 times that of a normal E. coli cell. Finally, we propose an evolutionary mechanism for this phenotype's emergence whereby the increased effective diffusivity provides a fitness advantage in allowing filamentous cells to more readily escape regions of high external stress.

It doesn't always pay to be fit: success landscapes.

Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.

Biodegradation of natural rubber and deproteinized natural rubber by enrichment bacterial consortia.

This study examined the biodegradation of natural rubber (NR) and deproteinized natural rubber (DPNR) by bacterial consortia enriched from a rubber-processing factory's waste in Vietnam. The results reveal the degradation in both NR and DPNR, and the DPNR was degraded easier than NR. The highest weight loss of 48.37% was obtained in the fourth enrichment consortium with DPNR, while 35.39% was obtained in the fifth enrichment consortium with NR after 14 days of incubation. Nitrogen content and fatty acid content determined by Kjeldahl method and fourier transform infrared spectroscopy (FTIR), respectively, were decreased significantly after being incubated with the consortia. Structure of degraded rubber film analyzed by nuclear magnetic resonance spectroscopy showed the presence of aldehyde group, a sign of rubber degradation. Bacterial cells tightly adhering and embedding into NR and DPNR films were observed by scanning electron microscopy. There were differences in the bacterial composition of the consortia with NR and DPNR, which were determined by metagenomic analysis using 16S rRNA gene sequencing. The phyla Bacteroidetes and Proteobacteria may play a role in the degradation of non-isoprene compounds such as protein or lipid, while the phylum Actinobacteria plays a crucial role in the degradation of rubber hydrocarbon in all consortia.

A Self-Powered and Low Pressure Loss Gas Flowmeter Based on Fluid-Elastic Flutter Driven Triboelectric Nanogenerator.

A self-powered and low pressure loss gas flowmeter is presently proposed and developed based on a membrane's flutter driven triboelectric nanogenerator (TENG). Such a flowmeter, herein named "TENG flowmeter", is made of a circular pipe in which two copper electrodes are symmetrically fixed and a nonconductive, thin membrane is placed in the middle plane of the pipe. When a gas flows through the pipe at a sufficiently high speed, the membrane will continuously oscillate between the two electrodes, generating a periodically fluctuating electric voltage whose frequency can be easily measured. As demonstrated experimentally, the fluctuation frequency (fF) relates linearly with the pipe flow mean velocity (Um), i.e., fF Um; therefore, the volume flow rate Q (=Um A) = C1fF + C2, where C1 and C2 are experimental constants and A is the pipe cross-sectional area. That is, by the TENG flowmeter, the pipe flow rate Q can be obtained by measuring the frequency fF. Notably, the TENG flowmeter has several advantages over some commercial flowmeters (e.g., vortex flowmeter), such as considerable lower pressure loss, higher sensitiveness of the measured flow rate, and self-powering. In addition, the effects of membrane material and geometry as well as flow moisture on the flowmeter are investigated. Finally, the performance of the TENG flowmeter is demonstrated.

Microfluidic Ecology Unravels the Genetic and Ecological Drivers of T4r Bacteriophage Resistance in E. coli: Insights into Biofilm-Mediated Evolution.

We use a microfluidic ecology which generates non-uniform phage concentration gradients and micro-ecological niches to reveal the importance of time, spatial population structure and collective population dynamics in the de novo evolution of T4r bacteriophage resistant motile E. coli. An insensitive bacterial population against T4r phage occurs within 20 hours in small interconnected population niches created by a gradient of phage virions, driven by evolution in transient biofilm patches. Sequencing of the resistant bacteria reveals mutations at the receptor site of bacteriophage T4r as expected but also in genes associated with biofilm formation and surface adhesion, supporting the hypothesis that evolution within transient biofilms drives de novo phage resistance.

Machine Learning Derived Lifting Technique in People without Low Back Pain.

This paper presents a method for determining the number of lifting techniques used by healthy individuals through the analysis of kinematic data collected from 115 participants utilizing an motion capture system. The technique utilizes a combination of feature extraction and Ward's method to analyse the range of motion in the sagittal plane of the knee, hip, and trunk. The findings identified five unique lifting techniques in people without low back pain. The multivariate analysis of variance statistical analysis reveals a significant difference in the range of motion in the trunk, hip and knee between each cluster for healthy people (F (12, 646) = 125.720, p < 0.0001).Clinical Relevance- This information can assist healthcare professionals in choosing effective treatments and interventions for those with occupational lower back pain by focusing rehabilitation on specific body parts associated with problematic lifting techniques, such as the trunk, hip, or knee, which may lead to improved pain and disability outcomes, exemplifying precision medicine.

Direct measurement of dynamic attractant gradients reveals breakdown of the Patlak-Keller-Segel chemotaxis model.

Chemotactic bacteria not only navigate chemical gradients, but also shape their environments by consuming and secreting attractants. Investigating how these processes influence the dynamics of bacterial populations has been challenging because of a lack of experimental methods for measuring spatial profiles of chemoattractants in real time. Here, we use a fluorescent sensor for aspartate to directly measure bacterially generated chemoattractant gradients during collective migration. Our measurements show that the standard Patlak-Keller-Segel model for collective chemotactic bacterial migration breaks down at high cell densities. To address this, we propose modifications to the model that consider the impact of cell density on bacterial chemotaxis and attractant consumption. With these changes, the model explains our experimental data across all cell densities, offering new insight into chemotactic dynamics. Our findings highlight the significance of considering cell density effects on bacterial behavior, and the potential for fluorescent metabolite sensors to shed light on the complex emergent dynamics of bacterial communities.

Amniotic band syndrome leading to severe malformations of the newborn: a case report at Tu Du Hospital, Vietnam, and literature review.

Amniotic band syndrome (ABS) refers to fibrous bands that appear to entangle various fetal parts in utero, leading to deformation, malformation, or disruption. To alleviate implementation of this diverse malformation, an early diagnosis on ultrasound is necessary to explain to the patient, thus, avoiding psychological shock and requiring timely intervention. Case Presentation: In the present case report, the authors describe a case of ABS that was diagnosed at the time of delivery at full term. Although the male newborn was alive, the infant underwent the distal deformity of amputated limbs and clubfoot. He has currently been followed up for the reconstruction treatment. Clinical Discussion: ABS remains a challenging diagnosis for obstetricians following the onset timepoint. A prenatal ultrasound scan is carefully required to detect the morphologic abnormalities of the fetus. Postnatal management should be integrated by a multidisciplinary team in order to improve the infant's outcome. Conclusion: ABS is an extremely dangerous entity during pregnancy, which leads to poor outcomes for the infant. An early detection on ultrasound helps in preparing better for the acceptance of the mother and the family as well as the prognosis afterwards.

Clinical Features and the Outcome Evaluations of Keloid and Hypertrophic Scar Treatment with Triamcinolone Injection in Mekong Delta, Vietnam - A Cross-Sectional Study.

Background: Excessive scarring is a common problem that can have significant cosmetic and psychological consequences for patients. Intralesional injection therapy, such as the use of triamcinolone, has emerged as an effective treatment option for hypertrophic scars. The objective of this study was to describe the morphological features of hypertrophic scars, categorize them, and evaluate the efficacy of triamcinolone injection therapy in treating these scars. Materials and Methods: A cross-sectional descriptive study of 80 patients with hypertrophic scars treated with triamcinolone intralesional injection at Can Tho University of Medicine and Pharmacy Hospital from 5/2018 to 5/2021. Results: There were 80 patients in all, with a male/female ratio of 1/1.05 and a median age of 15-35. There were 129 scars in all, with scar age >1 year accounting for 83%, keloid scars accounting for 64%, and hypertrophic scars accounting for the remaining 36%. Scars are most commonly seen on the trunk, accounting for 53.5% of all scars, particularly on the anterior chest wall. When the source of scars was discovered, trauma and acne accounted for 24% and 23%, respectively, while the rest were predominantly spontaneous scars, accounting for 49%. Scarring and discomfort of mild to moderate severity were common clinical symptoms; scars larger than 5cm in size had more symptoms than scars smaller than 5cm. Prior to the therapy, the mean Vancouver Score Scale-VSS was 6.55±2.13. After 24 weeks of the therapy, 96.7% of patients had entirely improved itching symptoms, 75% had completely improved pain, and 25% still had minimal pain. After therapy, the mean Vancouver Score Scale-VSS was 2.55±1.81 (p<0.05). At week 24, 3.75% of patients experienced skin shrinkage, 3.75% experienced depigmentation, and 13.75% experienced vasodilation. Conclusion: Triamcinolone intralesional injection should be utilized as a first-line therapy for hypertrophic scarring.

Protein dynamics implications of the low- and high-temperature denaturation of myoglobin.

We reinvestigate a simple model used in the literature concerning the thermodynamic analysis of protein cold denaturation. We derive an exact thermodynamic expression for cold denaturation and give a better approximation than exists in the literature for predicting cold denaturation temperatures in the two-state model. We discuss the "dark-side" implications of this work for previous temperature-dependent protein dynamics experiments and discuss microfluidic experimental technologies, which could explore the thermal stability range of proteins below the bulk freezing point of water.

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge.

To better understand early brain development in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods have achieved state-of-the-art performance; h owever, one of the major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners. To promote methodological development in the community, the iSeg-2019 challenge (http://iseg2019.web.unc.edu) provides a set of 6-month infant subjects from multiple sites with different protocols/scanners for the participating methods. T raining/validation subjects are from UNC (MAP) and testing subjects are from UNC/UMN (BCP), Stanford University, and Emory University. By the time of writing, there are 30 automatic segmentation methods participated in the iSeg-2019. In this article, 8 top-ranked methods were reviewed by detailing their pipelines/implementations, presenting experimental results, and evaluating performance across different sites in terms of whole brain, regions of interest, and gyral landmark curves. We further pointed out their limitations and possible directions for addressing the multi-site issue. We find that multi-site consistency is still an open issue. We hope that the multi-site dataset in the iSeg-2019 and this review article will attract more researchers to address the challenging and critical multi-site issue in practice.

Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios Predict All-Cause Mortality in Acute Pulmonary Embolism.

The aim of this study was to investigate the utility of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) to predict all-cause mortality in patients presenting with acute pulmonary embolism (PE). Three hundred consecutive patients with acute PE between March 2016 and December 2018 were retrospectively analyzed. We identified 191 patients who met the study inclusion criteria. Twenty-eight patients died during the study period. There was a significant difference in PLR, but not NLR, between patients with low risk, submassive, and massive risk PE (P = .02 and P = .58, respectively, by the Kruskal-Wallis test). Elevated NLR and PLR were associated with all-cause mortality (P < .01 and P < .01, respectively). Neutrophil-to-lymphocyte ratio of 5.46 was associated with all-cause mortality with sensitivity of 75.0% and specificity of 66.9% (area under the curve [AUC]: 0.692 [95% confidence interval, CI]: 0.568-0.816); P < .01). Platelet-to-lymphocyte ratio of 256.6 was associated with all-cause mortality with sensitivity of 53.6% and specificity of 82.2% (AUC: 0.693 [95% CI: 0.580-0.805]; P < .01). Neutrophil-to-lymphocyte ratio and PLR are simple biomarkers that are readily available from routine laboratory values and may be useful components of PE risk prediction models.

Characterisation of point mutations in domain V of the 23S rRNA gene of clinical Helicobacter pylori strains and clarithromycin-resistant phenotype in central Vietnam.

OBJECTIVES: The prevalence of clarithromycin (CLR)-resistant Helicobacter pylori is increasing worldwide, including in Vietnam. The aims of this study were to determine point mutations in the 23S rRNA domain V of clinical H. pylori strains in central Vietnam, to estimate the prevalence of phenotypic CLR resistance and to assess the association between 23S rRNA domain V genotype and CLR-resistant phenotype. METHODS: Sequencing of the 23S rRNA domain V of H. pylori strains from gastric biopsy specimens was performed for 185 patients with H. pylori-positive chronic gastritis, of which 104 samples were subjected to susceptibility testing to determine CLR resistance. RESULTS: A total of 24 types of point mutation were detected. A2143G and A2142G mutations were observed in 40.5% and 4.3%, respectively. New point mutations were detected (C2041T, C2083T, C2191T, G2220A, G2225A, G2240A, C2273T, T2276C, G2287A, C2399T, A2445G and C2622T). 23S rRNA domain V genotypes were diversified, with combinations of two or more point mutations as well as single point mutations. The rate of phenotypic CLR resistance was 53.8%, increasing from 40.4% in 2012-2014 to 70.2% in 2015-2017 (P=0.0045). A2143G and A2142G accounted for 89.3% of phenotypically CLR-resistant H. pylori isolates. CONCLUSIONS: A diversity of point mutations in the 23S rRNA domain V was observed in clinical H. pylori isolates. The rate of phenotypically CLR-resistant H. pylori is significantly increasing in central Vietnam. Further research is necessary to clarify the role of the combination of 23S rRNA domain V mutations in the molecular mechanism of CLR resistance.

Biomarkers of Inflammation, Thrombogenesis, and Collagen Turnover in Patients With Atrial Fibrillation.

The purpose of this study was to determine whether there are any differences in the levels of inflammatory, thrombotic, and collagen turnover biomarkers between individuals with atrial fibrillation (AF) and healthy volunteers. Circulating plasma levels of plasminogen activator inhibitor 1 (PAI-1), CD40-ligand (CD40-L), nucleosomes (which are indicators of cell death), C-reactive protein (CRP), procollagen III N-terminal propeptide (PIIINP), procollagen III C-terminal propeptide (PIIICP), procollagen I N-terminal propeptide, tissue plasminogen activator, and von Willebrand factor were analyzed as potential biomarkers of AF. Baseline plasma was collected from patients with AF prior to ablation surgery at Loyola University Medical Center. Individuals with AF had statistically significantly increased levels of PAI-1, CD40-L, and nucleosomes, when compared to the normal population ( P < .0001). Additionally, there was a statistically significant increase in the CRP ( P = .01), PIIINP ( P = .04), and PIIICP ( P = .0008) when compared to normal individuals. From this study, it is concluded that the prothrombotic, inflammatory, and collagen turnover biomarkers PAI-1, CD40-L, nucleosomes, CRP, PIIICP, and PIIINP are elevated in AF.