Different symmetries, different mechanisms.

Three common symmetries exist in the natural visual world: (i) mirror symmetry, i.e., reflections around a vertical axis, (ii) radial symmetry, i.e., rotations around a point, and (iii) translational symmetry, i.e., shifted repetitions. Are these processed by a common class of visual mechanism? Using stimuli comprising arrays of Gaussian blobs we examined this question using a visual search protocol in which observers located a single symmetric target patch among varying numbers of random-blob distractor patches. The testing protocol used a blocked present/absent task and both search times and accuracy were recorded. Search times for mirror and radial symmetry increased significantly with the number of distractors, as did translational-symmetry patterns containing few repetitions. However translational-symmetry patterns with four repeating sectors produced search slopes close to zero. Fourier analysis revealed that, as with images of natural scenes, the structural information in both mirror- and radial-symmetric patterns is carried by the phase spectrum. However, for translational patterns with four repeating sectors, the amplitude spectrum appears to capture the structure, consistent with previous analyses of texture regularity. Modeling revealed that while the mirror and radial patterns produced an approximately Gaussian-shaped energy response profile as a function of spatial frequency, the translational pattern profiles contained a distinctive spike, the magnitude of which increased with the number of repeating sectors. We propose distinct mechanisms for the detection of different symmetry types: a mechanism that encodes local positional information to detect mirror- and radial-symmetric patterns and a mechanism that computes energy in narrowband filters for the detection of translational symmetry containing many sectors.

Fast Healthcare Interoperability Resources for Inpatient Deterioration Detection With Time-Series Vital Signs: Design and Implementation Study.

BACKGROUND: Vital signs have been widely adopted in in-hospital cardiac arrest (IHCA) assessment, which plays an important role in inpatient deterioration detection. As the number of early warning systems and artificial intelligence applications increases, health care information exchange and interoperability are becoming more complex and difficult. Although Health Level 7 Fast Healthcare Interoperability Resources (FHIR) have already developed a vital signs profile, it is not sufficient to support IHCA applications or machine learning-based models. OBJECTIVE: In this paper, for IHCA instances with vital signs, we define a new implementation guide that includes data mapping, a system architecture, a workflow, and FHIR applications. METHODS: We interviewed 10 experts regarding health care system integration and defined an implementation guide. We then developed the FHIR Extract Transform Load to map data to FHIR resources. We also integrated an early warning system and machine learning pipeline. RESULTS: The study data set includes electronic health records of adult inpatients who visited the En-Chu-Kong hospital. Medical staff regularly measured these vital signs at least 2 to 3 times per day during the day, night, and early morning. We used pseudonymization to protect patient privacy. Then, we converted the vital signs to FHIR observations in the JSON format using the FHIR Extract Transform Load application. The measured vital signs include systolic blood pressure, diastolic blood pressure, heart rate, respiratory rate, and body temperature. According to clinical requirements, we also extracted the electronic health record information to the FHIR server. Finally, we integrated an early warning system and machine learning pipeline using the FHIR RESTful application programming interface. CONCLUSIONS: We successfully demonstrated a process that standardizes health care information for inpatient deterioration detection using vital signs. Based on the FHIR definition, we also provided an implementation guide that includes data mapping, an integration process, and IHCA assessment using vital signs. We also proposed a clarifying system architecture and possible workflows. Based on FHIR, we integrated the 3 different systems in 1 dashboard system, which can effectively solve the complexity of the system in the medical staff workflow.

A Precision Health Service for Chronic Diseases: Development and Cohort Study Using Wearable Device, Machine Learning, and Deep Learning.

This paper presents an integrated and scalable precision health service for health promotion and chronic disease prevention. Continuous real-time monitoring of lifestyle and environmental factors is implemented by integrating wearable devices, open environmental data, indoor air quality sensing devices, a location-based smartphone app, and an AI-assisted telecare platform. The AI-assisted telecare platform provided comprehensive insight into patients' clinical, lifestyle, and environmental data, and generated reliable predictions of future acute exacerbation events. All data from 1,667 patients were collected prospectively during a 24-month follow-up period, resulting in the detection of 386 abnormal episodes. Machine learning algorithms and deep learning algorithms were used to train modular chronic disease models. The modular chronic disease prediction models that have passed external validation include obesity, panic disorder, and chronic obstructive pulmonary disease, with an average accuracy of 88.46%, a sensitivity of 75.6%, a specificity of 93.0%, and an F1 score of 79.8%. Compared with previous studies, we establish an effective way to collect lifestyle, life trajectory, and symptom records, as well as environmental factors, and improve the performance of the prediction model by adding objective comprehensive data and feature selection. Our results also demonstrate that lifestyle and environmental factors are highly correlated with patient health and have the potential to predict future abnormal events better than using only questionnaire data. Furthermore, we have constructed a cost-effective model that needs only a few features to support the prediction task, which is helpful for deploying real-world modular prediction models.

Household air pollution from solid fuel use as a dose-dependent risk factor for cognitive impairment in northern China.

The relationship between exposure to household air pollution (HAP) from solid fuel use and cognition remains poorly understood. Among 401 older adults in peri-urban northern China enrolled in the INTERMAP-China Prospective Study, we estimated the associations between exposure to HAP and z-standardized domain-specific and overall cognitive scores from the Montreal Cognitive Assessment. Interquartile range increases in exposures to fine particulate matter (53.2-µg/m3) and black carbon (0.9-µg/m3) were linearly associated with lower overall cognition [- 0.13 (95% confidence interval: - 0.22, - 0.04) and - 0.10 (- 0.19, - 0.01), respectively]. Using solid fuel indoors and greater intensity of its use were also associated with lower overall cognition (range of point estimates: - 0.13 to - 0.03), though confidence intervals included zero. Among individual cognitive domains, attention had the largest associations with most exposure measures. Our findings indicate that exposure to HAP may be a dose-dependent risk factor for cognitive impairment. As exposure to HAP remains pervasive in China and worldwide, reducing exposure through the promotion of less-polluting stoves and fuels may be a population-wide intervention strategy to lessen the burden of cognitive impairment.

Dynamic molecular conformational change leading to energy transfer in F8-5% BSP copolymer revealed by single-molecule spectroscopy.

Polyfluorene-based copolymers such as poly(9,9-dioctylfluorene)-alt-5% [bis-N,N'-(4-butylphenyl)-bis-N,N'-phenyl-1,4-phenylenediamine] (F8-5% BSP) are efficient blue-emitting polymers with various electronic phases: F8 blue-emitting glassy phase, F8 ordered more red-emitting ß-phase, and F8/BSP charge transfer (CT) state. Polymer light-emitting device performance and color purity can be significantly improved by forming ß-phase segments. However, the role of the ß-phase on energy transfer (ET) among glassy F8, ß-phase, and F8/BSP CT state is unclear. Herein, we identify dynamic molecular conformation-controlled ET from locally excited states to either the CT state or ß-phase in light-emitting copolymers. By conducting single-molecule spectroscopy for single F8-5% BSP chains, we find inefficient intra-chain ET from glassy segments to the CT state, while efficient ET from the glassy to the ß-phase. Spontaneous and reversible CT on-off emission is observed both in the presence and absence of the ß-phase. The density functional theory calculations reveal the origin of the on-chain CT state and indicate this CT emission on-off switching behavior could be related to molecule torsional motion between BSP and F8 units. The population of the CT state by ET can be increased via through-space interaction between the F8 block and the BSP unit on a self-folded chain. Temperature-dependent single-molecule spectroscopy confirms such interaction showing a gradual increase in intensity of the CT emission with the temperature. Based on these observations, we propose the dynamic molecular motion-induced conformation change as the origin of the glassy-to-CT ET, and thermal energy may provide the activation for such a change to enhance the ET from glassy or ß-phases to the CT state.

Real-Time Monitoring of Formation and Dynamics of Intra- and Interchain Phases in Single Molecules of Polyfluorene.

Poly(9,9-dioctylfluorene) (PFO) is one of the most important conjugated polymer materials, exhibiting outstanding photophysical and electrical properties. PFO is also known for a diversity of morphological phases determined by conformational states of the main chain. Our goal in this work is to address some of the key questions on formation and dynamics of one such conformation, the ß-phase, by following in real time the evolution of fluorescence spectra of single PFO chains. The PFO is dispersed in a thin polystyrene film, and the spectra are monitored during the process of solvent vapor annealing with toluene. We confirm unambiguously that the PFO ß-phase segments are formed on a true single-chain level at room temperature in the solvent-softened polystyrene. We further find that the formation of the ß-phase is a dynamic and reversible process occurring on the order of seconds, leading to repeated spontaneous transitions between the glassy and ß-phase segments during the annealing. Comparison of PFO with two largely different molecular weights (Mw) shows that chains with lower Mw form the ß-phase segments much faster. For the high Mw PFO chains, a detailed Franck-Condon analysis of the ß-phase spectra shows a large distribution of the Huang-Rhys factor, S, and even dynamic changes of this factor occurring on a single chain. Such dynamics are likely a manifestation of changing coherence length of the exciton. Further, for the high Mw PFO chains we observe an additional conformational state, a crystalline γ-phase. The γ-phase formation is also a spontaneous reversible process in the solvent-softened matrix. The phase can form from both the ß-phase and the glassy phase, and the formation requires high Mw to enable intersegment interactions in a self-folded chain.

Two MYB-related transcription factors play opposite roles in sugar signaling in Arabidopsis.

KEY MESSAGE: Sugar regulation of gene expression has profound effects at all stages of the plant life cycle. Although regulation at the transcriptional level is one of the most prominent mechanisms by which gene expression is regulated, only a few transcription factors have been identified and demonstrated to be involved in the regulation of sugar-regulated gene expression. OsMYBS1, an R1/2-type MYB transcription factor, has been demonstrated to be involved in sugar- and hormone-regulated α-amylase gene expression in rice. Arabidopsis contains two OsMYBS1 homologs. In the present study, we investigate MYBS1 and MYBS2 in sugar signaling in Arabidopsis. Our results indicate that MYBS1 and MYBS2 play opposite roles in regulating glucose and ABA signaling in Arabidopsis during seed germination and early seedling development. MYB proteins have been classified into four subfamilies: R2R3-MYB, R1/2-MYB, 3R-MYB, and 4R-MYB. An R1/2-type MYB transcription factor, OsMYBS1, has been demonstrated to be involved in sugar- and hormone-regulated α-amylase genes expression in rice. In this study, two genes homologous to OsMYBS1, MYBS1 and MYBS2, were investigated in Arabidopsis. Subcellular localization analysis showed that MYBS1 and MYBS2 were localized in the nucleus. Rice embryo transient expression assays indicated that both MYBS1 and MYBS2 could recognize the sugar response element, TA-box, in the promoter and induced promoter activity. mybs1 mutant exhibited hypersensitivity to glucose, whereas mybs2 seedlings were hyposensitive to it. MYBS1 and MYBS2 are involved in the control of glucose-responsive gene expression, as the mybs1 mutant displayed increased expression of a hexokinase gene (HXK1), chlorophyll a/b-binding protein gene (CAB1), ADP-glucose pyrophosphorylase gene (APL3), and chalcone synthase gene (CHS), whereas the mybs2 mutant exhibited decreased expression of these genes. mybs1 also showed an enhanced response to abscisic acid (ABA) in the seed germination and seedling growth stages, while mybs2 showed reduced responses. The ABA biosynthesis inhibitor fluridone rescued the mybs1 glucose-hypersensitive phenotype. Moreover, the mRNA levels of three ABA biosynthesis genes, ABA1, NCED9, and AAO3, and three ABA signaling genes, ABI3, ABI4, and ABI5, were increased upon glucose treatment of mybs1 seedlings, but were decreased in mybs2 seedlings. These results indicate that MYBS1 and MYBS2 play opposite roles in regulating glucose and ABA signaling in Arabidopsis during seed germination and early seedling development.

Wave reflections, arterial stiffness, and orthostatic hypotension.

BACKGROUND: The effect of wave reflections on blood pressure change associated with posture remains unclear. We therefore applied a wave separation technique to investigate the relations of the backward pressure wave amplitude with orthostatic pressure changes and orthostatic hypotension (OH). METHODS: We analyzed data from 613 subjects who had participated in our hemodynamic studies. Measurements of brachial systolic (SBP) and diastolic blood pressures (DBP), carotid-femoral pulse wave velocity (cf-PWV), and backward pressure wave amplitude from a decomposed carotid pressure wave (Pb) were obtained at supine position. SBP and DBP were measured again 3 minutes after standing. OH was defined as a fall of ≥20 mm Hg in SBP and/or ≥10 mm Hg in DBP. RESULTS: Subjects with OH (n = 100) were characterized with significantly higher supine SBP and DBP and significantly lower standing SBP and DBP when compared with subjects without OH. Subjects with OH were also characterized with significantly higher cf-PWV and Pb. cf-PWV and Pb separately were significantly associated with the orthostatic SBP change in univariable and multivariable analyses. Also, cf-PWV and Pb separately were significant predictors of OH in univariable and multivariable analyses. cf-PWV predicted OH in the younger but less so in the older subgroup, whereas Pb demonstrated similar prediction in both subgroups. In a final multivariable model, both cf-PWV and Pb were significant independent predictors of OH. CONCLUSIONS: Wave reflections are an independent determinant of orthostatic SBP change and OH in both younger and older subjects.

Paradoxical aging changes of the atrioventricular nodal properties in patients with atrioventricular nodal re-entrant tachycardia.

BACKGROUND: This study aimed to investigate the impact of aging on electrophysiological characteristics in patients with atrioventricular nodal re-entrant tachycardia (AVNRT). METHODS AND RESULTS: The 2,111 patients who underwent an electrophysiological study and radiofrequency (RF) catheter ablation of AVNRT were enrolled. The patients were divided into 4 groups according to age (group 1: < 20 years; group 2: 20-39 years; group 3: 40-59 years; and group 4: ≥ 60 years). The gender distribution differed with age. The atrio-Hisian interval, and effective refractory periods (ERP) of the right atrium, ventricle, antegrade slow pathway, retrograde slow pathway and fast pathway, and tachycardia cycle length all increased with age. However, a paradoxical change in the fast pathway ERP was noted. The fast pathway ERP was significantly longer in group 2 than in other groups, and was associated with the largest tachycardia window. The response to catecholamines was similar between different age groups. Procedure time, radiation time, and complications did not differ. However, the number of RF impulses was higher in group 2 compared with other groups (7.6 ± 9.3, P=0.04), which might imply a differing complexity during the ablation. CONCLUSIONS: Paradoxical aging changes of AVN electrophysiological characteristics were associated with a different atrioventricular nodal conduction property and the number of RF impulses.