Environmental circadian disruption re-writes liver circadian proteomes.

Circadian gene expression is fundamental to the establishment and functions of the circadian clock, a cell-autonomous and evolutionary-conserved timing system. Yet, how it is affected by environmental-circadian disruption (ECD) such as shiftwork and jetlag are ill-defined. Here, we provided a comprehensive and comparative description of male liver circadian gene expression, encompassing transcriptomes, whole-cell proteomes and nuclear proteomes, under normal and after ECD conditions. Under both conditions, post-translation, rather than transcription, is the dominant contributor to circadian functional outputs. After ECD, post-transcriptional and post-translational processes are the major contributors to whole-cell or nuclear circadian proteome, respectively. Furthermore, ECD re-writes the rhythmicity of 64% transcriptome, 98% whole-cell proteome and 95% nuclear proteome. The re-writing, which is associated with changes of circadian regulatory cis-elements, RNA-processing and protein localization, diminishes circadian regulation of fat and carbohydrate metabolism and persists after one week of ECD-recovery.

Ni2P active site ensembles tune electrocatalytic nitrate reduction selectivity.

We demonstrate that active site ensembles on transition metal phosphides tune the selectivity of the nitrate reduction reaction. Using Ni2P nanocrystals as a case study, we report a mechanism involving competitive co-adsorption of H* and NOx* intermediates. A near 100% faradaic efficiency for nitrate reduction over hydrogen evolution is observed at -0.4 V, while NH3 selectivity is maximized at -0.2 V vs. RHE.

Intersubject representational similarity analysis uncovers the impact of state anxiety on brain activation patterns in the human extrastriate cortex.

The current study used functional magnetic resonance imaging (fMRI) and showed that state anxiety modulated extrastriate cortex activity in response to emotionally-charged visual images. State anxiety and neuroimaging data from 53 individuals were subjected to an intersubject representational similarity analysis (ISRSA), wherein the geometries between neural and behavioral data were compared. This analysis identified the extrastriate cortex (fusiform gyrus and area MT) to be the sole regions whose activity patterns covaried with state anxiety. Importantly, we show that this brain-behavior association is revealed when treating state anxiety data as a multidimensional response pattern, rather than a single composite score. This suggests that ISRSA using multivariate distances may be more sensitive in identifying the shared geometries between self-report questionnaires and brain imaging data. Overall, our findings demonstrate that a transient state of anxiety may influence how visual information - especially those relevant to the valence dimension - is processed in the extrastriate cortex.

Environmental circadian disruption re-programs liver circadian gene expression.

Circadian gene expression is fundamental to the establishment and functions of the circadian clock, a cell-autonomous and evolutionary-conserved timing system. Yet, how it is affected by environmental-circadian disruption (ECD) such as shiftwork and jetlag, which impact millions of people worldwide, are ill-defined. Here, we provided the first comprehensive description of liver circadian gene expression under normal and after ECD conditions. We found that post-transcription and post-translation processes are dominant contributors to whole-cell or nuclear circadian proteome, respectively. Furthermore, rhythmicity of 64% transcriptome, 98% whole-cell proteome and 95% nuclear proteome is re-written by ECD. The re-writing, which is associated with changes of circadian cis-regulatory elements, RNA-processing and protein trafficking, diminishes circadian regulation of fat and carbohydrate metabolism and persists after one week of ECD-recovery.

Design Rules for Obtaining Narrow Luminescence from Semiconductors Made in Solution.

Solution-processed semiconductors are in demand for present and next-generation optoelectronic technologies ranging from displays to quantum light sources because of their scalability and ease of integration into devices with diverse form factors. One of the central requirements for semiconductors used in these applications is a narrow photoluminescence (PL) line width. Narrow emission line widths are needed to ensure both color and single-photon purity, raising the question of what design rules are needed to obtain narrow emission from semiconductors made in solution. In this review, we first examine the requirements for colloidal emitters for a variety of applications including light-emitting diodes, photodetectors, lasers, and quantum information science. Next, we will delve into the sources of spectral broadening, including "homogeneous" broadening from dynamical broadening mechanisms in single-particle spectra, heterogeneous broadening from static structural differences in ensemble spectra, and spectral diffusion. Then, we compare the current state of the art in terms of emission line width for a variety of colloidal materials including II-VI quantum dots (QDs) and nanoplatelets, III-V QDs, alloyed QDs, metal-halide perovskites including nanocrystals and 2D structures, doped nanocrystals, and, finally, as a point of comparison, organic molecules. We end with some conclusions and connections, including an outline of promising paths forward.

Colloidal, Room-Temperature Growth of Metal Oxide Shells on InP Quantum Dots.

We demonstrate colloidal, layer-by-layer growth of metal oxide shells on InP quantum dots (QDs) at room temperature. We show with computational modeling that native InP QD surface oxides give rise to nonradiative pathways due to the presence of surface-localized dark states near the band edges. Replacing surface indium with zinc to form a ZnO shell results in reduced nonradiative decay and a density of states at the valence band edge that resembles defect-free, stoichiometric InP. We then developed a synthetic strategy using stoichiometric amounts of common atomic layer deposition precursors in alternating cycles to achieve layer-by-layer growth. Metal-oxide-shelled InP QDs show bulk and local structural perturbations as determined by X-ray diffraction and extended X-ray absorption fine structure spectroscopy. Upon growing ZnSe shells of varying thickness on the oxide-shelled QDs, we observe increased photoluminescence (PL) quantum yields and narrowing of the emission linewidths that we attribute to decreased ion diffusion to the shell, as supported by phosphorus X-ray emission spectroscopy. These results present a versatile strategy to control QD interfaces for novel heterostructure design by leveraging surface oxides. This work also contributes to our understanding of the connections between structural complexity and PL properties in technologically relevant colloidal optoelectronic materials.

Deterministic Quantum Light Arrays from Giant Silica-Shelled Quantum Dots.

Colloidal quantum dots (QDs) are promising candidates for single-photon sources with applications in photonic quantum information technologies. Developing practical photonic quantum devices with colloidal materials, however, requires scalable deterministic placement of stable single QD emitters. In this work, we describe a method to exploit QD size to facilitate deterministic positioning of single QDs into large arrays while maintaining their photostability and single-photon emission properties. CdSe/CdS core/shell QDs were encapsulated in silica to both increase their physical size without perturbing their quantum-confined emission and enhance their photostability. These giant QDs were then precisely positioned into ordered arrays using template-assisted self-assembly with a 75% yield for single QDs. We show that the QDs before and after assembly exhibit antibunching behavior at room temperature and their optical properties are retained after an extended period of time. Together, this bottom-up synthetic approach via silica shelling and the robust template-assisted self-assembly offer a unique strategy to produce scalable quantum photonics platforms using colloidal QDs as single-photon emitters.

Experimental study on total coliform violations in the complied NH2CL, O3, and UV treated municipal water supply system.

Water quality has become a severe concern on a global scale, owing mostly to the rapid increase of the nation's development. According to Malaysia's Natural Resources and Environment Ministry, poor water management is the primary cause of the country's water quality problems. Many river systems are polluted by home and industrial pollutants, according to the findings of research in Malaysia and comparable difficulties in a few other nations. Hence, the following are the research's goals: (1) To look into what is causing the infractions. (2) To undertake the inquiry, develop a thorough hypothesis. (3) To detect dangerous germs by sampling the most usually infected regions. (4) To develop a test for Total Coliform violations in chlorine-treated water at the water treatment plant and in water distribution systems. As a result, the most major barrier to ensuring the safe delivery of treated water to consumers and protecting human health from water-related diseases is the drinking water treatment process. As a result, practically all water treatment systems around the world, including those in the USA, use a chlorine-based procedure to disinfect the water system during treatment. According to studies, the ideal way of disinfecting treated water is both safe and beneficial. Any sort of pandemic or biologically caused disease has no societal implications. Many countries began to suffer in 2009 as a result of e-coli and total coliform contamination in their water systems, leading to ambiguity in disinfection methods. Some water from UNMC's coolers was within the guidelines, while some exceed them. Water coolers at Block E (614 m) and Block B (605 m), for example, measured 12 CFU/100 ml and 11 CFU/100 ml, respectively. Water coolers should be cleaned regularly to ensure that they perform correctly. Further, the microbial population was found to be higher at water storage tanks than that is at the water cooler. This demonstrates how a water cooler fulfils its purpose of filtering and trapping germs to provide clean drinking water.

Organic building blocks at inorganic nanomaterial interfaces.

This tutorial review presents our perspective on designing organic molecules for the functionalization of inorganic nanomaterial surfaces, through the model of an "anchor-functionality" paradigm. This "anchor-functionality" paradigm is a streamlined design strategy developed from a comprehensive range of materials (e.g., lead halide perovskites, II-VI semiconductors, III-V semiconductors, metal oxides, diamonds, carbon dots, silicon, etc.) and applications (e.g., light-emitting diodes, photovoltaics, lasers, photonic cavities, photocatalysis, fluorescence imaging, photo dynamic therapy, drug delivery, etc.). The structure of this organic interface modifier comprises two key components: anchor groups binding to inorganic surfaces and functional groups that optimize their performance in specific applications. To help readers better understand and utilize this approach, the roles of different anchor groups and different functional groups are discussed and explained through their interactions with inorganic materials and external environments.

[Development of a deep learning based prototype artificial intelligence system for the detection of dental caries in children].

Objective: To develop a prototype artificial intelligence image recognition system for detecting dental caries, especially those without cavities, in children. Methods: Seven hundred and twelve intraoral photos, which were taken by dental professionals using a digital camera from October 2013 to June 2020 in the Department of Pediatric Dentistry, Peking University School and Hospital of Stomatology, were collected from the children who received dental treatment under general anesthesia. The well-documented post-treatment electronic dental record of each child was identified as label standard to determine whether the teeth were carious and the type of caries types such as caries that had become cavities (caries with cavities), pit and fissure caries that had not become cavities (pit and fissure caries) and proximal caries which the marginal ridge enamel had not been destroyed (proximal caries). The various teeth and caries types were labeled by pediatric dentists using VoTT software (Windows 2.1.0, Microsoft, U S A). There were five labeled groups: pit and fissure caries, approximal caries, non-carious approximal surfaces, caries with cavities and teeth without caries (including intact fillings). Each group was randomly divided into training dataset, validation dataset and test dataset at a ratio of 6.4∶1.6∶2.0 by using random number table. After using the labeled training dataset for deep learning training, a deep learning-based artificial intelligence (AI) image recognition system for detecting dental caries was established, with the caries probability greater than 50.0% as the criterion for determining caries. Sensitivity and accuracy were used as indicators of recognition specificity. Results: Seven hundred and twelve single-jaw intraoral photographs were segmented and annotated into 953 pit and fissure caries, 1 002 approximal caries, 3 008 caries with cavities, 3 189 teeth without caries and 862 non-carious approximal surfaces, totaly 9 014 labels. The sensitivities and specificities of the test set were 96.0% and 97.0% for caries with cavities, 95.8% and 99.0% for pit and fissure caries and 88.1% and 97.1% for approximal caries. Conclusions: The current AI system developed based on deep learning of the intra-oral photos in the present study showed the ability to detect dental caries. Furthermore, the AI system could accurately verify different types of dental caries such as caries with cavities, pit and fissure caries and proximal caries.

Taking a Computational Cultural Neuroscience Approach to Study Parent-Child Similarities in Diverse Cultural Contexts.

Parent-child similarities and discrepancies at multiple levels provide a window to understand the cultural transmission process. Although prior research has examined parent-child similarities at the belief, behavioral, and physiological levels across cultures, little is known about parent-child similarities at the neural level. The current review introduces an interdisciplinary computational cultural neuroscience approach, which utilizes computational methods to understand neural and psychological processes being involved during parent-child interactions at intra- and inter-personal level. This review provides three examples, including the application of intersubject representational similarity analysis to analyze naturalistic neuroimaging data, the usage of computer vision to capture non-verbal social signals during parent-child interactions, and unraveling the psychological complexities involved during real-time parent-child interactions based on their simultaneous recorded brain response patterns. We hope that this computational cultural neuroscience approach can provide researchers an alternative way to examine parent-child similarities and discrepancies across different cultural contexts and gain a better understanding of cultural transmission processes.

[Deep learning-based dental plaque detection on permanent teeth and the influenced factors].

Objective: To develop an artificial intelligence system for detecting dental plaque on permanent teeth and find the influenced factors. Methods: Photos of the labial or buccal surfaces of the permanent teeth were taken by using an intraoral camera (1 280×960 pixels; TPC Ligang, Shenzhen, China) before and after applying the plaque-disclosing agent (Cimedical, Japan) in 25 volunteers [12 males, 13 femals, aged (23±3) years] recruided in accordance with the inclusion criteria from the students of Peking University School of Stomatology from October 2018 to June 2019. A total of 549 groups of photos were captured and then divided into a training dataset containing 440 groups of photos and a test dataset including 109 groups of photos. The scopes of teeth and dental plaque on photos were labeled using LabelMe (Windows 3.2.1, MIT, U S A). A DeepLab based deep learning system was designed for the intelligent detection of dental plaque on permanent teeth. The mean intersection over union (MIoU) was employed to indicate the detection accuracy. Matlab (Windows R2017a, MathWorks, U S A) was used to extract the plaque edge line of 109 groups of photos and to calculate the number of pixels for the measurement of the complexity of the plaque edge line. The percentage of dental plaque area was calculated. Multivariate linear regression was used to explore whether tooth site, plaque percentage, number of plaque edge line pixels and lens light spot location would influence the detection accuracy, of which P<0.05 was considered statistically significant. Results: The MIoU of the permanent tooth model was 0.700±0.191 when 440 photos were used for training and 109 photos were used for testing. In the regression model of significance test (P<0.05), the percentage of plaque and the number of pixels on the edge of plaque had significant influence on the accuracy of dental plaque detection. The standardized coefficient of the number of pixels of the plaque edge line is -0.289, and the standardized coefficient of the percentage of plaque is -0.551. Conclusions: In the present study, an artificial intelligence system was built to detect dental plaque area on tooth photos collected by family intraoral camera. The system showed the ability to detect the dental plaque of permanent teeth. The more complex the marginal line of dental plaque and higher the percentage of dental plaque are, the lower the accuracy of plaque recognition is.

Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience.

How we process ongoing experiences is shaped by our personal history, current needs, and future goals. Consequently, ventromedial prefrontal cortex (vmPFC) activity involved in processing these subjective appraisals appears to be highly idiosyncratic across individuals. To elucidate the role of the vmPFC in processing our ongoing experiences, we developed a computational framework and analysis pipeline to characterize the spatiotemporal dynamics of individual vmPFC responses as participants viewed a 45-minute television drama. Through a combination of functional magnetic resonance imaging, facial expression tracking, and self-reported emotional experiences across four studies, our data suggest that the vmPFC slowly transitions through a series of discretized states that broadly map onto affective experiences. Although these transitions typically occur at idiosyncratic times across people, participants exhibited a marked increase in state alignment during high affectively valenced events in the show. Our work suggests that the vmPFC ascribes affective meaning to our ongoing experiences.

Successful Concomitant Pulmonary Thromboendarterectomy and Heart Transplant.

Heart transplantation remains the gold standard of therapy for patients with end-stage heart failure. Submassive pulmonary embolism in a patient with heart failure is generally considered a contraindication to immediate heart transplantation, given the risk of right heart failure posttransplant. Generally patients must wait for extended periods of time to recover from pulmonary embolism therapies before being listed for transplant. We report a case of successful concomitant pulmonary thromboendarterectomy and heart transplantation.

Intersubject representational similarity analysis reveals individual variations in affective experience when watching erotic movies.

We spend much of our lives pursuing or avoiding affective experiences. However, surprisingly little is known about how these experiences are represented in the brain and if they are shared across individuals. Here, we explored variations in the construction of an affective experience during a naturalistic viewing paradigm based on subjective preferences in sociosexual desire and self-control using intersubject representational similarity analysis (IS-RSA). We found that when watching erotic movies, intersubject variations in sociosexual desire preferences of 26 heterosexual males were associated with similarly structured fluctuations in the cortico-striatal reward, default mode, and mentalizing networks. In contrast, variations in the self-control preferences were associated with shared dynamics in the fronto-parietal executive control and cingulo-insular salience networks. Importantly, these results were specific to the affective experience, as we did not observe any relationship with variation in preferences when individuals watched neutral movies. Moreover, these results appear to require multivariate representations of preferences as we did not observe any significant associations using single scalar summary scores. Our findings indicate that multidimensional variations in individual preferences can be used to uncover unique dimensions of an affective experience, and that IS-RSA can provide new insights into the neural processes underlying psychological experiences elicited through naturalistic experimental designs.

Benefits of Neurohormonal Therapy in Patients With Continuous-Flow Left Ventricular Assist Devices.

Left ventricular assist devices (LVADs) have dramatically improved short-term outcomes among patients with advanced heart failure. While neurohormonal blockade (NHB) is the cornerstone of treatment for patients with heart failure with reduced ejection fraction, its effect after LVAD placement has not been established. We reviewed medical records of 307 patients who underwent primary LVAD implantation from January 2006 to September 2015 at two institutions in the United States. Patients were followed for at least 2 years post-LVAD implantation or until explantation, heart transplantation, or death. Cox regression analysis stratifying on center was used to assess associations with mortality. Neurohormonal blockade use was treated as a time-dependent predictor. Stepwise selection indicated treatment with angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEIs/ARBs) (hazard ratio [HR] = 0.53 [0.30-0.95], p = 0.03), age at the time of implantation (HR = 1.28 [1.05-1.56] per decade, p = 0.02), length of stay postimplantation (HR = 1.16 [1.11-1.21] per week, p < 0.01) and INTERMACS profile of 1 or 2 (HR = 1.86 [1.17-2.97], p < 0.01) were independent predictors of mortality. In this large, retrospective study, treatment with ACEIs or ARBs was an independent factor associated with decreased mortality post-LVAD placement.

Socially transmitted placebo effects.

Medical treatments typically occur in the context of a social interaction between healthcare providers and patients. Although decades of research have demonstrated that patients' expectations can dramatically affect treatment outcomes, less is known about the influence of providers' expectations. Here we systematically manipulated providers' expectations in a simulated clinical interaction involving administration of thermal pain and found that patients' subjective experiences of pain were directly modulated by providers' expectations of treatment success, as reflected in the patients' subjective ratings, skin conductance responses and facial expression behaviours. The belief manipulation also affected patients' perceptions of providers' empathy during the pain procedure and manifested as subtle changes in providers' facial expression behaviours during the clinical interaction. Importantly, these findings were replicated in two more independent samples. Together, our results provide evidence of a socially transmitted placebo effect, highlighting how healthcare providers' behaviour and cognitive mindsets can affect clinical interactions.

Management of RVAD Thrombosis in Biventricular HVAD Supported Patients: Case Series.

Patients with biventricular assist devices (BIVAD) are severely critically ill compared with patients who receive left ventricular assist device (LVAD) support alone and portend a significant risk for greater adverse events including pump thrombosis (PT). Current approaches to treat PT are limited to LVAD with variable outcomes depending on the management strategy implemented. Moreover the management of PT in patients with BIVAD support, specifically to the right ventricular assist device (RVAD), is unknown. We describe the first care series to date on the management of PT in patients with durable right ventricular assist device and their outcomes.

Reducing reward responsivity and daily food desires in female dieters through domain-specific training.

According to the strength model, self-regulation relies on a domain-general capacity that may be strengthened by training. From this perspective, training self-regulation in one domain may transfer to other domains. Here we used two inhibitory training paradigms, a domain-general and domain-specific stop-signal training task and compared their effects on brain reward activity as well as daily food desires in female dieters. Before and after the training, functional magnetic resonance imaging was used to assess food cue-reactivity, coupled with one week of smart-phone ecological momentary assessments to examine eating urges. Whereas the food-specific inhibitory training was successful in reducing both food cue-reactivity and food desires, the domain-general (sound-cue) training showed no transfer effects. These findings suggest that domain-specific training may be a more effective method for supporting self-regulation than domain-general approaches aimed at strengthening self-regulation across domains.