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Abstract Unraveling drivers of the interannual variability of tropical land carbon cycle is critical for understanding land carbon-climate feedbacks. Here we utilize two generations of factorial model experiments to show that interannual variability of tropical land carbon uptake under both present and future climate is consistently dominated by terrestrial water availability variations in Earth system models. The magnitude of this interannual sensitivity of tropical land carbon uptake to water availability variations under future climate shows a large spread across the latest 16 models (2.3 ± 1.5 PgC/yr/Tt H2O), which is constrained to 1.3 ± 0.8 PgC/yr/Tt H2O using observations and the emergent constraint methodology. However, the long-term tropical land carbon-climate feedback uncertainties in the latest models can no longer be directly constrained by interannual variability compared with previous models, given that additional important processes are not well reflected in interannual variability but could determine long-term land carbon storage. Our results highlight the limited implication of interannual variability for long-term tropical land carbon-climate feedbacks and help isolate remaining uncertainties with respect to water limitations on tropical land carbon sink in Earth system models.

Abstract Metal‐semiconductor interfaces are crucial components of optoelectronic and electrical devices, the performance of which hinges on intricate dynamics involving charge transport and mechanical interaction at the interface. Nevertheless, structural changes upon photoexcitation and subsequent carrier transportation at the interface, which crucially impact hot carrier stability and lifetime, remain elusive. To address this long‐standing problem, they investigated the electron dynamics and resulting structural changes at the Au/TiO2 interface using ultrafast electron diffraction (UED). The analysis of the UED data reveals that interlayer electron transfer from metal to semiconductor generates a strong coupling between the two layers, offering a new way for ultrafast heat transfer through the interface and leading to a coherent structural vibration that plays a critical role in propagating mechanical stress. These findings provide insights into the relationship between electron transfer and interfacial mechanical and thermal properties.

Objectives: Posttraumatic stress disorder (PTSD) is a prevalent mental health condition, and techniques using sensory stimulation in processing traumatic memories have gained attention. The Emotional Freedom Techniques (EFT) is a psychotherapy that combines tapping on acupoints with exposure to cognitive reframing. This pilot study aimed to assess the feasibility of EFT as a treatment for PTSD by answering the following research questions: 1) What is the compliance and completion rate of patients with PTSD with regard to EFT protocol? Is the dropout rate reasonable? 2) Is the effect size of EFT protocol for PTSD sufficient to justify a future trial?Methods: Thirty participants diagnosed with PTSD were recruited. They received weekly EFT sessions for five weeks, in which they repeated a statement acknowledging the problem and accepting themselves while tapping the SI3 acupoint on the side of their hand. PTSD symptoms were evaluated using the PTSD Checklist for DSM-5 (PCL-5) before and after the intervention.Results: Of the 30 PTSD patients (mean age: 34.1 ± 9.1, 80% female), 96.7% showed over 80% compliance to the EFT sessions, and 86.7% completed the entire study process. The mean PCL-5 total score decreased significantly after the intervention, with a large effect size (change from baseline: –14.33 [95% CI: –19.79, –8.86], p < 0.0001, d = 1.06).Conclusion: The study suggests that EFT is a feasible treatment for PTSD, with high session compliance and low dropout rates. The effect size observed in this study supports the need for a larger trial in the future to further investigate EFT as a treatment for PTSD. However, the lack of a control group and the use of a self-rated questionnaire for PTSD symptoms are limitations of this study. The findings of this pilot study can be used to plan a future trial.

Abstract This study assesses the projected trajectory of Warm Arctic-Cold Continent (WACC) events in East Asia and North America through large ensemble simulation for the upcoming decades. It analyses the evolution of the geographical boundaries of threshold cold temperatures, revealing a significant northward shift as a sign of global warming’s impact on the southward advancement of Arctic cold air. While validating the intensification of the WACC phenomenon until the 2020 s, echoing earlier studies, the findings indicate a marked decrease beginning in the 2030s. If warming is not curbed, this shift suggests a critical modification in the WACC pattern, prompting a re-evaluation of existing theories and models for extreme winter weather events. The results have major implications, spurring communities impacted by WACC to anticipate future changes and encouraging the climate forecasting community to update conceptual models for improved adaptation and mitigation approaches.

Abstract We present a comprehensive analysis diagnosing the primary factors driving the observed changes in major atmospheric teleconnection patterns in the Northern Hemisphere winter, including the Pacific North American pattern (PNA), North Atlantic Oscillation (NAO), and North American winter dipole (NAWD), with particular focus on their roles in shaping anomalous weather across North America. Our investigation reveals a consistent influence of the NAWD over seven decades, contrasting with fluctuating impacts from PNA and minor impacts from NAO. In particular, an emergent negative correlation between the NAWD and PNA, signaling a shifted phase of teleconnection patterns, is identified. Such a relationship change is traced to enhanced upper-level ridges across western North America, reflecting a reinforced winter stationary wave. Through attribution analysis, we identify greenhouse gas emissions as a probable driver for the northward drift of the Asia-Pacific jet core, which, aided by orographic lifting over the Alaskan Range, subsequently amplifies the winter stationary wave across western North America. This work emphasizes the pronounced effect of human-induced global warming on the structure and teleconnection of large-scale atmospheric circulation in the Northern Hemisphere winter, providing vital perspectives on the dynamics of current climate trends.

Abstract Perovskite‐oxide‐based capacitors, which exhibit high charge storage capacity, have attracted considerable attention as a potential candidate for overcoming the limitations of nanoscale integration. Unfortunately, a dead layer forms in these capacitors at the interface between the electrode and the dielectric, which degrades the charge storage capacity; thus, this layer has been extensively investigated. The dead layer in perovskite‐oxide‐based capacitors exhibits different characteristics depending on the electrode materials; however, a method for minimizing this layer is lacking. In this study, the charge storage capacity of a perovskite‐oxide‐based capacitor is evaluated considering the effect of the Ru and SrRuO3 top electrodes on the SrRuO3/Ba0.5Sr0.5TiO3 stack. Dead layers at the interface between each top electrode material and the dielectric are studied on the atomic scale. The results indicate that the Ru metal electrode causes oxygen to diffuse from the dielectric to the electrode, forming elongated perovskite oxide at the interface, which acts as a dead layer. However, minimizing the dead layer at the top interface increases the dielectric permittivity from 667 to 953. Consequently, the phenomenon and mechanism of the dead layer are intuitively identified. This study proposes a method to overcome the limitations of next‐generation dynamic random access memory (DRAM).

Patients with inflammatory bowel diseases (IBDs), including ulcerative colitis (UC) and Crohn's disease (CD), often have concomitant mental disorders such as depression and anxiety. Therefore, a bidirectional approach involving the gut and brain axes is necessary for the prevention and treatment thereof. In this study, we explored the potential of Poncirus trifoliata extract (PT), traditionally known for its neuroprotective effects against gastrointestinal diseases, as a natural treatment agent for IBD in a dextran sulfate sodium (DSS)-induced colitis model. Oral administration of PT ameliorated weight loss and inflammatory responses in mice with DSS-induced colitis. Furthermore, PT treatment effectively restored the colon length and ameliorated enterocyte death by inhibiting DSS-induced reactive oxygen species (ROS)-mediated necroptosis. The main bioactive components of PT, poncirin and naringin, confirmed using ultra-performance liquid chromatography-quadrupole time-of-flight (UPLC-qTOF), can be utilized to regulate necroptosis. The antidepressant-like effects of PT were confirmed using open field test (OFT) and tail suspension test (TST). PT treatment also restored vascular endothelial cell integrity in the hippocampus. In the Cornu Ammonis 1 (CA1) and dentate gyrus (DG) regions of the hippocampus, PT controlled the neuroinflammatory responses of proliferated microglia. In conclusion, PT, which contains high levels of poncirin and naringin, has potential as a bidirectional therapeutic agent that can simultaneously improve IBD-associated intestinal and mental disorders.

IntroductionAttention-deficit/hyperactivity disorder (ADHD) affects a significant proportion of the pediatric population, making early detection crucial for effective intervention. Eye movements are controlled by brain regions associated with neuropsychological functions, such as selective attention, response inhibition, and working memory, and their deficits are related to the core characteristics of ADHD. Herein, we aimed to develop a screening model for ADHD using machine learning (ML) and eye-tracking features from tasks that reflect neuropsychological deficits in ADHD.MethodsFifty-six children (mean age 8.38 ± 1.58, 45 males) diagnosed with ADHD based on the Diagnostic and Statistical Manual of Mental Disorders, fifth edition were recruited along with seventy-nine typically developing children (TDC) (mean age 8.80 ± 1.82, 33 males). Eye-tracking data were collected using a digital device during the performance of five behavioral tasks measuring selective attention, working memory, and response inhibition (pro-saccade task, anti-saccade task, memory-guided saccade task, change detection task, and Stroop task). ML was employed to select relevant eye-tracking features for ADHD, and to subsequently construct an optimal model classifying ADHD from TDC.ResultsWe identified 33 eye-tracking features in the five tasks with the potential to distinguish children with ADHD from TDC. Participants with ADHD showed increased saccade latency and degree, and shorter fixation time in eye-tracking tasks. A soft voting model integrating extra tree and random forest classifiers demonstrated high accuracy (76.3%) at identifying ADHD using eye-tracking features alone. A comparison of the model using only eye-tracking features with models using the Advanced Test of Attention or Stroop test showed no significant difference in the area under the curve (AUC) (p = 0.419 and p=0.235, respectively). Combining demographic, behavioral, and clinical data with eye-tracking features improved accuracy, but did not significantly alter the AUC (p=0.208).DiscussionOur study suggests that eye-tracking features hold promise as ADHD screening tools, even when obtained using a simple digital device. The current findings emphasize that eye-tracking features could be reliable indicators of impaired neurobiological functioning in individuals with ADHD. To enhance utility as a screening tool, future research should be conducted with a larger sample of participants with a more balanced gender ratio.

Abstract Oxygen evolution reaction (OER) as a half‐anodic reaction of water splitting hinders the overall reaction efficiency owing to its thermodynamic and kinetic limitations. Iodide oxidation reaction (IOR) with low thermodynamic barrier and rapid reaction kinetics is a promising alternative to the OER. Herein, we present a molybdenum disulfide (MoS2) electrocatalyst for a high‐efficiency and remarkably durable anode enabling IOR. MoS2 nanosheets deposited on a porous carbon paper via atomic layer deposition show an IOR current density of 10 mA cm–2 at an anodic potential of 0.63 V with respect to the reversible hydrogen electrode owing to the porous substrate as well as the intrinsic iodide oxidation capability of MoS2 as confirmed by theoretical calculations. The lower positive potential applied to the MoS2‐based heterostructure during IOR electrocatalysis prevents deterioration of the active sites on MoS2, resulting in exceptional durability of 200 h. Subsequently, we fabricate a two‐electrode system comprising a MoS2 anode for IOR combined with a commercial Pt@C catalyst cathode for hydrogen evolution reaction. Moreover, the photovoltaic–electrochemical hydrogen production device comprising this electrolyzer and a single perovskite photovoltaic cell shows a record‐high current density of 21 mA cm–2 at 1 sun under unbiased conditions.

Abstract In recent decades, the interior regions of Eurasia and North America have experienced several unprecedentedly cold winters despite the global surface air temperature increases. One possible explanation of these increasing extreme cold winters comes from the so-called Warm Arctic Cold Continent (WACC) pattern, reflecting the effects of the amplified Arctic warming in driving the circulation change over surrounding continents. This study analyzed reanalysis data and model experiments forced by different levels of anthropogenic forcing. It is found that WACC exists on synoptic scales in observations, model’s historical and even future runs. In the future, the analysis suggests a continued presence of WACC but with a slightly weakened cold extreme due to the overall warming. Warm Arctic events under the warmer climate will be associated with not only a colder continent in East Asia but also a warmer continent, depending on the teleconnection process that is also complicated by the warmer Arctic. Such an increasingly association suggests a reduction in potential predictability of the midlatitude winter anomalies.

Nitrogen-doped graphene has been increasingly utilized in a variety of energy-related applications, serving as a catalyst or support material for fuel cells, and as an anode material for lithium-ion batteries, among others. The thermal reduction of graphene oxide (GO) in nitrogenous sources to incorporate nitrogen, producing nitrogen-doped reduced graphene oxide (NRGO), is the most favored method. Controlling atomic configurations of nitrogen-doped sites is the key factor for tailoring the physico-chemical properties of NRGO, but major challenges remain in identifying detailed atomic arrangements at nitrogen binding sites on highly defective and chemically functionalized GO surfaces. In this paper, we present atomistic-scale modeling of the nitrogen doping process of GO with different types of vacancy defects. Molecular dynamics simulations using a reactive force field indicate that the edge carbon atoms on defect sites are the dominant initiation location for nitrogen doping. Further, first-principles calculations using density functional theory present energetically favorable chemical transition pathways for nitrogen doping. The significance of this work lies in providing important chemical insights for the effective control of the desired properties of NRGO by suggesting a detailed mechanism of the nitrogen doping process of GO.

Developing new plant varieties plays a crucial role in competitiveness in the agricultural and food industries and enhancing food security. Daehong (DH) is a new variety of Crataegus pinnatifida Bunge (CP); however, its physiological functions and potential as a nutraceutical ingredient remain unknown. Here, the efficacy of DH on inflammatory bowel disease (IBD) was investigated using dextran sulfate sodium (DSS)-induced colitis mice, and its relative pharmacological effects were analyzed against CP. DH improved colitis-induced weight loss, colon shortening, and inflammatory responses and reduced intestinal permeability. The reactive oxygen species (ROS)-mediated necroptotic signal that triggers enterocyte cell death in DSS-induced colitis was effectively controlled by DH, attributed to epicatechin. DSS-induced gut dysbiosis was recovered into a healthy gut microbiome environment by DH, increasing beneficial bacteria, like Akkermansia muciniphila, and changing harmful bacteria, including Bacteroides vulgatus and Peptostreptococcaceae. DH shows potential as a dietary or pharmaceutical ingredient to promote gut health and to prevent and treat IBD.

Most studies on the pathogenesis of inflammatory bowel disease (IBD) focus on gut function damage and gastrointestinal symptoms; however, psychiatric disorders, including depression and anxiety, have also been recognized as significant causes. Recently, we reported that Magnolia officinalis bark extract (MBE) alleviated enterocyte death in dextran sulfate sodium (DSS)-induced colitis mouse model that mimics IBD; however, the therapeutic effects of MBE on neurological symptoms and underlying mechanisms of IBD remain unclear. In this study, we aimed to elucidate the mechanisms by which microglia and astrocytes improve MBE-induced depression and anxiety. We found that MBE treatment improved DSS-induced weight loss, colon-length shortening, and cell death, with ameliorateon of depression/anxiety-like behavioral disorders. Systemic treatment with MBE significantly decreased DSS-induced proliferation of microglia and astrocytes in the hippocampal region, and attenuated the increase in pro-inflammatory cytokines, including IL-6 and COX-2. Interestingly, MBE alleviated DSS-induced alterations of the serotonergic system by improving serotonin levels, and expression of serotonin 4 receptor (5-HT4R) and cAMP response element-binding protein (CREB) phosphorylation in the hippocampus. Overall, our findings indicate that MBE exerts protective effects not only on gastrointestinal function but also on neuropsychiatric disorders caused by colitis, which may be developed to treat IBD.

Abstract Capacitors based on ABO3-type perovskite oxides show considerable promise for overcoming the limitations of nanoscale integration with dynamic random access memory (DRAM) devices. Among the thermodynamically stable perovskite oxides, titanates (ATiO3) exhibit high dielectric permittivity in metal–insulator–metal (MIM) configurations. However, their performance in mitigating the large leakage current caused by their narrow bandgap (3 eV) remain under scrutiny. Herein, substantially enhanced dielectric properties of an epitaxial SrRuO3/Ba0.5Sr0.5TiO3/SrRuO3 MIM capacitor with a thin dielectric layer (10 nm) are reported. The dielectric/electrode heterointerface was engineered to realize a capacitor with a low leakage current and high dielectric permittivity. A pit-free and stoichiometric SrRuO3 bottom electrode with an atomically smooth surface was exploited to suppress defect formation at the heterointerface. The critical roles of oxygen vacancies and substituted transition-metal atoms in determining the leakage current were assessed, and a strategy for reducing the leakage current via interface engineering was established. Consequently, a dielectric permittivity of 861 and a leakage current density of 5.15 × 10−6 A/cm2 at 1 V were obtained with the thinnest dielectric layer ever reported. Our work paves the way for the development of perovskite-oxide-based capacitors in next-generation DRAM memories.

CO2 reduction rate shows a strong dependence on alkali metal cation identity but a unified molecular picture for underlying mechanism requires further investigation. Using advanced molecular simulations and experimental kinetic studies, here the authors establish a unified mechanism for cation-coupled electron transfer.

Understanding structure-property relationship of dye arrays is of great importance for designing organic photonic and photovoltaic materials. Here, authors present a slip-stacked perylene bisimide array as a model system to investigate singlet fission mechanisms by depending upon interchromophoric interaction.

Introduction The emotional freedom technique (EFT) is an acupuncture-based psychotherapy that combines tapping on acupoints with cognitive reframing. EFT has been previously shown to have potential for treating post-traumatic stress disorder (PTSD). However, further clinical evidence and underlying mechanisms of EFT are yet to be fully explored. This proposed clinical trial aims to examine the effect of EFT on patients with PTSD compared with the waitlist (WL) and active controls.Methods and analysis This study was designed as a randomised, assessor-blinded, three-arm clinical MRI study. A total of 120 eligible patients with PTSD will be recruited and randomised into EFT, written exposure therapy (WET) or WL groups. EFT and WET will be applied once a week for 5 weeks. For patients in the WL group, EFT will be performed after 12 weeks. PTSD symptoms, depression, anxiety, somatic symptoms and quality of life will be evaluated. Assessments will be conducted at baseline (week 0), post-treatment (week 6) and follow-up (week 12). Structural and functional brain images and recording videos of facial expressions to emotional stimuli will be obtained before and after treatment. Sixty participants without lifetime traumatic experiences will be enrolled as healthy controls. The primary objective of the study is to compare the change from baseline in the Clinician-Administered PTSD Scale after treatment (week 6) between EFT and WL groups and between EFT and WET groups.Ethics and dissemination Ethical approval was obtained from the Institutional Review Board of the Kyung Hee University Korean Medicine Hospital. The research findings will be shared at national and international conferences and will be published in peer-reviewed journals.Trial registration number Clinical Research Information Service KCT0007360 https://cris.nih.go.kr/cris/search/detailSearch.do/21974.

BackgroundLack of quantifiable biomarkers is a major obstacle in diagnosing and treating depression. In adolescents, increasing suicidality during antidepressant treatment further complicates the problem. ObjectiveWe sought to evaluate digital biomarkers for the diagnosis and treatment response of depression in adolescents through a newly developed smartphone app. MethodsWe developed the Smart Healthcare System for Teens At Risk for Depression and Suicide app for Android-based smartphones. This app passively collected data reflecting the social and behavioral activities of adolescents, such as their smartphone usage time, physical movement distance, and the number of phone calls and text messages during the study period. Our study consisted of 24 adolescents (mean age 15.4 [SD 1.4] years, 17 girls) with major depressive disorder (MDD) diagnosed with Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version and 10 healthy controls (mean age 13.8 [SD 0.6] years, 5 girls). After 1 week’s baseline data collection, adolescents with MDD were treated with escitalopram in an 8-week, open-label trial. Participants were monitored for 5 weeks, including the baseline data collection period. Their psychiatric status was measured every week. Depression severity was measured using the Children’s Depression Rating Scale-Revised and Clinical Global Impressions-Severity. The Columbia Suicide Severity Rating Scale was administered in order to assess suicide severity. We applied the deep learning approach for the analysis of the data. Deep neural network was employed for diagnosis classification, and neural network with weighted fuzzy membership functions was used for feature selection. ResultsWe could predict the diagnosis of depression with training accuracy of 96.3% and 3-fold validation accuracy of 77%. Of the 24 adolescents with MDD, 10 responded to antidepressant treatments. We predicted the treatment response of adolescents with MDD with training accuracy of 94.2% and 3-fold validation accuracy of 76%. Adolescents with MDD tended to move longer distances and use smartphones for longer periods of time compared to controls. The deep learning analysis showed that smartphone usage time was the most important feature in distinguishing adolescents with MDD from controls. Prominent differences were not observed in the pattern of each feature between the treatment responders and nonresponders. The deep learning analysis revealed that the total length of calls received as the most important feature predicting antidepressant response in adolescents with MDD. ConclusionsOur smartphone app demonstrated preliminary evidence of predicting diagnosis and treatment response in depressed adolescents. This is the first study to predict the treatment response of adolescents with MDD by examining smartphone-based objective data with deep learning approaches.

Amid increasing concerns about the impact of climate change on financial asset pricing, this paper investigates how drought risk affects stock returns in the U.S. energy sector over a thirty-year period (1990–2019). To this end, we ranked energy companies based on the long-term trend of the Palmer drought severity index (PDSI) to compare stock performance between groups experiencing the most significant increases and decreases in drought risk. Our analysis indicates that firms located in drought-prone regions have lower stock returns than those in regions with decreasing drought risk, particularly since 2010. This finding is noteworthy, as the average PDSI trend gap between regions at high risk of drought and those at low risk has widened during this period. We further divide our sample of energy companies into two subsectors-fuel production and electric utility-and find that the stock prices of both subsectors have been negatively affected by drought risk since 2010. The study underscores the energy sector’s dependency on water availability, suggesting novel implications for policymakers and investors in assessing the financial impacts of drought risks in their climate-related decision-making.

Wildfires in Northeast (NE) Siberia have become more frequent owing to the warming climate, exerting a profound impact on the global carbon cycle. While an increase in global temperature is recognized as a primary driver of unprecedented wildfires, the role of precipitation during wildfire season is relatively unexplored. Here, we present evidence that an increase in summer precipitation led to a sudden decrease in NE Siberian wildfires, especially in 2022, notwithstanding the persistent warming trend in the northern high latitudes. The interannual variability of summer precipitation, linked to the large-scale atmospheric circulation, known as the Scandinavia (SCAND) pattern, significantly impacts the regulation of wildfires. Climate models project enhanced variability in summer precipitation, potentially amplifying year-to-year fluctuations in wildfire occurrences. The interplay between the temperature and precipitation patterns in NE Siberia under ongoing warming may increase the occurrence of extreme wildfires, leading to a substantial release of carbon and further contributing to climate warming.

Significant regional disparities exist in the time left to prepare for unprecedented drought and how much we can buy time depending on climate scenarios. Specific regions pass this timing by the middle of 21st century even with stringent mitigation.

Abstract Satellite‐based precipitation estimations provide frequent, large‐scale measurements. Deep learning has recently shown significant potential for improving estimation accuracy. Most studies have employed a two‐stage framework, which is a sequential architecture of a rain/no‐rain binary classification task followed by a rain rate regression task. This study proposes a novel precipitation retrieval framework in which these two tasks are simultaneously trained using multi‐task learning approach (MTL). Furthermore, a novel network architecture and loss function were designed to reap the benefits of MTL. The proposed two‐task model successfully achieved a better performance than the conventional single‐task model possibly due to efficient knowledge transfer between tasks. Furthermore, the product intercomparison showed that our product outperformed existing products in rain rate retrieval and also yielded better skills in the rain/no‐rain retrieval task.

The selection of the π-conjugation spacers in semi-conducting polymer backbone is one of the important factors for determining the optoelectrical and morphological properties in organic photodiodes. To study the effects of π-conjugation spacers in donor–acceptor (D-A)-type alternating copolymers on their device performances in all-polymer-based photodiodes (all-PPDs), a series of diketopyrrolopyrrole (DPP)-based copolymers as polymer donors (PDs) were designed and synthesized. In detail, three different π-conjugation spacers, thiophene (T for P1), thienothiophene (TT for P2), and bithiophene (BT for P3), were incorporated into the DPP-based copolymer structures. Interestingly, all-PPDs based on the series of P1–P3 as PDs and N2200 as a polymer acceptor (PA) exhibited totally distinct device performances in terms of external quantum efficiency (EQE), dark current density (JD), and ideal detectivity (D*). The P1-based device showed suppressed JD (6.1 × 10−11 A/cm2 at −1 V) compared to those of the P2- and P3-based devices due to the lower lying of the highest occupied molecular orbital (HOMO) level of P1. However, the P3-based all-PPD showed higher EQE (16% at 630 nm wavelength and −1 V) compared to those of the P1- and P2-based devices. And, it mainly originated from the better molecular packing and final blend film morphology, as confirmed by morphological analyses.

Pluronics are amphiphilic triblock copolymers composed of two hydrophilic poly (ethylene oxide) (PEO) chains linked via a central hydrophobic polypropylene oxide (PPO). Owing to their low molecular weight polymer and greater number of PEO segments, Pluronics induce micelle formation and gelation at critical micelle concentrations and temperatures. Pluronics F-68 and F-127 are the only United States (U.S.) FDA-approved classes of Pluronics and have been extensively used as materials for living bodies. Owing to the fascinating characteristics of Pluronics, many studies have suggested their role in biomedical applications, such as drug delivery systems, tissue regeneration scaffolders, and biosurfactants. As a result, various studies have been performed using Pluronics as a tool in nanomedicine and targeted delivery systems. This review sought to describe the delivery of therapeutic cargos using Pluronic F-68 and F-127-based cancer nanomedicines and their composites for combination therapy.

The structure of the electric double layer (EDL) has been a long-standing question since the 19th century. Here, the authors simulate EDL structures and highlight their importance in catalysis through comparison of atomic simulations and experiment.

Abstract Active electronics are usually composed of semiconductor and metal electrodes which are connected by multiple vacuum deposition steps and photolithography patterning. However, the presence of interface of dissimilar material between semiconductor and metal electrode makes various problems in electrical contacts and mechanical failure. The ideal electronics should not have defective interfaces of dissimilar materials. In this study, we developed a novel method to fabricate active electronic components in a monolithic seamless fashion where both metal and semiconductor can be prepared from the same monolith material without creating a semiconductor–metal interface by reversible selective laser-induced redox (rSLIR) method. Furthermore, rSLIR can control the oxidation state of transition metal (Cu) to yield semiconductors with two different bandgap states (Cu2O and CuO with bandgaps of 2.1 and 1.2 eV, respectively), which may allow multifunctional sensors with multiple bandgaps from the same materials. This novel method enables the seamless integration of single-phase Cu, Cu2O, and CuO, simultaneously while allowing reversible, selective conversion between oxidation states by simply shining laser light. Moreover, we fabricated a flexible monolithic metal–semiconductor–metal multispectral photodetector that can detect multiple wavelengths. The unique monolithic characteristics of rSLIR process can provide next-generation electronics fabrication method overcoming the limitation of conventional photolithography methods.

It is assumed that mood can be inferred from one’s facial expression. While this association may prove to be an objective marker for mood disorders, few studies have explicitly evaluated this linkage.The facial movement responses of women with major depressive disorder (n = 66) and healthy controls (n = 46) under emotional stimuli were recorded using webcam. To boost facial movements, the naturalistic audio-visual stimuli were presented. To assess consistent global patterns across facial movements, scores for facial action units were extracted and projected onto principal component using principal component analysis. The associations of component for facial movements with functional brain circuitry was also investigated.Clusters of mouth movements, such as lip press and stretch, identified by principal component analysis, were attenuated in depressive patients compared to those in healthy controls. This component of facial movements was associated with depressive symptoms, and the strengths of resting brain functional connectivity between nucleus accumbens and both posterior insular cortex and thalamus.The evaluation of facial movements may prove to be a promising quantitative marker for assessing depressive symptoms and their underlying brain circuitry.

OBJECTIVES In Korea, a national coronavirus disease 2019 (COVID-19) vaccination program was implemented, including 4 vaccines against COVID-19. A text messaging-based survey, in addition to a passive adverse event reporting system, was launched to quickly report unusual symptoms post-vaccination. This study compared the frequency of adverse events after COVID-19 vaccination based on the vaccine type and the type of 2-dose regimen (homologous or heterologous). METHODS Self-reported adverse events were collected through a text-message survey for 7 days after each vaccination. This study included 50,950 vaccine recipients who responded to the survey at least once. Informed consent to receive surveys via text was obtained from the vaccine recipients on the date of first vaccination. RESULTS The recipients of mRNA vaccines reported local and systemic reactions 1.6 times to 2.8 times more frequently after dose 2 than after dose 1 (p

Alopecia areata (AA) is an autoimmune dermatological disease with multifactorial etiology and is characterized by reversible hair loss in patches. AA may be closely related to emotional stress and influenced by psychological factors as part of its pathophysiology; however, its etiology remains predominantly unknown. This review aimed to elucidate the association between AA occurrence and the neuropeptide substance P (SP) and corticotropin-releasing hormone (CRH), which are secreted during emotional stress, and have been understood to initiate and advance the etiopathogenesis of AA. Therefore, this review aimed to explain how SP and CRH initiate and contribute to the etiopathogenesis of AA. To assess the etiopathogenesis of AA, we conducted a literature search on PubMed and ClinicalTrials.gov. Overall, several authors described interactions between the hair follicles (HFs) and the stress-associated signaling substances, including SP and CRH, in the etiology of AA; this was attributed to the understanding in that AA can occur without the loss of HFs, similar to that observed in hereditary hair loss with age. Most studies demonstrated that the collapse of “immune privilege” plays a crucial role in the development and exacerbation of the AA; nonetheless, a few studies indicated that substances unrelated to autoimmunity may also cause apoptosis in keratocytes, leading to the development of AA. We investigated both the autoimmune and apoptotic pathways within the etiology of AA and assessed the potential interactions between the key substances of both pathways to evaluate potential therapeutic targets for the treatment of AA. Clinical trials of marketed/unreviewed intervention drugs for AA were also reviewed to determine their corresponding target pathways.

Cancer remains a major global health challenge. Traditional chemotherapy often results in side effects and drug resistance, necessitating the development of alternative treatment strategies such as gene therapy. Mesoporous silica nanoparticles (MSNs) offer many advantages as a gene delivery carrier, including high loading capacity, controlled drug release, and easy surface functionalization. MSNs are biodegradable and biocompatible, making them promising candidates for drug delivery applications. Recent studies demonstrating the use of MSNs for the delivery of therapeutic nucleic acids to cancer cells have been reviewed, along with their potential as a tool for cancer therapy. The major challenges and future interventions of MSNs as gene delivery carriers for cancer therapy are discussed.

Electrocatalytic conversion of nitrogen oxides to value-added chemicals is a promising strategy for mitigating the imbalance in the global nitrogen cycle. Here, the authors present iron–nitrogen-doped carbon as an efficient and durable electrocatalyst for selective nitric oxide reduction to hydroxylamine.

Fiber media filtration for combined sewer overflow (CSO) treatment was evaluated in this work. Pilot-scale experiments of CSO treatment involve seven layers that form radial-type fiber media filters. The fiber media filter was characterized using analysis techniques and exhibited extremely high hydrophobicity and negative charge. The results obtained for a sewer treatment plant at Tancheon in Seoul revealed potential for suspended solid, total organic carbon, and biochemical oxygen demand removal with efficiencies of 89.6%, 56%, and 42%, respectively. The results are consistent with the sieving effects and electrostatic repulsion between fiber media and pollutants. Head loss was induced by organic pollutants and was 10.5 cm after 20 h of operation. To mitigate the head loss induced by organic pollutants on the fiber media filter, sodium hypochlorite (NaClO) was used as a chemical backwashing agent. An NaClO concentration of 2000 mg/L with a soaking time of 24 h yielded an optimal head loss recovery of 96.2% of the initial head loss obtained for the virgin fiber media filter without media filter degradation. The result of the present study will provide practical insight and act as a technical guide for CSO treatment plant engineers.

With the recent development of high performance photography devices, vibration measurements using digital image processing can be utilized for the condition monitoring and the analysis of generation mechanisms. High-quality image recording provides very dense spatial information unlike physical sensors with a limited number of point-oriented measurements and output channels such as accelerometers. Moreover, image acquisition is a non-contact technique and ensures that the installed sensors do not affect the mass or stiffness. In this study, the vibration mode of rails is investigated using the phase-based video magnification method. An extensive amount of information that cannot be detected by human eyes, can be obtained with this imaging motion magnification technique by amplifying and visualising the minute vibrational movements. Flexural vibration modes in rails generate rolling noise, especially at high frequencies where the displacement amplitudes are small. The motion magnification method is applied using a high-speed camera to measure the rail mode shapes. The measured mode shapes are compared to the numerical results obtained from the waveguide finite element method. This method helps in understanding the vibration generation and the transfer mechanisms in the waveguide structures with a uniform cross-section in the lengthwise direction such as a railway track.

Magnetic RAM (MRAM)-based crossbar array has a great potential as a platform for in-memory binary neural network (BNN) computing. However, the number of word-lines that can be activated simultaneously is limited because of the low $I_{H}/I_{L}$ ratio of MRAM, which makes BNNs more vulnerable to the device variation. To address this issue, we propose an algorithm/hardware co-design methodology. First, we choose a promising memristor crossbar array (MCA) structure based on the sensitivity analysis to process variations. Since the selected MCA structure becomes more tolerant to the device variation when the number of 1 in input activation values decreases, we apply an input distribution regularization scheme to reduce the number of 1 in input of BNNs during training. We further improve the robustness against device variation by adopting the retraining scheme based on knowledge distillation. Experimental results show that the proposed method makes BNNs more tolerant to MRAM variation and increases the number of parallel word-line activation significantly; thereby achieving improved throughput and energy efficiency.

The recent advent of neural approaches for developing each dialog component in task-oriented dialog systems has remarkably improved, yet optimizing the overall system performance remains a challenge. Besides, previous research on modeling complicated multi-domain goal-oriented dialogs in end-to-end fashion has been limited. In this paper, we present an effective multi-domain end-to-end trainable neural dialog system SUMBT+LaRL that incorporates two previous strong models and facilitates them to be fully differentiable. Specifically, the SUMBT+ estimates user-acts as well as dialog belief states, and the LaRL models latent system action spaces and generates responses given the estimated contexts. We emphasize that the training framework of three steps significantly and stably increase dialog success rates: separately pretraining the SUMBT+ and LaRL, fine-tuning the entire system, and then reinforcement learning of dialog policy. We also introduce new reward criteria of reinforcement learning for dialog policy training. Then, we discuss experimental results depending on the reward criteria and different dialog evaluation methods. Consequently, our model achieved the new state-of-the-art success rate of 85.4% on corpus-based evaluation, and a comparable success rate of 81.40% on simulator-based evaluation provided by the DSTC8 challenge. To our best knowledge, our work is the first comprehensive study of a modularized E2E multi-domain dialog system that learning from each component to the entire dialog policy for task success.

Understanding reaction intermediates provides a foundation for active electrocatalysts’ design, but it remains elusive for heterogeneous electrocatalysts. Here, the authors report the spectroscopic characterization of low-spin Mn(IV)-oxo as the active intermediates during electrochemical water oxidation.

Designing efficient thin-film transistors and circuits based on transparent p-type semiconductors remains a challenge. Here, the authors propose a solution-based doping approach to realize high performance transparent inorganic p-type semiconductors (Zn-doped CuI) by spin coating at 80 C with good operational stability.

A team of operators is required for nuclear power plant operation, and communication between the operators is an important aspect of the team's ability to successfully carry out tasks. It has been difficult to evaluate the quality of this communication though, and as the relationship between communication quality and team performance has yet to be clarified, it has not been applied to most human reliability analysis (HRA) methodologies. This study investigates the relationship between the quality of communication and team performance using data from a full-scope training simulator of a digital main control room (MCR). Two important characteristics of communication were considered to determine quality: each operator's ability to self-confirm the status of a given task in a digital MCR, and the type of communication, as divided into 1-way, 2-way, and 3-way between operators. To measure team performance, the concept of an unsafe act was employed, which is defined as a human error that has the potential to negatively affect plant safety. Analysis results showed that the communication quality and team performance were related to each other. With this more clearly defined relationship, the results of this study can be applied to related performance shaping factors to improve HRA.

Abstract The hybridization of conductive nanospecies has garnered significant research interest because of its high efficacy in improving the diverse functionalities of nanostructured materials. In this study, a novel synthetic strategy is developed to optimize the defect structure, structural ordering, and energy‐related functionality of nanostructured‐materials by employing a multilayer multicomponent two‐dimenstional (2D) graphene/metal oxide/graphene nanosheet (NS) as a versatile hybridization matrix. The hybridization of the robust trilayer, polydiallyldiammonium (PDDA)‐anchored reduced‐graphene oxide (prGO)/metal oxide/prGO NS effectively enhance the structural ordering and porosity of the hybridized MoS2/MnO2 NS through suppression of defect formation and tight stacking. In comparison with monolayer rGO/RuO2 NS‐based homologs, the 2D superlattice trilayer prGO/RuO2/prGO NS hybrids deliver better functionalities as a hydrogen evolution electrocatalyst and as a supercapacitor electrode, demonstrating the merits of hybridization with multilayer NSs. The advantages of using multilayer multicomponent conductive NSs as hybridization matrices arise from the enhancement of charge and mass transport through the layer flattening or defect suppression of the hybridized NSs and the increase in porosity, as evidenced by density functional theory calculations. Finally, the universal utility of multilayer NSs is confirmed by investigating the strong effect of the stacking order on the electrocatalytic functionality of MoS2/rGO/RuO2 films fabricated through layer‐by‐layer deposition.

New materials for electrochemical energy storage and conversion are the key to the electrification and sustainable development of our modern societies. Molecular modelling based on the principles of quantum mechanics and statistical mechanics as well as empowered by machine learning techniques can help us to understand, control and design electrochemical energy materials at atomistic precision. Therefore, this roadmap, which is a collection of authoritative opinions, serves as a gateway for both the experts and the beginners to have a quick overview of the current status and corresponding challenges in molecular modelling of electrochemical energy materials for batteries, supercapacitors, CO _2 reduction reaction, and fuel cell applications.

Although river water storage contributes to Total Terrestrial Water Storage (TWS) variations obtained from GRACE satellite gravimetry, it is unclear if computationally expensive river routing schemes are required when GRACE data is used for calibration and validation in global hydrological modeling studies. Here, we investigate the role of river water storage on calibration and validation of a parsimonious global hydrological model. In a multi-criteria calibration approach, the model is constrained against either GRACE TWS or TWS from which river water storage is removed. While we find that removing river water storage changes the TWS constraint regionally and globally, there are no significant implications for model calibration and the resulting simulations. However, adding modeled river water storage a-posteriori to calibrated TWS simulations improves model validation against seasonal GRACE TWS variations globally and regionally, especially in tropics and Northern low- and wetlands. While our findings justify the exclusion of explicit river routing for global model calibration, we find that the inclusion of river water storage is relevant for model evaluation.

Bioactive compounds are widely used in the bio-industry because of their antioxidant and antibacterial activities. Because of excessive oxidative stress, which causes various diseases in humans, and because preservatives used in bioproducts cause allergies and contact dermatitis, it is important to use natural bioactive compounds in bioproducts to minimize oxidative stress. α-bisabolol (ABS) is a natural compound with both antioxidant and antibacterial properties. However, its water-insolubility makes its utilization in bioproducts difficult. In this study, ABS-loaded polyglyceryl-4 caprate nanoparticles (ABS@NPs) with improved aqueous stability and ABS loading were fabricated using an encapsulation method. The long-term stability of the ABS@NPs was analyzed with dynamic light scattering and methylene blue-staining to determine the optimized ABS concentration in ABS@NPs (10 wt%). The ABS@NPs exhibited excellent antioxidant activity, according to the 2,2-diphenyl-1-picrylhydrazyl assay and in vitro reactive oxygen species generation in NIH-3T3 fibroblast cells, and an outstanding antibacterial effect, as determined using the Staphylococcus aureus colony-counting method. Furthermore, we evaluated the biocompatibility of the ABS@NPs in vitro. This study suggests that ABS@NPs with improved antioxidant and antibacterial properties can be used to treat diseases related to various oxidative stresses and can be applied in many fields, such as pharmaceuticals, cosmetics, and foods.

An 11-year-old castrated male Shih Tzu was referred for lethargy and melena. The hematocrit level was 18.8% (normal range: 36–56%), indicating severe anemia. Abdominal ultrasound revealed a round-to-oval-shaped mass in the stomach. Computed tomography (CT) revealed an intraluminal mass (17 × 12 × 15 mm) cranial to the pyloric antrum. After obtaining informed consent from the owner, exploratory laparotomy and subsequent gastrostomy were performed, showing an ulcerated mass potentially responsible for the severe anemia. A lump of hair was firmly attached to the ulcerated surface of the mass. After complete removal of the mass, the anemia resolved spontaneously. Histological examination revealed that the mass was a gastric hyperplastic polyp. At the 6-month follow-up, the dog was healthy with a normal hematocrit level. Gastric hyperplastic polyps are tumor-like lesions arising from the mucosal surface of the stomach, and projecting into the lumen. They can appear in any part of the stomach, and are usually found incidentally during gastric endoscopy or necropsy. The clinical signs include chronic occult blood loss, abdominal pain, and gastric tract obstruction. Gastric polyps causing acute blood loss anemia have rarely been reported in human medicine. To our knowledge, this is the first report describing a gastric hyperplastic polyp that caused severe anemia because of acute blood loss in a dog.

Necroptosis is a form of programmed cell death with features of necrosis and apoptosis that occurs in the intestinal epithelium of patients with inflammatory bowel disease (IBD), including ulcerative colitis and Crohn’s disease. In addition, necroptosis has also been observed in enterocytes in animal models of dextran sulfate sodium (DSS)-induced colitis. Thus, the discovery of natural products for regulating necroptosis may represent an important therapeutic strategy for improving IBD. We found that Magnolia officinalis bark extract (MBE) prevented weight loss and suppressed the activation of the proinflammatory cytokine IL6 in DSS-induced colitis. Furthermore, MBE restored the length of the damaged colon and decreased the expression of necroptosis markers in mice with DSS-induced colitis. In vitro, necroptosis-induced reactive oxygen species (ROS) production was reduced by MBE, and the expression of COX2, a target protein of ROS, was simultaneously suppressed. Both magnolol and honokiol, the two major bioactive compounds in MBE, inhibited necroptosis in human primary intestinal epithelial cells and colorectal adenocarcinoma cells. Our findings highlight the effectiveness of MBE in modulating enterocyte necroptosis and suggest that MBE may be developed as a natural, disease-targeting drug for the treatment of colitis.

RNA interference (RNAi) therapies have significant potential for the treatment of inflammatory bowel diseases (IBD). Although administering small interfering RNA (siRNA) via an oral route is desirable, various hurdles including physicochemical, mucus, and cellular uptake barriers of the gastrointestinal tract (GIT) impede both the delivery of siRNA to the target site and the action of siRNA drugs at the target site. In this review, we first discuss various physicochemical and biological barriers in the GI tract. Furthermore, we present recent strategies and the progress of oral siRNA delivery strategies to treat IBD. Finally, we consider the challenges faced in the use of these strategies and future directions of oral siRNA delivery strategies.

Electroactive polymer (EAP) is a polymer that reacts to electrical stimuli, such as voltage, and can be divided into electronic and ionic EAP by an electrical energy transfer mechanism within the polymer. The mechanism of ionic EAP is the movement of the positive ions inducing voltage change in the polymer membrane. Among the ionic EAPs, an ionic polymer–metal composite (IPMC) is composed of a metal electrode on the surface of the polymer membrane. A common material for the polymer membrane of IPMC is Nafion containing hydrogen ions, and platinum, gold, and silver are commonly used for the electrode. As a result, IPMC has advantages, such as low voltage requirements, large bending displacement, and bidirectional actuation. Manufacturing of IPMC is composed of preparing the polymer membrane and plating electrode. Preparation methods for the membrane include solution casting, hot pressing, and 3D printing. Meanwhile, electrode formation methods include electroless plating, electroplating, direct assembly process, and sputtering deposition. The manufactured IPMC is widely demonstrated in applications such as grippers, micro-pumps, biomedical, biomimetics, bending sensors, flow sensors, energy harvesters, biosensors, and humidity sensors. This paper will review the overall field of IPMC by demonstrating the categorization, principle, materials, and manufacturing method of IPMC and its applications.

The π–π interaction is a major driving force that stabilizes protein assemblies during protein folding. Recent studies have additionally demonstrated its involvement in the liquid–liquid phase separation (LLPS) of intrinsically disordered proteins (IDPs). As the participating residues in IDPs are exposed to water, π–π interactions for LLPS must be modeled in water, as opposed to the interactions that are often established at the hydrophobic domains of folded proteins. Thus, we investigated the association of free energies of benzene and phenol dimers in water by integrating van der Waals (vdW)-corrected density functional theory (DFT) and DFT in classical explicit solvents (DFT-CES). By comparing the vdW-corrected DFT and DFT-CES results with high-level wavefunction calculations and experimental solvation free energies, respectively, we established the quantitative credibility of these approaches, enabling a reliable prediction of the benzene and phenol dimer association free energies in water. We discovered that solvation influences dimer association free energies, but not significantly when no direct hydrogen-bond-type interaction exists between two monomeric units, which can be explained by the enthalpy–entropy compensation. Our comprehensive computational study of the solvation effect on π–π interactions in water could help us understand the molecular-level driving mechanism underlying the IDP phase behaviors.

Super engineering plastics that utilise bio-derived cyclic monomers rarely offer the same thermal/mechanical properties, scalability and recyclability as petrochemical derived plastics. Here the authors use a phase transfer catalyst to synthesise a transparent, recyclable and tough isosorbide-based polymer with a high molecular weight.