High-speed and large-scale intrinsically stretchable integrated circuits.

Intrinsically stretchable electronics with skin-like mechanical properties have been identified as a promising platform for emerging applications ranging from continuous physiological monitoring to real-time analysis of health conditions, to closed-loop delivery of autonomous medical treatment1-7. However, current technologies could only reach electrical performance at amorphous-silicon level (that is, charge-carrier mobility of about 1 cm2 V-1 s-1), low integration scale (for example, 54 transistors per circuit) and limited functionalities8-11. Here we report high-density, intrinsically stretchable transistors and integrated circuits with high driving ability, high operation speed and large-scale integration. They were enabled by a combination of innovations in materials, fabrication process design, device engineering and circuit design. Our intrinsically stretchable transistors exhibit an average field-effect mobility of more than 20 cm2 V-1 s-1 under 100% strain, a device density of 100,000 transistors per cm2, including interconnects and a high drive current of around 2 µA µm-1 at a supply voltage of 5 V. Notably, these achieved parameters are on par with state-of-the-art flexible transistors based on metal-oxide, carbon nanotube and polycrystalline silicon materials on plastic substrates12-14. Furthermore, we realize a large-scale integrated circuit with more than 1,000 transistors and a stage-switching frequency greater than 1 MHz, for the first time, to our knowledge, in intrinsically stretchable electronics. Moreover, we demonstrate a high-throughput braille recognition system that surpasses human skin sensing ability, enabled by an active-matrix tactile sensor array with a record-high density of 2,500 units per cm2, and a light-emitting diode display with a high refreshing speed of 60 Hz and excellent mechanical robustness. The above advancements in device performance have substantially enhanced the abilities of skin-like electronics.

Construction of the Glycolysis Metabolic Pathway Inside an Artificial Cell for the Synthesis of Amino Acid and Its Reversible Deformation.

The bottom-up construction of artificial cells is beneficial for understanding cell working mechanisms. The glycolysis metabolism mimicry inside artificial cells is challenging. Herein, the glycolytic pathway (Entner-Doudoroff pathway in archaea) is reconstituted inside artificial cells. The glycolytic pathway comprising glucose dehydrogenase (GDH), gluconate dehydratase (GAD), and 2-keto-3-deoxygluconate aldolase (KDGA) converts glucose molecules to pyruvate molecules. Inside artificial cells, pyruvate molecules are further converted into alanine with the help of alanine dehydrogenase (AlaDH) to build a metabolic pathway for synthesizing amino acid. On the other hand, the pyruvate molecules from glycolysis stimulate the living mitochondria to produce ATP inside artificial cells, which further trigger actin monomers to polymerize to form actin filaments. With the addition of methylcellulose inside the artificial cell, the actin filaments form adjacent to the inner lipid bilayer, deforming the artificial cell from a spherical shape to a spindle shape. The spindle-shaped artificial cell reverses to a spherical shape by depolymerizing the actin filament upon laser irradiation. The glycolytic pathway and its further extension to produce amino acids (or ATP) inside artificial cells pave the path to build functional artificial cells with more complicated metabolic pathways.

Development of a double antibody sandwich ELISA method for the quantitative detection of serum C-reactive protein based on nanobody.

In this study, we successfully developed a nanobody-based double antibody sandwich ELISA kit for the detection of clinical serum C-reactive protein (CRP) by using two novel CRP specific nanobodies. The developed method exhibited a linear detection range of approximately 6-200 ng/mL, with a detection limit of 1 ng/mL. Furthermore, the method demonstrated excellent specificity, as there was no cross-reactivity with interfering substances such as total bilirubin and hemoglobin and so on. To assess reproducibility, independent measurements of the samples were conducted under experimental conditions, resulting in intra- and inter-batch coefficients of variation below 10% and a recovery rate of 93%-102%. These results indicate robust reproducibility of the method. To evaluate the performance of the developed kit, we collected 90 clinical samples for correlation analysis with commercial kits. The results showed a high correlation coefficient value (R2) of 0.98, indicating accurate concordance between the developed and commercial kits. In conclusion, our study successfully developed a nanobody-based double antibody sandwich ELISA kit to detect clinical serum CRP. The utilization of nanobodies represents a significant advancement in the field of CRP immunoassay development. The developed kit demonstrates excellent performance characteristics and holds promise for clinical applications.

ANXA5: A Key Regulator of Immune Cell Infiltration in Hepatocellular Carcinoma.

BACKGROUND Hepatocellular carcinoma (HCC) poses a significant threat to human life and is the most prevalent form of liver cancer. The intricate interplay between apoptosis, a common form of programmed cell death, and its role in immune regulation stands as a crucial mechanism influencing tumor metastasis. MATERIAL AND METHODS Utilizing HCC samples from the TCGA database and 61 anoikis-related genes (ARGs) sourced from GeneCards, we analyzed the relationship between ARGs and immune cell infiltration in HCC. Subsequently, we identified long non-coding RNAs (lncRNAs) associated with ARGs, using the least absolute shrinkage and selection operator (LASSO) regression analysis to construct a robust prognostic model. The predictive capabilities of the model were then validated through examination in a single-cell dataset. RESULTS Our constructed prognostic model, derived from lncRNAs linked to ARGs, comprised 11 significant lncRNAs: NRAV, MCM3AP-AS1, OTUD6B-AS1, AC026356.1, AC009133.1, DDX11-AS1, AC108463.2, MIR4435-2HG, WARS2-AS1, LINC01094, and HCG18. The risk score assigned to HCC samples demonstrated associations with immune indicators and the infiltration of immune cells. Further, we identified Annexin A5 (ANXA5) as the pivotal gene among ARGs, with it exerting a prominent role in regulating the lncRNA gene signature. Our validation in a single-cell database elucidated the involvement of ANXA5 in immune cell infiltration, specifically in the regulation of mononuclear cells. CONCLUSIONS This study delves into the intricate correlation between ARGs and immune cell infiltration in HCC, culminating in the development of a novel prognostic model reliant on 11 ARGs-associated lncRNAs. Furthermore, our findings highlight ANXA5 as a promising target for immune regulation in HCC, offering new perspectives for immune therapy in the context of HCC.

From field soil sampling to watershed model: Upscaling by integrating information entropy and interpolation method.

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation.

Synthesis of Chiral α-Aryl Ketones by Photoredox/Nickel-Catalyzed Enantioconvergent Acyl Cross-Coupling with Organotrifluoroborate.

Photoredox/nickel-catalyzed enantioconvergent acyl cross-coupling of carboxylic derivatives with racemic secondary organotrifluoroborate was developed for the synthesis of an enolizable chiral α-aryl ketone under mild neutral conditions. Moderate to high yields and good enantioselectivities were achieved.

The Relationship between Organizational Climate and Teaching Innovation among Preschool Teachers: The Mediating Effect of Teaching Efficacy.

Preschool teachers' teaching innovation is an important factor in enhancing teaching quality and improving children's creativity. Based on ecological systems theory and self-determination theory, the purpose of this study was to investigate the relationship between kindergartens' organizational climate and preschool teachers' teaching innovation and the mediating role of teaching efficacy in it. In this study, an online questionnaire was distributed to 2092 preschool teachers from different provinces using an Organizational Climate Scale, Teaching Efficacy Scale, and Teaching Innovation Scale. The study used SPSS 25.0 software and the SPSS PROCESS macro program for data processing. The results showed that there was a positive correlation among kindergartens' organizational climate, teaching efficacy, and teaching innovation, and that kindergartens' organizational climate not only directly and positively predicted teaching innovation, but also indirectly predicted teaching innovation through the mediating role of teaching efficacy. The study explored the internal and external influences on preschool teachers' teaching innovation and revealed their underlying mechanisms, providing theoretical support for research and educational practice on preschool teachers' teaching innovation and children's creativity.

Identifying mechanisms of persecutory ideation maintenance with smartphone technology: Examining threat importance, certainty, rumination, and behavior change.

Previous cross-sectional and laboratory research has identified risk factors for persecutory ideation including rumination, negative affect, and safety-seeking behaviors. Questions remain about what in-the-moment factors link general negative affect to PI as well as which maintain PI over time. In the present study, N = 219 individuals completed momentary assessments of PI as well as four factors (attributing threats as certain and important, ruminating, and changing one's behavior in response) proposed to maintain PI over time. Linear mixed effects models were used to analyze multiple time-varying relationships, including these factors predicting negative affect and vice versa, as well as factors predicting maintenance of PI over time. Linear mixed effects models were used to analyze multiple time-varying relationships, examining each PI-related factor predicting negative affect, negative affect predicting each PI-related factor, as well as each factor predicting maintenance of PI over time. All four factors were associated with increases in subsequent day self-reported severity of PI, suggesting all four increased the likelihood of maintaining or worsening next-day PI. Results of this study confirm that the proposed factors are key in maintaining a cycle by which PI and negative affect are maintained over time. These factors may represent targets for momentary interventions.

Direct Identification of Intact Proteins Using a Low-Resolution Mass Spectrometer with CIDn/ETnoD.

Over the past decades, proteomics has become increasingly important and a heavily discussed topic. The identification of intact proteins remains a major focus in this field. While most intact proteins are analyzed using high-resolution mass spectrometry, identifying them through low-resolution mass spectrometry continues to pose challenges. In our study, we investigated the capability of identifying various intact proteins using collision-induced dissociation (CID) and electron transfer without dissociation (ETnoD). Using myoglobin as our test protein, stable product ions were generated with CID, and the identities of the product ions were identified with ETnoD. ETnoD uses a short activation time (AcT, 5 ms) to create sequential charge-reduced precursor ion (CRI). The charges of the fragments and their sequences were determined with corresponding CRI. The product ions can be selected for subsequent CID (termed CIDn) combined with ETnoD for further sequence identification and validation. We refer to this method as CIDn/ETnoD. The use of a multistage CID activation (CIDn) and ETnoD protocol has been applied to several intact proteins to obtain multiple sequence identifications.

Capturing the College Experience: A Four-Year Mobile Sensing Study of Mental Health, Resilience and Behavior of College Students during the Pandemic.

Understanding the dynamics of mental health among undergraduate students across the college years is of critical importance, particularly during a global pandemic. In our study, we track two cohorts of first-year students at Dartmouth College for four years, both on and off campus, creating the longest longitudinal mobile sensing study to date. Using passive sensor data, surveys, and interviews, we capture changing behaviors before, during, and after the COVID-19 pandemic subsides. Our findings reveal the pandemic's impact on students' mental health, gender based behavioral differences, impact of changing living conditions and evidence of persistent behavioral patterns as the pandemic subsides. We observe that while some behaviors return to normal, others remain elevated. Tracking over 200 undergraduate students from high school to graduation, our study provides invaluable insights into changing behaviors, resilience and mental health in college life. Conducting a long-term study with frequent phone OS updates poses significant challenges for mobile sensing apps, data completeness and compliance. Our results offer new insights for Human-Computer Interaction researchers, educators and administrators regarding college life pressures. We also detail the public release of the de-identified College Experience Study dataset used in this paper and discuss a number of open research questions that could be studied using the public dataset.

MoodCapture: Depression Detection Using In-the-Wild Smartphone Images.

MoodCapture presents a novel approach that assesses depression based on images automatically captured from the front-facing camera of smartphones as people go about their daily lives. We collect over 125,000 photos in the wild from N=177 participants diagnosed with major depressive disorder for 90 days. Images are captured naturalistically while participants respond to the PHQ-8 depression survey question: "I have felt down, depressed, or hopeless". Our analysis explores important image attributes, such as angle, dominant colors, location, objects, and lighting. We show that a random forest trained with face landmarks can classify samples as depressed or non-depressed and predict raw PHQ-8 scores effectively. Our post-hoc analysis provides several insights through an ablation study, feature importance analysis, and bias assessment. Importantly, we evaluate user concerns about using MoodCapture to detect depression based on sharing photos, providing critical insights into privacy concerns that inform the future design of in-the-wild image-based mental health assessment tools.

Structural basis and synergism of ATP and Na+ activation in bacterial K+ uptake system KtrAB.

The K+ uptake system KtrAB is essential for bacterial survival in low K+ environments. The activity of KtrAB is regulated by nucleotides and Na+. Previous studies proposed a putative gating mechanism of KtrB regulated by KtrA upon binding to ATP or ADP. However, how Na+ activates KtrAB and the Na+ binding site remain unknown. Here we present the cryo-EM structures of ATP- and ADP-bound KtrAB from Bacillus subtilis (BsKtrAB) both solved at 2.8 Å. A cryo-EM density at the intra-dimer interface of ATP-KtrA was identified as Na+, as supported by X-ray crystallography and ICP-MS. Thermostability assays and functional studies demonstrated that Na+ binding stabilizes the ATP-bound BsKtrAB complex and enhances its K+ flux activity. Comparing ATP- and ADP-BsKtrAB structures suggests that BsKtrB Arg417 and Phe91 serve as a channel gate. The synergism of ATP and Na+ in activating BsKtrAB is likely applicable to Na+-activated K+ channels in central nervous system.

Left-Behind Experiences and Cyberbullying Behavior in Chinese College Students: The Mediation of Sense of Security and the Moderation of Gender.

Left-behind children seem to be more sensitive in interpersonal communication, find it more difficult to establish a stable, safe relationship with surrounding people, and have fewer positive coping styles when encountering problems, thus the aim of the present study was to explore the association between left-behind experiences and cyberbullying behavior among Chinese college students through the mediation of sense of security and the moderation of gender. A questionnaire survey comprised 553 college students with left-behind experiences and 526 college students without such experiences. The results showed that, firstly, cyberbullying behavior was significantly higher in college students with left-behind experiences than those without such experiences; secondly, left-behind experiences and cyberbullying behavior in college students was partially mediated by a sense of security; and finally, that gender moderated the mediation of the sense of security between left-behind experiences and cyberbullying behavior. This study suggests the family environment is important for individual growth and illustrates how the influence of childhood left-behind experience persists in individuals.

Artificial organelles for sustainable chemical energy conversion and production in artificial cells: Artificial mitochondrion and chloroplasts.

Sustainable energy conversion modules are the main challenges for building complex reaction cascades in artificial cells. Recent advances in biotechnology have enabled this sustainable energy supply, especially the adenosine triphosphate (ATP), by mimicking the organelles, which are the core structures for energy conversion in living cells. Three components are mainly shared by the artificial organelles: the membrane compartment separating the inner and outer parts, membrane proteins for proton translocation, and the molecular rotary machine for ATP synthesis. Depending on the initiation factors, they are further categorized into artificial mitochondrion and artificial chloroplasts, which use chemical nutrients for oxidative phosphorylation and light for photosynthesis, respectively. In this review, we summarize the essential components needed for artificial organelles and then review the recent progress on two different artificial organelles. Recent strategies, purified and identified proteins, and working principles are discussed. With more study on the artificial mitochondrion and artificial chloroplasts, they are expected to be very powerful tools, allowing us to achieve complex cascading reactions in artificial cells, like the ones that happen in real cells.

Analysis of the microbial diversity in takin (Budorcas taxicolor) feces.

Introduction: The intestinal tract of animals is a complex and dynamic microecosystem that is inextricably linked to the health of the host organism. Takin (Budorcas taxicolor) is a threatened species, and its gut microbiome is poorly understood. Therefore, this study aimed to analyze the microbial community structure and potential pathogens of takin. Methods: Takin fecal samples were collected from five sites in a nature reserve to ensure the uniformity of sample collection, determine the effects of different geographical locations on gut microbes, and analyze the differences in microbial communities between sites. Subsequently, high-throughput 16S rDNA gene sequencing was performed to analyze the microbial diversity and potential pathogens in the gut; the findings were verified by isolating and culturing bacteria and metagenomic sequencing. Results and discussion: The takin gut microflora consisted mainly of four phyla: Firmicutes (69.72%), Bacteroidota (13.55%), Proteobacteria (9.02%), and Verrucomicrobiota (3.77%), representing 96.07% of all microorganisms. The main genera were UCG-005 (20.25%), UCG-010_unclassified (12.35%), Firmicus_unclassified (4.03%), and Rumino coccsea_unclassified (3.49%), while the main species were assigned to Bacteria_unclassified. Potential pathogens were also detected, which could be used as a reference for the protection of takin. Pseudomonas presented the highest abundance at Shuichiping and may represent the main pathogen responsible for the death of takin at the site. This study provides an important reference for investigating the composition of the bacterial community in the intestine of takin.

COVID Student Study: A Year in the Life of College Students during the COVID-19 Pandemic Through the Lens of Mobile Phone Sensing.

The COVID-19 pandemic continues to affect the daily life of college students, impacting their social life, education, stress levels and overall mental well-being. We study and assess behavioral changes of N=180 undergraduate college students one year prior to the pandemic as a baseline and then during the first year of the pandemic using mobile phone sensing and behavioral inference. We observe that certain groups of students experience the pandemic very differently. Furthermore, we explore the association of self-reported COVID-19 concern with students' behavior and mental health. We find that heightened COVID-19 concern is correlated with increased depression, anxiety and stress. We evaluate the performance of different deep learning models to classify student COVID-19 concerns with an AUROC and F1 score of 0.70 and 0.71, respectively. Our study spans a two-year period and provides a number of important insights into the life of college students during this period.