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Abstract We consider the bending of light around a compact astrophysical object with both the electric field and the magnetic field in Einstein–Born–Infeld theory. From the null geodesic of a light ray passing a massive object with electric charge and magnetic dipole, the effective metric was obtained from the light cone condition reflecting the nonlinear electromagnetic effects. We found the asymptotic form of the effective metric up to the first order in gravitational constant G and Born–Infeld parameter $$1/\beta ^2$$ 1 / β 2 on the equatorial plane. Then we compute the bending angle of light from the geodesic equation. The result includes particular cases where only one type of field is present taking the appropriate limits.

Calcified amorphous tumors (CATs) of the heart are rare non-neoplastic cardiac masses primarily found in the mitral valve or annulus. However, their exact pathogenesis remains unknown. In this case report, we describe the CT and MRI findings and differentiating features of cardiac a CAT in the left atrium of a 79-year-old female.

Abstract In pathological diagnostics, histological images highlight the oncological features of excised specimens, but they require laborious and costly staining procedures. Despite recent innovations in label-free microscopy that simplify complex staining procedures, technical limitations and inadequate histological visualization are still problems in clinical settings. Here, we demonstrate an interconnected deep learning (DL)-based framework for performing automated virtual staining, segmentation, and classification in label-free photoacoustic histology (PAH) of human specimens. The framework comprises three components: (1) an explainable contrastive unpaired translation (E-CUT) method for virtual H&E (VHE) staining, (2) an U-net architecture for feature segmentation, and (3) a DL-based stepwise feature fusion method (StepFF) for classification. The framework demonstrates promising performance at each step of its application to human liver cancers. In virtual staining, the E-CUT preserves the morphological aspects of the cell nucleus and cytoplasm, making VHE images highly similar to real H&E ones. In segmentation, various features (e.g., the cell area, number of cells, and the distance between cell nuclei) have been successfully segmented in VHE images. Finally, by using deep feature vectors from PAH, VHE, and segmented images, StepFF has achieved a 98.00% classification accuracy, compared to the 94.80% accuracy of conventional PAH classification. In particular, StepFF’s classification reached a sensitivity of 100% based on the evaluation of three pathologists, demonstrating its applicability in real clinical settings. This series of DL methods for label-free PAH has great potential as a practical clinical strategy for digital pathology.

Dogs that had splenectomy are predisposed to fatal thrombotic conditions, and thrombocytosis is a risk factor for post-splenectomy hypercoagulability. However, in veterinary medicine, there are no specific therapeutic approaches for managing this hypercoagulability. This study aimed to determine the preventive effect of clopidogrel on post-operative hypercoagulability during the first 2 weeks post-splenectomy in dogs with splenic masses. This study included 12 dogs that had splenectomy. Seven dogs received no treatment (group A), and five were treated with clopidogrel (group B). Clopidogrel was loaded at 10 mg/kg on day 2 and continued at 2 mg/kg until day 14. Blood samples were collected on the day of surgery and 2, 7, and 14 days after splenectomy in both groups. In group B, thromboelastography (TEG) was performed on the same days. In group A, there was significant elevation of platelet counts on days 7 (p = 0.007) and 14 (p = 0.001) compared to day 0. In group B, the platelet counts were significantly elevated on day 7 (p = 0.032) but no significant difference was found on day 14 compared to day 0. Platelet counts on day 14 were significantly higher in group A than in group B (p = 0.03). The lower platelet counts were correlated with alterations in TEG parameters, and no significant differences were found in the K and α-angle values at all postoperative assessment points compared to day 0. Our study suggests that clopidogrel may reduce post-operative thrombocytosis and hypercoagulability in dogs that undergo splenectomy for splenic masses.

Abstract Background Recent advances in high-resolution mass spectrometry have now enabled the study of proteomes at the single-cell level, offering the potential to unveil novel aspects of cellular processes. Remarkably, there has been no prior attempt to investigate single-plant cell proteomes. In this study, we aimed to explore the feasibility of conducting a proteomic analysis on individual protoplasts. Findings As a result, our analysis identified 978 proteins from the 180 protoplasts, aligning with well-known biological processes in plant leaves, such as photosynthetic electron transport in photosystem II. Employing the SCP package in the SCoPE2 workflow revealed a notable batch effect and extensive missing values in the data. Following correction, we observed the heterogeneity in single-protoplast proteome expression. Comparing the results of single-protoplast proteomics with those of bulk leaf proteomics, we noted that only a small fraction of bulk data was detected in the single-protoplast proteomics data, highlighting a technical limitation of the current single-cell proteomics method. Conclusions In summary, we demonstrated the feasibility of conducting a single-protoplast proteomic experiment, revealing heterogeneity in plant cellular proteome expression. This underscores the importance of analyzing a substantial number of plant cells to discern statistically significant changes in plant cell proteomes upon perturbation such as abscisic acid treatment in future studies. We anticipate that our study will contribute to advancing single-protoplast proteomics in the near future.

Freshwater crayfish are amongst the largest macroinvertebrates and play a keystone role in the ecosystems they occupy. Understanding the global distribution of these animals is often hindered due to a paucity of distributional data. Additionally, non-native crayfish introductions are becoming more frequent, which can cause severe environmental and economic impacts. Management decisions related to crayfish and their habitats require accurate, up-to-date distribution data and mapping tools. Such data are currently patchily distributed with limited accessibility and are rarely up-to-date. To address these challenges, we developed a versatile e-portal to host distributional data of freshwater crayfish and their pathogens (using Aphanomyces astaci, the causative agent of the crayfish plague, as the most prominent example). Populated with expert data and operating in near real-time, World of Crayfish™ is a living, publicly available database providing worldwide distributional data sourced by experts in the field. The database offers open access to the data through specialized standard geospatial services (Web Map Service, Web Feature Service) enabling users to view, embed, and download customizable outputs for various applications. The platform is designed to support technical enhancements in the future, with the potential to eventually incorporate various additional features. This tool serves as a step forward towards a modern era of conservation planning and management of freshwater biodiversity.

Summary: In vivo models of brain pathology are crucial for studying neurological diseases. Here, we present a protocol to induce a pathological condition in a mouse brain area by local injection of neurotoxic stimulus. We describe steps for preparing reagents, stereotaxic injection procedures to induce neurodegeneration in the hippocampus, and preparation of brain sections to examine the induced model. This protocol is useful for studying how local pathology affects other brain areas and neighbor cells and its functional consequences in behavior.For complete details on the use and execution of this protocol, please refer to Zhang et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Background/Purpose: In vat photopolymerization, post-polymerization of the three-dimensional (3D) printing resin is necessary to ensure the optimum physical properties of the printed objects. This study aimed to evaluate the potential use of a handheld polywave light-emitting diode (LED) dental light-curing unit (LCU) for post-polymerizing 3D printed resins by measuring the microhardness and biaxial flexural strength of the post-polymerized resin. Material and methods: 3D printed 1- and 2-mm-thick disks were irradiated with a dental LCU at 3200 mW/cm2. Post-polymerization was repeated either on one side from the top surface: two cycles (T2), four cycles (T4), and eight cycles (T8), or on both sides from the top and bottom surfaces: one cycle (T1B1), two cycles (T2B2), and four cycles (T4B4) for each side. The microhardness and biaxial strength of the disks were compared to those post-polymerized by a conventional desktop polymerizing unit (PC) and those without post-polymerization (NC). Results: Microhardness of the disks varied between the top and bottom surfaces of the 1-mm and 2-mm-thick disks, depending on the post-polymerization methods. T8 and T4B4 produced comparable microhardness on the top surface to PC for both thicknesses. In contrast, PC, T2B2, and T4B4 exhibited the highest microhardness on the bottom surface. Except for NC, the 1-mm-thick disks had a higher biaxial flexural strength than the 2-mm-thick disks. T4B4 resulted in the highest biaxial flexural strength for both thicknesses, which was comparable to that of the desktop polymerizing unit. Conclusion: The microhardness and biaxial flexural strengths of the post-polymerized 3D-printed disks increase with polymerization time. With sufficient polymerization from both sides, the polywave LCU has the potential to be a viable alternative to desktop polymerization units.

Abstract Cancer cells often exhibit resistance to apoptotic cell death, but they may be vulnerable to other types of cell death. Elucidating additional mechanisms that govern cancer cell death is crucial for developing new therapies. Our research identified cyclic AMP-responsive element-binding protein 3 (CREB3) as a crucial regulator and initiator of a unique cell death mechanism known as karyoptosis. This process is characterized by nuclear shrinkage, deformation, and the loss of nuclear components following nuclear membrane rupture. We found that the N-terminal domain (aa 1-230) of full-length CREB3 (CREB3-FL), which is anchored to the nuclear inner membrane (INM), interacts with lamins and chromatin DNA. This interaction maintains a balance between the outward force exerted by tightly packed DNA and the inward constraining force, thereby preserving INM integrity. Under endoplasmic reticulum (ER) stress, aberrant cleavage of CREB3-FL at the INM leads to abnormal accumulation of the cleaved form of CREB3 (CREB3-CF). This accumulation disrupts the attachment of CREB3-FL to the INM, resulting in sudden rupture of the nuclear membrane and the onset of karyoptosis. Proteomic studies revealed that CREB3-CF overexpression induces a DNA damage response akin to that caused by UVB irradiation, which is associated with cellular senescence in cancer cells. These findings demonstrated that the dysregulation of CREB3-FL cleavage is a key factor in karyoptotic cell death. Consequently, these findings suggest new therapeutic strategies in cancer treatment that exploit the process of karyoptosis.

Abstract Alcohol and cocaine (COC) are commonly co-used drugs that cause addiction and have harmful effects. Their abuse may threaten the health of the abuser and public safety by causing serious accidents or crimes. The recidivism rate of drug-related crimes closely correlates with alcoholism. Several incidences of alcohol consumption in combination with drug abuse have been reported. Here, liquid chromatography tandem mass spectrometric method was developed to simultaneously analyze ethyl glucuronide (EtG), a metabolite of ethanol; COC; cocaethylene (CE), an alcohol-derived metabolite of COC; and benzoylecgonine (BZE), a major metabolite of COC, to determine the concurrent use of alcohol with COC. For pre-treatment, ultracentrifugation (5 min, 50,000 g) and mixed-mode anion exchange solid-phase extraction were used to increase the recovery of target compounds and minimize the matrix effect of hair. The lower limits of quantification were: 7 pg/mg (EtG), 2 pg/mg (COC), 10 pg/mg (CE), and 1 pg/mg (BZE). The correlation coefficient (r) of the calibration curve within the quantified range of target compounds was ≥ 0.9978. The intra- and inter-day accuracies were − 6.1–9.7% and − 9.3–8.3%, and intra- and inter-day precisions were 0.5–10.3% and 0.6–14.4%, respectively. The recovery, matrix effect, process efficiency, and autosampler stability were 89.2–104.8%, 81.6–105.4%, 81.5–107.1%, and 96.6–109.7%, respectively. The novel analytical method was validated with hair samples from individuals suspected of alcohol and COC use, and the method could distinguish between independent and concurrent use. Based on the findings, the analytical approach developed in this study is anticipated to be valuable in drug and alcohol dependence tests that require the simultaneous detection of alcohol and COC abuse.

Abstract Solute carrier family (SLC) transporters are expressed in the digestive system and play important roles in maintaining physiological functions in the body. In addition, SLC transporters act as oncoproteins or tumor-suppressor proteins during the development, progression, and metastasis of various digestive system cancers. SLC22A18, a member of the SLC22 gene family, is an orphan transporter with an unknown endogenous substrate. Previous study revealed that SLC22A18 is downregulated in colorectal cancer tissues and that it acts as a suppressor in colorectal cancer, although the effects of SLC22A18 variants on colon cancer cell proliferation, migration, and invasion are unknown. Therefore, in this study, we identified SLC22A18 variants found in multiple populations by searching public databases and determined the in vitro effects of these missense variations on transporter expression and cancer progression. Our results indicated that three missense SLC22A18 variants—p.Ala6Thr, p.Arg12Gln, and p.Arg86His—had significantly lower cell expression than the wild type, possibly owing to intracellular degradation. Furthermore, these three variants caused significantly higher proliferation, migration, and invasion of colon cancer cells than the wild type. Our findings suggest that missense variants of SLC22A18 can potentially serve as biomarkers or prognostic tools that enable clinicians to predict colorectal cancer progression.

Multiple myeloma (MM) is an incurable hematologic cancer that originates from plasma cells and occurs primarily in patients over 60. The prognosis of MM has improved after the introduction of new treatments, such as thalidomide, bortezomib, and lenalidomide. However, in recurrent and refractory MM patients, factors such as age and drug toxicity are important when choosing treatment options. Because of this, the demand for novel, low-toxicity drugs is increasing. This study demonstrated that KBB-N1, an ultra-low molecular weight ginsenoside compound K, effectively treated MM by increasing the expression of phosphorylated p53. Given its minimal toxicity to hematopoietic stem cells and major organs, KBB-N1 is a promising new drug for treating MM in older patients.

Magnetic microrobots and nanoparticles offer unique capabilities for medical applications by granting unprecedented access to intricate and delicate anatomical structures. Nevertheless, an intuitive manipulation approach remains a challenge due to their small size and limited feedback. This study presents a new method for magnetic microrobot and nanoparticle control that employs virtual reality (VR), creating an immersive and realistic view of the bodily anatomy and the microrobot within. This study compares three manipulation modes: a traditional mode using 2D displays, VR mode using a VR headset and touch controllers, and VR autonomous programmed maneuvering. It is shown that VR‐assisted modes reduce the manipulation time by improving spatial awareness. Nanoparticles in a VR environment are also manipulated. The proposed method will find applications in terms of intuitive, immersive microrobots or magnetic nanoparticle control in complex biological environments, thus in many medical procedures and for drug and cell delivery. The immersive nature of this approach enhances the ability of the user to perceive and understand complex anatomical structures, facilitating better navigation within delicate environments; both dexterity and spatial awareness are improved. Thus, it is shown how microrobots and magnetic nanoparticles can be controlled using immersive simulations to improve both visualization and manipulation.

ABSTRACT Mitogen-activated protein kinase (MAPK) pathways are fundamental to the regulation of biological processes in eukaryotic organisms. The basidiomycete Cryptococcus neoformans, known for causing fungal meningitis worldwide, possesses five MAPKs. Among these, Cpk1, Hog1, and Mpk1 have established roles in sexual reproduction, stress responses, and cell wall integrity. However, the roles of Cpk2 and Mpk2 are less understood. Our study elucidates the functional interplay between the Cpk1/Cpk2 and Mpk1/Mpk2 MAPK pathways in C. neoformans. We discovered that CPK2 overexpression compensates for cpk1Δ mating deficiencies via the Mat2 transcription factor, revealing functional redundancy between Cpk1 and Cpk2. We also found that Mpk2 is phosphorylated in response to cell wall stress, a process regulated by the MAPK kinase (MAP2K) Mkk2 and MAP2K kinases (MAP3Ks) Ssk2 and Ste11. Overexpression of MPK2 partially restores cell wall integrity in mpk1Δ by influencing key cell wall components, such as chitin and the polysaccharide capsule. Contrarily, MPK2 overexpression cannot restore thermotolerance and cell membrane integrity in mpk1Δ. These results suggest that Mpk1 and Mpk2 have redundant and opposing roles in the cellular response to cell wall and membrane stresses. Most notably, the dual deletion of MPK1 and MPK2 restores wild-type mating efficiency in cpk1Δ mutants via upregulation of the mating-regulating transcription factors MAT2 and ZNF2, suggesting that the Mpk1 and Mpk2 cooperate to negatively regulate the pheromone-responsive Cpk1 MAPK pathway. Our research collectively underscores a sophisticated regulatory network of cryptococcal MAPK signaling pathways that intricately govern sexual reproduction and cell wall integrity, thereby controlling fungal development and pathogenicity.IMPORTANCEIn the realm of fungal biology, our study on Cryptococcus neoformans offers pivotal insights into the roles of specific proteins called mitogen-activated protein kinases (MAPKs). Here, we discovered the cryptic functions of Cpk2 and Mpk2, two MAPKs previously overshadowed by their dominant counterparts Cpk1 and Mpk1, respectively. Our findings reveal that these “underdog” proteins are not just backup players; they play crucial roles in vital processes like mating and cell wall maintenance in C. neoformans. Their ability to step in and compensate when their dominant counterparts are absent showcases the adaptability of C. neoformans. This newfound understanding not only enriches our knowledge of fungal MAPK mechanisms but also underscores the intricate balance and interplay of proteins in ensuring the organism’s survival and adaptability.

IntroductionPrevious research has highlighted the duality of self-consciousness, which simultaneously plays adaptive and maladaptive roles. This study aims to develop a measure that categorically distinguishes between different types of self-consciousness styles based on the Regulatory Focus Theory (RFT) and examines their relationship with mental health-related indicators.MethodsData were gathered through an online mental health survey conducted at a University Student Counseling Center in Seoul. The study involved exploratory factor analysis, confirmatory factor analysis, and reliability and validity analysis, which resulted in the development of a 14-question Self-Consciousness Type Scale (SCTS).ResultsBoth exploratory and confirmatory factor analyses validated the two-factor structure of the SCTS. The fit indices of the final model indicated a good fit, with high internal consistency for both sub-factors. Convergent and discriminant validity were confirmed through correlations between the sub-scales. Cluster analysis identified four distinct subtypes of self-consciousness styles: Growth-oriented, Defensive, Ambivalent, and Low-focus self-consciousness. Group difference analysis revealed significant differences in mental health-related variables among the subtypes, supporting the 2 × 2 model of prevention-focused and promotion-focused self-consciousness.DiscussionThe findings support the SCTS as a valid measurement tool capable of distinguishing four distinct types of self-consciousness, aligning with the multidimensional model of self-consciousness. The study’s limitations and implications were discussed based on the results, emphasizing the potential applications of the SCTS in mental health research and practice.

Abstract The fabrication of kesterite Cu2ZnSn(S,Se)4 (CZTSSe) thin‐film solar cells using the electrochemical deposition (ED), which is valued for its industrial feasibility, offers a cost‐effective and environmentally friendly approach to the carbon‐free and clean energy production. However, the reported power conversion efficiency of approximately 10 % for electrodeposited CZTSSe thin‐film solar cells is lower compared to the alternative methods like sputtering and spin‐coating, which is mainly attributed to the phase inhomogeneity and the rough morphology generated during the ED process. Ensuring the microscopic and macroscopic uniformity of the electrodeposited films is crucial for the improvement of the film quality and the device performances. In this review, strategies to address these challenges including the intrinsic film control such as the deposition mode, pH, concentration of metal ions, and complexing agents, as well as the extrinsic approaches such as doping, substitution of metal elements, and the introduction of interfacial layers. In addition, the prospects for the electrochemically deposited CZTSSe solar cells were presented, focusing on the promising applications in tandem, flexible, and solar water‐splitting devices. Finally, this review will provide technical insights into the ED process for preparing CZTSSe solar cells, outlining a perspective for the future development of highly efficient CZTSSe thin film solar cells.

Abstract Background Recent studies demonstrated that elevated osmolarity could induce adipocyte dedifferentiation, representing an appealing procedure to generate multipotent stem cells. Here we aim to elucidate the molecular mechanisms that underlie osmotic induction of adipocyte reprogramming. Methods To induce dedifferentiation, the 3T3-L1 or SVF adipocytes were cultured under the hypertonic pressure in 2% PEG 300 medium. Adipocyte dedifferentiation was monitored by aspect ratio measurement, Oil Red staining and qPCR to examine the morphology, lipid droplets, and specific genes of adipocytes, respectively. The osteogenic and chondrogenic re-differentiation capacities of dedifferentiated adipocytes were also examined. To investigate the mechanisms of the osmotic stress-induced dedifferentiation, extracellular vesicles (EVs) were collected from the reprograming cells, followed by proteomic and functional analyses. In addition, qPCR, ELISA, and TNF-α neutralizing antibody (20 ng/ml) was applied to examine the activation and effects of the TNF-α signaling. Furthermore, we also analyzed the Wnt signaling by assessing the activation of β-catenin and applying BML-284, an agonist of β-catenin. Results Hypertonic treatment induced dedifferentiation of both 3T3-L1 and the primary stromal vascular fraction (SVF) adipocytes, characterized by morphological and functional changes. Proteomic profiling revealed that hypertonicity induced extracellular vesicles (EVs) containing mitochondrial molecules including NDUFA9 and VDAC. Functionally, the mitochondrial EVs (MEVs) stimulated TNF-α signaling that activates Wnt-β-catenin signaling and adipocyte dedifferentiation. Neutralizing TNF-α inhibited hypertonic dedifferentiation of adipocytes. In addition, direct activation of Wnt-β-catenin signaling using BML-284 could efficiently induce adipocyte dedifferentiation while circumventing the apoptotic effect of the hypertonic treatment. Conclusions Hypertonicity prompts the adipocytes to release MEVs, which in turn enhances the secretion of TNF-α as a pro-inflammatory cytokine during the stress response. Importantly, TNF-α is essential for the activation of the Wnt/β-catenin signaling that drives adipocyte dedifferentiation. A caveat of the hypertonic treatment is apoptosis, which could be circumvented by direct activation of the Wnt/β-catenin signaling using BML-284.

Abstract Three-dimensional (3D) microprinting is considered a next-generation manufacturing process for the production of microscale components; however, the narrow range of suitable materials, which include mainly polymers, is a critical issue that limits the application of this process to functional inorganic materials. Herein, we develop a generalised microscale 3D printing method for the production of purely inorganic nanocrystal-based porous materials. Our process is designed to solidify all-inorganic nanocrystals via immediate dispersibility control and surface linking-induced interconnection in the nonsolvent linker bath and thereby creates multibranched gel networks. The process works with various inorganic materials, including metals, semiconductors, magnets, oxides, and multi-materials, not requiring organic binders or stereolithographic equipment. Filaments with a diameter of sub-10 μm are printed into designed complex 3D microarchitectures, which exhibit full nanocrystal functionality and high specific surface areas as well as hierarchical porous structures. This approach provides the platform technology for designing functional inorganics-based porous materials.

Imbalanced datasets are common in industrial internet of things (IIoT) systems due to challenges in acquiring faulty labels. Augmentation and graph-based methods have been proposed to improve classification accuracy of deep learning-based systems. However, the conventional approaches can be limited by training complexity and inefficient memory usage. In this paper, GraphSAGE with contrastive encoder (GCE) is proposed to improve classification accuracy and memory utilization efficiency. From the simulation results, it is confirmed that the GCE can improve classification accuracy by up to 23% compared to conventional approaches.

Abstract This study aimed to evaluate the efficacy of a novel jet dispenser (JD) for filling simulated straight and curved canals with calcium hydroxide (Ca(OH)2) paste by comparing the level of intracanal medicament with traditional direct syringe delivery. The Ca(OH)2 paste was delivered into the canals using either a direct syringe with binding tip and unbinding tip or a JD. The analysis of the ratio of the canal filled area (RCFA) in the coronal, middle, and apical thirds was conducted using the Kruskal–Wallis and Mann–Whitney U tests (α = 0.05). The JD resulted in a significantly higher RCFA of 1.00 in the middle and apical thirds in both the straight and curved canals than the direct syringe method (p

We report the annealing time-dependent microstructure–mechanical properties relationship of cold-rolled and annealed Fe–6Mn-0.05C–3Ni-1.5Al (wt.%) steel, containing Ni and Al to form NiAl B2 precipitates. The microstructures of the investigated materials after cold-rolling and intercritical annealing show a mixture of lath and equiaxed zones consisting of a triplex matrix phase (ferrite, austenite, and tempered martensite) with B2 precipitates. Recovery of the deformed martensite in the cold-rolled microstructure during annealing resulted in the formation of sub-boundaries and a continuous transition from partially-recrystallized tempered martensite to recrystallized ferrite. The investigated materials showed a decrease in strength and an increase in ductility and strain-hardening rate with increasing annealing time. A decrease in the fraction of tempered martensite, an increase in the fraction of recrystallized ferrite/austenite grains, and enhanced transformation-induced plasticity (TRIP) kinetics with increasing annealing time led to enhanced ductility and strain hardening of the materials. The mixed presence of less stable equiaxed austenite and more stable lath austenite resulted in sustained TRIP effect during tensile deformation and superior strain hardening capacity of the specimen annealed for 24 h. This study provides a novel microstructure design solution for medium Mn steels, and further optimization of the composition and processing will lead to the development of medium Mn steels with superior mechanical performance.

During road construction, the accuracy of compaction work is critical for the structural stability and maintenance of the road. Although the plate load test (PLT) is commonly used for quality inspections, it is impractical to test every section due to time and cost constraints. Therefore, simpler testing methods are being extensively developed. This study compared quality inspection results using the commonly used PLT, the relatively simple dynamic cone penetrometer test (DCPT), the lightweight deflectometer (LWD) test, and an intelligent quality control system equipped with accelerometer and global positioning system (GPS) sensors in intelligent compaction (IC) rollers. The results showed a strong correlation between the conventional tests (PLT, DCPT, and LWD) and the values obtained from the intelligent quality control system. The correlation analysis between the intelligent quality control system and PLT, LWDT, and DCPT yielded R-square values of 0.69, 0.91, and 0.95, respectively, indicating significantly high correlations. The implementation of intelligent quality management systems in earthwork construction projects will facilitate a thorough verification of the compaction quality throughout all construction segments, ensuring consistent compaction across the project. By enabling real-time data acquisition and analysis, these systems differ markedly from traditional methods, reducing the frequency and necessity of manual inspections. This approach not only streamlines construction processes, but also enhances operational efficiency. As a result, integrating these intelligent systems is anticipated to significantly increase productivity by optimizing the workflow and resource utilization in earthwork construction.

In many machine learning applications, there are many scenarios when performance is not satisfactory by single classifiers. In this case, an ensemble classification is constructed using several weak base learners to achieve satisfactory performance. Unluckily, the construction of the ensemble classification is empirical, i.e., to try an ensemble classification and if performance is not satisfactory then discard it. In this paper, a challenging analytical problem of the estimation of ensemble classification using the prediction performance of the base learners is considered. The proposed formulation is aimed at estimating the performance of ensemble classification without physically developing it, and it is derived from the perspective of probability theory by manipulating the decision probabilities of the base learners. For this purpose, the output of a base learner (which is either true positive, true negative, false positive, or false negative) is considered as a random variable. Then, the effects of logical disjunction-based and majority voting-based decision combination strategies are analyzed from the perspective of conditional joint probability. To evaluate the forecasted performance of ensemble classifier by the proposed methodology, publicly available standard datasets have been employed. The results show the effectiveness of the derived formulations to estimate the performance of ensemble classification. In addition to this, the theoretical and experimental results show that the logical disjunction-based decision outperforms majority voting in imbalanced datasets and cost-sensitive scenarios.

Abstract Hygroscopic and acidic nature of organic hole transport layers (HTLs) insisted to replace it with metal oxide semiconductors due to their favorable charge carrier transport with long chemical stability. Apart from large direct bandgap and high optical transmittance, ionization energy in the range of −5.0 to −5.4 eV leads to use NiO as HTL due to good energetic matching with lead halide perovskites. Analyzing X‐ray photoelectron spectroscopic (XPS) data of NiO, it is speculated that p‐type conductivity is related to the NiOOH or Ni2O3 states in the structure and the electrical conductivity can be modified by altering the concentration of nickel or oxygen vacancies. However, it is difficult to separate the contribution from nonlocal screening, surface effect and the presence of vacancy induced Ni3+ ion due to very strong satellite structure in the Ni 2p XPS spectrum of NiO. Thus, an effective approach to analyze the NiO XPS spectrum is presented and the way to correlate the presence of Ni3+ with the conductivity results which will help to avoid overestimation in finding the oxygen‐rich/deficient conditions in NiO.

Summary: Circadian clocks, generating daily rhythms in biological processes, maintain homeostasis in physiology, so clock alterations are considered detrimental. Studies in brain pathology support this by reporting abnormal circadian phenotypes in patients, but restoring the abnormalities by light therapy shows no dramatic effects. Recent studies on glial clocks report the complex effects of altered clocks by showing their beneficial effects on brain repairs. However, how neuronal clocks respond to brain pathology is elusive. This study shows that neuronal BMAL1, a core of circadian clocks, reduces its expression levels in neurodegenerative excitotoxicity. In the dentate gyrus of excitotoxic hippocampal lesions, reduced BMAL1 in granule cells precedes apoptosis. This subsequently reduces BMAL1 levels in neighbor neural stem cells and progenitors in the subgranular zone, enhancing proliferation. This shows the various BMAL1 roles depending on cell types, and its alterations can benefit brain repair. Thus, cell-type-specific BMAL1 targeting is necessary to treat brain pathology.

Abstract In this study, the concentration of urinary creatinine (Cr) and urine color were analyzed, and a correlation obtained, to objectively verify normal urine samples prior to forensic drug testing. Cr was analyzed via a colorimetric method based on the Jaffé reaction using a Cobas C-311 analyzer (Roche SA, Basel, Switzerland; Hitachi, Tokyo, Japan). The Cr concentration for urine specimen validity testing was measured to screen urine samples submitted after dilution or upon the addition of a foreign substance that interferes with drug testing. Urine samples containing

Abstract Suppressing the oxidation of active-Ir(III) in IrOx catalysts is highly desirable to realize an efficient and durable oxygen evolution reaction in water electrolysis. Although charge replenishment from supports can be effective in preventing the oxidation of IrOx catalysts, most supports have inherently limited charge transfer capability. Here, we demonstrate that an excess electron reservoir, which is a charged oxygen species, incorporated in antimony-doped tin oxide supports can effectively control the Ir oxidation states by boosting the charge donations to IrOx catalysts. Both computational and experimental analyses reveal that the promoted charge transfer driven by excess electron reservoir is the key parameter for stabilizing the active-Ir(III) in IrOx catalysts. When used in a polymer electrolyte membrane water electrolyzer, Ir catalyst on excess electron reservoir incorporated support exhibited 75 times higher mass activity than commercial nanoparticle-based catalysts and outstanding long-term stability for 250 h with a marginal degradation under a water-splitting current of 1 A cm−2. Moreover, Ir-specific power (74.8 kW g−1) indicates its remarkable potential for realizing gigawatt-scale H2 production for the first time.

Abstract Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with impaired social behavior and communication, repetitive behaviors, and restricted interests. In addition to genetic factors, environmental factors such as prenatal drug exposure contribute to the development of ASD. However, how those prenatal factors induce behavioral deficits in the adult stage is not clear. To elucidate ASD pathogenesis at the molecular level, we performed a high-resolution mass spectrometry-based quantitative proteomic analysis on the prefrontal cortex (PFC) of mice exposed to valproic acid (VPA) in utero, a widely used animal model of ASD. Differentially expressed proteins (DEPs) in VPA-exposed mice showed significant overlap with ASD risk genes, including differentially expressed genes from the postmortem cortex of ASD patients. Functional annotations of the DEPs revealed significant enrichment in the Wnt/β-catenin signaling pathway, which is dysregulated by the upregulation of Rnf146 in VPA-exposed mice. Consistently, overexpressing Rnf146 in the PFC impaired social behaviors and altered the Wnt signaling pathway in adult mice. Furthermore, Rnf146-overexpressing PFC neurons showed increased excitatory synaptic transmission, which may underlie impaired social behavior. These results demonstrate that Rnf146 is critical for social behavior and that dysregulation of Rnf146 underlies social deficits in VPA-exposed mice.

The development of low-cost and low-power gas sensors for reliable NO2 gas detection is important due to the highly toxic nature of NO2 gas. Herein, initially, SnO2 nanowires (NWs) were synthesized through a simple vapor–liquid–solid growth mechanism. Subsequently, different amounts of SnO2 NWs were composited with MoS2 nanosheets (NSs) to fabricate SnO2 NWs/MoS2 NS nanocomposite gas sensors for NO2 gas sensing. The operation of the sensors in self-heating mode at 1–3.5 V showed that the sensor with 20 wt.% SnO2 (SM-20 nanocomposite) had the highest response of 13 to 1000 ppb NO2 under 3.2 V applied voltage. Furthermore, the SM-20 nanocomposite gas sensor exhibited high selectivity and excellent long-term stability. The enhanced NO2 gas response was ascribed to the formation of n-n heterojunctions between SnO2 NWs and MoS2, high surface area, and the presence of some voids in the SM-20 composite gas sensor due to having different morphologies of SnO2 NWs and MoS2 NSs. It is believed that the present strategy combining MoS2 and SnO2 with different morphologies and different sensing properties is a good approach to realize high-performance NO2 gas sensors with merits such as simple synthesis and fabrication procedures, low cost, and low power consumption, which are currently in demand in the gas sensor market.

Hydrogen (H2) gas, with its high calorimetric combustion energy and cleanness, is a green source of energy and an alternative to fossil fuels. However, it has a small kinetic diameter, with high diffusivity and a highly explosive nature. Hence, the reliable detection of H2 gas is essential in various fields such as fuel cells. Herein, we decorated ZnO nanoparticles (NPs) with Pd noble metal NPs, using UV irradiation to enhance their H2 gas-sensing performance. The synthesized materials were fully characterized in terms of their phases, morphologies, and chemical composition. Then, the sensing layer was deposited on the electrode-patterned glass substrate to make a transparent sensor. The fabricated transparent gas sensor was able to detect H2 gas at various temperatures and humidity levels. At 250 °C, the sensor exhibited the highest response to H2 gas. As a novelty of the present study, we successfully detected H2 gas in mixtures of H2/benzene and H2/toluene gases. The enhanced H2 gas response was related to the catalytic effect of Pd, the formation of heterojunctions between Pd and ZnO, the partial reduction of ZnO to Zn in the presence of H2 gas, and the formation of PdHx. With a high performance in a high response, good selectivity, and repeatability, we believe that the sensor developed in this study can be a good candidate for practical applications where the detection of H2 is necessary.

Tomatoes contain many secondary metabolites such as β-carotene, lycopene, phenols, flavonoids, and vitamin C, which are responsible for antioxidant activity. SlSGR1 encodes a STAY-GREEN protein that plays a critical role in the regulation of chlorophyll degradation in tomato leaves and fruits. Therefore, the present study was conducted to evaluate the sgr1 null lines based on their physicochemical characteristics, the content of secondary metabolites, and the γ-Aminobutyric acid (GABA) content. The total soluble solids (TSS), titrated acidity (TA), and brix acid ratio (BAR) of the sgr1 null lines were higher than those of the wild type(WT). Additionally, the sgr1 null lines accumulated higher levels of flavor-inducing ascorbic acid and total carotenoids compared to WT. Also, the total phenolic content, total flavonoids, GABA content, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical content of the sgr1 null lines were higher than those of the WT. Therefore, these studies suggest that the knockout of the SGR1 gene by the CRISPR/Cas9 system can improve various functional compounds in tomato fruit, thereby satisfying the antioxidant properties required by consumers.

Abstract Autism spectrum disorders (ASD) represent neurodevelopmental disorders characterized by social deficits, repetitive behaviors, and various comorbidities, including epilepsy. ANK2, which encodes a neuronal scaffolding protein, is frequently mutated in ASD, but its in vivo functions and disease-related mechanisms are largely unknown. Here, we report that mice with Ank2 knockout restricted to cortical and hippocampal excitatory neurons (Ank2-cKO mice) show ASD-related behavioral abnormalities and juvenile seizure-related death. Ank2-cKO cortical neurons show abnormally increased excitability and firing rate. These changes accompanied decreases in the total level and function of the Kv7.2/KCNQ2 and Kv7.3/KCNQ3 potassium channels and the density of these channels in the enlengthened axon initial segment. Importantly, the Kv7 agonist, retigabine, rescued neuronal excitability, juvenile seizure-related death, and hyperactivity in Ank2-cKO mice. These results suggest that Ank2 regulates neuronal excitability by regulating the length of and Kv7 density in the AIS and that Kv7 channelopathy is involved in Ank2-related brain dysfunctions.

Abstract With photovoltaic performance of metal halide perovskite-based solar cells skyrocketing to approximately 26% and approaching the theoretical Shockley–Queisser limit of single junction solar cells, researchers are now exploring multi-junction tandem solar cells that use perovskite materials to achieve high efficiency next-generation photovoltaics. Various types of bottom subcells, including silicon solar cells used commercially in industry, chalcogenide thin film cells, and perovskite cells, have been combined with perovskite top subcells on the strength of facile fabrication methods based on solution processes. However, owing to the nature that photovoltages of the subcells are added up and the structure containing numerous layers, interfacial issues that cause open-circuit voltage (V OC) deficit need to be handled carefully. In addition, morphological issues or process compatibility make it difficult to fabricate solution-processed perovskite top cells. In this paper, we summarize and review the fundamentals and strategies to overcome interfacial issues in tandem solar cells for high efficiency and stability confronting this field. Graphical Abstract

BackgroundRobust and accurate prediction of severity for patients with COVID-19 is crucial for patient triaging decisions. Many proposed models were prone to either high bias risk or low-to-moderate discrimination. Some also suffered from a lack of clinical interpretability and were developed based on early pandemic period data. Hence, there has been a compelling need for advancements in prediction models for better clinical applicability. ObjectiveThe primary objective of this study was to develop and validate a machine learning–based Robust and Interpretable Early Triaging Support (RIETS) system that predicts severity progression (involving any of the following events: intensive care unit admission, in-hospital death, mechanical ventilation required, or extracorporeal membrane oxygenation required) within 15 days upon hospitalization based on routinely available clinical and laboratory biomarkers. MethodsWe included data from 5945 hospitalized patients with COVID-19 from 19 hospitals in South Korea collected between January 2020 and August 2022. For model development and external validation, the whole data set was partitioned into 2 independent cohorts by stratified random cluster sampling according to hospital type (general and tertiary care) and geographical location (metropolitan and nonmetropolitan). Machine learning models were trained and internally validated through a cross-validation technique on the development cohort. They were externally validated using a bootstrapped sampling technique on the external validation cohort. The best-performing model was selected primarily based on the area under the receiver operating characteristic curve (AUROC), and its robustness was evaluated using bias risk assessment. For model interpretability, we used Shapley and patient clustering methods. ResultsOur final model, RIETS, was developed based on a deep neural network of 11 clinical and laboratory biomarkers that are readily available within the first day of hospitalization. The features predictive of severity included lactate dehydrogenase, age, absolute lymphocyte count, dyspnea, respiratory rate, diabetes mellitus, c-reactive protein, absolute neutrophil count, platelet count, white blood cell count, and saturation of peripheral oxygen. RIETS demonstrated excellent discrimination (AUROC=0.937; 95% CI 0.935-0.938) with high calibration (integrated calibration index=0.041), satisfied all the criteria of low bias risk in a risk assessment tool, and provided detailed interpretations of model parameters and patient clusters. In addition, RIETS showed potential for transportability across variant periods with its sustainable prediction on Omicron cases (AUROC=0.903, 95% CI 0.897-0.910). ConclusionsRIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.

Persistent damage to liver cells leads to liver fibrosis, which is characterized by the accumulation of scar tissue in the liver, ultimately leading to cirrhosis and serious complications. Because it is difficult to reverse cirrhosis once it has progressed, the primary focus has been on preventing the progression of liver fibrosis. However, studies on therapeutic agents for liver fibrosis are still lacking. Here, we investigated that the natural dipeptide cyclic histidine-proline (CHP, also known as diketopiperazine) shows promising potential as a therapeutic agent in models of liver injury by inhibiting the progression of fibrosis through activation of the Nrf2 pathway. To elucidate the underlying biological mechanism of CHP, we used the Cellular Thermal Shift Assay (CETSA)-LC–MS/MS, a label-free compound-based target identification platform. Chloride intracellular channel protein 1 (CLIC1) was identified as a target whose thermal stability is increased by CHP treatment. We analyzed the direct interaction of CHP with CLIC1 which revealed a potential interaction between CHP and the E228 residue of CLIC1. Biological validation experiments showed that knockdown of CLIC1 mimicked the antioxidant effect of CHP. Further investigation using a mouse model of CCl4-induced liver fibrosis in wild-type and CLIC1 KO mice revealed the critical involvement of CLIC1 in mediating the effects of CHP. Taken together, our results provide evidence that CHP exerts its anti-fibrotic effects through specific binding to CLIC1. These insights into the mechanism of action of CHP may pave the way for the development of novel therapeutic strategies for fibrosis-related diseases.

Abstract All‐inorganic perovskite solar cells have shown great potential owing to their superior stability against thermal stress and moisture compared to organic–inorganic perovskite solar cells. However, there are some remaining issues in the all‐inorganic perovskite solar cell fabrication process, such as the low solubility of the perovskite precursors and the occurrence of the secondary phases. In this review, we focus on all‐inorganic CsPbBr3 perovskite solar cells and categorize them based on their fabrication process. Various processes and strategies that have been developed to solve the aforementioned issues including the general process of multistep spin coating are thoroughly investigated. Finally, a summary of the various processes for the all‐inorganic CsPbBr3 perovskite solar cells and an outlook for the development of highly efficient all‐inorganic perovskite solar cells are proposed.