Bandgap Engineering of 2D Materials toward High-Performing Straintronics.

Straintronics leverages mechanical strain to alter the electronic properties of materials, providing an energy-efficient alternative to traditional electronic controls while enhancing device performance. Key to the application of straintronics is bandgap engineering, which enables tuning of the energy difference between the valence and conduction bands of a material to optimize its optoelectronic properties. This mini-review highlights the fundamental principles of straintronics and the critical role of bandgap engineering within this context. It discusses the unique characteristics of various two-dimensional (2D) materials, such as graphene, transition metal dichalcogenides (TMDs), hexagonal boron nitride (h-BN), and black phosphorus, which make them suitable for strain-engineered applications. Detailed examples of how mechanical deformation can modulate the bandgap to achieve desired electronic properties are provided, while recent experimental and theoretical studies demonstrating the mechanisms by which strain influences the bandgap in these materials are reviewed, emphasizing their implications for device fabrication. The review concludes with an assessment of the challenges and future directions in the development of high-performing straintronic devices, highlighting their potential applications in flexible electronics, sensors, and optoelectronics.

Allele-specific alternative splicing and its functional genetic variants in human tissues.

Alternative splicing is an RNA processing mechanism that affects most genes in human, contributing to disease mechanisms and phenotypic diversity. The regulation of splicing involves an intricate network of cis-regulatory elements and trans-acting factors. Due to their high sequence specificity, cis-regulation of splicing can be altered by genetic variants, significantly affecting splicing outcomes. Recently, multiple methods have been applied to understanding the regulatory effects of genetic variants on splicing. However, it is still challenging to go beyond apparent association to pinpoint functional variants. To fill in this gap, we utilized large-scale data sets of the Genotype-Tissue Expression (GTEx) project to study genetically modulated alternative splicing (GMAS) via identification of allele-specific splicing events. We demonstrate that GMAS events are shared across tissues and individuals more often than expected by chance, consistent with their genetically driven nature. Moreover, although the allelic bias of GMAS exons varies across samples, the degree of variation is similar across tissues versus individuals. Thus, genetic background drives the GMAS pattern to a similar degree as tissue-specific splicing mechanisms. Leveraging the genetically driven nature of GMAS, we developed a new method to predict functional splicing-altering variants, built upon a genotype-phenotype concordance model across samples. Complemented by experimental validations, this method predicted >1000 functional variants, many of which may alter RNA-protein interactions. Lastly, 72% of GMAS-associated SNPs were in linkage disequilibrium with GWAS-reported SNPs, and such association was enriched in tissues of relevance for specific traits/diseases. Our study enables a comprehensive view of genetically driven splicing variations in human tissues.

Studies of Anticancer Activities In Vitro and In Vivo for Butyltin(IV)-Iridium(III) Imidazole-Phenanthroline Complexes with Aggregation-Induced Emission Properties.

Organotin(IV) and iridium(III) complexes have shown good application potential in the field of anticancer; however, the aggregation-caused quenching (ACQ) effect induced by high concentration or dose has limited the research on their targeting and anticancer mechanism. Then, a series of aggregation-induced emission (AIE)-activated butyltin(IV)-iridium(III) imidazole-phenanthroline complexes were prepared in this study. Complexes exhibited significant fluorescence improvement in the aggregated state because of the restricted intramolecular rotation (RIR), accompanied by an absolute fluorescence quantum yield of up to 29.2% (IrSn9). Complexes demonstrated potential in vitro antiproliferative and antimigration activity against A549 cells, following a lysosomal-mitochondrial apoptotic pathway. Nude mouse models further confirmed that complexes had favorable in vivo antitumor and antimigration activity in comparison to cisplatin. Therefore, butyltin(IV)-iridium(III) imidazole-phenanthroline complexes possess the potential as potential substitutes for platinum-based drugs.

Automatic generation method for long-focal-length unobscured freeform optical systems with small volume.

The existing design methods for long-focal-length unobscured freeform systems rarely consider the imaging quality requirements and volume constraints simultaneously, causing most of the final designs to not fulfill the requirement of light weight. This study proposes a method to automatically design a long-focal-length unobscured reflective system that satisfies volume constraints while maintaining high imaging quality. First, a method to adaptively set the structural parameter range is proposed, and multiple parameters for different systemic specifications can be effectively calculated within it. Subsequently, the systemic volume and area functions are constructed using the ray tracing method, where the tilt angles, distances between mirrors, and radii of curvature of the mirrors are chosen as the optimization parameters. Third, a comprehensive objective function is jointly established combining ray obscuration and convergence as performance evaluation factors. Then, the structural parameters of a long-focal-length unobscured system with small volume are easily obtained via the simulated annealing method. Finally, the improved W-W method is used to further enhance the imaging quality of the system, and an unobscured freeform reflective optical system with three mirrors is automatically generated. Experimental results demonstrate that our method can automatically calculate the parameter ranges to facilitate the search for structural parameters, and effectively design the long-focal-length unobscured freeform systems with small volume and high imaging quality.

Detection methods for antibiotics in wastewater: a review.

Antibiotics are widely used as fungicides because of their antibacterial and bactericidal effects. However, it is necessary to control their dosage. If the amount of antbiotics is too much, it cannot be completely metabolized and absorbed, will pollute the environment, and have a great impact on human health. Many antibiotics usually left in factory or aquaculture wastewater pollute the environment, so it is vital to detect the content of antibiotics in wastewater. This article summarizes several common methods of antibiotic detection and pretreatment steps. The detection methods of antibiotics in wastewater mainly include immunoassay, instrumental analysis method, and sensor. Studies have shown that immunoassay can detect deficient concentrations of antibiotics, but it is affected by external factors leading to errors. The detection speed of the instrumental analysis method is fast, but the repeatability is poor, the price is high, and the operation is complicated. The sensor is a method that is currently increasingly studied, including electrochemical sensors, optical sensors, biosensors, photoelectrochemical sensors, and surface plasmon resonance sensors. It has the advantages of fast detection speed, high accuracy, and strong sensitivity. However, the reproducibility and stability of the sensor are poor. At present, there is no method that can comprehensively integrate the advantages. This paper aims to review the enrichment and detection methods of antibiotics in wastewater from 2020 to the present. It also aims to provide some ideas for future research directions in this field.

Identification and Compensation Method of Unbalanced Error in Driving Chain for Rate-Integrating Hemispherical Resonator Gyro.

The accuracy of the signal within a driving chain for the rate-integrating hemispherical resonator gyro (RI-HRG) plays a crucial role in the overall performance of the gyro. In this paper, a notable and effective method is proposed to realize the identification and compensation of the unbalanced error in the driving chain for the RI-HRG that improved the performance of the multi-loop control applied in the RI-HRG. Firstly, the assembly inclination and eccentricity error of the hemispherical resonator, the inconsistent metal conductive film layer resistance error of the resonator, the coupling error of the driving chain, and the parameter inconsistency error of the circuit components were considered, and the impact of these errors on the multi-loop control applied in the RI-HRG were analyzed. On this basis, the impact was further summarized as the unbalanced error in the driving chain, which included the unbalanced gain error, equivalent misalignment angle, and unbalanced equivalent misalignment angle error. Then, a model between the unbalanced error in the driving chain and a non-ideal precession angular rate was established, which was applicable to both single channel asynchronous control and dual channel synchronous control of the RI-HRG. Further, an unbalanced error identification and compensation method is proposed by utilizing the RI-HRG output with the virtual precession control. Finally, the effectiveness of the proposed method was verified through simulation and experiments in kind. After error compensation, the zero-bias instability of the RI-HRG was improved from 3.0950°/h to 0.0511°/h. The results of experiments in kind demonstrated that the proposed method can effectively suppress the non-ideal angular rate output caused by the unbalanced error in the driving chain for the RI-HRG, thereby further improving the overall performance of the RI-HRG.

Lightweight Substation Equipment Defect Detection Algorithm for Small Targets.

Substation equipment defect detection has always played an important role in equipment operation and maintenance. However, the task scenarios of substation equipment defect detection are complex and different. Recent studies have revealed issues such as a significant missed detection rate for small-sized targets and diminished detection precision. At the same time, the current mainstream detection algorithms are highly complex, which is not conducive to deployment on resource-constrained devices. In view of the above problems, a small target and lightweight substation main scene equipment defect detection algorithm is proposed: Efficient Attentional Lightweight-YOLO (EAL-YOLO), which detection accuracy exceeds the current mainstream model, and the number of parameters and floating point operations (FLOPs) are also advantageous. Firstly, the EfficientFormerV2 is used to optimize the model backbone, and the Large Separable Kernel Attention (LSKA) mechanism has been incorporated into the Spatial Pyramid Pooling Fast (SPPF) to enhance the model's feature extraction capabilities; secondly, a small target neck network Attentional scale Sequence Fusion P2-Neck (ASF2-Neck) is proposed to enhance the model's ability to detect small target defects; finally, in order to facilitate deployment on resource-constrained devices, a lightweight shared convolution detection head module Lightweight Shared Convolutional Head (LSCHead) is proposed. Experiments show that compared with YOLOv8n, EAL-YOLO has improved its accuracy by 2.93 percentage points, and the mAP50 of 12 types of typical equipment defects has reached 92.26%. Concurrently, the quantity of FLOPs and parameters has diminished by 46.5% and 61.17% respectively, in comparison with YOLOv8s, meeting the needs of substation defect detection.

MicroRNA expression as a prognostic biomarker of tongue squamous cell carcinoma (TSCC): a systematic review and meta-analysis.

BACKGROUND: Recent studies have indicated that microRNA (miRNA) expression in tumour tissues has prognostic significance in Tongue squamous cell carcinoma (TSCC) patients. This study explored the possible prognostic value of miRNAs for TSCC based on published research. METHODS: A comprehensive literature search of multiple databases was conducted according to predefined eligibility criteria. Data were extracted from the included studies by two researchers, and HR results were determined based on Kaplan‒Meier curves according to the Tierney method. The Newcastle‒Ottawa Scale (NOS) and GRADE (Grading of Recommendations Assessment, Development, and Evaluation) pro-GDT were applied to assess the quality of all studies. Publication bias was estimated by funnel plot, Egger's rank correlation test and sensitivity analysis. RESULTS: Eleven studies (891patients) were included, of which 6 reported up-regulated miRNAs and 7 mentioned down-regulated miRNAs. The pooled hazard ratio (HR) from the prognostic indicator overall survival (OS) was 1.34 (1.25-1.44), p < 0.00001, indicating a significant difference in miRNA expression between TSCC patients with better or worse prognosis. CONCLUSION: MiRNAs may have high prognostic value and could be used as prognostic biomarkers of TSCC.

Near-infrared speckle wavemeter based on nonlinear frequency conversion.

The wavemeter is an important instrument for spectrum analysis, widely used in spectral calibration, remote sensing, atomic physics, and high-precision metrology. However, near-infrared (NIR) wavemeters require infrared-sensitive detectors that are expensive and less sensitive compared to silicon-based visible light detectors. To circumvent these limitations, we propose an NIR speckle wavemeter based on nonlinear frequency conversion. We combine a scattering medium and the deep learning technique to invert the nonlinear mapping of the NIR wavelength and speckles in the visible wave band. With the outstanding performance of deep learning, a high-precision wavelength resolution of 1 pm is achievable in our experiment. We further demonstrate the robustness of our system and show that the recognition of power parameters and multi-spectral lines is also feasible. The proposed method offers a convenient and flexible way to measure NIR light, and it offers the possibility of cost reduction in miniaturized wavemeter systems.

Dietary nutrition regulates intestinal stem cell homeostasis.

Intestinal stem cells (ISCs), which locate at the base of intestinal crypts, are key determinants of governing proliferation and differentiation of the intestinal epithelium. The surrounding cells of ISCs and their related growth factors form ISC niche, supporting ISC function and self-renewal. ISC has an underappreciated but emerging role as a sensor of dietary nutrients, which fate decisions is adjusted in response to nutritional states to regulate gut homeostasis. Here, we review endogenous and exogenous factors, such as caloric restriction, fasting, fat, glucose and trace element. They instruct ISCs via mTORC1, PPAR/CPT1α, PPARγ/ß-catenin, Wnt/GSK-3ß pathway, respectively, jointly affect intestinal homeostasis. These dietary responses regulate ISC regenerative capacity and may be a potential target for cancer prevention. However, without precise definitions of nutrition intervene, it will be difficult to generate sufficient data to extending our knowledge of the biological response of ISC on nutrients. More accurately modeling organoids or high-throughput automated organoid culture in microcavity arrays have provided unprecedented opportunities for modeling diet-host interactions. These major advances collectively provide new insights into nutritional regulation of ISC proliferation and differentiation and drive us ever closer to breakthroughs for regenerative medicine and disease treatment by nutrition intervention in the clinic.

Study of Nanoparticle-Polymer Interactions via the Mechanical Stretching of Surface-Enhanced Raman Scattering Substrates.

It is shown that the aligned electrospun fibers are a convenient platform for studying the mechanical effects on nanomaterials, particularly when using surface-enhanced Raman scattering as a sensitive tool of monitoring. The ligands on the surface of the embedded Au nanoparticles fall off easily with the shear force from the stretching, in contrast to the counterparts protected by polymer/silica shells. Upon stretching, the chains of Au nanoparticles will reversibly break, as revealed by the dramatic changes in the longitudinal plasmon absorption. It is believed that such a platform will open a window for understanding mechanical effects at the nanoscale, and also a new means for synthetic control.

Neural responses to social decision-making in suicide attempters with mental disorders.

BACKGROUND: Decision-making deficits have been reported in suicide attempters and may be a neuropsychological trait of vulnerability to suicidal behavior. However, little is known about how neural activity is altered in decision-making. This study aimed to investigate the neural responses in suicide attempters with mental disorders during social decision-making. Electroencephalography (EEG) were recorded from 52 patients with mental disorders with past suicide attempts (SAs = 26) and without past suicide attempts (NSAs = 26), as well as from 22 age- and sex- matched healthy controls (HCs) during the Ultimatum Game (UG), which is a typical paradigm to investigate the responses to fair and unfair decision-making. METHODS: MINI 5.0 interview and self report questionnaire were used to make mental diagnosis and suicide behavior assessment for individuals. Event-related potential (ERP) and phase-amplitude coupling (PAC) were extracted to quantify the neural activity. Furthermore, Spearman correlation and logistic regression analyses were conducted to identify the risk factors of suicidal behavior. RESULTS: ERP analysis demonstrated that SA patients had decreased P2 amplitude and prolonged P2 latency when receiving unfair offers. Moreover, SA patients exhibited greater negative-going feedback-related negativity (FRN) to unfair offers compared to fair ones, whereas such a phenomenon was absent in NSA and HC groups. These results revealed that SA patients had a stronger fairness principle and a disregard toward the cost of punishment in social decision-making. Furthermore, theta-gamma and beta-gamma PAC were involved in decision-making, with compromised neural coordination in the frontal, central, and temporal regions in SA patients, suggesting cognitive dysfunction during social interaction. Statistically significant variables were used in logistic regression analysis. The area under receiver operating characteristic curve in the logistic regression model was 0.91 for SA/HC and 0.84 for SA/NSA. CONCLUSIONS: Our findings emphasize that suicide attempts in patients with mental disorders are associated with abnormal decision-making. P2, theta-gamma PAC, and beta-gamma PAC may be neuro-electrophysiological biomarkers associated with decision-making. These results provide neurophysiological signatures of suicidal behavior.

Off-axis three-mirror freeform systems design based on improved W-W differential equations.

Design of an off-axis system using the Wassermann-Wolf (W-W) differential equations can effectively eliminate the spherical aberration and coma problem; however, it is complicated and time consuming to calculate the discrete point coordinates on the freeform mirror surfaces due to multiple numbers of reference system transformation in the design process. This paper presents an improved W-W-differential-equations-based design method for off-axis three-mirror freeform systems. First, to reduce the number of coordinate transformations, a geometric relationship between different optical rays in an off-axis system is established using the distance between the central points of adjacent mirrors. Second, a three-dimensional rotation matrix is used to associate the optical paths passing through adjacent mirrors in different reference coordinate systems, and new simplified W-W differential equations based on the ray vectors are constructed. The experimental results show that our method can easily and effectively design off-axis three-mirror freeform systems with different parameters and structures, and the designed systems have good imaging quality.

Pan-cancer analysis identifies mutations in SUGP1 that recapitulate mutant SF3B1 splicing dysregulation.

The gene encoding the core spliceosomal protein SF3B1 is the most frequently mutated gene encoding a splicing factor in a variety of hematologic malignancies and solid tumors. SF3B1 mutations induce use of cryptic 3' splice sites (3'ss), and these splicing errors contribute to tumorigenesis. However, it is unclear how widespread this type of cryptic 3'ss usage is in cancers and what is the full spectrum of genetic mutations that cause such missplicing. To address this issue, we performed an unbiased pan-cancer analysis to identify genetic alterations that lead to the same aberrant splicing as observed with SF3B1 mutations. This analysis identified multiple mutations in another spliceosomal gene, SUGP1, that correlated with significant usage of cryptic 3'ss known to be utilized in mutant SF3B1 expressing cells. Remarkably, this is consistent with recent biochemical studies that identified a defective interaction between mutant SF3B1 and SUGP1 as the molecular defect responsible for cryptic 3'ss usage. Experimental validation revealed that five different SUGP1 mutations completely or partially recapitulated the 3'ss defects. Our analysis suggests that SUGP1 mutations in cancers can induce missplicing identical or similar to that observed in mutant SF3B1 cancers.

Two New Compounds Isolated from the Leaves of Ohwia caudata and Their Neuroprotective Effect against LPS-Induced BV2 Cells.

From the dried leaves of Ohwia caudata, two new compounds, namely (4E)-(4-hydroxyphenyl)-3-butenoic acid butyl ester (1), and 4-benzyl-1,3-phenylenedicarbamic acid methyl ester (2), together with five known compounds, were isolated and identified. The structures of compounds 1 and 2 were established using 1D-NMR, 2D-NMR and HR-ESI-MS spectral analysis. Previous studies on O. caudata had been reported to protect against Alzheimer's disease, two new compounds were evaluated for their neuroprotective effect against lipopolysaccharide-induced BV2 microglia cells. The result indicated two compounds showed well anti-neuroinflammatory activity at 12.5 µM.

Bmp5 Mutation Alters mRNA Expression During External Ear Development.

To understand changes in gene regulation and mRNA expression in external ear development, we used a bone morphogenetic protein 5 (BMP5) short-ear mouse model. External ear tissues at E15.5 and E17.5 were collected, and mRNA expression profiles were analyzed. Upregulated and downregulated mRNA expression was identified using find_circ and CIRI2 software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using the differentially expressed mRNAs. Alterations in related signal pathways were identified from the upregulated and downregulated mRNA transcripts. The results showed a correlation between the mRNA expression during external ear development in BMP5 short-ear mice, including key regulatory mRNA changes after point mutations of the Bmp5 gene. This study provides evidence for the mechanism underlying mRNA regulation during external ear development. Changes in mRNA expression profiles also provide clues for future studies regarding the regulatory mechanisms underlying external ear development.

Topology Optimization of Turbulent Flow Cooling Structures Based on the k-ε Model.

Topology optimization (TO) is an effective approach to designing novel and efficient heat transfer devices. However, the TO of conjugate heat transfer has been essentially limited to laminar flow conditions only. The present study proposes a framework for TO involving turbulent conjugate heat transfer based on the variable density method. Different from the commonly used and oversimplified Darcy model, this approach is based on the more accurate and widely accepted k-ε model to optimize turbulent flow channels. We add penalty terms to the Navier-Stokes equation, turbulent kinetic energy equation, and turbulent energy dissipation equation, and use interpolation models for the thermal properties of materials. A multi-objective optimization function, aiming to minimize the pressure drop and the average temperature, is set up to balance the thermal and hydraulic performance. A case study is conducted to compare various optimization methods in the turbulent regime, and the results show that the present method has substantially higher optimization effectiveness while remaining computationally inexpensive.

Anti-noise computational imaging using unsupervised deep learning.

Computational imaging enables spatial information retrieval of objects with the use of single-pixel detectors. By combining measurements and computational methods, it is possible to reconstruct images in a variety of situations that are challenging or impossible with traditional multi-pixel cameras. However, these systems typically suffer from significant loss of imaging quality due to various noises when the measurement conditions are single-photon detecting, undersampling and complicated. Here, we provide an unsupervised deep learning (UnDL) based anti-noise approach to deal with this problem. The proposed method does not require any clean experimental data to pre-train, so it effectively alleviates the difficulty of model training (especially for the biomedical imaging scene which is difficult to obtain training ground truth inherently). Our results show that an UnDL based imaging approach outperforms conventional single-pixel computational imaging methods considerably in reconstructing the target image against noise. Moreover, the well-trained model is generalized to image a real biological sample and can accurately image 64 × 64 resolution objects with a high speed of 20 fps at 5% sampling ratio. This method can be used in various solvers for general computational imaging and is expected to effectively suppress noises for high-quality biomedical imaging in generalizable complicated environments.

Geometrically incompatible confinement of solids.

The complex morphologies exhibited by spatially confined thin objects have long challenged human efforts to understand and manipulate them, from the representation of patterns in draped fabric in Renaissance art to current-day efforts to engineer flexible sensors that conform to the human body. We introduce a theoretical principle, broadly generalizing Euler's elastica-a core concept of continuum mechanics that invokes the energetic preference of bending over straining a thin solid object and that has been widely applied to classical and modern studies of beams and rods. We define a class of geometrically incompatible confinement problems, whereby the topography imposed on a thin solid body is incompatible with its intrinsic ("target") metric and, as a consequence of Gauss' Theorema Egregium, induces strain. By focusing on a prototypical example of a sheet attached to a spherical substrate, numerical simulations and analytical study demonstrate that the mechanics is governed by a principle, which we call the "Gauss-Euler elastica" This emergent rule states that-despite the unavoidable strain in such an incompatible confinement-the ratio between the energies stored in straining and bending the solid may be arbitrarily small. The Gauss-Euler elastica underlies a theoretical framework that greatly simplifies the daunting task of solving the highly nonlinear equations that describe thin solids at mechanical equilibrium. This development thus opens possibilities for attacking a broad class of phenomena governed by the coupling of geometry and mechanics.

Interference and frequency-to-time mapping based high anti-jamming and anti-interception frequency hopping receiving.

We have proposed an interference and frequency-to-time mapping based high anti-jamming and anti-interception frequency hopping receiving scheme. By changing the delay difference between the interference arms through high-speed switchable delay lines and using electrooptical sampling, fast and large-range frequency hopping signals can be received. Benefited from the high shaping resolution for using the interference as the spectral shaping method, more receiving passbands in high frequency bands can be available to enhance the anti-jamming and anti-interception performance. By fast pulse shaping through switchable delay lines, the bandwidth of the electric end, the sampling rate, and the number of frequencies in the frequency hopping pattern are decoupled, and the bandwidth of the electric end can be reduced to improve the receiving selectivity. In experiments, the signal hopping from 15.2 GHz to 35.4 GHz with the switching time up to that of the used optical switch is received. Utilizing a switchable delay line in the interference arm with the tuning step of 2.5 ps, eight available receiving passbands within 25 GHz to 42 GHz are generated. The receiving selectivity is also improved from 18.3 to 43.7 in terms of Q factor by decreasing the electric end's bandwidth in experiments.