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Background: Extracellular vesicles (EVs), which are nanometer-sized vesicles enclosed by lipid membranes, are secreted by most cells and contain lipids, proteins, and various nucleic acid species from the source cell. Due to their natural origin, high biocompatibility, stability, targeting ability, multifunctionality, and low immunogenicity, EVs have been increasingly explored as potential drug delivery system (DDS) agents, offering new strategies for the treatment of cardiovascular disease, neurodegenerative disease, cancer and many other diseases. However, there are several challenges facing EVs as drug delivery systems, such as the low drug loading efficiency and the need for consensus on ideal cell types as sources for EVs at the clinical level. Area Covered: This article briefly reviews the physiological characteristics of EVs and discusses the applicable conditions for endogenous and exogenous drug loading in EVs, as well as the delivery modes of EVs as carriers. Finally, the challenges of EVs stability and drug encapsulation efficiency of EVs as future DDS are also described. Expert Opinion: This article mainly focused on the different methods of endogenous and exogenous drug loading, described the delivery modes of EVs as carriers in drug delivery, and the challenges of stability and drug encapsulation efficiency facing in the future in detail and deeply.

Novel performance improvement technology is developed for an ultrathin Double Silicon-on-Insulator (DSOI) Lateral Double-diffused Metal–Oxide–Semiconductor (LDMOS) with a heavy doping drift region, which is simulated using TCAD and an advanced application module for circuit analysis (CA-AAM). A peripheral circuit was proposed to dynamically control the independent back-gate electrode of the DSOI, with a zero bias for the ON-state and a negative bias for the OFF-state. A heavily doped drift region was designed to maintain a low specific on-resistance (Ron,sp), where a negative back-gate bias would induce positive charges to compensate for the heavily doped ionized acceptors. This results in an improved breakdown voltage (BV). Therefore, it rebuilds the traditional reduced surface field (RESURF) condition. Results indicate that the developed technology exhibits optimization in terms of the BV, Ron,sp, OFF-state leakage current, ON-state current, peak transconductance, cut-off frequency, turn-off time, Baliga’s figure of merits (BFOM), and figure of merits (FOM) when compared with the conventional RESURF technology.

In this article, we establish a method to detect and formulate price bubbles in the cryptocurrency markets. This method identifies abnormal crashes through violations of the exponential decaying property. Confirmations of bubble bursts within these anomalies are obtained through wavelet analysis. By decomposing the cryptocurrency price into the high-frequency and low-frequency factors, we distinguish the price regimes versus the periods with bubbles and crashes in both time and frequency domains. In addition, we apply the log-periodic power law model to fit the bubble formation. In the analysis of eight cryptocurrencies—Bitcoin, Ethereum, Litecoin, Antshares, Ethereum Classic, Dash, Monero, and OmiseGO—from 15 May 2018 to 28 November 2022, we identify 24 bubbles. Some of them exhibit a significant and strong exponential growth pattern.

Beta-lactoglobulin (β-Lg), a prominent milk protein, is a major contributor to milk allergies. The quantitative assessment of β-Lg is a valuable method for assessing the allergenic potential of dairy products. In this study, a specific aptamer, β-Lg-01, with an affinity constant (KD) of 28.6 nM for β-Lg was screened through seven rounds of magnetic bead SELEX (MB-SELEX). A novel bio-layer interferometry (BLI)-based aptasensor was developed, which had a limit of detection (LOD) of 0.3 ng mL−1, a linear range of 1.5 ng mL−1–15 μg mL−1, and a recovery rate of 102–116% among the milk samples. This aptasensor provides a potential tool for the detection and risk assessment of β-Lg within 10 min.

Inspired by the two-path visual information processing mechanism (i.e., a bottom-up path and a top-down path), we propose a bidirectional binocular feature aggregation based stereo image quality assessment (SIQA) network, which considers a two-path visual mechanism and realizes the binocular fusion based on parallax information. To better aggregate binocular features from different levels, a two-path feature aggregation structure, which simulates the bottom-up and top-down mechanism in human visual system (HVS), is proposed. It not only realizes the supplement of low-level detail information to high-level semantic in the bottom-up path, but also realizes the supplement of high-level semantic information to low-level detail in the top-down path. Simultaneously, because feature misalignment exists in binocular features of adjacent levels, a feature alignment module (FAM) based on deformable convolution is designed to integrate the binocular fusion features of adjacent levels. In addition, considering the importance role of parallax in guiding binocular fusion, a binocular fusion module (BFM) based on parallax attention mechanism, which is different with existing binocular fusion methods, is explicitly proposed to achieve the binocular fusion between the left and right view features. Extensive experiments are conducted on LIVE I, LIVE II, WIVC I and WIVC II databases to demonstrate the effectiveness of the proposed method.

Quasi-two-dimensional (Q-2D) Ruddlesden-Popper perovskites have excellent optical performance due to self-assembling multiple quantum well structure. However, Q-2D perovskites usually contain a disordered phase distribution, which results in low emission efficiency. In this work, we introduced the 2-aminohexane ligand into the Q-2D perovskite films, reconstructed the phase distribution of the films. In addition, the defects were passivated after introducing the ligand, resulting in low trap density, so as to obtain high-quality Q-2D perovskite films. With this approach, the Q-2D perovskite light-emitting diodes (PeLEDs) achieved a maximum brightness of 187,869 cd m−2 and a peak external quantum efficiency of 21.6%.

In recent years, stereo image super-resolution based on convolutional neural network has been extensively researched and achieved impressive performance by introducing complementary information from another view. However, most existing methods still cannot fully capture both intra- and cross-view information due to the neglect of multi-scale information perception, multi-scale binocular alignment and the excitation of large scale to small scale in human vision system. And they generated blurry results due to the consideration of irrelevant information in search for cross-view information. To address these issues, we propose a multi-scale visual perception based progressive feature interaction network (MS-PFINet) for stereo image super-resolution. Specifically, to exploit comprehensive intra- and cross-view information for image reconstruction, we design a two-stream network with multi-branch structure to extract multi-scale features and progressively use cross-view interaction at larger scales to guide that at smaller scales. Moreover, to explore more proper and accurate cross-view information, we propose a feature transformer module (FTM) to search and transfer the most relevant features from another view by hard attention maps and soft attention maps, which are calculated by patch-wise similarity rather than pixel-wise. In addition, in order to encourage a more effective way to transfer texture features for the target view, we propose a perceptual texture matching loss to supervise the accuracy of feature transformer modules. Experimental results show that our proposed method is superior to the state-of-the-art methods in most cases.

Quasi-2D perovskites, multiquantum well materials with the energy cascade structure, exhibit impressive optoelectronic properties and a wide range of applications in various optoelectronic devices. However, the insufficient exciton energy transfer caused by the excess of small-nphases that induce nonradiative recombination and the spatially random phase distribution that impedes charge transport severely inhibit the device performance of light-emitting diodes (LEDs). Here, a faster energy transfer process and efficient carrier recombination are achieved by introducing the multifunctional additive 2-(methylsulfonyl)-4-(trifluoromethyl)benzoic acid (MTA) to manipulate the crystallization process of perovskites. The introduction of MTA not only constrains the PEA and restrains the formation of small-nphases to improve the energy transfer process but also optimizes the crystal orientation to promote charge transport. As a result, highly efficient pure green quasi-2D perovskite LEDs with a peak EQE of 25.9%, a peak current efficiency of 108.1 cd A–1, and a maximum luminance of 288798 cd m–2are achieved.

Objective: To evaluate whether the revised US Preventive Services Task Force (USPSTF) criteria reduced inequities in lung cancer screening (LCS) eligibility among a racially diverse sample of patients with lung cancer. Methods: This is a retrospective analysis of adults diagnosed with primary lung malignancies at an urban safety net hospital. For all patients and exclusively ever-smokers, χ2tests were used to evaluate differences in LCS eligibility among socio-demographic variables using the 2013 and 2021 USPSTF criteria. Patients who were ineligible for LCS were categorized by reason for exclusion. Results: Among 678 lung cancer patients (46% female, mean age 66 ± 10 years), 51% were White, and 39% were Black. Using the 2013 guidelines, White patients (57%) would have been more likely to be eligible than Black (37%) and other-race patients (35%) (P< 0.0001) at time of cancer diagnosis. Under the 2021 guidelines, White patients (68%) remained more likely to be eligible for LCS than Black (54%) and other-race patients (48%) (P= 0.0002). Among exclusively ever-smoking patients, we did not observe a significant difference in eligibility by race under the 2021 USPSTF guidelines (White [73%], Black [65%], and other-race [65%]; [P= 0.48]). Sex, ethnicity, education level, and insurance type were not associated with differential screening eligibility under either the 2013 or 2021 guidelines. Conclusion: The revised 2021 USPSTF LCS guidelines may not be sufficient to eliminate racial inequities in LCS eligibility among patients who go on to be diagnosed with primary lung cancer. Differential rates of lung cancer among never-smokers may contribute to this inequity.

Osteoarthritis (OA) is the most common disabling joint disease with no effective disease modifying drugs. Extracellular vesicles released by several types of mesenchymal stem cells could promote cartilage repair and ameliorate OA pathology in animal models, representing a novel therapeutic strategy. In this study, we demonstrated that extracellular vesicles derived from human umbilical cord mesenchymal stem cells (hUC-EVs) could maintain chondrocyte homeostasis and alleviate OA, and further revealed a novel molecular mechanism of this therapeutic effect. miR-223, which could directly bind with the 3′UTR of NLRP3 mRNA, was found to be a key miRNA for hUC-EVs to exert beneficial effects on inflammation inhibiting and cartilage protecting. For enhancing the effect on mitigating osteoarthritis, exogenous miR-223 was loaded into hUC-EVs by electroporation, and a collagen II-targeting peptide (WYRGRL) was modified onto the surface of hUC-EVs by genetic engineering to achieve a more targeted and efficient RNA delivery to the cartilage. The dual-engineered EVs showed a maximal effect on inhibiting the NLRP3 inflammasome activation and chondrocyte pyroptosis, and offered excellent results for the treatment of OA. This study provides a novel theoretical basis and a promising therapeutic strategy for the application of engineered extracellular vesicles in OA treatment.

Assays for carbendazim (Car) with high sensitivity and on-site screening have been urgently required to protect the ecosystem and prevent disease. In this work, a simple, sensitive, and reliable sensing system based on photoinduced electron transfer was established to detect carbendazim utilizing ultrathin graphitic carbon nitride (g-C3N4) nanosheets and rhodamine B (RB). Carbendazim reacts with g-C3N4by electrostatic interactions to form π–π stacking, and the quenching of the blue fluorescence is caused by electron transfer. While RB works as a reference fluorescence sensor without any fluorescence change, leading to obvious ratiometric fluorescence variation from blue to purple. Under optimal conditions, a favorable linear range from 20 to 180 nM was obtained, with a low detection limit of 5.89 nM. In addition, a portable smartphone sensing platform was successfully used for carbendazim detection in real samples with excellent anti-interference capability, demonstrating the potential applications of carbendazim monitoring.

By integrating a microcavity Kerr frequency comb with an interferometric arm structure for backward coupling with a slot sensing waveguide, we present a new on-chip multi-gas sensing device. The microcavity used for frequency comb generation has a novel symmetric double-ring structure with a large roundtrip length, which makes it possible to obtain high-resolution frequency-resolved absorption spectra. In the meanwhile, a flat octave-spanning broadband spectrum is obtained by dispersion engineering of the Si3N4-based micro-rings with a horizontal single slot structure. Without the use of an additional gas cell, the large-length sensing waveguide allows for improved integration. A multiple soliton comb with high pump-to-frequency comb conversion efficiency under the optimization of the microcavity structure to improve pump depletion was obtained. The simulation shows its high stability and application feasibility, and the sensing performance of several gas species in different wavelength regions is verified and analyzed.

Extracellular vesicles (EVs) derived from living cells play important roles in donor cell-induced recipient tissue regeneration. Although numerous studies have found that cells undergo apoptosis after implantation in an ischemic-hypoxic environment, the roles played by the EVs released by apoptotic cells are largely unknown. In this study, we obtained apoptotic vesicles (apoVs) derived from human deciduous pulp stem cells and explored their effects on the dental pulp regeneration process. Our work showed that apoVs were ingested by endothelial cells (ECs) and elevated the expression of angiogenesis-related genes, leading to pulp revascularization and tissue regeneration. Furthermore, we found that, at the molecular level, apoV-carried mitochondrial Tu translation elongation factor was transported and regulated the angiogenic activation of ECs via the transcription factor EB-autophagy pathway. In a beagle model of dental pulp regeneration in situ, apoVs recruited endogenous ECs and facilitated the formation of dental-pulp-like tissue rich in blood vessels. These findings revealed the significance of apoptosis in tissue regeneration and demonstrated the potential of using apoVs to promote angiogenesis in clinical applications.

Optical camera communication (OCC), as a complementary technology of radio frequency (RF), has played an important role in alleviating the burden on the existing spectrum and enhancing the reliability of communication. Theoretical investigations which describe the unique characteristics of camera-based optical wireless communication systems on a complete system model are limited, as most existing research utilized the indicators that are applied in photo detector (PD)-based systems. Due to the fact that cameras use pixel values to record the intensity of the LED, which carries the signals information, analysis based on pixel values has the ability to intuitively reflect OCC systems features. Motivated by this, a comprehensive system model which considers the photoelectric conversion and the imaging process of the camera is presented to characterize OCC systems in this paper. The proposed model which has been validated on the hardware platform describes the relationship between the LED driving current and the final pixel values on the image sensor. Some system parameters’ impact has been analyzed based on the proposed system model and corresponding experimental results. Performance analysis has been provided to characterize OCC systems from the communication perspective. Our investigation may help introduce a new perspective to understand the principle of OCC, as well as providing the theoretical support needed for the design in practical systems.

Corneal neovascularization (CNV) is a common disease that affects the vision ability of more than 1 million people annually. Small interfering RNA (siRNA) delivery nanoparticle platforms are a promising therapeutic modality for CNV treatment. However, the efficient delivery of siRNA into cells and the effective release of siRNA from delivery vehicles in a particular cell type challenge effective RNAi clinical application for CNV suppression. This study reports the design of a novel reactive oxygen species (ROS)-responsive lipid nanoparticle for siRNA delivery into corneal lesions for enhanced RNAi as a potential CNV treatment. We demonstrated that lipid nanoparticles could efficiently deliver siRNA into human umbilical vein endothelial cells and release siRNA for enhanced gene silencing by using the upregulated ROS of CNV to promote lipid nanoparticle degradation. Moreover, the subconjunctival injection of siRNA nanocomplexes into corneal lesions effectively knocked down vascular endothelial growth factor expression and suppressed CNV formation in an alkali burn model. Thus, we believe that the strategy of using ROS-responsive lipid nanoparticles for enhanced RNAi in CNV could be further extended to a promising clinical therapeutic approach to attenuate CNV formation.

Objective: Cleft lip and/or palate is a common birth defect worldwide, always accompanied by alveolar cleft. However, the success rate of secondary alveolar bone grafting is unsatisfactory. Rapid maxillary expansion (RME) often used after bone transplantation provides functional stimulation for bone graft area. This study aimed to investigate the effect of RME force on the bone graft area and midpalatal suture, and screen out the most suitable loaded force and loaded teeth, so as to provide a reference for clinical treatment.Methods: Fourteen 24-week-old male beagles were assigned randomly to 3 groups: blank control, autogenous, and autogenous with RME. Three-dimensional finite element analysis was conducted to evaluate the distribution and value of the stress in the model. The maxillae were collected and subjected to radiography and helical computed tomography to evaluate new bone formation in the graft area. Van Gieson’s Picrofuchsin staining was performed for histomorphological observation.Results: After 8 weeks of RME treatment, new bone formation of the dogs was markedly accelerated, and bone resorption was significantly reduced compared with the untreated dogs or those only treated with autogenous iliac bone. The treatment with RME evidently made the bone trabecula more abundant and the area of bone formation larger. Three-dimensional finite element analysis showed that the clinical effect can be achieved by using canine teeth as the loaded teeth and applying force of 10 MPa.Conclusion: Rapid maxillary expansion after bone grafting had a positive effect on osteogenesis in a canine model of alveolar cleft.

Renal interstitial fibrosis (RIF) is an incurable pathological lesion in chronic kidney diseases. Pericyte activation is the major pathological characteristic of RIF. Fibroblast and macrophage activation are also involved in RIF. Studies have revealed that core fucosylation (CF), an important post-translational modification of proteins, plays a key role in pericyte activation and RIF by regulating multiple profibrotic signaling pathways as a hub-like target. Here, we reveal that mesenchymal stem cell (MSC)-derived exosomes reside specifically in the injured kidney and deliver microRNA (miR)-34c-5p to reduce cellular activation and RIF by inhibiting CF. Furthermore, we showed that the CD81-epidermal growth factor receptor (EGFR) ligand-receptor complex aids the entry of exosomal miR-34c-5p into pericytes, fibroblasts, and macrophages. Altogether, our findings reveal a novel role of MSC-derived exosomes in inhibiting multicellular activation via CF and provide a potential intervention strategy for renal fibrosis.

To evaluate long-term anatomical and functional outcomes of the MICOF keratoprosthesis to treat end-stage corneal blindness.

Marine gas hydrate is a potential alternative energy. As the 173rd new mineral species, it can be qualitatively divided into diagenetic and non-diagenetic types. Because of its few drilling and production cases, high sampling cost, and great difficulty in heat preservation and pressure preservation technology, the in situtest of reservoir physical properties and the quantitative classification and evaluation of resource grade are not clear, and the relationship between resource-grade division and development-mode response is not clear. Therefore, in this paper, to solve this problem and technical difficulties, in combination with the actual hydrate sampling core data in the South China Sea, using the indoor hydrate acoustoelectric testing device, the physical parameters, such as acoustic wave, resistivity, saturation, permeability, partial stress and strain of hydrate deposits with different composition and saturation, were measured. An entropy weight comprehensive evaluation model for the sensitivity of physical parameters of natural gas hydrate is established on the basis of the decomposed hierarchy process. The order of sensitivity of hydrate parameters from high to low is stress, partial stress, decomposed gas, longitudinal wave, resistivity, permeability, and shear wave. In this paper, the evaluation method of physical parameters of marine natural gas hydrate and the five-grade classification standard of natural gas hydrate are established according to the law of parameter variation and the results of sensitivity analysis. Finally, the Liwan hydrate reservoir in the northern South China Sea is taken as a case study and defined as non-diagenetic grade II, which belongs to argillaceous shallow sedimentary hydrate with high saturation and high methane content without complete trap structure. This study provides an important technical method and theoretical guidance for the evaluation and classification of marine gas hydrate resources and the optimization of corresponding suitable development methods in the future.

Air quality data prediction in urban area is of great significance to control air pollution and protect the public health. The prediction of the air quality in the monitoring station is well studied in existing researches. However, air-quality-monitor stations are insufficient in most cities and the air quality varies from one place to another dramatically due to complex factors. A novel model is established in this paper to estimate and predict the Air Quality Index (AQI) of the areas without monitoring stations in Nanjing. The proposed model predicts AQI in a non-monitoring area both in temporal dimension and in spatial dimension respectively. The temporal dimension model is presented at first based on the enhanced k-Nearest Neighbor (KNN) algorithm to predict the AQI values among monitoring stations, the acceptability of the results achieves 92% for one-hour prediction. Meanwhile, in order to forecast the evolution of air quality in the spatial dimension, the method is utilized with the help of Back Propagation neural network (BP), which considers geographical distance. Furthermore, to improve the accuracy and adaptability of the spatial model, the similarity of topological structure is introduced. Especially, the temporal-spatial model is built and its adaptability is tested on a specific non-monitoring site, Jiulonghu Campus of Southeast University. The result demonstrates that the acceptability achieves 73.8% on average. The current paper provides strong evidence suggesting that the proposed non-parametric and data-driven approach for air quality forecasting provides promising results.

Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in ‘systems genetics and genomics’. In this Review, we highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis. Furthermore, we summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis. The integration of multiple technologies will provide a road map to illuminate the complex pathogenesis of osteoporosis, especially from molecular functional aspects, in vivo in humans.

In China, marine natural gas hydrate (NGH) resources are mainly distributed in the deepwater areas of 300–3000 m deep in the coastal continental shelf, and they are characterized by weak cementation and non-diagenesis. In order to test and study this type of NGH, it is necessary to prepare samples quickly in situ in large quantities. At present, the commonly used preparation technologies (e.g. stirring method, spraying method and bubbling method) are defective with slow generation and low gas storage density. In view of this, the 1062 L rapid non-diagenetic NGH preparation kettle was designed and developed independently. Then, based on the physical properties of non-diagenetic NGH in the South China Sea, NGH preparation tests were carried out on stirring method, spraying method, bubbling method and “three-in-one” method (the combination of stirring method, spraying method and bubbling method). Temperature, pressure, resistivity and reaction time in the process of test were tested, and NGH generation situations and preparation efficiency of different preparation processes were analyzed and compared. And the following research results were obtained. First, in the process of NGH preparation by stirring method, spraying method and bubbling method, respectively, the generated NGH increases slowly and spreads the whole liquid level gradually. Second, inducing period is obvious in the preparation process by the stirring method, but not obvious by the spraying method, the bubbling method and the “three-in-one” method. Third, in the process of NGH preparation by stirring method, spraying method, bubbling method and “three-in-one” method, the resistivity increases as the reaction goes, and its change trend is basically accordant with the NGH preparation rate. Fourth, the preparation cycle of NGH by “three-in-one” method is greatly shorter than that by single preparation method. The preparation time by stirring method, spraying method and bubbling method is about 5.14 times, 3.59 times and 3.16 times that of “three-in-one” method respectively. In conclusion, the 1062 L rapid NGH preparation kettle developed in this paper can prepare marine non-diagenetic NGH samples quickly in situ. And compared with single preparation method, “three-in-one” method is much higher in NGH preparation efficiency.

Surface modification has been widely applied to improve bioactivity of biomedical implants. A micro-nanostructured bioactive surface was successfully fabricated on titanium. Firstly, Ti6Al4V sheets with micro structure were prepared by Selective Laser Melting (SLM) and acid etching. Then TiO2nanotubes were constructed on titanium surfaces via anodic oxidation. The wettability and bioactivity were respectively investigated by measurement of surface contact angle and simulated body fluid soaking test. Results showed that after anodic oxidation the surface turned to super-hydrophilic with the water contact angle of nearly 0° and more hydroxyapatite deposition formed on the surface, which indicated bioactivity improvement.

The solar-driven interfacial evaporation (SDIE) technology serves as a clean and facile approach combining seawater desalination to address water shortage and energy crisis. Recently, porous organic framework materials have aroused great attention, and the development of MOF-based composites with significant performance in photothermal conversion and water activation has become one of the important focuses in this field. In this work, an MOF-based composite photothermal membrane (PON@MOF) was prepared via the in situ growth of metal–organic framework (MOF) nanoneedle arrays induced by a pyridine-based organic polymer nanowire network (PON). The PON@MOF membrane possessed an MOF array layer, a PON-induced layer, and a porous support layer. The PON is rich in coordinated nitrogen atoms for anchoring the metal-ion source, and the main role of the PON layer is to provide favorable nucleation sites and orient in situ growth of well-aligned MOF nanoneedle arrays. With the highly conjugated framework of PON@MOF and the light trapping of the nanoarrays strengthening the photothermal conversion as well as the hydrophilic chemical structure facilitating the decrease of the water evaporation enthalpy, the PON@MOF membrane realizes highly efficient thermal vapor conversion. Under solar irradiation (1.0 kW m–2), PON@MOF demonstrated an evaporation rate of 2.14 kg m–2h–1and a solar-to-vapor conversion efficiency of 98.5%. Meanwhile, the PON@MOF membrane has excellent salt resistance and stability, highlighting its potential application in desalination. Overall, this work provides a special idea for the structural design of photothermal composites for solar desalination and freshwater production.

Organophosphate pesticides (OPs) are widely utilized in agricultural production, and the residues threaten public health and environmental safety due to their toxicity. Herein, a novel and simple DNA aptamer-based sensor has been fabricated for the rapid, visual, and quantitative detection of profenofos and isocarbophos. The proposed DNA aptamers with a G-quadruplex spatial structure could be recognized by SYBR Green I (SG-I), resulting in strong green fluorescence emitted by SG-I. The DNA aptamers exhibit a higher specific binding ability to target OP molecules through aromatic ring stacking, disrupting the interaction between SG-I and DNA aptamers to induce green fluorescence quenching. Meanwhile, the fluorescence wavelength of G-quadruplex fluorescence emission peaks changes, accompanied by an obvious fluorescence variation from green to blue. SG-I-modified aptasensor without any additive reference fluorescence units for use in multicolor fluorescence assay for selective monitoring of OPs was first developed. The developed aptasensor provides a favorable linear range from 0 to 200 nM, with a low detection limit of 2.48 and 3.01 nM for profenofos and isocarbophos, respectively. Moreover, it offers high selectivity and stability in real sample detection with high recoveries. Then, a self-designed portable smartphone sensing platform was successfully used for quantitative result outputs, demonstrating experience in designing a neotype sensing strategy for point-of-care pesticide monitoring.

Exploring a novel natural cryoprotectant and understanding its antifreeze mechanism allows the rational design of future sustainable antifreeze analogues. In this study, various antifreeze polysaccharides were isolated from wheat bran, and the antifreeze activity was comparatively studied in relation to the molecular structure. The antifreeze mechanism was further revealed based on the interactions of polysaccharides and water molecules through dynamic simulation analysis. The antifreeze polysaccharides showed distinct ice recrystallization inhibition activity, and structural analysis suggested that the polysaccharides were arabinoxylan, featuring a xylan backbone with a majority of Arafand minor fractions of Manp, Galp, and Glcpinvolved in the side chain. The antifreeze arabinoxylan, characterized by lower molecular weight, less branching, and more flexible conformation, could weaken the hydrogen bonding of the surrounding water molecules more evidently, thus retarding the transformation of water molecules into the ordered ice structure.

Most packages for the analysis of fMRI-based functional connectivity (FC) and genomic data are used with a programming language interface, lacking an easy-to-navigate GUI frontend. This exacerbates two problems found in these types of data: demographic confounds and quality control in the face of high dimensionality of features. The reason is that it is too slow and cumbersome to use a programming interface to create all the necessary visualizations required to identify all correlations, confounding effects, or quality control problems in a dataset. FC in particular usually contains tens of thousands of features per subject, and can only be summarized and efficiently explored using visualizations. To remedy this situation, we have developed ImageNomer, a data visualization and analysis tool that allows inspection of both subject-level and cohort-level demographic, genomic, and imaging features. The software is Python-based, runs in a self-contained Docker image, and contains a browser-based GUI frontend. We demonstrate the usefulness of ImageNomer by identifying an unexpected race confound when predicting achievement scores in the Philadelphia Neurodevelopmental Cohort (PNC) dataset, which contains multitask fMRI and single nucleotide polymorphism (SNP) data of healthy adolescents. In the past, many studies have attempted to use FC to identify achievement-related features in fMRI. Using ImageNomer to visualize trends in achievement scores between races, we find a clear potential for confounding effects if race can be predicted using FC. Using correlation analysis in the ImageNomer software, we show that FCs correlated with Wide Range Achievement Test (WRAT) score are in fact more highly correlated with race. Investigating further, we find that whereas both FC and SNP (genomic) features can account for 10–15% of WRAT score variation, this predictive ability disappears when controlling for race. We also use ImageNomer to investigate race-FC correlation in the Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP) dataset. In this work, we demonstrate the advantage of our ImageNomer GUI tool in data exploration and confound detection. Additionally, this work identifies race as a strong confound in FC data and casts doubt on the possibility of finding unbiased achievement-related features in fMRI and SNP data of healthy adolescents.

We performed molecular simulations to investigate the adsorption and diffusion of benzene in metal–organic framework Mg-MOF-74. At 300 K and 20 Pa, the saturated loading of benzene reaches 8.2 mmol/g, almost twice of (12,12) single-walled carbon nanotube with a similar pore size, and 93% of the benzene molecules in Mg-MOF-74 can desorb at 390 K. The energy analysis indicates that the van der Waals contribution still dominates 70–80% of the total fluid–wall interaction energy compared with the Coulombic contribution. We further analyzed the structure of benzene confined in Mg-MOF-74 by the molecular snapshots, pair correlation functions, orientational order parameters, and local density profiles. It is found that low temperature and high pressure make the structure of adsorbed benzene more similar to that of the liquid benzene. Moreover, the benzene molecules in the contact adsorption layer lie flat on the surface of adsorbent, whereas those molecules near the pore center have no particular orientations. Due to the existence of open metal sites, the structures of adsorbed benzene are more compact and ordered than those of bulk liquid benzene. Consequently, the self-diffusion coefficient of saturated benzene in Mg-MOF-74 at 300 K is significantly lower than that of bulk liquid benzene and confined liquid benzene in slit pores and disordered carbons by 4–5 orders of magnitude. We investigated the separation and diffusion of benzene/cyclohexane in the mixture in Mg-MOF-74 and found that the pores almost completely adsorbed benzene, although its self-diffusion coefficient was slightly lower than that of cyclohexane.