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Summary: Endoscopic thyroidectomy (ET), a surgical procedure widely accepted by surgeons, has been proven to be feasible. The aim of this systematic review is to evaluate the effectiveness and safety of ET compared to conventional open thyroidectomy (COT) in the treatment of papillary thyroid microcarcinoma (PTMC) through a meta-analysis. Medical literature databases, including PubMed, Embase, Cochrane Library, CBM,CNKI, Wanfang, and VIP, were systematically searched for relevant studies on ET and COT for the treatment of PTMC. The search period was from January 2000 to June 2023. Two researchers independently performed literature screening and data extraction according to the inclusion and exclusion criteria, and the Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included studies. Meta-analysis was conducted using Revman 5.3 software. Six studies were eventually included, involving a total of 440 patients with PTMC. The meta-analysis results demonstrated that the ET group had shorter incision length (MD = −2.96, 95 % CI: −4.27 to −1.65, P 0.05), lymph node dissection (MD = 1.03, 95 % CI: −1.47 to 3.54, P = 0.42 > 0.05), postoperative hospital stay (MD = −0.96, 95 % CI: −2.00 to 0.08, P = 0.07 > 0.05), and transient recurrent laryngeal nerve paralysis (OR = 3.32, 95 % CI: 0.65 to 16.90, P = 0.15 > 0.05). Compared with COT, ET has the advantages of shorter incision length, less intraoperative blood loss, better prognosis and comparable safety, making it a worthy choice for clinical application.

The lithology and pore structure of conglomerate reservoir in the Mahu sag, China, are complex, which makes it difficult to identify reservoir fluids. In this study, the body relaxation characteristics of crude oil at different temperatures were obtained from block crude oil samples, and two simulated oil samples with different body relaxation characteristics were used to conduct experiments. The saturated water, bound water, and saturated oil states of some conglomerate samples were quickly established by vacuum compression saturation, high-speed centrifugation, and vacuum saturation simulation of oil, and the fluid and different simulated oil-water saturation states were analyzed by nuclear magnetic resonance (NMR) experiments. The experimental results showed that the distribution range of the water-saturated core NMR T2 spectrum is mainly affected by surface relaxation. The NMR spectra of saturated oil with different viscosity values are different from those of saturated water because of the relaxation property of the oil phase. The samples of this experiment indicated that the difference is more obvious when the oil is thinner. The distribution pattern of the oil-bearing NMR results was affected by the relaxation of the oil phase, surface relaxation, pore structure, and wettability. With consideration of the relaxation characteristics of the oil samples, the NMR T2 spectra of two oil-saturated conglomerates were analyzed by multi-component Gaussian fitting, and the relaxation signals of the oil phase were evaluated quantitatively.

The saturated impulse is a special phenomenon in the dynamic plastic behavior of engineering structures under intensive pulse loading, such as slamming loading. In this study, slamming experiments were performed on steel plates to investigate their slamming pressure and dynamic plastic responses, as well as the saturation phenomenon, and elucidate the effect of the plate thickness and material properties on the dimensionless saturated deflection and saturated impulse in combination with the published test data. The results show that the dimensionless saturated deflection and saturated impulse of the test plates gradually increased as the dimensionless stiffness decreased. After being validated against the experimental results, a numerical method that considered the fluid–structure interaction (FSI) effect was then employed to provide comprehensive insight into the transient plastic responses and saturated impulse of the flat plates under slamming impact. Numerical simulations revealed that the compressed air layer always existed during the effective process of the flat slamming impact. Through the numerical prediction of the dynamic plastic deflection and slamming pulse loading, it was observed that the saturated impulse phenomenon always took place after the time instant of the peak value of the pressure pulse. Furthermore, the analysis of the saturated impulse based on the numerical simulations indicated that the saturation phenomenon was more likely to be achieved as the water impact velocity increased.

Accurate monitoring of lithium-ion battery temperature is essential to ensure these batteries’ efficient and safe operation. This paper proposes a relevance-based reconstruction-oriented EMD-Informer machine learning model, which combines empirical mode decomposition (EMD) and the Informer framework to estimate the surface temperature of 18,650 lithium-ion batteries during charging and discharging processes under complex operating conditions. Initially, based on 9000 data points from the U.S. NASA Prognostics Center of Excellence’s random battery-usage dataset, where each data point includes three features: temperature, voltage, and current, EMD is used to decompose the temperature data into intrinsic mode functions (IMFs). Subsequently, the IMFs are reconstructed into low-, medium-, and high-correlation components based on their correlation with the original data. These components, along with voltage and current data, are fed into sub-models. Finally, the model captures the long-term dependencies among temperature, voltage, and current. The experimental results show that, in single-step prediction, the mean squared error, mean absolute error, and maximum absolute error of the model’s predictions are 0.00095, 0.02114, and 0.32164 °C; these metrics indicate the accurate prediction of the surface temperature of lithium-ion batteries. In multi-step predictions, when the prediction horizon is set to 12 steps, the model achieves a hit rate of 93.57% where the maximum absolute error is within 0.5 °C; under these conditions, the model combines high predictive accuracy with a broad predictive range, which is conducive to the effective prevention of thermal runaway in lithium-ion batteries.

Abstract Rabies is a lethal infectious disease caused by rabies virus (RABV). The mortality rate is very high after the appearance of clinical symptoms, with a survival rate of almost 0%. There is presently no cure for rabies. In the present study, we investigated whether the extract of Shougong powder—a calcium powder prepared from gecko that has demonstrated immunomodulatory properties in mice—is an effective treatment for rabies. The antiviral effects of the extract were evaluated both in vitro and in vivo with the cytotoxicity and antiviral assays and by immunofluorescence analysis, quantitative real‐time (qRT)‐PCR, and western blotting. The results showed that Shougong powder and its extract increased survival rate in RABV‐infected mice is up to 60% and 50%, respectively, even in 20 times of LD50, whereas the control groups treated with isoprinosine (IPS) or saline are only 20% and 0% survival (p = .011). qRT‐PCR and western blotting analyses showed that the extract strongly inhibited viral mRNA expression and protein synthesis in vitro: expression of the N, P, M, G, and L genes of RABV was decreased by 28.8%–45.0% in the IPS group (p < .05) and by 50.1%–59.0% in the extract group (p < .05) relative to the control group. These results demonstrate that Shougong powder has certain antiviral effects against RABV and can potentially be used for the treatment for rabies.

ABSTRACTEngineering microbial hosts to synthesize pyruvate derivatives depends on blocking pyruvate oxidation, thereby causing severe growth defects in aerobic glucose-based bioprocesses. To decouple pyruvate metabolism from cell growth to improve pyruvate availability, a genome-scale metabolic model combined with constraint-based flux balance analysis, geometric flux balance analysis, and flux variable analysis was used to identify genetic targets for strain design. Using translation elements from a ~3,000 cistronic library to modulate fxpK expression in a bicistronic cassette, a bifido shunt pathway was introduced to generate three molecules of non-pyruvate-derived acetyl-CoA from one molecule of glucose, bypassing pyruvate oxidation and carbon dioxide generation. The dynamic control of flux distribution by T7 RNAP-mediated synthetic small RNA decoupled pyruvate catabolism from cell growth. Adaptive laboratory evolution and multi-omics analysis revealed that a mutated isocitrate dehydrogenase functioned as a metabolic switch to activate the glyoxylate shunt as the only C4 anaplerotic pathway to generate malate from two molecules of acetyl-CoA input and bypass two decarboxylation reactions in the tricarboxylic acid cycle. A chassis strain for pyruvate derivative synthesis was constructed to reduce carbon loss by using the glyoxylate shunt as the only C4 anaplerotic pathway and the bifido shunt as a non-pyruvate-derived acetyl-CoA synthetic pathway and produced 22.46, 27.62, and 6.28 g/L of l-leucine, l-alanine, and l-valine by a controlled small RNA switch, respectively. Our study establishes a novel metabolic pattern of glucose-grown bacteria to minimize carbon loss under aerobic conditions and provides valuable insights into cell design for manufacturing pyruvate-derived products.IMPORTANCEBio-manufacturing from biomass-derived carbon sources using microbes as a cell factory provides an eco-friendly alternative to petrochemical-based processes. Pyruvate serves as a crucial building block for the biosynthesis of industrial chemicals; however, it is different to improve pyruvate availability in vivo due to the coupling of pyruvate-derived acetyl-CoA with microbial growth and energy metabolism via the oxidative tricarboxylic acid cycle. A genome-scale metabolic model combined with three algorithm analyses was used for strain design. Carbon metabolism was reprogrammed using two genetic control tools to fine-tune gene expression. Adaptive laboratory evolution and multi-omics analysis screened the growth-related regulatory targets beyond rational design. A novel metabolic pattern of glucose-grown bacteria is established to maintain growth fitness and minimize carbon loss under aerobic conditions for the synthesis of pyruvate-derived products. This study provides valuable insights into the design of a microbial cell factory for synthetic biology to produce industrial bio-products of interest.

The box girder’s condition significantly impacts the safety and overall performance of the entire ship because it is the primary stress component of the hull construction. This work used experimental research on the long-span hull box girder based on IFEM (Inverse Finite Element Method) technology to ensure the structural safety of the hull box girder. Due to the limitations of conventional experiments in this technical field, such as their reliance on finite element data and lack of input from physical tests, numerous research methods combining the strain sensing data from physical tests with the strain data from virtual sensors were conducted. The strain fields of the top plate, side plate, and bottom plate were each reconstructed in turn, and the verifier measuring points in the physical model test were used to assess the accuracy of the reconstruction results. The findings demonstrate that the top plate, side plate, and bottom plate reconstructions had relative errors of 0.24–7.86%, 0.75–8.13%, and 3.31–2.52%, respectively. This enables the reconstruction of the strain field of the long-span hull box girder using physical test data and promotes the use of iFEM technology in the field of structural health monitoring of large marine structures.

Abstract Background Conventional blood and stool tests are normally used for early screening of colorectal cancer (CRC) but the accuracy and efficiency remain to be improved. Recent findings suggest Fusobacterium nucleatum to be a biomarker for CRC. This study evaluated the role of F. nucleatum and developed CRC diagnostic models by combining F. nucleatum with fecal occult blood (FOB), transferrin (TRF), carcinoembryonic antigen (CEA), carbohydrate antigen 19‐9 (CA19‐9), gender, and age. Materials and Methods Candidates including 71 healthy individuals and 59 CRC patients were recruited. Abundance of F. nucleatum in stool or tissue samples was measured by quantitative real‐time PCR. CEA, CA19‐9, TRF, and FOB were measured in parallel. These biomarkers together with genders and ages were the seven parameters used to develop CRC diagnostic models. Ten different machine learning algorithms were tested to achieve the best performance. Results Fecal F. nucleatum abundance was found significantly higher in CRC group compared to healthy group (p = 0.0005). Among the CRC patients, F. nucleatum abundance in tumor tissue was significantly higher than that in paracancerous tissue (p = 0.0087). CRC diagnostic models using different parameters were generated based on Logistic Regression algorithm, which showed good performance. The area under the curve (AUC) score of fecal F. nucleatum as the single diagnostic biomarker was 0.68 while the accuracy was 0.56. The diagnostic performance was obviously improved with the highest AUC (0.93) and accuracy (0.87) achieved when using all the 7 clinical parameters. The combination F. nucleatum + FOB + gender + age had the second highest AUC (0.92) and accuracy (0.85). A more utilitarian model using F. nucleatum + FOB showed relatively high AUC at 0.86 and accuracy at 0.81. Conclusions F. nucleatum is valuable for CRC diagnosis. Combination of different clinical parameters could significantly improve CRC diagnostic performance. The combination F. nucleatum + FOB + gender + age may be an effective and noninvasive method for clinical application.

Tight conglomerate rocks consist of gravels and rock matrices. The existence of these stiff gravels leads to heterogeneity in conglomerates and makes it difficult to characterize rock mechanical properties, which then affects drilling and hydraulic fracturing operations in tight conglomerate hydrocarbon-bearing reservoirs. This case study introduces a series of experimental and numerical analyses for the better understanding of rock deformation and elastic wave propagation patterns in a tight conglomerate reservoir in Junggar Basin, China. Tri-axial compression tests, acoustic test, and finite element modeling of rock deformation and elastic wave propagation in conglomerate rocks are presented. Experimentally tested samples exhibit good brittleness and shearing failure patterns, while well correlated static-dynamic elastic moduli and P-S wave velocities are captured. Numerical results show that the existence of stiff gravels leads to strong direction-dependent stress and strain anisotropies. Stress concentrations are also induced by gravels radially and axially. In the elastic wave domain, stiff gravels facilitate the propagation of elastic waves. The gravel close to the wave source also induces stronger compressive/tensile states in the wave domain, indicating that the existence of gravels in conglomerates can alter waveforms. This integrated approach improves the quantitative understanding of stress, strain, and elastic wave responses in heterogeneous tight conglomerates. This case study also serves as a reference for the brittleness evaluation and geomechanical evaluation in the study area. The contribution of this work is primarily about the integrated experimental study, solid deformation modeling, and elastic wave modeling of tight conglomerate rocks.

A rare study on the quantitative relationship between the energetic impact of debris flows on the intensity and duration of growth disturbances of tree rings was carried out, partly due to a lack of feasible approaches and detailed field evidence. In this study, we first used a dendrogeomorphic technique to determine the age of a recent debris flow derived from historic landslide deposits at Qingyang Mountain (QYM) on the northeastern Tibet plateau. We acquired the quantitative data on the annual widths of tree rings in history and confirmed the influence of the debris flow rather than other factors (e.g., climatic events and inset outbreaking) in disturbing the growth of tree rings in a specific year. Using this approach, we determined that the age of the debris flow at QYM occurred in 1982, which was speculated to be triggered by the high monthly precipitation registered during July 1982. Subsequently, based on the boundaries of historic debris flow identified on remote sensing images before and after 1982 and the depth-integrated continuum model, we reconstructed the process of the 1982 debris flow and obtained the kinematic energy of the debris flow impacting the sampled trees. Based on the study, we observed that two growth disturbance patterns of tree rings influenced by the reconstructed 1982 debris flow were revealed, including growth suppression and asymmetric growth. We obtained a raw logarithm relationship between duration (i.e., lasting time for the disturbed tree rings to recover the initial width) and intensity of growth disturbances (i.e., growth suppression ratio of disturbed tree rings). We concluded that there is a negative exponential relationship between the simulated kinematic energy of debris flow impacting the disturbed trees and the time to recover the initial width of corresponding tree rings.

Proficiency testing based on quality control materials is an important component of the quality assurance system for detection methods. However, in the detection of infectious diseases, it is a challenge to use quality control materials derived from clinical samples or pathogens owing to their infectious nature. The Xpert MTB/RIF assay, endorsed by the World Health Organization, is one of the most widely implemented assays in the detection of Mycobacterium tuberculosis along with rifampicin resistance and its heterogeneity. Clinical isolates are typically used as quality controls for this assay, leading to concerns about biosafety, constrained target sequence polymorphisms, and time-consuming preparation. In this study, a heterogeneous quality control library for the Xpert MTB/RIF assay was constructed based on DNA synthesis and site-directed mutation, which provides sufficient rifampicin resistance polymorphisms, enabling monitoring all five probes of Xpert MTB/RIF and its combinations. Escherichia coli and Bacillus subtilis were used as heterogeneous hosts rather than the pathogen itself to eliminate biosafety risks; thus, preparation does not require a biosafety level III laboratory and the production time is reduced from a few months to a few days. The panel was stable for more than 15 months stored at 4°C and could be distributed at room temperature. All 11 laboratories in Shanghai participating in a pilot survey identified the specimens with corresponding probe patterns, and discordant results highlighted inappropriate operations in the process. Collectively, we show, for the first time, that this library, based on heterogeneous hosts, is an appropriate alternative for M. tuberculosis detection.

ObjectiveTo explore the functions of the polymorphisms in 5-methylcytosine (m5C) modification-related coding genes on the susceptibility of pediatric acute lymphoblastic leukemia (ALL).MethodsCase–control study and multinomial logistic regression analysis were performed to construct models to evaluate the susceptibility of pediatric ALL. The relationship between five functional SNPs in m5C modification-coding genes and pediatric ALL risk was analyzed. Genotyping of 808 cases and 1,340 healthy samples from South China was identified using a TaqMan assay; odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the relationship between the five selected SNPs and pediatric ALL susceptibility.ResultsAmong the five analyzed SNPs, NOL1 rs3764909 and NSUN4 rs10252 variants significantly increased the susceptibility of pediatric ALL, while NSUN3 rs7653521, NSUN5 rs1880948, and NSUN6 rs3740102 variants were not associated with the risk of ALL. Stratification analyses demonstrated that NOL1 rs3764909 C>A exhibited a significant association with increased pediatric ALL risk in subgroups of common B ALL, pre-B ALL, T-cell ALL, low and middle risk, other gene fusion types, non-gene fusion, hypodiploid, normal diploid, primitive lymphocytes in marrow < 5% on week 12, and minimal residual disease (MRD) A was related to increased risk of ALL children in subgroups of age ≥ 120 months, normal white blood cell (WBC) number, middle risk, non-gene fusion, MRD ≥ 0.01 on days 15–19, and primitive lymphocytes in marrow < 5% on day 33 after induced therapy. Compared with the reference haplotype CAGTA, children who harbored haplotypes CCGTG and ACATA were remarkably related to increased ALL susceptibility. rs3764909 and rs10252 varieties of alleles were not associated with MRD levels after the selected chemotherapeutics.ConclusionsIn conclusion, NOL1 rs3764909 and NSUN4 rs10252 variants were enhanced by pediatric ALL risk and were suggested to be potential biomarkers for pediatric ALL.

Exposure to fine particulate matter (PM2.5) has significant effects on human skin health, mainly disrupting skin homeostasis and accelerating aging. To date, the effects of PM2.5 on psoriasis (PSO) have not been elucidated. An ambient particulate matter exposed and well characterized imiquimod (IMQ)-induced psoriasis mouse model was established. Thirty male C57BL/6 mice aged 8 weeks were randomly divided into three groups: filtered air (FA) group (Control group), PSO+ FA group and PSO + PM2.5 group. A KRT17 knockdown (KRT17-KD) mouse model was simultaneously established by subcutaneously injecting KRT17-KD lentivirus. Forty male C57BL/6 mice were randomly divided into four groups: PSO + FA + KRT17-RNAi negative control lentivirus (KRT17-NC) group, PSO+ FA+ KRT17-KD group, PSO + PM2.5 + KRT17-NC group and PSO + PM2.5 + KRT17-KD group. PM2.5 exposure continued for 8 weeks. Psoriasis was induced by topically applying IMQ on the dorsal skin of the mice for 6 days during week 8. Morphometric and histological analyses were performed to investigate the changes in psoriatic lesions. Differentially expressed genes and enriched pathways were explored using bioinformatics analysis and showed that KRT17 gene and the vascular endothelial growth factor receptor signaling pathway were associated with psoriasis. HaCaT cells were stimulated with interleukin-17A and infected with KRT17-KD lentivirus to establish an in vitro KRT17 knockdown psoriasis cell model. Notably, PM2.5 exposure increased the expression of KRT17 protein and activated AKT/mTOR/HIF-1α signaling pathway in vivo. Moreover, specific agonist of AKT (740Y-P) reversed the decreased neovascularization induced by KRT17 knockdown through AKT/mTOR/HIF-1α signaling pathway in vitro. Consequently, PM2.5 exposure could promote the development and progression of psoriasis through KRT17-dependent activation of AKT/mTOR/HIF-1α signaling pathway.

Welded joints in grid structures are susceptible to damage and destruction when exposed to random excitation. The complexity of the grid structure poses challenges for realizing the damage recognition of welded joints. In this study, a two-step method is proposed specifically for damage identification of welded joints in grid structures, combining wavelet analysis and fuzzy pattern recognition to accurately identify the location and extent of damage in welded joints. Firstly, the structure is divided based on the analysis of the influence range of joint damage. Key joints are selected within the sub-regions where sensors are installed, and the acceleration response of these key joints is measured. Wavelet analysis is then applied to identify the sub-regions where weld damage occurs. Secondly, an equivalent finite element model is established for joints with varying degrees of damage. The damage index, calculated as the ratio of the absolute value of the difference in the first-order element strain mode of the members, increases with the degree of damage during joint weld damage. By monitoring the changes in the damage index of sensitive members, which exhibit significant changes with varying weld damage degrees, a damage pattern database is constructed for each sub-region. The membership degree between joint damage and the patterns in the pattern database is then calculated to determine the location and degree of weld damage. To validate the effectiveness of the proposed method, an experiment was conducted using a grid structure model with replaceable members. Highly sensitive FBG sensors were designed to measure the acceleration response of the joints, resulting in accurate identification of damaged sub-regions solely through the measurement of key joint acceleration responses. Furthermore, within the damaged sub-regions, the fuzzy pattern recognition method precisely determined the location and degree of weld damage in the joints. The experimental results demonstrate that the proposed method effectively reduces the complexity of the structure by dividing the grid structure into sub-regions, and enables the two-step identification method to achieve successful damage identification for the joints in the grid structure with high efficiency and accuracy.

This paper proposes an approach that utilizes Artificial-Intelligence-Generated Content (AIGC) to overcome the constraints of Structural Health Monitoring (SHM) devices in capturing global stress with limited sensors. Feature elements are selected based on correlation analysis among finite elements and used as stress-measured points. An Artificial Neural Network (ANN) is used to establish the relationship between the feature and correlation elements. The proposed method is applied to the connector structure of an offshore platform, and an optimal ANN is established to optimize its performance by considering factors such as the number of sensors, the neural network framework, and the convergence criteria. The generalization performance of the ANN is validated through a real-scale model test, with deviations below 10% and an average deviation of less than 4% in multiple conditions, verifying its accuracy. This technology represents a significant advancement, enhancing the practicality of the SHM technology from “point monitoring” to “field monitoring”.

Potential rockfall source areas are widely distributed in the high mountain areas of the Tibetan Plateau, posing significant hazards to human lives, infrastructures, and lifeline facilities. In a combination of field investigation, high-precision aerial photogrammetry, and numerical simulation, we took the Maoyaba basin as an example to explore a rapid identification method for high-altitude rockfall sources. An automatic potential rockfall source identification (PRSI) procedure was introduced to simplify the process of rockfall source identification. The study revealed that rockfall sources are concentrated in areas with intense frost weathering. Our identification results were validated using rockfall inventory data detection from remote sensing images and field investigation. Of the rockfall source areas identified by the PRSI procedure, 80.85% overlapped with the remote sensing images result. The accuracy assessment using precision, recall, and F1 score was 0.91, 0.81, and 0.85, respectively, which validates the reliability and effectiveness of the PRSI procedure. Meanwhile, we compared the rockfall source distribution of five DEMs with different resolutions and four neighborhood areas. We discovered that, in addition to high-resolution DEMs (i.e., 1 m and 2 m), medium-resolution DEMs (i.e., 5 m, 12.5 m) also perform well in identifying rockfall sources. Finally, we conducted a hazard assessment based on Culmann’s two-dimensional slope stability model and rockfall hazard vector method. Appropriate protective measures should be taken at high-hazard sections to safeguard pedestrians, vehicles, and related infrastructure from rockfalls.

As a current research hotspot, graph convolution networks (GCNs) have provided new opportunities for tree species classification in multi-source remote sensing images. To solve the challenge of limited label information, a new tree species classification model was proposed by using the semi-supervised graph convolution fusion method for hyperspectral images (HSIs) and multispectral images (MSIs). In the model, the graph-based attribute features and pixel-based features are fused to deepen the correlation of multi-source images to improve accuracy. Firstly, the model employs the canonical correlation analysis (CCA) method to maximize the correlation of multi-source images, which explores the relationship between information from various sources further and offers more valuable insights. Secondly, convolution calculations were made to extract features and then map graph node fusion, which not only reduces redundancy features but also enhances compelling features. Finally, the relationship between representative descriptors is captured through the use of hyperedge convolution in the training process, and the dominant features on the graph are fully mined. The tree species are classified through two fusion feature operations, leading to improved classification performance compared to state-of-the-art methods. The fusion strategy can produce a complete classification map of the study areas.

Study region: The Qilian Mountains, Northwest China Study focus: Trends in flood frequency and their driving factors must be analyzed to enable the effective management of water resources in the inland rivers originating in the Qilian mountains (QMs). Based on hydrological station datasets from 12 typical rivers with annual maximum peak discharge and peaks-over-threshold (POT) flood series for the period 1970–2019, the spatial and temporal variations of flooding in 12 rivers were detected using a linear regression estimator and Mann–Kendall trend tests. New hydrological insights: The results indicate that the frequency of POT floods in 12 rivers during 1970–2019 showed an increasing trend at the 90% significance level, with an increasing trend for small floods and decreasing trends for medium and large floods. Flood levels varied from east to west across the region, with an overall decreasing trend in the east, an increase in small floods in the central rivers, and significant increases in both small and medium floods in the west. Both temperature and precipitation increased after 1987, and summer precipitation was a significantly increased; as a result, POT floods in most rivers increased after the 1980 s, and trends in flood frequency showed decreases in spring and autumn and an increase in summer. The main causes of the changes in flood frequency were found to be heavy rainfall, abnormal warming, and accelerated glacial melting.

Porphyran possesses various activities, while the effects of the porphyran from Porphyra haitanensis (PPH) on obesity are rarely reported. In this study, C57BL/6J male mice were fed with HFD combined with PPH gavage (50 mg/kg/d) for 16 weeks, and body weight was measured once a week. After that, serum, adipose, and liver tissues were collected for physiological and biochemical analyses. Our research indicated that PPH treatment alleviated obesity in HFD-fed mice. PPH alleviated fat accumulation in serum, liver, and adipose tissues. In addition, PPH activated the AMPK-HSL/ACC pathway in epididymal adipose tissue to reduce lipid accumulation. Moreover, PPH turned white adipose into brown and activated the PGC 1α-UCP 1-mitochondrial pathway in scapular adipose tissue to generate more heat. Interestingly, PPH regulated colonic microbiota homeostasis in obese mice, including significant elevation of Roseburia and Eubacterium and marked reduction of Helicobacter. Moreover, Spearman’s correlation analysis demonstrated that regulation of gut microbiota can decrease lipid accumulation. In summary, our study illustrated that PPH possesses the potential to be developed as an anti-obesity agent.

Abstract The outbreak of coronavirus disease 2019 (COVID‐19, caused by SARS‐Cov‐2) is a big challenge for global health systems and the economy. Rapid and accurate tests are crucial at early stages of this pandemic. Reverse transcription‐quantitative real‐time polymerase chain reaction is the current gold standard method for detection of SARS‐Cov‐2. It is impractical and costly to test individuals in large‐scale population screens, especially in low‐ and middle‐income countries due to their shortage of nucleic acid testing reagents and skilled staff. Accordingly, sample pooling, such as for blood screening for syphilis, is now widely applied to COVID‐19. In this paper, we survey and review several different pooled‐sample testing strategies, based on their group size, prevalence, testing number, and sensitivity, and we discuss their efficiency in terms of reducing cost and saving time while ensuring sensitivity.

The current limited approaches to calculating hillslope erosion rate hamper the study of the relationships among the rates of hillslope erosion, river incision, and tectonic uplift and hence the discussion of steady-state landscape evolution. In this paper, we use remote sensing and geochronological methods to calculate the upper and lower bounding hillslope erosion rates in the Qilian Shan range, Tibet. Our analysis focuses on five convex landslide sediment units derived from the weathered hillslopes at Qingyang Mountain on the tectonically active northeastern Tibetan Plateau. These sediment units range in thickness from 5.5 to 12.8 m and in volume from 119 × 103 to 260 × 103 m3. Based on field observations, measurements extracted from high-resolution DEMs, and optical stimulated luminescence (OSL) ages on fluvial terraces, we obtain lower and upper bounding rates of 0.13 ± 0.03 and 0.21 ± 0.04 mm/yr, respectively. Finally, we calculate incision rates, ranging from 0.21 ± 0.02 to 0.39 ± 0.01 mm/yr, from heights of a dated fluvial terrace above the present river and the time of abandonment of the associated bedrock strath estimated from OSL ages. The rates of hillslope erosion and river incision at Qingyang Mountain and the tectonic uplift of the Qilian Mountains are estimated to be within a factor of two over the past 117 ka, suggesting that a state of dynamic equilibrium has likely existed on this timescale.

Piezoelectric ceramic has been widely applied in many fields because of its characteristics, and the performance of piezoelectric ceramic is determined strongly by its driver. In this study, an approach to analyzing the stability of a piezoelectric ceramic driver with an emitter follower stage was presented, and a compensation was proposed. First of all, using the method of modified nodal analysis and loop gain analysis, the transfer function for the feedback network was analytically deduced, and the cause of the instability of the driver was found to be the pole composed of the effective capacitance from the piezoelectric ceramic and the transconductance from the emitter follower. Then, a compensation involving a novel delta topology composed of an isolation resistor and a second feedback path was proposed, and its function principle was discussed. Simulations showed a correspondence between the analysis and the effectiveness of the compensation. Finally, an experiment was set up with two prototypes, one with compensation, and the other without compensation. Measurements showed the elimination of oscillation in the compensated driver.

With the ever-increasing world population, the energy produced from green, environmentally friendly approaches is in high demand. In this work, we proposed a green and cost-effective strategy for synthesizing a porous carbon electrode decorated with alumina oxide (Al2O3) from cherry blossom leaves using the pyrolysis method followed by a sol-gel method. An Al2O3-coating nano-layer (4–6 nm) is formed on the porous carbon during the composition fabrication, which further adversely affects battery performance. The development of a simple rich-shell-structured C@Al2O3 nanocomposite anode is expected to achieve stable electrochemical performances as lithium storage. A significant contributing factor to enhanced performance is the structure of the rich-shell material, which greatly enhances conductivity and stabilizes the solid–electrolyte interface (SEI) film. In the battery test assembled with composite C@Al2O3 electrode, the specific capacity is 516.1 mAh g−1 at a current density of 0.1 A g−1 after 200 cycles. The average discharge capacity of carbon is 290 mAh g−1 at a current density of 1.0 A g−1. The present study proposes bioinspired porous carbon electrode materials for improving the performance of next-generation lithium-ion batteries.

Analyzing trends in flood magnitude changes, and their underlying causes, under climate change, is a key challenge for the effective management of water resources in arid and semi-arid regions, particularly for inland rivers originating in the Qilian Mountains (QMs). Sen’s slope estimator and the Mann–Kendall test were used to investigate the spatial and temporal trends in flood magnitude, based on the annual maximum peak discharge (AMPD) and Peaks Over Threshold magnitude (POT3M) flood series, of twelve typical rivers, from 1970 to 2021. The results showed that, in the AMPD series, 42% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends; in the POT3M series, 25% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends. The regional differences in the QMs from east to west were that, rivers in the eastern region (e.g., Gulang, Zamu, and Xiying rivers) showed significantly decreasing trends in the AMPD and POT3M series; most rivers in the central region had non-significant trends, while the Shule river in the western region showed a significantly increasing trend. Temperatures and precipitation showed a fluctuating increasing trend after 1987, which were the main factors contributing to the change in flood magnitude trends of the AMPD and POT3M flood series in the QMs. Regional differences in precipitation, precipitation intensity, and the ratio of glacial meltwater in the eastern, central and western regions, resulted in the differences in flood magnitude trends between the east and west.

Conventional AlSi materials always have a coarse and discontinuous Si structure, which limits their application as thermal management materials. Fortunately, nature has evolved efficient strategies to form complex microstructures that exhibit excellent wear resistance and thermal properties; one such example is found in the red deer antler. Here, inspired by the antler structure, AlSi composites with a novel fenestrated network-particle structure (FN) and with a common isolated island structure (II) are designed and prepared. Subsequently, the dynamic formation of FN is tracked and studied using computational fluid dynamics (CFD) simulation. To investigate the reinforcement mechanisms of FN, the wear resistances and thermal properties of FN and II are compared and analyzed. Simulation and experimental results show that the reconstruction of a semi-continuous structure promotes the formation of a striated structure, whereas flowing Si particles provide some sites for the formation of the fenestrated structure. The dynamic formation of FN is strongly influenced by the convection–diffusion process and the flow path. Moreover, this biomimetic FN structure exhibits better wear resistance and thermal properties than II, owing to its strong structural support and high expansion resistance. This work is expected to provide new perspectives on the microstructural design of thermal management materials with good wear resistance.

Abstract Background This study profiled the somatic genes mutations and the copy number variations (CNVs) in cerebrospinal fluid (CSF)-circulating tumor DNA (ctDNA) from patients with neoplastic meningitis (NM). Methods A total of 62 CSF ctDNA samples were collected from 58 NM patients for the next generation sequencing. The data were bioinformatically analyzed by (Database for Annotation, Visualization and Integrated Discovery) DAVID software. Results The most common mutated gene was TP53 (54/62; 87.10%), followed by EGFR (44/62; 70.97%), PTEN (39/62; 62.90%), CDKN2A (32/62; 51.61%), APC (27/62: 43.55%), TET2 (27/62; 43.55%), GNAQ (18/62; 29.03%), NOTCH1 (17/62; 27.42%), VHL (17/62; 27.42%), FLT3 (16/62; 25.81%), PTCH1 (15/62; 24.19%), BRCA2 (13/62; 20.97%), KDR (10/62; 16.13%), KIT (9/62; 14.52%), MLH1 (9/62; 14.52%), ATM (8/62; 12.90%), CBL (8/62; 12.90%), and DNMT3A (7/62; 11.29%). The mutated genes were enriched in the PI3K-Akt signaling pathway by the KEGG pathway analysis. Furthermore, the CNVs of these genes were also identified in these 62 samples. The mutated genes in CSF samples receiving intrathecal chemotherapy and systemic therapy were enriched in the ERK1/2 signaling pathway. Conclusions This study identified genes mutations in all CSF ctDNA samples, indicating that these mutated genes may be acted as a kind of biomarker for diagnosis of NM, and these mutated genes may affect meningeal metastasis through PI3K-Akt signaling pathway.

Type 2 diabetes mellitus (T2DM) is associated with cardiovascular disease (CVD) and sodium glucose cotransporter 2 inhibitors, as oral medications for T2DM treatment have shown the potential to improve vascular dysfunction. The aim of this study was to evaluate the ability of canagliflozin (Cana) to relieve CVD in T2DM mice and its possible action mechanism. Mice with diabetic CVD was conducted by a high-fat diet for 24 weeks, followed by oral gavaging with metformin (200 mg/kg/day) or Cana (50 mg/kg/day) for 6 weeks. The result demonstrated that Cana reduced serum lipid accumulation, and decreased the arteriosclerosis index and atherogenic index of plasma. In addition, Cana treatment reduced the circulating markers of inflammation. More importantly, Cana improved cardiac mitochondrial homeostasis and relieved oxidative stress. Moreover, Cana treatment alleviated the myocardial injury with decreasing levels of serous soluble cluster of differentiation 40 ligand and cardiac troponin I. Thus, cardiovascular abnormality was relieved by suppressing fibrosis and basement membrane thickening, while elevating the cluster of differentiation 31 expression level. Importantly, Cana increased the ratio of gut bacteria Firmicutes/Bacteroidetes and the relative abundance of Alistipes, Olsenella, and Alloprevotella, while it decreased the abundance of Mucispirillum, Helicobacter, and Proteobacteria at various taxonomic levels in mice with diabetic CVD. In short, Cana treatment altered the colonic microbiota composition close to the normal level, which was related with blood lipid, inflammation, and oxidative stress, and might play a vital role in CVD. In general, the improvements in the gut microbiota and myocardial mitochondrial homeostasis may represent the mechanism of Cana on CVD treatment.

Abstract Ultralong room‐temperature phosphorescence (RTP) is highly useful for information encryption, organic electronics, bioelectronics, etc. However, the preparation of related metal‐free materials with multiple colors across the full spectrum remains a major challenge. Herein, a facile method is developed to fabricate boron‐doped carbon dot (B‐CD) composites with full‐color long lifetime RTP continuously tailorable in the range of 466–638 nm simply by pyrolysis of the citric acid and boric acid precursors with various mass ratios at different temperatures. This leads to the formation of luminescent B‐CD centers in a rigid polycrystalline B2O3 matrix, which effectively stabilizes the triplet excited states of B‐CDs. Thus, the composites become phosphorescent over a relatively long period (5–12 s) after the removal of the irradiation source. Meanwhile, the increased particle size and oxidation degree of B‐CDs obtained at larger citric acid feeding or higher pyrolysis temperature continuously shift the phosphorescence from blue to red. Due to the formation of multiple luminescence centers, the RTP can also be finely modulated by the excitation wavelength. The resulting B‐CD composites with highly tunable long lifetime RTP further allow a variety of distinctive applications in multidimensional encryption handily utilizing space, time, and color variations.

Surface plasmon resonance microscopy (SPRM) has been widely employed in biological fields because of its high spatial resolution and label-free detection modality. In this study, SPRM based on total internal reflection (TIR) is studied via a home-built SPRM system, and the principle of imaging of a single nanoparticle is analyzed as well. By designing a ring filter and combining it with the deconvolution algorithm in Fourier space, the parabolic tail of the nanoparticle image is removed, in which a spatial resolution of 248 nm is obtained. In addition, we also measured the specific binding between the human IgG antigen and goat anti-human IgG antibody using the TIR-based SPRM. The experimental results have proved that the system can image sparse nanoparticles and monitor biomolecular interactions.

In order to solve the problem of manual labeling in semi-supervised tree species classification, this paper proposes a pixel-level self-supervised learning model named M-SSL (multisource self-supervised learning), which takes the advantage of the information of plenty multisource remote sensing images and self-supervised learning methods. Based on hyperspectral images (HSI) and multispectral images (MSI), the features were extracted by combining generative learning methods with contrastive learning methods. Two kinds of multisource encoders named MAAE (multisource AAE encoder) and MVAE (multisource VAE encoder) were proposed, respectively, which set up pretext tasks to extract multisource features as data augmentation. Then the features were discriminated by the depth-wise cross attention module (DCAM) to enhance effective ones. At last, joint self-supervised methods output the tress species classification map to find the trade-off between providing negative samples and reducing the amount of computation. The M-SSL model can learn more representative features in downstream tasks. By employing the feature cross-fusion process, the low-dimensional information of the data is simultaneously learned in a unified network. Through the validation of three tree species datasets, the classification accuracy reached 78%. The proposed method can obtain high-quality features and is more suitable for label-less tree species classification.

COVID-19 continues to circulate globally in 2021, while under the precise policy implementation of China’s public health system, the epidemic was quickly controlled, and society and the economy have recovered. During the pandemic response, nucleic acid detection of SARS-CoV-2 has played an indispensable role in the first line of defence. In the cases of emergency operations or patients presenting at fever clinics, nucleic acid detection is required to be performed and reported quickly. Therefore, nucleic acid point-of-care testing (POCT) technology for SARS-CoV-2 identification has emerged, and has been widely carried out at all levels of medical institutions. SARS-CoV-2 POCT has served as a complementary test to conventional polymerase chain reaction (PCR) batch tests, thus forming an experimental diagnosis platform that not only guarantees medical safety but also improves quality services. However, in view of the complexity of molecular diagnosis and the biosafety requirements involved, pathogen nucleic acid POCT is different from traditional blood-based physical and chemical index detection. No guidelines currently exist for POCT quality management, and there have been inconsistencies documented in practical operation. Therefore, Shanghai Society of Molecular Diagnostics, Shanghai Society of Laboratory Medicine, Clinical Microbiology Division of Shanghai Society of Microbiology and Shanghai Center for Clinical Laboratory have cooperated with experts in laboratory medicine to generate the present expert consensus. Based on the current spectrum of major infectious diseases in China, the whole-process operation management of pathogen POCT, including its application scenarios, biosafety management, personnel qualification, performance verification, quality control, and result reporting, are described here. This expert consensus will aid in promoting the rational application and robust development of this technology in public health defence and hospital infection management.

Due to the use of horizontal wells and hydraulic fracturing, commercial tight oil production from some tight sandy conglomerate reservoirs has been achieved. Since the widely distributed gravels in the sandy matrix in conglomerate reservoir rocks are harder than the matrix, the rock mechanical response in conglomerates under compression is highly heterogeneous. This increases the complexity of understanding the hydraulic fracturing behaviors in conglomerate reservoirs. Previous tri-axial compression tests provided the stress-strain relationships of conglomerate samples as a whole, and the stress and strain in the gravels and in the sandy matrix were not investigated due to the limitation of the compression test lab. This study presents tri-axial test results for a conglomerate sample cored from a reservoir that has been economically developed. Lab results are then used to calibrate the numerical model for the simulation of the tri-axial compression process. Numerical results indicate that the elastic modulus and size of gravels have significant impacts on the axial stresses and axial strains in the conglomerate. Stress concentrations are observed in gravels due to the heterogeneous mechanical properties in the conglomerate. The reorientation of the maximum horizontal principal stress is quantified to study the mechanisms of the interaction types between hydraulic fractures and gravels embedded in the tight sandy matrix.

Surface plasmon resonance microscopy (SPRM) is a versatile technique for biosensing and imaging that facilitates high-sensitivity, label-free, real-time characterization. To date, SPR technology has been successfully commercialized and its performance has continued to improve. However, this method is inhibited by low spatial resolution and the inability to achieve single-molecule detection. In this report, we present an overview of SPRM research progress in the field of plasma imaging and sensing. A brief review of the technological advances in SPRM is outlined, as well as research progress in important applications. The combination of various new techniques with SPRM is emphasized. Finally, the current challenges and outlook of this technique are discussed.

It has been recognized that the anisotropic structures dominate the deformation and strength properties of laminated rock masses. The resultant strength anisotropy is strongly affected by confining pressures beyond anisotropic structures. Nevertheless, the effects of confinement are inconsistent among existing experiments and not fully understood. This study focuses on the effects of confining pressure on strength anisotropy through theoretical derivation together with experimental results analysis. The variations in the possibility of anisotropic structural plane dominant failure and strength anisotropy degree under different confining pressures are discussed. The different types of anisotropic structural planes, i.e., the fresh contact discontinuity or soft, thick layer, are found as the key factor resulting in different confinement effects. The strength anisotropy weakens gradually and vanishes eventually as confining stress increases for the anisotropic rock mass with the structural plane of fresh contact discontinuity. On the other hand, the strength does not vanish at very high confining stress and the anisotropic strength difference even rises as confining stress increases for the anisotropic rock mass with the anisotropic structural plane of the soft layer. This study improves the understanding of anisotropic rock mass mechanical behavior, especially at high confining stress, and may promote the development of excavation and supporting techniques for underground projects.

High-entropy alloys (HEAs) with high hardness are promising materials for advanced industrial manufacturing. In this study, the AlCrFeNiV HEA was designed and successfully prepared using a plasma instantaneous process. The hardness test showed that AlCrFeNiV had a high hardness of 1076 ± 15 HV, which was much higher than those reported in the literature. The microstructure of AlCrFeNiV was composed of two different types of body-centered cubic (BCC) structures, BCC1 (Al, Cr, Fe, and Ni) and BCC2 (enriched V and Cr). A mixture of different BCC systems produced solution strengthening, which was responsible for the superior hardness. Moreover, the reciprocating sliding wear behavior of HEA against Al2O3 balls under dry and lubricated conditions at ambient temperature was investigated. The wear rates of AlCrFeNiV against Al2O3 under dry wear and lubrication were 17.2 × 10−5 mm3 N−1·m−1 and 12.4 × 10−5 mm3N−1·m−1, respectively, which were of the same order of magnitude as the wear rates of BCC HEAs. Regardless of the dry wear or wear with lubrication, the wear mechanism of the HEA was abrasive and delamination wear.

The ion-enrichment inside carbon nanotubes (CNTs) offers the possibility of applications in water purification, ion batteries, memory devices, supercapacitors, field emission and functional hybrid nanostructures. However, the low filling capacity of CNTs in salt solutions due to end caps and blockages remains a barrier to the practical use of such applications. In this study, we fabricated ultra-short CNTs that were free from end caps and blockages using ball milling and acid pickling. We then compared their ion-enrichment capacity with that of long CNTs. The results showed that the ion-enrichment capacity of ultra-short CNTs was much higher than that of long CNTs. Furthermore, a broad range of ions could be enriched in the ultra-short CNTs including alkali-metal ions (e.g., K+), alkaline-earth-metal ions (e.g., Ca2+) and heavy-metal ions (e.g., Pb2+). The ultra-short CNTs were much more unobstructed than the raw long CNTs, which was due to the increased orifice number per unit mass of CNTs and the decreased difficulty in removing the blockages in the middle section inside the CNTs. Under the hydrated-cation–π interactions, the ultra-short CNTs with few end caps and blockages could highly efficiently enrich ions.

CRISPR is an acquired immune system found in prokaryotes that can accurately recognize and cleave foreign nucleic acids, and has been widely explored for gene editing and biosensing. In the past, CRISPR/Cas-based biosensors were mainly applied to detect nucleic acids in the field of biosensing, and their applications for the detection of other types of analytes were usually overlooked such as small molecules and disease-related proteins. The recent work shows that CRISPR/Cas biosensors not only provide a new tool for protein analysis, but also improve the sensitivity and specificity of protein detections. However, it lacks the latest review to summarize CRISPR/Cas-based biosensors for protein detection and elucidate their mechanisms of action, hindering the development of superior biosensors for proteins. In this review, we summarized CRISPR/Cas-based biosensors for protein detection based on their mechanism of action in three aspects: antibody-assisted CRISPR/Cas-based protein detection, aptamer-assisted CRISPR/Cas-based protein detection, and miscellaneous CRISPR/Cas-based methods for protein detection, respectively. Moreover, the prospects and challenges for CRISPR/Cas-based biosensors for protein detection are also discussed.

In this paper, a novel one-way single-wire power transfer structure is proposed. Different from the traditional single-wire power transfer system, power is one-way transmitted from the power source to the load, and no loop is constituted. The structure of one-way single-wire power transfer is studied in detail, and the influences of its length and shapes on the transmission efficiency are determined. Research shows that the length of the receiving structure plays a key role in improving the system’s efficiency, while the transmitting structure has a little effect. Based on ensuring transmission efficiency, the space volume optimization method is further applied. The expression of electromagnetic field distribution is derived theoretically, and the proposed structure is verified by simulation and experimental results.

Using the cloud-ground lightning locating data from 2007 to 2017 and the thunderstorm day data from 1961 to 2003 in Hubei, we selected six lightning parameters such as thunderstorm day, cloud-ground lightning density, lightning current wave-head gradients, lightning current amplitude, large current density and small current density as risk evaluation indices of lightning disaster in Hubei province, and then combined them with the projection pursuit method to establish a lightning disaster risk assessment model. Based on this model, we conducted a risk zoning of lightning disasters in Hubei province. The results indicate that the lightning hazards in Hubei province can be divided into five risk levels, i.e., higher risk, sub high risk, medium risk, inferior risk and lower risk. The lightning disaster risk is higher in the east than that in the west, which gradually decreases from east to west. The higher and sub high risk areas mainly locate in the eastern regions of Hongan, Xiaochang, Xiaonan, Dongxihu, Caidian, Hannan and Honghu, while the inferior and lower risk areas mainly distribute in the western regions of Xiangzhou, Xiangcheng, Gucheng, Baokang, Xingshan, Zigui, Badong and Wufeng. The zone between the eastern and western regions mentioned above is mainly a medium-risk zone with a total of 27 districts or counties or cities. The results of lightning disaster risk zoning can provide scientific basis for local lightning disaster prevention and mitigation work for effective reduction of disaster losses.

We report the synthesis of β-palladium hydride nanodendrites (PdH0.33 NDs). The uniform PdH0.33 NDs are 36.3 ± 5.0 nm in diameter and selectively expose (111) planes decorated with (221) and (331) high-indexed steps. The PdH0.33 NDs show a high mass activity of 0.719 A/mgPd at 0.9 V (vs. reversible hydrogen electrode-RHE) toward alkaline oxygen reduction reaction (ORR), which is 3.7 and 6.3 times that of commercial Pt/C and house-made Pd/C, respectively. This study exemplifies the possibility of using special morphology and lattice H to modify the strain and electronic effect of metal for the optimization of functionalities. Keywords: Palladium hydride, Nanodendrites, Oxygen reduction reaction, Oxygen adsorption energy

This data article includes the supplementary database material for the manuscript “Thermodynamic description for the NaF-KF-RbF-ZnF2 system”, (Tang et al., 2018). We present all the thermodynamic parameters used and optimized model parameters of the thermodynamic database of the NaF-KF-RbF-ZnF2 quaternary system, by which researchers can obtain the calculated phase diagrams. What׳s more, the comparison of calculations with experimental lattice constants of all compounds and relative deviations of unit cell parameters between before and after structure optimization for the NaF-KF-RbF-ZnF2 system are demonstrated in this work. Meanwhile, we provide the calculated mixing enthalpy in the binary AF-ZnF2 (A=Na, K and Rb) and AF-RbF (A=Na and K) system, which are helpful for researchers to better understand the system. These supplementary databases are most useful in understanding the manuscript (Tang et al., 2018).

Self-assembled biomaterials have been widely explored for real-time fluorescence imaging, imaging-guided surgery, and targeted therapy for tumors, etc. In particular, small molecule-based self-assembly has been established as a reliable strategy for cancer theranostics due to the merits of small-sized molecules, multiple functions, and ease of synthesis and modification. In this review, we first briefly introduce the supramolecular chemistry of small organic molecules in cancer theranostics. Then, we summarize and discuss advanced small molecule-based self-assembly for cancer theranostics based on three types, including peptides, amphiphilic molecules, and aggregation-induced emission luminogens. Finally, we conclude with a perspective on future developments of small molecule-based self-assembled biomaterials integrating diagnosis and therapy for biomedical applications. These applications highlight the opportunities arising from the rational design of small organic molecules with self-assembly properties for precision medicine.

The wave parameter is an important environmental input condition. Traditional contact wave measurement methods are unable to meet the requirements of high precision, non-contact, and ship wave field assessment. Alternatively, stereo vision technology can realize a non-contact and mobile form of measurement. However, this technology suffers from poor timeliness and adaptability. This paper proposes a comprehensive wave measurement method that is based on stereo vision, wherein the gridding of siftGPU is used to achieve the fast matching of large images. The whole algorithm can be run within 6 s and it guarantees more than 20,000 feature-matching logarithms. Furthermore, by utilizing the least squares method and sea surface wave surface theory, the sea surface base level can be calculated without control points, along with the inversion of the sea wave parameters (wave height, period, and wave direction) and error point fitting. The rationality and superiority of the algorithm were verified through multiple comparison experiments. Compared with the Richard Brancker Research (RBR) wave height meter, the measurement error of the wave height is less than 10%, the period error is less than 0.5 s, and the wave direction error is less than 10° with the proposed method.

Polymerase chain reaction (PCR) is the standard tool in genetic information analysis, and the desirable detection merits of PCR have been extended to disease-related protein analysis. Recently, the combination of PCR and gold nanoparticles (AuNPs) to construct colorimetric sensing platforms has received considerable attention due to its high sensitivity, visual detection, capability for on-site detection, and low cost. However, it lacks a related review to summarize and discuss the advances in this area. This perspective gives an overview of established methods based on the combination of PCR and AuNPs for the visual detection of health-related DNA and proteins. Moreover, this work also addresses the future trends and perspectives for PCR–AuNP hybrid biosensors.

Emerging evidence demonstrated that traffic-related air pollution induced adverse effects on cardiovascular system. We designed a population-based cross-sectional study to explore the association between residential proximity to major roadways, traffic density and the prevalence of valvular heart disease (VHD). A total of 34040 subjects from a Rural Health Project between 2013 and 2018 were collected. According to the inclusion and exclusion criteria, 4158 participants were enrolled in the final analysis. And we calculated the subjects’ proximity to major roadways and collected the traffic density on the major roadways. Transthoracic echocardiography (TTE) was performed to diagnose the VHD, according to the current AHA/ACC (the American Heart Association and the American College of Cardiology) guidelines. Differences between groups were examined by the one-way ANOVAs for continuous variables and the chi-square tests for categorical variables. A logistic regression models were used to assess the associations. The stratified analysis by age and sex were conducted to further analyze the association. The restricted cubic spline analysis was performed to further evaluate the association between road way distance and VHD. Bonferroni test was used to adjust the significance level. The subjects closer to the major roads had the higher risk of tricuspid regurgitation (TR) (odds risk, OR = 1.519, 95% confidence intervals, 95%CI: 1.058-2.181), especially in female. The risk of VHD was positive (high traffic density VS low traffic density, OR = 1.799, 95%CI: 1.221-2.651), especially in female. In addition, the high traffic density was associated with the risk of mitral regurgitation (MR) (OR = 1.758, 95%CI: 1.085-2.848). The restricted cubic spline analysis found a threshold distance of about 300 m, where had the lowest risk of VHD, aortic regurgitation (AR), MR, TR. Our results found a positive association between traffic-related air pollution and VHD especially in female.

HER2 amplification greatly contributes to the tumorigenesis of multiple cancers. Intronic miR-4728-5p is transcribed along with its host gene HER2. However, little is known about the role of miR-4728-5p in cancer. This study aims to elucidate the potential role of miR-4728-5p and the underlying mechanism in breast cancer. Kaplan-Meier analysis showed that higher expression of HER2 led to worse survival outcomes in breast cancer patients. The TCGA dataset revealed that compared to normal breast tissues, HER2 and miR-4728-5p levels were significantly upregulated in breast cancer tissues with a positive correlation. In functional assays, miR-4728-5p was confirmed to promote the proliferation and migration in breast cancer cell BT474. EBP1 was identified as a direct target of miR-4728-5p via bioinformatics and luciferase reporter assays. miR-4728-5p was further demonstrated to increase HER2 expression and promote cell proliferation and migration by directly inhibiting EBP1 in breast cancer. Taken together, the HER2-intronic miR-4728-5p/EBP1/HER2 feedback loop plays an important role in promoting breast cancer cell proliferation and migration. Our study provides novel insights for targeted therapies of breast cancer.

To control pores in the backfill, the air-entraining agents (AEAs) are used as an admixture to realize the pore structure changes under artificial action and explore the effect of pore structure on strength. Two AEAs at different dosages were added to the backfill. The relationship was then analyzed between them from the macro- and mesoscopic aspects. The results indicate that AEA can regulate pore structure changes of AEACPB. With the increase in AEA content, the total pore volume of different pore sizes in AEACPB increases, in which the proportion of big and medium pore gradually increases while the proportion of small pore gradually decreases. The AEACPB’s UCS is linearly negatively correlated with the porosity and pore percentage, which is the primary factor affecting the AEACPB of the pore structure. When the total pores’ volume in the AEACPB is constant, the influence of different pore structures differs. A higher proportion of small pores leads to a linear increase in strength; a higher proportion of medium pores leads to a linear decrease in strength; and a higher proportion of big pores leads to an exponential decrease in strength. And the fractal dimension has a linear negative correlation with the UCS by fractal theory analysis.

Gamma-aminobutyric acid (GABA) can be used as a bioactive component in the pharmaceutical industry and a precursor for the synthesis of butyrolactam, which functions as a monomer for the synthesis of polyamide 4 (nylon 4) with improved thermal stability and high biodegradability. The bio-based fermentation production of chemicals using microbes as a cell factory provides an alternative to replace petrochemical-based processes. Here, we performed model-guided metabolic engineering of Corynebacterium glutamicum for GABA and butyrolactam fermentation. A GABA biosynthetic pathway was constructed using a bi-cistronic expression cassette containing mutant glutamate decarboxylase. An in silico simulation showed that the increase in the flux from acetyl-CoA to α-ketoglutarate and the decrease in the flux from α-ketoglutarate to succinate drove more flux toward GABA biosynthesis. The TCA cycle was reconstructed by increasing the expression of acn and icd genes and deleting the sucCD gene. Blocking GABA catabolism and rewiring the transport system of GABA further improved GABA production. An acetyl-CoA-dependent pathway for in vivo butyrolactam biosynthesis was constructed by overexpressing act-encoding ß-alanine CoA transferase. In fed-batch fermentation, the engineered strains produced 23.07 g/L of GABA with a yield of 0.52 mol/mol from glucose and 4.58 g/L of butyrolactam. The metabolic engineering strategies can be used for genetic modification of industrial strains to produce target chemicals from α-ketoglutarate as a precursor, and the engineered strains will be useful to synthesize the bio-based monomer of polyamide 4 from renewable resources.

The performance and durability of proton exchange fuel cells (PEMFCs) are greatly affected by the bipolar plate (BP). In this paper, the thermal and electrical conductivities and mechanical property of graphite filled with resin composite BPs were collectively enhanced through the effectively coupled manipulations of molding pressure and impregnation pressure. The microstructures show that the resin tends to distribute at the top region of the rib under high impregnation pressure. The thermal and electrical conductivities of the pure expanded graphite BP is well reserved in the composite BPs under high molding pressure, which can facilitate the heat transfer and electron conduction in the PEMFCs. The relative density and compressive strength of composite BPs were greatly enhanced by the impregnation of resin compared to the expanded graphite under high molding pressure without the impregnation of resin (HU-BP). The maximum thermal conductivity, compressive strength, and minimum interfacial contact resistance (ICR) are collectively achieved in the HL-BP. The enhanced thermal-electrical and mechanical properties could be mainly attributed to the well-reserved continuous networks of graphite in the composite BPs. The findings in this paper are expected to synergetically improve the thermal, electrical, and mechanical properties of composite BPs through coupled manipulations of the molding and impregnation pressures, which in turn enhances the power density and durability of PEMFCs.