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Seroma formation and poor wound healing are common complications of many surgeries that create anatomical dead space (i.e., mastectomy), often causing tissue infection and even necrosis. Although negative pressure drainage and tissue adhesives are investigated to alleviate fluid accumulation post-surgery, however, their therapeutic efficacy remains unsatisfactory in most cases. Herein, the catechol-rich chemically crosslinked gelatin microspheres (ca-CGMSs) have been developed as biodegradable reconstructive implants for preventing seroma formation and concurrently promoting subcutaneous wound healing. Compared with the most representative hydrogel adhesive, i.e. commercial porcine fibrin sealant (PFS), the loosely packed ca-CGMSs with diameters range from 50 to 350 μm, provide numerous cell-adhesive interfaces and interconnected macro-pores for enhanced cell adhesion, proliferation and migration. Subcutaneous embedding trials show the in situ swelling aggregation and wet tissue adhesion of ca-CGMSs as well as their capacity in recruiting autologous cells in rat mastectomy models. The trials in rabbit mastectomy models demonstrate that, compared with PFS gluing, the implanted dried ca-CGMSs not only significantly inhibit seroma formation, but also achieve enhanced wound healing by inducing the formation of vascularized neo-tissue. The ca-CGMSs show a great potential to be the next-generation of restorative materials for both preventing seroma formation and healing subcutaneous wounds.

With the rapid development of the economy and society, the demand for power quality is constantly increasing. As a crucial part of grid situational awareness, distribution network state estimation plays a vital role in providing critical data support for other advanced applications, which is significant for ensuring the safe and reliable operation of the distribution network. Therefore, this paper proposes a dynamic state awareness method for distribution networks based on the robust adaptive cubature Kalman filter (RACKF). The proposed solution, grounded on the core computational concept of the cubature Kalman filter (CKF), constructs a robust noise statistical estimator (NSE) composed of a biased NSE and an unbiased NSE to adapt to the unknown and time-varying process noise parameters in the dynamic state estimation process. The proposed solution can ensure that the calculated process noise parameters always meet the constraints and guarantee the robustness of the algorithm. In addition, an estimation strategy for the fusion of multi-time scale measurement data is developed according to the RACKF-based dynamic state estimation features in order to realize system state corrections and updates. The results of simulation experiments and comparisons with traditional CKF methods demonstrate the accuracy and superiority of the proposed solution.

BackgroundThe third-line treatment for refractory colorectal cancer (CRC) has limited efficacy. This study aimed to evaluate the safety and efficacy of SHR-8068 (an anti-CTLA-4 antibody), combined with adebrelimab (an anti-PD-L1 antibody), and bevacizumab in refractory non-microsatellite instability-high (MSI-H) or proficient mismatch repair (pMMR) CRC.MethodThis study is a prospective, open-label, single-center phase Ib/II clinical trial. Patients with pathologically confirmed pMMR/non-MSI-H metastatic colorectal adenocarcinoma who have failed ≥2 lines prior standard systemic treatments will be enrolled (n=36). The Ib phase will evaluate two dosing regimens of SHR-8068 in combination therapy (n=9 each dosage): SHR-8068 (1 mg per kilogram, every six weeks, intravenously) or SHR-8068 (4 mg per kilogram, every twelve weeks, intravenously) combined with adebrelimab (1200 mg, every three weeks, intravenously) and bevacizumab (7.5 mg per kilogram, every three weeks, intravenously). The efficacy and adverse events (AEs) of these regimens will be assessed to determine the recommended phase II dose (RP2D) of SHR-8068. Those of RP2D group from the phase Ib will be included in the phase II. The study will go to include 18 additional patients according to the one-sample log-rank test design in the phase II. The primary endpoint of the Ib phase is safety, with secondary endpoints including the objective response rate (ORR), progression-free survival (PFS), overall survival (OS), disease control rate (DCR), and quality of life (QOL). The primary endpoint for phase II was PFS, with secondary endpoints including ORR, OS, DCR, safety, and QOL. Identifying biomarkers to predict the efficacy of this regimen is the exploratory study endpoint.DiscussionThis proof-of-concept study would provide safety and efficacy signals of this novel combination treatment for the MSS CRCs in the late-line setting. And it may offer new insights on the clinical application of dual immunotherapy combined with anti-angiogenic therapy in the MSS CRC.

Abstract Hydrothermal carbonization (HTC) has been regarded as a promising technique for turning wet biomass into hydrochar due to its low energy consumption, low exhaust gas emissions, etc. In addition, hydrochar is an important source of dissolved organic matter (DOM), which plays a crucial part in the migration and destiny of pollutants in the environmental medium. However, there are limited studies that focus on the factors that influence the formation of DOM in hydrochar, such as hydrothermal temperature. Therefore, the current study comprehensively characterized the optical properties of DOM within hydrochar derived from sawdust (HDOM) under different hydrothermal temperatures (150–300 °C) by Ultraviolet–visible (UV–Vis) and fluorescence spectroscopy, as well as its complexation characteristic with Cu(II). The findings revealed that the organic carbon content of HDOM reached a peak of 37.3 mg L−1 when the temperature rose to 240 °C and then decreased as the temperature increased. UV–Vis spectroscopy analysis showed that the absorption capacity of HDOM at 275 nm increases with temperature and reaches a maximum value at 240 °C, indicating that high temperature promotes the formation of monocyclic aromatic compounds. High temperature enhances the aromaticity, hydrophobicity, and humification degree of HDOM, thus improving its stability and aromaticity. The E3/E4 ratios are all greater than 3.5, confirming that the main component of HDOM is fulvic acid, which corresponds to 3D-EEM and Pearson's correlation coefficient analysis. The humification index (HIX) of HDOM increased with the rise in hydrothermal temperature (150–240 °C), as observed by the three-dimensional excitation-emission matrix spectroscopy (3D-EEMs). After reaching its peak at 240 °C, the HIX value gradually dropped in line with the trend of the DOC change. Moreover, the bioavailability (BIX) value of DOM was all high and greater than 1, indicating all the HDOM are readily bioavailable. Two microbial humic substances (C1 and C4), a humic-like substance (C2), and a protein-like substance (C3) were discovered in DOM by integrating 3D-EEMs with parallel factor analysis (PARAFAC). Their fluorescence intensity decreases as the Cu(II) concentration increases, indicating the formation of complexes with Cu(II). As the temperature rises, the binding ability of DOM and Cu(II) changes significantly, reaching the optimum at 300 °C. Meanwhile, the substance C2 has the strongest binding ability with Cu(II). This research emphasizes the significance of spectroscopy analysis in determining the evolution of hydrochar-derived DOM, the potential for heavy metal binding and migration, and its characteristics and features. Graphical Abstract

Abstract Edge detection in images is a vital application of image processing in fields such as object detection and identification of lesion regions in medical images. This problem is more complex in the domain of color images due to the combination of color layer information and the need to achieve a unified edge boundary across these layers, which increases the complexity of the problem. In this paper, a simple and effective method for edge detection in color images is proposed using a combination of support vector machine (SVM) and the social spider optimization (SSO) algorithm. In the proposed method, the input color image is first converted to a grayscale image, and an initial estimation of the image edges is performed based on it. To this end, the proposed method utilizes an SVM with a Radial Basis Function (RBF) kernel, in which the model's hyperparameters are tuned using the SSO algorithm. After the formation of initial image edges, the resulting edges are compared with pairwise combinations of color layers, and an attempt is made to improve the edge localization using the SSO algorithm. In this step, the optimization algorithm's task is to refine the image edges in a way that maximizes the compatibility with pairwise combinations of color layers. This process leads to the formation of prominent image edges and reduces the adverse effects of noise on the final result. The performance of the proposed method in edge detection of various color images has been evaluated and compared with similar previous strategies. According to the obtained results, the proposed method can successfully identify image edges more accurately, as the edges identified by the proposed method have an average accuracy of 93.11% for the BSDS500 database, which is an increase of at least 0.74% compared to other methods.

Formic acid is regarded to be one of the most prospective hydrogen carriers. Effective screening of the fitting non-noble-metal-based heterogeneous catalysts to substitute the expensive noble-metal-based ones for FA dehydrogenation is considered as a key to the commercial application for hydrogen economics. Herein, dehydrogenation of liquid neat FA achieved a gas production value of 1753.5 mL/gcat./h at 94 °C by using a biomass-derived γ-Mo2N based catalyst synthesized from the earth-abundant molybdenum and soybean with a facile pyrolysis process. The effect of material ratio, pyrolysis temperature on the catalytic performance of FA dehydrogenation were studied in details. In particular, the catalyst obtained at a pyrolysis temperature of 700 °C, weight ratios of ammonium molybdate to soybean of 0.2/1 exhibited the highest activity. In addition, the catalytic activity increased with the increase of FA concentration, but conversely, the dehydrogenation selectivity decreased with the increasing FA concentration. Moreover, it was found that the Bio-Mo2N catalyst was rather stable over the 40 h continuous reaction period.

The classification of garbage types is an important issue in today's world, and its proper implementation can contribute to environmental conservation and improved efficiency of recycling processes. Unfortunately, the classification of garbage types is currently predominantly performed through human supervision, which leads to high errors and environmental risks. It is crucial to automate this procedure utilizing machine vision methods as a result. This research proposes a revolutionary deep learning-based strategy for classifying domestic waste. The suggested method uses deep learning methods to extract information from images. The Capuchin Search Algorithm (CapSA) is used to improve the hyperparameters of the convolutional neural network (CNN) used as the feature extraction model. Furthermore, for categorizing the retrieved features from the CNN model, a hybrid learning model based on Error-Correcting Output Codes (ECOC) and Artificial Neural Networks (ANN) is used. The classification accuracy may be successfully increased by using this hybrid model, and the benefit becomes more pronounced as the number of target categories rises. The TrashNet and HGCD databases were used to assess the suggested method's effectiveness, and its results in waste type detection were contrasted with those of earlier techniques. Based on the study findings, the suggested approach can identify trash types with an accuracy of 98.81 % and 99.01 % on the TrashNet and HGCD databases, respectively. This is at least a 1.46 % improvement over earlier approaches. The study's conclusions validate that the suggested strategy may be used in real-world scenarios and show how successful the approaches used in it are.

Abstract Motion recognition (MR)‐based somatosensory interaction technology, which interprets user movements as input instructions, presents a natural approach for promoting human‐computer interaction, a critical element for advancing metaverse applications. Herein, this work introduces a non‐intrusive muscle‐sensing wearable device, that in conjunction with machine learning, enables motion‐control‐based somatosensory interaction with metaverse avatars. To facilitate MR, the proposed device simultaneously detects muscle mechanical activities, including dynamic muscle shape changes and vibrational mechanomyogram signals, utilizing a flexible 16‐channel pressure sensor array (weighing ≈0.38 g). Leveraging the rich information from multiple channels, a recognition accuracy of ≈96.06% is achieved by classifying ten lower‐limb motions executed by ten human subjects. In addition, this work demonstrates the practical application of muscle‐sensing‐based somatosensory interaction, using the proposed wearable device, for enabling the real‐time control of avatars in a virtual space. This study provides an alternative approach to traditional rigid inertial measurement units and electromyography‐based methods for achieving accurate human motion capture, which can further broaden the applications of motion‐interactive wearable devices for the coming metaverse age.

With the boom in artificial intelligence (AI), numerous reconfigurable convolution neural network (CNN) accelerators have emerged within both industry and academia, aiming to enhance AI computing capabilities. However, this rapid landscape has also witnessed a rise in hardware Trojan attacks targeted at CNN accelerators, thereby posing substantial threats to the reliability and security of these reconfigurable systems. Despite this escalating concern, there exists a scarcity of security protection schemes explicitly tailored to counteract hardware Trojans embedded in reconfigurable CNN accelerators, and those that do exist exhibit notable deficiencies. Addressing these gaps, this paper introduces a dedicated security scheme designed to mitigate the vulnerabilities associated with hardware Trojans implanted in reconfigurable CNN accelerators. The proposed security protection scheme operates at two distinct levels: the first level is geared towards preventing the triggering of the hardware Trojan, while the second level focuses on detecting the presence of a hardware Trojan post-triggering and subsequently neutralizing its potential harm. Through experimental evaluation, our results demonstrate that this two-level protection scheme is capable of mitigating at least 99.88% of the harm cause by three different types of hardware Trojan (i.e., Trojan within RI, MAC and ReLU) within reconfigurable CNN accelerators. Furthermore, this scheme can prevent hardware Trojans from triggering whose trigger signal is derived from a processing element (PE). Notably, the proposed scheme is implemented and validated on a Xilinx Zynq XC7Z100 platform.

The dynamic characteristics of single DNA molecules translocating within micro/nano-channels are fundamental for a wide range of applications such as stretching, separating, mapping, and even sequencing of DNA molecules. In this study, a type of tapered microchannel chip with uniform height for all configurations was fabricated, with the major tapered structure having a length of 13 μm and a width that tapers from 5 μm to 20 μm. The dynamic characteristics such as the trajectories and velocities of λ-DNA molecules translocating from different positions driven by an external DC electric field force were systematically investigated by single-molecule fluorescence imaging technology. Some dynamic characteristics of DNA molecules translocation were found. Considering simply the effects of electrophoretic force and electro-osmotic force on the DNA molecules, the dynamic characteristics of DNA molecules are well understood. For example, the velocity of the DNA molecule is inversely proportional to the diameter of the tapered channel and the turning phenomena of the trajectory of the DNA molecules translocating through microchannels. This study is helpful and proposes new ideas for the design and development of microfluidic chips for the quantitative manipulation of DNA molecules.

ABSTRACTLignocellulolytic enzymes play an important role in various industrial applications as well as the sustainable valorisation of lignocellulosic materials. Enzyme production using lignocellulosic fungi has shown great advantages such as high enzyme diversity, high production efficiency, and the availability of solid waste as raw materials. Agricultural waste, an abundant and non-food competitive feedstock, can be used to produce fungal lignocellulolytic enzymes. Pretreatment helps break down the complex structure of the raw material, thereby significantly improving product yield but also requiring more energy consumption. Multiple fermentation technologies, including submerged fermentation, solid-state fermentation, and co-culture, can be used for producing lignocellulolytic enzymes. Process optimisation may promote the yield and productivity of such enzymes without additional investment. Genetic engineering is also useful for enhancing enzyme production to meet industrial requirements. This review summarises the research progress in the fungal production of lignocellulolytic enzymes from various agricultural wastes via advanced fermentation strategies. It aims to provide technical references for the scale-up production of fungal lignocellulolytic enzymes.

In this study, thermoplastic starch (TPS) was prepared by melt extrusion process, in which glycerol and/or D-mannitol were used as plasticizers, and the effect of different glycerol/D-mannitol ratios (4:0, 3:1, 2:2, 1:3, and 0:4) on the physicochemical properties of the extruded starch samples was investigated. The short-range molecular order, crystallization, gelatinization, thermal stability, and thermal properties of the TPS samples were analyzed through attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray diffraction (XRD), rapid visco analysis (RVA), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). The results showed that the crystallinity and short-range molecular order of the TPS samples increased with increasing glycerol content. Conversely, the water absorption index (WAI) and water solubility index (WSI) of the TPS samples decreased with increasing glycerol content. In addition, the TPS samples with higher glycerol content exhibited higher gel and thermal stabilities. This study provides a theoretical basis for starch extrusion and plasticization in the preparation of TPS-based materials with specific properties.

This study focused on the detection of water inrush in tunnels excavated by full-section hard rock tunnel boring machines (TBMs) and employed ground penetrating radar methods for conducting research on radar signal processing algorithms. The research demonstrates that conventional techniques are inadequate for eliminating the interference of TBM equipment on radar signal propagation. This study employs a radar antenna array method for signal transmission, utilizing a wavelet double-threshold filtering algorithm and wave propagation theory to suppress clutter. These methods exhibit strong signal reception capabilities and are effective in eliminating 13.1% of the direct wave components. The adoption of a novel, efficient radar signal imaging algorithm simplifies the imaging process. Results of verification indicate that the synthetic aperture algorithm, enhanced with cross-correlation calculation, yields the optimal imaging effect. This investigation, which was conducted in conjunction with the construction of a diversion tunnel in a specific region, has confirmed the applicability of the ground penetrating radar method for the detection of water inrush in TBM tunnels by conducting a comparative analysis of the direct wave removal algorithm and the integration of the optimal imaging algorithm. The innovative application of ground penetrating radar within TBM tunnels, along with a targeted technology to mitigate signal interference from metal equipment, has led to the selection of an appropriate algorithm for both signal processing and imaging. This approach offers a novel solution for the detection of water source disasters in TBM tunnels.

In order to reduce costs, compress space, and improve system stability under harsh operating conditions, the current vehicle motor drive systems often use position sensorless control methods. However, due to the introduction of filters and the hysteresis of position observers, the position sensorless control has the problem of deteriorating dynamic performance when vehicles start from zero and low speeds or their loads change. Therefore, this article focuses on the problem of position sensorless control applied by permanent magnet synchronous motors when vehicles start and operate at zero and low speed. Combined with high-frequency pulse vibration injection method, the relationship between the types of position observers, parameter selection, and position tracking performance is analyzed and compared. The short-pulse injection method is proposed to locate the initial position of the motor, overcoming the inherent 180° position deviation of pulse vibration high-frequency injections. Subsequently, the impact of the amplitude and frequency of the injected high-frequency signal on the performance of position estimation is focused on. Considering the adverse effects caused by the phase delay of the filter, a design method for filter parameters is proposed to achieve a smooth start and operation of the permanent magnet synchronous motor under position sensorless control. Finally, the rationality of the theoretical analysis and the effectiveness of the adopted methods are fully verified through simulation and experiments.

Abstract Background Ammonium (NH4 +) is a key nitrogen source supporting plant growth and development. Proteins in the ammonium transporter (AMT) family mediate the movement of NH4 + across the cell membrane. Although several studies have examined AMT genes in various plant species, few studies of the AMT gene family have been conducted in chili pepper. Results Here, a total of eight AMT genes were identified in chili pepper, and their exon/intron structures, phylogenetic relationships, and expression patterns in response to arbuscular mycorrhizal (AM) colonization were explored. Synteny analyses among chili pepper, tomato, eggplant, soybean, and Medicago revealed that the CaAMT2;1, CaAMT2.4, and CaAMT3;1 have undergone an expansion prior to the divergence of Solanaceae and Leguminosae. The expression of six AMT2 genes was either up-regulated or down-regulated in response to AM colonization. The expression of CaAMT2;1/2;2/2;3 and SlAMT2;1/2;2/2;3 was significantly up-regulated in AM fungi-inoculated roots. A 1,112-bp CaAMT2;1 promoter fragment and a 1,400-bp CaAMT2;2 promoter fragment drove the expression of the β-glucuronidase gene in the cortex of AM roots. Evaluation of AM colonization under different NH4 + concentrations revealed that a sufficient, but not excessive, supply of NH4 + promotes the growth of chili pepper and the colonization of AM. Furthermore, we demonstrated that CaAMT2;2 overexpression could mediate NH4 + uptake in tomato plants. Conclusion In sum, our results provide new insights into the evolutionary relationships and functional divergence of chili pepper AMT genes. We also identified putative AMT genes expressed in AM symbiotic roots.

This study aimed to investigate the effects of dietary corn-resistant starch on the bile acid metabolism of broilers. In total, 80, 1-day-old male broilers were randomly distributed into two groups fed either the basic normal corn–soybean diet or a diet supplemented with 40 g/kg of corn-resistant starch. The results showed that dietary supplementation of 4% corn-resistant starch increased the F/G during the periods from 21 to 42 d. Resistant starch supplementation reduced the lipid levels in plasma, and the contents of total bile acids were increased with the altered bile acid profile in the ileum. A diet with corn resistant starch decreased the enzyme contents of the classical pathway of bile acid synthesis and activated the signaling pathway of FXR/LRH-1 in the liver. A decreased abundance of Clostridium cluster XIVa was found in the ileal digesta of the resistant starch group, and its abundance was negatively correlated with the level of lithocholic acid. In summary, the RS was effective at reducing broiler plasma and liver lipid levels, which was probably due to the change in bile acid synthesis and reabsorption capacities. These findings provided a unique landscape of the relationship between bile acid metabolism and resistant starch in broilers.

Artificial intelligence is changing and influencing our world. As one of the main algorithms in the field of artificial intelligence, convolutional neural networks (CNNs) have developed rapidly in recent years. Especially after the emergence of NASNet, CNNs have gradually pushed the idea of AutoML to the public’s attention, and large numbers of new structures designed by automatic searches are appearing. These networks are usually based on reinforcement learning and evolutionary learning algorithms. However, sometimes, the blocks of these networks are complex, and there is no small model for simpler tasks. Therefore, this paper proposes POSS-CNN aiming at target recognition and detection, which employs a multi-branch CNN structure with PSNC and a method of automatic parallel selection for super parameters based on a multi-branch CNN structure. Moreover, POSS-CNN can be broken up. By choosing a single branch or the combination of two branches as the “benchmark”, as well as the overall POSS-CNN, we can achieve seven models with different precision and operations. The test accuracy of POSS-CNN for a recognition task tested on a CIFAR10 dataset can reach 86.4%, which is equivalent to AlexNet and VggNet, but the operation and parameters of the whole model in this paper are 45.9% and 45.8% of AlexNet, and 29.5% and 29.4% of VggNet. The mAP of POSS-CNN for a detection task tested on the LSVH dataset is 45.8, inferior to the 62.3 of YOLOv3. However, compared with YOLOv3, the operation and parameters of the model in this paper are reduced by 57.4% and 15.6%, respectively. After being accelerated by WRA, POSS-CNN for a detection task tested on an LSVH dataset can achieve 27 fps, and the energy efficiency is 0.42 J/f, which is 5 times and 96.6 times better than GPU 2080Ti in performance and energy efficiency, respectively.

Accurately evaluating the interaction and stability of the landslide tunnel and formulating a reasonable disaster prevention plan are of great significance for ensuring the smooth completion of the Shangri-La to Lijiang highway. This paper takes the typical landslide-tunnel disaster site of Shangri-La to Lijiang highway-Changgeluo landslideas an example, uses on-site engineering geological surveys, drilling, and other methods to determine the cause mechanism and deformation characteristics of the landslide, utilizes numerical simulation to study the spatial stress-strain characteristics and stability state of the Changgeluo landslide under natural, rainfall and tunnel excavation conditions, studies the interaction between the landslide and the tunnel, and proposes corresponding disaster prevention and control plans. The results show that the Changgeluo landslide is a giant rock sliding landslide, which is in an unstable state under natural conditions. The tunnel excavation has limited influence on the overall stability of the landslide, but it will cause local deformation of the landslide.Affected by the deformation of the landslide body, the tunnel part of the landslide body will produce tensile-shear deformation failure. Rainfall seriously deteriorates the stability of the landslide, causing the landslide to lose instability and further causing the tunnel to fail and be destroyed. The original route selection plan faces huge risks, and the optimal prevention plan is to move the route eastward to avoid the tunnel so that the tunnel passes under the sliding surface. The research methods and results can provide a useful reference for similar Shangri-La to Lijiang highway disaster sites.

BackgroundGALAD model is a statistical model used to estimate the possibility of hepatocellular carcinoma (HCC) in patients with chronic liver disease. Many studies with other ethnic populations have shown that it has high sensitivity and specificity. However, whether this model can be used for Chinese patients remains to be determined. Our study was conducted to verify the performance of GALAD model in a Chinese cohort and construct a new model that is more appropriately for Chinese populations.MethodsThere are total 512 patients enrolled in the study, which can be divided into training set and validation set. 80 patients with primary liver cancer, 139 patients with chronic liver disease and 87 healthy people were included in the training set. Through the ROC(receiver operating characteristic) curve analysis, the recognition performance of GALAD model for liver cancer was evaluated, and the GAADPB model was established by logistic regression, including gender, age, AFP, DCP, total protein, and total bilirubin. The validation set (75 HCC patients and 130 CLD patients) was used to evaluate the performance of the GAADPB model.ResultThe GALAD and GAADPB achieved excellent performance (area under the receiver operating characteristic curve [AUC], 0.925, 0.945), and were better than GAAP, Doylestown, BALAD-2, aMAP, AFP, AFP-L3%, DCP and combined detection of AFP, AFP-L3 and DCP (AUCs: 0.894, 0.870, 0.648, 0.545, 0.879, 0.782, 0.820 and 0.911) for detecting HCC from CLD in the training set. As for early stage of HCC (BCLC 0/A), GAADPB had the best sensitivity compared to GALAD, ADP and DCP (56.3%, 53.1%, 40.6%, 50.0%). GAADPB had better performance than GALAD in the test set, AUC (0.896 vs 0.888).ConclusionsThe new GAADPB model was powerful and stable, with better performance than the GALAD and other models, and it also was promising in the area of HCC prognosis prediction. Further study on the real-world HCC patients in China are needed.

This study explored the effect of the long-term partial replacement of chemical fertilizer with organic fertilizer on soil organic carbon composition, enzyme activity, and crop yields in the wheat–maize rotation area of northern Anhui, China. This study also specified the proper amount of organic fertilizer replacement that should be used for chemical fertilizer. Different fertilization modes were used (no fertilization, CK; chemical fertilizer, CF; chemical fertilizer and straw returning, CF + S; chemical fertilizer, straw returning, and straw decomposition agent, CF + S + DA; 70% chemical fertilizer and 50% organic fertilizer, 70% CF + 50% OF; 70% chemical fertilizer, 50% organic fertilizer and straw returning, 70% CF + 50% OF + S; 50% chemical fertilizer and 100% organic fertilizer, 50% CF + 100% OF; and 50% chemical fertilizer, 100% organic fertilizer, and straw returning, 50% CF + 100% OF + S). Variations in the organic carbon composition, enzyme activity, soil pH, and crop yields in the wheat–maize rotation under different fertilization treatments were analyzed. The results showed that the replacement of chemical fertilizer with organic fertilizer results in improved crop yields in wheat–maize rotation. The long-term partial replacement of chemical fertilizer with organic fertilizer can increase the quality of soil humus, alleviate soil acidification, and improve soil enzyme activity. Straw returning and organic fertilizer application can considerably raise the activities of urease, acid phosphatase, and nitrate reductase in soil. The soil pH of the CF treatment was reduced compared to the CK treatment, while organic fertilizer application alleviated soil acidification when compared to CF treatment. Organic fertilization increases the total organic carbon content of the soil, which was 19.6~85.5% higher than in the CK treatment. Applying straw and organic fertilizer significantly increased the ratio of the humic/fulvic acid in the soil. The soil active carbon forms of the soil with the application of organic fertilizer and straw returning were significantly higher than those of the CK and CF treatments. This study suggests that the optimal fertilizer management option in northern Anhui’s wheat–maize rotation area is to replace 50% of the chemical fertilizer with organic fertilizer, and to fully return straw to the field. This would include 150 kg N h·m−2, 60 kg P2O5 h·m−2, 50 kg K2O h·m−2, 6000 kg organic fertilizer h·m−2, and full straw return to the field.

This study was designed to investigate the effect on wheat yield of applying organic fertilizers (OF) with five different selenium (Se) concentrations. The mineral nutrients, cadmium (Cd) content, and the distribution of Se in wheat plants were also measured. The results showed that wheat yields reached a maximum of 9979.78 kg ha−1 in Mengcheng (MC) County and 8868.97 kg ha−1 in Dingyuan (DY) County, Anhui Province, China when the application amount of selenium-containing organic fertilizer (SOF) was up to 600 kg ha−1. Among the six mineral nutrients measured, only the calcium (Ca) content of the grains significantly increased with an increase in the application amount of SOF in the two regions under study. Cd content showed antagonistic effects with the Se content of wheat grains, and when the SOF was applied at 1200 kg ha−1, the Cd content of the grains was significantly reduced by 30.1% in MC and 67.3% in DY, compared with under the Se0 treatment. After application of SOF, the Se content of different parts of the wheat plant ranked root > grain > spike-stalk > glume > leaf > stem. In summary, SOF application at a suitable concentration could increase wheat yields and significantly promote the Ca content of the grains. Meanwhile, the addition of Se effectively inhibited the level of toxic Cd in the wheat grains.

Lactic acid plays an important role in industrial applications ranging from the food industry to life sciences. The growing demand for lactic acid creates an urgent need to find economical and sustainable substrates for lactic acid production. Agricultural waste is rich in nutrients needed for microbial growth. Fermentative production of lactic acid from non-food-competing agricultural waste could reduce the cost of lactic acid production while addressing environmental concerns. This work provided an overview of lactic acid fermentation from different agricultural wastes. Although conventional fermentation approaches have been widely applied for decades, there are ongoing efforts toward enhanced lactic acid fermentation to meet the requirements of industrial productions and applications. In addition, agricultural waste contains a large proportion of pentose sugars. Most lactic-acid-producing microorganisms cannot utilize such reducing sugars. Therefore, advanced fermentation techniques are also discussed specifically for using agricultural waste feedstocks. This review provides valuable references and technical supports for the industrialization of lactic acid production from renewable materials.

In the era of big data, a significant volume of spatiotemporal data exists in a multiscale format, describing diverse phenomena in the objective world across different spatial and temporal scales. While existing methods focus on analyzing the features and connections of spatiotemporal data at various scales, they often overlook the consideration of uncertainty in spatiotemporal information within the context of multiscale meaning. To effectively harness the potential of spatiotemporal data, it becomes crucial to capture the fuzzy spatiotemporal information inherent in multiscale datasets. This paper proposes a novel multiscale spatiotemporal correlation method that accounts for and quantifies the uncertainty of spatiotemporal information. Spatiotemporal information is categorized into two types, explicit information and implicit information, based on respective levels of uncertainty. The method employs spatiotemporal cubes to interpret the spatiotemporal items within the data, followed by the introduction of a benchmark scale to determine the certainty of each spatiotemporal item based on its range and topological relationships. Subsequently, spatiotemporal confidence and correlation index are proposed to gauge the significance of geographical elements and their interrelationships. To validate the proposed method, a multiscale spatiotemporal transaction dataset is generated and utilized in the experiment. The experimental results demonstrate that the proposed method effectively captures spatiotemporal implicit information and enables better utilization of multiscale spatiotemporal data. Notably, the importance of each object of study varies when analyzed using different benchmark scales, providing valuable insights for professionals to identify novel objects and associations worthy of consideration. The obtained results can be used to construct spatiotemporal knowledge graphs.

Seismic intensity (SI) is an important reference index for understanding disaster situations, establishing emergency rescue plans and performing loss assessments after an earthquake. In this paper, we investigated the feasibility of assessing SI through interferometric synthetic aperture radar (InSAR) data after the Wenchuan earthquake on May 12, 2008, in China. The proposed approach relies on pre-existing residential data to obtain the regional seismic deformation corresponding to blocks. Theoretical maximum and minimum values analysis was carried out according to seismic attenuation relationships, and the deformation points were classified using Jenks natural breakpoints. The deformation field data were used to evaluate the epicenter and periphery areas. Instrument-based intensity values of stations were included in our analysis and used to investigate the periphery of the study area. Classification results of deformation field and instrument-based intensity values were combined to form a complete deformation field. The effectiveness of the method was verified based on a case study of the Yushu earthquake, another severe earthquake in China.The work represents one of the first attempts to establish the potential relationship between the seismic deformation field and intensity in China, validated against ground survey data. This study addresses methodological aspects, highlighting the potential of the co-seismic deformation field for intensity assessment, and discusses the limitations of terrain and data in this approach compared to ground surveys.

Abstract The effects of NaCl, Na2SO4, Na2HPO4, and Na3C6H5O7 on the production of 3-hydroxybutyrate, polyhydroxybutyrate, and by-products by Burkholderia cepacia. Proper addition of Na3C6H5O7 can significantly promote the production of 3-hydroxybutyric acid and polyhydroxybutyrate. The concentration, productivity, and yield of 3-hydroxybutyrate were increased by 48.2%, 55.6%, and 48.3% at 16 mM Na3C6H5O7. The increases of 80.1%, 47.1%, and 80.0% in the concentration, productivity, and yield of polyhydroxybutyrate were observed at 12 mM Na3C6H5O7. Na2SO4 and Na2HPO4 also have positive effects on the production capacity of 3-hydroxybutyrate and polyhydroxybutyrate within a certain range of concentration. NaCl is not conducive to the improvement of fermentation efficiency. Compared with a single nitrogen source, a mixed nitrogen source is more conducive to enhancing the production of 3-hydroxybutyrate and polyhydroxybutyrate.

Abstract Under the optimal conditions of immobilization and fermentation, the highest LA yield of 0.966 ± 0.006 g/g fructose and production rate of 2.426 ± 0.018 g/(L × h) with an error of -0.5% and -0.2% to the predicted results were obtained from batch fermentation by the CS film-coated SA-PVA immobilized L. pentosus cells. The LA yield and production rate of these immobilized cells were 2.7% and 10.1% higher than that of normal SA-PVA immobilized cells respectively, and they were 5.7% and 48.4% higher than that of free cells, respectively. The effect of temperature on different types of immobilized cells and free cells was significantly different, but the effect of pH on different types of cells was not much different. The kinetic models could effectively describe the different fermentation performances of three types of cells. The immobilized cells have excellent reusability to conduct 9 runs of repeated batch fermentation.

We have conducted a study on a very-low-frequency acoustic-velocity sensor which is based on a cantilever of distributed-feedback (DFB) fiber laser immersed in castor oil. A mathematical model of the frequency dependent response of the proposed sensor to the acoustic pressure signal influenced by the fluid viscosity is established. We have fabricated the proposed sensor and conducted experimental measurements in the standing wave tube. The results show that the sensor has an average phase sensitivity of −179.5 dB (0 dB = 1 rad/μPa) with ±1.45 dB fluctuation over the frequency range of 20–38 Hz. It has good cosine directivity with a directivity index of 32.5 dB and axial maximum asymmetry of 0.4 dB. The sensor presents promising applications for detecting very-low-frequency underwater acoustic signals.

Abstract Fiber-optic hydrophone (FOH) is a significant type of acoustic sensor, which can be used in both military and civilian fields such as underwater target detection, oil and natural gas prospecting, and earthquake inspection. The recent progress of FOH is introduced from five aspects, including large-scale FOH array, very-low-frequency detection, fiber-optic vector hydrophone (FOVH), towed linear array, and deep-sea and long-haul transmission. The above five aspects indicate the future development trends in the FOH research field, and they also provide a guideline for the practical applications of FOH as well as its array.

Rice blast, caused by Magnaporthe oryzae, is one of the most devastating diseases in rice and can affect rice production worldwide. Rice plasma membrane (PM) proteins are crucial for rapidly and precisely establishing a defense response in plant immunity when rice and blast fungi interact. However, the plant-immunity-associated vesicle trafficking network mediated by PM proteins is poorly understood. In this study, to explore changes in PM proteins during M. oryzae infection, the PM proteome was analyzed via iTRAQ in the resistant rice landrace Heikezijing. A total of 831 differentially expressed proteins (DEPs) were identified, including 434 upregulated and 397 downregulated DEPs. In functional analyses, DEPs associated with vesicle trafficking were significantly enriched, including the “transport” term in a Gene Ontology enrichment analysis, the endocytosis and phagosome pathways in a Encyclopedia of Genes and Genomes analysis, and vesicle-associated proteins identified via a protein–protein interaction network analysis. OsNPSN13, a novel plant-specific soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) 13 protein, was identified as an upregulated DEP, and transgenic plants overexpressing this gene showed enhanced blast resistance, while transgenic knockdown plants were more susceptible than wild-type plants. The changes in abundance and putative functions of 20 DEPs revealed a possible vesicle trafficking network in the M. oryzae-rice interaction. A comparative proteomic analysis of plasma membrane proteins in rice leaves revealed a plant-immunity-associated vesicle trafficking network that is provoked by blast fungi; these results provide new insights into rice resistance responses against rice blast fungi.

Abstract Parametric optimization is an effective way in fermentation process to improve product yield and productivity in order to save time, space and financial resources. In this study, Box–Behnken design was applied to optimize the conditions for lactic acid production by immobilized Lactobacillus pentosus ATCC 8041 cell fermentation. Two quadratic models and response surface methodology were performed to illustrate the effect of each parameters and their interactions on the lactic acid yield and glucose consumption rate in immobilized L. pentosus ATCC 8041 cell fermentation. The maximum lactic acid yield was obtained as 0.938 ± 0.003 g/g glucose with a productivity of 2.213 ± 0.008 g/(L × h) under the optimized conditions of 2.0 mm bead diameter, 5.60 pH, 115.3 g/L initial glucose concentration, and 398.2 mg biomass (CDW) in 100 mL hydrogel. The analysis of variance indicated that the quadratic model was significant and could be used to scale up the fermentation process.

Recent studies have indicated that prostate cancer (PCa) with BRCA2 mutations is more aggressive. However, these reports mostly focused on Caucasus populations, and large-scale studies on BRCA mutations in Chinese PCa populations remain limited. Herein, we screened, from multiple centers in China, a total of 172 patients with PCa carrying BRCA1/2 germline mutations. The variant distribution and type, associated somatic variant, and frequency of the BRCA germline variants in these patients were analyzed retrospectively. We found that Chinese patients with PCa carrying BRCA1/2 germline mutations were diagnosed at an earlier age, i.e., 67 years (range, 34–89 years), and most had metastatic castration-resistant PCa (mCRPC) (54.65%, 94/172). The top three BRCA variants were frameshift, missense, and splicing variants. The overall pathogenic rates of the BRCA1 and BRCA2 variants were 17.46% (11/63) and 56.55% (82/145), respectively. Among the somatic mutations associated with BRCA2 germline mutations, the highest frequency was for FOXA1 (circulating tumor DNA [ctDNA] sequencing, 7.4%; tissue samples, 52%) and NCOR2 mutations (ctDNA sequencing, 7.4%; tissue samples, 24%); TP53 was the dominant somatic mutation associated with BRCA1 germline mutations (ctDNA sequencing, 25%; tissue samples, 17%). Ultimately, in Chinese patients, PCa with BRCA1/2 germline mutations tends to be more aggressive. Compared with BRCA1, BRCA2 has a higher frequency of germline pathogenic mutations. FOXA1, NCOR2, and TP53 somatic mutations associated with higher BRCA1/2 germline pathogenic mutations. Our description of BRCA germline mutations in the Chinese PCa patients provides more reference data for the precise diagnosis and treatment of Chinese PCa patients.

Immune composition is commonly heterogeneous and varies among colorectal cancer (CRC) patients. A comprehensive immune classification may act as important characteristics to predict CRC prognosis. Thus, we aimed to identify novel immune specific subtypes to guide future therapies. Unsupervised clustering was used to classify CRC samples into different immune subtypes based on abundances of immune cell populations, during which TCGA and GSE17536 datasets were used as training and validation sets, respectively. The associations between the immune subtypes and patient prognosis were investigated. Further, we identified differentially expressed genes (DEGs) between immune high and low subtypes, followed by functional enrichment analyses of DEGs. The expression levels of 74 immunomodulators (IMs) across immune subtypes were analyzed. As a result, we clustered CRC samples into three distinct immune subtypes (immune high, moderate, and low). Patients with immune-high subtype showed the best prognosis, and patients with immune-low subtype had the worst survival in both TCGA and GSE17536 cohorts. A group of 2735 up-regulated DEGs were identified across immune high and low subtypes. The main DEGs were the members of complement components, chemokines, immunoglobulins, and immunosuppressive genes that are involved in immune modulation-related pathways (e.g., cytokine-cytokine receptor interaction) or GO terms (e.g., adaptive immune response and T cell activation). The expression levels of 63 IMs were significantly varied across immune subtypes. In conclusion, this study provides a conceptual framework and molecular characteristics of CRC immune subtypes, which may accurately predict prognosis and offer novel targets for personalized immunotherapy through modifying subtype-specific tumor immune microenvironment.

To understand the complex phenomena in social space and monitor the dynamic changes in people’s tracks, we need more cross-scale data. However, when we retrieve data, we often ignore the impact of multi-scale, resulting in incomplete results. To solve this problem, we proposed a management method of multi-granularity dimensions for spatiotemporal data. This method systematically described dimension granularity and the fuzzy caused by dimension granularity, and used multi-scale integer coding technology to organize and manage multi-granularity dimensions, and realized the integrity of the data query results according to the correlation between the different scale codes. We simulated the time and band data for the experiment. The experimental results showed that: (1) this method effectively solves the problem of incomplete query results of the intersection query method. (2) Compared with traditional string encoding, the query efficiency of multiscale integer encoding is twice as high. (3) The proportion of different dimension granularity has an impact on the query effect of multi-scale integer coding. When the proportion of fine-grained data is high, the advantage of multi-scale integer coding is greater.

Nanomaterial-based flexible sensors (NMFSs) can be tightly attached to the human skin or integrated with clothing to monitor human physiological information, provide medical data, or explore metaverse spaces. Nanomaterials have been widely incorporated into flexible sensors due to their facile processing, material compatibility, and unique properties. This review highlights the recent advancements in NMFSs involving various nanomaterial frameworks such as nanoparticles, nanowires, and nanofilms. Different triggering interaction interfaces between NMFSs and metaverse/virtual reality (VR) applications, e.g. skin-mechanics-triggered, temperature-triggered, magnetically triggered, and neural-triggered interfaces, are discussed. In the context of interfacing physical and virtual worlds, machine learning (ML) has emerged as a promising tool for processing sensor data for controlling avatars in metaverse/VR worlds, and many ML algorithms have been proposed for virtual interaction technologies. This paper discusses the advantages, disadvantages, and prospects of NMFSs in metaverse/VR applications.

BackgroundMounting studies have sought to identify novel mutation biomarkers having diagnostic and prognostic potentials. Nevertheless, the understanding of the mutated pathways related to development and prognosis of B-cell lymphoma is still lacking. We aimed to comprehensively analyze the mutation alterations in genes of canonical signaling pathways and their impacts on the clinic outcomes of patients with B-cell lymphoma.MethodsCirculating cell-free DNA (cfDNA) samples from 79 patients with B-cell lymphomas were used for targeted sequencing with a 560-gene panel for depicting mutation landscapes and identifying gene fusion events. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of mutated genes were performed. The associations of mutation status of genes and seven canonical oncogenic pathways with progression-free survival (PFS) were assessed using Kaplan-Meier test and multivariate Cox analysis. The variant allele frequencies (VAFs) of genes in TP53 and Hippo pathways in paired baseline and post-treatment samples from 18 B-cell lymphoma patients were compared. Finally, the associations of identified fusion genes, mutated genes, and pathways with treatment response were evaluated based on objective response rates (ORRs) comparisons of groups.ResultsWe identified 666 mutations from 262 genes in baseline cfDNAs from 79 B-cell lymphoma patients, and found some genes were preferentially mutated in our cohort such as GNAQ, GNAS, H3F3A, DNMT3A, HLA-A, and HLA-B. These frequently mutated genes were significantly associated with negative “regulation of gene expression, epigenetic” and virus infections such as cytomegalovirus, Epstein-Barr virus, human immunodeficiency virus 1 infections. We detected five fusion genes in at least two patients with B-cell lymphoma, and among them, TCF7L2_WT1 gene fusion was most frequently detected in 30.4% of patients (24 of 79 cases). SEPT6_TRIM33 gene fusion, mutated TP53 and Hippo pathways were significantly associated with poor PFS, and SEPT6_TRIM33 fusion gene and mutated TP53 pathway were independent prognostic factors for B-cell lymphoma. A decreased VAF of TP53 p.Y88C and LATS2 p.F972L was detected in patients with complete response to treatments. Moreover, a significant difference in ORR was observed in patients with NPM1_NR4A3 and SEPT6_TRIM33 fusions.ConclusionsSEPT6_TRIM33 gene fusion and mutated TP53 and Hippo pathways may serve as prognostic makers for B-cell lymphoma patients.

The two-stage suspension system (TSSS) is designed for the fiber optic vector hydrophone (FOVH) to isolate the vibration from the mooring rope. The acceleration transmissibility of the TSSS is studied theoretically and experimentally. The results show that the TSSS has a major advantage over the traditional one-stage suspension system (OSSS). Typically, the vibration isolation of the TSSS is demonstrated to be over 25 dB higher than that of the OSSS at 100 Hz. Meanwhile, it is demonstrated that the TSSS has little negative influence on the in-band acceleration response of the FOVH. The TSSS has the prospect of reducing the mechanical noise of the FOVH, which is conducive to suppressing the self-noise and enhancing the ability of weak signal detection.

Cholestasis is a clinical condition resulting from impaired bile flow. Currently, patients with cholestasis face several barriers in seeking diagnosis and treatment. Zhuyu Pill (ZYP) is an ancient classic formula of the Coptis-Evodia herb couples (CEHC), and has been used for cholestasis treatment in the clinic, however, its underlying biological activity in cholestasis remain to be clarified. In this study, an α-naphthyl-isothiocyanate (ANIT, 50 mg/kg)-induced rat model of cholestasis was treated with ZYP. Serum biochemical indices and histopathological evaluation was performed, together with the metabolomics analyses of feces and 16S rDNA sequencing of the fecal microbiota. We evaluated the anti-cholestatic activity of ZYP and investigated the mechanisms underlying its correlation with fecal microbiota and fecal metabolite regulation. The relationships between biochemical indices and changes in gene expression associated with liver injury, levels fecal metabolites, and composition of fecal microbiota were analyzed. The results showed that both high (1.2 g/kg) and low (0.6 g/kg) doses of ZYP could effectively improve biochemical parameters in the blood of cholestasis-induced rat models; the intervention effect of high dose ZYP was superior to that that of lower dose ZYP. Based on a metabolomics test of fecal samples, significantly altered metabolites in the ANIT and ZYP treatment group were identified. In total, 734 metabolites were differentially expressed, and whose biological functions were mainly associated with amino acid metabolism, steroid hormone biosynthesis, and bile secretion. In addition, sequencing of the 16S rDNA unit in fecal samples revealed that the ZYP could improve the fecal microbiota dysbiosis that ANIT had induced. Therefore, we conclude that ANIT altering of blood biochemical and metabolic profiles and of fecal microbiota could effectively be alleviated with ZYP treatment. This study contributes to the “TCM wisdom” applied in clinical diagnosis and treatment of cholestasis.

Purpose: Stroke-associated infection (SAI) is associated with adverse outcomes in patients with acute ischemic stroke (AIS). In this study, we aimed to evaluate the association between neutrophil percentage-to-albumin ratio (NPAR) and SAI occurrence in patients with AIS.Methods: We retrospectively analyzed all AIS patients who were admitted to the Neurology ward of The Second Hospital of Tianjin Medical University from November 2018 to October 2020. The relationship between NPAR and SAI was analyzed by multivariable analysis. The receiver operating characteristic (ROC) curve was used to compare the predicted value of albumin, neutrophil percentage, neutrophil-to-lymphocyte ratio (NLR), and NPAR.Results: We included 379 AIS patients out of which 51 (13.5%) developed SAI. The NPAR was independently associated with increased risk of SAI adjusting for confounders [adjusted odds ratio (aOR) = 10.52; 95% confidence interval (CI), 3.33–33.28; P

In this paper, we theoretically and experimentally investigate the all-optical modulation characteristics of a microfiber coupler combined Sagnac loop (MCSL). We inject pump lights with different intensities into the MCSL and utilize the thermo-optical effect from the microfiber coupler to control the phase relationship between the counter-propagating beams inside the Sagnac loop. The spectral characteristics from the Sagnac loop can be controlled accordingly, and the rate of the frequency comb (interference characteristic wavelength) shift can be 1 pm/mW. In addition, at a specific wavelength (e.g., 1550 nm), the MCSL can be used as an intensity modulator as well as a reflectivity-tunable Sagnac reflector. The reflectivity variation of the Sagnac reflector can reach about 10% when the pump light is at milliwatt level. The intensity modulation depth can be 9.3% at 100 Hz when the intensity-modulated 980 nm pump light imposed on the MCSL is 5.5 mW. Based on the thermo-optical effect, the MCSL can achieve the all-optical intensity modulation and all optically tunable filtering functions. The device is expected to play an important role in the development of tunable, multi-wavelength, and compact fiber lasers.

The microbial fuel cell has been considered a promising alternative to traditional fossil energy. It has great potential in energy production, waste management, and biomass valorization. However, it has several technical issues, such as low power generation efficiency and operational stability. These issues limit the scale-up and commercialization of MFC systems. This review presents the latest progress in microbial community selection and genetic engineering techniques for enhancing microbial electricity production. The summary of substrate selection covers defined substrates and some inexpensive complex substrates, such as wastewater and lignocellulosic biomass materials. In addition, it also includes electrode modification, electron transfer mediator selection, and optimization of operating conditions. The applications of MFC systems introduced in this review involve wastewater treatment, production of value-added products, and biosensors. This review focuses on the crucial process of microbial fuel cells from preparation to application and provides an outlook for their future development.

Neoadjuvant chemotherapy followed by radical cystectomy is the standard of care for patients diagnosed with muscle-invasive bladder cancer (MIBC). However, urinary diversion following radical cystectomy significantly reduces patient quality of life. In addition, patients who significantly respond to neoadjuvant chemotherapy have a strong will to preserve the bladder. Bladder-sparing therapy has become a research focus worldwide. Although the bladder-sparing regimen, referred to as trimodality therapy (TMT), has been accepted, the efficacy of immunotherapy combined with chemotherapy for bladder preservation in patients with MIBC has not yet been published. We describe the case of a 50-year-old male presented intermittent macrohematuria and was diagnosed with bladder urothelial carcinoma by diagnostic transurethral resection of bladder tumor (TURBt) with clinical stage IIIA (cT3bN0M0). A complete response was achieved after four courses of neoadjuvant chemotherapy combined with pembrolizumab. Then, we performed a second TURBt plus randomized biopsy by cystoscopy. The pathology indicated no tumor in the bladder. Adjuvant chemoradiotherapy and immunotherapy were subsequently performed. Imaging examinations, cystoscopy and urine tumor DNA (utDNA) levels were used for surveillance after treatment. Finally, the patient achieved bladder preservation and had remained cancer-free for 19 months at the last follow-up on February 20, 2021. This is the first published case study to describe neoadjuvant chemotherapy plus pembrolizumab followed by concurrent chemoradiotherapy as a novel bladder-sparing regimen and successfully achieved a promising outcome.

BackgroundThe development of immune checkpoint inhibitors (ICIs) is a revolutionary milestone in the field of immune-oncology. However, the low response rate is the major problem of ICI treatment. The recent studies showed that response rate to single-agent programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibition in unselected non-small cell lung cancer (NSCLC) patients is 25% so that researchers defined several biomarkers to predict the response of immunotherapy in ICIs treatment. Common biomarkers like tumor mutational burden (TMB) and PD-L1 expression have several limitations, such as low accuracy and inadequately validated cutoff value.MethodsTwo published and an unpublished ICIs treatment NSCLC cohorts with 129 patients were collected and divided into a training cohort (n = 53), a validation cohort (n = 22), and two independent test cohorts (n = 34 and n = 20). We identified six immune-related pathways whose mutational status was significantly associated with overall survival after ICIs treatment. Then these pathways mutational status combined with TMB, PD-L1 expression and intratumor heterogeneity were incorporated to build a Bayesian-regularization neural networks (BRNN) model to predict the ICIs treatment response.ResultsWe firstly proved that TMB, PD-L1, and mutant-allele tumor heterogeneity (MATH) were independent biomarkers. The survival analysis of six immune-related pathways revealed the mutational status could distinguish overall survival after ICIs treatment. When predicting immunotherapy efficacy, the overall accuracy of area under curve (AUC) in validation cohort reaches 0.85, outperforming previous predictors in either sensitivity or specificity. And the AUC in two independent test cohorts reach 0.74 and 0.80.ConclusionWe developed a pathway-model that could predict the efficacy of ICIs in NSCLC patients. Our study made a significant contribution to solving the low prediction accuracy of immunotherapy of single biomarker. With the accumulation of larger data sets, further studies are warranted to refine the predictive performance of the approach.

Most natural sedimentary clay contains organic matter, and even a small amount of organic matter will have a great impact on the physical and mechanical properties of clay. In order to clarify the influence of organic matter content on clay soil, the illite-quartz mixture was mixed with natural amorphous peat soil (organic matter content is 50%) in different proportions for studying the influence of different organic matter contents on the physical properties (specific gravity, Gs; moisture content, w; void ratio, e; liquid limit, wL; plastic limit, wp; plasticity index, Ip) and shear characteristics (cohesion, c; friction angle, φ) of clay soil. The experimental results found that, with the change of organic matter content, the specific gravity and void ratio of clay changed linearly, while the water content, Atterberg limit, shear strength, cohesion, and friction angle changed nonlinearly with the increase of organic matter content. Moisture content and Atterberg limit have a turning point when OC = 7.5%. Shear strength, cohesion, and friction angle all have obvious turning points when OC = 7.5% and OC = 37.5%. The variation of moisture content and Atterberg limit with organic matter content indicates that OC = 7.5% may be the limit value for the different forms of organic matter in the clay. When OC ≤ 7.5%, the organic matter in clay is in the bound state; when OC > 7.5%, the bound organic matter reaches saturation; and the free organic matter gradually increases. The change law of shear strength characteristics with organic matter content shows that the interaction between minerals and organic matter exhibits different shear characteristics under different organic matter content. When OC ≤ 7.5%, clay shows mineral properties, when 7.5% 37.5%, clay shows free organic matter properties.

Hazardous rock refers to an unstable rock block that is cut by weak structural planes and gradually separates from the slope. Hazardous rock generally collapses rapidly, and at present, it is challenging to effectively identify the separation degree of the rock and accurately predict its sudden failure. In this study, focusing on a hazardous rock with tilt behavior, a microelectromechanical system (MEMS) acceleration sensor is used in combination with the calculation principle of the included angle of the space vector to establish a microtilt angle monitoring method. A physical model test is designed, in which a thermally sensitive material (with heat-sensitive strength) is adopted as the weak structural plane of the hazardous block, and the change in the tilt angle during the process of block instability is monitored at a sampling frequency of 1000 Hz. The test results show that the accelerated evolution of the tilt angle is a precursor to hazardous rock failure. In the rapid acceleration stage, the reciprocal of the tilt angle rate is approximately linear with time, and a correlation equation is obtained. Assuming that the change rate of the tilt angle is approximately infinite, the failure time of hazardous rock can be predicted using the correlation equation. In addition, the effectiveness of the instability prediction method based on microtilt angle monitoring is verified by analyzing the long-term monitoring data of hazardous rock.

The tumor mutational burden (TMB) has been reported as a predictive marker of the response to immune checkpoint inhibition (ICI) therapy in previous melanoma clinical trials. However, the TMB alone is not sufficient to accurately predict immunotherapy benefit. Additional biomarkers are needed for better stratification of immunotherapy-sensitive patients. In the present study, mutation data and survival information of patients with melanoma were collected from several immunotherapy studies, and tumor heterogeneity was estimated using mutant-allele tumor heterogeneity (MATH). The benefit score was defined as the ratio between the TMB and tumor heterogeneity, and optimal critical values were selected to group patients and evaluate their response to ICI treatment. The benefit score significantly improved the performance of stratifying the overall survival of patients compared with the TMB alone as a predictor in two independent cohorts (p = 0.0068 vs. p = 0.1 and p = 0.045 vs. p = 0.13), in which patients were treated with Ipilimumab and Nivolumab, respectively. In another cohort of patients with melanoma receiving mixed ICI treatment, the benefit score was also positively associated with higher overall survival (p = 0.022) and outperformed the TMB alone, with a significance of p = 0.089. The benefit score showed a positive correlation with clonal TMB, a reported immunotherapy marker, and exceeded it in immunotherapy response prediction. Besides, a high benefit score was found to be associated with higher proportions of natural killer cells, lower proportions of M2 macrophages and elevated CD8 T cells, all of which favor ICI therapy. In summary, tumor heterogeneity combined with the TMB showed superior efficacy in predicting the response to ICI therapy. This might further help to delineate the mechanisms of immunotherapy in patients with melanoma.

Two experiments were conducted to investigate the effects of slow-release urea (SRU) on in vitro rumen fermentation parameters, growth performances, nutrient digestibility, and serum metabolites of beef cattle. The single factor design was applied in both experiments. Three diets with different nitrogen sources including soybean meal (Control group), slow-release urea (SRU group), and common urea (Urea group) was designed (concentrate to forage ratio was 4:6). The diets were formulated to be isoenergetic and isonitrogenous, 75% of the soybean meal in the control diet was replaced by 1.41% SRU and 1.15% urea in SRU group and Urea group, respectively. In experiment 1, five healthy Jinjiang cattle (average body weight (BW) was 380 ± 17.1 kg) with permanent rumen fistulas were used in in vitro ruminal fermentation experiment. The results showed that supplementing SRU increased the dry matter degradation rate (DMD), digestible organic matter (DOM) and propionic acid concentration in cultivated fluid, and SRU supplementation decreased pH, NH3-N, total volatile fatty acid (TVFA), acetic acid, butyric acid concentration and microbial growth efficiency (MOEFF) in cultivated fluid. In experiment 2, eighteen Simmental crossbred cattle BW= 315 ± 5.2 kg) were stratified by BW and then assigned to the three groups to have equal BW among groups. The results showed that supplementing SRU reduced the average dry matter intake (ADMI), apparent digestibility of ether extract (EE), the activity of glutathione peroxidase (GSH-Px), the levels of IgG and IgA, and the production of thiiodothronine (T3) in serum, SRU supplementation increased the apparent digestibility of dry matter and organic matter (OM) and alanine aminotransferase (ALT) concentration in serum. These results indicated that some soybean meal could be replaced by SRU and urea in the production of beef cattle. In addition, compared with urea, SRU had a good sustained-release effect. The replacement of some soybean meal by SRU in the diet had no adverse impact on rumen fermentation, growth performance, and serum metabolites of beef cattle.