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Abstract Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.

In the domain of micromotion target recognition, target characteristics can be extracted through either broadband or narrowband radar echoes. However, due to technical limitations and cost constraints in acquiring broadband radar waveform data, recognition can often only be performed through narrowband radar waveforms. To fully utilize the information embedded within narrowband radar waveforms, it is necessary to conduct in-depth research on multi-dimensional features of micromotion targets, including radar cross-sections (RCSs), time frequency (TF) images, and cadence velocity diagrams (CVDs). To address the limitations of existing identification methodologies in achieving accurate recognition with narrowband echoes, this paper proposes a graph fusion network based on a cross-modal attention mechanism, termed GF-AM Net. The network first adopts convolutional neural networks (CNNs) to extract unimodal features from RCSs, TF images, and CVDs independently. Subsequently, a cross-modal attention mechanism integrates these extracted features into a graph structure, achieving multi-level interactions among unimodal, bimodal, and trimodal features. Finally, the fused features are input into a classification module to accomplish narrowband radar micromotion target identification. Experimental results demonstrate that the proposed methodology successfully captures potential correlations between modal features by incorporating cross-modal multi-level information interactions across different processing stages, exhibiting exceptional accuracy and robustness in narrowband radar micromotion target identification tasks.

The video synthetic aperture radar (VideoSAR) has the high frame-rate imaging capability, which can perform the ground moving target detection. The moving target often leaves the shadow in the sequence of the VideoSAR images, which can indirectly detect the moving target by detecting its shadow. In view of the high false alarm rate and high missed detection rate of existing algorithms, this article proposes a moving target shadow detection method based on the improved ViBe in the VideoSAR images. First, the shadow information and local contrast information of the VideoSAR image are extracted by using the super-pixel segmentation technology, which can achieve the background reconstruction. Besides, the ViBe algorithm is improved by modifying the definition of the distance in the image pixel classification, adding the image pixel screening, and performing the morphological filtering, which is more suitable for the moving target shadow detection in VideoSAR images. Finally, by jointly extracting the regions of interest from multiple frames' detection results, most of the false alarms are suppressed, which can obtain the excellent performance in detecting the moving target shadow. The experimental results tested on the VideoSAR data released by the Sandia National Laboratories are shown to validate the correctness and effectiveness of the proposed algorithm, for which the detection rate of moving target shadows reached 97.66%, with only 8 false alarms.

Circular synthetic aperture radar (CSAR) has advantages of the omnidirectional detection and high-resolution imaging. However, when CSAR detects the dense target in the observation scene, the phenomena such as the layover effect in the CSAR image may make mutual interference between the adjacent vehicles, which leads to the poor performance of dense target detection by traditional methods. To address this problem, this article has proposed a high-precision imaging and dense vehicle target detection method for the airborne single-pass CSAR, which includes the CSAR high-precision imaging based on the extracted digital elevation model (DEM) information and high-precision dense vehicle target detection based on the CSAR image. For the high-precision imaging, the backprojection algorithm (BPA) is first used for the observation scene imaging, and then the DEM information of the vehicle target is extracted using the improved subaperture correlation method. Finally, the extracted DEM information is combined with the BPA for the high-precision imaging. For the high-precision detection, the obtained high-precision CSAR image is used to generate the maximally stable extremal region, then the extreme region is fused using the vehicle target length and width information, and finally the high-precision detection result of the dense vehicle target is obtained. Based on the public CSAR dataset from the American Air Force Research Laboratory, the experimental results show that the proposed method can obtain the high-precision CSAR images and improve the detection rate of dense vehicle target under the premise of ensuring a low false alarm rate.

The low-frequency ultrawideband synthetic aperture radar (UWB SAR) has the ability of the foliage-penetrating and high-resolution imaging, which can detect the foliage-concealed target. However, due to low-frequency UWB SAR characteristics and forest detection environments, there are usually some nontarget strong scattering points in the low-frequency UWB SAR images, which may increase the difficulty of the foliage-concealed target change detection. To solve the problem of the weak antijamming ability of the foliage-concealed target change detection, a foliage-concealed target change detection scheme based on the convolutional neural network in the low-frequency UWB SAR images is proposed, which combines the traditional image difference method and deep-learning method. First, a relatively low inspection threshold is set for the target change detection based on the image difference method, which can obtain a lot of the position information of the detection point. Moreover, for the target characteristics in the foliage-concealed scenarios, the corresponding data extraction and enhancement techniques are used to effectively extract the detection point samples from the detection image and reference image, which can prevent the overfitting of the model training caused by the sample scarcity. Finally, the samples of the detection points are input to the target classification network with the double input and single output for the classification training and testing. The experimental results tested on the CARABAS-II SAR dataset demonstrate the correctness and effectiveness of the proposed scheme, which has the better change detection performance and anti-interference capability.

Low-frequency ultrawideband synthetic aperture radar (UWB SAR) has high-resolution imaging and foliage-penetrating ability, which can detect the foliage-concealed target. However, due to the jungle detection environment and the low-frequency UWB SAR characteristics, there are often some nontarget strong scattering points in low-frequency UWB SAR images, which may increase the difficulty of foliage-concealed target change detection. To improve the change detection rate of the foliage-concealed target, a foliage-concealed target change detection strategy based on image stacks in low-frequency UWB SAR images is proposed. In image preprocessing, a relative radiometric correction method based on the bidirectional linear regression model is presented, which can eliminate the low-frequency UWB SAR image changes caused by nontarget factors. Besides, in change detection processing, multiple difference images are first obtained by subtracting the image to be detected from multiple reference images. Then, the Gaussian probability density function is used to model the distribution of the amplitude of these difference images. Finally, the generalized likelihood ratio test is used for target change detection, which effectively suppresses the interference, such as tree trunk clutter. Experimental results tested on the CARABAS-II SAR dataset demonstrate the correctness and effectiveness of the proposed strategy, which can improve the change detection probability of the foliage-concealed target with the lower false alarm rate.

This study evaluated the reliability of satellite-derived atmospheric temperature and humidity profiles derived from occultations of Fengyun-3D (FY-3D), the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), the Meteorological Operational Satellite program (METOP), and the microwave observations of NOAA Polar Orbital Environmental Satellites (POES) using various conventional sounding datasets from 2020 to 2021. Satellite-derived profiles were also used to explore the precursors of severe convective precipitations in terms of the atmospheric boundary layer (ABL) characteristics and convective parameters. It was found that the satellite-derived temperature profiles exhibited high accuracy, with RMSEs from 0.75 K to 2.68 K, generally increasing with the latitude and decreasing with the altitude. Among these satellite-derived profile sources, the COSMIC-2-derived temperature profiles showed the highest accuracy in the middle- and low-latitude regions, while the METOP series had the best performance in high-latitude regions. Comparatively, the satellite-derived relative humidity profiles had lower accuracy, with RMSEs from 13.72% to 24.73%, basically increasing with latitude. The METOP-derived humidity profiles were overall the most reliable among the different data sources. The ABL temperature and humidity structures from these satellite-derived profiles showed different characteristics between severe precipitation and non-precipitation regions and could reflect the evolution of ABL characteristics during a severe convective precipitation event. Furthermore, some convective parameters calculated from the satellite-derived profiles showed significant and rapid changes before the severe precipitation, indicating the feasibility of using satellite-derived temperature and humidity profiles as precursors to severe convective precipitation.

Multi-baseline circular synthetic aperture radar (MB CSAR) can be applied to obtain a three-dimensional (3D) image of the observation scene. However, the phase error caused by radar platform motion or atmospheric propagation delay restricts its 3D imaging capabilities. The phase error calibration of MB CSAR data is an essential step in the 3D imaging procedure due to the limited accuracy of positioning sensors. Phase gradient autofocus (PGA) is widely utilized to estimate the phase errors but is subject to shifts in the direction perpendicular to the line of sight and long iteration time in some sub-apertures. In this paper, an improved PGA method for MB CSAR 3D imaging is proposed, which can suppress the shifts and reduce computation time. This method is based on phase gradient estimation, but the prominent units are selected with an energy criterion. Then, weighted phase gradient estimation is presented to suppress the influence of prominent units with poor quality. Finally, a contrast criterion is adopted to reach faster convergence. The experimental results based on the measured MB CSAR data (Gotcha dataset) demonstrate the validity and feasibility of the proposed phase error calibration method for MB CSAR 3D imaging.

Enterotypes, which are defined as bacterial clusters in the gut microbiome, have been found to have a close relationship to host metabolism and health. However, this concept has never been used in the rumen, and little is known about the complex biological relationships between ruminants and their rumen bacterial clusters. In this study, we used young goats (n = 99) as a model, fed them the same diet, and analyzed their rumen microbiome and corresponding bacterial clusters. The relationships between the bacterial clusters and rumen fermentation and growth performance in the goats were further investigated. Two bacterial clusters were identified in all goats: the P-cluster (dominated by genus Prevotella, n = 38) and R-cluster (dominated by Ruminococcus, n = 61). Compared with P-cluster goats, R-cluster goats had greater growth rates, concentrations of propionate, butyrate, and 18 free amino acids¸ and proportion of unsaturated fatty acids, but lower acetate molar percentage, acetate to propionate ratio, and several odd and branched chain and saturated fatty acids in rumen fluid (P

Abstract Interleukin-2 (IL-2) is a pleiotropic cytokine that orchestrates bidirectional immune responses via regulatory T cells (Tregs) and effector cells, leading to paradoxical consequences. Here, we report a strategy that exploited genetic code expansion-guided incorporation of the latent bioreactive artificial amino acid fluorosulfate-L-tyrosine (FSY) into IL-2 for proximity-enabled covalent binding to IL-2Rα to selectively promote Treg activation. We found that FSY-bearing IL-2 variants, such as L72-FSY, covalently bound to IL-2Rα via sulfur-fluoride exchange when in proximity, resulting in persistent recycling of IL-2 and selectively promoting the expansion of Tregs but not effector cells. Further assessment of L72-FSY-expanded Tregs demonstrated that L72-FSY maintained Tregs in a central memory phenotype without driving terminal differentiation, as demonstrated by simultaneously attenuated expression of lymphocyte activation gene-3 (LAG-3) and enhanced expression of programmed cell death protein-1 (PD-1). Subcutaneous administration of L72-FSY in murine models of pristane-induced lupus and graft-versus-host disease (GvHD) resulted in enhanced and sustained therapeutic efficacy compared with wild-type IL-2 treatment. The efficacy of L72-FSY was further improved by N-terminal PEGylation, which increased its circulatory retention for preferential and sustained effects. This proximity-enabled covalent binding strategy may accelerate the development of pleiotropic cytokines as a new class of immunomodulatory therapies.

To investigate the difference between rumen-protected niacin (RPN) and rumen-protected nicotinamide (RPM) in the transcriptome of genes relating to the lipid metabolism of the liver of periparturient dairy cows, 10 healthy Chinese Holstein cows were randomly divided into two groups and fed diets supplemented with 18.4 g/d RPN or 18.7 g/d RPM, respectively. The experiment lasted from 14 days before to 21 days after parturition. Liver biopsies were taken 21 days postpartum for transcriptomic sequencing. In addition, human LO2 cells were cultured in a medium containing 1.6 mmol/L of non-esterified fatty acids and 1 mmol/L niacin (NA) or 2 mmol/L nicotinamide (NAM) to verify the expression of the 10 genes selected from the transcriptomic analysis of the liver biopsies. The expression of a total of 9837 genes was detected in the liver biopsies, among which 1210 differentially expressed genes (DEGs) were identified, with 579 upregulated and 631 downregulated genes. These DEGs were associated mainly with lipid metabolism, oxidative stress, and some inflammatory pathways. Gene ontology (GO) enrichment analysis showed that 355 DEGs were enriched in 38 GO terms. The differences in the expression of these DEGs between RPN and RPM were predominantly related to the processes of steroid catabolism, steroid hydroxylase, monooxygenase activity, oxidoreductase activity, hemoglobin binding, and ferric iron binding, which are involved mainly in lipid anabolism and redox processes. The expressions of FADS2, SLC27A6, ARHGAP24, and THRSP in LO2 cells were significantly higher (p < 0.05) while the expressions of BCO2, MARS1, GARS1, S100A12, AGMO, and OSBPL11 were significantly lower (p < 0.05) on the NA treatment compared to the NAM treatment, indicating that NA played a role in liver metabolism by directly regulating fatty acid anabolism and transport, inflammatory factor expression, and oxidative stress; and NAM functioned more as a precursor of nicotinamide adenine dinucleotide (NAD, coenzyme I) and nicotinamide adenine dinucleotide phosphate (NADP, coenzyme II) to participate indirectly in biological processes such as ether lipid metabolism, cholesterol metabolism, energy metabolism, and other processes.

The Indian Summer Monsoon (ISM) can profoundly influence the summer precipitation patterns of the Tibetan Plateau (TP) and indirectly affect the TP’s soil humidity. This study investigates the responses of TP’s precipitation and soil moisture to the ISM in the monsoon season (June to September, JJAS) from 1979 to 2019. Precipitation in the TP and the ISM intensity generally exhibit a positive correlation in the west and a negative correlation in the east. The response of TP soil moisture to the ISM generally aligns with precipitation patterns, albeit with noted inconsistencies in certain TP regions. A region exhibiting these inconsistencies (30°–32°N, 80°–90°E) is selected as the study area, hereafter referred to as IRR. In periods of strong ISM, precipitation in IRR increases, yet soil moisture decreases. Conversely, in years with a weak ISM, the pattern is reversed. During strong ISM years, the rainfall increase in IRR is modest, and the soil remains drier compared to other TP regions. Under the combined effects of a marginal increase in precipitation and relatively rapid evaporation, soil moisture in the IRR decreased during years of strong ISM. During weak ISM years, the surface temperature in the IRR is higher compared to strong ISM years, potentially accelerating the melting of surface permafrost and snow in this region. Additionally, glacier meltwater, resulting from warmer temperatures in the northwest edge of the TP, may also result in the humidification of the soil in the IRR.

The lack of observational data in Taklamakan Desert makes it very difficult to study its unique boundary layer structure. As a common means of supplementing observational data, the mesoscale boundary layer parameterization scheme in the numerical model method is difficult to capture small-scale turbulent processes, which may lead to large deviations in simulation. In order to obtain more accurate simulation data of desert atmospheric boundary layer, nested LES into WRF (WRF-LES) was configured to simulate the seasonal variations in Taklamakan Desert. By comparing LES with the conventional boundary layer parameterization scheme, the error characteristics between the two schemes are analyzed. The results show that LES exhibits superior performance in solving key atmospheric features such as small-scale processes and low-level jet streams. The simulation results in winter and summer have great uncertainty due to the boundary condition errors, respectively. LES also shows the maximum and minimum optimization degree in summer and winter, respectively, while the simulation results in spring and autumn are relatively stable. In the analysis of turbulence parameters, there are clear seasonal differences in turbulence characteristics, and the intensity of turbulence in summer is significantly higher than that in other seasons. When turbulent activity is strong, the difference in potential temperature and horizontal wind speed simulated between the two schemes is closely related to intense turbulent kinetic energy in LES. More accurate turbulence reproduced in LES leads to the better potential temperature and horizontal wind speed simulations in summer. In addition, large-scale cloud systems can lead to considerable simulation bias. Neither scheme can accurately simulate the cloud emergence process, and large differences between the two schemes occur at this point.

BackgroundOral microbiota is closely related to the homeostasis of the oral cavity and lungs. To provide potential information for the prediction, screening, and treatment strategies of individuals, this study compared and investigated the bacterial signatures in periodontitis and chronic obstructive pulmonary disease (COPD).Materials and methodsWe collected subgingival plaque and gingival crevicular fluid samples from 112 individuals (31 healthy controls, 24 patients with periodontitis, 28 patients with COPD, and 29 patients with both periodontitis and COPD). The oral microbiota was analyzed using 16S rRNA gene sequencing and diversity and functional prediction analysis were performed.ResultsWe observed higher bacterial richness in individuals with periodontitis in both types of oral samples. Using LEfSe and DESeq2 analyses, we found differentially abundant genera that may be potential biomarkers for each group. Mogibacterium is the predominant genus in COPD. Ten genera, including Desulfovibrio, Filifactor, Fretibacterium, Moraxella, Odoribacter, Pseudoramibacter Pyramidobacter, Scardovia, Shuttleworthia and Treponema were predominant in periodontitis. Bergeyella, Lautropia, Rothia, Propionibacterium and Cardiobacterium were the signature of the healthy controls. The significantly different pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) between healthy controls and other groups were concentrated in genetic information processing, translation, replication and repair, and metabolism of cofactors and vitamins.ConclusionsWe found the significant differences in the bacterial community and functional characterization of oral microbiota in periodontitis, COPD and comorbid diseases. Compared to gingival crevicular fluid, subgingival plaque may be more appropriate for reflecting the difference of subgingival microbiota in periodontitis patients with COPD. These results may provide potentials for predicting, screening, and treatment strategies for individuals with periodontitis and COPD.

In this work, we demonstrated a new type of biomimetic multispectral curved compound eye camera (BM3C) inspired by insect compound eyes for aerial multispectral imaging in a large field of view. The proposed system exhibits a maximum field of view (FOV) of 120 degrees and seven-waveband multispectral images ranging from visible to near-infrared wavelengths. Pinhole imaging theory and the image registration method from feature detection are used to reconstruct the multispectral 3D data cube. An airborne imaging experiment is performed by assembling the BM3C on an unmanned aerial vehicle (UAV). As a result, radiation intensity curves of several objects are successfully obtained, and a land type classification is performed using the K-means method based on the aerial image as well. The developed BM3C is proven to have the capability for large FOV aerial multispectral imaging and shows great potential applications for distant detecting based on aerial imaging.

Adenosine A2A receptors (A2ARs) appear early in the retina during postnatal development, but the roles of the A2ARs in the morphogenesis of distinct types of retinal ganglion cells (RGCs) during postnatal development and neonatal inflammatory response remain undetermined. As the RGCs are rather heterogeneous in morphology and functions in the retina, here we resorted to the Thy1-YFPH transgenic mice and three-dimensional (3D) neuron reconstruction to investigate how A2ARs regulate the morphogenesis of three morphologically distinct types of RGCs (namely Type I, II, III) during postnatal development and neonatal inflammation. We found that the A2AR antagonist KW6002 did not change the proportion of the three RGC types during retinal development, but exerted a bidirectional effect on dendritic complexity of Type I and III RGCs and cell type-specifically altered their morphologies with decreased dendrite density of Type I, decreased the dendritic field area of Type II and III, increased dendrite density of Type III RGCs. Moreover, under neonatal inflammation condition, KW6002 specifically increased the proportion of Type I RGCs with enhanced the dendrite surface area and volume and the proportion of Type II RGCs with enlarged the soma area and perimeter. Thus, A2ARs exert distinct control of RGC morphologies to cell type-specifically fine-tune the RGC dendrites during normal development but to mainly suppress RGC soma and dendrite volume under neonatal inflammation.

The fairness of the utilization of cultivated land resources is essential for the balanced development of the region, but there are few researches to analyze it. Against the background of the urgent need for farmland protection and ecological compensation, this paper takes cultivated land as the research object and uses a three-dimensional ecological footprint model to account for and analyze the utilization of natural capital stock and flow of cultivated land in Beijing-Tianjin-Hebei region from 2009 to 2016 in terms of footprint breadth and depth, so as to provide reference for cultivated land protection, ecological compensation and even coordinated regional ecological-economic development. The results show that from 2009 to 2016, the ecological footprint breadth of cultivated land in Beijing-Tianjin-Hebei region was generally low and the footprint depth was generally high, and the ecological footprint depth of cultivated land in the region as a whole tended to increase, except for Zhangjiakou and Chengde, which were able to achieve self-sufficiency in flow capital, 85% of the cities showed the phenomenon of depletion of cultivated land flow capital and intensification of stock capital depletion. After 2010, the overall Gini coefficient of the ecological footprint of cultivated land in the Beijing-Tianjin-Hebei area was less than 0.4, and the use of natural capital from cultivated land was relatively balanced. The study concludes that under the strategic role of Beijing-Tianjin-Hebei integration and collaborative development, the equity of natural capital utilization of cultivated land in each city in the Beijing-Tianjin-Hebei region has been improved, but the level of creating and utilizing natural capital flows of cultivated land still needs to be improved, and ecological protection of cultivated land needs to be further strengthened; the excessive depletion of natural capital of cultivated land caused by agricultural production can be used as a reference basis for cross-regional ecological compensation of cultivated land, thus supporting the ecological value of cultivated land. Over-consumption of natural capital from agricultural land caused by agricultural production can be used as a baseline for interregional ecological compensation of agricultural land, thus supporting the realization of the ecological value of agricultural land.

NiTi alloys have drawn significant attentions in biomedical and aerospace fields due to their unique shape memory effect (SME), superelasticity (SE), damping characteristics, high corrosion resistance, and good biocompatibility. Because of the unsatisfying processabilities and manufacturing requirements of complex NiTi components, additive manufacturing technology, especially laser powder bed fusion (LPBF), is appropriate for fabricating NiTi products. This paper comprehensively summarizes recent research on the NiTi alloys fabricated by LPBF, including printability, microstructural characteristics, phase transformation behaviors, lattice structures, and applications. Process parameters and microstructural features mainly influence the printability of LPBF-processed NiTi alloys. The phase transformation behaviors between austenite and martensite phases, phase transformation temperatures, and an overview of the influencing factors are summarized in this paper. This paper provides a comprehensive review of the mechanical properties with unique strain-stress responses, which comprise tensile mechanical properties, thermomechanical properties (e.g. critical stress to induce martensitic transformation, thermo-recoverable strain, and SE strain), damping properties and hardness. Moreover, several common structures (e.g. a negative Poisson’s ratio structure and a diamond-like structure) are considered, and the corresponding studies are summarized. It illustrates the various fields of application, including biological scaffolds, shock absorbers, and driving devices. In the end, the paper concludes with the main achievements from the recent studies and puts forward the limitations and development tendencies in the future.

Ag/SnO2, as a promising and environment-friendly electrical contact material, is widely applied in low-voltage apparatus. But the properties of Ag/SnO2 composites is difficult to improve due to the poor distribution phases and difficult component design. In this work, the Ag/SnO2 composites are prepared by selective laser melting. To get better performance, Ag/SnO2 composites with different energy density were studied. The microstructure was observed by field emission scanning electron microscope. In addition, reinforced SnO2 phase was characterized by X-ray diffraction and transmission electron microscope. The results indicated that the microstructure, relative density and hardness of are influenced by energy density, while Ag/SnO2 composites with homogeneous microstructure, high relative density, higher hardness and lower electrical resistivity can be obtained by proper energy density (E = 68 J/mm3). Keywords: Selective laser melting, Ag/SnO2, Composites, Electrical contact material

Land costs in agricultural production are rapidly becoming apparent and increasing in light of the market’s rapid development in rural China. This study examines how agricultural operators’ farming decisions are affected by explicit and implicit costs associated with land transfers. This study first categorizes explicit and implicit land costs theoretically and demonstrates that both types of land costs affect farmers’ crop-planting selections. The study then uses the most recent household survey data from the Chinese Family Database (CFD) and the China Household Finance Survey (CHFS), released in 2017, to empirically test the theoretical analysis and examine the mechanisms underlying the impact of land costs on crop-planting selections. This study makes the case that higher land costs, both explicit and implicit, cause agricultural operators to grow more crops for cash and less for food. The impact of land costs on planting selection can vary depending on the heterogeneity of production areas and geography. In terms of production area heterogeneity, the explicit cost of land has a greater influence on planting decisions in non-major food-producing areas, whereas the implicit cost of land has a greater influence on planting decisions in major food-producing areas. In terms of topographic heterogeneity, the less flat the terrain, the more growers would choose to grow cash crops. A complementary relationship between the two forms of costs is also suggested by this study’s confirmation that explicit and implicit land costs can positively reduce each other’s impact on cropping decisions. Additional mechanism research revealed that explicit and implicit land costs impact crop crop-planting selections. The explicit cost of land primarily affects the local land transfer market effect, whereas the implicit cost of land affects the land transfer service.

Congenital central hypoventilation syndrome (CCHS) is characterized by an alteration of the ventilatory response to hypercapnia and hypoxia, and is classically presented in neonates with abnormalities of the autonomic nervous system. Here, we generated human induced pluripotent stem cell (iPSC) lines from peripheral blood mononuclear cells (PBMCs) isolated from a male patient clinically diagnosed with CCHS. These iPSC lines carry a heterozygous RET mutation (c.2608-125C > T), express pluripotency markers, have the capacity to differentiate into the normal teratoma tissue, retain the RET mutation and display the normal karyotype, which will also provide a useful resource to study the pathogenesis of CCHS.

AISI 420 martensitic stainless steel with excellent corrosion resistance is an ideal choice for plastic injection molds. However, injection molds are easy to fail in high–intensity and high-pressure environments. Therefore, it's necessary to improve their hardness and tensile strength to prolong the service life of injection molds. In this work, Selective laser melting (SLM), an additive manufacturing technology was utilized to process 5 wt% TiC/AISI 420 composites. The influence of volumetric energy density (η) on relative density, constitutional phases, microstructure and mechanical properties were investigated. The results indicated that insufficient energy input could cause defects such as pores and crack in the parts, while a part with near-full density could be fabricated if the applied η was properly settled. The ring-like structure that was comprised of thin “metal-ceramic” interface along the grain boundary was distributed more uniform with the increase of applied η. The SLM-processed sample showed a best mechanical properties at highly applied η (320 W, 850 mm/s, η = 85.6 J/mm3). It had an elevated micro-hardness (592.2 ± 53.6 Hv), an enhanced tensile strength (1452.5 MPa) and an improved elongation (8.65%), which was higher than that of the cast AISI 420 stainless steel. The research would provide theoretical support for the application of SLM-processed AISI420 stainless steel composites. Keywords: Selective laser melting, TiC/AISI420 composites, Densification, Microstructure, Mechanical properties

The natural ecological lands, such as forest land, grassland, wetland, etc., constitute the most important factor for maintaining and preserving the earth’s ecosystem, which must be well concerned in the regional function-oriented planning for the sustainability of human economic development. We analyzed and evaluated the change of natural ecological land in the function-oriented planning regions where we applied the major function-oriented zones introduced as a new concept in China. Using the land-use data from 2009 to 2018 that were produced by the National Land Use Survey, we re-classified natural ecological land types into the forest, grassland, wetland, and bare land, and then addressed the changes of natural ecological land types from 2009 to 2018 in the major function-oriented zones. As a result, the area of natural ecological lands generally tended to decrease from 2009 to 2018, while the decreasing trend of natural ecological land areas was controlled after 2015 with the implementation of governmental policies for environment protection and eco-logical projects. Especially, the decrease of forest land area significantly tended to be zero in 2018 in optimal development zones. The decreased areas of natural ecological lands were mostly converted from artificial land from 2008 to 2019. On the other side, the forest lands mostly changed from cropland and grassland in key development zones, agricultural production zones, and key ecological function zones, due to the fact that grassland conversed in afforestation during this period. The evaluation of natural ecological land changes, which could be implemented by using the annual updates of national land-use data in China, is significant to support the government’s spatial regulation design, to reshape the planned regions, and make policies for environmental restoration and protection management.

The diurnal evolution of the atmospheric boundary layer—the lowermost part of the atmosphere where the majority of human activity and meteorological phenomena take place—is described by its depth. Additionally, the boundary layer height (BLH) and the turbulence intensity strongly impact the pollutant diffusion, especially during transition periods. Based on integrated observations from a 325-m meteorological tower and a Doppler Wind lidar in the center of Beijing, the entire diurnal cycle of urban BLH in December 2016 was characterized. Results highlight that the Doppler lidar exhibited it is well suited for monitoring convective BLH while it trudges in monitoring stable BLH, while a 325-m meteorological tower provided an important supplement for Doppler lidar under nocturnal boundary layer and heavily polluted conditions. For the diurnal cycle, under light wind condition, the pattern of urban BLH was largely modulated by thermal forcing of solar radiation and may partly be affected by wind speed. While under strong wind condition, the pattern of urban BLH was largely modulated both by thermal forcing and dynamical forcing. The present work also presented evidence for several new features in the morning and afternoon transitions of the urban boundary layer, showing the duration of the morning transition varied between 1 and 5 h, with the largest value occurring under weak wind with high PM2.5 concentration; while the afternoon transition ranged from 3 to 6 h, which was positively (negatively) correlated to wind speed (PM2.5 concentration). Our work highlights that weak wind speed (weak dynamic motion) and heavy aerosol pollution (weak thermal forcing due to the effect of cooling) can dramatically affect the evolution of the boundary layer.

Inspired by austenite and martensite crystal lattices in the NiTi microstructure with versatile performances, the bionic microlattice metamaterials with strut diameter from 0.4∼0.8 mm were constructed and prepared by the laser powder bed fusion for expanding the tailored mechanical-superelastic range, and the machine learning was utilized for mapping the relationship of various parameters. The mechanical-superelastic were highly related to orientation, the martensite-inspired microlattice metamaterial in the x-axis loading direction (M-x) possessed higher mechanical properties than that of the martensite-inspired microlattice metamaterials in the z-axis loading direction (M-z). For mechanical properties, the M-x possessed the highest Young's modulus (E=1001.5∼3720.4 MPa) and simultaneously the widest tailored range (87.32%), while the austenite-inspired microlattices metamaterial (A) exhibited a fully tailored ability for yield strength (σ). For superelastic, the austenite- and martensite-inspired microlattice metamaterial had superior superelasticity (98.10%∼99.36% recoverability) with wide volume tuning space, the M-x possessed the highest recoverability with a narrow tailored range. The relation between different parameters with mechanical and superelastic properties was established through machine learning, and multiple performance optimizations were carried out with vascular stents as typical application objectives. This research provides novel ideas for designing NiTi components, contributing to the future developments of different applications.

Background: Trigeminal neuralgia (TN) presents a significant challenge for athletes, where neuropathic pain can severely impact performance and quality of life. Microvascular decompression offers a potential cure, and novel surgical approaches such as the petrosal and cerebellopontine fissure methods have shown promising results. However, their effectiveness specifically in athletes requires further evaluation. Objective: This study aims to assess the effectiveness of the petrosal and cerebellopontine fissure approaches in complex microvascular decompression of TN in athletes, focusing on surgical outcomes and recovery quality. Methods: From August 2020 to August 2022, 90 athletes diagnosed with TN were randomized into two groups: a control group (n=45) treated via the conventional bone flap approach and an observation group (n = 45) undergoing surgery through the cerebellar petrosal and venous space approaches. Metrics compared included operation time, hospital stay, intraoperative blood loss, preoperative and postoperative pain levels, sleep quality, pain-associated factors, serum inflammatory markers, and postoperative complications. Results: The observation group showed a significantly higher treatment efficacy rate of 95.56% compared to 84.44% in the control group. Notably, the observation group experienced shorter operation times, less intraoperative bleeding, fewer surgical adjustments, and a lower incidence of cerebellar contusions (all P < 0.05). Improvements in digital pain scale (NRS) and Pittsburgh Sleep Quality Index (PSQI) scores were more pronounced in the observation group at intervals post-surgery (P < 0.05). Additionally, reductions in inflammatory markers such as IL-6, hs-CRP, and TNF-α were significantly greater in the observation group, aligning with lower postoperative complication rates of 4.44% compared to 17.78% in the control group (P < 0.05). Conclusion: The petrosal and cerebellopontine fissure approaches in microvascular decompression for TN are particularly beneficial for athletes, offering superior outcomes with reduced surgical impact and enhanced recovery. These techniques not only mitigate the immediate surgical risks but also support quicker resumption of training and competition by effectively managing pain and minimizing inflammatory responses post-surgery. This study advocates for a tailored surgical approach that considers the unique needs of athletes facing neuropathic conditions like TN. [ABSTRACT FROM AUTHOR]

Abstract: Acute pancreatitis (AP) have been documented to have severe impact on pancreatic function. Frequent incidence of AP can result in chronic pancreatitis and thereby it can increase the probability of pancreatic cancers. This study intended to examine the effect of selenium nanoparticles (Se-NPs) synthesized from Coleus forskohlii leaf extract on pancreatic function and AP in rat. Primarily, Se-NPs was fabricated using the C. forskohlii leaf extract. The synthesized nanomaterial was characterized through UV-visible, XRD, and FTIR spectroscopies. Notably, the zeta potential of Se-NPs was found to be –32.8 mV with a polydispersity index (PDI) of 0.18. Morphological analysis on SEM unveiled the spherical shape of Se-NP with an average particle size of 12.69 nm. Strikingly, cytotoxicity analysis on pancreatic cancer and normal cells unveiled the concentration-dependent toxicity profile. However, IC50 value is lower in normal pancreatic cell lines in comparison to pancreatic cancer cells lines. Assessment of Se-NPs on AP rats revealed the positive impact of Se-NPs. It effectively decreased the amount of lipase, amylase, IL-1β, MDA, NO, and Bcl-2 while increased the glucose, insulin, HOMA-β and antioxidant potential in AP rats. In addition, an evaluation of Se-NPs in the pancreatic functions revealed the non-harmful effect of Se-NPs. [ABSTRACT FROM AUTHOR]