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Tarim wapiti (Cervus elaphus yarkandensis) may have a complex gut microbiota that contributes to its unique qualities due to its biological characteristics of tolerance to coarse feed and salt-alkali. The contents of the forestomach (rumen, reticulum, and omasum), abomasum, and small intestine (duodenum, jejunum and ileum) were taken in this investigation from six Tarim wapiti. The objective was to assess the content of volatile fatty acids (VFAs) and microbiological diversity through 16S rDNA. The results showed that acetate, propionate, butyrate, and valerate concentrations were much higher in the forestomach compared to the small intestine. The communities of bacteria were abundant and diversified in the forestomach and abomasum compared to the small intestine. Bacteroidetes were significantly more abundant in the forestomach and abomasum than in the small intestine, but Firmicutes were the reverse. The predominant bacterial genera identified in the forestomach and abomasum were Rikenellaceae RC9 gut group, Prevotella and F082; Clostridium sensu stricto 1, Acetitomaculum, Paeniclostridium, and Romboutsia were the main bacterial genera in the small intestine. The relative abundance of genes for microbial energy metabolism functions was substantially reduced across the rumen to the reticulum, across the abomasum to the duodenum for carbohydrate metabolism and lipid metabolism functions, and across the jejunum to the ileum for lipid metabolism and energy metabolism functions. In addition, VFAs were found to be positively correlated with dominant bacteria in forestomach and abomasum, and negatively correlated with dominant bacteria in small intestine. According to the study, Tarim wapiti have developed a unique and distinct dominant bacterial community in its forestomach, abomasum, and intestines.

The durability of recycled aggregate concrete (RAC) in the marine environment is mainly influenced by chloride attack. In this paper, the chloride transport law in RAC with different recycled coarse aggregate (RCA) contents was investigated by dry-wet cycling tests considering RCA volume fractions. A five-phase randomly convex polygonal aggregate model was built through a self-compiled program and then a mesoscopic numerical method was established by finite element software development. The proposed numerical model was validated by experimental results and data from other scholars. The impact of interfacial transition zone (ITZ), RCA, new mortar and old mortar were studied. The results showed that: 1) As the thickness of ITZ grows, the chloride diffusion coefficient increases in RAC. When the thickness of the ITZ rises from 25 µm to 100 µm, the chloride diffusion coefficient rises by 37%; 2) The diffusion coefficient of ITZ and mortar have a positive impact on the diffusion of chloride ion in RAC; 3) The chloride diffusion coefficient of RAC is positively correlated with the volume fraction of RCA (VRCA). The chloride diffusion coefficient increases by 102.0% as the VRCA increases from 0% to 50%. The proposed mesoscopic model not only effectively simulates the chloride attack process but also can be used to simulate other ionic attack behaviors and mechanical properties of RAC.

Abstract Elucidating physical transport phenologies in large lakes can aid understanding of larval recruitment dynamics. Here, we integrate a series of climate, hydrodynamic, biogeochemical, and Lagrangian particle dispersion models to: (1) simulate hatch and transport of fish larvae throughout an illustrative large lake, (2) evaluate patterns of historic and potential future climate‐induced larval transport, and (3) consider consequences for overlap with suitable temperatures and prey. Simulations demonstrate that relative offshore transport increases seasonally, with shifts toward offshore transport occurring earlier during relatively warm historic and future simulations. Intra‐ and inter‐annual trends in transport were robust to assumed pelagic larval duration and precise location and timing of hatching. Larvae retained nearshore generally encountered more favorable temperatures and zooplankton densities compared to larvae transported offshore. Larval exploitation of nearshore resources under climate change may depend on a concomitant shift to earlier spawning and hatch times in advance of earlier offshore transport.

Abstract There is a complex high-dimensional nonlinear mapping relationship between the compressive strength of High-Performance Concrete (HPC) and its components, which has great influence on the accurate prediction of compressive strength. In this paper, an efficient robust software calculation strategy combining BP Neural Network (BPNN), Support Vector Machine (SVM) and Genetic Algorithm (GA) is proposed for the prediction of compressive strength of HPC. 8 features were extracted from the previous literature, and a compressive strength database containing 454 sets of data was constructed. The model was trained and tested, and the performance of 4 Machine Learning (ML) models, namely BPNN, SVM, GA-BPNN and GA-SVM, was compared. The results show that the coupled model is superior to the single model. Moreover, because GA-SVM has better generalization ability and theoretical basis, its convergence speed and prediction accuracy are better than GA-BPNN. Then Grey Relational Analysis (GRA) and Shapley analysis were used to verify the interpretability of the GA-SVM model, which showed that the water-binder ratio had the most significant influence on the compressive strength. Finally, the combination of multiple input variables to evaluate the compressive strength supplemented this research, and again verified the significant influence of water-binder ratio, providing reference value for subsequent research.

Background: Facet joint osteoarthritis (FJOA) is a prevalent condition contributing to low back pain, particularly in the elderly population. This study aimed to investigate the potential role of Cytokine Receptor-like Factor 1 (CRLF1) in FJOA pathogenesis and its therapeutic implications. Methods: Bioinformatics analysis was utilized to identify CRLF1 as the target gene, followed by quantification of CRLF1 expression levels and joint degeneration degree using immunohistochemistry (IHC). In primary chondrocytes, the inhibition of CRLF1 expression by siRNA was performed, and Western blot analysis was conducted to evaluate the involvement of the extracellular matrix and MAPK/ERK signaling pathway. Flow cytometry was employed to assess the apoptosis rate of chondrocytes, while immunofluorescence (IF) was utilized to evaluate the localization of CRLF1, cleaved-caspase3, MMP13, COL2A1, and ERK. Results: The expression of CRLF1 was found to be significantly elevated in FJOA tissues compared to normal tissues. Through the use of loss-of-function assays, it was determined that CRLF1 not only enhanced the rate of apoptosis in chondrocytes, but also facilitated the degradation of the extracellular matrix in vitro. Furthermore, CRLF1 was found to activate the ERK1/2 pathways. The pro-arthritic effects elicited by CRLF1 were mitigated by treatment with the MEK inhibitor U0126 in chondrocytes. Conclusion: These results suggest that CRLF1 enhances chondrocytes apoptosis and extracellular matrix degration in FJOA and thus may therefore be a potential therapeutic target for FJOA.

Abstract Lake‐effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo‐Global Warming method with a fully three‐dimensional two‐way coupled lake‐land‐atmosphere modeling system at a cloud‐resolving 4 km resolution, we show a 14% increase in storm precipitation under the end‐century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain‐on‐Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake‐atmosphere dynamics during LES storms under future warming.

Al/Ni reactive multilayer foil (RMF) possesses excellent comprehensive properties as a promising substitute for traditional Cu bridge. A theoretical resistivity model of Al/Ni RMF was developed to guide the optimization of EFIs. Al/Ni RMF with different bilayer thicknesses and bridge dimensions were prepared by MEMS technology and electrical explosion tests were carried out. According to physical and chemical reactions in bridge, the electrical explosion process was divided into 5 stages: heating of condensed bridge, vaporization and diffusion of Al layers, intermetallic combination reaction, intrinsic explosion, ionization of metal gases, which are obviously shown in measured voltage curve. Effects of interface and grain boundary scattering on the resistivity of film metal were considered. Focusing on variations of substance and state, the resistivity was developed as a function of temperature at each stage. Electrical explosion curves were calculated by this model at different bilayer thicknesses, bridge dimensions and capacitor voltages, which showed an excellent agreement with experimental ones.

Imaging of nanoscale magnetic textures within extended material systems is of critical importance to both fundamental research and technological applications. While high-resolution magnetic imaging of thin nanoscale samples is well established with electron and soft x-ray microscopy, the extension to micrometer-thick systems currently requires hard x rays, which limits high-resolution imaging to rare-earth magnets. Here, we overcome this limitation by establishing soft x-ray magnetic imaging of micrometer-thick systems using the pre-edge phase x-ray magnetic circular dichroism signal, thus making possible the study of a wide range of magnetic materials. By performing dichroic spectroptychography, we demonstrate high spatial resolution imaging of magnetic samples up to 1.7 μm thick, an order of magnitude higher than conventionally possible with soft x-ray absorption-based techniques. We demonstrate the applicability of the technique by harnessing the pre-edge phase to image thick chiral helimagnets, and naturally occurring magnetite particles, gaining insight into their three-dimensional magnetic configuration. This new regime of magnetic imaging makes possible the study of extended non-rare-earth systems that have until now been inaccessible, including magnetic textures for future spintronic applications, non-rare-earth permanent magnets for energy harvesting, and the magnetic configuration of giant magnetofossils.

Abstract Reconstructions of ocean oxygenation are critical for understanding the role of respired carbon storage in regulating atmospheric CO2. Independent sediment redox proxies are essential to assess such reconstructions. Here, we present a long magnetofossil record from the eastern Indian Ocean in which we observe coeval magnetic hardening and enrichment of larger, more elongated, and less oxidized magnetofossils during glacials compared to interglacials over the last ~900 ka. Our multi-proxy records of redox-sensitive magnetofossils, trace element concentrations, and benthic foraminiferal Δδ13C consistently suggest a recurrence of lower O2 in the glacial Indian Ocean over the last 21 marine isotope stages, as has been reported for the Atlantic and Pacific across the last glaciation. Consistent multi-proxy documentation of this repeated oxygen decline strongly supports the hypothesis that increased Indian Ocean glacial carbon storage played a significant role in atmospheric CO2 cycling and climate change over recent glacial/interglacial timescales.

Assessing root sources of three uncertainties – parameterization of soil hydraulic characteristics, boundary conditions, and estimation of source/sink terms – is a significant challenge in soil water transport modeling. This study aims to evaluate the uncertainty of three each widely-used parameter estimation methods affecting plot-scale water dynamics. The study employs HYDRUS, a process-based hydrologic model, to incorporate these uncertainties and compare model predictions to measured values in a semiarid Inner Mongolia steppe, China. Soil hydraulic parameters are determined using two direct methods (laboratory-derived approach and evaporation method) and one indirect method (neural network). While each hydraulic parameter method generally simulates soil moisture dynamics, the evaporation method performed better, especially under dry conditions. This suggests that measuring the intensity properties, such as unsaturated hydraulic conductivity, with the evaporation method is crucial for reasonable soil moisture simulation. The study also demonstrates the impact of different applied boundary conditions on simulated soil moisture, specifically the partitioning of reference FAO evapotranspiration via one direct method (soil fraction cover) and two indirect methods (leaf area index and crop height). The partitioning via soil fraction cover reflected a better simulation. Additionally, the study compares the uncertainties of root water uptake function with root growth parameters and constant root depth referenced to grass and pasture, and finds no significant difference among them. Comparing three sources of uncertainty in predicting soil moisture, the study concludes that the input soil hydraulic parameter is more sensitive than evapotranspiration partitioning or representation of root water uptake function. Our study highlights that measuring soil intensity properties can better reflect the effects of land use change, such as compaction, on field water transports.

An exploding foil initiator system (EFIs) is essential in modern weaponry for its safety and reliability. As the main component of EFIs, the performance of the switch is critical to EFIs. In this study, a planar three-electrode trigger switch was designed and fabricated using the Flexible Printed Circuits (FPC) process. Subsequently, the performance of the FPC switch was tested. The results show that the self-breakdown voltage of the FPC switch is stable. In addition, an FPF switch with a 0.6 mm main electrode gap demonstrated consistency, with delay times below 31.75 ns, and a jitter ranging from 1.7 ns to 10.94 ns at 900 V to 1200 V, evidencing the FPC switches’ reliability and uniform performance across various voltages. Compared to the Micro-Electro-Mechanical Systems (MEMS) switches of similar dimensions, the FPC switches achieved a faster high-current attainment with less inductance, showing a 5% reduction in loop inductance. The repetitive testing results demonstrate that the FPC switch maintains consistent output performance, with stable peak currents, peak current time, and delay time over 50 action cycles, highlighting its repeatability. The FPC switch was assembled with an EFI chip and capacitor into an integrated system, which was subsequently able to successfully detonate HNS-IV at 1000 V/0.22 μF, proving the FPC switch’s potential in low inductance applications.

To enhance the energy efficiency of exploding foil initiator systems (EFIs) and mitigate energy loss due to ablation in the bridge-wing regions, a low-energy bridge-wing-thickened EFI chip was designed and fabricated. Computational analysis revealed that increasing the thickness of the bridge flanks significantly reduces ablation within the bridge region during the electrical explosion. The refinement of the design led to the adoption of a bridge flank thickness of 19 μm, with the bridge area dimensions specified as 0.25 mm × 0.25 mm × 4 μm. This bridge-wing-thickened EFI chip was produced by employing micro-electro-mechanical systems (MEMS) technology and underwent rigorous performance evaluations. The empirical results closely matched the computational predictions, thereby corroborating the precision of the proposed model in simulating the temperature distribution seen during the explosion process. Notably, this enhanced EFI design achieves a flyer velocity of 3800 m/s at a condition of 900 V/0.22 μF, signifying a significant advancement in EFI system efficiency and performance.

Abstract Shoreline cities are influenced by both urban‐scale processes and land‐water interactions, with consequences on heat exposure and its disparities. Heat exposure studies over these cities have focused on air and skin temperature, even though moisture advection from water bodies can also modulate heat stress. Here, using an ensemble of model simulations covering Chicago, we find that Lake Michigan strongly reduces heat exposure (2.75°C reduction in maximum average air temperature in Chicago) and heat stress (maximum average wet bulb globe temperature reduced by 0.86°C) during the day, while urbanization enhances them at night (2.75 and 1.57°C increases in minimum average air and wet bulb globe temperature, respectively). We also demonstrate that urban and lake impacts on temperature (particularly skin temperature), including their extremes, and lake‐to‐land gradients, are stronger than the corresponding impacts on heat stress, partly due to humidity‐related feedback. Likewise, environmental disparities across community areas in Chicago seen for skin temperature are much higher (1.29°C increase for maximum average values per $10,000 higher median income per capita) than disparities in air temperature (0.50°C increase) and wet bulb globe temperature (0.23°C increase). The results call for consistent use of physiologically relevant heat exposure metrics to accurately capture the public health implications of urbanization.

With the exhaustion of the IPv4 addresses, the promotion and deployment of IPv6 has been accelerating.Dual-stack technology allows devices to enable both IPv4 and IPv6 protocols, which means that users are facing more security risks.Although the existing work can realize the identification and measurement of some dual-stack servers, the following problems still exist.Dual-stack host identification requires deep protocol identification of host services, but this method consumes too much scanning resources.Besides, network service providers may provide consistent services on distributed hosts, making it difficult to guarantee the accuracy of dual-stack host identification through service fingerprints.To solve these problems, the LAN service discovery protocol was used to bind host services to IP addresses, and a dual-stack host discovery method based on SSDP and DNS-SD protocols was proposed.In IPv4 network environment, the target host was induced to actively send a request to the constructed IPv6 server through SSDP protocol, and then the IPv6 address was extracted from the server’s log.Or the service list of the target host and its corresponding AAAA record was enumerated through the DNS-SD protocol and the IPv6 address of the target host was obtained, in order to realize the discovery of the dual stack address pairs.With this method, IPv6 addresses was obtained directly from the IPv4 host, which ensured the accuracy of the discovered dual-stack host.At the same time, only request packets for specific protocols were needed during the discovery process, which greatly saved scanning resources.Based on this method, the SSDP hosts and DNS-SD hosts accidentally exposed to the global IPv4 network were measured.A total number of 158k unique IPv6 addresses were collected, of which 55k were dual-stack host address pairs with globally reachable IPv6 addresses.Unlike existing work that focused on dual-stack servers, this method mainly targeted end-users and client devices, and built a unique set of active IPv6 devices and dual-stack host address pairs that have not been explored so far.Through the analysis of the obtained IPv6 address addressing type, it shows that IPv6 address is mainly generated in a random manner, which greatly reduces the possibility of IPv6 hosts being discovered by scanning.In particular, by measuring the ports and services of dual-stack hosts, we found that the security policy differences of dual-stack hosts on different protocol stacks.Especially, IPv6 protocol stack exposes more high-risk services, expanding the attack surface of hosts.The research results also show that the infeasibility of IPv6 address space traversal scanning mitigates the security risks of IPv6, but incorrect network configuration greatly increases the possibility of these high-risk IPv6 hosts being discovered and users should revisit IPv6 security strategy on dual-stack hosts.

Abstract The Laurentian Great Lakes are the world's largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one‐dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two‐way coupled modeling system using the Weather Research and Forecasting model and a three‐dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake‐atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two‐way coupled modeling system and our observation‐driven modeling system, we find that coupled‐lake atmosphere dynamics can lead to a higher LST during June‐September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system.

Abstract Downscaling methods are critical in efficiently generating high‐resolution atmospheric data. However, state‐of‐the‐art statistical or dynamical downscaling techniques either suffer from the high computational cost of running a physical model or require high‐resolution data to develop a downscaling tool. Here, we demonstrate a recently proposed zero‐shot super‐resolution method, the Fourier neural operator (FNO), to efficiently perform downscaling without the need for high‐resolution data. Because the FNO learns dynamics in Fourier space, FNO is a resolution‐invariant emulator; it can be trained at a coarse resolution and produces emulation at any high resolution. We applied FNO to downscale a 4‐km resolution Weather Research and Forecasting (WRF) Model simulation of near‐surface heat‐related variables over the Great Lakes region. The FNO is driven by the atmospheric forcings and topographic features used in the WRF model at the same resolution. We incorporated a physics‐constrained loss in FNO by using the Clausius–Clapeyron relation to better constrain the relations among the emulated states. Trained on merely 600 WRF snapshots at 4‐km resolution, the FNO shows comparable performance with a widely‐used convolutional network, U‐Net, achieving averaged modified Kling–Gupta Efficiency of 0.88 and 0.94 on the test data set for temperature and pressure, respectively. We then employed the FNO to produce 1‐km emulations to reproduce the fine climate features. Further, by taking the WRF simulation as ground truth, we show consistent performances at the two resolutions, suggesting the reliability of FNO in producing high‐resolution dynamics. Our study demonstrates the potential of using FNO for zero‐shot super‐resolution in generating first‐order estimation on atmospheric modeling.

Abstract Multipolarity remanence in greigite‐bearing sediments has long been recognized, but the cause of this anomalous remanence behavior is not well understood. Here, we use electron microscopic and magnetic analyses to investigate the origin of such multipolarity in Miocene greigite‐bearing sediments from the Pannonian Basin (Hungary). We find a magnetic softening and partial transformation of iron sulfides to magnetite and pyrrhotite from “single‐polarity” to “multi‐polarity” samples. The inward alteration of sulfide grains is topotactic and is size‐dependent with higher alteration in smaller grains. We propose a multi‐phase self‐reversal chemical remanent magnetization (CRM) mechanism in altered greigite: the neoformed magnetite/pyrrhotite shell acquires a CRM coupled in the opposite direction to the primary CRM of the greigite core, likely through magnetostatic interactions or interfacial exchange interactions between the closely contacting core and shell. This new greigite self‐reversal model can explain the commonly observed antiparallel polarities and has broad geochronological, tectonic and paleoenvironmental implications.

The stability of contemporary ice shelves is under threat due to global warming, and the geological records in the Ross Sea offer such an opportunity to test the linkage between them. However, the absence of calcareous microfossils in the sediments of the Ross Sea results in uncertainties in establishing a precise chronology for studies. Hence, three sediment cores were collected and studied in terms of radiocarbon dating, magnetic susceptibility, and sediment grain size to reconstruct the environmental processes in the Ross Sea since the last glacial period. The main results are as follows: (1) two grain-size components were identified for the studied cores, which can be correlated to ice-shelf and sea-ice transport, respectively; (2) due to old-carbon contamination and an inconsistent carbon reservoir, the radiocarbon dates were generally underestimated, and as an alternative, changes in magnetic susceptibility of the studied cores can be tuned to the ice-core records to establish a reliable age–depth model and; (3) integrating sediment grain-size changes and comparisons with other paleoenvironmental proxies in the Antarctic, a process from a sub-ice sheet in the last glacial period to a sub-ice shelf in the glacial maximum, and, finally, to a glaciomarine state since the last deglacial period was identified in the western Ross Sea. Integrating these findings, the warming processes in the Antarctic were highlighted in the retreat processes of the Ross Ice Shelf in the past.

The rumen is divided into multiple rumen sacs based on anatomical structure, and each has its unique physiological environment. Tarim wapiti preserved roughage tolerance after domestication, and adaptation to the desertified environment led to the development of a unique rumen shape and intraruminal environment. In this work, six Tarim wapiti were chosen and tested for fermentation parameters, microbes, and histomorphology in four rumen areas (Dorsal sac, DS; Ventral sac, VS; Caudodorsal blind sac, CDBS; Caudoventral blind sac, CVBS). Tarim wapiti’s rumen blind sac had better developed rumen histomorphology, the ventral sac was richer in VFAs, and the dominant bacteria varied most notably in the phylum Firmicutes, which was enriched in the caudoventral blind sac. The ventral sac biomarkers focused on carbohydrate fermentation-associated bacteria, the dorsal sac focused on N recycling, and the caudoventral blind sac identified the only phylum-level bacterium, Firmicutes; we were surprised to find a probiotic bacterium, Bacillus clausii, identified as a biomarker in the ventral sac. This research provides a better understanding of rumen fermentation parameters, microorganisms, and histomorphology in the Tarim wapiti rumen within a unique ecological habitat, laying the groundwork for future regulation targeting the rumen microbiota and subsequent animal production improvement.

Objective To translate the original English version of the Spinal Instability Neoplastic Score (SINS) into simplified Chinese, adapt it cross‐culturally, validate its psychometric properties in measuring spinal instability in patients with metastatic spinal tumors in the Chinese mainland, examine the reliability and validity to demonstrate its accuracy and applicability in clinical practice. Methods Patients diagnosed with metastatic spinal disease between January 2016 and January 2020 were recruited. The number of participants was advised to be at least 50 for appropriate analysis of reliability, construct validity, as well as ceiling or floor effects, and recruitment of 100 patients was advised for internal consistency analysis. The study was conducted in two phases: first, the SINS was translated into simplified Chinese; second, the factor structure, internal consistency, test–retest reliability, validity, and floor and ceiling effects of the SC‐SINS were assessed. The internationally recognized cross‐cultural adaptation guidelines were followed. Internal consistency was evaluated with Cronbach's alpha. Test–retest reliability was examined among the patients with a 4‐week interval. The validity of the Chinese version of SINS (SC‐SINS) was assessed by examining its relationship with Kostuik classification. Principal component analysis was conducted to confirm the factor structure of each subscale. Results A total of 160 participants (88 males and 72 females) were enrolled. No major difficulties occurred in the forward and backward translations of SINS. The internal consistency of SC‐SINS was excellent (Cronbach's α =0.857, ranging from 0.68 to 0.85). Test–retest reliability was also excellent with a value of 0.89, ranging from 0.86 to 0.95. Validity analyses indicated that the SC‐SINS was positively and significantly correlated with Kostuik classification. The correlation between “Posterolateral Involvement of Spinal Elements” and “1‐2 Partial Damage” was the highest with a correlation value of 0.792. The correlation between “Pain” and “1–2 Partial Damage” was the lowest with a value of 0.341. All items showed principal component coefficients greater than 0.4. The values of Factor 1 ranged from 0.523 to 0.681; Factor 2 ranged from 0.591 to 0.731; Factor 3 ranged from 0.613 to 0.754; Factor 4 ranged from 0.461 to 0.711; Factor 5 ranged from 0.513 to 0.701; and Factor 6 ranged from 0.501 to 0.668. In addition, neither floor nor ceiling effects were seen in the SC‐SINS. Conclusion The SC‐SINS demonstrated high internal consistency and test–retest reliability, which has been proven valid and reliable to measure spinal stability in patients from the Chinese mainland with metastatic spinal tumor.

Abstract Given the critical role of precipitation on hydroclimate, we quantified the contributions of moisture source regions to precipitation in the Great Lakes Region (GLR) using multiple reanalysis data sets. Results show that the Great Plains (GPs) and the GLR itself are the primary sources of moisture. The moisture sources for the double peaks in the GLR precipitation that occur in June and September are identified, which is caused by a shift in the peak timing of moisture contribution from the GLR and GPs. In particular, moisture from the GPs contributes more to the heavy precipitation, while moisture from the GLR contributes more to the light precipitation. We also found a statistically significant (p

Background: To reveal candidate genes and the molecular genetic mechanism underlying primary feather color trait in ducks, a genome-wide association study (GWAS) for the primary feather color trait was performed based on the genotyping-by-sequencing (GBS) technology for a native Chinese female duck, Longyan Shan-ma ducks.Methods: Blood genomic DNA from 314 female Longyan Shan-ma duck were genotyped using GBS technology. A GWAS for the primary feather color trait with genome variations was performed using an univariate linear mixed model based on all SNPs in autosomes.Results: Seven genome-wide significant single nucleotide polymorphisms (SNPs, Bonferroni-adjusted p-value

PurposeTo compare the clinical outcomes and radiological parameters of patients undergoing percutaneous vertebroplasty (PVP) versus those undergoing percutaneous vertebral-disc plasty (PVDP) for back pain, segmental instability, and kyphosis due to thoracolumbar very severe osteoporotic vertebral compression fractures (vsOVCFs).MethodsThis prospective randomized controlled study included elderly patients with thoracolumbar vsOVCFs. All the patients were randomly allocated into the PVP group (who underwent conventional PVP) and the PVDP group (who underwent PVP combined percutaneous cement discoplasty). The visual analogue scale (VAS), Oswestry Disability Index (ODI), local kyphosis angle, and disc height were recorded preoperatively and postoperatively.ResultsSignificant postoperative improvements in the VAS, ODI, and the local kyphosis angle (LKA) were shown, compared with the preoperative values in both groups (p 0.05). The change was significantly lower in the PVDP group at the last follow-up in those parameters (p

The environmental impact of the chiral fungicide epoxiconazole and its chiral transformation products (TPs) on non-target organisms and the environment has become a significant concern due to its widespread use in agricultural practice. Enantioselectivity studies of parent contaminants cannot adequately assess the complexity of its chiral TPs in the environment. This study aimed to investigate the environmental behavior of epoxiconazole in an earthworm-soil system. 2S,3R-(–)-epoxiconazole was preferentially enriched in earthworms during the accumulation phase (p 0.8 was observed for the TPs in different matrices. The CYP450 monooxygenase of earthworm was significant activated. In vitro enzyme metabolism experiments (earthworm microsomes and recombinant CYP450 enzymes CYP2A6, CYP 2C9, and CYP 3A4) were carried out to further explain the biotransformation mechanism of epoxiconazole in earthworm. This study provides new evidence of enantiomeric biotransformation of chiral fungicide epoxiconazole in the earthworm-soil system and could provide valuable insights into their environmental risk assessment.

Accurate estimates for the lake surface temperature (LST) of the Great Lakes are critical to understanding the regional climate. Dedicated lake models of various complexity have been used to simulate LST but they suffer from noticeable biases and can be computationally expensive. Additionally, the available historical LST datasets are limited by either short temporal coverage (

The centralization of the global DNS ecosystem may accelerate the creation of an oligopoly market, thereby, increasing the risk of a single point of failure and network traffic manipulation. Earlier studies have revealed the level of centralization in terms of the market share of public DNS services and DNS traffic seen by major CDN providers. However, the level of centralization in the infrastructure of the DNS Ecosystem is not well understood. In this paper, we present a novel and lightweight measurement approach that effectively discovers resolver pools from a single probing point. We conduct an Internet-wide active measurement on the client-side as well as the server-side DNS infrastructure to assess the level of DNS centralization in terms of the supporting infrastructure. Our measurement results show that the DNS infrastructure is much more centralized than previously believed. Over 90% of forwarding resolvers are backed by less than 5% (4071) of indirect resolvers. Merely 0.45% (12,679) of all name servers across 1138 gTLDs, operated by just 10 DNS providers, provide authoritative domain resolution service for 48.5% (more than 100 million) of domain names. We also investigated several leading DNS providers in IP infrastructure, load distribution, and service geo-distribution. The findings of our measurements provide novel insights into the centrality of the DNS infrastructure, which will help the Internet community promote the understanding of the DNS ecosystem.

To accommodate the rapid change of radio propagation environment for mobile communication scenarios, millimeter-wave beamforming requires instantaneous channel state information (CSI) to update its operational parameters in real time, resulting in heavy system overhead. As the number of antennas increases, the system overhead associated with beam management will increase dramatically. To address this overarching problem, a neural network-aided millimeter-wave beamforming algorithm is proposed in this paper. A new parameter, referred to as “beam adjustment interval”, is proposed to evaluate the beamforming performance. It is defined as the maximum time duration in which the signal-to-interference-plus-noise ratio (SINR) of the user equipment can be maintained above the predefined threshold. Besides, a predictive method of beam adjustment to maximize the beam adjustment interval is developed, which considers the SINR not only at the current location but also future possible locations. Simulation results show that the proposed algorithm can significantly increase beam adjustment interval and reduce the total number of beam adjustments for the moving user equipment, thus reducing the system overhead 41.4% on average over 10 randomly generated test traces.

Paleocene carbonates from the Gamba area of South Tibet provide the largest paleomagnetic dataset for constraining the paleogeography of the India-Asia collision in the early stage. Previous studies argued that the characteristic remanences (ChRMs) obtained from this unit were remagnetized via orogenic fluids. This study carries out a high-resolution petrographic study on the Paleocene carbonates from Gamba aiming to test the nature of the ChRMs. Electron microscopic observation on magnetic extracts identified a large amount of detrital magnetite that are multi- to single domain in sizes and nanoscale biogenic magnetite. Minor framboidal iron oxides were also identified, which were previously interpreted as authigenic magnetite that substitutes pyrite. However, our scanning and transmission electron microscopic (SEM/TEM) observations, along with optical microscope and Raman spectrum investigations further suggest that these magnetic minerals are pigmentary hematite and goethite that are incapable of carrying a stable primary magnetization. We therefore argue that the ChRMs of the limestones from the Zongpu Formation in the Gamba area are carried by detrital and biogenic magnetites rather than authigenic magnetite. The paleomagnetic data from the Gamba area are interpreted as primary origin and can thus be used for tectonic reconstructions. We emphasize that magnetic extraction, integrated with advanced mineralogic studies (e.g., electron backscatter diffraction and electron diffraction) are effective approaches for investigating the origin of magnetic carriers in carbonate rocks.

Grazing is one of the main human disturbance factors in alpine grassland on the Qinghai-Tibet Plateau (QTP), which can directly or indirectly influence the community structures and ecological functions of grassland ecosystems. However, despite extensive field grazing experiments, there is currently no consensus on how different grazing management approaches affect alpine grassland diversity, soil carbon (C), and nitrogen (N). Here, we conducted a meta-analysis of 70 peer-reviewed publications to evaluate the general response of 11 variables related to alpine grassland ecosystems plant diversity and ecological functions to grazing. Overall, the results showed that grazing significantly increased the species richness, Shannon–Wiener index, and Pielou evenness index values by 9.89% (95% CI: 2.75–17.09%), 7.28% (95% CI: 1.68–13.62%), and 3.74% (95% CI: 1.40–6.52%), respectively. Aboveground biomass (AGB) and belowground biomass (BGB) decreased, respectively, by 41.91% (95% CI: −50.91 to −32.88%) and 17.68% (95% CI: −26.94 to −8.52%). Soil organic carbon (SOC), soil total nitrogen (TN), soil C:N ratio, and soil moisture decreased by 13.06% (95% CI: −15.88 to −10.15%), 12.62% (95% CI: −13.35 to −8.61%), 3.27% (95% CI: −4.25 to −2.09%), and 20.75% (95% CI: −27.89 to −13.61%), respectively, whereas, soil bulk density and soil pH increased by 17.46% (95% CI: 11.88–24.53%) and 2.24% (95% CI: 1.01–3.64%), respectively. Specifically, moderate grazing, long-durations (>5 years), and winter grazing contributed to increases in the species richness, Shannon–Wiener index, and Pielou evenness index. However, AGB, BGB, SOC, TN, and soil C:N ratios showed a decrease with enhanced grazing intensity. The response ratio of SOC was positively associated with AGB and BGB but was negatively related to the Shannon–Wiener index and Pielou evenness index. Furthermore, the effects of grazing on plant diversity, AGB, BGB, SOC, and TN in alpine grassland varied with grazing duration, grazing season, livestock type, and grassland type. The findings suggest that grazing should synthesize other appropriate grazing patterns, such as seasonal and rotation grazing, and, furthermore, additional research on grazing management of alpine grassland on the QTP is needed in the future.

Detailed knowledge of wave climate change is essential for understanding coastal geomorphological processes, ecosystem resilience, the design of offshore and coastal engineering structures and aquaculture systems. In Lake Michigan, the in-situ wave observations suitable for long-term analysis are limited to two offshore MetOcean buoys. Since this distribution is inadequate to fully represent spatial patterns of wave climate across the lake, a series of high-resolution SWAN model simulations were performed for the analysis of long-term wave climate change for the entirety of Lake Michigan from 1979 to 2020. Model results were validated against observations from two offshore buoys and 16 coastal buoys. Linear regression analysis of significant wave height (Hs) (mean, 90th percentile, and 99th percentile) across the entire lake using this 42-year simulation suggests that there is no simple linear trend of long-term changes of Hs for the majority (>90%) of the lake. To address the inadequacy of linear trend analysis used in previous studies, a 10-year trailing moving mean was applied to the Hs statistics to remove seasonal and annual variability, focusing on identifying long-term wave climate change. Model results reveal the regime shifts of Hs that correspond to long-term lake water level changes. Specifically, downward trends of Hs were found in the decade of 1990–2000; low Hs during 2000–2010 coincident with low lake levels; and upward trends of Hs were found during 2010–2020 along with rising water levels. The coherent pattern between the wave climate and the water level was hypothesized to result from changing storm frequency and intensity crossing the lake basin, which influences both waves (instantly through increased wind stress on the surface) and water levels (following, with a lag through precipitation and runoff). Hence, recent water level increases and wave growth were likely associated with increased storminess observed in the Great Lakes. With regional warming, the decrease in ice cover in Lake Michigan (particularly in the northernmost region of the lake) favored the wave growth in the winter due to increased surface wind stress, wind fetch, and wave transmission. Model simulations suggest that the basin-wide Hs can increase significantly during the winter season with projected regional warming and associated decreases in winter ice cover. The recent increases in wave height and water level, along with warming climate and ice reduction, may yield increasing coastal damages such as accelerating coastal erosion.

The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, trained with the limited data from hypothetical monitoring networks, can provide consistent and robust performance. The LSTM prediction captured the LST spatiotemporal variabilities across the five Great Lakes well, suggesting an effective and efficient way for monitoring network design in assisting the ML-based forecast. Furthermore, we employed an explainable artificial intelligence (XAI) technique named SHapley Additive exPlanations (SHAP) to uncover how the features impact the LSTM prediction. Our XAI analysis shows air temperature is the most influential feature for predicting LST in the trained LSTM. The relatively large bias in the LSTM prediction during the spring and fall was associated with substantial heterogeneity of air temperature during the two seasons. In contrast, the physics-based hydrodynamic model performed better in spring and fall yet exhibited relatively large biases during the summer stratification period. Finally, we developed a statistical integration of the hydrodynamic modeling and deep learning results based on the Best Linear Unbiased Estimator (BLUE). The integration further enhanced prediction accuracy, suggesting its potential for next-generation Great Lakes forecast systems.

The Persian/Arabian Gulf is the most important region for seawater desalination. Surrounding countries produce about 50% of global desalinated seawater. If Gulf salinity significantly rises because of desalination effluent (brine), marine ecosystems and the water supply for many population centers will be threatened. In order to quantify current and future impacts of seawater desalination on Gulf salinity and avoid costly environmental problems, it is vital to first examine the present Gulf salinity state and its response to salinity perturbation (i.e., determine its stability). Here, using a coupled Gulf-Atmosphere numerical climate model, we test the hypothesis that the Gulf has a single stable equilibrium state under the current climate. Simulations with different initializations under identical external forcing show that the natural coupled Gulf-Atmosphere system may exhibit a mixture of unstable and stable equilibrium salinity states. When continuous salinity perturbation is added to the simulations, results show that the present Gulf equilibrium state, characterized by annual mean basin-average salinity of about 40.5 g/kg, is stable. We conclude that Gulf basin salinity is resilient to present brine discharge activities under the current climate.

Stimulated by excess levels of phosphorus, the attached, filamentous green alga Cladophora grows to nuisance proportions in Lake Michigan, one of the Laurentian Great Lakes. While nearshore waters impacted by local sources of the nutrient continue to support nuisance conditions, offshore waters have undergone oligotrophication in response to reductions in phosphorus loading and benthification of phosphorus cycling by invasive dreissenid mussels. A concept termed the Dual Challenge recognizes that implementation of more stringent phosphorus-loading objectives (to control Cladophora in the nearshore) stands in conflict with a foreseen need to mitigate oligotrophication in the offshore (to sustain a healthy fishery). Attention to this nearshore–offshore dynamic calls into play the role of cross-margin phosphorus transport in mediating both endmembers of the conflict. We applied a biophysical model simulating soluble reactive (SRP) and particulate (PP) phosphorus, mussel biokinetics, and cross-margin mass transport in addressing the Dual Challenge. Pre- and post-dreissenid monitoring results suggest that a reduction in offshore PP levels (food web nutrition) in excess of 40% (2.4 to 1.4 mgP·m−3) has driven oligotrophication and attendant food web dysfunction. Yet, in the absence of local sources, model-predicted nearshore SRP levels remain at or below those required to prevent nuisance growth. These findings indicate that there is a margin of ~1 mgP·m−3 over which offshore PP levels could be increased (to the benefit of the food web and the fishery) without hindering efforts to reduce nuisance algal growth through local source control.

The filamentous green alga Cladophora grows to nuisance proportions in Lake Ontario. Stimulated by high phosphorus concentrations, nuisance growth results in the degradation of beaches and clogging of industrial water intakes with attendant loss of beneficial uses. We develop a multi-module bioavailable phosphorus model to examine the efficacy of phosphorus management strategies in mitigating nuisance algal growth. The model platform includes modules simulating hydrodynamics (FVCOM), phosphorus-phytoplankton dynamics (GEM) and Cladophora growth (GLCMv3). The model is applied along a 25 km stretch of the Lake Ontario nearshore, extending east from Toronto, ON and receiving effluent from three wastewater treatment plants. Simulation results identify the Duffin Creek wastewater treatment plant effluent as a driving force for nuisance conditions of Cladophora growth, as reflected in effluent bioavailable phosphorus concentrations and the dimensions of the plant’s phosphorus footprint. Simulation results demonstrate that phosphorus removal by chemically enhanced secondary treatment is insufficient to provide relief from nuisance conditions. Tertiary treatment (chemically enhanced secondary treatment with ballasted flocculation) is shown to eliminate phosphorus-saturated conditions associated with the Duffin Creek wastewater treatment plant effluent, providing local relief from nuisance conditions. Management guidance presented here has wider application at sites along the highly urbanized Canadian nearshore of Lake Ontario.

As an important part of the wetland ecosystem, alpine wetland is not only one of the most important ecological water conservation areas in the Qinghai–Tibet Plateau region, but is also an effective regulator of the local climate. In this study, using three machine learning algorithms to extract wetland, we employ the landscape ecological index to quantitatively analyze the evolution of landscape patterns and grey correlation to analyze the driving factors of Zoige wetland landscape pattern change from 1995 to 2020. The following results were obtained. (1) The random forest algorithm (RF) performs best when dealing with high-dimensional data, and the accuracy of the decision tree algorithm (DT) is better. The performance of the RF and DT is better than that of the support vector machine algorithm. (2) The alpine wetland in the study area was degraded from 1995 to 2015, whereas wetland area began to increase after 2015. (3) The results of landscape analysis show the decrease in wetland area from 1995 to 2005 was mainly due to the fragmentation of larger patches into many small patches and loss of the original small patches, while the 2005 to 2015 decrease was caused by the loss of many middle patches and the decrease in large patches from the edge to the middle. The 2015 to 2020 increase is due to an increase in the number of smaller patches and recovery of original wetland area. (4) The grey correlation degree further shows that precipitation and evaporation are the main factors leading to the change in the landscape pattern of Zoige alpine wetland. The results are of great significance to the long-term monitoring of the Zoige wetland ecosystem.

As an important production base for livestock and a unique ecological zone in China, the northeast Tibetan Plateau has experienced dramatic land use/land cover (LULC) changes with increasing human activities and continuous climate change. However, extensive cloud cover limits the ability of optical remote sensing satellites to monitor accurately LULC changes in this area. To overcome this problem in LULC mapping in the Ganan Prefecture, 2000–2018, we used the dense time stacking of multi-temporal Landsat images and random forest algorithm based on the Google Earth Engine (GEE) platform. The dynamic trends of LULC changes were analyzed, and geographical detectors quantitatively evaluated the key driving factors of these changes. The results showed that (1) the overall classification accuracy varied between 89.14% and 91.41%, and the kappa values were greater than 86.55%, indicating that the classification results were reliably accurate. (2) The major LULC types in the study area were grassland and forest, and their area accounted for 50% and 25%, respectively. During the study period, the grassland area decreased, while the area of forest land and construction land increased to varying degrees. The land-use intensity presents multi-level intensity, and it was higher in the northeast than that in the southwest. (3) Elevation and population density were the major driving factors of LULC changes, and economic development has also significantly affected LULC. These findings revealed the main factors driving LULC changes in Gannan Prefecture and provided a reference for assisting in the development of sustainable land management and ecological protection policy decisions.

The emerging shift in Great Lakes management from offshore to nearshore waters will require attention to complexities of coastal hydrodynamics and biogeochemical transformations. Emphasizing hydrodynamics, this work resolves transport processes in quantifying discharge plume and pollutant of concern (POC) footprint dimensions, the latter being the portion of the plume where water quality standards are not met. A generic approach, isolated from pollutant-specific biokinetics, provides first-approximation estimates of the footprint area. A high-resolution, linked hydrodynamic-tracer model is applied at a site in the Greater Toronto Area on Lake Ontario. Model results agree with observed meteorological and hydrodynamic conditions and satisfactorily simulate plume dimensions. Footprints are examined in the context of guidelines for regulatory mixing zone size and attendant loss of beneficial use. We demonstrate that the ratio of the water quality standard to the POC concentration at discharge is a key determinant of footprint dimensions. Footprint size for traditional pollutants (ammonia, total phosphorus) meets regulatory guidelines; however, that for soluble reactive phosphorus, a presently unattended pollutant, is ~1−2 orders of magnitude larger. This suggests that it may be necessary to upgrade treatment technologies to maintain consistency with regulatory guidelines and mitigate manifestations of the eutrophication-related soluble reactive phosphorus POC.

Current numerical methods for simulating biophysical processes in aquatic environments are typically constructed in a grid-based Eulerian framework or as an individual-based model in a particle-based Lagrangian framework. Often, the biogeochemical processes and physical (hydrodynamic) processes occur at different time and space scales, and changes in biological processes do not affect the hydrodynamic conditions. Therefore, it is possible to develop an alternative strategy to grid-based approaches for linking hydrodynamic and biogeochemical models that can significantly improve computational efficiency for this type of linked biophysical model. In this work, we utilize a new technique that links hydrodynamic effects and biological processes through a property-carrying particle model (PCPM) in a Lagrangian/Eulerian framework. The model is tested in idealized cases and its utility is demonstrated in a practical application to Sandusky Bay. Results show the integration of Lagrangian and Eulerian approaches allows for a natural coupling of mass transport (represented by particle movements and random walk) and biological processes in water columns which is described by a nutrient-phytoplankton-zooplankton-detritus (NPZD) biological model. This method is far more efficient than traditional tracer-based Eulerian biophysical models for 3-D simulation, particularly for a large domain and/or ensemble simulations.

We consider a single-machine scheduling problem with upper bounded actual processing time and upper bounded maintenance time under deteriorating effect. The actual processing time of a job is a position-dependent power function. If the actual processing time of a job exceeds the upper bound, tardiness penalty of the job should be paid. And if the maintenance time exceeds the corresponding upper bound, tardiness penalty of the maintenance should also be paid. The maintenance duration studied in the paper is a position-dependent exponential function. The objective is to find jointly the optimal maintenance frequency and the optimal job sequence to minimize the total cost, which is a linear function of the makespan and the total tardiness. We show that the studied scheduling problem can be transformed as a classic assignment problem to solve. There is also shown that a special case of the scheduling problem can be optimally solved by a lower order algorithm.

Micrometer-size magnetite crystals with peculiar morphologies, such as spearhead, spindle, needle, and giant bullet, known as giant magnetofossils, were previously identified in marine sediments mainly during the Eocene epoch. The origin of these unusual magnetite crystals remains unclear because no known modern analogues have been found, and data about their spatiotemporal distribution are sparse. Here, using electron microscope observations, we performed a large-scale spatiotemporal search for these mysterious magnetite crystals. We report the occurrence of giant magnetofossils in variable marine sedimentary environments, including the first report in modern South Atlantic and Indian Ocean environments and the oldest occurrence at ca. 93 Ma in the North Atlantic Ocean. Grain-size data for the giant magnetofossils in the Southwest Pacific and North Atlantic Oceans suggest that the dimension of spearheads is sensitive to regional environments during similar warming periods but is insensitive to environmental conditions across the distinct geological periods at the same locality. The grain-size distributions of needles and giant bullets do not show significant changes in diverse environments. These observations greatly expand the known temporal and geographic distribution of giant magnetofossils, shedding new light on their likely biological origin. [ABSTRACT FROM AUTHOR]

Objective: Kinesin family member C1 (KIFC1), a non-essential kinesin-like motor protein, has been found to serve a crucial role in supernumerary centrosome clustering and the progression of several human cancer types. However, the role of KIFC1 in glioma has been rarely reported. Thus, the present study aimed to investigate the role of KIFC1 in glioma progression. Methods: Online bioinformatics analysis was performed to determine the association between KIFC1 expression and clinical outcomes in glioma. Immunohistochemical staining was conducted to analyze the expression levels of KIFC1 in glioma and normal brain tissues. Furthermore, KIFC1 expression was knocked in the glioma cell lines, U251 and U87MG, and the functional roles of KIFC1 in cell proliferation, invasion and migration were analyzed using cell multiplication, wound healing and Transwell invasion assays, respectively. The autophagic flux and expression levels matrix metalloproteinase-2 (MMP2) were also determined using imaging flow cytometry, western blotting and a gelation zymography assay. Results: The results revealed that KIFC1 expression levels were significantly upregulated in glioma tissues compared with normal brain tissues, and the expression levels were positively associated with tumor grade. Patients with glioma with low KIFC1 expression levels had a more favorable prognosis compared with patients with high KIFC1 expression levels. In vitro, KIFC1 knockdown not only inhibited the proliferation, migration and invasion of glioma cells, but also increased the autophagic flux and downregulated the expression levels of MMP2. Conclusion: Upregulation of KIFC1 expression may promote glioma progression and KIFC1 may serve as a potential prognostic biomarker and possible therapeutic target for glioma. [ABSTRACT FROM AUTHOR]

Sediment suspension and transport driven by waves and currents play a significant role in both the ecological and physical environments of large lakes. Lake Michigan has faced a rapidly increasing water level associated with intensified wind waves in the past decade. To investigate the spatiotemporal characteristics of suspended sediment concentration (SSC) and associated coastal sediment budgets in southern Lake Michigan, a 30‐year (1991–2020) hindcast was performed using a coupled wave‐current‐ sediment model (SWAN‐FVCOM‐CSTMS). We found that in southern Lake Michigan, the basin‐wide mean SSC increased, and the coastal sediment loss accelerated dramatically, corresponding with intensified waves, currents and lake water level rises over the past decade. The basin‐wide mean SSC, coastal sediment loss, wave height, wind speed, current speed, and water level in southern Lake Michigan are highly correlated. Spatially, the results reveal decreases in coastal SSC and sediment loss in the western portion of the southern basin, while the eastern sectors show an increase in both metrics. This reflects a clear shift in the wave climate and hydrodynamic environment. The alterations in long‐term coastal sediment budgets imply that considerable shoreline transformations are being influenced by modifications in the wave climate. Understanding the spatiotemporal characteristics of SSC and coastal sediment budgets is crucial for strategic water resource management and coastal infrastructure planning. [ABSTRACT FROM AUTHOR]