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Background In the literature, filum terminale arteriovenous shunts (FTAVSs) always feature a single shunt point. Nidus-type FTAVSs have rarely been reported, and the best treatment strategy is unclear. This is a report of 1 exceptional case of a nidus-type FTAVS and surgical treatment of the lesion. Case description The patient suffered from cauda equina syndrome for 9 months. Magnetic resonance imaging and spinal angiography revealed a nidus-type FTAVF at the L2 level. Surgical resection was performed in the hybrid operating room, and the nidus was completely resected with the assistance of intraoperative methylene blue angiography and neurophysiological monitoring. The postoperative neurological function was stable. Conclusions A nidus-type AVS could originate from the FT, and in such cases, complete surgical resection with intraoperative neurophysiological monitoring in a hybrid operating room should be suggested.

Reducing consumption of sugar-sweetened beverages (SSBs) is a global public health priority because of their limited nutritional value and associations with increased risk of obesity and metabolic diseases. Gut microbiota-related metabolites emerged as quintessential effectors that may mediate impacts of dietary exposures on the modulation of host commensal microbiome and physiological status.This study assessed the associations among SSBs, circulating microbial metabolites, and gut microbiota-host co-metabolites, as well as metabolic health outcomes in young Chinese adults (n = 86), from the Carbohydrate Alternatives and Metabolic Phenotypes study in Shaanxi Province. Five principal component analysis-derived beverage drinking patterns were determined on self-reported SSB intakes, which were to a varying degree associated with 143 plasma levels of gut microbiota-related metabolites profiled by untargeted metabolomics. Moreover, carbonated beverages, fruit juice, energy drinks, and bubble tea exhibited positive associations with obesity-related markers and blood lipids, which were further validated in an independent cohort of 16,851 participants from the Regional Ethnic Cohort Study in Northwest China in Shaanxi Province. In contrast, presweetened coffee was negatively associated with the obesity-related traits. A total of 79 metabolites were associated with both SSBs and metabolic markers, particularly obesity markers. Pathway enrichment analysis identified the branched-chain amino acid catabolism and aminoacyl-tRNA biosynthesis as linking SSB intake with metabolic health outcomes.Our findings demonstrate the associations between habitual intakes of SSBs and several metabolic markers relevant to noncommunicable diseases, and highlight the critical involvement of gut microbiota-related metabolites in mediating such associations.

A 2 m class robotic drill was sent to the Moon and successfully collected and returned regolith samples in late 2020 by China. It was a typical thick wall spiral drill (TWSD) with a hollow auger containing a complex coring system to retain subsurface regolith samples. Before the robotic drill was launched, a series of laboratory tests were carried out to investigate and predict the possible drilling loads it may encounter in the lunar environment. This work presents how the sampling performance of the TWSD is affected by the regolith compressibility. Experiments and analysis during the drilling and sampling process in a simulated lunar regolith environment were conducted. The compressibility of a typical lunar regolith simulant (LRS) was measured through uni-directional compression tests to study the relationship between its inner regolith stress and bulk density. A theoretical model was established to elucidate the cutting discharge behavior by auger flights based on the aforementioned relationship. Experiments were conducted with the LRS, and the results show that the sampling performance is greatly affected by the flux of the drilled cuttings into the spiral flight channels. This work helped in scheduling reasonable drilling parameters to promote the sampling performance of the robotic drill in the Chinese Chang'E 5 mission.

Airway epithelial cells (AECs) are the first cell barrier of the respiratory system against external stimuli that play a critical role in the development of asthma. It is known that AECs play a key role in asthma susceptibility and severity. ITGB4 is a downregulated adhesion molecule in the airway epithelia of asthma patients, which was involved in the exaggerated lung inflammation after allergy stimulation. Toll-like receptor 4 (TLR4) in AECs has also been shown to play a crucial role in the development of lung inflammation in asthma patients. However, the specific intrinsic regulatory mechanism of TLR4 in AECs are still obscure. In this article, we demonstrated that ITGB4 deficiency in AECs enhances HDM-induced airway inflammation through hyperactivation of the TLR4 signaling pathway, which is mediated by inhibition of FYN phosphorylation. Moreover, TLR4-antagonist treatment or blockade of FYN can inhibit or exaggerate lung inflammation in HDM-stressed ITGB4-deficient mice, separately. Together, these results demonstrated that ITGB4 deficiency in AECs enhances HDM-induced lung inflammatory response through the ITGB4-FYN-TLR4 axis, which may provide new therapeutic approaches for the management of lung inflammation in asthma.

The simultaneous advances in artificial neural networks and photonic integration technologies have spurred extensive research in optical computing and optical neural networks (ONNs). The potential to simultaneously exploit multiple physical dimensions of time, wavelength and space give ONNs the ability to achieve computing operations with high parallelism and large-data throughput. Different photonic multiplexing techniques based on these multiple degrees of freedom have enabled ONNs with large-scale interconnectivity and linear computing functions. Here, we review the recent advances of ONNs based on different approaches to photonic multiplexing, and present our outlook on key technologies needed to further advance these photonic multiplexing/hybrid-multiplexing techniques of ONNs.

Graphene plasmons, possessing a lot of unique optical properties, have been employed to enable a variety of applications in the THz frequency range. Here, we demonstrate bound states in the continuum (BICs), electromagnetically induced transparency (EIT)-like effects, high-performance broadband optical absorption (OA), and narrow-band OA in a square lattice of graphene non-concentric rings (GNCRs). We show that due to inversion symmetry breaking, the symmetry-protected BICs will evolve into quasi-BICs as the eccentricity of GNCRs becomes nonzero, manifested itself as a new resonance dip appearing in the transmission spectrum. The observation can be well described by a coupled-oscillator model, namely, the coupling between a dipole state and a quadrupole state. Besides, as the eccentricity becomes very large, the structure can also support EIT-like effects, in which a transparency window will occur at the frequency of the original transmission dip caused by the dipole state, and the transmission spectrum turns into a typical W-shape. Based on the idea of BICs, we propose a broadband terahertz (THz) perfect OA by using the typical sandwiched structure, namely, with the configuration of the GNCR layer-spacer layer-metal layer. Full wave simulations are performed, which show that the OA of over 90% absorptance can be achieved at frequencies from 0.67 THz to 1.66 THz, and over 99% absorptance can be achieved at frequencies from 1.24 THz to 1.49 THz. In the absorption band, three peaks come from three graphene plasmonic modes, which are two dipole resonances and a quadrupole resonance induced by symmetry breaking. Moreover, the perfect OA performance can be well maintained for oblique incidences of transverse electric polarization, with an incidence angle of up to 30°. Finally, we show that the broadband perfect OA can be switched to narrowband perfect OA, and its operating frequency can be continuously tuned by changing the Fermi level. Our results will promote the development of graphene-based applications in THz and infrared regimes.

Textual logical reasoning, especially question-answering (QA) tasks with logical reasoning, requires awareness of particular logical structures. The passage-level logical relations represent entailment or contradiction between propositional units (e.g., a concluding sentence). However, such structures are unexplored as current QA systems focus on entity-based relations. In this work, we propose logic structural-constraint modeling to solve the logical reasoning QA and introduce discourse-aware graph networks (DAGNs). The networks first construct logic graphs leveraging in-line discourse connectives and generic logic theories, then learn logic representations by end-to-end evolving the logic relations with an edge-reasoning mechanism and updating the graph features. This pipeline is applied to a general encoder, whose fundamental features are joined with the high-level logic features for answer prediction. Experiments on three textual logical reasoning datasets demonstrate the reasonability of the logical structures built in DAGNs and the effectiveness of the learned logic features. Moreover, zero-shot transfer results show the features' generality to unseen logical texts.

Antibiotic pollution has become a global environmental pollution problem. Chlorophyll fluorescence is one of the most important indicators reflecting the degree to which plants are influenced by the environment. Ofloxacin (OFL) is a highly toxic antibiotic pollutant, and there are few reports on the effects of changes in OFL levels on tomato chlorophyll fluorescence parameters. In this study, we investigated the responses of tomato growth, photosynthetic activity and chlorophyll fluorescence kinetics to exogenous OFL exposure (as the concentrations of 0, 2.5, 5, 10 and 20 mg L

Breast milk DHA proportion was positively associated with maternal aquatic product intake and DHA supplement use, and negatively associated with postpartum depression status.

Traditional differentiable rendering approaches are usually hard to converge in inverse rendering optimizations, especially when initial and target object locations are not so close. Inspired by Lagrangian fluid simulation, we present a novel differentiable rendering method to address this problem. We associate each screen-space pixel with the visible 3D geometric point covered by the center of the pixel and compute derivatives on geometric points rather than on pixels. We refer to the associated geometric points as point proxies of pixels. For each point proxy, we compute its 5D RGBXY derivatives which measures how its 3D RGB color and 2D projected screen-space position change with respect to scene parameters. Furthermore, in order to capture global and long-range object motions, we utilize optimal transport based pixel matching to design a more sophisticated loss function. We have conducted experiments to evaluate the effectiveness of our proposed method on various inverse rendering applications and have demonstrated superior convergence behavior compared to state-of-the-art baselines.

The advancements in hardware have drawn more attention than ever to high-quality offline rendering with modern stream processors, both in the industry and in research fields. However, the graphics APIs are fragmented and existing shading languages lack high-level constructs such as polymorphism, which adds complexity to developing and maintaining cross-platform high-performance renderers. We present LuisaRender 1 , a high-performance rendering framework for modern stream-architecture hardware. Our main contribution is an expressive C++-embedded DSL for kernel programming with JIT code generation and compilation. We also implement a unified runtime layer with resource wrappers and an optimized Monte Carlo renderer. Experiments on test scenes show that LuisaRender achieves much higher performance than existing research renderers on modern graphics hardware, e.g., 5--11× faster than PBRT-v4 and 4--16× faster than Mitsuba 3.

This study aimed to explore the potential mediating effects of cognitive reserve on the association between frailty and cognition in the older people without dementia.We performed a cross-sectional analysis of data from 3122 community-dwelling older adults (≥ 65-years-old) without dementia of the Cognitive Function and Ageing Study in Wales. A 31-item frailty index was used to assess frailty. A cognitive lifestyle score was constructed to evaluate cognitive reserve, which includes participants' educational level, occupational attainment, and engagement in social and cognitive activities in later life. Linear regression and mediation modeling were used to investigate the relationship between frailty and cognition and the mediating effects of cognitive reserve as well as social and cognitive activities, an alterable component of cognitive reserve for older adults.Frailty was negatively associated with cognition. Cognitive reserve was a mediator of the association between frailty and global cognition (- 1.92; 95% CI: - 2.50, - 1.35), as well as individual cognitive domains, with indirect effects contributing to 13-59% of the total effects. Social and cognitive activities have smaller but similar mediating effects on these associations.Negative effect of frailty on cognition was partially mediated by a reduction in cognitive reserve. Our results support the possibility that enhancing cognitive reserve, especially engagement in social and cognitive activities may protect cognitive health against frailty.