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ABSTRACT: Sepsis is a life-threatening organ dysfunction that occurs due to a dysregulated host response to infection. Septic-associated liver injury (SALI) has been closely linked to the prognosis and mortality of sepsis. Recent investigations have delved into the gut-liver axis and its association with SALI, identifying its pivotal role in the gut microbiota. Bacterial translocation and the onset of SALI can occur due to an imbalance in the gut microbiota, impairing the function of the gut barrier. Moreover, their metabolites might exacerbate or initiate SALI by modulating immune responses. Nevertheless, interventions to restore the balance of the gut microbiota, such as the administration of probiotics, fecal microbiota transplantation, or dietary adjustments, may ameliorate SALI and enhance the prognosis and survival rates of septic patients. This review aimed to elucidate the function of the gut microbiota in the genesis and procession of SALI and its potential therapeutic value, offering a deeper understanding of the pathogenesis and therapeutic avenues for SALI.
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Emerging optoelectronic memristive devices with high parallelism and low-power consumption have made neuromorphic computing hardware a tangible reality. The coordination of conductivity regulation through both electrical and light signals is pivotal for advancing the development of synaptic memristors with brainlike functionalities. Here, an artificial visual synapse is presented with the Ti3C2 MXene memristor which demonstrates not only the nonvolatile memory effect (Set/Reset: 0.58/-0.55 V; Retention: >103 s) and sustained multistage conductivity, but also facile modulation of both electrical- and light-stimulated synaptic behaviors. By adjusting the stimulus parameters, the Ti3C2 MXene enables the realization of biosynaptic excitatory postsynaptic current, sustained conductivity, stable long-term facilitation/depression, paired pulse facilitation, spiking-timing-dependent plasticity, and experiential learning. Particularly, benefiting from the distinguishable photoconductive and memory effects of multiple near-infrared intensities (7-13 mW/cm2), potential applications in visual nociceptive perception ("threshold", "noadaption", "relaxation") and imaging (e.g., "Superman" cartoon character) in infrared environments are well achieved in such Ti3C2 MXene memristors. These results hold significant implications for the future advancement of integrated optoelectronic sensing, memory, nociception, and imaging systems.
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Developing brain-inspired neuromorphic paradigms is imperative to breaking through the von Neumann bottleneck. The emulation of synaptic functionality has motivated the exploration of optoelectronic memristive devices as high-performance artificial synapses, yet the realization of such a modulatory terminal capable of full light-modulation, especially near-infrared stimuli, remains a challenge. Here, a fully light-modulated synaptic memristor is reported on a P-MoSe2/PxOy heterostructure formed by a facile one-step selenization process. The results demonstrate successful achievement of multiwavelength (visible 470 nm to near-infrared 808 nm) modulated switching operations (reset in 0.21-0.97 V) and diverse synaptic behaviors, including postsynaptic current, paired-pulse facilitation, short- and long-term memory (STM and LTM), and learning-forgetting. Notably, the device can exhibit a 3.42 µA PSC increase under six identical 655 nm stimuli, a 11.90-46.24 µA PSC modulation by changing 808 nm light intensity from 6 to 14 mW/cm2, and a transition from STM to LTM lasting between 2.47 and 4.27 s by a prolonged 808 nm pulse from 1 to 30 s. A novel possible light-induced switching mechanism in such a heterostructure is proposed. Furthermore, brain-like light-stimulated memory behavior and Pavlov's classical conditioning demonstrate the device's capacity for processing complex inputs. The study presents a design toward a multiwavelength modulated artificial visual system for color recognition.
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Temperature is an important parameter to be monitored in new wearable electronic devices. Layered black phosphorus (BP) has inherent good thermal stability and semiconductor properties and has a promising application as a temperature sensing layer. Here, we investigate the temperature sensing properties of BP, using in situ Raman spectroscopy and x-ray diffraction techniques. Flexible sensors are constructed, and temperature response is investigated in the range of 6-38 °C. The prospect application for monitoring the temperature of human body parts is demonstrated. The results show that the BP-based temperature sensors demonstrate good negative temperature coefficient characteristics and display high sensitivity and reproducible sensing performance. The temperature-dependent performance suggests the feasibility of BP as a sensitive layer in a wide temperature range. This work paves the way for exploring new applications of amazing layered materials, such as BP, in wearable electronic devices.
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The ever-growing requirement for electrochemical energy storage has exacerbated the production of spent batteries, and the recycling of valuable battery components has recently received a remarkable attention. Among all battery components, copper foil is widely utilized as a current collector for stable zinc platting and stripping in zinc metal batteries (ZMBs) due to the perfect lattice matching of between metal copper and zinc, which is accompanied by the formation of multiple copper-zinc alloy components during the cycling process. Herein, a novel "two birds with one-stone" strategy through a one simple heat treatment step to revive the discarded copper foil in zinc metal battery is reported to further obtain a lithiophilic current collector (CuxZny-Cu) with multiple copper-zinc alloy components on the surface of the discarded copper foil. Such revived CuxZny-Cu current collector greatly reduces the lithium nucleation overpotential and realizes uniform lithium deposition and further inhibits lithium dendrites growth. The formed multiple CuxZny alloy phases on the surface of discarded copper foil exhibit a low Li nucleation overpotential of only 15 mV at 0.5 mA cm-2 for the first cycle. Moreover, such a CuxZny-Cu current collector could achieve stable cycle for 220 cycles at 0.5 mA cm-2 and 110 cycles at 1 mA cm-2 with a Li plating capacity of 1 mAh cm-2. Theoretical calculations indicate that, compared with pure Cu foil, the formed multiple alloy components of CuZn5, CuZn8, Cu0.61Zn0.39 and CuZn have low adsorption energy of -2.17, -2.55, -2.16 and -2.35 eV with lithium atoms, respectively, which result in reduced lithium nucleation overpotential. The full cell composed of CuxZny alloy current collector with deposition of 5 mAh cm-2 metal Li anode coupled with LiFePO4 (LFP) cathode exhibits a reversible capacity of 125.6 mAh/g after 110 cycles at a current of 0.5 C with capacity retention of 85.1 %. This work proposed a promising strategy to regenerate the discarded copper foil in rechargeable batteries.
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A large open-circuit voltage (VOC) deficit is the major challenge hindering the efficiency improvement of Cu2ZnSn(S,Se)4 (CZTSSe) solar cells. Cation substitution, or doping, is usually an effective strategy to achieve carrier regulation and improve efficiency. In this work, we developed a rare-earth element lanthanum (La) doped CZTSSe thin-film solar cell by directly introducing La3+ ions into the CZTS precursor solution. Such a proposed La doping approach could effectively enhance light harvesting, adjust the bandgap, and increase the electron diffusion length. Furthermore, appropriate concentrations of La doping can reduce harmful defect cluster. Benefiting from the La doping, the VOC significantly increases from 431 to 497 mV. Consequently, the power conversion efficiency is enhanced significantly from 6.54% (VOC = 431 mV, JSC = 25.50 mA/cm2, FF = 58.28%) for the reference cell to 10.21% (VOC = 497 mV, JSC = 35.20 mA/cm2, FF = 58.41%) for the optimized La-doped cell. This research provides a new direction for enhancing the performance of CZTSSe cells, offering promising prospects for the future of CZTSSe thin-film solar cells.
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Background: Driving is a complex skill involving various cognitive activities. Previous research has explored differences in the brain structures related to the navigational abilities of drivers compared to non-drivers. However, it remains unclear whether changes occur in the structures associated with low-level sensory and higher-order cognitive abilities in drivers. Methods: Gray matter volume, assessed via voxel-based morphometry analysis of T1-weighted images, is considered a reliable indicator of structural changes in the brain. This study employs voxel-based morphological analysis to investigate structural differences between drivers (n = 22) and non-drivers (n = 20). Results: The results indicate that, in comparison to non-drivers, drivers exhibit significantly reduced gray matter volume in the middle occipital gyrus, middle temporal gyrus, supramarginal gyrus, and cerebellum, suggesting a relationship with driving-related experience. Furthermore, the volume of the middle occipital gyrus, and middle temporal gyrus, is found to be marginally negative related to the years of driving experience, suggesting a potential impact of driving experience on gray matter volume. However, no significant correlations were observed between driving experiences and frontal gray matter volume. Conclusion: These findings suggest that driving skills and experience have a pronounced impact on the cortical areas responsible for low-level sensory and motor processing. Meanwhile, the influence on cortical areas associated with higher-order cognitive function appears to be minimal.
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Encéfalo , Sustancia Gris , Sustancia Gris/diagnóstico por imagen , Encéfalo/diagnóstico por imagen , Cerebelo , Cognición , Lóbulo Occipital/diagnóstico por imagenRESUMEN
Integrating both electrical and light-modulated multi-type neuromorphic functions in a single synaptic memristive device holds the most potential for realizing next-generation neuromorphic systems, but is still challenging yet achievable. Herein, a simple bi-terminal optoelectronic synaptic memristor is newly proposed based on kesterite Cu2ZnSnS4, exhibiting stable nonvolatile resistive switching with excellent spatial uniformity and unique optoelectronic synaptic behaviors. The device demonstrates not only low switching voltage (-0.39 ± 0.08 V), concentrated Set/Reset voltage distribution (<0.08/0.15 V), and long retention time (>104 s) but also continuously modulable conductance by both electric (different width/interval/amplitude) and light (470-808 nm with different intensity) stimulus. These advantages make the device good electrically and optically simulated synaptic functions, including excitatory and inhibitory, paired-pulsed facilitation, short-/long-term plasticity, spike-timing-dependent plasticity, and "memory-forgetting" behavior. Significantly, decimal arithmetic calculation (addition, subtraction, and commutative law) is realized based on the linear conductance regulation, and high precision pattern recognition (>88%) is well achieved with an artificial neural network constructed by 5 × 5 × 4 memristor array. Predictably, such kesterite-based optoelectronic memristors can greatly open the possibility of realizing multi-functional neuromorphic systems.
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Memristor holds great potential for enabling next-generation neuromorphic computing hardware. Controlling the interfacial characteristics of the device is critical for seamlessly integrating and replicating the synaptic dynamic behaviors; however, it is commonly overlooked. Herein, we report the straightforward oxidation of a Mo electrode in air to design MoOx memristors that exhibit nonvolatile ultrafast switching (0.6-0.8 mV/decade, <1 mV/decade) with a high on/off ratio (>104), a long durability (>104 s), a low power consumption (17.9 µW), excellent device-to-device uniformity, ingeniously synaptic behavior, and finely programmable multilevel analog switching. The analyzed physical mechanism of the observed resistive switching behavior might be the conductive filaments formed by the oxygen vacancies. Intriguingly, upon organization into memristor-based crossbar arrays, in addition to simulated multipattern memorization, edge detection on random images can be implemented well by parallel processing of pixels using a 3 × 3 × 2 array of Prewitt filter groups. These are vital functions for neural system hardware in efficient in-memory computing neural systems with massive parallelism beyond a von Neumann architecture.
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Neuromorphic simulation, i.e., the use of electronic devices to simulate the neural networks of the human brain, has attracted a lot of interest in the fields of data processing and memory. This work provides a new method for preparing a 1,3-dimethylimidazolium nitrate ([MMIm][NO3]:H2O) microfluidic memristor that is ultralow cost and technically uncomplicated. Such a fluidic device uses capillaries as memory tubes, which are structurally similar to interconnected neurons by simple solution treatment. When voltage is applied, the transmission of anions and cations in the tube corresponds to the release of neurotransmitters from the presynaptic membrane to the postsynaptic membrane. The change of synaptic weights (plasticity) also can be simulated by the gradual change of conductance of the fluid memristor. The learning process of microfluidic memristors is very obvious, and the habituation and recovery behaviors they exhibit are extremely similar to biological activities, representing its good use for simulating neural synapses.
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Flexible pressure sensors, an important class of intelligent sensing devices, are widely explored in body-motion and medical health monitoring, artificial intelligence and human-machine interaction. As a unique layered nanomaterial, black phosphorus (BP) has excellent electrical, mechanical, and flexible characteristics, which make it a promising candidate for fabricating high-performance pressure sensors. Herein, hierarchically structured BP-based pressure sensors were constructed. The sensors exhibit high sensitivity, stability and a wide sensing range and respond to various human motions including finger pressure, swallowing, and wrist bending. The sensors can identify different handwriting processes with featured signals. In particular, benefiting from the unique structure of loose-dense layers, the sensors show a distinctive response to bending angles and directions, revealing a characteristic of direction recognition. This feature facilitates the sensors to monitor human motions. The sensors have been successfully powered by a home-made Cu2ZnSn(S,Se)4 thin-film solar cell, which demonstrates the sustainability, flexibility and low power consumption of integrated devices. This work offers a strategy to construct hierarchically structured pressure/strain sensors with direction recognition and provides further insights into manufacturing portable sensing devices for realistic and innovative applications.
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Background/aim: Ribosomal proteins have been shown to perform unique extraribosomal functions in cell apoptosis and other biological processes. Ribosomal protein L8 (RPL8) not only has important nonribosomal regulatory functions but also participates in the oncogenesis and development of tumors. However, the specific biological functions and pathways involved in this process are still unknown. Materials and methods: RPL8 was overexpressed (RPL8-OE) in HeLa cells. MTT assay and flow cytometry were used to detect cell proliferation and apoptosis, respectively. Transcriptome sequencing was performed to analyze the differentially expressed genes (DEGs) and regulated alternative splicing events (RASEs) by RPL8-OE, both of which were validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay. Results: RPL8-OE inhibited cell proliferation and promoted cell apoptosis. RPL8 regulated the differential expression of many oncogenic genes and the occurrence of RASEs. Many DEGs and RASE genes (RASGs) were enriched in tumorigenesis and tumor progression-related pathways, including angiogenesis, inflammation, and regulation of cell proliferation. RPL8 could regulate the RASGs enriched in the negative regulation of apoptosis, consistent with its proapoptosis function. Furthermore, RPL8 may influence cancer-related DEGs by modulating the alternative splicing of transcription factors. Conclusion: RPL8 might affect the phenotypes of cancer cells by altering the transcriptome profiles, including gene expression and splicing, which provides novel insights into the biological functions of RPL8 in tumor development.
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Optoelectronic memristors hold the most potential for realizing next-generation neuromorphic computation; however, memristive devices that can integrate excellent resistive switching and both electrical-/light-induced bio-synaptic behaviors are still challenging to develop. In this study, an artificial optoelectronic synapse is proposed and realized using a kesterite-based memristor with Cu2ZnSn(S,Se)4 (CZTSSe) as the switching material and Mo/Ag as the back/top electrode. Benefiting from unique electrical features and a bi-layered structure of CZTSSe, the memristor exhibits highly stable nonvolatile resistive switching with excellent spatial uniformity, concentrated Set/Reset voltage distribution (variation <0.08/0.02 V), high On/Off ratio (>104), and long retention time (>104 s). A possible mechanism of the switching behavior in such a device is proposed. Furthermore, these memristors successfully achieve essential bio-synaptic functions under both electrical and various visible light (470-655 nm) stimulations, including electrical-induced excitatory postsynaptic current, paired pulse facilitation, long-term potentiation, long-term depression, spike-timing-dependent plasticity, as well as light-stimulated short-/long-term plasticity and learning-forgetting-relearning process. As such, the proposed neotype kesterite-based memristor demonstrates significant potential in facilitating artificial optoelectronic synapses and enabling neuromorphic computation.
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Deep-learning-based polarization 3D imaging techniques, which train networks in a data-driven manner, are capable of estimating a target's surface normal distribution under passive lighting conditions. However, existing methods have limitations in restoring target texture details and accurately estimating surface normals. Information loss can occur in the fine-textured areas of the target during the reconstruction process, which can result in inaccurate normal estimation and reduce the overall reconstruction accuracy. The proposed method enables extraction of more comprehensive information, mitigates the loss of texture information during object reconstruction, enhances the accuracy of surface normal estimation, and facilitates more comprehensive and precise reconstruction of objects. The proposed networks optimize the polarization representation input by utilizing the Stokes-vector-based parameter, in addition to separated specular and diffuse reflection components. This approach reduces the impact of background noise, extracts more relevant polarization features of the target, and provides more accurate cues for restoration of surface normals. Experiments are performed using both the DeepSfP dataset and newly collected data. The results show that the proposed model can provide more accurate surface normal estimates. Compared to the UNet architecture-based method, the mean angular error is reduced by 19%, calculation time is reduced by 62%, and the model size is reduced by 11%.
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Introduction: Hepatocellular carcinoma (HCC) has a high mortality rate worldwide. The dysregulation of RNA splicing is a major event leading to the occurrence, progression, and drug resistance of cancer. Therefore, it is important to identify new biomarkers of HCC from the RNA splicing pathway. Methods: We performed the differential expression and prognostic analyses of RNA splicing-related genes (RRGs) using The Cancer Genome Atlas-liver hepatocellular carcinoma (LIHC). The International Cancer Genome Consortium (ICGC)-LIHC dataset was used to construct and validate prognostic models, and the PubMed database was used to explore genes in the models to identify new markers. The screened genes were subjected to genomic analyses, including differential, prognostic, enrichment, and immunocorrelation analyses. Single-cell RNA (scRNA) data were used to further validate the immunogenetic relationship. Results: Of 215 RRGs, we identified 75 differentially expressed prognosis-related genes, and a prognostic model incorporating thioredoxin like 4A (TXNL4A) was identified using least absolute shrinkage and selection operator regression analysis. ICGC-LIHC was used as a validation dataset to confirm the validity of the model. PubMed failed to retrieve HCC-related studies on TXNL4A. TXNL4A was highly expressed in most tumors and was associated with HCC survival. Chi-squared analyses indicated that TXNL4A expression positively correlated positively with the clinical features of HCC. Multivariate analyses revealed that high TXNL4A expression was an independent risk factor for HCC. Immunocorrelation and scRNA data analyses indicated that TXNL4A was correlated with CD8 T cell infiltration in HCC. Conclusion: Therefore, we identified a prognostic and immune-related marker for HCC from the RNA splicing pathway.
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Memristive devices with both electrically and optically induced synaptic dynamic behaviors will be crucial to the accomplishment of brain-inspired neuromorphic computing systems, in which the resistive materials and device architectures are two of the most important cornerstones, but still under challenge. Herein, kuramite Cu3SnS4 is newly introduced into poly-methacrylate as the switching medium to construct memristive devices, and the expected high-performance bio-mimicry of diverse optoelectronic synaptic plasticity is demonstrated. In addition to the excellent basic performances, such as stable bipolar resistive switching with On/Off ratio of â¼486, Set/Reset voltage of â¼-0.88/+0.96 V, and good retention feature of up to 104 s, the new designs of memristors possess not only the multi-level controllable resistive-switching memory property but also the capability of mimicking optoelectronic synaptic plasticity, including electrically and visible/near-infrared light-induced excitatory postsynaptic currents, short-/long-term memory, spike-timing-dependent plasticity, long-term plasticity/depression, short-term plasticity, paired-pulse facilitation, and "learning-forgetting-learning" behavior as well. Predictably, as a new class of switching medium material, such proposed kuramite-based artificial optoelectronic synaptic device has great potential to be applied to construct neuromorphic architectures in simulating human brain functions.
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The great potential of artificial optoelectronic devices that are capable of mimicking biosynapse functions in brain-like neuromorphic computing applications has aroused extensive interest, and the architecture design is decisive yet challenging. Herein, a new architecture of p-type Cu2ZnSnS4@BiOBr nanosheets embedded in poly(methyl methacrylate) (PMMA) films (CZTS@BOB-PMMA) is presented acting as a switching layer, which not only shows the bipolar resistive switching features (SET/RESET voltages, â¼ -0.93/+1.35 V; retention, >104 s) and electrical- and near-infrared light-induced synapse plasticity but also demonstrates electrical-driven excitatory postsynaptic current, spiking-time-dependent plasticity, paired pulse facilitation, long-term plasticity, long- and short-term memory, and "learning-forgetting-learning" behaviors. The approach is a rewarding attempt to broaden the research of optoelectric controllable memristive devices for building neuromorphic architectures mimicking human brain functionalities.
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Train axlebox bearings are subject to harsh service conditions, and the difficulty of diagnosing compound faults has brought greater challenges to the maintenance of high-quality train performance. In this paper, based on the traditional symplectic geometry mode decomposition (SGMD) algorithm, a maximum spectral coherence signal reconstruction algorithm is proposed to extract the intrinsic connection between the SGMD components with the help of the frequency domain coherence idea and reconstruct the key signal components so as to effectively improve the extraction of composite fault features of axlebox bearings under different speed conditions. Firstly, based on the traditional SGMD algorithm, the vibration signal of the axle box is decomposed to extract its symplectic geometry components (SGCs). Secondly, the spectral coherence coefficient between the SGCs is calculated, and the signal in which the maximum value is located is taken as the key component for the additive reconstruction Finally, the envelope spectrum is used to extract the reconstructed signal fault features. The inner race, outer race, and compound bearing failure vibration signal acquisition under different speed conditions were carried out on the equal scale axlebox bearing failure simulation test bench, and the effectiveness of the proposed algorithm was verified based on the axlebox vertical acceleration signal.
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Concernin the crucial interfacial issues in multi-layered kesterite Cu2ZnSn(S,Se)4 (CZTSSe) solar cells, (NH4)2S treatment has been proven to be effective in eliminating surface secondary phases. While for the CZTSSe absorbers without impurity phases, what can the low-temperature (NH4)2S treatment do to the absorbers, thus to the device performance? Herein, the chloride-fabricated CZTSSe absorbers are surface treated with the (NH4)2S solution at room temperature, and its influence on the device performance is investigated in detail. Surprisingly, such treatment can make the absorbers' surface become nearly super-hydrophilicity, greatly decreasing the surface wetting angle from 63.1° ± 3.4° to 7.3° ± 0.6° after 50 min-treating, and thus lead to marked differences in the interfacial properties of the CdS/CZTSSe heterojunctions deposited in a chemical bath. Consequently, for the best-performing CZTSSe cells, combining the passivated interfacial defects, increased carrier concentration, reduced carrier recombination, and prolonged minority lifetime, the efficiency is improved from 6.54% to 9.88%, together with the 37 mV and 7.9% increase in VOC and FF, respectively. This study confirms the newfound results that the (NH4)2S treatment can effectively adjust the wettability of the absorbers to form high-quality heterojunctions to boost the device efficiency, which would be valuable for an in-depth understanding of the intrinsic mechanisms of interfacial processing.
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Most animal species display dimorphic sexual behaviors and male-biased aggressiveness. Current models have focused on the male-specific product from the fruitless (fruM) gene, which controls male courtship and male-specific aggression patterns in fruit flies, and describe a male-specific mechanism underlying sexually dimorphic behaviors. Here we show that the doublesex (dsx) gene, which expresses male-specific DsxM and female-specific DsxF transcription factors, functions in the nervous system to control both male and female sexual and aggressive behaviors. We find that Dsx is not only required in central brain neurons for male and female sexual behaviors, but also functions in approximately eight pairs of male-specific neurons to promote male aggressiveness and approximately two pairs of female-specific neurons to inhibit female aggressiveness. DsxF knockdown females fight more frequently, even with males. Our findings reveal crucial roles of dsx, which is broadly conserved from worms to humans, in a small number of neurons in both sexes to establish dimorphic sexual and aggressive behaviors.