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Abstract Diverse neuro-imaging techniques measure different aspects of neural responses with distinct spatial and temporal resolutions. Relating measured neural responses across different methods has been challenging. Here, we take a step towards overcoming this challenge, by comparing the nonlinearity of neural dynamics measured across methods. We used widefield voltage-sensitive dye imaging (VSDI) to measure neural population responses in macaque V1 to visual stimuli with a wide range of temporal waveforms. We found that stimulus-evoked VSDI responses are surprisingly near-additive in time. These results are qualitatively different from the strong sub-additive dynamics previously measured using fMRI and electrocorticography (ECoG) in human visual cortex with a similar set of stimuli. To test whether this discrepancy is specific to VSDI—a signal dominated by subthreshold neural activity, we repeated our measurements using widefield imaging of a genetically encoded calcium indicator (GcaMP6f)—a signal dominated by spiking activity, and found that GCaMP signals in macaque V1 are also near-additive. Therefore, the discrepancies in the extent of sub-additivity between the macaque and the human measurements are unlikely due to differences between sub- and supra-threshold neural responses. Finally, we use a simple yet flexible delayed normalization model to capture these different dynamics across measurements (with different model parameters). The model can potentially generalize to a broader set of stimuli, which aligns with previous suggestion that dynamic gain-control is a canonical computation contributing to neural processing in the brain.

Abstract The incidence of autoimmune diseases has significantly increased over the past 20 years. Excessive host immunoreactions and disordered immunoregulation are at the core of the pathogenesis of autoimmune diseases. The traditional anti-tumor chemotherapy drug CPT-11 is associated with leukopenia. Considering that CPT-11 induces leukopenia, we believe that it is a promising drug for the control of autoimmune diseases. Here, we show that CPT-11 suppresses T cell proliferation and pro-inflammatory cytokine production in healthy C57BL/6 mice and in complete Freund’s adjuvant-challenged mice. We found that CPT-11 effectively inhibited T cell proliferation and Th1 and Th17 cell differentiation by inhibiting glycolysis in T cells. We also assessed CPT-11 efficacy in treating autoimmune diseases in models of experimental autoimmune encephalomyelitis and psoriasis. Finally, we proved that treatment of autoimmune diseases with CPT-11 did not suppress long-term immune surveillance for cancer. Taken together, these results show that CPT-11 is a promising immunosuppressive drug for autoimmune disease treatment.

The cognitive radar framework presents a closed-loop adaptive processing paradigm that ensures the efficient acquisition of target information while exploring the environment and enhancing overall sensing performance. In this study, instead of mutual information, we employed the squared Pearson correlation coefficient (SPCC) to measure the target information in observations specifically considering only linear dependency. A waveform design method is proposed that simultaneously maximizes target information and minimizes the integrated sidelobe level (ISL) under the constant modulus constraint (CMC). To enhance computational efficiency, we reformulated the constrained problem as an unconstrained optimization problem by leveraging the inherent geometric property of CMC. Additionally, we present two conditional equivalences associated with waveform design in relation to target information. The simulation results validate the feasibility and effectiveness of the proposed method.

Abstract The reserve sharing amongst the interconnected power systems will facilitate the improvements on their anti‐disturbance capability and operating economy. Based on the design of reserve sharing mechanism across different areas, a multi‐area generation‐reserve sharing model is constructed. The stochastic fluctuation of load and wind power will cause the power grid to be in an unpredictable random state when the reserve is needed, and the transmission capacity constraint of the power grid may restrict the effective deployment of the reserve. To address these issues, a max‐min bi‐level optimization model is proposed to check the reserve availability. The joint generation and reserve optimization sub‐model, together with the reserve check sub‐model, constitutes the two‐stage robust optimization model in this paper. The column‐and‐constraint generation (C&CG), algorithm is adopted to solve the proposed model. The modified IEEE 118‐node test case is used to verify the proposed model and algorithm. The test results indicate that the proposed method can realize the multi‐area generation‐reserve joint optimization under the condition of guaranteeing the reserve availability, and it possesses the advantage of high efficiency in dealing with stochastic scenarios.

The complexity of intestinal homeostasis results from the ability of the intestinal epithelium to absorb nutrients, harbor multiple external and internal antigens, and accommodate diverse immune cells. Intestinal intraepithelial lymphocytes (IELs) are a unique cell population embedded within the intestinal epithelial layer, contributing to the formation of the mucosal epithelial barrier and serving as a first-line defense against microbial invasion. TCRαβ+ CD4- CD8αα+ CD8αβ- and TCRγδ+ CD4- CD8αα+ CD8αβ- IELs are the two predominant subsets of natural IELs. These cells play an essential role in various intestinal diseases, such as infections and inflammatory diseases, and act as immune regulators in the gut. However, their developmental and functional patterns are extremely distinct, and the mechanisms underlying their development and migration to the intestine are not fully understood. One example is that Bcl-2 promotes the survival of thymic precursors of IELs. Mature TCRαβ+ CD4- CD8αα+ CD8αβ- IELs seem to be involved in immune regulation, while TCRγδ+ CD4- CD8αα+ CD8αβ- IELs might be involved in immune surveillance by promoting homeostasis of host microbiota, protecting and restoring the integrity of mucosal epithelium, inhibiting microbiota invasion, and limiting excessive inflammation. In this review, we elucidated and organized effectively the functions and development of these cells to guide future studies in this field. We also discussed key scientific questions that need to be addressed in this area.

As a natural sugar, mannose is a type of hexose that is abundant in many different types of fruits. Since mannose is rarely used for glycolysis in mammals, studies on the role of mannose have not attracted much attention. Glycosylation of specific proteins was thought to be the major function of mannose. Surprisingly, during the past few years, mannose was found to be effective in promoting immune tolerance and suppressing inflammatory diseases related to autoimmunity and allergy. Moreover importantly, mannose was also found to be efficient in suppressing tumors by suppressing glycolysis and enhancing chemotherapeutic agents. In this review, we summarize the recent studies of mannose on antitumor properties and anti-inflammatory characteristics. We emphasize that mannose could play a beneficial role in the treatment of a variety of diseases, including cancers and inflammatory diseases, and could be a novel therapeutic strategy that deserves continued evaluation.

Abstract Background Recent studies have emphasized determining the ability of microRNAs (miRNAs) as crucial regulators in the occurrence and development of pancreatic cancer (PC), which continues to be one of the deadliest malignancies with few effective therapies. The study aimed to investigate the functional role of miR-135b and its associated mechanism to unravel the biological characteristics of tumor growth in pancreatic cancer stem cells (PCSCs). Methods Microarray analyses were initially performed to identify the PC-related miRNAs and genes. The expression of miR-135b and PCSC markers in PC tissues and cells was determined by RT-qPCR and western blot analysis, respectively. The potential gene (JADE-1) that could bind to miR-135b was confirmed by the dual-luciferase reporter assay. To investigate the tumorigenicity, migration, invasion, and stemness of PC cells, several gain-of-function and loss-of-function genetic experiments were conducted. Finally, tumor formation in nude mice was conducted to confirm the results in vivo. Results miR-135b was highly-expressed in PC tissues and PCSCs, which was identified to specifically target JADE-1. The overexpression of miR-135b promoted proliferation, migration, and invasion of PCSC, inhibited cell apoptosis and increased the expression of stemness-related factors (Sox-2, Oct-4, Nanog, Aldh1, and Slug). Moreover, miR-135b could promote the expression of phosphorylated AKT and phosphorylated mTOR in the AKT/mTOR pathway. Additionally, miR-135b overexpression accelerated tumor growth in nude mice. Conclusions Taken together, the silencing of miR-135b promotes the JADE-1 expression, which inactivates the AKT/mTOR pathway and ultimately results in inhibition of self-renewal and tumor growth of PCSCs. Hence, this study contributes to understanding the role of miR-135 in PCSCs and its underlying molecular mechanisms to aid in the development of effective PC therapeutics.

Summary: Recent studies have shown that PM2.5 may activate the hypothalamus-pituitary-adrenal (HPA) axis by inducing hormonal changes, potentially explaining the increase in neurological and cardiovascular risks. In addition, an association between PM2.5 and gut microbiota and metabolites was established. The above evidence represents crucial parts of the gut-brain axis (GBA). In view of this evidence, we proposed a hypothesis that PM2.5 exposure may affect the HPA axis through the gastrointestinal tract microbiota pathway (GBA mechanism), leading to an increased risk of neurological and cardiovascular diseases. We conducted a real-world prospective repeated panel study in Jinan, China. At each visit, we measured real-time personal PM2.5 and collected fecal and blood samples. A linear mixed-effects model was used to analyze the association between PM2.5 and serum biomarkers, gut microbiota, and metabolites. We found that PM2.5 was associated with increased serum levels of hormones, especially the adrenocorticotropic hormone (ACTH) and cortisol, which are reliable hormones of the HPA axis. Gut microbiota and tryptophan metabolites and inflammation, which are important components of the GBA, were significantly associated with PM2.5. We also found links between PM2.5 and changes in the nervous and cardiovascular outcomes, e.g., increases of 19.77% (95% CI: −36.44, 125.69) in anxiety, 1.19% (95% CI: 0.65, 1.74) in fasting blood glucose (FBG), 2.09% (95% CI: 1.48, 2.70) in total cholesterol (TCHOL), and 0.93% (95% CI: 0.14, 1.72) in triglycerides (TG), were associated with 10 μg/m3 increase in PM2.5 at the lag 0–72 h, which represent the main effects of GBA. This study indicated the link between PM2.5 and the microbiota GBA for the first time, providing evidence of the potential mechanism for PM2.5 with neurological and cardiovascular system dysfunction.

In a general wireless sensor network, a sink node collects data from each node successively and then post-processes the data to obtain useful information. However, conventional methods have a scalability problem: the data collection/processing time increases with the number of nodes, and frequent transmission collisions degrade spectrum efficiency. If only statistical values of the data are needed, using over-the-air computation (AirComp) can efficiently perform data collection and computation. However, AirComp also has its problems: when the channel gain of a node is too low, (i) the transmission power of that node will be high, decreasing the lifetime of that node and the entire network, and (ii) sometimes, the computation error still occurs even though the maximal transmission power is used. To jointly solve these two problems, in this paper we investigate the relay communication for AirComp and study a relay selection protocol. The basic method selects an ordinary node with a good channel condition as a relay node, considering both computation error and power consumption. This method is further enhanced to explicitly consider network lifetime in relay selection. Extensive simulation evaluations confirm that the proposed method helps to prolong the lifetime of the entire network and reduce computation errors as well.

Based on a previously designed variable-stiffness load transfer component (LTC), a novel dispersed-tendon cable anchor system (CAS) was developed to increase the anchoring efficiency of large-diameter basalt-fiber-reinforced polymer (BFRP) cables. The static behaviors of the CAS are then numerically evaluated by a simplified three-dimensional finite-element (FE) model and implemented in a full-scale BFRP cable. The FE results indicated that the accuracy of the simplified dispersed-tendon model could be effectively ensured by dividing the revised compensation factor. The anchor behavior of the dispersed-tendon CAS was superior to that of the parallel-tendon CAS when the same cable was applied. The radial stress and tensile stress difference can be reduced by decreasing the tendon spacing. The testing and simulated results agreed well with the load–displacement relationship and axial displacement. All tendons fractured in the testing section, and the LTC suffered minimal damage. The ultimate force of the cable with 127 4-mm-diameter tendons was 2419 kN, and the corresponding anchoring efficiency was 93%. The cable axial tensile strain in the anchoring zone decreased linearly from the loading end to the free end. The cable shear stress concentration at the loading end can be avoided by employing a variable-stiffness anchoring method.

Visual neurons respond to static images with specific dynamics: neuronal responses sum sub-additively over time, reduce in amplitude with repeated or sustained stimuli (neuronal adaptation), and are slower at low stimulus contrast. Here, we propose a simple model that predicts these seemingly disparate response patterns observed in a diverse set of measurements-intracranial electrodes in patients, fMRI, and macaque single unit spiking. The model takes a time-varying contrast time course of a stimulus as input, and produces predicted neuronal dynamics as output. Model computation consists of linear filtering, expansive exponentiation, and a divisive gain control. The gain control signal relates to but is slower than the linear signal, and this delay is critical in giving rise to predictions matched to the observed dynamics. Our model is simpler than previously proposed related models, and fitting the model to intracranial EEG data uncovers two regularities across human visual field maps: estimated linear filters (temporal receptive fields) systematically differ across and within visual field maps, and later areas exhibit more rapid and substantial gain control. The model is further generalizable to account for dynamics of contrast-dependent spike rates in macaque V1, and amplitudes of fMRI BOLD in human V1.

The integration of shiftable/curtailment distribution generators (DGs) along with quick-response storage has not only increased the transaction’s flexibility but also puzzled the bidding willingness of transmission-connected market players (TMPs). In this paper, the method of heterogeneous decomposition and coordination (HGDC) is applied to decompose the integrated transmission-distribution market framework into a bi-level problem with a transmission wholesale market master problem and several distribution retail market subproblems in a decentralized organization structure. The price-based bidding willingness of demand-side resources’ (DSRs’) aggregator is simulated considering the relation between distribution system operator’s (DSO’s) operation modes and its equivalent market transactive price. Besides the traditional mixed-integer linear programming (MILP) model, the active reconfiguration model of DSOs based on mixed-integer second-order conic programming (MI-SOCP) is proposed to rearrange its operation switch status and elaborate its operation cost according to the market transaction. Multi-period optimal operation modes could be obtained through an HGDC-based iteration process by coordinating the transmission system operator (TSO) with DSOs and considering the market energy equilibrium and reserve requirements for security considerations. Karush-Kuhn-Tucker (KKT) conditions are used to testify the optimality and convergence of the bi-level model in theory. The T5-3D33 case is employed to illustrate the efficiency of the proposed model and method.

The perception of sensory attributes is often quantified through measurements of sensitivity (the ability to detect small stimulus changes), as well as through direct judgments of appearance or intensity. Despite their ubiquity, the relationship between these two measurements remains controversial and unresolved. Here, we propose a framework in which they arise from different aspects of a common representation. Specifically, we assume that judgments of stimulus intensity (e.g., as measured through rating scales) reflect the mean value of an internal representation, and sensitivity reflects a combination of mean value and noise properties, as quantified by the statistical measure of Fisher information. Unique identification of these internal representation properties can be achieved by combining measurements of sensitivity and judgments of intensity. As a central example, we show that Weber's law of perceptual sensitivity can coexist with Stevens' power-law scaling of intensity ratings (for all exponents), when the noise amplitude increases in proportion to the representational mean. We then extend this result beyond the Weber's law range by incorporating a more general and physiology-inspired form of noise and show that the combination of noise properties and sensitivity measurements accurately predicts intensity ratings across a variety of sensory modalities and attributes. Our framework unifies two primary perceptual measurements--thresholds for sensitivity and rating scales for intensity--and provides a neural interpretation for the underlying representation. [ABSTRACT FROM AUTHOR]

Interlaminar fracture or delamination is one of the major failure modes for fiber reinforced polymer (FRP) laminate. Especially, the synergistic effect of environmental exposure and fatigue loads accelerates interface degradation. The main objective in this work was to investigate the fatigue damage propagation of basalt FRP (BFRP) laminate under coupling of acidic environment and fatigue load. The fatigue cycling of 40,000 and the maximum stress of 30% fu (fu = ultimate tensile strength) were adopted. The fatigue specimens under air condition (air fatigue), immersing in water (water fatigue) and immersing in acid (acid fatigue) were introduced. The double cantilever beam (DCB) test was used to evaluate the interlaminar damage of BFRP laminate after fatigue cycling. The fatigue damage propagation mechanism was explored by means of failure modes, load displacement curves, mode I fracture toughness and crack propagation resistance model. The results show that the fatigue weakened the interlaminar properties and resulted in reduced fiber bridging. Especially for the acid fatigue, the laminate was damaged by the coupling of fatigue and acid corrosion. The linear loading stage, nonlinear slow growing stage, stable crack propagation stage and linear unloading stage for DCB after fatigue were observed in the load–displacement curve. The fatigue cycling has caused fracture toughness decrease of 15.0%, 13.8% and 24.1% on air fatigue, water fatigue and acid fatigue respectively. Compared to air fatigue, additional 9.1% interlaminar toughness decrease was evidenced for acidic corrosion fatigue due to the coupling effect of chemical corrosion and physical swelling. The fluctuating decline of crack resistance was caused by discontinuous interface damage, and the interlayer damage was randomly distributed. Thus the interface damage model was proposed to characterize the damage distribution and the damage size. Highlights: Degradation law of BFRP under the coupling effect of acid immersion and fatigue load.Interface damage model for characterization of the damage distribution and damage size.Fatigue damage propagation of BFRP under coupling effect of cyclic load and corrosion. [ABSTRACT FROM AUTHOR]