trans-Interacting Plasma Membrane Proteins and Binding Partner Identification.

Plasma membrane proteins (PMPs) play critical roles in a myriad of physiological and disease conditions. A unique subset of PMPs functions through interacting with each other in trans at the interface between two contacting cells. These trans-interacting PMPs (tiPMPs) include adhesion molecules and ligands/receptors that facilitate cell-cell contact and direct communication between cells. Among the tiPMPs, a significant number have apparent extracellular binding domains but remain orphans with no known binding partners. Identification of their potential binding partners is therefore important for the understanding of processes such as organismal development and immune cell activation. While a number of methods have been developed for the identification of protein binding partners in general, very few are applicable to tiPMPs, which interact in a two-dimensional fashion with low intrinsic binding affinities. In this review, we present the significance of tiPMP interactions, the challenges of identifying binding partners for tiPMPs, and the landscape of method development. We describe current avidity-based screening approaches for identifying novel tiPMP binding partners and discuss their advantages and limitations. We conclude by highlighting the importance of developing novel methods of identifying new tiPMP interactions for deciphering the complex protein interactome and developing targeted therapeutics for diseases.

Collaborative FFE-assisted simplified soft-output MLSE with LDPC for high-speed IM-DD transmissions.

In this paper, we propose a feed-forward equalizer (FFE)-assisted simplified soft-output MLSE (sMLSE) by collaborating the maximum likelihood sequence estimation (MLSE) with soft-decision low-density-parity-check (LDPC) decoding. The simplified sMLSE results in undetermined log-likelihood ratio (LLR) magnitudes when the reserved level is less than or equal to the half of modulation order. This severely degrades the performance of soft-decision forward error correction (SD-FEC) decoding. In the FFE-assisted simplified sMLSE, we use the LLRs calculated from pre-set FFE to replace these undetermined LLRs of simplified sMLSE. Thus, the proposed method eliminates the SD-FEC decoding performance degradation resulted from simplification. We conduct experiments to transmit 184-Gb/s PAM-4 or 255-Gb/s PAM-8 signal in IM-DD system at C-band to evaluate the performance of the proposed sMLSE. The results show that the proposed sMLSE can effectively compensate for the degradation of LLR quality. For 255-Gb/s PAM-8 signal transmissions, the FFE-assisted simplified sMLSE achieves almost the same SD-FEC decoding performance as the conventional sMLSE but with 85% complexity reduction.

Molecular Mechanisms in Pathophysiology of Mucopolysaccharidosis and Prospects for Innovative Therapy.

Mucopolysaccharidoses (MPSs) are a group of inborn errors of the metabolism caused by a deficiency in the lysosomal enzymes required to break down molecules called glycosaminoglycans (GAGs). These GAGs accumulate over time in various tissues and disrupt multiple biological systems, including catabolism of other substances, autophagy, and mitochondrial function. These pathological changes ultimately increase oxidative stress and activate innate immunity and inflammation. We have described the pathophysiology of MPS and activated inflammation in this paper, starting with accumulating the primary storage materials, GAGs. At the initial stage of GAG accumulation, affected tissues/cells are reversibly affected but progress irreversibly to: (1) disruption of substrate degradation with pathogenic changes in lysosomal function, (2) cellular dysfunction, secondary/tertiary accumulation (toxins such as GM2 or GM3 ganglioside, etc.), and inflammatory process, and (3) progressive tissue/organ damage and cell death (e.g., skeletal dysplasia, CNS impairment, etc.). For current and future treatment, several potential treatments for MPS that can penetrate the blood-brain barrier and bone have been proposed and/or are in clinical trials, including targeting peptides and molecular Trojan horses such as monoclonal antibodies attached to enzymes via receptor-mediated transport. Gene therapy trials with AAV, ex vivo LV, and Sleeping Beauty transposon system for MPS are proposed and/or underway as innovative therapeutic options. In addition, possible immunomodulatory reagents that can suppress MPS symptoms have been summarized in this review.

[New Design of Revivent TC System].

Left ventricular aneurysm (LVA) is a common complication of myocardial infarction. Traditional medical and surgical treatments are not effective or require high doctors' operational skills and patients' physical fitness. With the development of minimally invasive medical devices, it becomes possible for revivent TC system to treat LVA and reconstruct the left ventricle. This study introduces an existing product and its defect when used. From the perspective of clinical needs, we propose a new design of revivent TC system which realizes accurate force measurement and simplifies surgery.

Stability of motor cortex network states during learning-associated neural reorganizations.

A substantial reorganization of neural activity and neuron-to-movement relationship in motor cortical circuits accompanies the emergence of reproducible movement patterns during motor learning. Little is known about how this tempest of neural activity restructuring impacts the stability of network states in recurrent cortical circuits. To investigate this issue, we reanalyzed data in which we recorded for 14 days via population calcium imaging the activity of the same neural populations of pyramidal neurons in layer 2/3 and layer 5 of forelimb motor and premotor cortex in mice during the daily learning of a lever-press task. We found that motor cortex network states remained stable with respect to the critical network state during the extensive reorganization of both neural population activity and its relation to lever movement throughout learning. Specifically, layer 2/3 cortical circuits unceasingly displayed robust evidence for operating at the critical network state, a regime that maximizes information capacity and transmission and provides a balance between network robustness and flexibility. In contrast, layer 5 circuits operated away from the critical network state for all 14 days of recording and learning. In conclusion, this result indicates that the wide-ranging malleability of synapses, neurons, and neural connectivity during learning operates within the constraint of a stable and layer-specific network state regarding dynamic criticality, and suggests that different cortical layers operate under distinct constraints because of their specialized goals.NEW & NOTEWORTHY The neural activity reorganizes throughout motor learning, but how this reorganization impacts the stability of network states is unclear. We used two-photon calcium imaging to investigate how the network states in layer 2/3 and layer 5 of forelimb motor and premotor cortex are modulated by motor learning. We show that motor cortex network states are layer-specific and constant regarding criticality during neural activity reorganization, and suggests that layer-specific constraints could be motivated by different functions.

A deep neural network approach to acoustic source localization in a shallow water tank experiment.

In this paper, an acoustic source localization method using the emerging technology of the deep neural network (DNN) is proposed. After the construction and training of the DNN, the capability of the DNN for source localization through a set of numerical simulations is verified. Next, experimental studies and demonstrations in a very shallow water tank with acoustic reflective walls are prepared, which enable the quick acquisition of a huge amount of experimental data for the training of a one-dimensional DNN-based source localization model. The development of the DNN-based source localization method and the corresponding numerical and experimental demonstration constitute the main contribution of this work. The associated performance is then evaluated at various frequencies. In particular, the localization results of the DNN are compared with readily available model-based localization methods, such as the conventional matched field processing method and the normal-mode based multiple signal classification method. The comparison shows that the proposed DNN approach is able to produce satisfactory accuracy in this reflective shallow water tank environment, for which a forward acoustic propagating model is not required. Last but not least, the generality of the proposed DNN approach from one-dimensional localization to progressively more complicated two-dimensional tasks is also considered.

Strength of PD-1 signaling differentially affects T-cell effector functions.

High surface expression of programmed death 1 (PD-1) is associated with T-cell exhaustion; however, the relationship between PD-1 expression and T-cell dysfunction has not been delineated. We developed a model to study PD-1 signaling in primary human T cells to study how PD-1 expression affected T-cell function. By determining the number of T-cell receptor/peptide-MHC complexes needed to initiate a Ca(2+) flux, we found that PD-1 ligation dramatically shifts the dose-response curve, making T cells much less sensitive to T-cell receptor-generated signals. Importantly, other T-cell functions were differentially sensitive to PD-1 expression. We observed that high levels of PD-1 expression were required to inhibit macrophage inflammatory protein 1 beta production, lower levels were required to block cytotoxicity and IFN-γ production, and very low levels of PD-1 expression could inhibit TNF-α and IL-2 production as well as T-cell expansion. These findings provide insight into the role of PD-1 expression in enforcing T-cell exhaustion and the therapeutic potential of PD-1 blockade.

SGLFormer: Spiking Global-Local-Fusion Transformer with high performance.

Introduction: Spiking Neural Networks (SNNs), inspired by brain science, offer low energy consumption and high biological plausibility with their event-driven nature. However, the current SNNs are still suffering from insufficient performance. Methods: Recognizing the brain's adeptness at information processing for various scenarios with complex neuronal connections within and across regions, as well as specialized neuronal architectures for specific functions, we propose a Spiking Global-Local-Fusion Transformer (SGLFormer), that significantly improves the performance of SNNs. This novel architecture enables efficient information processing on both global and local scales, by integrating transformer and convolution structures in SNNs. In addition, we uncover the problem of inaccurate gradient backpropagation caused by Maxpooling in SNNs and address it by developing a new Maxpooling module. Furthermore, we adopt spatio-temporal block (STB) in the classification head instead of global average pooling, facilitating the aggregation of spatial and temporal features. Results: SGLFormer demonstrates its superior performance on static datasets such as CIFAR10/CIFAR100, and ImageNet, as well as dynamic vision sensor (DVS) datasets including CIFAR10-DVS and DVS128-Gesture. Notably, on ImageNet, SGLFormer achieves a top-1 accuracy of 83.73% with 64 M parameters, outperforming the current SOTA directly trained SNNs by a margin of 6.66%. Discussion: With its high performance, SGLFormer can support more computer vision tasks in the future. The codes for this study can be found in https://github.com/ZhangHanN1/SGLFormer.

Self-architectural knowledge distillation for spiking neural networks.

Spiking neural networks (SNNs) have attracted attention due to their biological plausibility and the potential for low-energy applications on neuromorphic hardware. Two mainstream approaches are commonly used to obtain SNNs, i.e., ANN-to-SNN conversion methods, and Directly-trained-SNN methods. However, the former achieve excellent performance at the cost of a large number of time steps (i.e., latency), while the latter exhibit lower latency but suffers from suboptimal performance. To tackle the performance-latency trade-off, we propose Self-Architectural Knowledge Distillation (SAKD), an intuitive and effective method for SNNs leveraging Knowledge Distillation (KD). We adopt a bilevel teacher-student training strategy in SAKD, i.e., level-1 involves directly transferring same-architectural pre-trained ANN weights to SNNs, and level-2 encourages the SNNs to mimic ANN's behavior, considering both final responses and intermediate features aspects. Learning with informative supervision signals fostered by labels and ANNs, our SAKD achieves new state-of-the-art (SOTA) performance with a few time steps on widely-used classification benchmark datasets. On ImageNet-1K, with only 4 time steps, our Spiking-ResNet34 model attains a Top-1 accuracy of 70.04%, outperforming the previous same-architectural SOTA methods. Notably, our SEW-ResNet152 model reaches a Top-1 accuracy of 77.30% on ImageNet-1K, setting a new SOTA benchmark for SNNs. Furthermore, we apply our SAKD to various dense prediction downstream tasks, such as object detection and semantic segmentation, demonstrating strong generalization ability and superior performance. In conclusion, our proposed SAKD framework presents a promising approach for achieving both high performance and low latency in SNNs, potentially paving the way for future advancements in the field.

T cell receptor triggering by force.

Antigen recognition through the interaction between the T cell receptor (TCR) and peptide presented by major histocompatibility complex (pMHC) is the first step in T cell-mediated immune responses. How this interaction triggers TCR signalling that leads to T cell activation is still unclear. Taking into account the mechanical stress exerted on the pMHC-TCR interaction at the dynamic interface between T cells and antigen presenting cells (APCs), we propose the so-called receptor deformation model of TCR triggering. In this model, TCR conformational change induced by mechanical forces initiates TCR signalling. The receptor deformation model, for the first time, explains all three aspects of the TCR triggering puzzle: mechanism, specificity, and sensitivity.

CAR T Cells for Treating Severe Atopic Allergic Diseases.

The prevalence of allergic diseases is rising rapdly in the US and the world. While antibody drugs and corticosteroids can provide symptom relief, they cannot cure allergic diseases. Described herein is a novel approach to treating severe atopic allergic diseases - chimeric antigen receptor-engineered T cells - that target and eliminate the cells that produce the causative agent of all atopic allergic diseases, immunoglubulin E (IgE).

6,6'-Diheptyl-3,3'-bis-[(pyridin-3-yl)ethyn-yl]-5H,5'H-di-pyrrolo-[1,2-b:1',2'-g][2,6]naphthyridine-5,5'-dione.

The complete mol-ecule of the title compound, C42H42N4O2, is generated by a crystallographic centre of symmetry. The pendant heptyl chains adopt extended conformations and the dihedral angle between the pyrrole and pyridine rings is 8.18 (15)°. In the crystal, the mol-ecules are arranged in columnar stacks propagating in the [010] direction via slipped aromatic π-π stacking inter-actions.

Modulation of Neuronal Activity and Saccades at Theta Rhythm During Visual Search in Non-human Primates.

Active exploratory behaviors have often been associated with theta oscillations in rodents, while theta oscillations during active exploration in non-human primates are still not well understood. We recorded neural activities in the frontal eye field (FEF) and V4 simultaneously when monkeys performed a free-gaze visual search task. Saccades were strongly phase-locked to theta oscillations of V4 and FEF local field potentials, and the phase-locking was dependent on saccade direction. The spiking probability of V4 and FEF units was significantly modulated by the theta phase in addition to the time-locked modulation associated with the evoked response. V4 and FEF units showed significantly stronger responses following saccades initiated at their preferred phases. Granger causality and ridge regression analysis showed modulatory effects of theta oscillations on saccade timing. Together, our study suggests phase-locking of saccades to the theta modulation of neural activity in visual and oculomotor cortical areas, in addition to the theta phase locking caused by saccade-triggered responses.

Surface-anchored monomeric agonist pMHCs alone trigger TCR with high sensitivity.

At the interface between T cell and antigen-presenting cell (APC), peptide antigen presented by MHC (pMHC) binds to the T cell receptor (TCR) and initiates signaling. The mechanism of TCR signal initiation, or triggering, remains unclear. An interesting aspect of this puzzle is that although soluble agonist pMHCs cannot trigger TCR even at high concentrations, the same ligands trigger TCR very efficiently on the surface of APCs. Here, using lipid bilayers or plastic-based artificial APCs with defined components, we identify the critical APC-associated factors that confer agonist pMHCs with such potency. We found that CD4+ T cells are triggered by very low numbers of monomeric agonist pMHCs anchored on fluid lipid bilayers or fixed plastic surfaces, in the absence of any other APC surface molecules. Importantly, on bilayers, plastic surfaces, or real APCs, endogenous pMHCs did not enhance TCR triggering. TCR triggering, however, critically depended upon the adhesiveness of the surface and an intact T cell actin cytoskeleton. Based on these observations, we propose the receptor deformation model of TCR triggering to explain the remarkable sensitivity and specificity of TCR triggering.

Cancer Cell-Derived Exosomes Promote HCC Tumorigenesis Through Hedgehog Pathway.

PURPOSE: Hepatocellular carcinoma (HCC) accounts for more than 80% of primary liver cancers and is one of the leading causes of cancer-related death in many countries. Cancer cell-derived exosomes are shown to mediate communications between cancer cells and the microenvironment, promoting tumorigenesis. Hedgehog signaling pathway plays important roles in cancer development of HCC. METHODS: Exosomes were isolated from culture medium of HCC cell lines PLC/PRF/5 and MHCC-97H and were found to promote cancer cell growth measured with cell proliferation and colony formation assay. HCC cells cultured with cancer cell-derived exosome had increased cancer stem cell (CSC) population demonstrated by increased cell sphere formation CSC marker expressions. Hedgehog protein Shh was found to be highly expressed in these two HCC cell lines and preferably carried by exosomes. When Shh was knocked down with shRNA, the resulting exosomes had a reduced effect on promoting cancer cell growth or CSC population increase compared to normal cell-derived exosomes. RESULTS: The ability of PLC/PRF/5 cells to form tumor in a xenograft model was increased by the addition of the exosomes from control cancer cells but not the exosomes from Shh knocked down cancer cells. Finally, the higher plasma Exo-Shh levels were associated with later tumor stages, higher histological grades, multiple tumors, and higher recurrence rates. CONCLUSION: This study demonstrated that HCC cells secreted Shh via exosome and promote tumorigenesis through the activated Hedgehog pathway.

The receptor deformation model of TCR triggering.

Through T cell receptors (TCRs), T cells can detect and respond to very small numbers of foreign peptides among a huge number of self-peptides presented by major histocompatibility complexes (pMHCs) on the surface of antigen-presenting cells (APCs). How T cells achieve such remarkable sensitivity and specificity through pMHC-TCR binding is an intensively pursued issue in immunology today; the key question is how pMHC-TCR binding initiates, or triggers, a signal from TCRs. Multiple competing models have been proposed, none of which fully explains the sensitivity and specificity of TCR triggering. What has been omitted from existing theories is that the pMHC-TCR interaction at the T cell/APC interface must be under constant mechanical stress, due to the dynamic nature of cell-cell interaction. Taking this condition into consideration, we propose the receptor deformation model of TCR triggering. In this model, TCR signaling is initiated by conformational changes of the TCR/CD3 complex, induced by a pulling force originating from the cytoskeleton and transmitted through pMHC-TCR binding interactions with enough strength to resist rupture. By introducing mechanical force into a model of T cell signal initiation, the receptor deformation model provides potential mechanistic solutions to the sensitivity and specificity of TCR triggering.

Cortical Circuit Dynamics Are Homeostatically Tuned to Criticality In Vivo.

Homeostatic mechanisms stabilize neuronal activity in vivo, but whether this process gives rise to balanced network dynamics is unknown. Here, we continuously monitored the statistics of network spiking in visual cortical circuits in freely behaving rats for 9 days. Under control conditions in light and dark, networks were robustly organized around criticality, a regime that maximizes information capacity and transmission. When input was perturbed by visual deprivation, network criticality was severely disrupted and subsequently restored to criticality over 48 h. Unexpectedly, the recovery of excitatory dynamics preceded homeostatic plasticity of firing rates by >30 h. We utilized model investigations to manipulate firing rate homeostasis in a cell-type-specific manner at the onset of visual deprivation. Our results suggest that criticality in excitatory networks is established by inhibitory plasticity and architecture. These data establish that criticality is consistent with a homeostatic set point for visual cortical dynamics and suggest a key role for homeostatic regulation of inhibition.

Poly (propylene fumarate)/ß-calcium phosphate composites for enhanced bone repair.

A composite based on poly (propylene fumarate) (PPF) was investigated as a potential bone repair material for clinical use and it showed low heat release, suitable mechanical property and good biocompatibility. The in situ curing process would finish in less than 10 min. Compared with PMMA, PPF/TCP showed great decrease in heat release as the maximum temperature during curing process was 54.7 °C ± 1.69 °C. The compressive strength was between 109 ± 2 and 133 ± 6 MPa and the compressive modulus was 146 ± 11 to 161 ± 27 MPa, which were believed to be compatible and further supportive to surrounding bone. Besides, the surface morphology and hydrophilicity could be tailored by adjusting the content of ß-calcium phosphate (ß-TCP). Relatively stable pH value during degradation in PBS solution implied that it would not bring about acidification when implanted in vivo. In addition, PPF/TCP would boost mineralization and the apatite-like deposits on surface may advance the integrity of bone and materials. Moreover, the PPF/TCP obviously degraded and new bone formed especially when loaded with recombinant human bone morphogenetic protein-2 (rhBMP-2) in vivo. In summary, PPF/TCP composites showed suitable physical and chemical properties as well as good bioactivity and may therefore be a promising material for bone repair.

The Influence of Tool Rake Surface Geometry on the Hard Turning Process of AISI52100 Hardened Steel.

The hard turning process has been widely used in the field of hard material precision machining because of its high efficiency, low processing residual stress, and low environmental pollution. Due to its undesirably processing quality, it is still not a substitute for traditional grinding, so many studies have reported that the process has been optimized. However, there has been little research on the geometry optimization of hard cutting tools, which have a great influence on the traditional machining process. In this paper, two tools with different rake face shapes are designed. The finite element analysis method is used to compare their performance with a conventional plane tool while turning hardened steel. The results show that the cutting performance of the designed tool T1 and T2 (chip morphology, cutting force, and cutting temperature) and the quality of the machined surface are improved compared with the tool. The cutting force decreased by 12.72% and 14.74%, the cutting temperature decreased by 7.56% and 9.01%, respectively, and the surface residual stress decreased by 26.56% and 28.66%.