Novel immunosuppressive effect of FK506 by upregulation of PD-L1 via FKBP51 in heart transplantation.

The calcineurin inhibitor-FK506-is a first-line immunosuppressant that regulates T cell secretion of IL-2 and other cytokines. However, the mechanism of its protective effect on target cells and its role on tumour recurrence and interaction with anti-tumour immune checkpoint inhibitors, such as PD-L1 blocking, are still unclear. Here, in a murine heart transplantation model, we observed the upregulation of programmed death-ligand 1 (PD-L1) expression by FK506 in both dendritic cells (DCs) and allografts. Blocking PD-L1 during FK506 treatment increased IFN-γ and TNF-α expression, enhanced CD4+ and CD8+ T cell proliferation, and suppressed Treg differentiation. Moreover, PD-L1 decreased T cell infiltration and induced T cell apoptosis in both the spleen and graft. PD-L1 was not only required in FK506-mediated immunosuppression but also upregulated by FK506. Treatment with SAFit2, a FKBP51 selective inhibitor, reduced the expression of PD-L1 on DCs and the grafts and interfered with the immunosuppressive effect of FK506, suggesting that the mechanism depends on FK506-binding protein (FKBP) 51 expression. Overall, our results add new insights into the role of FK506, not only on T cell cytokine secretion but also on co-inhibitory molecular regulation and target cell immune privilege.

A bidirectional Hopf bifurcation analysis of Parkinson's oscillation in a simplified basal ganglia model.

In this paper, we study the parkinson oscillation mechanism in a computational model by bifurcation analysis and numerical simulation. Oscillatory activities can be induced by abnormal coupling weights and delays. The bidirectional Hopf bifurcation phenomena are found in simulations, which can uniformly explain the oscillation mechanism in this model. The Hopf1 represents the transition between the low firing rate stable state (SS) and oscillation state (OS), the Hopf2 represents the transition between the high firing rate stable state (HSS) and the OS, the mechanisms of them are different. The Hopf1 and Hopf2 bifurcations both show that when the state transfers from the stable region to the oscillation region, oscillatory activities originate from the beta frequency band or the gamma frequency band. We find that the changing trends of the frequency (DF) and oscillation amplitude (OSAM) are contrary in many cases. The effect of the delay in inhibitory pathways is greater than that of in excitatory pathways, and appropriate delays improve the discharge activation level (DAL) of the system. In all, we infer that oscillations can be induced by the follow factors: 1. Improvement of the DAL of the globus pallidus externa (GPe); 2. Reduce the DAL of the GPe from the HSS or the discharge saturation state; 3. The GPe can also resonate with the subthalamic nucleus (STN).

Decompression-Induced Diamond Formation from Graphite Sheared under Pressure.

Graphite is known to transform into diamond under dynamic compression or under combined high pressure and high temperature, either by a concerted mechanism or by a nucleation mechanism. However, these mechanisms fail to explain the recently reported discovery of diamond formation during ambient temperature compression combined with shear stress. Here we report a new transition pathway for graphite to diamond under compression combined with shear, based on results from both theoretical simulations and advanced experiments. In contrast to the known model for thermally activated diamond formation under pressure, the shear-induced diamond formation takes place during the decompression process via structural transitions. At a high pressure with large shear, graphite transforms into ultrastrong sp^{3} phases whose structures depend on the degree of shear stress. These metastable sp^{3} phases transform into either diamond or graphite upon decompression. Our results explain several recent experimental observations of low-temperature diamond formation. They also emphasize the importance of shear stress for diamond formation, providing new insight into the graphite-diamond transformation mechanism.

Evaluation of ESA Active, Passive and Combined Soil Moisture Products Using Upscaled Ground Measurements.

The European Space Agency (ESA) Climate Change Initiative (CCI) project combines multi-sensors at different microwave frequencies to derive three harmonized soil moisture products using active, passive and combined approaches. These long-term soil moisture products assist in understanding the global water and carbon cycles. However, extensive validations are a prerequisite before applying the retrieved soil moisture into climatic or hydrological models. To fulfill this objective, we assess the performances of three CCI soil moisture products (active, passive and combined) with respect to in-situ soil moisture networks located in China, Spain and Canada. In order to compensate the scale differences between ground stations and the CCI product's coarse resolution, we adopted two upscaling approaches of Inverse Distance Weighting (IDW) interpolation and simple Arithmetic Mean (AM). The temporal agreements between the satellite retrieved and ground-measured soil moisture were quantified using the unbiased root mean square error (ubRMSE), RMSE, correlation coefficients (R) and bias. Furthermore, the temporal variability of the CCI soil moisture is interpreted and verified with respect to the Tropical Rainfall Measuring Mission (TRMM) precipitation observations. The results show that the temporal variations of CCI soil moisture agreed with the in-situ ground measurements and the precipitation observations over the China and Spain test sites. In contrast, a significant overestimation was observed over the Canada test sites, which may be due to the strong heterogeneity in soil and vegetation characteristics in accordance with the reported poor performance of soil moisture retrieval there. However, despite a retrieval bias, the relatively temporal variation of the CCI soil moisture also followed the ground measurements. For all the three test sites, the soil moisture retrieved from the combined approach outperformed the active-only and passive-only methods, with ubRMSE of 0.034, 0.050, and 0.050-0.054 m3/m3 over the test sites in China, Spain and Canada, respectively. Thus, the CCI combined soil moisture product is suggested to drive the climatic and hydrological studies.

Mathematical derivation and mechanism analysis of beta oscillations in a cortex-pallidum model.

In this paper, we develop a new cortex-pallidum model to study the origin mechanism of Parkinson's oscillations in the cortex. In contrast to many previous models, the globus pallidus internal (GPi) and externa (GPe) both exert direct inhibitory feedback to the cortex. Using Hopf bifurcation analysis, two new critical conditions for oscillations, which can include the self-feedback projection of GPe, are obtained. In this paper, we find that the average discharge rate (ADR) is an important marker of oscillations, which can divide Hopf bifurcations into two types that can uniformly be used to explain the oscillation mechanism. Interestingly, the ADR of the cortex first increases and then decreases with increasing coupling weights that are projected to the GPe. Regarding the Hopf bifurcation critical conditions, the quantitative relationship between the inhibitory projection and excitatory projection to the GPe is monotonically increasing; in contrast, the relationship between different coupling weights in the cortex is monotonically decreasing. In general, the oscillation amplitude is the lowest near the bifurcation points and reaches the maximum value with the evolution of oscillations. The GPe is an effective target for deep brain stimulation to alleviate oscillations in the cortex.

An umbrella-inspired snap-on robotic 3D photoacoustic endoscopic probe for augmented intragastric sensing: Proof of concept study.

In this paper, we present a novel on-demand modular robotic photoacoustic tomography (PAT) probe integrated into an endoscopic device, potentially for deep intragastric sensing. The proposed solution offers a plug-and-play approach through the use of meso-scale steerable endoscopy and a new 'snap-on' 3D robotic PAT probe that can reconfigure the geometry of the intracorporeal light delivery, inspired by an umbrella structure. Specifically, using the limited esophageal access, steerable endoscopy allows navigation and advancement of a distally mounted robotic add-on for PAT that is folded until it reaches the deep-seated gastric lesion. Once the tip is positioned near the lesion site in the gastric cavity, there is ample working space for the robotic probe to adjust its umbrella-like unfolded shape. This allows fine-tuning of the laser delivery orientation of the fiber bundles to achieve the lesion-specific light delivery scheme. This design allows volumetric imaging of the intragastric PAT with enhanced sensitivity. To evaluate the performance of the modular robotic PAT probe, we performed a simulation analysis of the light intensity and ultrasound field distribution. The simulation results show that the robotic probe is feasible for intracorporeal PAT imaging. In addition, we printed a 3D model of a human stomach containing a simulated gastric tumour. Both the phantom and ex vivo experimental results validate the feasibility of the proposed robotic PAT probe.

Photoacoustic imaging plus X: a review.

Significance: Photoacoustic (PA) imaging (PAI) represents an emerging modality within the realm of biomedical imaging technology. It seamlessly blends the wealth of optical contrast with the remarkable depth of penetration offered by ultrasound. These distinctive features of PAI hold tremendous potential for various applications, including early cancer detection, functional imaging, hybrid imaging, monitoring ablation therapy, and providing guidance during surgical procedures. The synergy between PAI and other cutting-edge technologies not only enhances its capabilities but also propels it toward broader clinical applicability. Aim: The integration of PAI with advanced technology for PA signal detection, signal processing, image reconstruction, hybrid imaging, and clinical applications has significantly bolstered the capabilities of PAI. This review endeavor contributes to a deeper comprehension of how the synergy between PAI and other advanced technologies can lead to improved applications. Approach: An examination of the evolving research frontiers in PAI, integrated with other advanced technologies, reveals six key categories named "PAI plus X." These categories encompass a range of topics, including but not limited to PAI plus treatment, PAI plus circuits design, PAI plus accurate positioning system, PAI plus fast scanning systems, PAI plus ultrasound sensors, PAI plus advanced laser sources, PAI plus deep learning, and PAI plus other imaging modalities. Results: After conducting a comprehensive review of the existing literature and research on PAI integrated with other technologies, various proposals have emerged to advance the development of PAI plus X. These proposals aim to enhance system hardware, improve imaging quality, and address clinical challenges effectively. Conclusions: The progression of innovative and sophisticated approaches within each category of PAI plus X is positioned to drive significant advancements in both the development of PAI technology and its clinical applications. Furthermore, PAI not only has the potential to integrate with the above-mentioned technologies but also to broaden its applications even further.

Electroencephalographic Signal Data Augmentation Based on Improved Generative Adversarial Network.

EEG signals combined with deep learning play an important role in the study of human-computer interaction. However, the limited dataset makes it challenging to study EEG signals using deep learning methods. Inspired by the GAN network in image generation, this paper presents an improved generative adversarial network model L-C-WGAN-GP to generate artificial EEG data to augment training sets and improve the application of BCI in various fields. The generator consists of a long short-term memory (LSTM) network and the discriminator consists of a convolutional neural network (CNN) which uses the gradient penalty-based Wasserstein distance as the loss function in model training. The model can learn the statistical features of EEG signals and generate EEG data that approximate real samples. In addition, the performance of the compressed sensing reconstruction model can be improved by using augmented datasets. Experiments show that, compared with the existing advanced data amplification techniques, the proposed model produces EEG signals closer to the real EEG signals as measured by RMSE, FD and WTD indicators. In addition, in the compressed reconstruction of EEG signals, adding the new data reduces the loss by about 15% compared with the original data, which greatly improves the reconstruction accuracy of the EEG signals' compressed sensing.

The mechanism of Parkinson oscillation in the cortex: Possible evidence in a feedback model projecting from the globus pallidus to the cortex.

The origin, location and cause of Parkinson's oscillation are not clear at present. In this paper, we establish a new cortex-basal ganglia model to study the origin mechanism of Parkinson beta oscillation. Unlike many previous models, this model includes two direct inhibitory projections from the globus pallidus external (GPe) segment to the cortex. We first obtain the critical calculation formula of Parkinson's oscillation by using the method of Quasilinear analysis. Different from previous studies, the formula obtained in this paper can include the self-feedback connection of GPe. Then, we use the bifurcation analysis method to systematically explain the influence of some key parameters on the oscillation. We find that the bifurcation principle of different cortical nuclei is different. In general, the increase of the discharge capacity of the nuclei will cause oscillation. In some special cases, the sharp reduction of the discharge rate of the nuclei will also cause oscillation. The direction of bifurcation simulation is consistent with the critical condition curve. Finally, we discuss the characteristics of oscillation amplitude. At the beginning of the oscillation, the amplitude is relatively small; with the evolution of oscillation, the amplitude will gradually strengthen. This is consistent with the experimental phenomenon. In most cases, the amplitude of cortical inhibitory nuclei (CIN) is greater than that of cortical excitatory nuclei (CEX), and the two direct inhibitory projections feedback from GPe can significantly reduce the amplitude gap between them. We calculate the main frequency of the oscillation generated in this model, which basically falls between 13 and 30 Hz, belonging to the typical beta frequency band oscillation. Some new results obtained in this paper can help to better understand the origin mechanism of Parkinson's disease and have guiding significance for the development of experiments.

The inhibition mechanism of epilepsy disease in a computational model.

BACKGROUND: The mechanism of prevention and treatment of epilepsy is a hot issue in theoretical research. OBJECTIVE: In this paper, we studied the control mechanism of the generalized spike-and-wave discharges (GSWD) by different types of external electrical stimulation acting on the subthalamic nucleus (STN) in a computational model. METHODS: Firstly, we analyzed the pathological mechanism of seizures, which were induced by different parameters in the thalamocortical (TC) circuit. Then, a voltage V was exerted in the STN. At last, we used the sine wave and square wave current stimulation in the STN. RESULTS: We found that seizures can be inhibited by tuning stimulus intensity into suitable range, and the direction of adjustment depended on the size of the parameter. We observed that the seizure can also be inhibited by tuning different parameters in current. CONCLUSIONS: Different inhibition mechanisms can be explained in this model, which may provide theoretical evidences for selecting the optimal treatment scheme in the clinical.

Existence of solutions of an impulsive integro-differential equation with a general boundary value condition.

In this paper, we discuss the existence of solutions for a first-order nonlinear impulsive integro-differential equation with a general boundary value condition. New comparison principles are developed, and existence results for extremal solutions are obtained using the established principles and the monotone iterative technique. The results are more general than those of the periodic boundary problems, which may be widely applied in this field.

Revealing Spatial Patterns of Cultural Ecosystem Services in Four Agricultural Landscapes: A Case Study from Hangzhou, China.

Monitoring and mapping agricultural cultural ecosystem services (CES) is essential, especially in areas with a sharp contradiction between agricultural land protection and urban development. Despite research assessing CES increasing exponentially in recent years, our knowledge of the CES of agricultural landscapes is still inadequate. This study used four types of agricultural landscapes in Hangzhou, China, as the study area, analyzed their CES spatial patterns, and explored their societal preferences by integrating the multi-sourced datasets, clustering algorithms, and Maxent model. The results indicated that hot spots of agricultural CES correspond to river valley plains, which were also easily vulnerable to urbanization. Moreover, we found that the CES level of paddy field and dry farmland were higher than tea garden and orchard. Based on the above spatial patterns of supply, demand, and flow of CES, we identified four groups of agricultural land by cluster analysis, distinguishing between significant, unimportant, little used, and potential CES. Further, our results showed that natural and human factors could explain societal preferences. This study can provide a valuable basis for stakeholders to develop balanced strategies by the aforementioned results.

SentiVec: Learning Sentiment-Context Vector via Kernel Optimization Function for Sentiment Analysis.

Deep learning-based sentiment analysis (SA) methods have drawn more attention in recent years, which calls for more precise word embedding methods. This article proposes SentiVec, a kernel optimization function system for sentiment word embedding, which is based on two phases. The first phase is a supervised learning method, and the second phase consists of two unsupervised updating models, object-word-to-surrounding-words reward model (O2SR) and context-to-object-word reward model (C2OR). SentiVec is aimed at: 1) integrating the statistical information and sentiment orientation into sentiment word vectors and 2) propagating and updating the semantic information to all the word representations in a corpus. Extensive experimental results show that the optimal sentiment vectors successfully extract the features in terms of semantic and sentiment information, which makes it outperform the baseline methods on word similarity, word analogy, and SA tasks.

Hierarchical Hydrogels with Ordered Micro-Nano Structures for Cancer-on-a-Chip Construction.

In the drug therapy of tumor, efficient and stable drug screening platforms are required since the drug efficacy varies individually. Here, inspired by the microstructures of hepatic lobules, in which hepatocytes obtain nutrients from both capillary vessel and the central vein, we present a novel hierarchical hydrogel system with ordered micro-nano structure for liver cancer-on-a-chip construction and drug screening. The hierarchical hydrogel system was fabricated by using pregel to fill and replicate self-assembled colloidal crystal arrays and microcolumn array template. Due to the synergistic effect of its interconnected micro-nano structures, the resultant system could not only precisely control the size of cell spheroids but also realize adequate nutrient supply of cell spheroids. We have demonstrated that by integrating the hierarchical hydrogel system into a multichannel concentration gradients microfluidic chip, a functional liver cancer-on-a-chip could be constructed for high-throughput drug screening with good repeatability and high accuracy. These results indicated that the hierarchical hydrogel system and its derived liver cancer-on-a-chip are ideal platforms for drug screening and have great application potential in the field of personalized medicine.

The therapeutic mechanism of epilepsy seizures in different target areas: Research on a theoretical model.

BACKGROUND: The selection of optimal target areas in the surgical treatment of epilepsy is always a difficult problem in medicine. OBJECTIVE: We employed a theoretical calculation model to explore the control mechanism of seizures by an external voltage stimulus acting in different nerve nuclei. METHODS: Theoretical analysis and numerical simulation were combined. RESULTS: The globus pallidus, excitatory pyramidal neurons, striatal D1 neurons, thalamic reticular nucleus and specific relay nuclei were selected, we analyzed that the electrical stimulation has different effects in these target areas. CONCLUSIONS: The data selected were reasonable in study, the results may give a theoretical support for similar studies in clinical.

Photoacoustic Characterization of Cortical and Cancellous Bone in The Vertebrae.

To date, spinal problems are not rare, and relevant therapies are always required. Although the combination of photoacoustic imaging (PAI) and spinal fusion surgery, a widely applied operation for spinal cures, is unprecedented, we assume that such combination might improve the accuracy and safety of the surgery. This paper aims to testify that PAI is effective in monitoring and navigating during spinal fusion surgery. Specifically, we examined the optical absorption spectrum of bones to determine the optimal laser wavelength as 532nm. Afterwards, we measured the photoacoustic signals of this bone samples, discovering that the signals of two kinds of samples, cortical bone and cancellous bone, differ considerably in frequency domain. It demonstrated the feasibility that PAI is effective enough to distinguish different bone tissues during the spinal fusion surgery.

Molecular genetics with clinical characteristics of Leber congenital amaurosis in the Han population of western China.

Purpose: Leber congenital amaurosis (LCA) is one of the earliest inherited retinal dystrophies (IRD) that leads to blindness. To date, there have been 25 LCA-associated genes reported in China as well as other countries. The current study aimed to present the dominant molecular genetics and clinical features of LCA in the Han population of western China.Methods: Our study comprised 37 patients with strictly defined Leber congenital amaurosis in a cohort of IRD (2009-2019). The mutations were detected by targeted next-generation sequencing (NGS), Sanger sequencing, and segregation analysis. The patients underwent comprehensive clinical examinations, analysis of phenotypes and genotypes.Results: Out of the 37 patients, 34 harbored known LCA genes; the detection rate of mutations was 91.9%. Forty-seven different alleles incorporated 21 novel mutations; 8 were known LCA-associated genes. The three most frequently mutated genes included CRB1 (27.0%), RDH12 (24.3%), and RPGRIP1 (18.9%). The CRB1-associated LCA showed a pigmented fundus; the RDH12-associated LCA featured macular atrophy. Our results revealed that CRB1 and RPGRIP1 genes occupied a greater proportion in the western Chinese population. The proportion of these two genes was similar in other regions of China as well. The difference existed in a larger proportion of RDH12-associated LCA in the western Chinese population.Conclusions: The new findings in our study group polished the spectrum of the novel mutations and phenotypes of LCA with regional and ethnic variations. This comprehensive database can provide essential information for gene therapies.

Pressure tuned photoluminescence and band gap in two-dimensional layered g-C3N4: the effect of interlayer interactions.

We show that the photoluminescence (PL) emission color of few layered g-C3N4 (FL-CN) can be tuned from blue to yellow by applying pressure. FL-CN also exhibits an anomalous PL enhancement and obvious change in the light absorption at very low pressure. Further studies reveal that the increase of pressure-induced interlayer interactions affects the charge separation of photo-induced electrons and holes and thus leads to PL enhancement. An obvious decrease in interlayer compressibility probably due to interlayer stacking transition in FL-CN has been observed at above 3 GPa, which becomes less compressible than that of graphite, accompanied by obvious PL intensity weakening and emission band broadening. The results suggest that interlayer interactions may play dominant roles in the optical properties of FL-CN, shedding new insights into our understanding on PL engineering in g-C3N4.

Pressure-induced SERS enhancement in a MoS2/Au/R6G system by a two-step charge transfer process.

Pressure-induced surface-enhanced Raman spectroscopy (PI-SERS) represents a new frontier in the research field of SERS. However, relatively few studies have focused on PI-SERS due to many difficulties, such as easy aggregation of nanoparticles, and difficulty in understanding the interaction mechanisms between probe molecules and the SERS substrate at high pressure. Here we developed an efficient semiconductor-metal SERS substrate (MoS2/Au) to study PI-SERS. Different from the previously reported monotonous decrease in Raman intensities upon compression, an anomalous Raman enhancement of R6G molecules adsorbed on the MoS2/Au substrate was observed up to 2.39 GPa, at which the degree of charge transfer (ρCT) between the R6G molecules and the MoS2/Au substrate reaches a maximum. By comparison, it is proposed that the decoration of Au on the SERS system could bring about a two-step charge transfer (CT) process, introduce localized surface plasmon resonance (LSPR), and thus favor the PI-SERS enhancement. Moreover, this charge transfer also causes obvious changes in the optical behaviors of R6G molecules upon compression. This brings new insights into the SERS study and also offers new ideas for the development of SERS application in high pressure studies.

Circulating tumor cells in early stage lung adenocarcinoma: a case series report and literature review.

PURPOSE: The study aimed to monitor circulating tumor cells (CTCs) in early stage lung adenocarcinoma patients. RESULTS: CTCs were characterized and classified to epithelial (E-) CTCs, mesenchymal (M-) CTCs and epithelial- mesenchymal (E&M-) CTCs, as per epithelial-mesenchymal transition(EMT) biomarkers. CTCs could not be found in healthy controls. However, in cohort A, CTCs were found in 17 (17/18) cases. Detection rate of E-CTCs was lower (5/18) compared with M-CTC (10/18) or E&M-CTC (14/18). Highly abundant M-CTCs were prone to being in the tumors > 2 cm. In cohorts A and B, CTCs count increased significantly in all patients with tumor progression (7/7). Higher CTCs level or change range could be found postoperatively in the patients with tumor progression, as compared with patients with disease free survival (P < 0.01). Additionally, CTCs detected by CanPatrolTM could be validated by CytoploRare or Pep@MNPs. MATERIALS AND METHODS: We included four cohorts of patients and 20 healthy controls. In cohort A, CTCs were detected by a newly established approach, i.e., CanPatrolTM, prior to anesthesia and monitored after operation longitudinally. In cohort B, CTCs were not assessed prior to operation, but were longitudinally detected after operation. For validation, we detected FOLR(+)-CTCs by using CytoploRare and EPCAM(+)-CTCs by using Pep@MNPs prior to operation, in cohorts C and D, respectively. CONCLUSION: CTCs can be detected in early stage lung adenocarcinoma, even in adenocarcinoma in situ, and CTCs detection can effectively monitor tumor progression. The distinguishing of biomarkers of highly invasive and aggressive CTCs warrants further robust study.