Phosphoantigens glue butyrophilin 3A1 and 2A1 to activate Vγ9Vδ2 T cells.

In both cancer and infections, diseased cells are presented to human Vγ9Vδ2 T cells through an 'inside out' signalling process whereby structurally diverse phosphoantigen (pAg) molecules are sensed by the intracellular domain of butyrophilin BTN3A11-4. Here we show how-in both humans and alpaca-multiple pAgs function as 'molecular glues' to promote heteromeric association between the intracellular domains of BTN3A1 and the structurally similar butyrophilin BTN2A1. X-ray crystallography studies visualized that engagement of BTN3A1 with pAgs forms a composite interface for direct binding to BTN2A1, with various pAg molecules each positioned at the centre of the interface and gluing the butyrophilins with distinct affinities. Our structural insights guided mutagenesis experiments that led to disruption of the intracellular BTN3A1-BTN2A1 association, abolishing pAg-mediated Vγ9Vδ2 T cell activation. Analyses using structure-based molecular-dynamics simulations, 19F-NMR investigations, chimeric receptor engineering and direct measurement of intercellular binding force revealed how pAg-mediated BTN2A1 association drives BTN3A1 intracellular fluctuations outwards in a thermodynamically favourable manner, thereby enabling BTN3A1 to push off from the BTN2A1 ectodomain to initiate T cell receptor-mediated γδ T cell activation. Practically, we harnessed the molecular-glue model for immunotherapeutics design, demonstrating chemical principles for developing both small-molecule activators and inhibitors of human γδ T cell function.

Multi-omic analysis revealed the immunological patterns and diagnostic value of exhausted T cell-derived PTTG1 in patients with psoriasis.

BACKGROUND: Psoriasis, characterized by chronic inflammation, is a persistent skin condition that is notoriously challenging to manage and prone to relapse. Despite significant advancements in its treatment, many adverse reactions still occur. Therefore, exploring the mechanisms behind the occurrence and development of psoriasis is extremely important. METHODS: The weighted correlation network analysis (WGCNA) algorithm was used to identify phenotype-related genes in patients with psoriasis. We recruited clinical samples of patients with psoriasis, and used single-cell RNA sequencing (scRNA-seq) to visualize divergent genes and metabolisms of varied cells for the psoriasis. Various machine-learning methods were used to identify core genes, and molecular docking was used to analyze the stability of leptomycin B targeting pituitary tumor transforming 1 (PTTG1). Immunofluorescence (IHC) analysis, multiplex immunofluorescence (mIF) analysis, and quantitative reverse transcription polymerase chain reaction (qRT-PCR) were used to validate the results. RESULTS: Our results identified 1391 genes associated with the phenotype in patients with psoriasis and highlighted the significant alterations in T-cell functionality observed in the disease by WGCNA. There were nine distinct cellular clusters in psoriasis analyzed with the aid of scRNA-seq data. Each subtype of cell exhibited distinct genetic profiles, functional roles, signaling mechanisms, and metabolic characteristics. Machine-learning methods further demonstrated the potential diagnostic value of T cell-derived PTTG1 and its relationship with T-cell exhaustion in psoriasis. Lastly, the leptomycin B was scrutinized and verified had high stability targeting PTTG1. CONCLUSIONS: This study elucidates the biological basis of psoriasis. At the same time, it was discovered that PTTG1 derived from exhausted T cells serves as a diagnostic biomarker for psoriasis. Leptomycin B could be a potential drug for targeted treatment of psoriasis on PTTG1.

Proteomic characterization of murine hematopoietic stem progenitor cells reveals dynamic fetal-to-adult changes in metabolic-related pathways.

Hematopoietic stem progenitor cells (HSPCs) give rise to the hematopoietic system, maintain hematopoiesis throughout the lifespan, and undergo molecular and functional changes during their development and aging. The importance of hematopoietic stem cell (HSC) biology has led to their extensive characterization at genomic and transcriptomic levels. However, the proteomics of HSPCs throughout the murine lifetime still needs to be fully completed. Here, using mass spectrometry (MS)-based quantitative proteomics, we report on the dynamic changes in the proteome of HSPCs from four developmental stages in the fetal liver (FL) and the bone marrow (BM), including E14.5, young (2 months), middle-aged (8 months), and aging (18 months) stages. Proteomics unveils highly dynamic protein kinetics during the development and aging of HSPCs. Our data identify stage-specific developmental features of HSPCs, which can be linked to their functional maturation and senescence. Our proteomic data demonstrated that FL HSPCs depend on aerobic respiration to meet their proliferation and oxygen supply demand, while adult HSPCs prefer glycolysis to preserve the HSC pool. By functional assays, we validated the decreased mitochondrial metabolism, glucose uptake, reactive oxygen species (ROS) production, protein synthesis rate, and increased glutathione S-transferase (GST) activity during HSPC development from fetal to adult. Distinct metabolism pathways and immune-related pathways enriched in different HSPC developmental stages were revealed at the protein level. Our study will have broader implications for understanding the mechanism of stem cell maintenance and fate determination and reversing the HSC aging process.

Reconstruction for beam blockage of lidar based on generative adversarial networks.

Doppler lidar is an active laser remote sensing instrument. However, beam blockage caused by low-altitude obstacles is a critical factor affecting the quality of lidar data. To reconstruct the line of sight velocities (LOSV) in areas with beam blockages and to evaluate the effectiveness of reconstruction results, the LOSV-filling network (LFnet) approach based on generative adversarial networks (GANs) and an evaluation scheme based on the degree of blockage are proposed in this paper. The LFnet comprises two adversarial models. The first adversarial model captures the structural features of LOSV to output the edge map, and the second adversarial fills in the blockage area using the edge map. We have built a packaged dataset consisting of training, validation and test datasets with mask sets. Then the sensitivity of the reconstruction effectiveness with different shielding conditions is studied, to reveal the mechanism of shielding influencing the reconstruction. A series of indicators were used to evaluate the model's performance, including the traditional indicators and the proposed indicator of root mean square error (RMSE). Finally, LFnet was demonstrated in a practical application in an airport. The complete process of an easterly gust front is reconstructed with RMSE less than 0.85 m/s, which has significance for flight safety.

Sequential covariate-adjusted randomization via hierarchically minimizing Mahalanobis distance and marginal imbalance.

In comparative studies, covariate balance and sequential allocation schemes have attracted growing academic interest. Although many theoretically justified adaptive randomization methods achieve the covariate balance, they often allocate patients in pairs or groups. To better meet the practical requirements where the clinicians cannot wait for other participants to assign the current patient for some economic or ethical reasons, we propose a method that randomizes patients individually and sequentially. The proposed method conceptually separates the covariate imbalance, measured by the newly proposed modified Mahalanobis distance, and the marginal imbalance, that is the sample size difference between the 2 groups, and it minimizes them with an explicit priority order. Compared with the existing sequential randomization methods, the proposed method achieves the best possible covariate balance while maintaining the marginal balance directly, offering us more control of the randomization process. We demonstrate the superior performance of the proposed method through a wide range of simulation studies and real data analysis, and also establish theoretical guarantees for the proposed method in terms of both the convergence of the imbalance measure and the subsequent treatment effect estimation.

Covalent Bonding of Salen Metal Complexes with Pyrene Chromophores to Porous Polymers for Photocatalytic Hydrogen Evolution.

The development of low-cost and efficient photocatalysts to achieve water splitting to hydrogen (H2) is highly desirable but remains challenging. Herein, we design and synthesize two porous polymers (Co-Salen-P and Fe-Salen-P) by covalent bonding of salen metal complexes and pyrene chromophores for photocatalytic H2 evolution. The catalytic results demonstrate that the two polymers exhibit excellent catalytic performance for H2 generation in the absence of additional noble-metal photosensitizers and cocatalysts. Particularly, the H2 generation rate of Co-Salen-P reaches as high as 542.5 µmol g-1 h-1, which is not only 6 times higher than that of Fe-Salen-P but also higher than a large amount of reported Pt-assisted photocatalytic systems. Systematic studies show that Co-Salen-P displays faster charge separation and transfer efficiencies, thereby accounting for the significantly improved photocatalytic activity. This study provides a facile and efficient way to fabricate high-performance photocatalysts for H2 production.

High-Throughput Screening and Prediction of Nucleophilicity of Amines Using Machine Learning and DFT Calculations.

Nucleophilic index (NNu) as a significant parameter plays a crucial role in screening of amine catalysts. Indeed, the quantity and variety of amines are extensive. However, only limited amines exhibit an NNu value exceeding 4.0 eV, rendering them potential nucleophiles in chemical reactions. To address this issue, we proposed a computational method to quickly identify amines with high NNu values by using Machine Learning (ML) and high-throughput Density Functional Theory (DFT) calculations. Our approach commenced by training ML models and the exploration of Molecular Fingerprint methods as well as the development of quantitative structure-activity relationship (QSAR) models for the well-known amines based on NNu values derived from DFT calculations. Utilizing explainable Shapley Additive Explanation plots, we were able to determine the five critical substructures that significantly impact the NNu values of amine. The aforementioned conclusion can be applied to produce and cultivate 4920 novel hypothetical amines with high NNu values. The QSAR models were employed to predict the NNu values of 259 well-known and 4920 hypothetical amines, resulting in the identification of five novel hypothetical amines with exceptional NNu values (>4.55 eV). The enhanced NNu values of these novel amines were validated by DFT calculations. One novel hypothetical amine, H1, exhibits an unprecedentedly high NNu value of 5.36 eV, surpassing the maximum value (5.35 eV) observed in well-established amines. Our research strategy efficiently accelerates the discovery of the high nucleophilicity of amines using ML predictions, as well as the DFT calculations.

Highly Stretchable, Transparent, Self-Healing Ion-Conducting Elastomers for Long-Term Reliable Human Motion Detection.

The flexible electronic sensor is a critical component of wearable devices, generally requiring high stretchability, excellent transmittance, conductivity, self-healing capability, and strong adhesion. However, designing ion-conducting elastomers meeting all these requirements simultaneously remains a challenge. In this study, a novel approach is presented to fabricate highly stretchable, transparent, and self-healing ion-conducting elastomers, which are synthesized via photo-polymerization of two polymerizable deep eutectic solvents (PDESs) monomers, i.e., methacrylic acid (MAA)/choline chloride (ChCl) and itaconic acid (IA)/ChCl. The as-prepared ion-conducting elastomers possess outstanding properties, including high transparency, conductivity, and the capability to adhere to various substrates. The elastomers also demonstrate ultra-stretchability (up to 3900%) owing to a combination of covalent cross-linking and noncovalent cross-linking. In addition, the elastomers can recover up to 3250% strain and over 94.5% of their original conductivity after self-healing at room temperature for 5 min, indicating remarkable mechanical and conductive self-healing abilities. When utilized as strain sensors to monitor real-time motion of human fingers, wrist, elbow, and knee joints, the elastomers exhibit stable and strong repetitive electrical signals, demonstrating excellent sensing performance for large-scale movements of the human body. It is anticipated that these ion-conducting elastomers will find promising applications in flexible and wearable electronics.

Outcome evaluation of dye-assist arthroscopic inside-out ganglionectomy: a retrospective study of 29 patients.

OBJECTIVE: To evaluate the clinical outcomes of arthroscopic inside-out ganglionectomy of dominant dorsal wrist ganglion. METHODS: Patients with dominant wrist ganglion cyst treated in our hospital from January 1, 2014 to June 31, 2023 was enrolled in this retrospective analysis. All patients underwent dye-assist arthroscopic inside-out ganglionectomy. After discharge, the patients were followed for a minimum of 6 months. The primary outcomes were to assess patient wrist function using the Patient-Rated Wrist Evaluation (PRWE) and Mayo Modified Wrist Score (MMWS). The secondary outcomes were visual analog score (VAS), wrist active range of motion (ROM), grip strength, recurrence rate and complication. RESULTS: All ganglion were successfully resected after dye staining. Patients were followed for an average of 12.17 months. There were no significant changes between preoperative and postoperative wrist active ROM or grip strength, except for wrist flexion (which showed a slightly greater improvement after surgery, P = 0.049), there were notable improvements in VAS, MMWS, and PRWE postoperatively. Recurrence occurred in 3 patients. No major complications observed during the follow-up period. CONCLUSION: Dye-assist arthroscopic inside-out ganglionectomy is safe and uncomplicated, worth of clinical promotion.

[Chemical composition and pharmacological effects of Cinnamomum camphora chvar. borneol essential oil: a review].

Cinnamomum camphora chvar. borneol, a rare camphor tree variant recently identified in China, is distinguished by its high concentration of D-borneol, also known as " plant gold" due to its significant value. The essential oil extracted from this variant,rich in monoterpenes and sesquiterpenes, demonstrates a broad spectrum of pharmacological activities, including analgesic, antiinflammatory, antioxidant, cognition-enhancing, anti-bacterial, and insecticidal effects. These properties, underscored by extensive research, highlight the oil's potential in the biomedical, chemical, and food sectors as a valuable commodity. Nonetheless, the safety profile of this valuable oil remains poorly characterized, with its chemical composition and therapeutic efficacy subject to variations in the factors like geographic origin, harvesting timing, part used for extraction, and processing techniques. Such variability poses challenges to its clinical application and hampers the efficient exploitation of this resource. This review synthesizes current studies on C. camphora chvar. borneol essential oil and provides a detailed examination of its chemical and pharmacological profiles. In this study, we discuss existing research gaps and propose strategies for advancing its clinical use and industrial application, aiming to provide a foundational reference for future investigations and the resolution of its commercial and therapeutic challenges.

Mussel-Inspired, Underwater Self-Healing Ionoelastomers Based on α-Lipoic Acid for Iontronics.

Weak adhesion and lack of underwater self-healability hinder advancing soft iontronics particularly in wet environments like sweaty skin and biological fluids. Mussel-inspired, liquid-free ionoelastomers are reported based on seminal thermal ring-opening polymerization of a biomass molecule of α-lipoic acid (LA), followed by sequentially incorporating dopamine methacrylamide as a chain extender, N,N'-bis(acryloyl) cystamine, and lithium bis(trifluoromethanesulphonyl) imide (LiTFSI). The ionoelastomers exhibit universal adhesion to 12 substrates in both dry and wet states, superfast self-healing underwater, sensing capability for monitoring human motion, and flame retardancy. The underwater self-repairabilitiy prolongs over three months without deterioration, and sustains even when mechanical properties greatly increase. The unprecedented underwater self-mendability benefits synergistically from the maximized availability of dynamic disulfide bonds and diverse reversible noncovalent interactions endowed by carboxylic groups, catechols, and LiTFSI, along with the prevented depolymerization by LiTFSI and tunability in mechanical strength. The ionic conductivity reaches 1.4 × 10-6 -2.7 × 10-5 S m-1 because of partial dissociation of LiTFSI. The design rationale offers a new route for creating a wide range of LA- and sulfur-derived supramolecular (bio)polymers with superior adhesion, healability, and other functionalities, and thus has technological implications for coatings, adhesives, binders and sealants, biomedical engineering and drug delivery, wearable and flexible electronics, and human-machine interfaces.

Deciphering and investigating fragment mechanism of quinolones using multi-collision energy mass spectrometry and computational chemistry strategy.

RATIONALE: Quinolones show characteristic fragments in mass spectrometry (MS) analysis due to their common core structures, and energy-dependent differences among these fragments are generated through the same fragmentation pathway of different molecules. Computational chemistry, which provides quantitative results of molecule parameters, is helpful for investigating the mechanisms of chemistry. METHODS: MS/MS spectra of five quinolones, namely norfloxacin (NOR), enoxacin (ENO), enrofloxacin (ENR), gatifloxacin (GAT), and lomefloxacin (LOM), were acquired for deciphering fragmentation pathways under multi-collision energy (CE). Computational methods were used for excluding little possibility pathways from the point of view of energy and stable conformations, whereas optimized collision energy (OCE) and maximum relative intensity (MRI) of major competitive fragments were investigated and confirmed using computational results. RESULTS: Fragmentation results of NOR, ENO, ENR, and GAT were deciphered using experimental and computational data, of which fragmentation regularities were summarized. Fragmentation pathways of LOM were deciphered under the guidance of foregoing regularities. Meanwhile, the whole process was validated by comparing OCE and MRI and computational energy results, which showed good agreement. CONCLUSIONS: A strategy for explaining quinolone fragmentation results of multi-CE values and deciphering fragment mechanism using computational methods was developed. Relevant data and strategy may provide ideas for how to design and decipher new drug molecules with similar structures.

"One Stone Two Birds" Strategy of Synthesizing the Battery Material Lithium Sulfide: Aluminothermal Reduction of Lithium Sulfate.

Lithium sulfide (Li2S) is a critical material for clean energy technologies, i.e., the cathode material in lithium-sulfur batteries and the raw material for making sulfide solid electrolytes in all-solid-state batteries. However, its practical application at a large scale is hindered by its industrial production method of reducing lithium sulfate with carbon materials at high temperatures, which emits carbon dioxide and is time-consuming. We hereby report a method of synthesizing Li2S by thermally reducing lithium sulfate with aluminum. Compared with the carbothermal method, this aluminothermal approach has several advantages, such as operation at lower temperatures, completion in minutes, no emission of greenhouse gases, and valuable byproducts of aluminum oxide (Al2O3). The home-made Li2S demonstrates competitive performance in battery tests versus the commercial counterpart. Moreover, using the byproduct Al2O3 to coat the cathode side of the separator can enhance the battery's capacity without influencing its rate capability. Thus, this "one stone two birds" method has great potential for practical applications of developing Li-S batteries.

ABTS as Both Activator and Electron Shuttle to Activate Persulfate for Diclofenac Degradation: Formation and Contributions of ABTS•+, SO4•-, and •OH.

The activation of peroxydisulfate (PDS) by organic compounds has attracted increasing attention. However, some inherent drawbacks including quick activator decomposition and poor anti-interference capacity limited the application of organic compound-activated PDS. It was interestingly found that 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonate) (ABTS) could act as both activator and electron shuttle for PDS activation to enhance diclofenac (DCF) degradation over a pH range of 2.0-11.0. Multiple reactive species of ABTS•+, •OH, and SO4•- were generated in the PDS/ABTS system, while only ABTS•+ and •OH directly contributed to DCF degradation. ABTS•+, generated via the reactions of ABTS with PDS, SO4•-, and •OH, was the dominant reactive species of DCF degradation. No significant decomposition of ABTS was observed in the PDS/ABTS system, and ABTS acted as both activator and electron shuttle. Four possible degradation pathways of DCF were proposed, and the toxicity of DCF decreased after treatment with the PDS/ABTS system. The PDS/ABTS system had good anti-interference capacity to common natural water constituents. Additionally, ABTS was encapsulated into cellulose to obtain ABTS@Ce beads, and the PDS/ABTS@Ce system possessed excellent performance on DCF degradation. This study proposes a new perspective to reconsider the mechanism of activating PDS with organic compounds and highlights the considerable contribution of organic radicals on contaminant removal.

The analgesic effects and neural oscillatory mechanisms of virtual reality scenes based on distraction and mindfulness strategies in human volunteers.

BACKGROUND: Virtual reality (VR) has been widely used as a non-pharmacological adjunct to pain management. However, there is no consensus on what type of VR content is the best for pain alleviation and by what means VR modulates pain perception. We used three experiments to explore the analgesic effect of VR scenes in healthy adult volunteers. METHODS: We first compared the effect of immersive VR on pain perception with active (i.e. non-immersive, two-dimensional video) and passive (i.e. no VR or audiovisual input) controls at both subjective perceptual (Experiment 1) and electrophysiological (electroencephalography) levels (Experiment 2), and then explored possible analgesic mechanisms responsible for VR scenes conveying different strategies (e.g. exploration or mindfulness; Experiment 3). RESULTS: The multisensory experience of the VR environment lowered pain intensity and unpleasantness induced by contact heat stimuli when compared with two control conditions (P=0.001 and P<0.001, respectively). The reduced pain intensity rating correlated with decreased P2 amplitude (r=0.433, P<0.001) and increased pre-stimulus spontaneous gamma oscillations (r=-0.339, P=0.004) by 32-channel electroencephalography. A VR exploration scene induced a strong sense of immersion that was associated with increased pre-stimulus gamma oscillations (r=0.529, P<0.001), whereas a VR mindfulness meditation scene had a minor effect on immersive feelings but induced strong pre-stimulus alpha oscillations (r=-0.550, P<0.001), which led to a comparable analgesic effect. CONCLUSIONS: Distinct neural mechanisms are responsible for VR-induced analgesia, deepening our understanding of the analgesic benefits of VR and its neural electrophysiological correlates. These findings support further development of digital healthcare.

Simultaneous quantification of fatty acids in serum with dual derivatization by liquid chromatography-tandem mass spectrometry.

Fatty acids have multitudinous biological functions and play a crucial role in many biological processes, but due to poor ionization efficiency and lack of appropriate internal standards, the comprehensive quantification of fatty acids by liquid chromatography-tandem mass spectrometry is still challenging. In this study, a new, accurate, and reliable method for quantifying 30 fatty acids in serum using dual derivatization was proposed. Indole-3-acetic acid hydrazide derivants of fatty acids were used as the internal standard and indole-3-carboxylic acid hydrazide derivants of them were used to quantify. The derivatization conditions were systematically optimized and the method validation results showed good linearity with R2  > 0.9942, low detection limit (0.03-0.6 nM), precision (1.6%-9.8% for intra-day and 4.6%-14.1% for inter-day), recovery (88.2%-107.2% with relative standard deviation < 10.5%), matrix effect (88.3%-105.2% with the relative standard deviation < 9.9%) and stability (3.4%-13.8% for fatty acids derivants in 24 h at 4°C and 4.2%-13.8% for three freeze-thaw cycles). Finally, this method was successfully applied to quantify fatty acids in serum samples of Alzheimer's patients. In contrast to the healthy control group, nine fatty acids showed a significant increase in the Alzheimer's disease group.

Curative effect of external fixation combined with kirschner wire versus hollow screw in the treatment of first metacarpal bone base fracture.

PURPOSE: This study was conducted aimed at comparing the curative effect of external fixation combined with Kirschner wire fixation versus hollow screw fixation in the treatment of first metacarpal bone base fracture. METHODS: The current retrospective study included a total of 80 patients diagnosed with first metacarpal bone base fracture who were admitted in Wuxi 9th People's Hospital Affiliated to Soochow University between October 2017 and October 2020. The patients enrolled were equally divided into the combined group (40 cases, receiving external fixation combined with Kirschner wire fixation), and the control group (40 cases, receiving hollow screw fixation). Perioperative indices were collected and compared between the two groups. Pain scores before operation and three months, six months, and one year after operation were compared. Additionally, we compared the finger function in the last follow-up visit ( the follow-up period was 1 year) and rate of complications. RESULTS: Operation time, amount of bleeding, length of incision, length of hospital stay, and fracture healing time did not differ between the two groups (all P > 0.05). Pain score was comparable between the two groups before operation (P = 0.704). Despite lower results showing at 3, 6, and 12 months after operation in both groups, the pain score did not significantly differ in any time point between the two groups (all P > 0.05). Additionally, no significant differences were observed in finger function and rate of complications at the last follow-up between the two groups (both P > 0.05). CONCLUSION: External fixation combined with Kirschner wire fixation and hollow screw fixation exhibited similar curative effect in treating first metacarpal bone base fracture, indicating both surgery methods may be considered as the preferred approach.

Comparison of diaphyseal and metaphyseal ulnar shortening osteotomies for the treatment of ulnar impaction syndrome.

BACKGROUND: Ulnar shortening osteotomy (USO) is a common surgical procedure for the treatment of ulnar impaction syndrome (UIS). The purpose of this study was to compare the results of metaphyseal and diaphyseal USO.  METHODS: This retrospective study compared the clinical outcomes and complications of 32 patients who underwent diaphyseal step-cut USO (n = 10), diaphyseal oblique USO (n = 12), or metaphyseal USO (n = 10). RESULTS: Patient characteristics, ulnar variance, wrist range of motion, preoperative pain, grip strength, and functional scores (quick disability of the arm, shoulder, and hand and patient-rated wrist evaluation) were comparable. Both operation time (79.5 vs. 138/139 min) and incision length (7.80 vs. 9.67/13.00 cm) were shorter in the metaphyseal USO than in the diaphyseal oblique/step-cut USO. Compared with diaphyseal oblique/step-cut USO, metaphyseal osteotomies were associated with greater improvement in the pain on postoperative day 3 and shorter bone healing time. The requirements for implant removal were the same among the three groups. No complications were observed in any group. CONCLUSION: Compared with diaphyseal USO, metaphyseal USO has advantages for operation time and incision length, early postoperative pain, bone healing in UIS management. The results suggested that metaphyseal USO could be widely applied to the surgical treatment of UIS. However, the long-term outcomes of these techniques still require further evaluation using more large-scale, randomized clinical trials.

HDAC2 exacerbates rheumatoid arthritis progression via the IL-17-CCL7 signaling pathway.

Histone deacetylases (HDACs) have been reported to regulate the immune response in rheumatoid arthritis (RA). The current study aimed to explore key HDACs and their molecular mechanism in RA. First, the expression of HDAC1, HDAC2, HDAC3 and HDAC8 in RA synovial tissue was determined by qRT-PCR. The effects of HDAC2 on the proliferation, migration, invasion, and apoptosis of fibroblast-like synoviocytes (FLS) in vitro were studied. Furthermore, collagen-induced arthritis (CIA) rat models were established to evaluate the severity of arthritis in joints, and the levels of inflammatory factors were examined by immunohistochemistry staining, ELISA, and qRT-PCR. Transcriptome sequencing was used to screen differentially expressed genes (DEGs) with HDAC2 silencing in the synovial tissue of CIA rat, and downstream signaling pathways were predicted by enrichment analysis. The results showed that HDAC2 was highly expressed in the synovial tissue of RA patients and CIA rats. Overexpressed HDAC2 promoted FLS proliferation, migration, and invasion and inhibited FLS apoptosis in vitro, resulting in secretion of inflammatory factors and RA exacerbation in vivo. There were 176 DEGs, including 57 downregulated and 119 upregulated genes, after silencing HDAC2 in CIA rats. DEGs were primarily enriched in Platinum drug resistance, IL-17 as well as the PI3K-Akt signaling pathways. CCL7, which was implicated in the IL-17 signaling pathway, was downregulated after HDAC2 silencing. Furthermore, CCL7 overexpression aggravated the development of RA, which was demonstrated to be effectively attenuated by HDAC2 suppression. In conclusion, this study demonstrated that HDAC2 exacerbated the progression of RA by regulating the IL-17-CCL7 signaling pathway, suggesting that HDAC2 may be a promising therapeutic target for RA treatment.

Robust Learning with Noisy Ship Trajectories by Adaptive Noise Rate Estimation.

Ship trajectory classification is of great significance for shipping analysis and marine security governance. However, in order to cover up their illegal fishing or espionage activities, some illicit ships will forge the ship type information in the Automatic Identification System (AIS), and this label noise will significantly impact the algorithm's classification accuracy. Sample selection is a common and effective approach in the field of learning from noisy labels. However, most of the existing methods based on sample selection need to determine the noise rate of the data through prior means. To address these issues, we propose a noise rate adaptive learning mechanism that operates without prior conditions. This mechanism is integrated with the robust training paradigm JoCoR (joint training with co-regularization), giving rise to a noise rate adaptive learning robust training paradigm called A-JoCoR. Experimental results on real-world trajectories provided by the Danish Maritime Authority verified the effectiveness of A-JoCoR. It not only realizes the adaptive learning of the data noise rate during the training process, but also significantly improves the classification performance compared with the original method.