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Background: Several respiratory infections outbreaks have been observed in mainland China after reduction of non-pharmaceutical interventions. Other countries have seen increases in respiratory infections outside typical seasons post-COVID-19, warranting investigation into underlying causes. Methods: We established monitoring networks for suspected respiratory infection in 14 tertiary hospitals nationwide. PCR for SARS-CoV-2, influenza A and B were performed on 3708 respiratory specimens and deep sequencing were conducted to identify co-infections or newly emerging microbes in 2023. Viral evolutionary analysis was completed. We retrospectively detected serum antibody level for various respiratory pathogens from 4324 adults without respiratory infections over 7 years to observe its dynamic curves. Findings: SARS-CoV-2 and influenza A were the main pathogens during outbreaks in 2023, bacterial-virus and bacterial-bacterial co-infections were most detected, but community co-infections didn't significantly increase pneumonia incidence. Different SARS-CoV-2 and influenza variants were present in different outbreaks, and no novel pathogens were found. The epidemiological patterns of influenza A, COVID-19 and etc. were altered, exhibiting characteristics of being "staggered" compared to most global regions, and potentially led to "overlapping prevalence". Binding antibody testing showed regular fluctuation, without significant decrease against common respiratory pathogens in adults. Influenza A antibody stimulation was attenuated during the 2023 outbreak. Conclusions: "Misaligned" alteration in seasonal respiratory disease patterns possibly caused combined epidemics, leading to cases spike in China, 2023. In adults, antibody levels didn't show significant decline, but reduced immune response to influenza during 2020-2023 emphasizes the need for consistent vaccination during pandemics.
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Objective: Ferroptosis and necroptosis are two recently identified forms of non-apoptotic cell death. Their dysregulation plays a critical role in the development and progression of Psoriasis (PsD) and Atherosclerosis (AS). This study explores shared Ferroptosis and necroptosis-related genes and elucidates their molecular mechanisms in PsD and AS through the analysis of public databases. Methods: Data sets for PsD (GSE30999) and AS (GSE28829) were retrieved from the GEO database. Differential gene expression (DEG) and weighted gene co-expression network analysis (WGCNA) were performed. Machine learning algorithms identified candidate biomarkers, whose diagnostic values were assessed using Receiver Operating Characteristic (ROC) curve analysis. Additionally, the expression levels of these biomarkers in cell models of AS and PsD were quantitatively measured using Western Blot (WB) and real-time quantitative PCR (RT-qPCR). Furthermore, CIBERSORT evaluated immune cell infiltration in PsD and AS tissues, highlighting the correlation between characteristic genes and immune cells. Predictive analysis for candidate drugs targeting characteristic genes was conducted using the DGIdb database, and an lncRNA-miRNA-mRNA network related to these genes was constructed. Results: We identified 44 differentially expressed ferroptosis-related genes (DE-FRGs) and 30 differentially expressed necroptosis-related genes (DE-NRGs). GO and KEGG enrichment analyses revealed significant enrichment of these genes in immune-related and inflammatory pathways, especially in NOD-like receptor and TNF signaling pathways. Two ferroptosis-related genes (NAMPT, ZFP36) and eight necroptosis-related genes (C7, CARD6, CASP1, CTSD, HMOX1, NOD2, PYCARD, TNFRSF21) showed high sensitivity and specificity in ROC curve analysis. These findings were corroborated in external validation datasets and cell models. Immune infiltration analysis revealed increased levels of T cells gamma delta, Macrophages M0, and Macrophages M2 in PsD and AS samples. Additionally, we identified 43 drugs targeting 5 characteristic genes. Notably, the XIST-miR-93-5p-ZFP36/HMOX1 and NEAT1-miR-93-5p-ZFP36/HMOX1 pathways have been identified as promising RNA regulatory pathways in AS and PsD. Conclusion: The two ferroptosis-related genes (NAMPT, ZFP36) and eight necroptosis-related genes (C7, CARD6, CASP1, CTSD, HMOX1, NOD2, PYCARD, TNFRSF21) are potential key biomarkers for PsD and AS. These genes significantly influence the pathogenesis of PsD and AS by modulating macrophage activity, participating in immune regulation, and mediating inflammatory responses.
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Aterosclerose , Ferroptose , Necroptose , Psoríase , Ferroptose/genética , Humanos , Aterosclerose/genética , Aterosclerose/imunologia , Aterosclerose/metabolismo , Necroptose/genética , Psoríase/genética , Psoríase/imunologia , Redes Reguladoras de Genes , Perfilação da Expressão Gênica , Biomarcadores , Bases de Dados Genéticas , Biologia Computacional/métodos , Regulação da Expressão GênicaRESUMO
The development of scalable and passive coatings that can adapt to seasonal temperature changes while maintaining superhydrophobic self-cleaning functions is crucial for their practical applications. However, the incorporation of passive cooling and heating functions with conflicting optical properties in a superhydrophobic coating is still challenging. Herein, an all-in-one coating inspired by the hierarchical structure of a lotus leaf that combines surface wettability, optical structure, and temperature self-adaptation is obtained through a simple one-step phase separation process. This coating exhibits an asymmetrical gradient structure with surface-embedded hydrophobic SiO2 particles and subsurface thermochromic microcapsules within vertically distributed hierarchical porous structures. Moreover, the coating imparts superhydrophobicity, high infrared emission, and thermo-switchable sunlight reflectivity, enabling autonomous transitions between radiative cooling and solar warming. The all-in-one coating prevents contamination and over-cooling caused by traditional radiative cooling materials, opening up new prospects for the large-scale manufacturing of intelligent thermoregulatory coatings.
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Social relation inference intrinsically requires high-level semantic understanding. In order to accurately infer relations of persons in images, one needs not only to understand scenes and objects in images, but also to adaptively attend to important clues. Unlike prior works of classifying social relations using attention on detected objects, we propose a MUlti-level Conditional Attention (MUCA) mechanism for social relation inference, which attends to scenes, objects and human interactions based on each person pair. Then, we develop a transformer-style network to achieve the MUCA mechanism. The novel network named as Graph-based Relation Inference Transformer (i.e., GRIT) consists of two modules, i.e., a Conditional Query Module (CQM) and a Relation Attention Module (RAM). Specifically, we design a graph-based CQM to generate informative relation queries for all person pairs, which fuses local features and global context for each person pair. Moreover, we fully take advantage of transformer-style networks in RAM for multi-level attentions in classifying social relations. To our best knowledge, GRIT is the first for inferring social relations with multi-level conditional attention. GRIT is end-to-end trainable and significantly outperforms existing methods on two benchmark datasets, e.g., with performance improvement of 7.8% on PIPA and 9.6% on PISC.
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Benchmarking , Conhecimento , Humanos , SemânticaRESUMO
Existing deep learning methods for fine-grained visual recognition often rely on large-scale, well-annotated training data. Obtaining fine-grained annotations in the wild typically requires concentration and expertise, such as fine category annotation for species recognition, instance annotation for person re-identification (re-id) and dense annotation for segmentation, which inevitably leads to label noise. This paper aims to tackle label noise in deep model training for fine-grained visual recognition. We propose a Neighbor-Attention Label Correction (NALC) model to correct labels during the training stage. NALC samples a training batch and a validation batch from the training set. It hence leverages a meta-learning framework to correct labels in the training batch based on the validation batch. To enhance the optimization efficiency, we introduce a novel nested optimization algorithm for the meta-learning framework. The proposed training procedure consistently improves label accuracy in the training batch, consequently enhancing the learned image representation. Experimental results demonstrate that our method significantly increases label accuracy from 70% to over 98% and outperforms recent approaches by up to 13.4% in mean Average Precision (mAP) on various fine-grained image retrieval (FGIR) tasks, including instance retrieval on CUB200 and person re-id on Market1501. We also demonstrate the efficacy of NALC on noisy semantic segmentation datasets generated from Cityscapes, where it achieves a significant 7.8% improvement in mIOU score. NALC also exhibits robustness to different types of noise, including simulated noise such as Asymmetric, Pair-Flip, and Pattern noise, as well as practical noisy labels generated by tracklets and clustering.
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The Topoisomerase 3B (Top3b) - Tudor domain containing 3 (Tdrd3) protein complex is the only dual-activity topoisomerase complex that can alter both DNA and RNA topology in animals. TOP3B mutations in humans are associated with schizophrenia, autism and cognitive disorders; and Top3b-null mice exhibit several phenotypes observed in animal models of psychiatric and cognitive disorders, including impaired cognitive and emotional behaviors, aberrant neurogenesis and synaptic plasticity, and transcriptional defects. Similarly, human TDRD3 genomic variants have been associated with schizophrenia, verbal short-term memory and educational attainment. However, the importance of Tdrd3 in normal brain function has not been examined in animal models. Here we generated a Tdrd3-null mouse strain and demonstrate that these mice display both shared and unique defects when compared to Top3b-null mice. Shared defects were observed in cognitive behaviors, synaptic plasticity, adult neurogenesis, newborn neuron morphology, and neuronal activity-dependent transcription; whereas defects unique to Tdrd3-deficient mice include hyperactivity, changes in anxiety-like behaviors, olfaction, increased new neuron complexity, and reduced myelination. Interestingly, multiple genes critical for neurodevelopment and cognitive function exhibit reduced levels in mature but not nascent transcripts. We infer that the entire Top3b-Tdrd3 complex is essential for normal brain function, and that defective post-transcriptional regulation could contribute to cognitive and psychiatric disorders.
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Disfunção Cognitiva , Regulação da Expressão Gênica , Animais , Humanos , Camundongos , Sequência de Aminoácidos , Neurogênese/genética , Plasticidade Neuronal/genética , Proteínas/genética , Proteínas/metabolismoRESUMO
The lateral hypothalamus (LH) is involved in feeding behavior and defense responses by interacting with different brain structures, including the Ventral Tegmental Area (VTA). Emerging evidence indicates that LH-glutamatergic neurons infrequently synapse on VTA-dopamine neurons but preferentially establish multiple synapses on VTA-glutamatergic neurons. Here, we demonstrated that LH-glutamatergic inputs to VTA promoted active avoidance, long-term aversion, and escape attempts. By testing feeding in the presence of a predator, we observed that ongoing feeding was decreased, and that this predator-induced decrease in feeding was abolished by photoinhibition of the LH-glutamatergic inputs to VTA. By VTA specific neuronal ablation, we established that predator-induced decreases in feeding were mediated by VTA-glutamatergic neurons but not by dopamine or GABA neurons. Thus, we provided evidence for an unanticipated neuronal circuitry between LH-glutamatergic inputs to VTA-glutamatergic neurons that plays a role in prioritizing escape, and in the switch from feeding to escape in mice.
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Região Hipotalâmica Lateral , Área Tegmentar Ventral , Animais , Camundongos , Neurônios GABAérgicos , Neurônios Dopaminérgicos , AfetoRESUMO
Radiative cooling is a zero-energy technology that enables subambient cooling by emitting heat into outer space (~3 K) through the atmospheric transparent windows. However, existing designs typically focus only on the main atmospheric transparent window (8-13 µm) and ignore another window (16-25 µm), under-exploiting their cooling potential. Here, we show a dual-selective radiative cooling design based on a scalable thermal emitter, which exhibits selective emission in both atmospheric transparent windows and reflection in the remaining mid-infrared and solar wavebands. As a result, the dual-selective thermal emitter exhibits an ultrahigh subambient cooling capacity (~9 °C) under strong sunlight, surpassing existing typical thermal emitters (≥3 °C cooler) and commercial counterparts (as building materials). Furthermore, the dual-selective sample also exhibits high weather resistance and color compatibility, indicating a high practicality. This work provides a scalable and practical radiative cooling design for sustainable thermal management.
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The rate of MRD clearance in AML with standard consolidation chemotherapy is not well defined. A multi-institution retrospective analysis was performed on 107 consecutively treated AML patients in morphologic complete remission with detectable MRD post-induction therapy who received standard chemotherapy consolidation. In response to standard intermediate/high-dose cytarabine consolidation therapy, 26 of 60 patients (43.3%) with MRD threshold of detection of at least 0.1% converted to MRD-negative status (undetectable with assay used), and 6 of 47 patients (12.8%) with MRD threshold of detection > 0.1% converted to MRD-negative status. Multivariable logistic regression for patients with MRD threshold of detection of at least 0.1% showed that, when controlling for age, ELN risk category, dose of cytarabine, and use of a combination agent, treatment with 1 cycle of consolidation cytarabine versus ≥2 cycles decreased the odds of conversion of AML to MRD-negative (OR = 0.24, 95% CI 0.07-0.85, p = 0.03).
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Transplante de Células-Tronco Hematopoéticas , Leucemia Mieloide Aguda , Humanos , Quimioterapia de Consolidação , Estudos Retrospectivos , Leucemia Mieloide Aguda/diagnóstico , Leucemia Mieloide Aguda/tratamento farmacológico , Indução de Remissão , Citarabina , Neoplasia Residual/diagnóstico , PrognósticoRESUMO
OBJECTIVE: Activation of farnesoid X receptor (FXR), a bile acid nuclear receptor, may be implicated in the pathophysiology of diabetic nephropathy. We explored a possible role for FXR activation in preventing renal fibrosis in high fat diet (HFD)-fed mice. METHODS: We investigated the effects of HFD on mouse kidney and renal tubular epithelial cells both in vivo and in vitro, and observed the changes of FXR and ß-catenin pathway. FXR agonist was also used to alleviate this HFD-induced effect, and the interaction between FXR and ß-catenin was further verified. RESULTS: Mice were fed by a 60% kcal fat diet for 20 weeks developed the typical traits of metabolic syndrome with subsequent renal lipid accumulation and renal injury. Treatment with the FXR agonist CDCA or GW4064 decreased body weight, renal lipid accumulation, as well as renal injury. Moreover, renal ß-catenin signaling was activated and improved with FXR-agonist treatment in HFD-fed mice. To examine whether FXR affected ß-catenin signaling, and was involved in tubulo-interstitial fibrosis, we explored the FXR expression and function in ox-LDL induced-renal tubular injury. In rat proximal tubular epithelial cells (NRK-52E) stimulated by ox-LDL, FXR protein was decreased compared to control group, and phosphorylated (Ser675) ß-catenin was activated by ox-LDL in a dose- and time-dependent manner. Ox-LDL enhanced α-SMA and fibronectin expressions and reduced E-cadherin levels, whereas FXR agonism or FXR overexpression inhibited fibronectin and α-SMA expressions and restored E-cadherin. Moreover, FXR agonist treatment also decreased phosphorylated (Ser675) ß-catenin, nuclear translocation and ß-catenin-mediated transcription induced by ox-LDL in NRK-52E cells. We showed that FXR could bind with ß-catenin via the AF1 domain, and disrupt the assembly of the core ß-catenin/TCF4 complex. CONCLUSION: These experimental data suggest that FXR activation, via modulating ß-catenin signaling, may contribute to attenuating the development of lipid-mediated tubulo-interstitial fibrosis.
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Nefropatias Diabéticas , beta Catenina , Animais , Camundongos , Ratos , beta Catenina/metabolismo , Caderinas , Fibronectinas , Fibrose , LipídeosRESUMO
The development of genetically encoded dopamine sensors such as dLight has provided a new approach to measuring slow and fast dopamine dynamics both in brain slices and in vivo, possibly enabling dopamine measurements in areas like the dorsolateral striatum (DLS) where previously such recordings with fast-scan cyclic voltammetry (FSCV) were difficult. To test this, we first evaluated dLight photometry in mouse brain slices with simultaneous FSCV and found that both techniques yielded comparable results, but notable differences in responses to dopamine transporter inhibitors, including cocaine. We then used in vivo fiber photometry with dLight in mice to examine responses to cocaine in DLS. We also compared dopamine responses during Pavlovian conditioning across the striatum. We show that dopamine increases were readily detectable in DLS and describe transient dopamine kinetics, as well as slowly developing signals during conditioning. Overall, our findings indicate that dLight photometry is well suited to measuring dopamine dynamics in DLS.
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Cocaína , Dopamina , Animais , Camundongos , Corpo Estriado , Neostriado , Encéfalo , Cocaína/farmacologia , CorantesRESUMO
In person re-identification (re-ID), extracting part-level features from person images has been verified to be crucial to offer fine-grained information. Most of the existing CNN-based methods only locate the human parts coarsely, or rely on pretrained human parsing models and fail in locating the identifiable nonhuman parts (e.g., knapsack). In this article, we introduce an alignment scheme in transformer architecture for the first time and propose the auto-aligned transformer (AAformer) to automatically locate both the human parts and nonhuman ones at patch level. We introduce the "Part tokens (PARTs)", which are learnable vectors, to extract part features in the transformer. A PART only interacts with a local subset of patches in self-attention and learns to be the part representation. To adaptively group the image patches into different subsets, we design the auto-alignment. Auto-alignment employs a fast variant of optimal transport (OT) algorithm to online cluster the patch embeddings into several groups with the PARTs as their prototypes. AAformer integrates the part alignment into the self-attention and the output PARTs can be directly used as part features for retrieval. Extensive experiments validate the effectiveness of PARTs and the superiority of AAformer over various state-of-the-art methods.
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Diabetic cardiomyopathy (DCM) is one of the severe complications of diabetes, characterized by structural and functional abnormalities in the hearts of diabetic patients without hypertension, coronary heart disease, or valvular heart disease. DCM can progress to heart failure, which is a significant cause of death in diabetic patients, but currently, there is no effective treatment available. Programmed cell death (PCD) is a genetically regulated form of cell death that includes apoptosis, autophagy, necroptosis, ferroptosis, and pyroptosis. PCD is essential for tissue homeostasis and normal development of the body. DCM is a complex condition, and abnormalities in the cascade of PCD signaling have been observed in its pathological process, suggesting that targeting PCD could be a potential therapeutic strategy. Studies have shown that natural substances can effectively modulate PCD to intervene in the treatment of DCM, and their use is safe. This review explores the role of different forms of PCD in the pathogenesis of DCM and summarizes the research progress in targeting PCD with natural substances to treat DCM. It can serve as a basis for further research and drug development to provide new treatment strategies for DCM patients.
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Diabetes Mellitus , Cardiomiopatias Diabéticas , Humanos , Cardiomiopatias Diabéticas/tratamento farmacológico , Apoptose , Morte Celular , Coração , Resultado do TratamentoRESUMO
The ventral tegmental area (VTA) has been proposed to play a role in pain, but the brain structures modulating VTA activity in response to nociceptive stimuli remain unclear. Here, we demonstrate that the lateral preoptic area (LPO) glutamate neurons relay nociceptive information to the VTA. These LPO glutamatergic neurons synapsing on VTA neurons respond to nociceptive stimulation and conditioned stimuli predicting nociceptive stimulation and also mediate aversion. In contrast, LPO GABA neurons synapsing in the VTA mediate reward. By ultrastructural quantitative synaptic analysis, ex vivo electrophysiology, and functional neuroanatomy we identify a complex circuitry between LPO glutamatergic and GABAergic neurons and VTA dopaminergic, GABAergic, and glutamatergic neurons. We conclude that LPO glutamatergic neurons play a causal role in the processing of nociceptive stimuli and in relaying information about nociceptive stimuli. The pathway from LPO glutamatergic neurons to the VTA represents an unpredicted interface between peripheral nociceptive information and the limbic system.
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Ácido Glutâmico , Área Tegmentar Ventral , Ácido Glutâmico/metabolismo , Área Tegmentar Ventral/metabolismo , Área Pré-Óptica/metabolismo , Nociceptividade , Neurônios GABAérgicos/metabolismo , Neurônios Dopaminérgicos/metabolismoRESUMO
Vision Transformers (ViTs) split an image into fixed-size patches as tokens. This strategy has succeeded in computer vision tasks, but introduces considerable tokens similar in semantics and appearances. This work proposes Token Merger to spot redundant tokens and merge them into a compact representation to accelerate ViTs. For each forward inference, the Token Merger first identifies meta tokens to represent meaningful cues of the image content, then adaptively merges similar tokens into a uniform one referring to meta tokens. To pursue a reasonable tradeoff between accuracy and efficiency, we further introduce learnable gates to adaptively decide the token merge ratios of different layers. As a generalizable module, Token Merger can be easily plugged into different layers of ViTs to boost their efficiency. Visualizations show that Token Merger progressively merges tokens and finally learns a compact set of tokens representing clear semantics. Compared with token pruning methods, Token Merger is more effective in preserving meaning contextual cues, thus performs and generalizes substantially better in different vision tasks. Extensive experiments and comparisons with other state-of-the-art downsampling methods also demonstrate its promising performance. For instance, it reduces 95% tokens and accelerates the inference speed by 62%. Meanwhile, the ImageNet classification accuracy only drops by 0.4%. The code will be available.
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Differential privacy (DP) defines privacy protection by promising quantified indistinguishability between individuals who consent to share their privacy-sensitive information and those who do not. DP aims to deliver this promise by including well-crafted elements of random noise in the published data, and thus there is an inherent tradeoff between the degree of privacy protection and the ability to utilize the protected data. Currently, several open-source tools have been proposed for DP provision. To the best of our knowledge, there is no comprehensive study for comparing these open-source tools with respect to their ability to balance DP's inherent tradeoff as well as the use of system resources. This work proposes an open-source evaluation framework for privacy protection solutions and offers evaluation for OpenDP Smartnoise, Google DP, PyTorch Opacus, Tensorflow Privacy, and Diffprivlib. In addition to studying their ability to balance the above tradeoff, we consider discrete and continuous attributes by quantifying their performance under different data sizes. Our results reveal several patterns that developers should have in mind when selecting tools under different application needs and criteria. This evaluation survey can be the basis for an improved selection of open-source DP tools and quicker adaptation of DP.
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Optogenetics is a widely used technology with potential for translational research. A critical component of such applications is the ability to track the location of the transduced opsin in vivo. To address this problem, we engineered an excitatory opsin, ChRERα (hChR2(134R)-V5-ERα-LBD), that could be visualized using positron emission tomography (PET) imaging in a noninvasive, longitudinal, and quantitative manner. ChRERα consists of the prototypical excitatory opsin channelrhodopsin-2 (ChR2) and the ligand-binding domain (LBD) of the human estrogen receptor α (ERα). ChRERα showed conserved ChR2 functionality and high affinity for [18F]16α-fluoroestradiol (FES), an FDA-approved PET radiopharmaceutical. Experiments in rats demonstrated that adeno-associated virus (AAV)-mediated expression of ChRERα enables neural circuit manipulation in vivo and that ChRERα expression could be monitored using FES-PET imaging. In vivo experiments in nonhuman primates (NHPs) confirmed that ChRERα expression could be monitored at the site of AAV injection in the primary motor cortex and in long-range neuronal terminals for up to 80 weeks. The anatomical connectivity map of the primary motor cortex identified by FES-PET imaging of ChRERα expression overlapped with a functional connectivity map identified using resting state fMRI in a separate cohort of NHPs. Overall, our results demonstrate that ChRERα expression can be mapped longitudinally in the mammalian brain using FES-PET imaging and can be used for neural circuit modulation in vivo.
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Neoplasias da Mama , Receptor alfa de Estrogênio , Ratos , Humanos , Animais , Feminino , Receptor alfa de Estrogênio/metabolismo , Opsinas/metabolismo , Tomografia por Emissão de Pósitrons , Encéfalo/diagnóstico por imagem , Encéfalo/metabolismo , Primatas , Estradiol/metabolismo , Neoplasias da Mama/metabolismo , Mamíferos/metabolismoRESUMO
BACKGROUND: Microvascular angina (MVA) substantially threatens human health, and the Shenzhi Tongxin (SZTX) capsule demonstrates a remarkable cardioprotective effect, making it a potential treatment option for MVA. However, the precise mechanism of action for this medication remains unclear. This study utilized network pharmacology and molecular docking technology to investigate the active components and potential mechanisms underlying the efficacy of the SZTX capsule in alleviating MVA. METHODS: The main ingredients of the SZTX capsule, along with their targets proteins and potential disease targets associated with MVA, were extracted from public available databases. This study utilized the STRING database and Cytoscape 3.7.2 software to establish a protein-protein interaction network and determine key signaling pathway targets. Subsequently, the DAVID database was utilized to conduct Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analyses on the intersection targets. To further investigate the molecular interactions, Autodock and PyMOL software were employed to perform molecular docking and visualize the resulting outcomes. RESULTS: A total of 130 and 142 bioactive ingredients and intersection targets were identified respectively. Six core targets were obtained through protein-protein interaction network analysis. Gene Ontology enrichment analysis showed that 610 biological processes, 75 cellular components, and 92 molecular functions were involved. The results of Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that SZTX capsule molecular mechanism in the treatment of MVA may be related to several pathways, including mitogen-activated protein kinases, PI3K-Akt, HIF-1, and others. The results of molecular docking showed that the 7 key active ingredients of SZTX capsule had good binding ability to 6 core proteins. CONCLUSION: SZTX capsule potentially exerts its effects by targeting multiple signaling pathways, including the mitogen-activated protein kinases signaling pathway, PI3K-Akt signaling pathway, and HIF-1 signaling pathway. This multi-target approach enables SZTX capsule to inhibit inflammation, alleviate oxidative stress, regulate angiogenesis, and enhance endothelial function.
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Angina Microvascular , Farmacologia em Rede , Humanos , Simulação de Acoplamento Molecular , Fosfatidilinositol 3-Quinases , Proteínas Proto-Oncogênicas c-akt , Proteínas Quinases Ativadas por Mitógeno , Fator 1 Induzível por HipóxiaRESUMO
BACKGROUND: The choice between nonmyeloablative chemotherapy (NMA-C) or autologous hematopoietic cell transplantation (autoHCT) as consolidation in primary central nervous system lymphoma (PCNSL), and timing of autoHCT differs among centers. We aimed to clarify these points. METHODS: We retrospectively analyzed PCNSL adult patients who received consolidation in CR1 or underwent autoHCT during their treatment course. Cohort A included those who underwent autoHCT in CR1, cohort B included those who underwent NMA-C in CR1, and cohort C included patients who underwent autoHCT in CR2+. We compared cohorts A and B, and cohorts A and C. The primary endpoint was overall survival (OS), and secondary endpoints were progression-free survival (PFS), treatment-related mortality (TRM) and cumulative incidence of relapse (CIR). RESULTS: 36 patients were included in cohort A, 30 in cohort B, and 14 in cohort C. The 5-year OS for cohorts A vs B and vs C were 90.7% vs 62.8% (P = .045) and vs 77.9% (P = .32), respectively. The 5-year PFS from diagnosis for cohorts A vs B was 87.8% vs 37.3% (P < .001). The 5-year PFS from autoHCT for cohorts A vs C was 87.6% vs 58.4% (P = .023). The 5-year TRM and CIR in cohorts A vs B was 9.4% vs 9.5% (P = .674), and 2.9% vs 53.2% (P < .001), respectively. The 5-year TRM and CIR in cohorts A vs C from the time of autoHCT was 9.5% vs 22.1% (P = .188), and 2.9% vs 19.5% (P = .104), respectively. CONCLUSION: Despite the limitations, thiotepa-based autoHCT in CR1 appears to improve outcomes in eligible patients with PCNSL.