D1-like dopamine receptors promote B-cell differentiation in systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune disease that currently cannot be completely cured with a great health burden. Since the production of autoantibodies plays a key role in the pathogenesis of SLE, discovering the underlying immunoregulation mechanism of B cells will be helpful for developing promising immunotherapy for SLE. In recent studies, dopamine receptors (DRDs), G protein-coupled receptors that include D1-like and D2-like subtypes, are expressed on B cells and participate in various physiological processes, involving immune responses. However, the regulatory effect of DRDs on B cells has not been determined. METHODS: This study explored the expression of DRDs on B-cell subsets from SLE patients and healthy individuals. The effects of D1-like receptor on B-cell activation and differentiation were further explored using D1-like receptor agonists or antagonists. RNA-seq and bioinformatics analyses were used to identify specific molecular mechanisms involved. RESULTS: The D1-like DRDs on B cells of SLE patients were highly expressed compared with those of healthy controls (HCs). D1-like receptor agonist treatment exacerbated lupus-like symptoms in pristane-induced lupus-like mice, while D1-like receptor antagonists alleviated the lupus-like phenotypes. Inhibition of D1-like receptor signals impeded B-cell differentiation, while activation of D1-like receptor signals could promote B cell differentiation. Further RNA-seq confirmed that PTGS2, a gene related to B-cell differentiation, was up-regulated once the D1-like receptor signals were activated, while BMP6 and IL-24 were up-regulated once the D1-like receptor signals were inhibited. CONCLUSION: D1-like receptors probably promote B-cell differentiation through the PTGS2/PRDM1 pathway.

CRISPR screens unveil nutrient-dependent lysosomal and mitochondrial nodes impacting intestinal tissue-resident memory CD8+ T cell formation.

Nutrient availability and organelle biology direct tissue homeostasis and cell fate, but how these processes orchestrate tissue immunity remains poorly defined. Here, using in vivo CRISPR-Cas9 screens, we uncovered organelle signaling and metabolic processes shaping CD8+ tissue-resident memory T (TRM) cell development. TRM cells depended on mitochondrial translation and respiration. Conversely, three nutrient-dependent lysosomal signaling nodes-Flcn, Ragulator, and Rag GTPases-inhibited intestinal TRM cell formation. Depleting these molecules or amino acids activated the transcription factor Tfeb, thereby linking nutrient stress to TRM programming. Further, Flcn deficiency promoted protective TRM cell responses in the small intestine. Mechanistically, the Flcn-Tfeb axis restrained retinoic acid-induced CCR9 expression for migration and transforming growth factor ß (TGF-ß)-mediated programming for lineage differentiation. Genetic interaction screening revealed that the mitochondrial protein Mrpl52 enabled early TRM cell formation, while Acss1 controlled TRM cell development under Flcn deficiency-associated lysosomal dysregulation. Thus, the interplay between nutrients, organelle signaling, and metabolic adaptation dictates tissue immunity.

Evaluating the causal relationship of Levo-carnitine and risk of schizophrenia: a bidirectional two-sample mendelian randomization study.

BACKGROUND: Schizophrenia is a debilitating mental disorder affecting about 1% of the global population, characterized by significant cognitive impairments and a strong hereditary component. Carnitine, particularly Levo-carnitine and its derivatives, plays a crucial role in cellular metabolism and mitochondrial function, with evidence suggesting a link between levo-carnitine deficiency and schizophrenia pathology. This study aims to investigate the causal relationship between different subtypes of levo-carnitine and the susceptibility to schizophrenia using Mendelian randomization analysis. METHODS: Forward Mendelian randomization analysis was conducted using levo-carnitine and its derivatives as exposure and schizophrenia as the outcome. Candidate data were obtained from the Open-GWAS database. Instrumental variables were identified as single nucleotide polymorphisms closely associated with exposure and harmonized with the outcome data after removing confounders and outliers. Mendelian randomization analysis was performed using inverse variance weighting as the primary approach, and sensitivity analysis was conducted to assess the reliability and robustness of the results. Finally, a reverse Mendelian randomization analysis was carried out using the same analytical procedures. RESULTS: The Mendelian randomization results indicate a significant negative causal relationship between isovaleryl-levo-carnitine and schizophrenia (P < 0.05), but no significant associations in other groups (P > 0.05). Additionally, the reverse Mendelian randomization analysis did not identify any causal relationship between schizophrenia and levo-carnitine related exposures (P > 0.05). Sensitivity analyses, including pleiotropy and heterogeneity analysis, did not reveal any potential bias in the Mendelian randomization results (P > 0.05). CONCLUSION: The results suggest that elevated levels of isovaleryl-levo-carnitine may potentially mitigate the risk of developing schizophrenia, highlighting the prospective therapeutic and preventive implications of isovaleryl-levo-carnitine in the clinical management of schizophrenia.

A numerical analysis of metal-supported solid oxide fuel cell with a focus on temperature field.

Metal-supported solid oxide fuel cell (MS-SOFC) is very promising for intermediate temperature solid oxide fuel cell (SOFC) due to better mechanical strength, low materials cost, and simplified stack assembling. However, the effects of metal support on the performance and temperature field of MS-SOFC is still necessary for further study. In this study, a three-dimensional multi-physical model is developed to investigate how the use of metal support influence the electrochemical performance and the temperature field of MS-SOFC with a ceria-based electrolyte. The multi-physical model fully considers the conservation equations of mass, momentum, and energy that are coupled with mass transport and electrochemical reactions. The wall temperature in the radiation model is calculated using a discrete method. It is found that the radiation heat flux accounts for 3.13 % of the total heat flux. More importantly, the temperature difference of MS-SOFC is 3.61 % lower than that of conventional anode-supported SOFC, leading to improved temperature uniformity and cell durability.

Effect of Mn2+ concentration on the growth of δ-MnO2 crystals under acidic conditions.

δ-MnO2 is an important component of environmental minerals and is among the strongest sorbents and oxidants. The crystalline morphology of δ-MnO2 is one of the key factors affecting its reactivity. In this work, δ-MnO2 was initially synthesized and placed in an acidic environment to react with Mn2+ and undergo a crystalline transformation. During the transformation of crystalline δ-MnO2, kinetic sampling was conducted, followed by analyses of the structures and morphologies of the samples. The results showed that at pH 2.5 and 4, δ-MnO2 nanoflakes spontaneously self-assembled into nanoribbons via edge-to-edge assembly in the initial stage. Subsequently, these nanoribbons attached to each other to form primary nanorods through a face-to-face assembly along the c-axis. These primary nanorods then assembled along the (001) planes and lateral surfaces, achieving further growth and thickening. Since a lower pH is more favorable for the formation of vacancies in δ-MnO2, δ-MnO2 can rapidly adsorb Mn2+ directly onto the vacancies to form tunnel walls. At the same time, the rapid formation of the tunnel walls leads to a quick establishment of hydrogen bonding between adjacent nanoribbons, enabling the assembly of these nanoribbons into primary nanorods. Therefore, in a solution with the same concentration of Mn2+, the structure transformation and morphology evolution of δ-MnO2 to α-MnO2 occur faster at pH 2.5 than at pH 4. These findings provide insights into the mechanism for crystal growth from layer-based to tunnel-based nanorods and methods for efficient and controlled syntheses of nanomaterials.

Practical Performance Analysis of MDI-QKD with Orbital Angular Momentum on UAV Relay Platform.

The integration of terrestrial- and satellite-based quantum key distribution (QKD) experiments has markedly advanced global-scale quantum networks, showcasing the growing maturity of quantum technologies. Notably, the use of unmanned aerial vehicles (UAVs) as relay nodes has emerged as a promising method to overcome the inherent limitations of fiber-based and low-Earth orbit (LEO) satellite connections. This paper introduces a protocol for measurement-device-independent QKD (MDI-QKD) using photon orbital angular momentum (OAM) encoding, with UAVs as relay platforms. Leveraging UAV mobility, the protocol establishes a secure and efficient link, mitigating threats from untrusted UAVs. Photon OAM encoding addresses reference frame alignment issues exacerbated by UAV jitter. A comprehensive analysis of atmospheric turbulence, state-dependent diffraction (SDD), weather visibility, and pointing errors on free-space OAM-state transmission systems was conducted. This analysis elucidates the relationship between the key generation rate and propagation distance for the proposed protocol. Results indicate that considering SDD significantly decreases the key rate, halving previous data results. Furthermore, the study identifies a maximum channel loss capacity of 26 dB for the UAV relay platform. This result is pivotal in setting realistic parameters for the deployment of UAV-based quantum communications and lays the foundation for practical implementation strategies in the field.

Causal Relationship between Aging and Anorexia Nervosa: A White-Matter-Microstructure-Mediated Mendelian Randomization Analysis.

This study employed a two-step Mendelian randomization analysis to explore the causal relationship between telomere length, as a marker of aging, and anorexia nervosa and to evaluate the mediating role of changes in the white matter microstructure across different brain regions. We selected genetic variants associated with 675 diffusion magnetic resonance imaging phenotypes representing changes in brain white matter. F-statistics confirmed the validity of the instruments, ensuring robust causal inference. Sensitivity analyses, including heterogeneity tests, horizontal pleiotropy tests, and leave-one-out tests, validated the results. The results show that telomere length is significantly negatively correlated with anorexia nervosa in a unidirectional manner (p = 0.017). Additionally, changes in specific white matter structures, such as the internal capsule, corona radiata, posterior thalamic radiation, left cingulate gyrus, left longitudinal fasciculus, and left forceps minor (p < 0.05), were identified as mediators. These findings enhance our understanding of the neural mechanisms, underlying the exacerbation of anorexia nervosa with aging; emphasize the role of brain functional networks in disease progression; and provide potential biological targets for future therapeutic interventions.

Initial stage oxidation corrosion of commercial ferritic stainless steels with different Cr contents at 650 °C for solid oxide fuel cells.

Selecting adequate ferritic stainless steel (FSS) with a high corrosion resistance and a low cost is critical for solid oxide fuel cells (SOFCs) operating at intermediate temperature. In this study, the corrosion behaviors of four commercial FSSs involving TS430, TY441, YG442, and TY445 with a Cr content ranging from 16.18 wt.% to 21.73 wt.% are investigated at 650 °C. The oxidation mass gains, microstructures of surface oxide scale, and electrical conductivities are measured. The effects of grain size as well as doped elements are estimated together with the Cr volatilization. Flaky Cr2O3 particles are formed on TS430 and TY441 dominated by the outward migration of Cr3+. In comparison, a thin and dense layer of chromia is observed on YG442 and TY445. A high Cr content and a uniformly distributed grain size are conducive to the formation of a thin and dense chromia scale on the FSS surface during the initial oxidation process. On the other hand, the addition of Nb, Ti, and Mo weakens the outward diffusion of Cr3+ and reduces the particle size of chromia. After oxidation at 650 °C for 120 h, scattered (Mn, Cr)3O4 spinel particles occur on TS430, YG442, and TY445. TY445 and YG442 exhibit a higher conductivity although all the results of area specific resistance (ASR) are less than 6 mΩ·cm2. Meanwhile, the effect of Cr volatilization is enlarged on the estimation of mass gain at 650 °C compared with even higher temperatures.

A unified model-based framework for doublet or multiplet detection in single-cell multiomics data.

Droplet-based single-cell sequencing techniques rely on the fundamental assumption that each droplet encapsulates a single cell, enabling individual cell omics profiling. However, the inevitable issue of multiplets, where two or more cells are encapsulated within a single droplet, can lead to spurious cell type annotations and obscure true biological findings. The issue of multiplets is exacerbated in single-cell multiomics settings, where integrating cross-modality information for clustering can inadvertently promote the aggregation of multiplet clusters and increase the risk of erroneous cell type annotations. Here, we propose a compound Poisson model-based framework for multiplet detection in single-cell multiomics data. Leveraging experimental cell hashing results as the ground truth for multiplet status, we conducted trimodal DOGMA-seq experiments and generated 17 benchmarking datasets from two tissues, involving a total of 280,123 droplets. We demonstrated that the proposed method is an essential tool for integrating cross-modality multiplet signals, effectively eliminating multiplet clusters in single-cell multiomics data-a task at which the benchmarked single-omics methods proved inadequate.

Pyroptotic-Spatiotemporally Selective Delivery of siRNA against Pyroptosis and Autoimmune Diseases.

Small-interfering RNAs (siRNAs) offer promising prospects for treating pyroptosis-related autoimmune diseases. However, poor stability and off-target effects during in vivo transportation hinder their practical clinical applications. Precision delivery and adaptive release of siRNAs into inflamed tissues and immune cells could unleash their full therapeutic potential. This study establishes a pyroptotic-spatiotemporally selective siRNA delivery system (PMRC@siGSDME) that selectively targets inflammatory tissues, responds to pyroptosis, and exhibits remarkable therapeutic efficacy against various autoimmune diseases. Novel hybrid nanovesicles (NVs) are designed as a combination of pyroptotic macrophage membranes (PMs) and R8-cardiolipin-containing nanovesicles (RC-NVs). Evidence provides that PM-derived proteins involved in cell-cell interactions and membrane trafficking may contribute to the specificity of NVs to inflammatory tissue. In addition, cardiolipin anchored in the hybrid NVs increases its affinity for activated gasdermin E (GSDME) and achieves pyroptosis-adaptive release of siGSDME for the spatiotemporally selective suppression of immune responses. More importantly, PMRC@siGSDME displays significant anti-inflammatory and therapeutic effects in multiple mouse autoimmune disease models, including arthritis and inflammatory bowel disease (IBD). Collectively, an innovative siRNA delivery strategy precisely tailored for pyroptotic cells has been developed, paving the way for new treatments for autoimmune inflammatory diseases with minimal side effects and wide clinical applicability.

tBHQ mitigates fatty liver ischemia-reperfusion injury by activating Nrf2 to attenuate hepatocyte mitochondrial damage and macrophage STING activation.

BACKGROUND: Liver ischemia-reperfusion (IR) injury is an inevitable pathophysiological process in various liver surgeries. Previous studies have found that IR injury is exacerbated in fatty liver due to significant hepatocellular damage and macrophage inflammatory activation, though the underlying mechanisms are not fully understood. In this study, we aim to explore the role and mechanism of Nrf2 (Nuclear factor erythroid 2-related factor 2) signaling in regulating hepatocellular damage and macrophage immune response in fatty liver IR injury. METHODS: The study used high-fat diet-induced fatty liver mice to establish an IR model, alongside an in vitro co-culture system of primary hepatocytes and macrophages. This approach was used to examine mitochondrial dysfunction, oxidative stress, mitochondrial DNA (mtDNA) release, and activation of macrophage STING (Stimulator of interferon genes) signaling. We also conducted recovery verification using H-151 (a STING inhibitor) and tBHQ (an Nrf2 activator). RESULTS: Compared to the control group, mice on a high-fat diet demonstrated more severe liver IR injury, as evidenced by increased histological damage, elevated liver enzyme levels, and heightened inflammatory markers. The HFD group showed significant oxidative stress and mitochondrial dysfunction and damage post-IR, as indicated by elevated levels of ROS and lipid peroxidation markers, and decreased antioxidant enzyme activity. Elevated mtDNA release from hepatocytes post-IR activated macrophage STING signaling, worsening inflammation and liver damage. However, STING signaling inhibition with H-151 in vivo or employing STING knockout macrophages significantly reduced these injuries. In-depth mechanism studies have found that the transfer of Nrf2 protein into the nucleus of liver cells after IR in fatty liver is reduced. Pre-treatment with tBHQ ameliorated liver oxidative stress, mitochondrial damage and suppressed the macrophage STING signaling activation. CONCLUSIONS: Our study reveals a novel mechanism where the interaction between hepatocellular damage and macrophage inflammation intensifies liver IR injury in fatty liver. Enhancing Nrf2 activation to protect mitochondrial from oxidative stress damage and inhibiting macrophage STING signaling activation emerge as promising strategies for clinical intervention in fatty liver IR injury.

Neutrophil-to-lymphocyte ratio in colorectal tissue affects prognosis in patients with colorectal cancer.

The objective of this investigation was to analyse the correlation between the neutrophil-to-lymphocyte ratio (NLR) status in the immune microenvironment (IME) and the prognostic outcomes of patients who have undergone radical surgery for colorectal cancer (CRC). In light of the continued prevalence of CRC in China, this study utilised Kaplan-Meier and Cox regression analyses to assess the prognostic relevance of NLR status in IME among patients with CRC. Furthermore, cellular experiments, such as cell scratching, were conducted to elucidate the underlying mechanisms of NLR's impact on CRC. The NLR status in IME has been found to have a significant impact on the prognosis of patients with CRC. Patients who exhibit elevated intratumoural and extratumoural NLR are associated with a poor prognosis. Experimental evidence indicates that tumour-associated neutrophil (TAN) augments the migratory, invasive, and proliferative potential of HT-29, HCT-116 and LOVO colorectal cancer cells, while concurrently reducing their sensitivity to oxaliplatin. Conversely, lymphocytes have demonstrated cytotoxic effects on HT-29 cells. The NLR status in IME may serve as a prognostic biomarker for resectable CRC.

Inflammation in diabetes complications: molecular mechanisms and therapeutic interventions.

At present, diabetes mellitus (DM) has been one of the most endangering healthy diseases. Current therapies contain controlling high blood sugar, reducing risk factors like obesity, hypertension, and so on; however, DM patients inevitably and eventually progress into different types of diabetes complications, resulting in poor quality of life. Unfortunately, the clear etiology and pathogenesis of diabetes complications have not been elucidated owing to intricate whole-body systems. The immune system was responsible to regulate homeostasis by triggering or resolving inflammatory response, indicating it may be necessary to diabetes complications. In fact, previous studies have been shown inflammation plays multifunctional roles in the pathogenesis of diabetes complications and is attracting attention to be the meaningful therapeutic strategy. To this end, this review systematically concluded the current studies over the relationships of susceptible diabetes complications (e.g., diabetic cardiomyopathy, diabetic retinopathy, diabetic peripheral neuropathy, and diabetic nephropathy) and inflammation, ranging from immune cell response, cytokines interaction to pathomechanism of organ injury. Besides, we also summarized various therapeutic strategies to improve diabetes complications by target inflammation from special remedies to conventional lifestyle changes. This review will offer a panoramic insight into the mechanisms of diabetes complications from an inflammatory perspective and also discuss contemporary clinical interventions.

Human-multimodal deep learning collaboration in 'precise' diagnosis of lupus erythematosus subtypes and similar skin diseases.

BACKGROUND: Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of cutaneous LE (CLE), clinical skin image-based artificial intelligence is still experiencing difficulties in distinguishing subtypes of LE. OBJECTIVES: We aim to develop a multimodal deep learning system (MMDLS) for human-AI collaboration in diagnosis of LE subtypes. METHODS: This is a multi-centre study based on 25 institutions across China to assist in diagnosis of LE subtypes, other eight similar skin diseases and healthy subjects. In total, 446 cases with 800 clinical skin images, 3786 multicolor-immunohistochemistry (multi-IHC) images and clinical data were collected, and EfficientNet-B3 and ResNet-18 were utilized in this study. RESULTS: In the multi-classification task, the overall performance of MMDLS on 13 skin conditions is much higher than single or dual modals (Sen = 0.8288, Spe = 0.9852, Pre = 0.8518, AUC = 0.9844). Further, the MMDLS-based diagnostic-support help improves the accuracy of dermatologists from 66.88% ± 6.94% to 81.25% ± 4.23% (p = 0.0004). CONCLUSIONS: These results highlight the benefit of human-MMDLS collaborated framework in telemedicine by assisting dermatologists and rheumatologists in the differential diagnosis of LE subtypes and similar skin diseases.

Association between gut microbiota and menstrual disorders: a two-sample Mendelian randomization study.

Background: Evidence from observational studies and clinical trials suggests that the gut microbiota is associated with gynecological diseases. However, the causal relationship between gut microbiota and menstrual disorders remains to be determined. Methods: We obtained summary data of gut microbiota from the global consortium MiBio-Gen's genome-wide association study (GWAS) dataset and data on menstrual disorders from the IEU Open GWAS project. MR-Egger, weighted median, inverse variance weighted, simple mode, and weighted mode were used to examine the causal association between gut microbiota and menstrual disorders. Thorough sensitivity studies were performed to confirm the data's horizontal pleiotropy, heterogeneity, and robustness. Results: Through MR analysis of 119 kinds of gut microbiota and 4 kinds of clinical phenotypes, it was discovered that 23 different kinds of gut microbiota were loosely connected to menstrual disorders. After FDR correction, the results showed that only Escherichia/Shigella (p = 0.00032, PFDR = 0.0382, OR = 1.004, 95%CI = 1.002-1.006) is related to menstrual disorders. Conclusion: According to our MR Analysis, there are indications of a causal relationship between menstrual disorders and gut microbiota. This finding could lead to new discoveries into the mechanisms behind menstrual disorders and clinical research involving the microbiota.

Data-driven learning of chaotic dynamical systems using Discrete-Temporal Sobolev Networks.

We introduce the Discrete-Temporal Sobolev Network (DTSN), a neural network loss function that assists dynamical system forecasting by minimizing variational differences between the network output and the training data via a temporal Sobolev norm. This approach is entirely data-driven, architecture agnostic, and does not require derivative information from the estimated system. The DTSN is particularly well suited to chaotic dynamical systems as it minimizes noise in the network output which is crucial for such sensitive systems. For our test cases we consider discrete approximations of the Lorenz-63 system and the Chua circuit. For the network architectures we use the Long Short-Term Memory (LSTM) and the Transformer. The performance of the DTSN is compared with the standard MSE loss for both architectures, as well as with the Physics Informed Neural Network (PINN) loss for the LSTM. The DTSN loss is shown to substantially improve accuracy for both architectures, while requiring less information than the PINN and without noticeably increasing computational time, thereby demonstrating its potential to improve neural network forecasting of dynamical systems.

Phenolylazoindole scaffold for facilely synthesized and bis-functional photoswitches combining controllable fluorescence and antifungal properties using theoretical methods.

Functionalization is a major challenge for the application of photoswitches. With the aim to develop novel bis-functional azo photoswitches with stationary photophysical properties, a series of phenolylazoindole derivatives were designed, synthesized, and characterized via NMR spectroscopy studies and high-resolution mass spectrometry (HRMS). Herein, UV/Vis and 1H NMR spectra revealed that the photostationary state (PSS) proportions for PSScis and PSStrans were 76-80% and 68-81%, respectively. Furthermore, the thermal half-lives (t1/2) of compounds A2-A4 and B2 ranged from 0.9 to 5.3 h, affected by the diverse substituents at the R1 and R2 positions. The results indicated that azo photoswitches based on the phenolylazoindole scaffold had stationary photophysical properties and wouldn't be excessively affected by modifying the functional groups. Compounds A4 and B2, which were modified with an aryl group, also exhibited fluorescence emission properties (the quantum yields of A4 and B2 were 2.32% and 13.34%) through the modification of the flexible conjugated structure (benzene) at the R2 position. Significantly, compound C1 was obtained via modification with a pharmacophore in order to acquire antifungal activities against three plant fungi, Rhizoctonia solani (R. solani), Botrytis cinerea (B. cinerea), and Fusarium graminearum (F. graminearum). Strikingly, the inhibitory activity of the cis-isomer of compound C1towards R. solani (53.3%) was significantly better than that of the trans-isomer (34.2%) at 50 µg mL-1. In order to further reveal the antifungal mechanism, molecular docking simulations demonstrated that compound C1 effectively integrates into the cavity of succinate dehydrogenase (SDH); the optically controlled cis-isomer showed a lower binding energy with SDH than that of the trans-isomer. This research confirmed that phenolylazoindole photoswitches can be appropriately applied as molecular regulatory devices and functional photoswitch molecules via bis-functionalization.

Construction of a conjugated covalent organic framework for iodine capture.

Radioactive iodine in the nuclear field is considered very dangerous nuclear waste because of its chemical toxicity, high mobility and long radioactive half-life. Herein, a conjugated two-dimensional covalent organic framework, TPB-TMPD-COF, has been designed and synthesized for iodine capture. TPB-TMPD-COF has been well characterized by several techniques and showed long order structure and a large surface area (1090 m2 g-1). Moreover, TPB-TMPD-COF shows a high iodine capture value at 4.75 g g-1 under 350 K and normal pressure conditions, benefitting from the increased density of adsorption sites. By using multiple techniques, the iodine vapor adsorbed into the pores may readily generate the electron transfer species (I3- and I5-) due to the strong interactions between imine groups and iodine molecules, which contributes to the high iodine uptake for TPB-TMPD-COF. Our study will stimulate the design and synthesis of COFs as a solid-phase adsorbent for iodine uptake.

The Influence of the Preoperative Albumin to Alkaline Phosphatase Ratio on Overall Survival in Post-Radical Surgery for Colorectal Cancer and the Construction of a Nomogram Prediction Model.

PURPOSE: The albumin to alkaline phosphatase ratio (AAPR) is a newly developed blood biomarker that has been reported to have prognostic value in several types of cancers. The aim of this study was to investigate the predictive value of AAPR in overall survival after radical colon cancer surgery in patients with stage I-III colorectal cancer (CRC). METHODS: The clinical data of 221 eligible patients with stage I ∼ III CRC were retrospectively analyzed. A series of survival analyses were performed to assess the prognostic value of AAPR. Univariate and multifactorial Cox analyses were performed to identify independent risk factors. Columnar graph prediction models were further constructed based on independent risk factors such as AAPR, and their predictive properties were validated. RESULTS: The optimal cutoff value of preoperative AAPR for postoperative overall survival (OS) in patients undergoing laparoscopic radical CRC was .495 as shown by univariate and multifactorial Cox regression analysis. The factors of age ≤65 years, Tumor-Node-Metastasis (TNM) stage I-II, tumor grading (high/medium differentiation), CEA ≤5, and AAPR ≥.495 were associated with better OS (P < .05). CONCLUSIONS: Preoperative AAPR level was a good predictor of postoperative survival in patients undergoing laparoscopic radical CRC surgery, and AAPR <.495 was an independent risk factor for decreased postoperative OS.

Deletion of Mettl3 in mesenchymal stem cells promotes acute myeloid leukemia resistance to chemotherapy.

Acute myeloid leukemia (AML) cell survival and chemoresistance are influenced by the existence of bone marrow mesenchymal stem cells (BMMSCs); however, the pathways by which BMMSCs contribute to these processes remain unclear. We earlier revealed that methyltransferase-like 3 (METTL3) expression is significantly reduced in AML BMMSCs and that METTL3 mediates BMMSC adipogenesis to promote chemoresistance in human AML cell lines in vitro. In this investigation, we evaluated the METTL3 function in vivo. Mice exhibiting a conditional removal of Mettl3 in BMMSCs were developed by mating Prrx1-CreERT2;Mettl3fl/+ mice with Mettl3fl/fl mice using the CRISPR-Cas9 system. The Mettl3 deletion increased bone marrow adiposity, enhanced disease progression in the transplantation-induced MLL-AF9 AML mouse model, and chemoresistance to cytarabine. The removal of Mettl3 in BMMSCs resulted in a significant increase in BMMSC adipogenesis. This effect was attributed to the downregulation of AKT1 expression, an AKT serine/threonine kinase 1, in an m6A-dependent manner. The development of chemoresistance in AML is linked to the promoted adipogenesis of BMMSCs. We conclude that METTL3 expression in BMMSCs has a critical function in limiting AML progression and chemoresistance, providing a basis for the progression of therapeutic approaches for AML.