A multi-bin rarefying method for evaluating alpha diversities in TCR sequencing data.

MOTIVATION: T cell receptors (TCRs) constitute a major component of our adaptive immune system, governing the recognition and response to internal and external antigens. Studying the TCR diversity via sequencing technology is critical for a deeper understanding of immune dynamics. However, library sizes differ substantially across samples, hindering the accurate estimation/comparisons of alpha diversities. To address this, researchers frequently use an overall rarefying approach in which all samples are sub-sampled to an even depth. Despite its pervasive application, its efficacy has never been rigorously assessed. RESULTS: In this paper, we develop an innovative "multi-bin" rarefying approach that partitions samples into multiple bins according to their library sizes, conducts rarefying within each bin for alpha diversity calculations, and performs meta-analysis across bins. Extensive simulations using real-world data highlight the inadequacy of the overall rarefying approach in controlling the confounding effect of library size. Our method proves robust in addressing library size confounding, outperforming competing normalization strategies by achieving better-controlled type-I error rates and enhanced statistical power in association tests. AVAILABILITY AND IMPLEMENTATION: The code is available at https://github.com/mli171/MultibinAlpha. The datasets are freely available at https://doi.org/10.21417/B7001Z and https://doi.org/10.21417/AR2019NC.

Development of a Novel Prediction Tool for Response to First-Line Treatments of Monosymptomatic Nocturnal Enuresis-A Randomized, Controlled International Multicenter Study (DRYCHILD).

PURPOSE: Nocturnal urine volume and bladder reservoir function are key pathogenic factors behind monosymptomatic nocturnal enuresis (MNE). We investigated the predictive value of these together with other demographic and clinical variables for response to first-line treatments in children with MNE. MATERIALS AND METHODS: A randomized, controlled, international multicenter study was conducted in 324 treatment-naïve children (6-14 years) with primary MNE. The children were randomized to treatment with or without prior consideration of voiding diaries. In the group where treatment choice was based on voiding diaries, children with nocturnal polyuria and normal maximum voided volume (MVV) received desmopressin (dDAVP) treatment and children with reduced MVV and no nocturnal polyuria received an enuresis alarm. In the other group, treatment with dDAVP or alarm was randomly allocated. RESULTS: A total of 281 children (72% males) were qualified for statistical analysis. The change of responding to treatment was 21% higher in children where treatment was individualized compared to children where treatment was randomly selected (RR = 1.21 (1.02-1.45), P = .032). In children with reduced MVV and no nocturnal polyuria (35% of all children), individualized treatment was associated with a 46% improvement in response compared to random treatment selection (RR = 1.46 (1.14-1.87), P = .003). Furthermore, we developed a clinically relevant prediction model for response to dDAVP treatment (ROC 0.85). CONCLUSIONS: The present study demonstrates that treatment selection based on voiding diaries improve response to first line treatment, particularly in specific subtypes. Information from voiding diaries together with clinical and demographic information provides the basis for predicting response.

Construction of Highly Accurate Machine Learning Potential Energy Surfaces for Excited-State Dynamics Simulations Based on Low-Level Data Sets.

Machine learning is capable of effectively predicting the potential energies of molecules in the presence of high-quality data sets. Its application in the construction of ground- and excited-state potential energy surfaces is attractive to accelerate nonadiabatic molecular dynamics simulations of photochemical reactions. Because of the huge computational cost of excited-state electronic structure calculations, the construction of a high-quality data set becomes a bottleneck. In the present work, we first built two data sets. One was obtained from surface hopping dynamics simulations at the semiempirical OM2/MRCI level. Another was extracted from the dynamics trajectories at the CASSCF level, which was reported previously. The ground- and excited-state potential energy surfaces of ethylene-bridged azobenzene at the CASSCF computational level were constructed based on the former low-level data set. Although non-neural network machine learning methods can achieve good or modest performance during the training process, only neural network models provide reliable predictions on the latter external test data set. The BPNN and SchNet combined with the Δ-ML scheme and the force term in the loss functions are recommended for dynamics simulations. Then, we performed excited-state dynamics simulations of the photoisomerization of ethylene-bridged azobenzene on machine learning potential energy surfaces. Compared with the lifetimes of the first excited state (S1) estimated at different computational levels, our results on the E isomer are in good agreement with the high-level estimation. However, the overestimation of the Z isomer is unimproved. It suggests that smaller errors during the training process do not necessarily translate to more accurate predictions on high-level potential energies or better performance on nonadiabatic dynamics simulations, at least in the present case.

Assessment of toxic effects of thallium on the earthworm Eisenia fetida using the biomarker response index.

Thallium (Tl), though not essential for biological systems, is widely used in industrial activities, resulting in soil pollution and adverse effects on soil biota. Systematic toxicological studies on Tl, especially concerning soil organisms, are relatively rare. This research evaluates the toxic effects of Tl on earthworms by measuring oxidative stress biomarkers, such as superoxide dismutase (SOD), catalase (CAT), glutathione S-transferase (GST), malondialdehyde (MDA), and 8-hydroxydeoxyguanosine (8-OHdG), and by assessing the expression of functional genes, such as heat shock protein 70 (Hsp70), metallothionein (MT), and annetocin (ANN). Additionally, this study employs the Biomarker Response Index (BRI) and two-way ANOVA to comprehensively assess the cumulative toxicity of Tl in earthworms. The findings indicate that Tl exposure significantly exacerbates oxidative stress and cellular damage in earthworms, particularly under conditions of high concentration and prolonged exposure. BRI results demonstrate a continuous decline in the physiological state of earthworms with increasing Tl concentration and exposure duration. Two-way ANOVA reveals significant dose-responsive increases in SOD and CAT activities, as well as in ANN gene expression. Apart from GST activity, other biomarkers significantly increased over time, and the changes in biomarkers such as SOD, CAT, MDA, and 8-OHdG were significantly influenced by dose and time. LSD post hoc tests show significant effects of dose, time, and their interactions on all biomarkers except for GST. These findings are valuable for gaining a deeper understanding of the ecological risks of Tl in soil environments and its potential threats to soil biota, aiding in the management of ecological risks associated with Tl-contaminated soils.

Pedobacter deserti sp. nov., a novel species isolated from desert soil.

An aerobic, Gram-stain-negative bacterium, designated as SYSU D00382T, was sourced from soil of Gurbantunggut Desert, PR China. The strain was short-rod-shaped, oxidase-positive and catalase-negative, with yellow-colored, convex, round, and smooth colonies on TSA plate. Growth and proliferation occurred at 4-37 °C (optimal: 28-30 °C), pH 5.0-8.0 (optimal: pH 6.0-7.0) and NaCl concentration of 0-2.5% (optimal: 0-0.5%). The 16S rRNA gene based phylogenetic assessment showed that SYSU D00382T belonged to the genus Pedobacter, and was most closely related to Pedobacter ginsengisoli Gsoil 104T with similarity of 97.7%. The genomic DNA G+C content of SYSU D00382T was 46.4%. The average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values between SYSU D00382T and P. ginsengisoli Gsoil 104T were 75.7% and 17.5%, respectively. The main polar lipid was phosphatidylethanolamine. The major fatty acids (> 5%) were iso-C15:0, iso-C17:0 3-OH, summed features 3 and 9. The sole respiratory quinone identified was MK-7. The phylogeny based on 16S rRNA gene and whole-genome sequences revealed that SYSU D00382T formed a robust lineage with P. ginsengisoli Gsoil 104T. Based on phenotypic, phylogenetic and genotypic data, a novel specie named Pedobacter deserti sp. nov. is proposed. The type strain is SYSU D00382T (= CGMCC 1.18627T = MCCC 1K04972T = KCTC 82279T).

TalkingStyle: Personalized Speech-Driven 3D Facial Animation with Style Preservation.

It is a challenging task to create realistic 3D avatars that accurately replicate individuals' speech and unique talking styles for speech-driven facial animation. Existing techniques have made remarkable progress but still struggle to achieve lifelike mimicry. This paper proposes "TalkingStyle", a novel method to generate personalized talking avatars while retaining the talking style of the person. Our approach uses a set of audio and animation samples from an individual to create new facial animations that closely resemble their specific talking style, synchronized with speech. We disentangle the style codes from the motion patterns, allowing our method to associate a distinct identifier with each person. To manage each aspect effectively, we employ three separate encoders for style, speech, and motion, ensuring the preservation of the original style while maintaining consistent motion in our stylized talking avatars. Additionally, we propose a new style-conditioned transformer decoder, offering greater flexibility and control over the facial avatar styles. We comprehensively evaluate TalkingStyle through qualitative and quantitative assessments, as well as user studies demonstrating its superior realism and lip synchronization accuracy compared to current state-of-the-art methods. To promote transparency and further advancements in the field, we also make the source code publicly available at https://github.com/wangxuanx/TalkingStyle.

Language-Guided 3-D Action Feature Learning Without Ground-Truth Sample Class Label.

This work pays the first research effort to leverage point cloud sequence-based Self-supervised 3-D Action Feature Learning (S3AFL), under text's cross-modality weak supervision. We intend to fill the huge performance gap between point cloud sequence and 3-D skeleton-based manners. The key intuition derives from the observation that skeleton-based manners actually hold the human pose's high-level knowledge that leads to attention on the body's joint-aware local parts. Inspired by this, we propose to introduce the text's weak supervision of high-level semantics into a point cloud sequence-based paradigm. With RGB-point cloud pair sequence acquired via RGB-D camera, text sequence is first generated from RGB component using pretrained image captioning model, as auxiliary weak supervision. Then, S3AFL runs in a cross and intra-modality contrastive learning (CL) way. To resist text's missing and redundant semantics, feature learning is conducted in a multistage way with semantic refinement. Essentially, text is only required for training. To facilitate the feature's representation power on fine-grained actions, a multirank max-pooling (MR-MP) way is also proposed for the point set network to better maintain discriminative clues. Experiments verify that the text's weak supervision can facilitate performance by 10.8%, 10.4%, and 8.0% on NTU RGB + D 60, 120, and N-UCLA at most. The performance gap between point cloud sequence and skeleton-based manners has been remarkably narrowed down. The idea of transferring text's weak supervision to S3AFL can also be applied to a skeleton manner, with strong generality. The source code is available at https://github.com/tangent-T/W3AMT.

Overexpression of COX7A1 Promotes the Resistance of Gastric Cancer to Oxaliplatin and Weakens the Efficacy of Immunotherapy.

Gastric cancer (GC) is one of the most common clinical malignant tumors worldwide, with high morbidity and mortality. Presently, the overall response rate to immunotherapy is low, and current methods for predicting the prognosis of GC are not optimal. Therefore, novel biomarkers with accuracy, efficiency, stability, performance ratio, and wide clinical application are needed. Based on public data sets, the chemotherapy cohort and immunotherapy cohort from Sun Yat-sen University Cancer Center, a series of bioinformatics analyses, such as differential expression analysis, survival analysis, drug sensitivity prediction, enrichment analysis, tumor immune dysfunction and exclusion analysis, single-sample gene set enrichment analysis, stemness index calculation, and immune cell infiltration analysis, were performed for screening and preliminary exploration. Immunohistochemical staining and in vitro experiments were performed for further verification. Overexpression of COX7A1 promoted the resistance of GC cells to Oxaliplatin. COX7A1 may induce immune escape by regulating the number of fibroblasts and their cellular communication with immune cells. In summary, measuring the expression levels of COX7A1 in the clinic may be useful in predicting the prognosis of GC patients, the degree of chemotherapy resistance, and the efficacy of immunotherapy.

Higher water content observed in smaller size fraction of Chang'e-5 lunar regolith samples.

Water has been detected in lunar regolith, with multiple sources identified through the analysis of individual grains. However, the primary origin of water in the bulk lunar regolith remains uncertain. This study presents spectroscopic analyses of water content in sealed Chang'e-5 samples. These samples were sieved into various size fractions (bulk, <45 µm, and 45-355 µm) inside a glovebox filled with high-purity nitrogen. Results indicate a higher water content in the fine fractions (∼87 ± 11.9 ppm) than in bulk soil (∼37 ± 4.8 ppm) and coarse fractions (∼11 ± 1.5 ppm). This suggests that water is predominantly concentrated in the outermost rims of the regolith grains, and thus exhibits dependence on the surface volume ratio (also known as surface correlation), indicating solar wind is a primary source of lunar surface water. Laboratory, in-situ, and orbital results bridge sample analysis and remote sensing, offering a cohesive understanding of lunar surface water characteristics as represented by Chang'e-5. The discovery provides statistical evidence for the origin of water in lunar soil and can be considered representative of the lunar surface conditions. The water enrichment of the finest fraction suggests the feasibility of employing size sorting of lunar soils as a potential technological approach for water resource extraction in future lunar research stations.

Downregulation of HIGD1B induces mitochondria-mediated apoptosis in gastric cancer cells by inactivating Akt and ERK pathways.

Gastric cancer (GC) is one of the most common malignancies worldwide. Hypoxia-inducible domain (HIGD) family members (e.g., HIGD1A) have been linked to tumor progression. However, the role of HIGD1B (another HIGD family member) in GC has yet to be fully understood. Based on data from TCGA_GC, GSE65801, and GSE65801 data sets, HIGD1B levels were evaluated in normal and GC tissues. Next, HIGD1B levels were validated by reverse transcription-quantitative PCR and western blot analysis analyses. Meanwhile, patients with GC in the TCGA_GC cohort were grouped into high- and low-HIGD1B level groups, and overall survival, functional enrichment, and immune infiltration were analyzed. Additionally, gain- and loss-of-function experiments were performed to determine the function of HIGD1B in GC cells. Compared to normal controls, HIGD1B mRNA levels were significantly elevated in GC tissues. Moreover, high HIGD1B levels may be an independent indicator of poor prognosis in patients with GC. Additionally, high HIGD1B levels were correlated with high stromal and ESTIMATE scores and elevated expression of immune checkpoints in patients with GC. Functional analyses showed that HIGD1B deficiency notably suppressed GC cell proliferation, migration, and invasion. Moreover, HIGD1B deficiency significantly induced mitochondria-mediated apoptosis in GC cells by inactivating Akt and ERK pathways. Collectively, HIGD1B may predict the prognosis of patients with GC and may function as an oncogene in GC. These findings suggest that HIGD1B may serve as a prognostic biomarker and potential therapeutic target in GC.

Deep learning model to discriminate diverse infection types based on pairwise analysis of host gene expression.

Accurate detection of pathogens, particularly distinguishing between Gram-positive and Gram-negative bacteria, could improve disease treatment. Host gene expression can capture the immune system's response to infections caused by various pathogens. Here, we present a deep neural network model, bvnGPS2, which incorporates the attention mechanism based on a large-scale integrated host transcriptome dataset to precisely identify Gram-positive and Gram-negative bacterial infections as well as viral infections. We performed analysis of 4,949 blood samples across 40 cohorts from 10 countries using our previously designed omics data integration method, iPAGE, to select discriminant gene pairs and train the bvnGPS2. The performance of the model was evaluated on six independent cohorts comprising 374 samples. Overall, our deep neural network model shows robust capability to accurately identify specific infections, paving the way for precise medicine strategies in infection treatment and potentially also for identifying subtypes of other diseases.

Variation in soil bacterial community characteristics inside and outside the West Ordos National Nature Reserve, northern China.

Nature reserves are crucial for protecting biological habitats and maintaining biodiversity. Soil bacterial community plays an irreplaceable role in the structure and function of ecosystem. However, the impact of nature reserves on soil bacterial communities is still unclear. To explore the effects of desert grassland nature reserve management on soil microbial communities, we compared the differences in soil bacterial community composition, α-diversity and community structure inside and outside a desert grassland nature reserve, and explored the correlation between soil bacterial communities and plant biomass and soil chemical index. We found that (1) the relative abundance of Acidobacteriota is highest in the soil both inside and outside the nature reserve in shrub grassland; (2) the Chao1 index of soil bacterial communities in the core protected zone and general control zone of the reserve was significantly higher than that outside the reserve (p < 0.05) in the shrub grassland. Similarly, in the herbaceous grassland, the Shannon index of soil bacterial communities was significantly higher in the core protected zone of the reserve than that outside the reserve (p < 0.05). (3) While we found no significant difference in soil bacterial community structure between inside and outside the reserve in the shrub grassland, we found that the soil bacterial community structure in the core protected zone was significantly different from that outside the reserve in the herbaceous grassland (p < 0.05); (4) we also found that higher plant productivity and soil nutrients promoted most soil dominant bacterial phyla, while higher soil pH and salinity inhibited most soil dominant bacterial phyla. Our findings thus help better understand the influencing factors of and the mechanisms behind variation in soil bacterial communities inside and outside desert grassland nature reserves.

A Zeroing Neural Network Approach for Calculating Time-Varying G-Outer Inverse of Arbitrary Matrix.

Calculation of the time-varying (TV) matrix generalized inverse has grown into an essential tool in many fields, such as computer science, physics, engineering, and mathematics, in order to tackle TV challenges. This work investigates the challenge of finding a TV extension of a subclass of inner inverses on real matrices, known as generalized-outer (G-outer) inverses. More precisely, our goal is to construct TV G-outer inverses (TV-GOIs) by utilizing the zeroing neural network (ZNN) process, which is presently thought to be a state-of-the-art solution to tackling TV matrix challenges. Using known advantages of ZNN dynamic systems, a novel ZNN model, called ZNNGOI, is presented in the literature for the first time in order to compute TV-GOIs. The ZNNGOI performs excellently in performed numerical simulations and an application on addressing localization problems. In terms of solving linear TV matrix equations, its performance is comparable to that of the standard ZNN model for computing the pseudoinverse.

The fusiform skin paddle in fibula free flap: a fusiform-designed skin paddle for maxillofacial soft defect reconstruction and reducing leg wound tension.

Objective: To investigate the feasibility of leg wound closure and reconstruction of maxillofacial soft defect by a fusiform-designed skin paddle in fibula free flap (FFF). Methods: Fifty patients who underwent FFF for reconstruction of maxillofacial soft defect were divided into two groups. The fusiform group (20 patients) was treated using a fusiform-designed skin paddle in FFF (skin paddle width less than 2 cm), and leg wound was closed using primary suturing. Reconstruction of the maxillofacial soft defect or filling of dead space was achieved by folding the fusiform skin paddle. The conventional group (30 patients) was treated using the conventional-designed skin paddle (skin paddle width no less than 2.5 cm). The leg wound was closed using mattress suturing or skin graft, while reconstruction of the maxillofacial soft defect or filling of dead space by conventional way. The average postoperative length of hospital stay, healing time of leg wound, and post-surgical complications were recorded at least 6 months after the surgery. Results: Compared with traditional method, the fusiform-designed skin paddle reduced the average healing time of the leg wound (fusiform group: 11.05 days, conventional group: 14.77 days, P < 0.05). The average length-to-width ratio in fusiform group was significantly greater than that of in conventional group (fusiform group: 5.85, conventional group: 2.93, P < 0.05), and no difference was observed on the graft size of skin paddle between two groups (fusiform group: 23.13, conventional group: 27.13, P > 0.05). The post-surgical early complications of the leg wound in the conventional group were higher than that of in the fusiform group (fusiform group: 0%, conventional group: 6.67%), while the post-surgical late complication of the donor site between the two groups showed no case. Healing disorders of maxillofacial soft reconstruction in the conventional group were higher than that of in the fusiform group (fusiform group: 5.26%, conventional group: 20.69%). Conclusions: Fusiform-designed skin paddle for closure of the leg wound and maxillofacial soft defect is a feasible alternative to the conventional- designed skin paddle. The fusiform- designed skin paddle resulted in the less postoperative length of hospital stay, shorter healing time of leg wound and less complication.

Discrete-Time Impedance Control for Dynamic Response Regulation of Parallel Soft Robots.

Accurately controlling the dynamic response and suppression of undesirable dynamics such as overshoots and vibrations is a vital requirement for soft robots operating in industrial environments. Pneumatically actuated soft robots usually undergo large overshoots and significant vibrations when deactuated because of their highly flexible bodies. These large vibrations not only decrease the reliability and accuracy of the soft robot but also introduce undesirable characteristics in the system. For example, it increases the settling time and damages the body of the soft robot, compromising its structural integrity. The dynamic behavior of the soft robots on deactuation needs to be accurately controlled to increase their utility in real-world applications. The literature on pneumatic soft robots still does not sufficiently address the issue of suppressing undesirable vibrations. To address this issue, we propose the use of impedance control to regulate the dynamic response of pneumatic soft robots since the superiority of impedance control is already established for rigid robots. The soft robots are highly nonlinear systems; therefore, we formulated a nonlinear discrete sliding mode impedance controller to control the pneumatic soft robots. The formulation of the controller in discrete-time allows efficient implementation for a high-order system model without the need for state-observers. The simplification and efficiency of the proposed controller enable fast implementation of an embedded system. Unlike other works on pneumatic soft robots, the proposed controller does not require manual tuning of the controller parameters and automatically calculates the parameters based on the impedance value. To demonstrate the efficacy of the proposed controller, we used a 6-chambered parallel soft robot as an experimental platform. We presented the comparative results with an existing state-of-the-art controller in SMC control of pneumatic soft robots. The experiment results indicate that the proposed controller can effectively limit the amplitude of the undesirable vibrations.

In Situ Generation and High Bioresistance of Trityl-based Semiquinone Methide Radicals under Anaerobic Conditions in Cellular Systems.

Bioreduction of spin labels and polarizing agents (generally stable radicals) has been an obstacle limiting the in-cell applications of pulsed electron paramagnetic resonance (EPR) spectroscopy and dynamic nuclear polarization (DNP). In this work, we have demonstrated that two semiquinone methide radicals (OXQM• and CTQM•) can be easily produced from the trityl-based quinone methides (OXQM and CTQM) via reduction by various reducing agents including biothiols and ascorbate under anaerobic conditions. Both radicals have relatively low pKa's and exhibit EPR single line signals at physiological pH. Moreover, the bioreduction of OXQM in three cell lysates enables quantitative generation of OXQM• which was most likely mediated by flavoenzymes. Importantly, the resulting OXQM• exhibited extremely high stability in the E.coli lysate under anaerobic conditions with 76- and 14.3-fold slower decay kinetics as compared to the trityl OX063 and a gem-diethyl pyrrolidine nitroxide. Intracellular delivery of OXQM into HeLa cells was also achieved by covalent conjugation with a cell-permeable peptide as evidenced by the stable intracellular EPR signal from the OXQM• moiety. Owing to extremely high resistance of OXQM• towards bioreduction, OXQM and its derivatives show great application potential in in-cell EPR and in-cell DNP studies for various cells which can endure short-term anoxic treatments.

RUNX1 regulates MCM2/CDC20 to promote COAD progression modified by deubiquitination of USP31.

Colon adenocarcinoma (COAD) is the second leading cause of cancer death, and there is still a lack of diagnostic biomarkers and therapeutic targets. In this study, bioinformatics analysis of the TCGA database was used to obtain RUNX1, a gene with prognostic value in COAD. RUNX1 plays an important role in many malignancies, and its molecular regulatory mechanisms in COAD remain to be fully understood. To explore the physiological role of RUNX1, we performed functional analyses, such as CCK-8, colony formation and migration assays. In addition, we investigated the underlying mechanisms using transcriptome sequencing and chromatin immunoprecipitation assays. RUNX1 is highly expressed in COAD patients and significantly correlates with survival. Silencing of RUNX1 significantly slowed down the proliferation and migratory capacity of COAD cells. Furthermore, we demonstrate that CDC20 and MCM2 may be target genes of RUNX1, and that RUNX1 may be physically linked to the deubiquitinating enzyme USP31, which mediates the upregulation of RUNX1 protein to promote transcriptional function. Our results may provide new insights into the mechanism of action of RUNX1 in COAD and reveal potential therapeutic targets for this disease.

Acetylcytidine modification of Amotl1 by N-acetyltransferase 10 contributes to cardiac fibrotic expansion in mice after myocardial infarction.

Cardiac fibrosis is a pathological scarring process that impairs cardiac function. N-acetyltransferase 10 (Nat10) is recently identified as the key enzyme for the N4-acetylcytidine (ac4C) modification of mRNAs. In this study, we investigated the role of Nat10 in cardiac fibrosis following myocardial infarction (MI) and the related mechanisms. MI was induced in mice by ligation of the left anterior descending coronary artery; cardiac function was assessed with echocardiography. We showed that both the mRNA and protein expression levels of Nat10 were significantly increased in the infarct zone and border zone 4 weeks post-MI, and the expression of Nat10 in cardiac fibroblasts was significantly higher compared with that in cardiomyocytes after MI. Fibroblast-specific overexpression of Nat10 promoted collagen deposition and induced cardiac systolic dysfunction post-MI in mice. Conversely, fibroblast-specific knockout of Nat10 markedly relieved cardiac function impairment and extracellular matrix remodeling following MI. We then conducted ac4C-RNA binding protein immunoprecipitation-sequencing (RIP-seq) in cardiac fibroblasts transfected with Nat10 siRNA, and revealed that angiomotin-like 1 (Amotl1), an upstream regulator of the Hippo signaling pathway, was the target gene of Nat10. We demonstrated that Nat10-mediated ac4C modification of Amotl1 increased its mRNA stability and translation in neonatal cardiac fibroblasts, thereby increasing the interaction of Amotl1 with yes-associated protein 1 (Yap) and facilitating Yap translocation into the nucleus. Intriguingly, silencing of Amotl1 or Yap, as well as treatment with verteporfin, a selective and potent Yap inhibitor, attenuated the Nat10 overexpression-induced proliferation of cardiac fibroblasts and prevented their differentiation into myofibroblasts in vitro. In conclusion, this study highlights Nat10 as a crucial regulator of myocardial fibrosis following MI injury through ac4C modification of upstream activators within the Hippo/Yap signaling pathway.

Role of gut microbiota in regulating immune checkpoint inhibitor therapy for glioblastoma.

Glioblastoma (GBM) is a highly malignant, invasive, and poorly prognosed brain tumor. Unfortunately, active comprehensive treatment does not significantly prolong patient survival. With the deepening of research, it has been found that gut microbiota plays a certain role in GBM, and can directly or indirectly affect the efficacy of immune checkpoint inhibitors (ICIs) in various ways. (1) The metabolites produced by gut microbiota directly affect the host's immune homeostasis, and these metabolites can affect the function and distribution of immune cells, promote or inhibit inflammatory responses, affect the phenotype, angiogenesis, inflammatory response, and immune cell infiltration of GBM cells, thereby affecting the effectiveness of ICIs. (2) Some members of the gut microbiota may reverse T cell function inhibition, increase T cell anti-tumor activity, and ultimately improve the efficacy of ICIs by targeting specific immunosuppressive metabolites and cytokines. (3) Some members of the gut microbiota directly participate in the metabolic process of drugs, which can degrade, transform, or produce metabolites, affecting the effective concentration and bioavailability of drugs. Optimizing the structure of the gut microbiota may help improve the efficacy of ICIs. (4) The gut microbiota can also regulate immune cell function and inflammatory status in the brain through gut brain axis communication, indirectly affecting the progression of GBM and the therapeutic response to ICIs. (5) Given the importance of gut microbiota for ICI therapy, researchers have begun exploring the use of fecal microbiota transplantation (FMT) to transplant healthy or optimized gut microbiota to GBM patients, in order to improve their immune status and enhance their response to ICI therapy. Preliminary studies suggest that FMT may enhance the efficacy of ICI therapy in some patients. In summary, gut microbiota plays a crucial role in regulating ICIs in GBM, and with a deeper understanding of the relationship between gut microbiota and tumor immunity, it is expected to develop more precise and effective personalized ICI therapy strategies for GBM, in order to improve patient prognosis.