pH-responsive and nanoenzyme-loaded artificial nanocells relieved osteomyelitis efficiently by synergistic chemodynamic and cuproptosis therapy.

Osteomyelitis is an osseous infectious disease that primarily affects children and the elderly with high morbidity and recurrence. The conventional treatments of osteomyelitis contain long-term and high-dose systemic antibiotics with debridements, which are not effective and lead to antibiotic resistance with serious side/adverse effects in many cases. Hence, developing novel antibiotic-free interventions against osteomyelitis (especially antibiotic-resistant bacterial infection) is urgent and anticipated. Here, a bone mesenchymal stem cell membrane-constructed nanocell (CFE@CM) was fabricated against osteomyelitis with the characteristics of acid-responsiveness, hydrogen peroxide self-supplying, enhanced chemodynamic therapeutic efficacy, bone marrow targeting and cuproptosis induction. Notably, mRNA sequencing was applied to unveil the underlying biological mechanisms and found that the biological processes related to copper ion binding, oxidative phosphorylation, peptide biosynthesis and metabolism, etc., were disturbed by CFE@CM in bacteria. This work provided an innovative antibiotic-free strategy against osteomyelitis through copper-enhanced Fenton reaction and distinct cuproptosis, promising to complement the current insufficient therapeutic regimen in clinic.

Characterization of driver mutations identifies gene signatures predictive of prognosis and treatment sensitivity in multiple myeloma.

In multiple myeloma (MM), while frequent mutations in driver genes are crucial for disease progression, they traditionally offer limited insights into patient prognosis. This study aims to enhance prognostic understanding in MM by analyzing pathway dysregulations in key cancer driver genes, thereby identifying actionable gene signatures. We conducted a detailed quantification of mutations and pathway dysregulations in 10 frequently mutated cancer driver genes in MM to characterize their comprehensive mutational impacts on the whole transcriptome. This was followed by a systematic survival analysis to identify significant gene signatures with enhanced prognostic value. Our systematic analysis highlighted 2 significant signatures, TP53 and LRP1B, which notably outperformed mere mutation status in prognostic predictions. These gene signatures remained prognostically valuable even when accounting for clinical factors, including cytogenetic abnormalities, the International Staging System (ISS), and its revised version (R-ISS). The LRP1B signature effectively distinguished high-risk patients within low/intermediate-risk categories and correlated with significant changes in the tumor immune microenvironment. Additionally, the LRP1B signature showed a strong association with proteasome inhibitor pathways, notably predicting patient responses to bortezomib and the progression from monoclonal gammopathy of unknown significance to MM. Through a rigorous analysis, this study underscores the potential of specific gene signatures in revolutionizing the prognostic landscape of MM, providing novel clinical insights that could influence future translational oncology research.

Overcoming CRISPR-Cas9 off-target prediction hurdles: A novel approach with ESB rebalancing strategy and CRISPR-MCA model.

The off-target activities within the CRISPR-Cas9 system remains a formidable barrier to its broader application and development. Recent advancements have highlighted the potential of deep learning models in predicting these off-target effects, yet they encounter significant hurdles including imbalances within datasets and the intricacies associated with encoding schemes and model architectures. To surmount these challenges, our study innovatively introduces an Efficiency and Specificity-Based (ESB) class rebalancing strategy, specifically devised for datasets featuring mismatches-only off-target instances, marking a pioneering approach in this realm. Furthermore, through a meticulous evaluation of various One-hot encoding schemes alongside numerous hybrid neural network models, we discern that encoding and models of moderate complexity ideally balance performance and efficiency. On this foundation, we advance a novel hybrid model, the CRISPR-MCA, which capitalizes on multi-feature extraction to enhance predictive accuracy. The empirical results affirm that the ESB class rebalancing strategy surpasses five conventional methods in addressing extreme dataset imbalances, demonstrating superior efficacy and broader applicability across diverse models. Notably, the CRISPR-MCA model excels in off-target effect prediction across four distinct mismatches-only datasets and significantly outperforms contemporary state-of-the-art models in datasets comprising both mismatches and indels. In summation, the CRISPR-MCA model, coupled with the ESB rebalancing strategy, offers profound insights and a robust framework for future explorations in this field.

Rational design of a high-affinity fluorescent probe for visualizing monitoring the amyloid ß clearance effect of anti-Alzheimer's disease drug candidates.

Beta-amyloid (Aß), the most pivotal pathological hallmark for Alzheimer's disease (AD) diagnosis and drug evaluation, was recognized by TZ095, a high-affinity fluorescent probe developed by rational molecular design. With a TICT mechanism, TZ095 exhibited remarkable affinity with Aß aggregates (Kd = 81.54 nM for oligomers; Kd = 66.70 nM for fibril) and substantial fluorescence enhancement (F/F0 = 44), enabling real-time monitoring of Aß in live cells and nematodes. Significantly, this work used TZ095 to construct a new protocol that can quickly and conveniently monitor Aß changes at the cellular and nematode levels to evaluate the anti-AD efficacy of candidate compounds, and four reported Aß-lowering drug candidates were administrated for validation. Imaging data demonstrated that TZ095 can visually and quantitatively track the effect of Aß elimination after drug treatment. Furthermore, TZ095 excelled in ex vivo histological staining of 12-month-old APP/PS1 mouse brains, accurately visualizing Aß plaques. Integrating CUBIC technology, TZ095 facilitated whole-brain, 3D imaging of Aß distribution in APP/PS1 mice, enabling high-resolution in situ analysis of Aß plaques. Collectively, these innovative applications of TZ095 offer a promising strategy for rapid, convenient, and real-time monitoring of Aß levels in preclinical therapeutic assessments.

Correction: Cheng et al. Dietary Chlorella vulgaris Ameliorates Altered Immunomodulatory Functions in Cyclophosphamide-Induced Immunosuppressive Mice. Nutrients 2017, 9, 708.

In the original publication [...].

Research on key pathogenesis and potential intervention targets of idiopathic renal calculi composed of calcium oxalate (CaOx) based on bioinformatics.

Background: Calcium oxalate (CaOx) kidney stones are the most common type of stones in the urinary system, and their formation involves a complex mechanism with multiple contributing factors. In recent years, with the development of bioinformatics, there has been a deeper understanding of the pathogenesis of this type of disease. This study aimed to analyze the gene expression profiles of idiopathic kidney stones composed of CaOx using bioinformatics methods. By investigating the pathogenesis at the molecular level and identifying potential therapeutic targets, the study also integrated clinical data to validate the clinical relevance of the target genes. Methods: Gene expression profiles from the GSE73680 dataset were analyzed via the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between Randall's plaques (RPs) from kidney papillae associated with CaOx stones and normal kidney papillae tissues. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to construct transcription factor (TF)-DEG-microRNA (miRNA) networks, and key genes were screened using the Molecular Complex Detection (MCODE) plugin. A gene set enrichment analysis (GSEA) was performed to investigate the possible underlying mechanisms of the key genes. The clinical data of idiopathic CaOx kidney stone patients who received treatment at the General Hospital of Northern Theater Command from January 2020 to December 2022 were retrospectively analyzed. Enzyme-linked immunosorbent assay (ELISA) kits were used to measure the transcriptional activity of the key genes in calcified kidney papillae tissues. Univariate and multivariate logistic regression analyses were employed to analyze the transcriptional activity of the key genes and their association with idiopathic kidney stones composed of CaOx. Results: In the GSE73680 dataset, 276 upregulated and 538 downregulated DEGs were identified. Protein-protein interaction network construction revealed one significant module and three candidate genes [interleukin 11 (IL-11), interleukin 16 (IL-16), and interleukin 32 (IL-32)]. The TF-DEG-miRNA network indicated that IL-11 might be regulated by 25 TFs and interact with six miRNAs. The GSEA suggested that IL-11 could influence the development of idiopathic CaOx stones through chemokine expression and via the signaling pathways of the nucleotide-binding oligomerization domain-like receptors [NOD-like receptors (NLRs)] and toll-like receptors (TLRs). The clinical data analysis revealed that the IL-11 serum levels were significantly elevated in the patients with idiopathic kidney stones composed of CaOx compared to the control subjects (P<0.001). Additionally, IL-11 was identified as an independent risk factor for the development of idiopathic CaOx kidney stones (P<0.001). Conclusions: The bioinformatically identified key genes and signaling pathways provide a deeper understanding of the potential mechanisms underlying idiopathic CaOx kidney stones. Preliminary clinical trials suggest that elevated serum IL-11 levels in idiopathic CaOx kidney stone patients could serve as a possible diagnostic biomarker and treatment target.

The digital MySteps intervention for abused women at risk for firearm-related injuries and homicides: Findings from the feasibility, acceptability and preliminary efficacy trial.

Background: Firearms are the leading cause of victimization of abused women by intimate partner homicide and intimate partner homicide-suicides in the US. This calls for evidence-based intervention strategies to prevent firearm-related injuries or mortality and address the firearms-related safety needs of women in abusive relationships. My Safety Steps (MySteps) was designed to comprehensively assess women's firearm-related risks, and current safety needs and to prevent women's harm from their abuser's access or ownership of a firearm through a digitally delivered firearm-focused safety planning intervention. This paper describes the development, feasibility, acceptability, and preliminary evaluation of the digital BSHAPE intervention among women survivors of intimate partner violence (IPV). Methods: Using a pretest post-test control group design, the study was conducted with 103 participants with 55 women randomly assigned to the MySteps arm and 48 women to the standard of care control arm. The feasibility and acceptability outcomes assessed were enrollment, adherence, and perceptions of the intervention. Preliminary evaluation outcomes included the partner's access to a firearm, women's self-efficacy beliefs, and empowerment. Further, qualitative follow-up interviews were conducted with 30 survivors of IPV in the MySteps arm to follow up on the use and helpfulness of safety strategies provided in MySteps. Results and conclusion: The intervention was found to be feasible, and acceptable and demonstrated improved outcomes for survivors of IPV at risk from their partner's firearm. Women provided feedback for further refinement. The findings of this study will be useful in further refining MySteps and testing it in a full-scale randomized controlled trial.

Advances in delivery systems for CRISPR/Cas-mediated cancer treatment: a focus on viral vectors and extracellular vesicles.

The delivery of CRISPR/Cas systems holds immense potential for revolutionizing cancer treatment, with recent advancements focusing on extracellular vesicles (EVs) and viral vectors. EVs, particularly exosomes, offer promising opportunities for targeted therapy due to their natural cargo transport capabilities. Engineered EVs have shown efficacy in delivering CRISPR/Cas components to tumor cells, resulting in inhibited cancer cell proliferation and enhanced chemotherapy sensitivity. However, challenges such as off-target effects and immune responses remain significant hurdles. Viral vectors, including adeno-associated viruses (AAVs) and adenoviral vectors (AdVs), represent robust delivery platforms for CRISPR/Cas systems. AAVs, known for their safety profile, have already been employed in clinical trials for gene therapy, demonstrating their potential in cancer treatment. AdVs, capable of infecting both dividing and non-dividing cells, offer versatility in CRISPR/Cas delivery for disease modeling and drug discovery. Despite their efficacy, viral vectors present several challenges, including immune responses and off-target effects. Future directions entail refining delivery systems to enhance specificity and minimize adverse effects, heralding personalized and effective CRISPR/Cas-mediated cancer therapies. This article underscores the importance of optimized delivery mechanisms in realizing the full therapeutic potential of CRISPR/Cas technology in oncology. As the field progresses, addressing these challenges will be pivotal for translating CRISPR/Cas-mediated cancer treatments from bench to bedside.

Visual analysis on ferroptosis and its cross-talk to coronavirus disease 2019 (COVID-19).

Background: Ferroptosis is a new type of programmed cell death. Although ferroptosis has been studied in various aspects, there has been no visual analysis of ferroptosis in coronavirus disease 2019 (COVID-19) to date. It is still a global health concern of the COVID-19 pandemic worldwide, three years after its outbreak. Yet the emergence of the mutant strain Omicron has caused a fourth wave of infections in many countries. The pathogenesis of COVID-19 is still undergoing extensive exploration, which holds paramount importance in mitigating future epidemics. Methods: For this study, CiteSpace 6.2 R4 software was used for bibliometric and visual atlas analysis of ferroptosis-related research, and the Genecards database was used to mine ferroptosis and COVID-19-related genes. Results: We found increasing studies about ferroptosis. China and the United States have demonstrated robust scientific innovation over recent years, with extensive collaboration between their institutions and authors. Ferroptosis and COVID-19 were seen to have 13 shared genes, which may be new targets for the treatment of COVID-19 in the future. Most of the shared genes are enriched in tumor necrosis factor (TNF) pathways. The majority of those genes are up-regulated under the cellular response to oxidative stress. Genes including Tumour necrosis factor (TNF), RELA proto-oncogene (RELA), Activating transcription factor 4 (ATF4), Cytochrome b-245 beta chain (CYBB), Jun proto-oncogene (JUN), Mitogen-activated protein kinase 1 (MAPK1) and Heme oxygenase 1 (HMOX1), maybe a breakthrough for ferroptosis and COVID-19. Whilst previous research has shown there to be a relationship between ferroptosis and COVID-19, the specific role of ferroptosis remained unclear. Our study aimed to analyze the research status of ferroptosis and its relationship with COVID-19, to provide a useful reference for further prevention and treatment of COVID-19. Overall, uncovering the role of ferroptosis in SARS-CoV-2 infection is important for the development of new treatment strategies for COVID-19.

How do gamified digital therapeutics work on obesity self-management?

Obesity management can effectively reduce the risks and complications associated with obesity and improve the quality of life of patients. After assessing the advantages and limitations of various obesity management approaches, self-management has been strongly recommended due to the advantages of minimal side effects and lower costs compared to treatment via drugs and surgery. However, successfully implementing lifestyle intervention strategies requires scientific guidance and strong determination. With the development of electronic and information technology, lifestyle intervention has transformed considerably. A new concept, called Gamified Digital Therapeutics (GDTx), represents a gaming format with Digital Therapeutics (DTx). It can effectively enhance patient compliance and accessibility to chronic disease management. Here, we review recent studies on the application of GDTx for the self-management of obesity and discuss three aspects surrounding its completion rates, satisfaction levels, and effectiveness. In contrast to traditional approaches to obesity self-management, implementing GDTx effectively corrects unhealthy dietary and lifestyle habits, markedly enhancing the dissemination of nutritional and exercise-related health knowledge. Of particular significance is the evident improvement in the adherence of obese patients to weight loss programs. Despite numerous studies indicating that GDTx may offer an effective solution for obesity self-management, there are still several limitations in the medicalization of GDTx for self-management of obesity. This review aimed to provide a reference for subsequent studies and promote the widespread application of GDTx in obesity self-management to help reduce the obesity rate and alleviate the burden on obese patients.

Comparison between a Novel Knee Arthrometer and Simultaneous Stress Radiography for the Diagnosis of Complete and Partial Acute Anterior Cruciate Ligament Tears.

OBJECTIVES: The type of ligamentous tear and the degree of knee laxity have important guiding significance for the diagnosis and management of anterior cruciate ligament (ACL) tears. Instrumental measurement is necessary for ACL tears since physical examination and magnetic resonance imaging (MRI) cannot provide an objective and quantitative assessment of knee laxity. This study aimed to compare the application of a novel knee arthrometer and simultaneous stress radiography in differentiating between complete and partial acute ACL tears, and further assess the correlation between the two measurements. METHODS: A total of 106 patients with complete acute ACL tears and 52 patients with partial acute ACL tears were included in the study. Preoperative arthrometry and simultaneous stress radiography were performed using the Ligs arthrometer at 90, 120, and 150 N to assess side-to-side difference (SSD) in anterior knee laxity. The optimal threshold was determined using the receiver operating characteristic (ROC) curve. The area under the ROC curve (AUC) was used to assess the diagnostic value of the measurement. Pearson's correlation coefficient was used to assess the correlation between the two measurements. RESULTS: The optimal differential SSD thresholds in the Ligs arthrometer were 2.7 mm at 90 N, 3.8 mm at 120 N, and 4.6 mm at 150 N. Similarly, the optimal differential SSD thresholds in simultaneous stress radiography were 3.8 mm at 90 N, 5.1 mm at 120 N, and 5.6 mm at 150 N. The AUC analysis revealed that the Ligs arthrometer was fairly informative at 90 N (AUC = 0.851), 120 N (AUC = 0.878), and 150 N (AUC = 0.884), and simultaneous stress radiography was highly informative at 90 N (AUC = 0.910), 120 N (AUC = 0.925), and 150 N (AUC = 0.948). Moreover, the AUC of the combined measurements was 0.914 at 90 N, 0.931 at 120 N, and 0.951 at 150 N. A significantly strong correlation was found between the two measurements at 90 N (r = 0.743, p < 0.001), 120 N (r = 0.802, p < 0.001), and 150 N (r = 0.823, p < 0.001). CONCLUSIONS: The Ligs arthrometer and simultaneous stress radiography proved to be valid diagnostic tools to differentiate between complete and partial acute ACL tears, with a strong correlation between the two measurements in SSD values. Compared with single instrumental measurement, the combination of the two measurements can further improve the diagnostic value in this regard.

Efficient asymmetric diffusion channel in MnCo2O4 spinel for ammonium-ion batteries.

Transition metal oxides ion diffusion channels have been developed for ammonium-ion batteries (AIBs). However, the influence of microstructural features of diffusion channels on the storage and diffusion behavior of NH4+ is not fully unveiled. In this study, by using MnCo2O4 spinel as a model electrode, the asymmetric ion diffusion channels of MnCo2O4 have been regulated through bond length optimization strategy and investigate the effect of channel size on the diffusion process of NH4+. In addition, the reducing channel size significantly decreases NH4+ adsorption energy, thereby accelerating hydrogen bond formation/fracture kinetics and NH4+ reversible diffusion within 3D asymmetric channels. The optimized MnCo2O4 with oxygen vacancies/carbon nanotubes composite exhibits impressive specific capacity (219.2 mAh g-1 at 0.1 A g-1) and long-cycle stability. The full cell with 3,4,9,10-perylenetetracarboxylic diimide anode demonstrates a remarkable energy density of 52.3 Wh kg-1 and maintains 91.9% capacity after 500 cycles. This finding provides a unique approach for the development of cathode materials in AIBs.

Zearalenone Triggers Programmed Cell Death and Impairs Milk Fat Synthesis via the AKT-mTOR-PPARγ-ACSL4 Pathway in Bovine Mammary Epithelial Cells.

Zearalenone (ZEN), a mycotoxin from Fusarium fungi, impairs fertility and milk production in female animals, however, the mechanisms remain poorly understood. Using the bovine mammary epithelial cells (MAC-T) as the model, this study investigated the impacts of ZEN on programmed cell death (PCD) and milk fat synthesis, and explored the underlying mechanism. We found that 10 ng/mL prolactin (PRL) notably enhanced the differentiation of MAC-T cells, promoting the expression of genes related to the synthesis of milk fat, protein, and lactose. Next, the toxic effects of different doses of ZEN on the differentiated MAC-T with PRL treatment were determined. 10 µM and 20 µM ZEN significantly reduced cell viability, induced oxidative stress, and triggered PCD (e.g. apoptosis and necrosis). Notably, ZEN exposure downregulated the mRNA/protein levels of critical factors involving in milk fat synthesis by disrupting the AKT-mTOR-PPARγ-ACSL4 pathway. Interestingly, melatonin (MT), known for its antioxidant properties, protected against the above ZEN-induced effects by enhancing the binding of PPARγ to the promoter regions of ACSL4, which led to the upregulated expression of ACSL4 gene. These results underscored the potential of MT to mitigate the adverse effects of ZEN on mammary cells, highlighting a way for potential therapeutic intervention.

Sustainable design and synthesis of high-performance lignin-based sunscreen ingredients.

The active ingredients most commonly employed in sunscreens are compounds containing one or two aromatic rings. Lignin is the most abundant renewable aromatic polymer that has the potential to yield low molecular weight aromatic chemicals when strategically depolymerized. Here, the UV absorbance of a series of monomeric and dimeric lignin model compounds (LMCs) were studied. Specifically, vanillin and ferulic acid demonstrated good absorption in the UVB (280-320 nm) range, while the 5-5 dimer showed efficient absorption in the UVA (320-400 nm) range. Based on this, vanillin, ferulic acid and 5-5 dimer were mixed in pairs and dispersed in the oily isoeugenol to prepare LMC hybrid dispersions. Subsequently, demethylated lignin (DL) was synthesized and used to encapsulate the LMC hybrid dispersions via ultrasonic cavitation to prepare DL-based nano-capsules (DLNCs). The DLNCs were used as the only active ingredient in sunscreens, whose sun protection factor (SPF) value could be up to 55 with a dosage of 10 wt%. Due to anti-photolysis property of DL, the SPF value of DLNCs-based sunscreens increased initially and maintained >8 h under UV irradiation. Additionally, the prepared DLNCs exhibited excellent anti-permeability, antioxidant capacity and biocompatibility, making them a potential substitute for conventional petroleum-based sunscreen agents.

Chemosensory protein 22 in Riptortus pedestris is involved in the recognition of three soybean volatiles.

Riptortus pedestris (Hemiptera: Alydidae), a common agricultural pest, is the major causative agent of "soybean staygreen." However, the interactions between chemosensory proteins (CSPs) in R. pedestris and host plant volatiles have yet to be comprehensively studied. In this study, we performed real-time fluorescence quantitative polymerase chain reaction (PCR) to analyze the antennal expression of RpedCSP22 and subsequently analyzed the interactions between 21 soybean volatiles, five aggregation pheromones, and RpedCSP22 protein in vitro using a protein expression system, molecular docking, site-directed mutagenesis, and fluorescence competitive binding experiments. The RpedCSP22 protein showed binding affinity to three soybean volatiles (benzaldehyde, 4-ethylbenzaldehyde, and 1-octene-3-ol), with optimal binding observed under neutral pH conditions, and lost binding ability after site-directed mutagenesis. In subsequent RNA interference (RNAi) studies, gene silencing was more than 90 %, and in silenced insects, electroantennographic responses were reduced by more than 75 % compared to non-silenced insects. Moreover, Y-tube olfactory behavioral assessments revealed that the attraction of R. pedestris to the three soybean volatiles was significantly attenuated. These findings suggest that RpedCSP22 plays an important role in the recognition of host plant volatiles by R. pedestris andprovides a theoretical basis for the development of novel inhibitors targeting pest behavior.

Mycophenolate Mofetil and New-Onset Systemic Lupus Erythematosus: A Randomized Clinical Trial.

Importance: Anti-double-stranded DNA (dsDNA) antibody has been reported to have a close relationship with systemic lupus erythematosus (SLE) flares and participates in the pathogenesis of lupus nephritis (LN) as well as causing damage to other organs. However, whether early use of mycophenolate mofetil (MMF) could prevent SLE flares is not clear. Objective: To assess the efficacy and safety of MMF plus prednisone and hydroxychloroquine sulfate compared with prednisone and hydroxychloroquine sulfate alone in patients with SLE. Design, Setting, and Participants: This investigator-initiated, multicenter, observer-blinded randomized clinical trial enrolled 130 participants aged 18 to 65 years and was conducted in 3 hospitals across China. Treatment-naive patients with newly diagnosed SLE, a high titer of anti-dsDNA antibody, and no major organ involvement were included. The study was started September 1, 2018, and the follow-up was completed September 30, 2021. Data were analyzed from December 1, 2021, to March 31, 2022. Interventions: Patients were randomized 1:1 to receive oral prednisone (0.5 mg/kg/d) and hydroxychloroquine sulfate (5 mg/kg/d) (control group) or prednisone (0.5 mg/kg/d) and hydroxychloroquine sulfate (5 mg/kg/d) plus MMF (500 mg twice daily) (MMF group) for 96 weeks. Main Outcomes and Measures: The primary outcome was the proportion of patients presenting with flares according to the Safety of Estrogens in Lupus Erythematosus National Assessment-Systemic Lupus Erythematosus Disease Activity Index (SELENA-SLEDAI) Flare Index. The secondary outcomes included the proportion with lupus low disease activity state at week 96, 36-Item Short Form Health Survey scores before and after treatment, proportion of adverse events (AEs), and changes in SLEDAI-2000 scores and prednisone doses. Results: Among 130 randomized patients (mean [SD] age, 34.5 [12.5] years; 112 [86.2%] women), 119 (91.5%) completed the follow-up. The risk of severe flare was significantly lower in the MMF group (7 of 65 [10.8%]) vs the control group (18 of 65 [27.7%]) (relative risk [RR], 0.39 [95% CI, 0.17-0.87]; P = .01). Additionally, 1 of 65 patients in the MMF group (1.5%) and 9 of 65 in the control group (13.8%) manifested LN (RR, 0.11 [95% CI, 0.01-0.85]; P = .008). Most common serious study drug-related AEs were infections (20 of 65 [30.8%] in the control group and 22 of 65 [33.8%] in the MMF group). Conclusions and Relevance: The findings of this randomized clinical trial suggest that MMF may reduce the rate of severe flare and lower the incidence of LN in patients with new-onset SLE and a high titer of anti-dsDNA antibody without major organ involvement. Trial Registration: Chinese Clinical Trial Registry: ChiCTR1800017540.

Non-cell-autonomous regulation of germline proteostasis by insulin/IGF-1 signaling-induced dietary peptide uptake via PEPT-1.

Gametogenesis involves active protein synthesis and is proposed to rely on proteostasis. Our previous work in C. elegans indicates that germline development requires coordinated activities of insulin/IGF-1 signaling (IIS) and HSF-1, the central regulator of the heat shock response. However, the downstream mechanisms were not identified. Here, we show that depletion of HSF-1 from germ cells impairs chaperone gene expression, causing protein degradation and aggregation and, consequently, reduced fecundity and gamete quality. Conversely, reduced IIS confers germ cell resilience to HSF-1 depletion-induced protein folding defects and various proteotoxic stresses. Surprisingly, this effect was not mediated by an enhanced stress response, which underlies longevity in low IIS conditions, but by reduced ribosome biogenesis and translation rate. We found that IIS activates the expression of intestinal peptide transporter PEPT-1 by alleviating its repression by FOXO/DAF-16, allowing dietary proteins to be efficiently incorporated into an amino acid pool that fuels germline protein synthesis. Our data suggest this non-cell-autonomous pathway is critical for proteostasis regulation during gametogenesis.

Bioinformatics and experimental validation were combined to explore lactylation-related biomarkers in HBV-associated acute liver failure.

BACKGROUND AND AIM: Currently, hepatitis B virus-related acute liver failure (HBV-ALF) has limited treatment options. Studies have shown that histone lactylation plays a role in the progression of liver-related diseases. Therefore, it is essential to explore lactylation-related gene (LRGs) biomarkers in HBV-ALF to provide new information for the treatment of HBV-ALF. METHODS: Two HBV-ALF-related datasets (GSE38941 and GSE14668) and 65 LRGs were used. First, the differentially expressed genes (DEGs) were derived from differential expression analysis, the key module genes from weighted gene co-expression network analysis; and LRGs were used to intersect to obtain the candidate genes. Subsequently, the feature genes obtained from least absolute shrinkage and selection operator regression analysis and support vector machine analysis were intersected to obtain the candidate key genes. Among them, genes with consistent and significant expression trends in both GSE38941 and GSE14668 were used as biomarkers. Subsequently, biomarkers were analyzed for functional enrichment, immune infiltration, and sensitive drug prediction. RESULTS: In this study, five candidate genes (PIGM, PIGA, EGR1, PIGK, and PIGL) were identified by intersecting 6461 DEGs and 2496 key module genes with 65 LRGs. We then screened four candidate key genes from the machine learning algorithm, among which PIGM and PIGA were considered biomarkers in HBV-ALF. Moreover, the results of enrichment analysis showed that the significant enrichment signaling pathways for biomarkers included allograft rejection and valine, leucine, and isoleucine degradation. Thereafter, 11 immune cells differed significantly between groups, with resting memory CD4+ T cells having the strongest positive correlation with biomarkers. Methylphenidate hydrochloride is a potential therapeutic drug for PIGM. CONCLUSION: Two genes, PIGM and PIGA, were identified as biomarkers related to LRGs in HBV-ALF, providing a basis for understanding HBV-ALF pathogenesis.

Radiomics predicts the prognosis of patients with clear cell renal cell carcinoma by reflecting the tumor heterogeneity and microenvironment.

PURPOSE: We aimed to develop and externally validate a CT-based deep learning radiomics model for predicting overall survival (OS) in clear cell renal cell carcinoma (ccRCC) patients, and investigate the association of radiomics with tumor heterogeneity and microenvironment. METHODS: The clinicopathological data and contrast-enhanced CT images of 512 ccRCC patients from three institutions were collected. A total of 3566 deep learning radiomics features were extracted from 3D regions of interest. We generated the deep learning radiomics score (DLRS), and validated this score using an external cohort from TCIA. Patients were divided into high and low-score groups by the DLRS. Sequencing data from the corresponding TCGA cohort were used to reveal the differences of tumor heterogeneity and microenvironment between different radiomics score groups. What's more, univariate and multivariate Cox regression were used to identify independent risk factors of poor OS after operation. A combined model was developed by incorporating the DLRS and clinicopathological features. The SHapley Additive exPlanation method was used for interpretation of predictive results. RESULTS: At multivariate Cox regression analysis, the DLRS was identified as an independent risk factor of poor OS. The genomic landscape of different radiomics score groups was investigated. The heterogeneity of tumor cell and tumor microenvironment significantly varied between both groups. In the test cohort, the combined model had a great predictive performance, with AUCs (95%CI) for 1, 3 and 5-year OS of 0.879(0.868-0.931), 0.854(0.819-0.899) and 0.831(0.813-0.868), respectively. There was a significant difference in survival time between different groups stratified by the combined model. This model showed great discrimination and calibration, outperforming the existing prognostic models (all p values < 0.05). CONCLUSION: The combined model allowed for the prognostic prediction of ccRCC patients by incorporating the DLRS and significant clinicopathologic features. The radiomics features could reflect the tumor heterogeneity and microenvironment.

METTL16 Promotes Stability of SYNPO2L mRNA and leading to Cancer Cell Lung Metastasis by Secretion of COL10A1 and attract the Cancer-Associated Fibroblasts.

The occurrence of metastasis is a major factor contributing to poor prognosis in colorectal cancer. Different stages of the disease play a crucial role in distant metastasis. Furthermore, m6A has been demonstrated to play a significant role in regulating tumor metastasis. Therefore, we conducted an analysis of transcriptome data from high-stage and low-stage colorectal cancer patients in The Cancer Genome Atlas (TCGA) to identify genes associated with m6A-related regulation. We identified SYNPO2L as a core gene regulated by m6A, and it is correlated with adverse prognosis and metastasis in patients. Additionally, we demonstrated that the m6A writer gene Mettl16 can regulate the stability of SYNPO2L through interaction with YTHDC1. Subsequently, using Weighted Gene Co-expression Network Analysis (WGCNA), we discovered that SYNPO2L can regulate COL10A1, mediating the actions of Cancer-Associated Fibroblasts. SYNPO2L promotes the secretion of COL10A1 and the infiltration of tumor-associated fibroblasts, thereby facilitating Epithelial-Mesenchymal Transition (EMT) in tumor cells and making them more prone to distant metastasis.