Tumor microenvironment RNA test to predict immunotherapy outcomes in advanced gastric cancer: The TIMES001 trial.

BACKGROUND: Clinical trials support the efficacy of immune checkpoint blockades (ICBs) plus chemotherapy in a subset of patients with metastatic gastric cancer (mGC). To identify the determinants of response, we developed a TMEscore model to assess tumor microenvironment (TME), which was previously proven to be a biomarker for ICBs. METHODS: A reference database of TMEscore assays was established using PCR assay kits containing 30 TME genes. This multi-center prospective clinical trial (NCT#04850716) included patients with mGC who were administered ICB combined with chemotherapy as a first-line regimen. Eighty-six tumor samples extracted from five medical centers before treatment were used to estimate the TMEscore, PD-L1 (CPS), and mismatch repair deficiency. FINDINGS: The objective response rate (ORR) and median PFS of the cohort were 31.4% and six months. Enhanced ORR was observed in TMEscore-high mGC patients (ORR = 59%). The survival analysis demonstrated that high TMEscore was significantly associated with a more favorable PFS and OS. Moreover, TMEscore was found to be a predictive biomarker that surpassed MSI and CPS (AUC = 0.873, 0.511, and 0.524, respectively). By integrating the TMEscore and clinical variables, the fused model further enhances the predictive efficiency and translational application in a clinical setting. CONCLUSIONS: This prospective clinical study indicates that the TMEscore assay is a robust biomarker for screening patients with mGC who may derive survival benefits from ICB plus chemotherapy. FUNDING: Guangdong Basic and Applied Basic Research Foundation (2023A1515011214), Science and Technology Program of Guangzhou (202206080011), and Guangzhou Science and Technology Project (2023A03J0722 and 2023A04J2357).

The traditional Chinese medicine Qiliqiangxin in heart failure with reduced ejection fraction: a randomized, double-blind, placebo-controlled trial.

Previous findings have indicated the potential benefits of the Chinese traditional medicine Qiliqiangxin (QLQX) in heart failure. Here we performed a double-blind, randomized controlled trial to evaluate the efficacy and safety of QLQX in patients with heart failure and reduced ejection fraction (HFrEF). This multicenter trial, conducted in 133 hospitals in China, enrolled 3,110 patients with HFrEF with NT-proBNP levels of ≥450 pg ml-1 and left ventricular ejection fraction of ≤40%. Participants were randomized to receive either QLQX capsules or placebo (four capsules three times daily) alongside standard heart failure therapy. The trial met its primary outcome, which was a composite of hospitalization for heart failure and cardiovascular death: over a median follow-up of 18.3 months, the primary outcome occurred in 389 patients (25.02%) in the QLQX group and 467 patients (30.03%) in the placebo group (hazard ratio (HR), 0.78; 95% confidence interval (CI), 0.68-0.90; P < 0.001). In an analysis of secondary outcomes, the QLQX group showed reductions in both hospitalization for heart failure (15.63% versus 19.16%; HR, 0.76; 95% CI, 0.64-0.90; P = 0.002) and cardiovascular death (13.31% versus 15.95%; HR, 0.83; 95% CI, 0.68-0.996; P = 0.045) compared to the placebo group. All-cause mortality did not differ significantly between the two groups (HR, 0.84; 95% CI, 0.70-1.01; P = 0.058) and adverse events were also comparable between the groups. The results of this trial indicate that QLQX may improve clinical outcomes in patients with HFrEF when added to conventional therapy. ChiCTR registration: ChiCTR1900021929 .

Mutual exclusivity and co-occurrence patterns of immune checkpoints indicate NKG2A relates to anti-PD-1 resistance in gastric cancer.

BACKGROUND: An increasing number of clinical studies have begun to explore combination strategies with immune checkpoint inhibitors, aiming to present new opportunities for overcoming anti-PD-1 treatment resistance in gastric cancer. Unfortunately, the exploration of certain immune checkpoint inhibitor combination strategies has yielded suboptimal results. Therefore, it is necessary to comprehensively analyze the expression patterns of immune checkpoints and identify optimal combination regimens of anti-PD-1 inhibitors with other immune checkpoint inhibitors. METHODS: Leveraging single-cell RNA sequencing (scRNA-seq) and multivariate linear regression interaction models, we dissected the immune checkpoint expression characteristics of CD8+ T cells in gastric cancer and the immune checkpoint expression pattern (ICEP) mediating anti-PD-1 treatment resistance. Furthermore, we employed transcription factor analysis and CellOracle to explore the transcriptional regulatory mechanisms governing CD8+ T cell differentiation fates. Finally, we utilized Nichenet and spatial transcriptomic analysis to investigate the spatial expression patterns of immune checkpoints. RESULTS: Interaction analysis indicated that, among the known immune checkpoints, co-expression of NKG2A and PD-1 might exert a more profound inhibitory effect on the proliferative capacity of CD8+ T cells. The co-expression analysis revealed differential co-expression pattern of PD-1 and NKG2A, defined as ICEP1 (CD8+ T cells co-expressing PD-1, CTLA-4, TIGIT, LAG-3 or CD38) and ICEP2 (CD8+ T cells solely expressing NKG2A or co-expressing with other immune checkpoints), reflecting the co-occurrence pattern of PD-1 and the mutual exclusivity of NKG2A. Further, these two ICEP CD8+ T cell subsets represented distinct CD8+ T cell differentiation fates governed by MSC and RUNX3. Notably, ICEP2 CD8+ T cells were associated with anti-PD-1 therapy resistance in gastric cancer. This phenomenon may be attributed to the recruitment of LGMN+ macrophages mediated by the CXCL16-CXCR6 signaling pathway. CONCLUSION: This study unveiled two distinct ICEPs and the mutually exclusivity and co-occurrence characteristics of CD8+ T cells in gastric cancer. The ICEP2 CD8+ T cell subset, highly expressed in gastric cancer patients resistant to anti-PD-1 therapy, may be recruited by LGMN+ macrophages through CXCL16-CXCR6 axis. These findings provide evidence for NKG2A as a novel immunotherapeutic target in gastric cancer and offer new insights into combination strategies for immune checkpoint inhibitors in gastric cancer.

Understanding symptom contribution to sex inequality in bladder and renal cancer stage at diagnosis.

Background: Understanding sex-specific factors contributing to advanced-stage diagnosis can guide interventions to reduce sex inequality in patients with urological cancers. Method: We used linked primary care and cancer registry data to examine associations between symptoms and advanced-stage in 1151 bladder cancer and 440 renal cancer patients diagnosed between January 2012 and December 2015 in England. We performed logistic regression, adjusting for sex, age, deprivation and routes to diagnosis, including interaction terms between symptoms and sex and symptoms and age. Results: Female sex (OR vs. men 1.89 [1.28-2.79]; p = 0.001) and patients presenting with urinary tract infections (OR 2.22 [1.34-3.69]) and abdominal symptoms (OR 2.19 [1.30-3.70]) were associated with increased odds of advanced-stage bladder cancer (vs. haematuria, p = 0.016 for both). Women with haematuria and men with abdominal symptoms (compared with the opposite sex with the same presenting symptom) were more likely to have advanced-stage bladder cancer. Neither sex nor symptom associations were observed for renal cancer. Conclusion: Non-haematuria symptoms are associated with higher risk of advanced-stage bladder cancer. Greater risk of advanced-stage bladder cancer in women may reflect biological differences in haematuria onset and sex differences during diagnostic process. Identifying higher risk women with haematuria may reduce sex inequalities in bladder cancer outcomes.

Deep learning modeling using mammography images for predicting estrogen receptor status in breast cancer.

BACKGROUND: The estrogen receptor (ER) serves as a pivotal indicator for assessing endocrine therapy efficacy and breast cancer prognosis. Invasive biopsy is a conventional approach for appraising ER expression levels, but it bears disadvantages due to tumor heterogeneity. To address the issue, a deep learning model leveraging mammography images was developed in this study for accurate evaluation of ER status in patients with breast cancer. OBJECTIVES: To predict the ER status in breast cancer patients with a newly developed deep learning model leveraging mammography images. MATERIALS AND METHODS: Datasets comprising preoperative mammography images, ER expression levels, and clinical data spanning from October 2016 to October 2021 were retrospectively collected from 358 patients diagnosed with invasive ductal carcinoma. Following collection, these datasets were divided into a training dataset (n = 257) and a testing dataset (n = 101). Subsequently, a deep learning prediction model, referred to as IP-SE-DResNet model, was developed utilizing two deep residual networks along with the Squeeze-and-Excitation attention mechanism. This model was tailored to forecast the ER status in breast cancer patients utilizing mammography images from both craniocaudal view and mediolateral oblique view. Performance measurements including prediction accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curves (AUCs) were employed to assess the effectiveness of the model. RESULTS: In the training dataset, the AUCs for the IP-SE-DResNet model utilizing mammography images from the craniocaudal view, mediolateral oblique view, and the combined images from both views, were 0.849 (95% CIs: 0.809-0.868), 0.858 (95% CIs: 0.813-0.872), and 0.895 (95% CIs: 0.866-0.913), respectively. Correspondingly, the AUCs for these three image categories in the testing dataset were 0.835 (95% CIs: 0.790-0.887), 0.746 (95% CIs: 0.793-0.889), and 0.886 (95% CIs: 0.809-0.934), respectively. A comprehensive comparison between performance measurements underscored a substantial enhancement achieved by the proposed IP-SE-DResNet model in contrast to a traditional radiomics model employing the naive Bayesian classifier. For the latter, the AUCs stood at only 0.614 (95% CIs: 0.594-0.638) in the training dataset and 0.613 (95% CIs: 0.587-0.654) in the testing dataset, both utilizing a combination of mammography images from the craniocaudal and mediolateral oblique views. CONCLUSIONS: The proposed IP-SE-DResNet model presents a potent and non-invasive approach for predicting ER status in breast cancer patients, potentially enhancing the efficiency and diagnostic precision of radiologists.

Prospective Role of Foundation Models in Advancing Autonomous Vehicles.

With the development of artificial intelligence and breakthroughs in deep learning, large-scale foundation models (FMs), such as generative pre-trained transformer (GPT), Sora, etc., have achieved remarkable results in many fields including natural language processing and computer vision. The application of FMs in autonomous driving holds considerable promise. For example, they can contribute to enhancing scene understanding and reasoning. By pre-training on rich linguistic and visual data, FMs can understand and interpret various elements in a driving scene, and provide cognitive reasoning to give linguistic and action instructions for driving decisions and planning. Furthermore, FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data collection. The enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving systems. Another testament to the potential of FMs' applications lies in world models, exemplified by the DREAMER series, which showcases the ability to comprehend physical laws and dynamics. Learning from massive data under the paradigm of self-supervised learning, world models can generate unseen yet plausible driving environments, facilitating the enhancement in the prediction of road users' behaviors and the off-line training of driving strategies. In this paper, we synthesize the applications and future trends of FMs in autonomous driving. By utilizing the powerful capabilities of FMs, we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving, consequently advancing overall safety in this domain.

Investigating the Relationship between Oral Health and Severe Mental Illness: Analysis of NHANES 1999-2016.

OBJECTIVES: To explore whether: (i) people with severe mental illness (SMI) experience worse oral health than the general population, and (ii) the risk factors for poor oral health in people with SMI. METHODS: Cross-sectional data were extracted from the National Health and Nutrition Examination Survey (1999-2016), including on self-rated oral health, oral pain, tooth loss, periodontitis stage, and number of decayed, missing, and filled teeth. Candidate risk factors for poor oral health included demographic characteristics, lifestyle factors, physical health comorbidities, and dental hygiene behaviours. Ordinal logistic regression and zero-inflated negative binomial models were used to explore predictors of oral health outcomes. RESULTS: There were 53,348 cases included in the analysis, including 718 people with SMI. In the fully adjusted model, people with SMI were more likely to suffer from tooth loss (OR 1.60, 95% CI: 1.34-1.92). In people with SMI, risk factors identified for poor oral health outcomes were older age, white ethnicity, lower income, smoking history, and diabetes. Engaging in physical activity and daily use of dental floss were associated with better oral health outcomes. CONCLUSIONS: People with SMI experience higher rates of tooth loss than the general population, and certain subgroups are particularly at risk. Performing regular physical exercise and flossing may lower the risk of poor oral health, while smoking and diabetes may increase the risk. These findings suggest opportunities for targeted prevention and early intervention strategies to mitigate adverse oral health outcomes in people with SMI.

α-Mangostin reduces hypertension in spontaneously hypertensive rats and inhibits EMT and fibrosis in Ang II-induced HK-2 cells.

Hypertension affects a large number of individuals globally and is a common cause of nephropathy, stroke, ischaemic heart disease and other vascular diseases. While many anti-hypertensive medications are used safely and effectively in clinic practice, controlling hypertensive complications solely by reducing blood pressure (BP) can be challenging. α-Mangostin, a xanthone molecule extracted from the pericarp of Garcinia mangostana L., has shown various beneficial effects such as anti-tumor, anti-hyperuricemia, and anti-inflammatory properties. However, the effects of α-Mangostin on hypertension remain unknown. In this study, we observed that α-Mangostin significantly decreased systolic and diastolic blood pressure in spontaneously hypertensive rats (SHR), possibly through the down-regulation of angiotensin II (Ang II). We also identified early markers of hypertensive nephropathy, including urinary N-acetyl-ß-D-glucosaminidase (NAG) and ß2-microglobulin (ß2-MG), which were reduced by α-Mangostin treatment. Mechanistic studies suggested that α-Mangostin may inhibit renal tubular epithelial-to-mesenchymal transformation (EMT) by down-regulating the TGF-ß signaling pathway, thus potentially offering a new therapeutic approach for hypertension and hypertensive nephropathy.

Dandelion-like VSe2-embellished CuSe-Co3Se4 hollow nanotube clusters as bifunctional catalysts for high-performance alkaline hydrogen evolution and solar cells.

Among the various non-precious metal catalysts that drive hydrogen evolution reactions (HERs) and dye-sensitized solar cells (DSSCs), transition metal selenides (TMSs) stand out due to their unique electronic properties and tunable morphology. Herein, the multicomponent selenide CuSe-Co3Se4@VSe2 was successfully synthesized by doping with metal element vanadium and selenization on the copper-cobalt carbonate hydroxide (CuCo-CH) template. CuSe-Co3Se4@VSe2 exhibited the dandelion-like cluster structure composed of hollow nanotubes doped with VSe2 nanoparticles. Due to the unique structure and the synergistic effect of various elements, CuSe-Co3Se4@VSe2 showed excellent alkaline HER and DSSC performances. The DSSC based on CuSe-Co3Se4@VSe2 exhibited an impressive power conversion efficiency (PCE) of 9.64 %, which was much higher than that of Pt (8.39 %). Besides, it possessed a low HER overpotential of 76 mV@10 mA cm-2 and a small Tafel slope of 88.9 mV dec-1 in 1.0 M KOH.

Nicotinamide metabolism face-off between macrophages and fibroblasts manipulates the microenvironment in gastric cancer.

Immune checkpoint blockade has led to breakthroughs in the treatment of advanced gastric cancer. However, the prominent heterogeneity in gastric cancer, notably the heterogeneity of the tumor microenvironment, highlights the idea that the antitumor response is a reflection of multifactorial interactions. Through transcriptomic analysis and dynamic plasma sample analysis, we identified a metabolic "face-off" mechanism within the tumor microenvironment, as shown by the dual prognostic significance of nicotinamide metabolism. Specifically, macrophages and fibroblasts expressing the rate-limiting enzymes nicotinamide phosphoribosyltransferase and nicotinamide N-methyltransferase, respectively, regulate the nicotinamide/1-methylnicotinamide ratio and CD8+ T cell function. Mechanistically, nicotinamide N-methyltransferase is transcriptionally activated by the NOTCH pathway transcription factor RBP-J and is further inhibited by macrophage-derived extracellular vesicles containing nicotinamide phosphoribosyltransferase via the SIRT1/NICD axis. Manipulating nicotinamide metabolism through autologous injection of extracellular vesicles restored CD8+ T cell cytotoxicity and the anti-PD-1 response in gastric cancer.

The nexus between urbanization and ecosystem services balance in China: A coupling perspective.

Urbanization inevitably interfered with the supply and demand of ecosystem services (ESs), which has a crucial impact on the ESs balance. Scientific exploration and clarification of the coupling and decoupling relationship between them can effectively reveal the disturbance of urbanization to the ecosystem, which can help to reasonably manage and protect the ecosystem. Previous studies have paid more attention to the coupling relationship but less attention to the decoupling relationship. This study comprehensively reflected urbanization from the three aspects of construction land, population, and economy and used the evaluation matrix to measure ESs. On this basis, coupling and decoupling analyses were taken to fully clarify the complex relationship between urbanization and ESs balance in China, so as to provide a reference for the formulation of relevant policies. Coupling aspect, the coupling degrees between the proportion of construction land (CLP) and ESs balance index (ESBI) were higher only in the central and eastern plains. The coupling degrees between population density (PD) and ESBI, economic density (ED) and ESBI, and land development index (LDI) and ESBI were only lower in the central and eastern plains than in other regions. Decoupling aspect, strong, weak negative, weak, and strong negative decoupling were the main decoupling types between urbanization and ESs balance in China. Among them, the proportion of the strong decoupling type is much higher than other types, which proves the opposite relationship between the two. Weak decoupling can not only promote economic growth and social development but also protect the ecological environment and biodiversity, which is a type of sustainable development and an ideal state that urbanization should pursue. The results can provide scientific guidance for the formulation of differentiated ecosystem management policies.

Simultaneous quantification of co-administered trastuzumab and pertuzumab in serum based on nano-surface and molecular-orientation limited (nSMOL) proteolysis.

Monoclonal antibodies (mAbs) are pivotal therapeutic agents for various diseases, and effective treatment hinges on attaining a specific threshold concentration of mAbs in patients. With the rising adoption of combination therapy involving multiple mAbs, there arises a clinical demand for multiplexing assays capable of measuring the concentrations of these mAbs. However, minimizing the complexity of serum samples while achieving rapid and accurate quantification is difficult. In this work, we introduced a novel method termed nano-surface and molecular orientation limited (nSMOL) proteolysis for the fragment of antigen binding (Fab) region-selective proteolysis of co-administered trastuzumab and pertuzumab based on the pore size difference between the protease nanoparticles (∼200 nm) and the resin-captured antibody (∼100 nm). The hydrolyzed peptide fragments were then quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In this process, the digestion time is shortened, and the produced digestive peptides are greatly reduced, thereby minimizing sample complexity and increasing detection accuracy. Assay linearity was confirmed within the ranges of 0.200-200 µg mL-1 for trastuzumab and 0.300-200 µg mL-1 for pertuzumab. The intra- and inter-day precision was within 9.52% and 8.32%, except for 12.5% and 10.8% for the lower limit of quantitation, and the accuracy (bias%) was within 6.3%. Additionally, other validation parameters were evaluated, and all the results met the acceptance criteria of the guiding principles. Our method demonstrated accuracy and selectivity for the simultaneous determination of trastuzumab and pertuzumab in clinical samples, addressing the limitation of ligand binding assays incapable of simultaneously quantifying mAbs targeting the same receptor. This proposed assay provides a promising technical approach for realizing clinical individualized precise treatment, especially for co-administered mAbs.

Interventions to Reduce Intra-Operative and Post-Operative Pain Associated with Routine Dental Procedures in Children: A Systematic Review and Meta-Analysis.

OBJECTIVE: implementing appropriate pharmacological and non-pharmacological interventions to alleviate pain related to routine dental procedures in paediatric patients could enhance children's ability to manage dental care. The aim of this review was to investigate the effectiveness of and provide recommendations for interventions that can be used to reduce intra-operative and post-operative pain associated with routine paediatric dental procedures. METHODS: A systematic review of randomised controlled clinical trials (RCT) was conducted. Multiple electronic databases were systematically searched. The Cochrane risk-of-bias tool for RCTs was used to evaluate the quality of the included studies. A meta-analysis was performed to determine the effectiveness of the interventions using the Cohen's d standardised mean differences (SMD) and 95% confidence intervals (CIs) for continuous outcomes. The GRADE tool was used to assess the certainty of evidence to make recommendations. RESULTS: The review included forty-five RCTs comprising 3093 children. Thirty-seven RCTs were included in the meta-analysis, which showed the effectiveness of behavioural interventions (SMD = -0.50, 95% CI -0.83 to -0.18), mechanoreceptor and thermal receptor stimulation (SMD = -1.38, 95% CI -2.02 to -0.73) for intra-operative pain, and pre-emptive oral analgesics (SMD = -0.77, 95% CI -1.21 to -0.33) for reducing post-operative pain in children receiving routine dental care. CONCLUSION: The GRADE results for these interventions were strong recommendation (IB) for their use, based on moderate evidence and their benefits far outweighing the harm, and they can be delivered readily with minimal training to reduce the pain experience of paediatric patients.

Surface Reconstruction of Silicone-Based Amphiphilic Polymers for Mitigating Marine Biofouling.

Poly(dimethylsiloxane) (PDMS) coatings are considered to be environmentally friendly antifouling coatings. However, the presence of hydrophobic surfaces can enhance the adhesion rate of proteins, bacteria and microalgae, posing a challenge for biofouling removal. In this study, hydrophilic polymer chains were synthesised from methyl methacrylate (MMA), Poly(ethylene glycol) methyl ether methacrylate (PEG-MA) and 3-(trimethoxysilyl) propyl methacrylate (TPMA). The crosslinking reaction between TPMA and PDMS results in the formation of a silicone-based amphiphilic co-network with surface reconstruction properties. The hydrophilic and hydrophobic domains are covalently bonded by condensation reactions, while the hydrophilic polymers migrate under water to induce surface reconstruction and form hydrogen bonds with water molecules to form a dense hydrated layer. This design effectively mitigates the adhesion of proteins, bacteria, algae and other marine organisms to the coating. The antifouling performance of the coatings was evaluated by assessing their adhesion rates to proteins (BSA-FITC), bacteria (B. subtilis and P. ruthenica) and algae (P. tricornutum). The results show that the amphiphilic co-network coating (e.g., P-AM-15) exhibits excellent antifouling properties against protein, bacterial and microalgal fouling. Furthermore, an overall assessment of its antifouling performance and stability was conducted in the East China Sea from 16 May to 12 September 2023, which showed that this silicon-based amphiphilic co-network coating remained intact with almost no marine organisms adhering to it. This study provides a novel approach for the development of high-performance silicone-based antifouling coatings.

Troxerutin suppress inflammation response and oxidative stress in jellyfish dermatitis by activating Nrf2/HO-1 signaling pathway.

Background: Stomolophus meleagris envenomation causes severe cutaneous symptoms known as jellyfish dermatitis. The potential molecule mechanisms and treatment efficiency of dermatitis remain elusive because of the complicated venom components. The biological activity and molecular regulation mechanism of Troxerutin (TRX) was firstly examined as a potential treatment for jellyfish dermatitis. Methods: We examined the inhibit effects of the TRX on tentacle extract (TE) obtained from S. meleagris in vivo and in vitro using the mice paw swelling models and corresponding assays for Enzyme-Linked Immunosorbent Assay (ELISA) Analysis, cell counting kit-8 assay, flow cytometry, respectively. The mechanism of TRX on HaCaT cells probed the altered activity of relevant signaling pathways by RNA sequencing and verified by RT-qPCR, Western blot to further confirm protective effects of TRX against the inflammation and oxidative damage caused by TE. Results: TE significantly induced the mice paw skin toxicity and accumulation of inflammatory cytokines and reactive oxygen species in vivo and vitro. Moreover, a robust increase in the phosphorylation of mitogen-activated protein kinase (MAPKs) and nuclear factor-kappa B (NF-κB) signaling pathways was observed. While, the acute cutaneous inflammation and oxidative stress induced by TE were significantly ameliorated by TRX treatment. Notablly, TRX suppressed the phosphorylation of MAPK and NF-κB by initiating the nuclear factor erythroid 2-related factor 2 signaling pathway, which result in decreasing inflammatory cytokine release. Conclusion: TRX inhibits the major signaling pathway responsible for inducing inflammatory and oxidative damage of jellyfish dermatitis, offering a novel therapy in clinical applications.

All-cause and cause-specific mortality in US adults with periodontal diseases: A prospective cohort study.

AIM: This prospective cohort study investigated the association between periodontal diseases (PDs) and all-cause and cause-specific mortality. MATERIALS AND METHODS: We utilized adult participants recruited from six National Health and Nutrition Examination Survey cycles (1999-2014) and linked mortality data from the National Death Index up to December 2019. Baseline clinical periodontal examinations were performed by trained and calibrated examiners. All-cause and cause-specific mortality was modelled through multivariable Cox proportional hazards and Fine-Gray models to account for competing risks. All models were adjusted for demographic and lifestyle variables, clinical measurements and comorbidities. RESULTS: Overall, 15,030 participants were included, with a median length of follow-up of 9 years. Risk of all-cause mortality was 22% greater in people with PD than the control group (adjusted hazard ratio [HR]: 1.22, 95% confidence interval [CI]: 1.12-1.31). Risks of mortality by cardiovascular diseases (CVD), respiratory disease and diabetes were highest in participants with severe PD (CVD-sub-distribution HR [SHR]: 1.38, 95% CI: 1.16-1.64; respiratory-SHR: 1.62, 95% CI: 1.07-2.45; diabetes-SHR: 1.68, 95% CI: 1.12-2.53). CONCLUSIONS: Severe PD is associated with all-cause and cause-specific mortality among US adults after multivariable adjustment.

Prediction of incident chronic kidney disease in community-based electronic health records: a systematic review and meta-analysis.

Background: Chronic kidney disease (CKD) is a major global health problem and its early identification would allow timely intervention to reduce complications. We performed a systematic review and meta-analysis of multivariable prediction models derived and/or validated in community-based electronic health records (EHRs) for the prediction of incident CKD in the community. Methods: Ovid Medline and Ovid Embase were searched for records from 1947 to 31 January 2024. Measures of discrimination were extracted and pooled by Bayesian meta-analysis, with heterogeneity assessed through a 95% prediction interval (PI). Risk of bias was assessed using Prediction model Risk Of Bias ASsessment Tool (PROBAST) and certainty in effect estimates by Grading of Recommendations, Assessment, Development and Evaluation (GRADE). Results: Seven studies met inclusion criteria, describing 12 prediction models, with two eligible for meta-analysis including 2 173 202 patients. The Chronic Kidney Disease Prognosis Consortium (CKD-PC) (summary c-statistic 0.847; 95% CI 0.827-0.867; 95% PI 0.780-0.905) and SCreening for Occult REnal Disease (SCORED) (summary c-statistic 0.811; 95% CI 0.691-0.926; 95% PI 0.514-0.992) models had good model discrimination performance. Risk of bias was high in 64% of models, and driven by the analysis domain. No model met eligibility for meta-analysis if studies at high risk of bias were excluded, and certainty of effect estimates was 'low'. No clinical utility analyses or clinical impact studies were found for any of the models. Conclusions: Models derived and/or externally validated for prediction of incident CKD in community-based EHRs demonstrate good prediction performance, but assessment of clinical usefulness is limited by high risk of bias, low certainty of evidence and a lack of impact studies.

Population pharmacokinetics of intravenous daptomycin in critically ill patients: implications for selection of dosage regimens.

Daptomycin is gaining prominence for the treatment of methicillin-resistant Staphylococcus aureus infections. However, the dosage selection for daptomycin in critically ill patients remains uncertain, especially in Chinese patients. This study aimed to establish the population pharmacokinetics of daptomycin in critically ill patients, optimize clinical administration plans, and recommend appropriate dosage for critically ill patients in China. The study included 64 critically ill patients. Blood samples were collected at the designated times. The blood daptomycin concentration was determined using validated liquid chromatography-tandem mass spectrometry. A nonlinear mixed-effects model was applied for the population pharmacokinetic analysis and Monte Carlo simulations of daptomycin. The results showed a two-compartment population pharmacokinetic model of daptomycin in critically ill adult Han Chinese patients. Monte Carlo simulations revealed that a daily dose of 400 mg of daptomycin was insufficient for the majority of critically ill adult patients to achieve the anti-infective target. For critically ill adult patients with normal renal function (creatinine clearance rate >90 mL/min), the probability of achieving the target only reached 90% when the daily dose was increased to 700 mg. For patients undergoing continuous renal replacement therapy (CRRT), 24 h administration of 500 mg met the pharmacodynamic goals and did not exceed the safety threshold in most patients. Therefore, considering its efficacy and safety, intravenous daptomycin doses are best scaled according to creatinine clearance, and an increased dose is recommended for critically ill patients with hyperrenalism. For patients receiving CRRT, medication is recommended at 24 h intervals.