Urea to Treat Hyponatremia Due to Syndrome of Inappropriate Antidiuretic Hormone Secretion: A Systematic Review and Meta-Analysis.

RATIONALE & OBJECTIVE: The use of urea to treat hyponatremia related to the Syndrome of Inappropriate Antidiuretic Hormone Secretion (SIADH) has not been universally adopted due to questions about effectiveness, safety, and tolerability. This systematic review and meta-analysis of observational studies aimed to address these questions. STUDY DESIGN: This PRISMA-guided study examined published research across four electronic databases. STUDY POPULATIONS: Patients with SIADH-related hyponatremia. SELECTION CRITERIA: Clinical trials and observational studies reporting at least one outcome related to serum sodium concentration, symptom resolution, or adverse effects after oral or nasogastric urea administration. DATA EXTRACTION: Data extraction was performed independently by two reviewers using a standardized form recording study characteristics, participant demographics, intervention details, and treatment outcomes. ANALYTICAL APPROACH: A meta-analysis was conducted using the restricted maximum likelihood method for the random-effects model to assess the effect of urea treatment on serum sodium and serum urea compared to other treatment modalities. Subgroup analyses were conducted based on treatment duration and SIADH severity. RESULTS: Urea treatment significantly increased serum sodium [mean difference (MD) = 9.08 (95%CI 7.64-10.52), p < 0.01] and urea [MD = 31.66 (95%CI 16.05-47.26), p < 0.01] in patients with SIADH albeit with significantly high heterogeneity. Subgroup analysis based on the treatment duration showed a significant rise in the serum sodium level after 24 hours, two, five, seven, and fourteen days, as well as after one year of treatment. Greater increases in serum sodium levels after treatment with urea occurred in patients with severe (<120 mEq/L) [MD = 18.04 (95%CI 13.68-22.39)] than with moderate (120-129 mEq/L [MD = 7.86 (95%CI 6.78-8.94)] or mild (130-135 mEq/L) [MD = 8.00 (95%CI 7.31-8.69)] SIADH induced hyponatremia. Urea treatment was comparable to fluid restriction [MD = 0.81 (95%CI: -0.93-2.55), p = 0.36) and vaptans [MD = -1.96 (95%CI: -4.59-0.66, p = 0.14) but superior to no treatment [MD = 7.99 (95%CI 6.25-9.72), p < 0.01]. Urea was associated with minor adverse events, with poor palatability being most common. LIMITATIONS: As no RCTs investigating urea as a treatment for hyponatremia were identified for inclusion, these analyses were based on observational studies. CONCLUSIONS: Urea is safe and effective for managing SIADH-induced hyponatremia. These finding suggest that urea may be a useful treatment modality in resource-limited settings or when other treatments are contraindicated or poorly tolerated.

Letter to the editor: Comment on "possible protective effect of rosuvastatin in chemotherapy-induced cardiotoxicity in HER2 positive breast cancer patients: a randomized controlled trial".

We have read with keen interest the original article by Kettana et al., which investigates the potential cardioprotective effects of rosuvastatin in HER2-positive breast cancer patients undergoing chemotherapy. We appreciate the study's meticulous methodology and its contribution to medicine oncology. However, we suggest a cautious interpretation of the results due to unmeasured confounding variables that could influence cardiotoxicity development and treatment efficacy. The study's fixed dosing approach to rosuvastatin precludes the assessment of dose-dependent effects, prompting a recommendation for future dose-response analyses. We also highlight the need to incorporate patient-reported outcomes for a more holistic treatment efficacy evaluation. Furthermore, we propose metabolomic analysis to uncover the drug's mechanisms of action and computational methods like molecular docking to predict its potential targets, which could refine drug design and inform personalized treatment strategies. Our commentary aims to refine the study's conclusions and encourage research that maximizes the understanding and clinical management of chemotherapy-induced cardiotoxicity.

Beneficial effect of sequential treatment with high-dose steroids and short-course oral glucocorticoids in patients with severe influenza virus-associated pneumonia.

Accumulating evidence supports that glucocorticoid treatment for viral pneumonia (VPA) can shorten the disease course and improve survival. However, currently, the use of glucocorticoids in treating VPA remains controversial. Moreover, a unified standard for the dosage and duration of glucocorticoid therapy has not been presented in published articles. A retrospective analysis was conducted in patients who were hospitalized for severe influenza virus-associated pneumonia, and they received sequential treatment with high-dose glucocorticoids and short-course oral glucocorticoids. Patients were followed up for 3 months. A total of 11 patients were included in the study (average age 56 years). There was no gender difference, but age and underlying diseases could be risk factors for severe influenza virus-associated pneumonia. The types of viruses causing pneumonia included influenza A/B. The main clinical symptoms of patients were fever, cough, sputum production, and dyspnea. Chest computed tomography showed multiple ground-glass shadows in the lobes, and the presence of bacterial and fungal infections was accompanied by consolidation shadows. After glucocorticoid therapy, the symptoms improved. None of the patients underwent tracheal intubation, and all survived. After a 3-month follow-up, lung CT absorption in all patients had reached more than 80%, and lung imaging absorption in 20% patients was complete. No serious complications occurred in any of the patients. Sequential treatment with high-dose steroids and short-course oral glucocorticoids may be helpful for reducing the tracheal intubation rate and mortality rate in patients with severe influenza virus-associated pneumonia. Additionally, short-course oral glucocorticoids may reduce pulmonary fibrosis in patients with severe influenza virus-associated pneumonia without any serious complications.

The two-sided battlefield of tumour-associated macrophages in glioblastoma: unravelling their therapeutic potential.

Gliomas are the most common primary malignant tumours of the central nervous system (CNS), which are highly aggressive, with increasing morbidity and mortality rates year after year, posing a serious threat to the quality and expected survival time of patients. The treatment of gliomas is a major challenge in the field of neuro-oncology, especially high-grade gliomas such as glioblastomas (GBMs). Despite considerable progress in recent years in the study of the molecular and cellular mechanisms of GBMs, their prognosis remains bleak. Tumour-associated macrophages (TAMs) account for up to 50% of GBMs, and they are a highly heterogeneous cell population whose role cannot be ignored. Here, we focus on reviewing the contribution of classically activated M1-phenotype TAMs and alternatively activated M2-phenotype TAMs to GBMs, and exploring the research progress in reprogramming M1 TAMs into M2 TAMs.

Revealing the association between East Asian oral microbiome and colorectal cancer through Mendelian randomization and multi-omics analysis.

Background: Colorectal cancer (CRC) poses a global health threat, with the oral microbiome increasingly implicated in its pathogenesis. This study leverages Mendelian Randomization (MR) to explore causal links between oral microbiota and CRC using data from the China National GeneBank and Biobank Japan. By integrating multi-omics approaches, we aim to uncover mechanisms by which the microbiome influences cellular metabolism and cancer development. Methods: We analyzed microbiome profiles from 2017 tongue and 1915 saliva samples, and GWAS data for 6692 CRC cases and 27178 controls. Significant bacterial taxa were identified via MR analysis. Single-cell RNA sequencing and enrichment analyses elucidated underlying pathways, and drug predictions identified potential therapeutics. Results: MR identified 19 bacterial taxa significantly associated with CRC. Protective effects were observed in taxa like RUG343 and Streptococcus_umgs_2425, while HOT-345_umgs_976 and W5053_sp000467935_mgs_712 increased CRC risk. Single-cell RNA sequencing revealed key pathways, including JAK-STAT signaling and tyrosine metabolism. Drug prediction highlighted potential therapeutics like Menadione Sodium Bisulfite and Raloxifene. Conclusion: This study establishes the critical role of the oral microbiome in colorectal cancer development, identifying specific microbial taxa linked to CRC risk. Single-cell RNA sequencing and drug prediction analyses further elucidate key pathways and potential therapeutics, providing novel insights and personalized treatment strategies for CRC.

A Mendelian randomization study of the association between serum uric acid and osteoporosis risk.

Background: The relationship between serum uric acid (SUA) and osteoporosis (OP) has yielded conflicting results in observational studies. This Mendelian randomization (MR) study aims to elucidate the causal association between SUA and OP. Methods: A two-sample MR analysis was conducted using summary-level data from genome-wide association studies (GWAS). Two sets of polygenic instruments strongly associated (p < 5 × 10-8) with SUA were extracted from the CKDGen consortium and UK biobank. Polygenic instruments associated with OP (p < 5 × 10-8) were derived from FinnGen biobank and UK biobank. Inverse variance weighting (IVW) was employed as the primary analysis method. Additionally, we utilized MR-Egger, weighted median, the simple mode method, and the weighted mode as complementary analyses. Cochran's Q statistics were used to assess heterogeneity, with MR-Egger intercept testing and MR pleiotropy residual sum and outlier (MR-PRESSO) to examine horizontal pleiotropy. Sensitivity analysis was performed using the leave-one-out method. Results: The IVW analysis conducted across four groups confirms no significant causal relationship between SUA concentration and OP: UKB-UKB (OR: 1.001, 95% CI: 0.999-1.003, p=0.464), CKD-UKB (OR: 1.001, 95% CI: 0.999-1.003, p=0.349), UKB-Fin (OR: 0.934, 95% CI: 0.747-1.168, p=0.549), CKD-Fin (OR: 1.041, 95%CI: 0.934-1.161, p=0.470). Furthermore, additional four MR analyses corroborated these findings. Upon excluding all outliers identified by the MR-PRESSO test, no significant directional pleiotropy was observed, except for some data heterogeneity noted in the UKB-UKB group (Q=50.65, P=0.002). Additionally, a leave-one-out analysis indicated that no single SNP exerted undue influence on the results. Conclusion: This MR analysis provides convincing genetic evidence that there is no causal association between SUA and OP, SUA is unlikely to increase or reduce the risk of OP.

Artificial Intelligence Hybrid Survival Assessment System for Robot-Assisted Proctectomy: A Retrospective Cohort Study.

PURPOSE: Robotic-assisted proctectomy (RAP) has emerged as the predominant surgical approach for patients with rectal cancer in recent years; although good postoperative patient recovery with accurate prediction is a guarantee of adaptive surveillance management, there is still a lack of easy-to-use prognostic tools and risk scores designed specifically for those patients undergoing RAP. METHODS: This study used the electronic health records of 506 RAP participants, including a National Specialist Center for da Vinci Robotic Colorectal Surgery (NSCVRCS) meta cohort, and an independent external validation Sun Yat-sen Memorial Hospital cohort. In the NSCVRCS meta cohort, patients were divided into a discovery cohort (70%, n = 268), where the best-fit model was applied to model our prediction system, RAP-AIscore. Subsequently, an internal validation process for RAP-AIscore was conducted using a replication cohort (30%, n = 116). The study designed and implemented a large-scale artificial intelligence (AI) hybrid framework to identify the best strategy for building a survival assessment system, the RAP-AIscore, from 132 potential modeling scenarios through a combination of iterative cross-validation, Monte Carlo cross-validation, and bootstrap resampling. The 10 variables most relevant to clinical interpretability were identified on the basis of the AI hybrid optimal model values, which helps provide reliable prognostic survival guidance for new patients. RESULTS: The consistent evaluation of discrimination, calibration, generalization, and prognostic value across cohorts reaffirmed the accuracy and robust extrapolation capability of this system. The 10 feature variables most associated with clinical interpretability on the basis of Shapley values were identified, facilitating reliable prognostic survival guidance for new patients. CONCLUSION: This study introduces a promising and informative tool, the RAP-AIscore, which can be explained through nomograms for interpreting clinical outcomes. It facilitates postoperative risk stratification management and enhances clinical management of prognosis for RAP patients.

Integrative biomarker discovery and immune profiling for ulcerative colitis: a multi-methodological approach.

Background We aimed to pinpoint biomarkers, create a diagnostic model for ulcerative colitis (UC), and delve into its immune features to better understand this autoimmune condition. Methods The sequencing data for both the UC and the control groups were obtained from GEO, including both bulk and single-cell data. Using GSE87466 as training group, we applied differential analysis, WGCNA, PPI, LASSO, RF, and SVM-RFE for biomarker selection. A neural network shaped our diagnostic model, corroborated by GSE92415 as the validation cohort with ROC assessment. Immune cell profiling was conducted using CIBERSORT. Results 53 disease-associated genes were screened. Enrichment analysis highlighted roles in complement cascades and cell adhesion. Eight biomarkers were finally identified through multiple machine learning and PPI: B4GALNT2, PDZK1IP1, FAM195A, REG4, MTMR11, FLJ35024, CD55, and CD44. The diagnostic model had AUCs of 0.984 (training group) and 0.957 (validation group). UC tissues revealed heightened plasma cells, CD8 T cells, and other immune cells. Two unique UC immune patterns emerged, with certain T and NK cells central to immune modulation. Conclusion We identified eight biomarkers of UC by various methods, constructed a diagnostic model through neural networks, and explored the immune complexity of the disease, which contributes to the diagnosis and treatment of UC.

Multi-modal transcriptomic analysis reveals metabolic dysregulation and immune responses in chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD), a progressive inflammatory condition of the airways, emerges from the complex interplay between genetic predisposition and environmental factors. Notably, its incidence is on the rise, particularly among the elderly demographic. Current research increasingly highlights cellular senescence as a key driver in chronic lung pathologies. Despite this, the detailed mechanisms linking COPD with senescent genomic alterations remain elusive. To address this gap, there is a pressing need for comprehensive bioinformatics methodologies that can elucidate the molecular intricacies of this link. This approach is crucial for advancing our understanding of COPD and its association with cellular aging processes. Utilizing a spectrum of advanced bioinformatics techniques, this research delved into the potential mechanisms linking COPD with aging-related genes, identifying four key genes (EP300, MTOR, NFE2L1, TXN) through machine learning and weighted gene co-expression network analysis (WGCNA) analyses. Subsequently, a precise diagnostic model leveraging an artificial neural network was developed. The study further employed single-cell analysis and molecular docking to investigate senescence-related cell types in COPD tissues, particularly focusing on the interactions between COPD and NFE2L1, thereby enhancing the understanding of COPD's molecular underpinnings. Leveraging artificial neural networks, we developed a robust classification model centered on four genes-EP300, MTOR, NFE2L1, TXN-exhibiting significant predictive capability for COPD and offering novel avenues for its early diagnosis. Furthermore, employing various single-cell analysis techniques, the study intricately unraveled the characteristics of senescence-related cell types in COPD tissues, enriching our understanding of the disease's cellular landscape. This research anticipates offering novel biomarkers and therapeutic targets for early COPD intervention, potentially alleviating the disease's impact on individuals and healthcare systems, and contributing to a reduction in global COPD-related mortality. These findings carry significant clinical and public health ramifications, bolstering the foundation for future research and clinical strategies in managing and understanding COPD.

Substrate-directed regioselective alkene functionalizations of (E)-ß,γ-unsaturated carboxylic acids.

A carboxylate-directed regioselective Heck-type alkenylation and alkenylative lactonization of (E)-ß,γ-unsaturated carboxylic acids by simply substrate control is reported. (E)- and (Z)-alkenyl bromides reacted to give energetically more favorable palladacyles, allowing access to fully stereocontrolled conjugated 1,3-dienes and alkenyled γ-lactones. Mechanistic studies suggest that excellent regioselectivity may be strongly influenced by the steric factors of reactants involved in the palladacycle intermediates.

Camrelizumab combined with transcatheter arterial chemoembolization and sorafenib or lenvatinib for unresectable hepatocellular carcinoma: A multicenter, retrospective study.

INTRODUCTION AND OBJECTIVES: We initiated this study to explore the efficacy of camrelizumab combined with transcatheter arterial chemoembolization (TACE) plus sorafenib or lenvatinib versus TACE plus sorafenib or Lenvatinib for unresectable hepatocellular carcinoma (HCC). MATERIALS AND METHODS: From June 2019 to November 2022, 127 advanced HCC patients were retrospectively analyzed in this study. This consisted of 44 patients that received camrelizumab plus TACE plus sorafenib or lenvatinib (triple therapy group) and 83 patients that received TACE plus sorafenib or lenvatinib (double treatment group). The overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR) were compared between the two patient groups. RESULTS: Our findings demonstrated that patients received the triple therapy exhibited superior median OS (15.8 vs. 10.3 months, P=0.0011) and median PFS (7.2 vs. 5.2 months, P=0.019) compared to the double treatment group. In addition, the triple therapy group exhibited better 6-month (93.5% vs. 66.3%), 12-month (67.2% vs. 36.3%), and 24-month (17.2% vs. 7.6%) survival rates than the double treatment group. However, the ORR (43.2% vs. 28.9%, P = 0.106) and DCR (93.2% vs. 81.9%, P = 0.084) of the two groups were similar. Subgroup analysis showed that compared with the double treatment group, the triple therapy group had a better mOS for HCC with HBV (15.8 vs. 9.6 months, P = 0.0015) and tumor diameter ≥ 5cm (15.3 vs. 9.6 months, P = 0.00055). CONCLUSIONS: Camrelizumab plus TACE and sorafenib or lenvatinib may be a promising treatment approach for the clinical management of unresectable HCC patients.

sTREM2 Mediates the Correlation Between BIN1 Gene Polymorphism and Tau Pathology in Alzheimer's Disease.

Background: Bridging integrator 1 (BIN1) gene polymorphism has been reported to play a role in the pathological processes of Alzheimer's disease (AD). Objective: To explore the association of BIN1 loci with neuroinflammation and AD pathology. Methods: Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 495) was the discovery cohort, and Chinese Alzheimer's Biomarker and LifestylE (CABLE, N = 619) study was used to replicate the results. Two BIN1 gene polymorphism (rs7561528 and rs744373) were included in the analysis. Multiple linear regression model and causal mediation analysis conducted through 10,000 bootstrapped iterations were used to examine the BIN1 loci relationship with cerebrospinal fluid (CSF) AD biomarkers and alternative biomarker of microglial activation microglia-soluble triggering receptor expressed on myeloid cells 2 (sTREM2). Results: In ADNI database, we found a significant association between BIN1 loci (rs7561528 and rs744373) and levels of CSF phosphorylated-tau (P-tau) (pc = 0.017; 0.010, respectively) and total-tau (T-tau) (pc = 0.011; 0.013, respectively). The BIN1 loci were also correlated with CSF sTREM2 levels (pc = 0.010; 0.008, respectively). Mediation analysis demonstrated that CSF sTREM2 partially mediated the association of BIN1 loci with P-tau (Proportion of rs7561528 : 20.8%; Proportion of rs744373 : 24.8%) and T-tau (Proportion of rs7561528 : 36.5%; Proportion of rs744373 : 43.9%). The analysis in CABLE study replicated the mediation role of rs7561528. Conclusions: This study demonstrated the correlation between BIN1 loci and CSF AD biomarkers as well as microglia biomarkers. Additionally, the link between BIN1 loci and tau pathology was partially mediated by CSF sTREM2.

Photonic generation and programmable switching of variable-band chirped waveforms with immunity to power fading.

A photonic approach for generating and programmable switching variable-band chirped waveforms by using a dual-parallel Mach-Zehnder modulator (DPMZM) is proposed and experimentally demonstrated. By coupling binary switching codes with the baseband chirped signal and applying them into the RF input port of DPMZM, the variable-band chirped waveforms can be generated and fast switched. The switching speed is consistent with the input code bit rate. Moreover, by properly adjusting the bias voltages, the generated signals can be anti-dispersion transmitted over different distances. Full experimental verification on the generation and programmable switching of the chirped waveforms centered at 2.1, 6.3, and 8.4 GHz or 1.5, 4.5, and 6 GHz over 10 or 20 km standard single-mode fibers with 4 or 100 Mbps switching rates are successfully carried out. The proposed approach features compact architecture, programmable switching capability and immunity to power fading, which are significant in distributed multifunction radar networks with optical fiber-based transmission.

An overview of multi-omics technologies in rheumatoid arthritis: applications in biomarker and pathway discovery.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease with a complex pathological mechanism involving autoimmune response, local inflammation and bone destruction. Metabolic pathways play an important role in immune-related diseases and their immune responses. The pathogenesis of rheumatoid arthritis may be related to its metabolic dysregulation. Moreover, histological techniques, including genomics, transcriptomics, proteomics and metabolomics, provide powerful tools for comprehensive analysis of molecular changes in biological systems. The present study explores the molecular and metabolic mechanisms of RA, emphasizing the central role of metabolic dysregulation in the RA disease process and highlighting the complexity of metabolic pathways, particularly metabolic remodeling in synovial tissues and its association with cytokine-mediated inflammation. This paper reveals the potential of histological techniques in identifying metabolically relevant therapeutic targets in RA; specifically, we summarize the genetic basis of RA and the dysregulated metabolic pathways, and explore their functional significance in the context of immune cell activation and differentiation. This study demonstrates the critical role of histological techniques in decoding the complex metabolic network of RA and discusses the integration of histological data with other types of biological data.

Circadian rhythms and breast cancer: unraveling the biological clock's role in tumor microenvironment and ageing.

Breast cancer (BC) is one of the most common and fatal malignancies among women worldwide. Circadian rhythms have emerged in recent studies as being involved in the pathogenesis of breast cancer. In this paper, we reviewed the molecular mechanisms by which the dysregulation of the circadian genes impacts the development of BC, focusing on the critical clock genes, brain and muscle ARNT-like protein 1 (BMAL1) and circadian locomotor output cycles kaput (CLOCK). We discussed how the circadian rhythm disruption (CRD) changes the tumor microenvironment (TME), immune responses, inflammation, and angiogenesis. The CRD compromises immune surveillance and features and activities of immune effectors, including CD8+ T cells and tumor-associated macrophages, that are important in an effective anti-tumor response. Meanwhile, in this review, we discuss bidirectional interactions: age and circadian rhythms, aging further increases the risk of breast cancer through reduced vasoactive intestinal polypeptide (VIP), affecting suprachiasmatic nucleus (SCN) synchronization, reduced ability to repair damaged DNA, and weakened immunity. These complex interplays open new avenues toward targeted therapies by the combination of clock drugs with chronotherapy to potentiate the immune response while reducing tumor progression for better breast cancer outcomes. This review tries to cover the broad area of emerging knowledge on the tumor-immune nexus affected by the circadian rhythm in breast cancer.