The ERK inhibitor GDC-0994 selectively inhibits growth of BRAF mutant cancer cells.

BRAF or RAS mutation-induced aberrant activation of the mitogen-activated protein kinase (MAPK) pathway is frequently observed in human cancers. As the key downstream node of MAPK pathway, ERK1/2 is as an important therapeutic target. GDC-0994 (ravoxertinib), an orally bioavailable, highly selective small-molecule inhibitor of ERK1/2, showed acceptable safety and pharmacodynamic profile in a recent phase I clinical trial. In this study, we investigated dependence of the anti-tumor effect of ERK inhibitor GDC-0994 on genetic alterations in the MAPK pathway. The results showed that GDC-0994 sharply inhibited cell proliferation and colony formation and induced remarkable G1 phase cell-cycle arrest in cancer cells harboring BRAF mutation but had little effect on cell behaviors in most RAS mutant or wild-type cell lines. The expression of a large number of genes, particularly the genes in the cell cycle pathway, were significantly changed after GDC-0994 treatment in BRAF mutant cells, while no remarkable expression change of such genes was observed in wild-type cells. Moreover, GDC-0994 selectively inhibited tumor growth in a BRAF mutant xenograft mice model. Our findings demonstrate a BRAF mutation-dependent anti-tumor effect of GDC-0994 and provide a rational strategy for patient selection for ERK1/2 inhibitor treatment.

ACNN-BiLSTM: A Deep Learning Approach for Continuous Noninvasive Blood Pressure Measurement Using Multi-Wavelength PPG Fusion.

As an essential physiological indicator within the human body, noninvasive continuous blood pressure (BP) measurement is critical in the prevention and treatment of cardiovascular disease. However, traditional methods of blood pressure prediction using a single-wavelength Photoplethysmographic (PPG) have bottlenecks in further improving BP prediction accuracy, which limits their development in clinical application and dissemination. To this end, this study proposed a method to fuse a four-wavelength PPG and a BP prediction model based on the attention mechanism of a convolutional neural network and bidirectional long- and short-term memory (ACNN-BiLSTM). The effectiveness of a multi-wavelength PPG fusion method for blood pressure prediction was evaluated by processing PPG signals from 162 volunteers. The study compared the performance of the PPG signals with different individual wavelengths and using a multi-wavelength PPG fusion method in blood pressure prediction, assessed using mean absolute error (MAE), root mean squared error (RMSE) and AAMI-related criteria. The experimental results showed that the ACNN-BiLSTM model achieved a better MAE ± RMSE for a systolic BP and diastolic BP of 1.67 ± 5.28 and 1.15 ± 2.53 mmHg, respectively, when using the multi-wavelength PPG fusion method. As a result, the ACNN-BiLSTM blood pressure model based on multi-wavelength PPG fusion could be considered a promising method for noninvasive continuous BP measurement.

Reconstruction of Missing Electrocardiography Signals from Photoplethysmography Data Using Deep Neural Network.

ECG helps in diagnosing heart disease by recording heart activity. During long-term measurements, data loss occurs due to sensor detachment. Therefore, research into the reconstruction of missing ECG data is essential. However, ECG requires user participation and cannot be used for continuous heart monitoring. Continuous monitoring of PPG signals is conversely low-cost and easy to carry out. In this study, a deep neural network model is proposed for the reconstruction of missing ECG signals using PPG data. This model is an end-to-end deep learning neural network utilizing WNet architecture as a basis, on which a bidirectional long short-term memory network is added in establishing a second model. The performance of both models is verified using 146 records from the MIMIC III matched subset. Compared with the reference, the ECG reconstructed using the proposed model has a Pearson's correlation coefficient of 0.851, root mean square error (RMSE) of 0.075, percentage root mean square difference (PRD) of 5.452, and a Fréchet distance (FD) of 0.302. The experimental results demonstrate that it is feasible to reconstruct missing ECG signals from PPG.

Carbon quantum dots of ginsenoside Rb1 for application in a mouse model of intracerebral Hemorrhage.

After intracerebral hemorrhage (ICH) occurs, the overproduction of reactive oxygen species (ROS) and iron ion overload are the leading causes of secondary damage. Removing excess iron ions and ROS in the meningeal system can effectively alleviate the secondary damage after ICH. This study synthesized ginsenoside Rb1 carbon quantum dots (RBCQDs) using ginsenoside Rb1 and ethylenediamine via a hydrothermal method. RBCQDs exhibit potent capabilities in scavenging ABTS + free radicals and iron ions in solution. After intrathecal injection, the distribution of RBCQDs is predominantly localized in the subarachnoid space. RBCQDs can eliminate ROS and chelate iron ions within the meningeal system. Treatment with RBCQDs significantly improves blood flow in the meningeal system, effectively protecting dying neurons, improving neurological function, and providing a new therapeutic approach for the clinical treatment of ICH.

Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study.

BACKGROUND: Early identification of patients at high-risk of postoperative acute kidney injury (AKI) can facilitate the development of preventive approaches. This study aimed to develop prediction models for postoperative AKI in noncardiac surgery using machine learning algorithms. The authors also evaluated the predictive performance of models that included only preoperative variables or only important predictors. MATERIALS AND METHODS: Adult patients undergoing noncardiac surgery were retrospectively included in the study (76 457 patients in the discovery cohort and 11 910 patients in the validation cohort). AKI was determined using the KDIGO criteria. The prediction model was developed using 87 variables (56 preoperative variables and 31 intraoperative variables). A variety of machine learning algorithms were employed to develop the model, including logistic regression, random forest, extreme gradient boosting, and gradient boosting decision trees. The performance of different models was compared using the area under the receiver operating characteristic curve (AUROC). Shapley Additive Explanations (SHAP) analysis was employed for model interpretation. RESULTS: The patients in the discovery cohort had a median age of 52 years (IQR: 42-61 years), and 1179 patients (1.5%) developed AKI after surgery. The gradient boosting decision trees algorithm showed the best predictive performance using all available variables, or only preoperative variables. The AUROCs were 0.849 (95% CI: 0.835-0.863) and 0.828 (95% CI: 0.813-0.843), respectively. The SHAP analysis showed that age, surgical duration, preoperative serum creatinine, and gamma-glutamyltransferase, as well as American Society of Anesthesiologists physical status III were the most important five features. When gradually reducing the features, the AUROCs decreased from 0.852 (including the top 40 features) to 0.839 (including the top 10 features). In the validation cohort, the authors observed a similar pattern regarding the models' predictive performance. CONCLUSIONS: The machine learning models the authors developed had satisfactory predictive performance for identifying high-risk postoperative AKI patients. Furthermore, the authors found that model performance was only slightly affected when only preoperative variables or only the most important predictive features were included.

CircAKT3 alleviates postoperative cognitive dysfunction by stabilizing the feedback cycle of miR-106a-5p/HDAC4/MEF2C axis in hippocampi of aged mice.

Circular RNAs (circRNAs) have garnered significant attention in the field of neurodegenerative diseases including Alzheimer's diseases due to their covalently closed loop structure. However, the involvement of circRNAs in postoperative cognitive dysfunction (POCD) is still largely unexplored. To identify the genes differentially expressed between non-POCD (NPOCD) and POCD mice, we conducted the whole transcriptome sequencing initially in this study. According to the expression profiles, we observed that circAKT3 was associated with hippocampal neuronal apoptosis in POCD mice. Moreover, we found that circAKT3 overexpression reduced apoptosis of hippocampal neurons and alleviated POCD. Subsequently, through bioinformatics analysis, our data showed that circAKT3 overexpression in vitro and in vivo elevated the abundance of miR-106a-5p significantly, resulting in a decrease of HDAC4 protein and an increase of MEF2C protein. Additionally, this effect of circAKT3 was blocked by miR-106a-5p inhibitor. Interestingly, MEF2C could activate the transcription of miR-106a-5p promoter and form a positive feedback loop. Therefore, our findings revealed more potential modulation ways between circRNA-miRNA and miRNA-mRNA, providing different directions and targets for preclinical studies of POCD.

Macrophage migration inhibitor factor (MIF): Potential role in cognitive impairment disorders.

Macrophage migration inhibitory factor (MIF) is a cytokine in the immune system, participated in both innate and adaptive immune responses. Except from immune cells, MIF is also secreted by a variety of non-immune cells, including hematopoietic cells, endothelial cells (ECs), and neurons. MIF plays a crucial role in various diseases, such as sepsis, rheumatoid arthritis, acute kidney injury, and neurodegenerative diseases. The role of MIF in the neuropathogenesis of cognitive impairment disorders is emphasized, as it recruits multiple inflammatory mediators, leading to activating microglia or astrocyte-derived neuroinflammation. Furthermore, it contributes to the cell death of neurons and ECs with the binding of apoptosis-inducing factor (AIF) through parthanatos-associated apoptosis-inducing factor nuclease (PAAN) / MIF pathway. This review comprehensively delves into the relationship between MIF and the neuropathogenesis of cognitive impairment disorders, providing a series of emerging MIF-targeted pharmaceuticals as potential treatments for cognitive impairment disorders.

TERT promoter methylation is associated with high expression of TERT and poor prognosis in papillary thyroid cancer.

The telomerase reverse transcriptase (TERT) is overexpressed and associated with poor prognosis in papillary thyroid cancer (PTC), the most common subtype of thyroid cancer. The overexpression of TERT in PTC was partially attributed to transcriptional activation by two hotspot mutations in the core promoter region of this gene. As one of the major epigenetic mechanisms of gene expression regulation, DNA methylation has been proved to regulate several tumor-related genes in PTC. However, the association of TERT promoter DNA methylation with TERT expression and PTC progression is still unclear. By treating PTC cell lines with demethylating agent decitabine, we found that the TERT promoter methylation and the genes' expression were remarkably decreased. Consistently, PTC patients with TERT hypermethylation had significantly higher TERT expression than patients with TERT hypomethylation. Moreover, TERT hypermethylated patients showed significant higher rates of poor clinical outcomes than patients with TERT hypomethylation. Results from the cox regression analysis showed that the hazard ratios (HRs) of TERT hypermethylation for overall survival, disease-specific survival, disease-free interval (DFI) and progression-free interval (PFI) were 4.81 (95% CI, 1.61-14.41), 8.28 (95% CI, 2.14-32.13), 3.56 (95% CI, 1.24-10.17) and 3.32 (95% CI, 1.64-6.71), respectively. The HRs for DFI and PFI remained significant after adjustment for clinical risk factors. These data suggest that promoter DNA methylation upregulates TERT expression and associates with poor clinical outcomes of PTC, thus holds the potential to be a valuable prognostic marker for PTC risk stratification.

Non-invasive detection of lymphoma with circulating tumor DNA features and protein tumor markers.

Background: According to GLOBOCAN 2020, lymphoma ranked as the 9th most common cancer and the 12th leading cause of cancer-related deaths worldwide. Traditional diagnostic methods rely on the invasive excisional lymph node biopsy, which is an invasive approach with some limitations. Most lymphoma patients are diagnosed at an advanced stage since they are asymptomatic at the beginning, which has significantly impacted treatment efficacy and prognosis of the disease. Method: This study assessed the performance and utility of a newly developed blood-based assay (SeekInCare) for lymphoma early detection. SeekInCare utilized protein tumor markers and a comprehensive set of cancer-associated genomic features, including copy number aberration (CNA), fragment size (FS), end motif, and lymphoma-related virus, which were profiled by shallow WGS of cfDNA. Results: Protein marker CA125 could be used for lymphoma detection independent of gender, and the sensitivity was 27.8% at specificity of 98.0%. After integrating these multi-dimensional features, 77.8% sensitivity was achieved at specificity of 98.0%, while its NPV and PPV were both more than 92% for lymphoma detection. The sensitivity of early-stage (I-II) lymphoma was up to 51.3% (47.4% and 55.0% for stage I and II respectively). After 2 cycles of treatment, the molecular response of SeekInCare was correlated with the clinical outcome. Conclusion: In summary, a blood-based assay can be an alternative to detect lymphoma with adequate performance. This approach becomes particularly valuable in cases where obtaining tissue biopsy is difficult to obtain or inconclusive.

Vision-driven metasurfaces for perception enhancement.

Metasurfaces have exhibited unprecedented degree of freedom in manipulating electromagnetic (EM) waves and thus provide fantastic front-end interfaces for smart systems. Here we show a framework for perception enhancement based on vision-driven metasurface. Human's eye movements are matched with microwave radiations to extend the humans' perception spectrum. By this means, our eyes can "sense" visual information and invisible microwave information. Several experimental demonstrations are given for specific implementations, including a physiological-signal-monitoring system, an "X-ray-glasses" system, a "glimpse-and-forget" tracking system and a speech reception system for deaf people. Both the simulation and experiment results verify evident advantages in perception enhancement effects and improving information acquisition efficiency. This framework can be readily integrated into healthcare systems to monitor physiological signals and to offer assistance for people with disabilities. This work provides an alternative framework for perception enhancement and may find wide applications in healthcare, wearable devices, search-and-rescue and others.

Prognostic significance of preoperative nutritional status for postoperative acute kidney injury in older patients undergoing major abdominal surgery: a retrospective cohort study.

BACKGROUND: The association between malnutrition and postoperative acute kidney injury (AKI) has not been well studied. In this study, the authors examined the association between preoperative nutritional status and postoperative AKI in older patients who underwent major abdominal surgery, as well as the predictive value of malnutrition for AKI. MATERIALS AND METHODS: The authors retrospectively included patients aged 65 or older who underwent major elective abdominal surgery. The nutritional status of the patient was evaluated using three objective nutritional indices, such as the geriatric nutritional risk index (GNRI), the prognostic nutritional index (PNI), and the controlling nutritional status (CONUT). AKI was determined using the KDIGO criteria. The authors performed logistic regression analysis to investigate the association between preoperative nutritional status and postoperative AKI, as well as the predictive value of nutritional scores for postoperative AKI. RESULTS: A total of 2775 patients were included in the study, of which 707 (25.5%), 291 (10.5%), and 517 (18.6%) had moderate to severe malnutrition according to GNRI, PNI, and CONUT calculations. After surgery, 144 (5.2%) patients developed AKI, 86.1% at stage 1, 11.1% at stage 2, and 2.8% at stage 3 as determined by KDIGO criteria. After adjustment for traditional risk factors, worse nutritional scores were associated with a higher AKI risk. In addition to traditional risk factors, these nutritional indices improved the predictive ability of AKI prediction models, as demonstrated by significant improvements in integrated discrimination and net reclassification. CONCLUSIONS: Poor preoperative nutritional status, as assessed by GNRI, PNI, and CONUT scores, was associated with an increased risk of postoperative AKI. Incorporating these scores into AKI prediction models improved their performance. These findings emphasize the need for screening surgical patients for malnutrition risk. Further research is needed to determine whether preoperative malnutrition assessment and intervention can reduce postoperative AKI incidence.

Intermittent Fasting on Neurologic Diseases: Potential Role of Gut Microbiota.

As the global population ages, the prevalence of neurodegenerative diseases is surging. These disorders have a multifaceted pathogenesis, entwined with genetic and environmental factors. Emerging research underscores the profound influence of diet on the development and progression of health conditions. Intermittent fasting (IF), a dietary pattern that is increasingly embraced and recommended, has demonstrated potential in improving neurophysiological functions and mitigating pathological injuries with few adverse effects. Although the precise mechanisms of IF's beneficial impact are not yet completely understood, gut microbiota and their metabolites are believed to be pivotal in mediating these effects. This review endeavors to thoroughly examine current studies on the shifts in gut microbiota and metabolite profiles prompted by IF, and their possible consequences for neural health. It also highlights the significance of dietary strategies as a clinical consideration for those with neurological conditions.

Multifunctional Carbon Quantum Dots: Iron Clearance and Antioxidation for Neuroprotection in Intracerebral Hemorrhage Mice.

Iron overload and oxidative stress are pivotal in the pathogenesis of brain injury secondary to intracerebral hemorrhage (ICH). There is a compelling need for agents that can chelate iron and scavenge free radicals, particularly those that demonstrate substantial brain penetration, to mitigate ICH-related damage. In this study, we have engineered an amine-functionalized aspirin-derived carbon quantum dot (NACQD) with a nominal diameter of 6-13 nm. The NACQD possesses robust iron-binding and antioxidative capacities. Through intrathecal administration, NACQD therapy substantially reduced iron deposition and oxidative stress in brain tissue, alleviated meningeal inflammatory responses, and improved the recovery of neurological function in a murine ICH model. As a proof of concept, the intrathecal injection of NACQD is a promising therapeutic strategy to ameliorate the ICH injury.

Circulating cell-free DNA fragmentation is a stepwise and conserved process linked to apoptosis.

BACKGROUND: Circulating cell-free DNA (cfDNA) is a pool of short DNA fragments mainly released from apoptotic hematopoietic cells. Nevertheless, the precise physiological process governing the DNA fragmentation and molecular profile of cfDNA remains obscure. To dissect the DNA fragmentation process, we use a human leukemia cell line HL60 undergoing apoptosis to analyze the size distribution of DNA fragments by shallow whole-genome sequencing (sWGS). Meanwhile, we also scrutinize the size profile of plasma cfDNA in 901 healthy human subjects and 38 dogs, as well as 438 patients with six common cancer types by sWGS. RESULTS: Distinct size distribution profiles were observed in the HL60 cell pellet and supernatant, suggesting fragmentation is a stepwise process. Meanwhile, C-end preference was seen in both intracellular and extracellular cfDNA fragments. Moreover, the cfDNA profiles are characteristic and conserved across mammals. Compared with healthy subjects, distinct cfDNA profiles with a higher proportion of short fragments and lower C-end preference were found in cancer patients. CONCLUSIONS: Our study provides new insight into fragmentomics of circulating cfDNA processing, which will be useful for early diagnosis of cancer and surveillance during cancer progression.

Comparative Transcriptome Analysis Reveals the Molecular Mechanisms of Acetic Acid Reduction by Adding NaHSO3 in Actinobacillus succinogenes GXAS137.

Acetic acid (AC) is a major by-product from fermentation processes for producing succinic acid (SA) using Actinobacillus succinogenes. Previous experiments have demonstrated that sodium bisulfate (NaHSO3) can significantly decrease AC production by A. succinogenes GXAS137 during SA fermentation. However, the mechanism of AC reduction is poorly understood. In this study, the transcriptional profiles of the strain were compared through Illumina RNA-seq to identify differentially expressed genes (DEGs). A total of 210 DEGs were identified by expression analysis: 83 and 127 genes up-regulated and down-regulated, respectively, in response to NaHSO3 treatment. The functional annotation analysis of DEGs showed that the genes were mainly involved in carbohydrates, inorganic ions, amino acid transport, metabolism, and energy production and conversion. The mechanisms of AC reduction might be related to two aspects: (i) the lipoic acid synthesis pathway (LipA, LipB) was significantly down-regulated, which blocked the pathway catalyzed by pyruvate dehydrogenase complex to synthesize acetyl-coenzyme A (acetyl-CoA) from pyruvate; (ii) the expression level of the gene encoding bifunctional acetaldehyde-alcohol dehydrogenase was significantly up-regulated, and this effect facilitated the synthesis of ethanol from acetyl-CoA. However, the reaction of NaHSO3 with the intermediate metabolite acetaldehyde blocked the production of ethanol and consumed acetyl-CoA, thereby decreasing AC production. Thus, our study provides new insights into the molecular mechanism of AC decreased underlying the treatment of NaHSO3 and will deepen the understanding of the complex regulatory mechanisms of A. succinogenes.

Exploring Astrocyte-Mediated Mechanisms in Sleep Disorders and Comorbidity.

Astrocytes, the most abundant cells in the brain, are integral to sleep regulation. In the context of a healthy neural environment, these glial cells exert a profound influence on the sleep-wake cycle, modulating both rapid eye movement (REM) and non-REM sleep phases. However, emerging literature underscores perturbations in astrocytic function as potential etiological factors in sleep disorders, either as protopathy or comorbidity. As known, sleep disorders significantly increase the risk of neurodegenerative, cardiovascular, metabolic, or psychiatric diseases. Meanwhile, sleep disorders are commonly screened as comorbidities in various neurodegenerative diseases, epilepsy, and others. Building on existing research that examines the role of astrocytes in sleep disorders, this review aims to elucidate the potential mechanisms by which astrocytes influence sleep regulation and contribute to sleep disorders in the varied settings of brain diseases. The review emphasizes the significance of astrocyte-mediated mechanisms in sleep disorders and their associated comorbidities, highlighting the need for further research.

Rosai-Dorfman disease of the breast: a clinicoradiologic and pathologic study.

Rosai-Dorfman disease (RDD) is an uncommon histiocytic disorder typically involving lymph nodes and less frequently extranodal tissues. RDD involving the breast is rare and may clinically and radiologically mimic neoplastic and non-neoplastic disorders. We report seven patients with breast RDD, describe their clinicoradiologic and pathologic features, and discuss the differential diagnosis. Patients, ranging from 15 to 74 years of age, presented with unilateral and unifocal (5/7) or bilateral and multifocal (2/7) masses. RDD was either confined to the breast (6/7) or concurrently involved a lymph node (1/7). Masses ranged from 8 to 31 mm, categorized as Breast Imaging-Reporting and Data System (BI-RADS) 4 (6/7) or 5 (1/7). All cases showed similar morphology with many large histiocytes displaying emperipolesis with associated fibrosis and dense lymphoplasmacytic infiltrate. The abnormal histiocytes co-expressed CD68/CD163, S100, OCT2, and Cyclin D1 (7/7), and were negative for CK AE1/AE3 (7/7), CD1a (7/7), and BRAF V600E (6/6). Flow cytometry (n = 3), kappa/lambda in situ hybridization (n = 5), and IgG4/IgG immunohistochemistry (n = 1) did not reveal lymphoma or IgG4-related disease. No mycobacterial or fungal organisms were identified on acid-fast bacillus (AFB) and Grocott methenamine silver (GMS) stains (n = 5). Three patients underwent complete excision and none recurred or progressed to systemic disease during follow-up (88-151 months). In summary, breast RDD should be included in the differential diagnosis of a mass-forming breast lesion. Histopathology with ancillary studies and clinicoradiologic correlation is essential for accurate diagnosis and optimal clinical management. Patients with RDD of the breast have an excellent prognosis after complete excision.

A panel of seven protein tumour markers for effective and affordable multi-cancer early detection by artificial intelligence: a large-scale and multicentre case-control study.

Background: Early detection of cancer aims to reduce cancer deaths. Unfortunately, many established cancer screening technologies are not suitable for use in low- and middle-income countries (LMICs) due to cost, complexity, and dependency on extensive medical infrastructure. We aimed to assess the performance and robustness of a protein assay (OncoSeek) for multi-cancer early detection (MCED) that is likely to be more practical in LMICs. Methods: This observational study comprises a retrospective analysis on the data generated from the routine clinical testings at SeekIn and Sun Yat-sen Memorial Hospital. 7565 participants (954 with cancer and 6611 without) from the two sites were divided into training and independent validation cohort. The second validation cohort (1005 with cancer and 812 without) was from Johns Hopkins University School of Medicine. Patients with cancer prior to therapy were eligible for inclusion in the study. Individuals with no history of cancer were enrolled from the participating sites as the non-cancer group. One tube of peripheral blood was collected from each participant and quantified a panel of seven selected protein tumour markers (PTMs) by a common clinical electrochemiluminescence immunoassay analyser. An algorithm named OncoSeek was established using artificial intelligence (AI) to distinguish patients with cancer from those without cancer by calculating the probability of cancer (POC) index based on the quantification results of the seven PTMs and clinical information including sex and age of the individuals and to predict the possible affected tissue of origin (TOO) for those who have been detected with cancer signals in blood. Findings: Between November 2012 and May 2022, 7565 participants were enrolled at SeekIn and Sun Yat-sen Memorial Hospital. The conventional clinical method, which relies only on a single threshold for each PTM, would suffer from a high false positive rate that accumulates as the number of markers increased. OncoSeek was empowered by AI technology to significantly reduce the false positive rate, increasing the specificity from 56.9% (95% confidence interval [CI]: 55.8-58.0) to 92.9% (92.3-93.5). In all cancer types, the overall sensitivity of OncoSeek was 51.7% (49.4-53.9), resulting in 84.3% (83.5-85.0) accuracy. The performance was generally consistent in the training and the two validation cohorts. The sensitivities ranged from 37.1% to 77.6% for the detection of the nine common cancer types (breast, colorectum, liver, lung, lymphoma, oesophagus, ovary, pancreas, and stomach), which account for ∼59.2% of global cancer deaths annually. Furthermore, it has shown excellent sensitivity in several high-mortality cancer types for which routine screening tests are lacking in the clinic, such as the sensitivity of pancreatic cancer which was 77.6% (69.3-84.6). The overall accuracy of TOO prediction in the true positives was 66.8%, which could assist the clinical diagnostic workup. Interpretation: OncoSeek significantly outperforms the conventional clinical method, representing a novel blood-based test for MCED which is non-invasive, easy, efficient, and robust. Moreover, the accuracy of TOO facilitates the follow-up diagnostic workup. Funding: The National Key Research and Development Programme of China.

Postoperative short-term mortality between insulin-treated and non-insulin-treated patients with diabetes after non-cardiac surgery: a systematic review and meta-analysis.

Background: Diabetes mellitus is an independent risk factor for postoperative complications. It has been reported that insulin-treated diabetes is associated with increased postoperative mortality compared to non-insulin-treated diabetes after cardiac surgery; however, it is unclear whether this finding is applicable to non-cardiac surgery. Objective: We aimed to assess the effects of insulin-treated and non-insulin-treated diabetes on short-term mortality after non-cardiac surgery. Methods: Our study was a systematic review and meta-analysis of observational studies. PubMed, CENTRAL, EMBASE, and ISI Web of Science databases were searched from inception to February 22, 2021. Cohort or case-control studies that provided information on postoperative short-term mortality in insulin-treated diabetic and non-insulin-treated diabetic patients were included. We pooled the data with a random-effects model. The Grading of Recommendations, Assessment, Development, and Evaluation system was used to rate the quality of evidence. Results: Twenty-two cohort studies involving 208,214 participants were included. Our study suggested that insulin-treated diabetic patients was associated with a higher risk of 30-day mortality than non-insulin-treated diabetic patients [19 studies with 197,704 patients, risk ratio (RR) 1.305; 95% confidence interval (CI), 1.127 to 1.511; p < 0.001]. The studies were rated as very low quality. The new pooled result only slightly changed after seven simulated missing studies were added using the trim-and-fill method (RR, 1.260; 95% CI, 1.076-1.476; p = 0.004). Our results also showed no significant difference between insulin-treated diabetes and non-insulin-treated diabetes regarding in-hospital mortality (two studies with 9,032 patients, RR, 0.970; 95% CI, 0.584-1.611; p = 0.905). Conclusion: Very-low-quality evidence suggests that insulin-treated diabetes was associated with increased 30-day mortality after non-cardiac surgery. However, this finding is non-definitive because of the influence of confounding factors. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021246752, identifier: CRD42021246752.