[Clinical value of the implication of extracorporeal carbon dioxide removal in patients with acute respiratory distress syndrome]

Extracorporeal carbon dioxide removal (ECCO2R) is a respiratory support technique based on extra-pulmonary gas exchange, which can effectively remove carbon dioxide generated in-vivo, reducing the requirements of respiratory support from mechanical ventilation. With improvements in extracorporeal life support technologies and increasing clinical experience, ECCO2R has potential value in clinical application with acute respiratory distress syndrome (ARDS). This review article discusses the principles of ECCO2R, its relevant indications for ARDS, clinical evidence, existing issues, and future directions, aiming to provide more references for the application in ARDS.

Stem Cell-Based Strategies: The Future Direction of Bioartificial Liver Development

Acute liver failure (ALF) results from severe liver damage or end-stage liver disease. It is extremely fatal and causes serious health and economic burdens worldwide. Once ALF occurs, liver transplantation (LT) is the only definitive and recommended treatment; however, LT is limited by the scarcity of liver grafts. Consequently, the clinical use of bioartificial liver (BAL) has been proposed as a treatment strategy for ALF. Human primary hepatocytes are an ideal cell source for these methods. However, their high demand and superior viability prevent their widespread use. Hence, finding alternatives that meet the seed cell quality and quantity requirements is imperative. Stem cells with self-renewing, immunogenic, and differentiative capacities are potential cell sources. MSCs and its secretomes encompass a spectrum of beneficial properties, such as anti-inflammatory, immunomodulatory, anti-ROS (reactive oxygen species), anti-apoptotic, pro-metabolomic, anti-fibrogenesis, and pro-regenerative attributes. This review focused on the recent status and future directions of stem cell-based strategies in BAL for ALF. Additionally, we discussed the opportunities and challenges associated with promoting such strategies for clinical applications.

Exosome-transmitted FOSL1 from cancer-associated fibroblasts drives colorectal cancer stemness and chemo-resistance through transcriptionally activating ITGB4

Cancer-associated fibroblasts (CAFs) have been proved to facilitate colorectal cancer (CRC) development, either with boosting chemo-resistance by communicating with CRC cells in the tumor microenvironment. However, the underlying molecular mechanisms remain largely unclear. Relative expressions of FOSL1 and ITGB4, either with their correlations in CRC tissues, were assessed using qRT-PCR analysis. Also, Kaplan-Meier survival analysis was employed for evaluating the prognosis. Identification of CAFs was determined by the detection of specific makers (α-SMA, FAP, and FSP1) using western blot and immunofluorescence staining. Cell proliferation, self-renewal capacity, and cell apoptosis were estimated by CCK-8, sphere-formation, and flow cytometry assays. Transcriptional regulation of FOSL1 on integrin β4 (ITGB4) was confirmed using ChIP and dual-luciferase reporter assays. Increased FOSL1 and ITGB4 in CRC tissues were both positively correlated with the poor prognosis of CRC patients. Interestingly, FOSL1 was enriched in the CAFs isolated from CRC stroma, instead of ITGB4. CRC cells under a co-culture system with CAFs-conditioned medium (CAFs-CM) exhibited increased FOSL1, promotive cell proliferation, and reduced apoptosis, while these effects could be blocked by exosome inhibitor (GW4869). Moreover, CAFs-derived exosomal FOSL1 was validated to enhance proliferative ability and oxaliplatin resistance of CRC cells. Our results uncovered that CAFs-derived exosomes could transfer FOSL1 to CRC cells, thereby promoting CRC cell proliferation, stemness, and oxaliplatin resistance by transcriptionally activating ITGB4.

Comparing perioperative outcomes between regional anesthesia and general anesthesia in patients undergoing hip fracture surgery: a systematic review and meta-analysis

PURPOSE

Nearly all patients with hip fractures undergo surgical treatment. The use of different anesthesia techniques during surgery may influence the clinical outcomes. The optimal anesthetic technique for patients undergoing hip fracture surgery is still controversial. We performed this updated systematic review and meta-analysis to compare clinical outcomes of patients undergoing hip fracture surgery with different anesthesia techniques.

SOURCE

Articles published from 2000 to May 2023 were included from MEDLINE, Embase, Web of Science, and the Cochrane Library. We included randomized controlled trials and observational studies comparing general anesthesia (GA) with regional anesthesia (RA) for the outcomes of 30-day mortality, 90-day mortality, in-hospital mortality, perioperative complications, length of hospital stay, and length of surgery in patients undergoing hip fracture surgery. Subgroup analyses were performed for the outcomes based on study design (randomized controlled trials or observational studies). We used a random-effects model for all analyses.

PRINCIPAL FINDINGS

In this meta-analysis, we included 12 randomized controlled trials. There was no difference in postoperative 30-day mortality between the two groups (odds ratio [OR], 0.88; 95% confidence interval [CI], 0.44 to 1.74; I2 = 0%). The incidence of intraoperative hypotension was lower in patients who received RA vs GA (OR, 0.52; 95% CI, 0.38 to 0.72; I2 = 0%). No significant differences were observed in 90-day mortality, in-hospital mortality, postoperative delirium, pneumonia, myocardial infarction, venous thromboembolism, length of surgery, and length of hospital stay.

CONCLUSION

In this updated systematic review and meta-analysis, RA did not reduce postoperative 30-day mortality in hip fracture surgery patients compared to GA. Fewer patients receiving RA had intraoperative hypotension than those receiving GA did. Apart from intraoperative hypotension, the data showed no differences in complications between the two anesthetic techniques.

STUDY REGISTRATION

PROSPERO (CRD42023411854); registered 7 April 2023.

Membrane-Based Preparation Process and Antioxidant and Anti-AGEs Activities of a Novel Propolis Ultrafiltrate

Propolis is one functional supplement with hundreds of years of usage. However, it's rarely consumed directly for its resinous property. Herein, a pre-treated process which can remove the impurity while preserve its bioactivities is needed to maximise its therapeutic opportunities. In the present study, a membrane-based ultrafiltration process was developed on a KM1812-NF experimental instrument. Using Brazilian green propolis as testing material, all experimental steps and parameters were sequentially optimized. In addition, a mathematical model was developed to fit the process. As a result, the optimum solvent was 60 % ethanol adjusted to pH 8-9, while the optimum MWCO (molecular weight cut-off) value of membrane was 30 KDa. The membrane filtration dynamic model fitted with the function y=(ax+b)/(1+cx+dx2 ). The resulting propolis ultrafiltrate from Brazilian green propolis, termed P30K, contains the similar profile of flavonoids and phenolic acids as raw propolis. Meanwhile, the ORAC (oxygen radical absorbance capacity) value of P30K is 11429.45±1557.58 μM TE/g and the IC50 value of inhibition of fluorescent AGEs (advanced glycation end products) formation is 0.064 mg/mL. Our work provides an innovative alternative process for extraction of active compounds from propolis and reveals P30K as an efficient therapeutic antioxidant.

Our experience diagnosing 225 patients with cervical glandular lesions: current technologies, lessons learned, and areas for improvement

OBJECTIVE

To explore the relative sensitivity of different methods for detecting cervical glandular lesions.

METHODS

A total of 225 patients with cervical glandular lesions diagnosed from January 2018 to February 2023 were retrieved from the pathology database of Guangdong Maternal and Child Health Hospital, and their clinicopathological features were reviewed.

RESULTS

Four human papillomavirus (HPV) genotypes: HPV18, 16, 45, and 52, dominated all glandular lesions, and accounting for 74.10% of HPV-positive tumors. Furthermore, 36.89% of abnormal squamous cells were diagnosed as abnormal based on cytological examinations leading to the detection of cervical glandular lesions; only 16.89% were diagnosed based on the initial detection of abnormal glandular cytology. The most common abnormal cervical screening result was ASC-US on cytology (14.22%), followed by HSIL (11.56%). Only few number of patients were diagnosed with or suspected of having cervical adenopathy via a Pap test (18.22%). Nearly one-third of cervical glandular lesions cases were not detected on the Pap test; but were diagnosed upon cervical biopsy or based on the histological examination of ECC, LEEP, or CKC specimens. The LEEP or CKC biopsy specimens had negative margins in 49 cases (40.83%), while the margins were positive in the other 71 cases (59.17%). Five cases (10.20%) with negative margins still had residual lesions following total hysterectomy, and 19 (26.76%) with positive margins had no residual lesions after total hysterectomy.

CONCLUSION

The ability to detect cervical glandular lesions varies for routine HPV genotyping, Pap test, or biopsy/ECC, with different sensitivities and advantages and disadvantages for each method.

Pre-hospital symptom clusters and symptom network analysis in decompensated cirrhotic patients: A cross-sectional study

AIMS

To generate pre-hospital symptom networks, explore core, bridge and sentinel symptoms, identify pre-hospital symptom clusters and analyse relationship between influencing factors and symptom clusters in decompensated cirrhosis patients.

DESIGN

A cross-sectional study design using the Strengthening the Reporting of Observational Studies in Epidemiology checklist.

METHODS

Demographical, physiological, psychological and sociological characteristics and the pre-hospital symptoms of 292 decompensated cirrhotic patients were collected from October 2021 to March 2023 in China. Frequencies, percentages, means, standard deviations, independent samples t-tests, one-way analysis of variance, exploratory factor analysis, multiple stepwise regression analysis and network analysis were used for data analysis.

RESULTS

'I don't look like myself' and itching were core and bridge symptoms, while bloating and lack of energy were sentinel symptoms in decompensated cirrhotic patients. Monthly family income, anxiety, depression, social support and disease duration influenced the neuropsychological symptom cluster, with worrying as the strongest predictor symptom. Influential factors for cirrhosis-specific symptom cluster included Child-Pugh class, monthly family income, disease duration, anxiety and depression, with itching being the strongest predictor symptom. Monthly family income, disease duration and depression were influential factors for gastrointestinal symptom cluster, with loss of appetite as the strongest predictor symptom.

CONCLUSIONS

Neuropsychological, cirrhosis-specific and gastrointestinal symptom clusters were formed in decompensated cirrhotic patients. Through network analysis, direct connections between symptoms, symptom clusters and their influencing factors were revealed, thereby offering clinicians a foundation for effectively managing patients' pre-hospital symptoms.

IMPACT

Decompensated cirrhosis patients commonly have multiple symptoms, while the management of pre-hospital symptoms is often suboptimal. This study identified neuropsychological, cirrhosis-specific, gastrointestinal symptom clusters and recognized core, bridge and sentinel symptoms in these patients. It also revealed the most prominent symptoms within each cluster. This provides insight into the hierarchy of symptoms, improving symptom management in decompensated cirrhosis.

PATIENT AND PUBLIC INVOLVEMENT

There was no patient or public involvement.

Adipose-derived Mesenchymal Stem Cells are Ideal for the Cell-based Treatment of Refractory Wounds: Strong Potential for Angiogenesis

Although Mesenchymal Stem Cells (MSCs)-based therapy has been proposed as a promising strategy for the treatment of chronic lower-extremity ulcers, their optimal sources, amounts, and delivery methods are urgently needed to be determined. In this study, we compared the heterogeneity of the human MSCs derived from bone marrow (BMSCs), umbilical cord (UCMSCs), and adipose tissue (ADSCs) in accelerating wound healing and promoting angiogenesis and explored the underlying mechanism. Briefly, a diabetic rat model with a full-thickness cutaneous wound on the dorsal foot was developed. The wound was topically administered with three types of MSCs. Additionally, we carried out in vitro and in vivo analysis of the angiogenic properties of the MSCs. Moreover, the molecular mechanism of the heterogeneity of the MSCs derived from the three tissues was explored by transcriptome sequencing. When compared with the BMSCs- and UCMSCs-treated groups, the ADSCs-treated group exhibited markedly accelerated healing efficiency, characterized by increased wound closure rates, enhanced angiogenesis, and collagen deposition at the wound site. The three types of MSCs formed three-dimensional capillary-like structures and promoted angiogenesis in vitro and in vivo, with ADSCs exhibiting the highest capacity for tube formation and pro-angiogenesis. Furthermore, transcriptome sequencing revealed that ADSCs had higher expression levels of angiogenesis-associated genes. Our findings indicate that MSCs-based therapy accelerates the healing of ischemia- and diabetes-induced lower-extremity ulcers and that adipose tissue-derived MSCs might be ideal for therapeutic angiogenesis and treatment of chronic ischemic wounds.

Radiomics Nomogram with Added Nodal Features Improves Treatment Response Prediction in Locally Advanced Esophageal Squamous Cell Carcinoma: A Multicenter Study

OBJECTIVE

We aimed to develop and validate a radiomics nomogram and determine the value of radiomic features from lymph nodes (LNs) for predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced esophageal squamous cell carcinoma (ESCC).

METHODS

In this multicenter retrospective study, eligible participants who had undergone NCRT followed by radical esophagectomy were consecutively recruited. Three radiomics models (modelT, modelLN, and modelTLN) based on tumor and LN features, alone and combined, were developed in the training cohort. The radiomics nomogram was developed by incorporating the prediction value of the radiomics model and clinicoradiological risk factors using multivariate logistic regression, and was evaluated using the receiver operating characteristic curve, validated in two external validation cohorts.

RESULTS

Between October 2011 and December 2018, 116 patients were included in the training cohort. Between June 2015 and October 2020, 51 and 27 patients from two independent hospitals were included in validation cohorts 1 and 2, respectively. The radiomics modelTLN performed better than the radiomics modelT for predicting pCR. The radiomics nomogram incorporating the predictive value of the radiomics modelTLN and heterogeneous after NCRT outperformed the clinicoradiological model, with an area under the curve (95% confidence interval) of 0.833 (0.765-0.894) versus 0.764 (0.686-0.833) [p = 0.088, DeLong test], 0.824 (0.718-0.909) versus 0.692 (0.554-0.809) [p = 0.012], and 0.902 (0.794-0.984) versus 0.696 (0.526-0.857) [p = 0.024] in all three cohorts.

CONCLUSIONS

Radiomic features from LNs could provide additional value for predicting pCR in ESCC patients, and the radiomics nomogram provided an accurate prediction of pCR, which might aid treatment decision.

Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures

BACKGROUND

Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic-MRI and DLR features can more accurately distinguish GBM from SBM remains uncertain.

PURPOSE

To construct and validate a demographic-MRI deep-learning radiomics nomogram (DDLRN) integrating demographic-MRI and DLR signatures to differentiate GBM from SBM preoperatively.

STUDY TYPE

Retrospective.

POPULATION

Two hundred and thirty-five patients with GBM (N = 115) or SBM (N = 120), randomly divided into a training cohort (90 GBM and 98 SBM) and a validation cohort (25 GBM and 22 SBM).

FIELD STRENGTH/SEQUENCE

Axial T2-weighted fast spin-echo sequence (T2WI), T2-weighted fluid-attenuated inversion recovery sequence (T2-FLAIR), and contrast-enhanced T1-weighted spin-echo sequence (CE-T1WI) using 1.5-T and 3.0-T scanners.

ASSESSMENT

The demographic-MRI signature was constructed with seven imaging features ("pool sign," "irregular ring sign," "regular ring sign," "intratumoral vessel sign," the ratio of the area of peritumoral edema to the enhanced tumor, the ratio of the lesion area on T2-FLAIR to CE-T1WI, and the tumor location) and demographic factors (age and sex). Based on multiparametric MRI, radiomics and deep-learning (DL) models, DLR signature, and DDLRN were developed and validated.

STATISTICAL TESTS

The Mann-Whitney U test, Pearson test, least absolute shrinkage and selection operator, and support vector machine algorithm were applied for feature selection and construction of radiomics and DL models.

RESULTS

DDLRN showed the best performance in differentiating GBM from SBM with area under the curves (AUCs) of 0.999 and 0.947 in the training and validation cohorts, respectively. Additionally, the DLR signature (AUC = 0.938) outperformed the radiomics and DL models, and the demographic-MRI signature (AUC = 0.775) was comparable to the T2-FLAIR radiomics and DL models in the validation cohort (AUC = 0.762 and 0.749, respectively).

DATA CONCLUSION

DDLRN integrating demographic-MRI and DLR signatures showed excellent performance in differentiating GBM from SBM.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Brain tumor image segmentation based on improved FPN

PURPOSE

Automatic segmentation of brain tumors by deep learning algorithm is one of the research hotspots in the field of medical image segmentation. An improved FPN network for brain tumor segmentation is proposed to improve the segmentation effect of brain tumor.

MATERIALS AND METHODS

Aiming at the problem that the traditional full convolutional neural network (FCN) has weak processing ability, which leads to the loss of details in tumor segmentation, this paper proposes a brain tumor image segmentation method based on the improved feature pyramid networks (FPN) convolutional neural network. In order to improve the segmentation effect of brain tumors, we improved the model, introduced the FPN structure into the U-Net structure, captured the context multi-scale information by using the different scale information in the U-Net model and the multi receptive field high-level features in the FPN convolutional neural network, and improved the adaptability of the model to different scale features.

RESULTS

Performance evaluation indicators show that the proposed improved FPN model has 99.1% accuracy, 92% DICE rating and 86% Jaccard index. The performance of the proposed method outperforms other segmentation models in each metric. In addition, the schematic diagram of the segmentation results shows that the segmentation results of our algorithm are closer to the ground truth, showing more brain tumour details, while the segmentation results of other algorithms are smoother.

CONCLUSIONS

The experimental results show that this method can effectively segment brain tumor regions and has certain generalization, and the segmentation effect is better than other networks. It has positive significance for clinical diagnosis of brain tumors.

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes

OBJECTIVES

Using contrast-enhanced computed tomography (CECT) and deep learning technology to develop a deep learning radiomics nomogram (DLRN) to preoperative predict risk status of patients with thymic epithelial tumors (TETs).

METHODS

Between October 2008 and May 2020, 257 consecutive patients with surgically and pathologically confirmed TETs were enrolled from three medical centers. We extracted deep learning features from all lesions using a transformer-based convolutional neural network and created a deep learning signature (DLS) using selector operator regression and least absolute shrinkage. The predictive capability of a DLRN incorporating clinical characteristics, subjective CT findings and DLS was evaluated by the area under the curve (AUC) of a receiver operating characteristic curve.

RESULTS

To construct a DLS, 25 deep learning features with non-zero coefficients were selected from 116 low-risk TETs (subtypes A, AB, and B1) and 141 high-risk TETs (subtypes B2, B3, and C). The combination of subjective CT features such as infiltration and DLS demonstrated the best performance in differentiating TETs risk status. The AUCs in the training, internal validation, external validation 1 and 2 cohorts were 0.959 (95% confidence interval [CI]: 0.924-0.993), 0.868 (95% CI: 0.765-0.970), 0.846 (95% CI: 0.750-0.942), and 0.846 (95% CI: 0.735-0.957), respectively. The DeLong test and decision in curve analysis revealed that the DLRN was the most predictive and clinically useful model.

CONCLUSIONS

The DLRN comprised of CECT-derived DLS and subjective CT findings showed a high performance in predicting risk status of patients with TETs.

CLINICAL RELEVANCE STATEMENT

Accurate risk status assessment of thymic epithelial tumors (TETs) may aid in determining whether preoperative neoadjuvant treatment is necessary. A deep learning radiomics nomogram incorporating enhancement CT-based deep learning features, clinical characteristics, and subjective CT findings has the potential to predict the histologic subtypes of TETs, which can facilitate decision-making and personalized therapy in clinical practice.

KEY POINTS

• A non-invasive diagnostic method that can predict the pathological risk status may be useful for pretreatment stratification and prognostic evaluation in TET patients. • DLRN demonstrated superior performance in differentiating the risk status of TETs when compared to the deep learning signature, radiomics signature, or clinical model. • The DeLong test and decision in curve analysis revealed that the DLRN was the most predictive and clinically useful in differentiating the risk status of TETs.

The effect of perioperative diuretic administration on acute kidney injury in patients with acute myocardial infarction after percutaneous coronary intervention: a real-world retrospective study

PURPOSE

The relationship between diuretic use and contrast-induced acute kidney injury (CI-AKI) after contrast exposure remains unclear. In this study, we conducted a retrospective analysis using propensity score matching (PSM) to investigate the effect of perioperative diuretic administration on contrast-induced acute kidney injury (CI-AKI) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI).

METHODS

A total of 1894 patients with AMI who underwent PCI were retrospectively analyzed using PSM and multivariate models. Depending on whether diuretics were used, the patients were divided into two groups: the perioperative diuretic group (497 patients, 26.2%) and the non-diuretic group (1397 patients, 73.8%). And the relationship between perioperative diuretic administration and CI-AKI was evaluated by multiple regression models. Furthermore, Kaplan Meier survival curve ratio was used to evaluate and compare overall postoperative survival between the two groups.

RESULTS

Most patients who received diuretics were older (67 vs. 60 years, respectively, p < 0.001) and women (22.5% vs. 15.2%, p < 0.001) and had combined hypertension (62.8% vs. 47%, p < 0.001), atrial fibrillation (5.4% vs. 1.8%, p < 0.001), stroke (9.3% vs. 4.9%, p < 0.001), and diabetes mellitus (33.4% vs. 23.6%, p < 0.001) compared to those who did not. After the baseline characteristics were balanced using the PSM model, no significant difference was observed in the incidence of postoperative CI-AKI (22.7% vs. 19.5%, p = 0.356) and major cardiovascular adverse events (21.5% vs. 18.7%, p = 0.398). Multiple regression analysis showed no association between perioperative diuretic administration and postoperative CI-AKI occurrence (odds ratio: 1.14, 95% confidence interval: 0.86-1.51, p = 0.371). Further subgroup analysis and sensitivity analysis confirmed the above findings.

CONCLUSION

We found no significant association between perioperative diuretic administration and postoperative CI-AKI in patients with AMI who underwent PCI.

Single-cell RNA-seq and bulk-seq identify RAB17 as a potential regulator of angiogenesis by human dermal microvascular endothelial cells in diabetic foot ulcers

Background

Angiogenesis is crucial in diabetic wound healing and is often impaired in diabetic foot ulcers (DFUs). Human dermal microvascular endothelial cells (HDMECs) are vital components in dermal angiogenesis; however, their functional and transcriptomic characteristics in DFU patients are not well understood. This study aimed to comprehensively analyse HDMECs from DFU patients and healthy controls and find the potential regulator of angiogenesis in DFUs.

Methods

HDMECs were isolated from skin specimens of DFU patients and healthy controls via magnetic-activated cell sorting. The proliferation, migration and tube-formation abilities of the cells were then compared between the experimental groups. Both bulk RNA sequencing (bulk-seq) and single-cell RNA-seq (scRNA-seq) were used to identify RAB17 as a potential marker of angiogenesis, which was further confirmed via weighted gene co-expression network analysis (WGCNA) and least absolute shrink and selection operator (LASSO) regression. The role of RAB17 in angiogenesis was examined through in vitro and in vivo experiments.

Results

The isolated HDMECs displayed typical markers of endothelial cells. HDMECs isolated from DFU patients showed considerably impaired tube formation, rather than proliferation or migration, compared to those from healthy controls. Gene set enrichment analysis (GSEA), fGSEA, and gene set variation analysis (GSVA) of bulk-seq and scRNA-seq indicated that angiogenesis was downregulated in DFU-HDMECs. LASSO regression identified two genes, RAB17 and CD200, as characteristic of DFU-HDMECs; additionally, the expression of RAB17 was found to be significantly reduced in DFU-HDMECs compared to that in the HDMECs of healthy controls. Overexpression of RAB17 was found to enhance angiogenesis, the expression of hypoxia inducible factor-1α and vascular endothelial growth factor A, and diabetic wound healing, partially through the mitogen-activated protein kinase/extracellular signal-regulated kinase signalling pathway.

Conclusions

Our findings suggest that the impaired angiogenic capacity in DFUs may be related to the dysregulated expression of RAB17 in HDMECs. The identification of RAB17 as a potential molecular target provides a potential avenue for the treatment of impaired angiogenesis in DFUs.

Inflammatory mechanisms and intervention strategies for sepsis-induced myocardial dysfunction

Sepsis-induced myocardial dysfunction (SIMD) is the leading cause of death in patients with sepsis in the intensive care units. The main manifestations of SIMD are systolic and diastolic dysfunctions of the myocardium. Despite our initial understanding of the SIMD over the past three decades, the incidence and mortality of SIMD remain high. This may be attributed to the large degree of heterogeneity among the initiating factors, disease processes, and host states involved in SIMD. Previously, organ dysfunction caused by sepsis was thought to be an impairment brought about by an excessive inflammatory response. However, many recent studies have shown that SIMD is a consequence of a combination of factors shaped by the inflammatory responses between the pathogen and the host. In this article, we review the mechanisms of the inflammatory responses and potential novel therapeutic strategies in SIMD.

TLR-4 targeting contributes to the recovery of osteoimmunology in periodontitis

OBJECTIVE

The aim of this study was to determine the potential role of TLR-4 in the osteoimmunological imbalance of periodontitis.

BACKGROUND

Although current evidence supports that TLR-4 plays an important role in the inflammatory response of periodontal tissues triggered by microorganisms, little information is available regarding the function of TLR-4 in the osteoimmune regulation of homeostasis in periodontitis.

METHODS

Human gingival epithelial cells (HGEC) were isolated from the gingival tissues of 3 healthy volunteers and the expression of osteoclastogenic cytokines was evaluated by ELISA and real time RT-PCR. In addition, 30 C57BL/6 mice were used and randomly divided into three groups: control group, periodontitis group (CP) and periodontitis+TAK-242 (a specific inhibitor of TLR-4) group (TAK-242) and the expression of osteoclastogenic cytokines and the osteoclast density in the periodontal tissue were evaluated by immunohistochemical staining and tartrate resistant acid phosphatase staining. Moreover, micro-computed tomography (Micro-CT) was used to assess bone resorption.

RESULTS

The in vitro results showed that TAK-242 blocked the overproduction of IL-1, IL-6, TNF-α and RANKL in HGEC treated with LPS. The in vivo results revealed that TAK-242 also effectively decreased these osteoclastogenic cytokines in periodontal tissue of mice with periodontitis. More importantly, Micro-CT analysis showed a significant reduction of the alveolar bone loss in the TAK-242 group compared with the CP group. Furthermore, the TRAP staining showed a significant lower density of osteoclasts in the alveolar bone area of the TAK-242 group.

CONCLUSION

TLR-4 inhibition decreased the differentiation of osteoclast through the inhibition of the overproduction of osteoclastogenic cytokines and the prevention of the alveolar bone absorption in mouse periodontitis models. Therefore, the use of TAK-242 might contribute to the recovery of the osteoimmunological homeostasis and might provide a potential strategy to treat periodontal diseases.

Association of TG/HDLC ratio trajectory and risk of type 2 diabetes: A retrospective cohort study in China

BACKGROUND

The association of ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-C ratio) change trajectory with risk of type 2 diabetes mellitus (T2DM) remains unknown. The aim of this study was to evaluate the association between risk of T2DM and TG/HDL-C ratio change trajectory.

METHODS

A total of 18 444 participants aged 18-80 years old were included in this cohort study. Linear regression and quadratic regression models were used to determine the TG/HDL-C ratio change trajectory. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between TG/HDL-C ratio change trajectory and probability of T2DM.

RESULTS

T2DM developed in 714 participants during a median follow-up of 5.74 years (92 076.23 person-years of follow-up). After adjusting for baseline potential confounders, odds of T2DM were greater for participants with the increasing, U-shape, bell-shape, and other shape change vs decreasing change (adjusted OR [aOR] 2.01, 95% CI 1.42-2.81; 1.56, 1.15-2.13; 1.60, 1.17-2.20; and 1.49, 1.13-2.00, respectively). The results were robust in the sensitivity analyses on excluding baseline participants with T2DM. Moreover, the associations remained significant with male sex, age <60 years and body mass index <24 kg/m2 .

CONCLUSIONS

This retrospective study revealed increased probability of T2DM with increasing, U-shape, bell-shape, and other-shape TG/HDL-C ratio change trajectories, especially with male sex, age <60 years and body mass index <24 kg/m2 .

Association of total sedentary behaviour and television viewing with risk of overweight/obesity, type 2 diabetes and hypertension: A dose-response meta-analysis

AIMS

To explore the quantitative dose-response association of total sedentary behaviour and television viewing with overweight/obesity, type 2 diabetes and hypertension in a meta-analysis.

MATERIALS AND METHODS

We searched three databases to identify English-language reports that assessed the association of total sedentary behaviour or television viewing with the aforementioned health outcomes. Restricted cubic splines were used to evaluate possible linear or non-linear associations of total sedentary behaviour and television viewing with these health outcomes.

RESULTS

We included 48 articles (58 studies) with a total of 1 071 967 participants in the meta-analysis; 21 (six cohort and 15 cross-sectional) studies examined the association of total sedentary behaviour with overweight/obesity, 23 (13 cohort and 10 cross-sectional) studies examined the association with type 2 diabetes and 14 (one cohort and 13 cross-sectional) studies examined the association with hypertension. We found linear associations between total sedentary behaviour and type 2 diabetes (P_{non-linearity} = 0.190) and hypertension (P_{non-linearity} = 0.225) and a non-linear association between total sedentary behaviour and overweight/obesity (P_{non-linearity} = 0.003). For each 1-h/d increase in total sedentary behaviour, the risk increased by 5% for type 2 diabetes and 4% for hypertension. We also found linear associations between television viewing and type 2 diabetes (P_{non-linearity} = 0.948) and hypertension (P_{non-linearity} = 0.679) and a non-linear association for overweight/obesity (P_{non-linearity} = 0.007). For each 1-h/d increase in television viewing, the risk increased by 8% for type 2 diabetes and 6% for hypertension.

CONCLUSIONS

High levels of total sedentary behaviour and television viewing were associated with overweight/obesity, type 2 diabetes and hypertension.

Effect of Subjective and Objective Sleep Quality on Subsequent Peptic Ulcer Recurrence in Older Adults

OBJECTIVE

To examine the effect of subjective and objective sleep quality on subsequent recurrence of peptic ulcer disease (PUD) among older patients after Helicobacter pylori eradication.

SETTING

Eight grade A hospitals in China.

PARTICIPANTS

Of 1689 older Chinese with H. pylori-infected PUD recruited between January 2011 and October 2014, H. pylori were eradicated and PUD was cleared in 1538 patients by the end of 2014; 1420 of these patients were followed up for up to 36 months.

MEASUREMENTS

Using multiple measures at 6-month intervals, PUD recurrence was determined with esophagogastroduodenoscopy. Subjective sleep quality was measured using the Pittsburgh Sleep Quality Index. Objective sleep quality domains were measured using an accelerometer, including sleep onset latency, sleep efficiency, total sleep time, and number of awakenings.

RESULTS

This study documented a 36-month cumulative PUD recurrence of 8.3% (annual rate = 2.8%). Multivariate analyses showed that participants who reported poorer sleep quality were more likely to experience PUD recurrence during the 36-month follow-up period (hazard ratio [HR] = 1.895; 95% confidence interval [CI] = 1.008-3.327). Regarding objective sleep quality domains, longer sleep onset latency (HR = 1.558; 95% CI = 1.156-2.278) and more nighttime awakenings (HR = 1.697; 95% CI = 1.168-2.665) increased the risk of PUD recurrence. However, a longer total sleeping time protected against PUD recurrence (HR = 0.768; 95% CI = 0.699-0.885).

CONCLUSIONS

Poor sleep quality predicts a greater risk of PUD recurrence. Accurate diagnosis and effective treatments should, therefore, be provided for older adults afflicted with poor sleep, particularly for those who previously had PUD. It is equally important to include sleep assessment as an integral part while dealing with these patients.

Cohort study to determine the waist circumference cutoffs for predicting type 2 diabetes mellitus in rural China

BACKGROUND

Limited information is available on the cutoffs of waist circumference (WC) for predicting type 2 diabetes mellitus (T2DM). We aimed to define the optimal WC cutoffs for predicting T2DM among rural Chinese people.

METHODS

A cohort of 11 968 participants (732 new-onset T2DM) from a rural area in China with age 18 to 87 years was established at baseline during July to August of 2007 and 2008 and followed up during July to August of 2013 and 2014. Scatterplot, X-tile plot, and receiver operating characteristic (ROC) curve analyses were used to determine WC cutoffs for predicting T2DM.

RESULTS

The WC cutoffs for males and females were 84 and 86 cm (scatterplot), 83 and 88 cm (X-tile plot), and 87 and 88 cm (ROC curve). According to the highest risk score, the optimal WC cutoffs were 87 cm for males and 88 cm for females. With the optimal WC cutoffs, the sensitivity, specificity, positive likelihood ratio, area under the ROC curve, and population-attributable risk proportions were 67.9%, 67.0%, 2.06%, 0.70%, and 46%, respectively, for males and 52.5%, 75.0%, 2.10%, 0.69%, and 34%, respectively, for females; the corresponding adjusted hazard ratio for WC predicting T2DM was 3.66 (95% confidence interval 2.80-4.78) for males and 2.55 (2.08-3.12) for females.

CONCLUSIONS

The optimal WC cutoffs for predicting T2DM were similar between males and females. As well, the criteria of WC for central obesity are no longer practical for predicting T2DM.