Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer.

BACKGROUND: Liver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. Nevertheless, there is still no effective model to predict the risk of LM in T1 CRC patients. Hence, we aim to construct an accurate predictive model and an easy-to-use tool clinically. METHODS: We integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER, training dataset) and Xijing hospital (testing dataset). Artificial intelligence (AI) and machine learning (ML) methods were adopted to establish the predictive model. RESULTS: A total of 16,785 and 326 T1 CRC patients from SEER database and Xijing hospital were incorporated respectively into the study. Every single ML model demonstrated great predictive capability, with an area under the curve (AUC) close to 0.95 and a stacking bagging model displaying the best performance (AUC = 0.9631). Expectedly, the stacking model exhibited a favorable discriminative ability and precisely screened out all eight LM cases from 326 T1 patients in the outer validation cohort. In the subgroup analysis, the stacking model also demonstrated a splendid predictive ability for patients with tumor size ranging from one to50mm (AUC = 0.956). CONCLUSION: We successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in the external dataset. Ultimately, we designed a novel and easy-to-use decision tree, which only incorporated four fundamental parameters and could be successfully applied in clinical practice.

The differentiation of colorectal cancer is closely relevant to m6A modification.

The occurrence and development of tumors cannot be separated from the influence of differentiation at different stages and levels. Our study found that E-cadherin was significantly increased in cell model induced by sodium butyrate and cell density, while METTL3, METTL16 and WTAP were decreased during the differentiation of cells. In the clinicopathological tissues, E-cadherin was low expressed in poorly differentiated tumor tissues and above three regulators were highly expressed in poorly differentiated tissues. At the levels of clinicopathological differentiation, tissue differentiation and cell differentiation, the result indicated that the poor prognosis of colorectal cancer (CRC) may be closely related to high expression of total m6A level and high expression of METTL3, METTL16 and WTAP.

Cryptotanshinone inhibits prostaglandin E2 production and COX-2 expression via suppression of TLR4/NF-κB signaling pathway in LPS-stimulated Caco-2 cells.

Crytotanshinone (CTN), one of the main constituents of Salvia miltiorrhiza, has been known to exhibit antioxdative, anti-inflammatory and other important therapeutic activities. The aim of this study was to evaluate the effect of CTN on prostaglandin E2 and COX-2 production in LPS-stimulated human intestinal cells (Caco-2 cells). Caco-2 cells were stimulated with LPS in the presence or absence of CTN. The production of prostaglandin E2 (PGE2) was detected by ELISA. The expression of COX-2 was detected by qRT-PCR and Western blot. The extent of phosphorylation of IκB-α, NF-κB p65 and the expression of TLR4 were detected by western blot. The results showed that CTN dose-dependently inhibited the expression of COX-2 both in mRNA and protein levels, resulting in a decreased production of PGE2. We also found that CTN suppressed LPS-induced NF-κB activation and IκBα degradation. Furthermore, CTN inhibited the expression of TLR4 up-regulated by LPS. These results suggest that CTN exerts an anti-inflammatory property by inhibiting TLR4/NF-κB signaling pathway and the release of pro-inflammatory mediators. These findings suggest that CTN may be a therapeutic agent against intestinal inflammatory diseases.

Effects of alliin on LPS-induced acute lung injury by activating PPARγ.

Alliin is a garlic organosulfur compound that possesses various pharmacological properties. In the present study, the protective effects and molecular mechanism of alliin on Lipopolysaccharides (LPS)-induced acute lung injury (ALI) were analyzed. LPS-induced ALI was induced in BALB/c mice by intranasal instillation of LPS. Alliin was administered intraperitoneally to mice 1 h after LPS treatment. The results showed that alliin markedly inhibited lung myeloperoxidase (MPO) activity and wet/dry (W/D) ratio induced by LPS. Alliin also inhibited TNF-α and IL-1ß in the bronchoalveolar lavage fluid (BALF) induced by LPS. Furthermore, LPS-induced lung pathological injury was attenuated by treatment of alliin. LPS-induced NF-κB activation was significantly inhibited by alliin. In addition, the expression of peroxisome proliferator-activated receptor γ (PPARγ) was up-regulated by treatment of alliin. Taken together, these results suggested that alliin protected against LPS-induced ALI by activating PPARγ, which subsequently inhibited LPS-induced NF-κB activation and inflammatory response. Alliin might be used as an anti-inflammatory agent in the treatment of ALI.

Exploring hospital resilience protective or risk factors: lessons for future disaster response efforts.

Background: Hospital resilience is essential in responding to disasters, but current research focuses mainly on frameworks and models rather than the protection of resilience and analysis of risk factors during public health emergencies. This study aims to examine the development of resilience in Chinese frontline hospitals during the initial COVID-19 outbreak in 2020, providing insights for future disaster response efforts. Objectives: We conducted interviews with 26 hospital staff members who were involved in the initial response to the COVID-19 outbreak in China. We used a semi-structured interview approach and employed purposive sampling and snowball sampling techniques. The interview outline was guided by the 'Action Framework' proposed by the World Health Organization (WHO) for responding to infectious disease emergencies. This framework includes dimensions such as command, surveillance, risk communication, medical response, and public health response. We analyzed the collected data using Colaizzi's seven-step data analysis method and the template analysis method. Results: WHO's 'action framework' effectively highlights the factors that contribute to hospital resilience. While medical response, including the availability of materials and facilities, the use of information technology, and the capacity for infectious disease diagnosis and treatment, remains crucial, other important aspects include awareness and beliefs about infections, treatment experience, interdisciplinary collaboration, and more. Additionally, it is essential to establish an intelligent command system, foster trusting partnerships between teams, improve monitoring capabilities for infectious disease agents, enhance risk communication through information synchronization and transparency, strengthen infection control planning, and improve environmental disinfection capabilities for effective public health emergency response. These contradictions significantly impact the enhancement of hospital resilience in dealing with major infectious disease outbreaks. Conclusion: In responding to sudden major infectious diseases, hospitals play a vital role within the healthcare system. Enhancing hospital resilience involves more than just improving treatment capabilities. It also requires effective command coordination at the hospital level, infection control planning, and the deployment of intelligent equipment. Additionally, planning for effective communication and coordination between hospitals, communities, and the national healthcare system can further enhance hospital resilience.

Insight into modified CeMn based catalysts for efficient degradation of toluene by in situ infrared.

Trace activated carbon (AC) and diatomaceous earth (DE) were used as structural promoters to be incorporated into Ce-Mn-based solid-solution catalysts by the redox precipitation method. The modified catalysts exhibit superior reducibility, with abundant Ce3+, Mn3+and reactive oxygen species, which are facilitated to the migration of oxygen and the generation of oxygen vacancies. In particular, the catalytic combustion temperatures of 90 % toluene (3000 ppm) on Ce1Mn3Ox-AC/DE were 84 °C (dry) and 123 °C (10 vol% H2O), respectively. The role of lattice oxygen and adsorbed oxygen was revealed by in situ DRIFTS. Additionally, in situ DRIFTS was employed to verify that the degradation of toluene by Ce1Mn3Ox-AC/DE satisfied the Langmuir-Hinshelwood (L-H) mechanism and the Mars-Van Krevelen (MvK) mechanism. The possible reaction pathway was elucidated (toluene → benzyl alcohol → benzoic acid → maleic anhydride → CO2 + H2O). Furthermore, final products attributed to toluene oxidation were detected by in situ DRIFTS at 50 °C in the absence of oxygen, confirming that the catalyst possessed outstanding performance at low temperatures beyond mere adsorption.

Identification of a hypoxia-related gene prognostic signature in colorectal cancer based on bulk and single-cell RNA-seq.

Colorectal cancer (CRC) is the most common and fatal tumor in the gastrointestinal system. Its incidence and mortality rate have increased in recent years. Hypoxia, a persistent physiological tumor feature, plays a vital role in CRC tumorigenesis, metastasis, and tumor microenvironment (TME). Therefore, we constructed a hypoxia-related gene (HRG) nomogram to predict overall survival (OS) and explored the role of HRGs in the CRC TME. The Cancer Genome Atlas (TCGA) dataset was used as the training set, and two Gene Expression Omnibus datasets (GSE39582 and GSE103479) were used as the testing sets. HRGs were identified using the Gene Set Enrichment Analysis (GSEA) database. An HRG prognostic model was constructed in the training set using the least absolute shrinkage and selection operator regression algorithm and validated in the testing sets. Then, we analyzed tumor-infiltrating cells (TICs) using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. Furthermore, single-cell next-generation RNA sequencing (RNA-seq) was used to investigate HRG expression in different TICs in the GSE139555 dataset. Finally, reverse transcription polymerase chain reactions (RT-PCR) were used to validate HRG mRNA expression in ten pairs of CRC normal and cancer tissue samples. A six HRG prognostic signature was constructed, with a superior OS prediction ability in CRC patients (area under the receiver operating characteristic curve (AUC) at one year: 0.693, AUC at three years: 0.712, and AUC at five years: 0.780). GSEA enrichment analysis identified six pathways enriched in the high-risk group. The TIC analysis indicated that the high-risk group had lower T-cell expression and higher neutrophil expression than the low-risk group. Furthermore, immune-related genes had an inseparable relationship with the HRG prognostic signature. Based on single-cell RNA-seq data, we found elevated hexokinase 1 (HK1) and glucose-6-phosphate isomerase (GPI) gene expression in natural killer (NK) and CD8+ T cells. RT-PCR in ten CRC normal-tumor tissue pairs showed that expression of the signature's six HRGs varied differently in cancerous and paracancerous tissues. The constructed HRG signature successfully predicted the OS of whole-stage CRC patients. In addition, we showed that the signature's six HRGs were closely associated with the TME in CRC, where hypoxia inhibits the antitumor function of T cells.

Finding the minimum number of retrieved lymph nodes in node-negative colorectal cancer using Real-world Data and the SEER database.

BACKGROUND: Current clinical guidelines recommend the removal of at least 12 lymph nodes (LNs) in resectable colorectal cancer (CRC). With advancements in lymphadenectomy technologies, the number of retrieved lymph nodes (rLNs) has markedly increased. This study aimed to investigate the lowest number of rLNs in node-negative patients. MATERIALS AND METHODS: A total of 1103 N0 and 208 N1a stage patients were enrolled in our cohort, while 8503 N0 and 1276 N1a patients from the Surveillance, Epidemiology, and End Results CRC database were included. Propensity score matching and multivariate Cox regression analyses were performed to mitigate the influence of selection bias and control for potential confounding variables. RESULTS: The median number of rLNs in N0 patients increased from 13.5 (interquartile range [IQR]: 9-18) in 2013 to 17 (IQR: 15-20) in 2019. The restrictive cubic spline illustrated a nonlinear relationship between rLNs and prognosis (nonlinearity, P =0.009), with a threshold ( N =16) influencing clinical outcomes. Patients at either N0 or N1a stage with sufficient rLNs (≥16) demonstrated superior prognoses to those with a limited rLNs (<16). After adjusting for clinical confounders, similar prognoses were observed in N0 limited and N1a adequate populations. Furthermore, Kaplan-Meier curves revealed that N0 limited patients who received chemotherapy exhibited better outcomes than those who did not. CONCLUSIONS: Among patients with node-negative CRC, it is crucial to remove 16 or more LNs effectively. Fewer than 16 rLNs should be regarded as an independent risk factor, implying the need for adjuvant chemotherapy.

Application of machine learning in the prediction of deficient mismatch repair in patients with colorectal cancer based on routine preoperative characterization.

Simple summary: Detecting deficient mismatch repair (dMMR) in patients with colorectal cancer is essential for clinical decision-making, including evaluation of prognosis, guidance of adjuvant chemotherapy and immunotherapy, and primary screening for Lynch syndrome. However, outside of tertiary care centers, existing detection methods are not widely disseminated and highly depend on the experienced pathologist. Therefore, it is of great clinical significance to develop a broadly accessible and low-cost tool for dMMR prediction, particularly prior to surgery. In this study, we developed a convenient and reliable model for predicting dMMR status in CRC patients on routine preoperative characterization utilizing multiple machine learning algorithms. This model will work as an automated screening tool for identifying patients suitable for mismatch repair testing and consequently for improving the detection rate of dMMR, while reducing unnecessary labor and cost in patients with proficient mismatch repair. Background: Deficient mismatch repair (dMMR) indicates a sustained anti-tumor immune response and has a favorable prognosis in patients with colorectal cancer (CRC). Although all CRC patients are recommended to undergo dMMR testing after surgery, current diagnostic approaches are not available for all country hospitals and patients. Therefore, efficient and low-cost predictive models for dMMR, especially for preoperative evaluations, are warranted. Methods: A large scale of 5596 CRC patients who underwent surgical resection and mismatch repair testing were enrolled and randomly divided into training and validation cohorts. The clinical features exploited for predicting dMMR comprised the demographic characteristics, preoperative laboratory data, and tumor burden information. Machine learning (ML) methods involving eight basic algorithms, ensemble learning methods, and fusion algorithms were adopted with 10-fold cross-validation, and their performance was evaluated based on the area under the receiver operating characteristic curve (AUC) and calibration curves. The clinical net benefits were assessed using a decision curve analysis (DCA), and a nomogram was developed to facilitate model clinical practicality. Results: All models achieved an AUC of nearly 0.80 in the validation cohort, with the stacking model exhibiting the best performance (AUC = 0.832). Logistical DCA revealed that the stacking model yielded more clinical net benefits than the conventional regression models. In the subgroup analysis, the stacking model also predicted dMMR regardless of the clinical stage. The nomogram showed a favorable consistence with the actual outcome in the calibration curve. Conclusion: With the aid of ML algorithms, we developed a novel and robust model for predicting dMMR in CRC patients with satisfactory discriminative performance and designed a user-friendly and convenient nomogram.

Dual-Channel Probe of Carbon Dots Cooperating with Lanthanide Complex Employed for Simultaneously Distinguishing and Sequentially Detecting Tetracycline and Oxytetracycline.

Tetracycline (TC) and oxytetracycline (OTC) are the most widely used broad-spectrum antimicrobial agents in tetracycline drugs, and their structures and properties are very similar, so it is a great challenge to distinguish and detect these two antibiotics with a single probe at the same time. Herein, a dual-channel fluorescence probe (SiCDs@mMIPs-cit-Eu) was developed by integrating two independent reaction sites with SiCDs-doped mesoporous silica molecular imprinting group and europium complex group into a nanomaterial. The synergistic influence of inner filter effect and "antenna effect" can be guaranteed to solve the distinction between TC and OTC. Moreover, this novel strategy can also sequentially detect TC and OTC in buffer solution and real samples with high sensitivity and selectivity. This method revealed good responses to TC and OTC ranging from 0 to 5.5 µM with a detection limit of 5 and 16 nM, respectively. Combined with the smartphone color-scanning application, the portable and cheap paper-based sensor was designed to realize the multi-color visual on-site detection of TC and OTC. In addition, the logic gate device was constructed according to the fluorescence color change of the probe for TC and OTC, which provided the application possibility for the intelligent detection of the probe.

A stick-like intelligent multicolor nano-sensor for the detection of tetracycline: The integration of nano-clay and carbon dots.

In recent years, the overuse of antibiotics has caused more and more serious environmental pollution, the uncontrolled abuse of antibiotics makes bacteria produce resistance to antibiotics faster than the replacement rate of antibiotics themselves, leading to the emergence of super drug-resistant bacteria. Therefore, it is of great practical significance to establish a simple, rapid and sensitive method for the detection of antibiotics. By integrating natural nano-clay (Atta) and carbon dots (CDs), the real-time and rapid visual detection of tetracycline (TC) in the sample can be realized by chromaticity pick-up APP on smartphone. The nano-sensor can detect tetracycline in the concentration between 25 nM and 20 µM with the detection limit of 8.7 nM. The low detection limit coupled with good accuracy, sensitivity and specificity meets the requirements for the detection of tetracycline in food. More importantly, the test paper and fluorescent stick-like nano-sensor are designed to detect tetracycline by polychromatic fluorescence changes. In addition, a logic gate for semi-quantitative identification of the concentration of tetracycline is designed, which makes it possible for the application of the nano-sensor in the field of smart devices.

A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme.

BACKGROUND: Emerging evidence shows that serum tumor biomarkers (TBs) and log odds of positive lymph node scheme (LODDS) are closely associated with the prognosis of colorectal cancer (CRC) patients. The aim of our study is to validate the predictive value of TBs and LODDS clinically and to develop a robust prognostic model to predict the overall survival (OS) of patients with CRC. METHODS: CRC patients who underwent radical resection and with no preoperative chemotherapy were enrolled in the study. The eligible population were randomized into training (70%) and test (30%) cohorts for the comprehensive evaluation of the prognostic model. Clinical implications of serum biomarkers and LODDS were identified by univariate and multivariate Cox proportion regression analysis. The predictive ability and discriminative performance were evaluated by Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves. Clinical applicability of the prognostic model was assessed by decision curve analysis (DCA), and the corresponding nomogram was constructed based on the above factors. RESULTS: A total of 1,202 eligible CRC patients were incorporated into our study. Multivariable COX analysis demonstrated that CA199 (HR = 1.304), CA125 (HR = 1.429), CEA (HR = 1.307), and LODDS (HR = 1.488) were independent risk factors for OS (all P < 0.0001). K-M curves showed that the high-risk group possessed a shorter OS than the low-risk counterparts. The area under curves (AUCs) of the model for 1-, 3- and 5-year OS were 86.04, 78.70, and 76.66% respectively for the train cohort (80.35, 77.59, and 74.26% for test cohort). Logistic DCA and survival DCA confirmed that the prognostic model displayed more clinical benefits than the conventional AJCC 8th TNM stage and CEA model. The nomograms were built accordingly, and the calibration plot for the probability of survival at 3- or 5-years after surgery showed an optimal agreement between prediction and actual observation. CONCLUSIONS: Preoperative serum TBs and LODDS have significant clinical implications for CRC patients. A novel prognostic model incorporating common TBs (CA199, CA125, and CEA) and LODDS displayed better predictive performance than both single factor and the TNM classification. A novel nomogram incorporating TBs and LODDS could individually predict OS in patients with CRC.

Chameleon Luminophore for Erasable Encrypted and Decrypted Devices: From Dual-Channel, Programmable, Smart Sensory Lanthanide Hydrogel to Logic Devices.

With the rapid development of the data security technology, increasing attention has been paid to programmable memory materials with desirable security. However, most conventional memory devices only have a single switchable color state. In this research, a kind of pH-responsive Chameleon luminescent sensor (Lap@Eu-OFX, Lap = laponite, OFX = ofloxacin) based on lanthanide doping has been fabricated, which can realize highly contrast, dynamically controlled full-color display by changing the pH value of the solution. The advanced programmable security inks, including the green and red luminescent inks, have been prepared and used to protect confidential information. More interestingly, triethylamine and hydrochloric acid are selected as encryption and decryption reagents, which can repeatedly switch the emission color of important data. Hence, the high-tech security inks show great potential in data coding, multiencryption, and decryption under UV light. Furthermore, the designed dual-channel memory device, Lap@Eu-OFX@CS (CS = Chitosan), enables reversible synchronous switching of sol-gel and emission color when converting from acid to base conditions. This can be dynamically monitored by a subsequent logic gate system and can be converted and stored into binary values. This work provides an effective approach for the design and promising application of information encryptor, smart monitor, and circuit controllers.

Effects of elastic band exercise on the frailty states in pre-frail elderly people.

OBJECTIVE: To discuss the effects of elastic band exercise on the frailty states in pre-frail elderly people. METHODS: This study was a randomized controlled trial. Trial registration number is ChiCTR-IOC-17012579. Seventy pre-frail elderly people were randomly divided into elastic band group (n = 35) and control group (n = 35). Elastic band exercise was applied to elastic band group, 45-60 min per time for 8 weeks by 3 days a week; no exercise was applied to the control group. The frailty states, grip strength (female/male), walking speed, and physical activity were measured by the Fried frailty phenotype at pre-intervention, 4, and 8 weeks after intervention to assess the effects of exercise. RESULTS: The elastic band group showed significant improvements in the frailty states, grip strength (female) and walking speed both after 4-week and 8-week intervention (P< 0.001), and significant improvements in grip strength (male) and physical activity after 8-week intervention (P< 0.05). Within-group analysis (pre-intervention vs. after 4-week, after 4-week vs after 8-week, pre-intervention vs after 8-week) showed significant improvements (P< 0.001) in grip strength (female/male) and walking speed in the elastic band group over time, while no significant differences in the control group (P > 0.05). CONCLUSION: Elastic band exercise can improve frailty states in pre-frail elderly people, make them broke away from pre-frailty and restore them to non-frailty through improving the grip strength, walking speed and physical activity, and the effects after 8 weeks are better than those after 4 weeks.

Dual-Mode, Color-Tunable, Lanthanide-Doped Core-Shell Nanoarchitectures for Anti-Counterfeiting Inks and Latent Fingerprint Recognition.

With the rapid development of information in modern society, the research and development of advanced anti-counterfeiting technology is becoming more and more important to protect the security and comprehensiveness of information. Therefore, fluorescent ink as an anti-counterfeiting technology and fingerprint recognition technology as a ″human information identification card″ has attracted the attention of many research groups. Herein, dual-mode (upconversion and downconversion) lanthanide-doped luminescent nanoarchitectures were developed using Y2O3:Er3+,Yb3+ nanoparticles as a core and layered lanthanide hydroxides nanomaterials as a shell. Under the irradiation of 980 nm near-infrared light, the nanoarchitectures emitted a bright upconverted red light emission. Meanwhile, under the irradiation of 254 nm UV light, the nanoarchitectures can directly emit multicolor luminescence (from green to yellow-green, yellow, orange, and red) by changing the suitable ratios of Tb3+/Eu3+ ions. The information can only be extracted when the irradiation of two kinds of excitation light sources existed at the same time, which can improve the difficulty of illegal imitation and enhance the level of anti-counterfeiting. Furthermore, these luminescent nanoarchitectures were investigated for visual latent fingerprint recognition on various substrates with high definition, high sensitivity, and high anti-interference. These results indicated that the nanoarchitectures reported in this study may have great application prospects in information security and identity recognition.

Tumor-induced disorder of iron metabolism in major organs: a new insight from chemical speciation of iron.

Objective To investigate the evolution of iron speciation in major organs of tumor-bearing mice and its role in cancer formation and cancer-associated complications. Methods The concentration and chemical speciation of iron in the spleen, liver, lung, kidney, heart, blood, muscle, and tumor tissue of healthy mice and tumor-bearing mice were studied by synchrotron radiation-based total reflection X-ray fluorescence spectrometry (SR-TXRF) coupled with X-ray absorption spectroscopy (XAS). Results The TXRF and XAS results showed that the iron content, especially the ferritin content, significantly decreased in the blood and spleen but significantly increased in the liver, lung, and muscle of mice after tumor implantation. The chemical speciation of iron in the tumor mainly comprised ferrous-sulfide-like iron and ferritin. Conclusion The tumors disturbed the iron metabolism in major organs, and the evolution of iron may be involved in iron deficiency anemia, cancer growth, and immunity. Additionally, iron speciation-based markers may be further developed as clinical indicators for cancer and cancer-associated complications.

Saikosaponin a Inhibits Cigarette Smoke-Induced Oxidant Stress and Inflammatory Responses by Activation of Nrf2.

Saikosaponin a (SSa), a triterpenoid saponin, has numerous pharmacological properties, including anti-inflammatory and antioxidant effects. The purpose of this study was to investigate whether and how SSa protected against cigarette smoke (CS)-induced lung inflammation in mice. The mice were exposed to CS and SSa was administered by an intraperitoneal (i.p.) injection 1 h before CS treatment for 5 consecutive days. The results showed that SSa significantly inhibited CS-induced inflammatory cell infiltration, NO, TNF-α, and IL-1ß production in BALF. SSa also inhibited CS-induced MPO and MDA contents in lung tissues. Furthermore, SSa significantly inhibited CS-induced NF-κB and upregulated the expression of Nrf2 and HO-1. In conclusion, these results support a therapeutic potential for SSa in CS-induced lung inflammation.

Characterization and in vitro mineralization function of a soluble protein complex P60 from the nacre of Pinctada fucata.

A soluble protein complex P60 from the powdered nacre of Pinctada fucata was extracted and partially characterized. The biological activity of the P60 on pre-osteoblast cell line MC3T3-E1 and bone marrow stroma cells (MSCs) was investigated. The P60 protein from the decalcified powered nacre was solubilized with acetic acid and then purified by liquid chromatography. The P60 protein was a protein complex composed of several subunits with disulfide bridges. The known protein nacrein, and its two derivatives, N28 and N35, were included in the P60 protein complex. The most abundant amino acids in the P60 that account for 68.3% of the total residues are glycine (32.1%), aspartic acid (17.4%), alanine (13.6%), and glutamic acid (5.2%). The in vitro study of the crystallization showed that this protein complex could control the formation and size of calcium carbonate. The assay of biological activity of the P60 protein complex on the pre-osteoblast cell line MC3T3-E1 and MSCs suggested that the P60 could stimulate the formation of mineralized nodules.

Effects of levosimendan on mortality in patients with septic shock: systematic review with meta-analysis and trial sequential analysis.

OBJECT: Several studies have investigated a survival benefit for levosimendan treatment in patients with septic shock. However, data are conflicting. We conducted a meta-analysis to evaluate the effect of levosimendan treatment on mortality in patients with septic shock. MATERIALS AND METHODS: We searched PubMed, EMBASE and Cochrane Library Databases up to March 27, 2017, without language restrictions. We searched for terms related to septic shock, levosimendan, randomized clinical trial. Randomized controlled trials reported the effect of levosimendan on mortality were included. Moreover, we constructed the trial sequential analysis (TSA) to determine the reliability of the outcomes. Furthermore, secondary outcomes were cardiac index(CI), mean arterial pressure (MAP), blood lactate, norepinephrine dose and length of ICU stay. RESULTS: Ten studies with a total of 816 patients were included in this meta-analysis. There was no significant difference in the mortality between the levosimendan group and the standard inotropic therapy group [RR = 0.96, 95% CI (0.81-1.12), I2 = 0]. However, methods adapted from formal interim monitoring boundaries applied to TSA indicated that the cumulative evidence was unreliable and inconclusive. Blood lactate was significantly reduced in the levosimendan group while there was no difference in MAP, CI, norepinephrine dose and length of ICU stay. CONCLUSIONS: Findings from this meta-analysis demonstrated that levosimendan treatment may not reduce mortality in patients with septic shock. The result remains inclusive and further randomized controlled trials were needed to confirm these conclusions.