Microextraction techniques with deep eutectic solvents for gas chromatographic analysis: a minireview.

Sample pretreatment is one of the key steps in sample analysis. The design and development of new materials promote advancements in sample pretreatment technology. Deep eutectic solvents (DESs) are a novel material that have been developed in recent years. They possess characteristics such as low toxicity, good thermal stability, simple preparation methods, and low cost. DESs have the potential to replace traditional organic extraction solvents. DESs are formed from a hydrogen bond donor (HBD) and acceptor (HBA). Changing the type of HBA and HBD or their ratio leads to variations in the structure and properties of the resulting DESs. Gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) are the primary analytical techniques used in laboratories. This paper analyzes the selection relationship between DESs and analytes, as well as the steps of sample pretreatment, based on the characteristics of GC instruments, and utilizing DES extractants and extraction materials for sample pretreatment. This paper summarizes the progress of DES-based microextraction methods for GC. It introduces the different classifications of liquid and solid-phase microextraction and the application of DESs in them. The theoretical mechanism and extraction/separation mechanism of DESs are analyzed, and potential application of DESs in extraction/separation technology is discussed.

Combined Impact of Heart Rate Sensor Placements with Respiratory Rate and Minute Ventilation on Oxygen Uptake Prediction.

Oxygen uptake (V˙O2) is an essential metric for evaluating cardiopulmonary health and athletic performance, which can barely be directly measured. Heart rate (HR) is a prominent physiological indicator correlated with V˙O2 and is often used for indirect V˙O2 prediction. This study investigates the impact of HR placement on V˙O2 prediction accuracy by analyzing HR data combined with the respiratory rate (RESP) and minute ventilation (V˙E) from three anatomical locations: the chest; arm; and wrist. Twenty-eight healthy adults participated in incremental and constant workload cycling tests at various intensities. Data on V˙O2, RESP, V˙E, and HR were collected and used to develop a neural network model for V˙O2 prediction. The influence of HR position on prediction accuracy was assessed via Bland-Altman plots, and model performance was evaluated by mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE). Our findings indicate that HR combined with RESP and V˙E (V˙O2HR+RESP+V˙E) produces the most accurate V˙O2 predictions (MAE: 165 mL/min, R2: 0.87, MAPE: 15.91%). Notably, as exercise intensity increases, the accuracy of V˙O2 prediction decreases, particularly within high-intensity exercise. The substitution of HR with different anatomical sites significantly impacts V˙O2 prediction accuracy, with wrist placement showing a more profound effect compared to arm placement. In conclusion, this study underscores the importance of considering HR placement in V˙O2 prediction models, with RESP and V˙E serving as effective compensatory factors. These findings contribute to refining indirect V˙O2 estimation methods, enhancing their predictive capabilities across different exercise intensities and anatomical placements.

Photonic crystal gas sensors based on metal-organic frameworks and polymers.

A photonic crystal (PC) is an optical microstructure with an adjustable dielectric constant. The PC sensor was deemed a powerful tool for gas molecule detection due to its excellent sensitivity, stability, online use and tailorable optical performance. The detection signals are generated by monitoring the changes of the photonic band gap when the sensing behavior occurs. Recently, many efforts have been devoted to improving the PC sensor's detection performance and reducing technical costs by selecting and refining functional materials. In this case, metal-organic frameworks (MOFs) with a large specific surface, tunable structural properties and polymers with unique swelling properties have attracted increasingly attention. In this review, a systematic review of PC gas sensors based on MOFs and polymers was carried out for the first time. Firstly, the optical properties and gas sensing mechanism of PCs were briefly summarized. Secondly, a detailed discussion of the structural properties and rapid preparation methods of distributed Bragg reflectors (DBRs), opals and inverse opals (IOPCs) was presented. Thirdly, the recent advances in MOF, polymer and MOF/polymer-based PC sensors over the past few years were summarized. It should be noted that the sensitivity and selectivity enhancement strategy by appropriate material species selection, organic ligand functionalization, metal-ion doping, diverse functional material arrays, and multi-component compounding were analyzed in detail. Finally, prospects on PC gas sensors are given in terms of preparation methods, material functionalization and future applications.

Effects of co-application of tiotropium bromide and traditional Chinese medicine on patients with stable chronic obstructive pulmonary disease: a muilticenter, randomized, controlled trial study.

Background: Chronic Obstructive Pulmonary Disease (COPD) is a common, preventable, and treatable disease. Traditional Chinese Medicine (TCM) has shown promising potential in COPD treatment. and we conducted a multi-center RCT to evaluate the effectiveness of TCM-based therapy in stable COPD patients. Methods: In this multicenter, double-blind RCT, a total of 200 patients were supposed to be assigned to either trial or control group randomly. Both groups received Tiotropium (18 µg) from month 0 to month 12. Trial group received additional TCM granules, while control group received a placebo from month 0 to month 6. Symptom assessment, total effective rate, lung function measurements, hospitalization rates, and quality of life were evaluated at month 0, month 6, and month 12. Adverse events were assessed at month 12. Results: Of the initial 105 patients (aged 40-80) who completed the study, 51 were in trial group and 54 were in control group. At month 6, significant differences were observed between two groups in total effective rate (p = 0.020), sputum score (p = 0.047), changes in FVC% (p = 0.047) and FEV1 (p = 0.046). At month 12, significant differences were observed in sputum score (p = 0.020), FVC (p = 0.042), and change in FEV1 (p = 0.013). Compared to baseline, they both demonstrated improvements in symptoms, acute exacerbation, lung function, quality of life, and exercise tolerance. Conclusion: TCM treatment effectively improved total effective rate, sputum symptom, FVC%, FEV1, and exhibited prolonged efficacy in improving sputum symptoms and FEV1 in stable COPD patients.Clinical trial registration:https://www.chictr.org.cn/showproj.html?proj=6029 identifier ChiCTR-TRC-13003531.

Lung function benefits of traditional Chinese medicine Qiju granules against fine particulate air pollution exposure: a randomized controlled trial.

Introduction: Multiple targets are considered as the causes of ambient fine particulate matter [aerodynamic diameters of < 2.5 µm (PM2.5)] induced lung function injury. Qiju granules are derived from the traditional Chinese medicine (TCM) formula known as Qi-Ju-Di-Huang-Wan (Lycium, Chrysanthemum, and Rehmannia Formula, QJDHW), which has been traditionally used to treat symptoms such as cough with phlegm, dry mouth and throat, and liver heat. This treatment approach involves attenuating inflammation, oxidative stress, and fibrosis response. This study investigated the effects of Qiju granules on protecting lung function against PM2.5 exposure in a clinical trial. Methods: A randomized, double-blinded, and placebo-controlled trial was performed among 47 healthy college students in Hangzhou, Zhejiang Province in China. The participants were randomly assigned to the Qiju granules group or the control group based on gender. Clinical follow-ups were conducted once every 2 weeks during a total of 4 weeks of intervention. Real-time monitoring of PM2.5 concentrations in the individually exposed participants was carried out. Data on individual characteristics, heart rate (HR), blood pressure (BP), and lung function at baseline and during the follow-ups were collected. The effects of PM2.5 exposure on lung function were assessed within each group using linear mixed-effect models. Results: In total, 40 eligible participants completed the scheduled follow-ups. The average PM2.5 level was found to be 64.72 µg/m3 during the study period. A significant negative correlation of lung function with PM2.5 exposure concentrations was observed, and a 1-week lag effect was observed. Forced expiratory volume in one second (FEV1), peak expiratory flow (PEF), maximal mid-expiratory flow (MMEF), forced expiratory flow at 75% of forced vital capacity (FVC) (FEF75), forced expiratory flow at 50% of FVC (FEF50), and forced expiratory flow at 25% of FVC (FEF25) were significantly decreased due to PM2.5 exposure in the control group. Small airway function was impaired more seriously than large airway function when PM2.5 exposure concentrations were increased. In the Qiju granules group, the associations between lung function and PM2.5 exposure were much weaker, and no statistical significance was observed. Conclusion: The results of the study showed that PM2.5 exposure was associated with reduced lung function. Qiju granules could potentially be effective in protecting lung functions from the adverse effects of PM2.5 exposure. Clinical Trial Registration: identifier: ChiCTR1900021235.

Au- ZnFe2O4 hollow microspheres based gas sensor for detecting the mustard gas simulant 2-chloroethyl ethyl sulfide.

Mustard gas, a representative of blister agents, poses a severe threat to human health. Although the structure of 2-chloroethyl ethyl sulfide (2-CEES) is similar to mustard gas, 2-CEES is non-toxic, rendering it a commonly employed simulant in related research. ZnFe2O4-based semiconductor gas sensors exhibit numerous advantages, including structural stability, high sensitivities, and easy miniaturization. However, they exhibit insufficient sensitivity at low concentrations and require high operating temperatures. Owing to the effect of electronic and chemical sensitization, the gas-sensing performance of a sensor may be remarkably enhanced via the sensitization method of noble metal loading. In this study, based on the morphologies of ZnFe2O4 hollow microspheres, a solvothermal method was adopted to realize different levels of Au loading. Toward 1 ppm of 2-CEES, the gas sensor based on 2 wt.% Au-loaded ZnFe2O4 hollow microspheres exhibited a response sensitivity twice that of the gas sensor based on pure ZnFe2O4; furthermore, the response/recovery times decreased. Additionally, the sensor displayed excellent linear response to low concentrations of 2-CEES, outstanding selectivity in the presence of several common volatile organic compounds, and good repeatability, as well as long-term stability. The Au-loaded ZnFe2O4-based sensor has considerable potential for use in detecting toxic chemical agents and their simulants.

The Properties of High-Performance Concrete with Manganese Slag under Salt Action.

Manganese slag (MS) containing a certain amount of active hydration substances may be used as a kind of cementitious material. In the present study, we measured the mass, the relative dynamic modulus of elasticity (RDME), and the flexural and compressive strengths of MS high-performance concrete (MS-HPC) with added basalt fibers exposed to NaCl freeze-thaw cycles (N-FCs), NaCl dry-wet alternations (N-DAs), and Na2SO4 dry-wet alternations (NS-DAs). Scanning electron microscope energy-dispersive spectrometer (SEM-EDS) spectra, thermogravimetric analysis (TG) curves, and X-ray diffraction spectroscopy (XRD) curves were obtained. The mass ratio of MS ranged from 0% to 40%. The volume ratio of basalt fibers varied from 0% to 2%. We found that, as a result of salt action, the mass loss rate (MLR) exhibited linear functions which were inversely correlated with the mass ratio of MS and the volume ratio of basalt fibers. After salt action, MLR increased by rates of 0~56.3%, but this increase was attenuated by the addition of MS and basalt fibers. Corresponding increases in RDME exhibited a linear function which was positively correlated with MS mass ratios in a range of 0~55.1%. The addition of MS and basalt fibers also led to decreased attenuation of mechanical strength, while the addition of MS led to increased levels of flocculent hydration products and the elements Mn, Mg, and Fe. CaClOH and CaSO4 crystals were observed in XRD curves after N-DA and NS-DA actions, respectively. Finally, the addition of MS resulted in increased variation in TG values. However, the opposite result was obtained when dry-wet actions were exerted.

Brain network hierarchy reorganization in subthreshold depression.

BACKGROUND: Hierarchy is the organizing principle of human brain network. How network hierarchy changes in subthreshold depression (StD) is unclear. The aim of this study was to investigate the altered brain network hierarchy and its clinical significance in patients with StD. METHODS: A total of 43 patients with StD and 43 healthy controls matched for age, gender and years of education participated in this study. Alterations in the hierarchy of StD brain networks were depicted by connectome gradient analysis. We assessed changes in network hierarchy by comparing gradient scores in each network in patients with StD and healthy controls. The study compared different brain subdivisions if there was a different network. Finally, we analysed the relationship between the altered gradient scores and clinical characteristics. RESULTS: Patients with StD had contracted network hierarchy and suppressed cortical range gradients. In the principal gradient, the gradient scores of default mode network were significantly reduced in patients with StD compared to controls. In the default network, the subdivisions of reduced gradient scores were mainly located in the precuneus, superior temporal gyrus, and anterior and posterior cingulate gyrus. Reduced gradient scores in the default mode network, the anterior and posterior cingulate gyrus were correlated with severity of depression. CONCLUSIONS: The network hierarchy of the StD changed and was significantly correlated with depressive symptoms and severity. These results provided new insights into further understanding of the neural mechanisms of StD.

Synthesis and Application of Polymer SXFA in the Detection of Organophosphine Agents with a SAW Sensor.

The effective detection of isopropyl methylfluorophosphonate (GB, sarin), a type of organophosphine poisoning agent, is an urgent issue to address to maintain public safety. In this research, a gas-sensitive film material, poly (4-hydroxy-4,4-bis trifluoromethyl)-butyl-1-enyl)-siloxane (SXFA), with a structure of hexafluoroisopropyl (HFIP) functional group was synthesized by using methyl vinylpropyl dichlorosilane and hexafluoroacetone trihydrate as initial materials. The synthesis process products were characterized using FTIR. SXFA was prepared on a 200 MHz shear surface wave delay line using the spin-coating method for GB detection. A detection limit of <0.1 mg/m3 was achieved through conditional experiments. Meanwhile, we also obtained a maximum response of 2.168 mV at a 0.1 mg/m3 concentration, indicating the much lower detection limit of the SAW-SXFA sensor. Additionally, a maximum response standard deviation of 0.11 mV with a coefficient of variation of 0.01 and a maximum recovery standard deviation of 0.22 mV with a coefficient of variation of 0.02 were also obtained through five repeated experiments. The results show that the SAW-SXFA sensor has strong selectivity and reproducibility, good selectivity, positive detection ability, high sensitivity, and fast alarm performance for sarin detection.

A passive wireless surface acoustic wave (SAW) sensor system for detecting warfare agents based on fluoroalcohol polysiloxane film.

Long-term monitoring of environmental warfare agengts is a challenge for chemical gas sensors. To address this issue, we developed a 433 MHz passive wireless surface acoustic wave (WSAW) gas sensor for dimethyl methylphosphonate (DMMP) detection. This WSAW gas sensor includes a YZ lithium niobate (LiNbO3) substrate with metallic interdigital transducers (IDTs) etched on it, and an antenna was placed near the IDT. A DMMP-sensitive viscoelastic polymer fluoroalcoholpolysiloxane (SXFA) film was prepared on a LiNbO3 substrate, and mode modeling coupling was used to optimize the design parameters. The sensor can function properly in an environments between -30 °C and 100 °C with humidity less than 60% RH. When the wireless transmission distance was within the range of 0-90 cm, the sensor noise increased with distance, and the stability was less than 32°/h. While optimizing the film thickness of SXFA, a relationship was observed between sensor sensitivity and film thickness. When the film thickness of SXFA reached 450 nm, the optimal value was reached. At a distance of 20 cm between the transmitting and receiving antennas, DMMP was detected at different concentrations with the developed WSAW gas sensor. The lower detection limit of DMMP was 0.48 mg/m3, the sensitivity of the sensor was 4.63°/(mg/m3), and repeatable performance of the sensor was confirmed.

Alterations in hippocampus-centered morphological features and function of the progression from normal cognition to mild cognitive impairment.

Mild cognitive impairment (MCI) is a significant precursor to dementia, highlighting the critical need for early identification of individuals at high risk of MCI to prevent cognitive decline. The study aimed to investigate the changes in brain structure and function before the onset of MCI. This study enrolled 19 older adults with progressive normal cognition (pNC) to MCI and 19 older adults with stable normal cognition (sNC). The gray matter (GM) volume and functional connectivity (FC) were estimated via magnetic resonance imaging during their normal cognition state 3 years prior. Additionally, spatial associations between FC maps and neurochemical profiles were examined using JuSpace. Compared to the sNC group, the pNC group showed decreased volume in the left hippocampus and left amygdala. The significantly positive correlation was observed between the GM volume of the left hippocampus and the MMSE scores after 3 years in pNC group. Besides, it showed that the pNC group had increased FC between the left hippocampus and the anterior-posterior cingulate gyrus, which was significantly correlated with the spatial distribution of dopamine D2 and noradrenaline transporter. Taken together, the study identified the abnormal brain characteristics before the onset of MCI, which might provide insight into clinical research.

Atypical characteristic changes of surface morphology and structural covariance network in developmental dyslexia.

BACKGROUND: Developmental dyslexia (DD) is a neurodevelopmental disorder that is characterized by difficulties with all aspects of information acquisition in the written word, including slow and inaccurate word recognition. The neural basis behind DD has not been fully elucidated. METHOD: The study included 22 typically developing (TD) children, 16 children with isolated spelling disorder (SpD), and 20 children with DD. The cortical thickness, folding index, and mean curvature of Broca's area, including the triangular part of the left inferior frontal gyrus (IFGtriang) and the opercular part of the left inferior frontal gyrus, were assessed to explore the differences of surface morphology among the TD, SpD, and DD groups. Furthermore, the structural covariance network (SCN) of the triangular part of the left inferior frontal gyrus was analyzed to explore the changes of structural connectivity in the SpD and DD groups. RESULTS: The DD group showed higher curvature and cortical folding of the left IFGtriang than the TD group and SpD group. In addition, compared with the TD group and the SpD group, the structural connectivity between the left IFGtriang and the left middle-frontal gyrus and the right mid-orbital frontal gyrus was increased in the DD group, and the structural connectivity between the left IFGtriang and the right precuneus and anterior cingulate was decreased in the DD group. CONCLUSION: DD had atypical structural connectivity in brain regions related to visual attention, memory and which might impact the information input and integration needed for reading and spelling.

Prognostic value of oxygen saturation index trajectory phenotypes on ICU mortality in mechanically ventilated patients: a multi-database retrospective cohort study.

BACKGROUND: Heterogeneity among critically ill patients undergoing invasive mechanical ventilation (IMV) treatment could result in high mortality rates. Currently, there are no well-established indicators to help identify patients with a poor prognosis in advance, which limits physicians' ability to provide personalized treatment. This study aimed to investigate the association of oxygen saturation index (OSI) trajectory phenotypes with intensive care unit (ICU) mortality and ventilation-free days (VFDs) from a dynamic and longitudinal perspective. METHODS: A group-based trajectory model was used to identify the OSI-trajectory phenotypes. Associations between the OSI-trajectory phenotypes and ICU mortality were analyzed using doubly robust analyses. Then, a predictive model was constructed to distinguish patients with poor prognosis phenotypes. RESULTS: Four OSI-trajectory phenotypes were identified in 3378 patients: low-level stable, ascending, descending, and high-level stable. Patients with the high-level stable phenotype had the highest mortality and fewest VFDs. The doubly robust estimation, after adjusting for unbalanced covariates in a model using the XGBoost method for generating propensity scores, revealed that both high-level stable and ascending phenotypes were associated with higher mortality rates (odds ratio [OR]: 1.422, 95% confidence interval [CI] 1.246-1.623; OR: 1.097, 95% CI 1.027-1.172, respectively), while the descending phenotype showed similar ICU mortality rates to the low-level stable phenotype (odds ratio [OR] 0.986, 95% confidence interval [CI] 0.940-1.035). The predictive model could help identify patients with ascending or high-level stable phenotypes at an early stage (area under the curve [AUC] in the training dataset: 0.851 [0.827-0.875]; AUC in the validation dataset: 0.743 [0.709-0.777]). CONCLUSIONS: Dynamic OSI-trajectory phenotypes were closely related to the mortality of ICU patients requiring IMV treatment and might be a useful prognostic indicator in critically ill patients.

Polydatin alleviates bleomycin-induced pulmonary fibrosis and alters the gut microbiota in a mouse model.

To investigate the effect and mechanism of polydatin on bleomycin (BLM)-induced pulmonary fibrosis in a mouse model. The lung fibrosis model was induced by BLM. The contents of TNF-α, LPS, IL-6 and IL-1ß in lung tissue, intestine and serum were detected by ELISA. Gut microbiota diversity was detected by 16S rDNA sequencing; R language was used to analyse species composition, α-diversity, ß-diversity, species differences and marker species. Mice were fed drinking water mixed with four antibiotics (ampicillin, neomycin, metronidazole, vancomycin; antibiotics, ABx) to build a mouse model of ABx-induced bacterial depletion; and faecal microbiota from different groups were transplanted into BLM-treated or untreated ABx mice. The histopathological changes and collagen I and α-SMA expression were determined. Polydatin effectively reduced the degree of fibrosis in a BLM-induced pulmonary fibrosis mouse model; BLM and/or polydatin affected the abundance of the dominant gut microbiota in mice. Moreover, faecal microbiota transplantation (FMT) from polydatin-treated BLM mice effectively alleviated lung fibrosis in BLM-treated ABx mice compared with FMT from BLM mice. Polydatin can reduce fibrosis and inflammation in a BLM-induced mouse pulmonary fibrosis model. The alteration of gut microbiota by polydatin may be involved in the therapeutic effect.

Automatic brain extraction for rat magnetic resonance imaging data using U2-Net.

Objective.Skull stripping is a key step in the pre-processing of rodent brain magnetic resonance images (MRI). This study aimed to develop a new skull stripping method via U2-Net, a neural network model based on deep learning method, for rat brain MRI.Approach.In this study, 599 rats were enrolled and U2-Net was applied to segment MRI images of rat brain. The intercranial tissue of each rat was manually labeled. 476 rats (approximate 80%) were used for training set while 123 rats (approximate 20%) were used to test the performance of the trained U2-Net model. For evaluation, the segmentation result by the U2-Net model is compared with the manual label, and traditional segment methods. Quantitative evaluation, including Dice coefficient, Jaccard coefficient, Sensitivity, Specificity, Pixel accuracy, Hausdorff coefficient, True positive rate, False positive rate and the volumes of whole brain, were calculated to compare the segmentation results among different models.Main results.The U2-Net model was performed better than the software of RATS and BrainSuite, in which the quantitative values of training U2-Net model were 0.9907 ± 0.0016 (Dice coefficient), 0.9816 ± 0.0032 (Jaccard coefficient), 0.9912 ± 0.0020 (Sensitivity), 0.9989 ± 0.0002 (Specificity), 0.9982 ± 0.0003 (Pixel accuracy), 5.2390 ± 2.5334 (Hausdorff coefficient), 0.9902 ± 0.0025 (True positive rate), 0.0009 ± 0.0002(False positive rate) respectively.Significance.This study provides a new method that achieves reliable performance in rat brain skull stripping of MRI images, which could contribute to the processing of rat brain MRI.

High-performance metal-oxide gas sensors based on hierarchical core-shell ZnFe2O4 microspheres for detecting 2-chloroethyl ethyl sulfide.

Mustard gas, an erosive chemical agent, is primarily used as a chemical weapon, which seriously threatens human life and health. Therefore, detecting mustard gas and its simulant, 2-chloroethyl ethyl sulfide (2-CEES), is a very important task. As a binary metal oxide with a spinel structure, ZnFe2O4 is widely used for fabricating gas sensors because of its stable chemical structure and abundant oxygen vacancies. In this study, gas-sensing ZnFe2O4 microspheres with a hierarchical core-shell nanosheet structure were prepared via a simple one-step solvothermal method. Scanning electron microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and N2 adsorption analyses were performed to characterize the morphology, structure, and chemical composition of these microspheres. A gas sensor was fabricated from the as-synthesized material, and its gas sensing performance was evaluated, using 2-CEES as a target gas. The obtained ZnFe2O4-based sensor exhibited a high sensitivity of 9.07 to 1 ppm 2-CEES at the optimal working temperature of 250 °C. The sensor response and recovery times were 18 and 546 s, respectively, and its detection sensitivity of 2.87 achieved at a 2-CEES concentration of 0.01 ppm was within an acceptable range. Additionally, the sensor demonstrated sufficiently high 2-CEES selectivity, repeatability, and long-term stability.

A Data-Driven Intelligent Management Scheme for Digital Industrial Aquaculture based on Multi-object Deep Neural Network.

With the development of intelligent aquaculture, the aquaculture industry is gradually switching from traditional crude farming to an intelligent industrial model. Current aquaculture management mainly relies on manual observation, which cannot comprehensively perceive fish living conditions and water quality monitoring. Based on the current situation, this paper proposes a data-driven intelligent management scheme for digital industrial aquaculture based on multi-object deep neural network (Mo-DIA). Mo-IDA mainly includes two aspects of fish state management and environmental state management. In fish state management, the double hidden layer BP neural network is used to build a multi-objective prediction model, which can effectively predict the fish weight, oxygen consumption and feeding amount. In environmental state management, a multi-objective prediction model based on LSTM neural network was constructed using the temporal correlation of water quality data series collection to predict eight water quality attributes. Finally, extensive experiments were conducted on real datasets and the evaluation results well demonstrated the effectiveness and accuracy of the Mo-IDA proposed in this paper.

Which Specific Exercise Models Are Most Effective on Global Cognition in Patients with Cognitive Impairment? A Network Meta-Analysis.

(1) Introduction: Physical exercise interventions can impart significant cognitive benefits to older adults suffering from cognitive impairment (CI). However, the efficacy of these interventions can vary widely, depending on the type, intensity, duration and frequency of exercise. (2) Aim: To systematically review the efficacy of exercise therapy on global cognition in patients with CI using a network meta-analysis (NMA). (3) Methods: The PubMed, Embase, Sport Discus (EBSCO) and Cochrane Library databases were electronically searched to collect randomized controlled trials (RCTs) on exercise for patients with CI from inception to 7 August 2022. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. The NMA was performed using the consistency model. (4) Results: A total of 29 RCTs comprising 2458 CI patients were included. The effects of different types of exercise on patients with CI were ranked as follows: multicomponent exercise (SMD = 0.84, 95% CI 0.31 to 1.36, p = 0.002), short duration (≤45 min) (SMD = 0.83, 95% CI 0.18 to 1.19, p = 0.001), vigorous intensity (SMD = 0.77, 95% CI 0.18 to 1.36, p = 0.011) and high frequency (5-7 times/week) (SMD = 1.28, 95% CI 0.41 to 2.14, p = 0.004). (5) Conclusion: These results suggested that multicomponent, short-duration, high-intensity, and high-frequency exercise may be the most effective type of exercise in improving global cognition in CI patients. However, more RCTs based on direct comparison of the effects of different exercise interventions are needed. (6) NMA registration identifier: CRD42022354978.

Emodin inhibiting epithelial-mesenchymal transition in pulmonary fibrosis through the c-MYC/miR-182-5p/ZEB2 axis.

Emodin is a natural anthraquinone compound, which is the main component found in the traditional Chinese herb Polygonum cuspidatum. The anti-fibrosis effects of Emodin have been reported. This study aimed to explore the specific mechanism of Emodin in the epithelial-mesenchymal transition (EMT) of pulmonary fibrosis. The pulmonary fibrosis mice models were constructed with bleomycin, the EMT models of alveolar epithelial cells were stimulated by TGF-ß1, and Emodin was used for intervention. c-MYC and miR-182-5p were overexpressed or silenced by cell transfection. Our results demonstrated that Emodin attenuated pulmonary fibrosis induced by bleomycin in mice, and inhibited EMT, meanwhile downregulated c-MYC, upregulated miR-182-5p, and downregulated ZEB2 in vitro and vivo. Next, overexpression of c-MYC promoted EMT, while silencing c-MYC and overexpressing miR-182-5p inhibited EMT. Then, c-MYC negatively regulated the expression of miR-182-5p with a direct binding relationship. And miR-182-5p inhibited ZEB2 expression in a targeted manner. Finally, Emodin inhibited EMT that had been promoted by overexpression of c-MYC. In conclusion, Emodin could attenuate pulmonary fibrosis and EMT by regulating the c-MYC/miR-182-5p/ZEB2 axis, which might provide evidence for the application of Emodin in the treatment of pulmonary fibrosis.

Effect of ischemic preconditioning on maximum accumulated oxygen deficit in 400-meter runners.

The main aim of this study was to examine the influence of ischemic preconditioning (IPC) on maximal accumulated oxygen deficit (MAOD). We conducted a three-arm and assessor-blinded randomized, controlled crossover study. Sixteen 400-meter running male athletes (19.9 ± 1.3 years; 1.78 ± 0.05 m; 67.9 ± 5.5 kg) completed three supramaximal intensity tests separated with Control, Local (legs), and Remote (arms) IPC interventions. IPC was induced on the limbs on both sides (4×5 min alternating unilateral occlusion 220 mmHg and reperfusion; arms or thighs; right side first) before participants performed the supramaximal intensity test on a treadmill at 110% VO2max intensity to exhaustion. During each test, indices of respiratory gas exchange, blood lactate, and heart rate were determined. The MAOD was calculated as the difference between the theoretical VO2 demand and the actual VO2 during the supramaximal intensity test. Differences from three trials were analyzed using ANOVA with repeated measures. IPC increased MAOD (RIPC, 59 ± 17 ml/kg/min, p = 0.018; LIPC, 57 ± 15 ml/kg/min, p = 0.037; p < 0.05) compared with Control (49 ± 9 ml/kg/min). Time to exhaustion was enhanced after IPC (Control: 257.2 ± 69.5 s, RIPC, 292.3 ± 66.6 s, p = 0.048; LIPC, 291.6 ± 79.2 s, p = 0.042; p < 0.05). In contrast, the enhancements of RIPC and LIPC trials were similar (p = 1.000). Blood lactate concentrations were similar across the three intervention conditions (p > 0.05). Acute IPC improved MAOD and supramaximal intensity exercise capacity in 400-meter running athletes. The increased MAOD indicated greater anaerobic capacity, which can be the potential mediator for improvement in exhaustion time.HighlightsIschemic preconditioning may improve the exhaustion time of supramaximal intensity running in well-trained 400-meter middle distance athletes.Acute IPC may be beneficial to anaerobic exercise capacity as the maximal accumulated oxygen deficit increases after IPC.Acute IPC occlusion on the upper arms or thighs may improve anaerobic capacity.