The effects of probiotics supplementation on glycaemic control among adults with type 2 diabetes mellitus: a systematic review and meta-analysis of randomised clinical trials.

OBJECTIVE: This systematic review and meta-analysis study aimed to evaluate the effectiveness of probiotics supplementation on glycaemic control in patients with type 2 diabetes mellitus (T2DM) based on the data from the randomised clinical trials (RCTs). METHODS: PubMed, Web of Sciences, Embase, and Cochrane Library were searched from the inception to October 2022, and RCTs about probiotics and T2DM were collected. The standardised mean difference (SMD) with 95% confidence interval (CI) was used to estimate the effects of probiotics supplementation on glycaemic control related parameters, e.g. fasting blood glucose (FBG), insulin, haemoglobin A1c (HbA1c), and homeostasis model of assessment of insulin resistance (HOMA-IR). RESULTS: Thirty RCTs including 1,827 T2MD patients were identified. Compared with the placebo group, the probiotics supplementation group had a significant decrease in the parameters of glycaemic control, including FBG (SMD = - 0.331, 95% CI - 0.424 to - 0.238, Peffect < 0.001), insulin (SMD = - 0.185, 95% CI - 0.313 to - 0.056, Peffect = 0.005), HbA1c (SMD = - 0.421, 95% CI - 0.584 to - 0.258, Peffect < 0.001), and HOMA-IR (SMD = - 0.224, 95% CI - 0.342 to - 0.105, Peffect < 0.001). Further subgroup analyses showed that the effect was larger in the subgroups of Caucasians, high baseline body mass index (BMI ≥ 30.0 kg/m2), Bifidobacterium and food-type probiotics (Psubgroup < 0.050). CONCLUSION: This study supported that probiotics supplementation had favourable effects on glycaemic control in T2DM patients. It may be a promising adjuvant therapy for patients with T2DM.

Minimum Criteria for Brain Death Determination: Consensus Promotion and Chinese Practice.

BACKGROUND: Brain death (BD), the irreversible cessation of function in the whole brain, is a well-known condition in most countries. The criteria and practical guidelines for brain death determination (BDD) in China were issued by the Brain Injury Evaluation Quality Control Center (BQCC) of the National Health and Family Planning Commission in 2013. Thereafter, we proposed a plan called the three-step quality control plan (three-step QCP) to ensure the safety and consistency of the clinical judgments regarding BD. By retrospectively reviewing this plan, we aimed to identify problems during its implementation and to provide suggestions for future work on quality control for BDD. METHODS: Data were retrieved from the BQCC database. The characteristics and test results of physicians undergoing a BDD training course and the BD case records submitted by hospitals before and after receiving accreditation were analyzed. RESULTS: In the first step of the plan, the error rate for physicians undergoing the BDD paper test was highest for limb movement discrimination (26.29%); this error rate was correlated with age (per 10-year increase) (odds ratio = 1.262, 95% confidence interval 1.067-1.491, P = 0.007) but was nonsignificantly associated with sex, specialty category, professional level, and hospital level (P > 0.05). During the second step of the plan, the highest percentage of problems was associated with apnea testing (22.75%), followed by ancillary testing of BDD (16.17%). In the last step, the highest percentage of problems in the case records was associated with apnea testing (41.73%). CONCLUSIONS: The three-step QCP is of significant utility for ensuring accuracy and appropriateness in BDD. Simultaneously, this study provides important evidence for advancing quality control for BDD in the next stage.

[An EHG-based Preterm Delivery Prediction Algorithm via Convolution Neural Network].

Premature delivery is one of the direct factors that affect the early development and safety of infants. Its direct clinical manifestation is the change of uterine contraction intensity and frequency. Uterine Electrohysterography(EHG) signal collected from the abdomen of pregnant women can accurately and effectively reflect the uterine contraction, which has higher clinical application value than invasive monitoring technology such as intrauterine pressure catheter. Therefore, the research of fetal preterm birth recognition algorithm based on EHG is particularly important for perinatal fetal monitoring. We proposed a convolution neural network(CNN) based on EHG fetal preterm birth recognition algorithm, and a deep CNN model was constructed by combining the Gramian angular difference field(GADF) with the transfer learning technology. The structure of the model was optimized using the clinical measured term-preterm EHG database. The classification accuracy of 94.38% and F1 value of 97.11% were achieved. The experimental results showed that the model constructed in this paper has a certain auxiliary diagnostic value for clinical prediction of premature delivery.

Effects of PRSS1-PRSS2 rs10273639, CLDN2 rs7057398 and MORC4 rs12688220 polymorphisms on individual susceptibility to pancreatitis: A meta-analysis.

BACKGROUND: Genetic association studies regarding relationship between PRSS1-PRSS2 rs10273639/CLDN2 rs7057398/MORC4 rs12688220 polymorphisms and pancreatitis yielded conflicting results. We performed this meta-analysis to explore associations between these polymorphisms and pancreatitis in a larger pooled population. METHODS: A systematic search of the literature was conducted for eligible studies. We used Review Manager to conduct statistical analyses. RESULTS: Fifteen studies were included in this meta-analysis. The results of pooled analyses showed that CLDN2 rs7057398, MORC4 rs12688220 and PRSS1-PRSS2 rs10273639 polymorphisms were all significantly associated with susceptibility to acute pancreatitis in Caucasians. Moreover, MORC4 rs12688220 and PRSS1-PRSS2 rs10273639 polymorphisms were also significantly associated with susceptibility to chronic pancreatitis in Asians. CONCLUSIONS: Our findings suggested that rs7057398, rs12688220 and rs10273639 polymorphisms could be used to identify individuals at an elevated susceptibility to acute pancreatitis in Caucasians. Moreover, rs12688220 and rs10273639 polymorphisms could be used to identify individuals at an elevated susceptibility chronic pancreatitis in Asians.

[Classification of Fetal Heart Rate Based on Poincare Plot and LSTM].

Fetal heart rate plays an essential role in maternal and fetal monitoring and fetal health detection. In this study, a method based on Poincare Plot and LSTM is proposed to realize the high performance classification of abnormal fetal heart rate. Firstly, the original fetal heart rate signal of CTU-UHB database is preprocessed via interpolation, then the sequential fetal heart rate signal is converted into Poincare Plot to obtain nonlinear characteristics of the signals, and then SquenzeNet is used to extract the features of Poincare Plot. Finally, the features extracted by SqueezeNet are classified by LSTM. And the accuracy, the true positive rate and the false positive rate are 98.00%, 100.00%, 92.30% respectively on 2 000 test set data. Compared with the traditional fetal heart rate classification method, all respects are improved. The method proposed in this study has good performance in CTU-UHB fetal monitoring database and has certain practical value in the clinical diagnosis of auxiliary fetal heart rate detection.

Ratio of Optic Nerve Sheath Diameter to Eyeball Transverse Diameter by Ultrasound Can Predict Intracranial Hypertension in Traumatic Brain Injury Patients: A Prospective Study.

BACKGROUND: Measuring optic nerve sheath diameter (ONSD), an indicator to predict intracranial hypertension, is noninvasive and convenient, but the reliability of ONSD needs to be improved. Instead of using ONSD alone, this study aimed to evaluate the reliability of the ratio of ONSD to eyeball transverse diameter (ONSD/ETD) in predicting intracranial hypertension in traumatic brain injury (TBI) patients. METHODS: We performed a prospective study on patients admitted to the Surgery Intensive Care Unit. The included 52 adults underwent craniotomy for TBI between March 2017 and September 2018. The ONSD and ETD of each eyeball were measured by ultrasound and computed tomography (CT) scan within 24 h after a fiber optic probe was placed into lateral ventricle. Intracranial pressure (ICP) > 20 mmHg was regarded as intracranial hypertension. The correlations between invasive ICP and ultrasound-ONSD/ETD ratio, ultrasound-ONSD, CT-ONSD/ETD ratio, and CT-ONSD were each analyzed separately. RESULTS: Ultrasound measurement was successfully performed in 94% (n = 49) of cases, and ultrasound and CT measurement were performed in 48% (n = 25) of cases. The correlation efficiencies between ultrasound-ONSD/ETD ratio, ultrasound-ONSD, CT-ONSD/ETD ratio, and ICP were 0.613, 0.498, and 0.688, respectively (P < 0.05). The area under the curve (AUC) values of the receiver operating characteristic (ROC) curve for the ultrasound-ONSD/ETD ratio and CT-ONSD/ETD ratio were 0.920 (95% CI 0.877-0.964) and 0.896 (95% CI 0.856-0.931), respectively. The corresponding threshold values were 0.25 (sensitivity of 90%, specificity of 82.3%) and 0.25 (sensitivity of 85.7%, specificity of 83.3%), respectively. CONCLUSION: The ratio of ONSD to ETD tested by ultrasound may be a reliable indicator for predicting intracranial hypertension in TBI patients.

A preoperative whey protein and glucose drink before hip fracture surgery in the aged improves symptomatic and metabolic recovery.

BACKGROUND AND OBJECTIVES: We investigated the effects of a carbohydrate-whey protein solution on aged patients undergoing hip fracture surgery. METHODS AND STUDY DESIGN: Forty patients were randomly assigned to the carbohydrate-whey protein (CHP) group or the control group (CTL). In the CHP group, a mixed solution of CHP was orally administered to patients before surgery: 400 mL was administered on the day before surgery, and 200 mL was administered 3 h before surgery. The size of the liquid dark area in the gastric antrum was measured by ultrasound, and the bleeding volume during surgery was assayed. The incidence of nausea, vomiting, thirst, hunger, and days of hospitalization and the levels of blood glucose, C-reactive protein (CRP) and serum albumin were assessed. RESULTS: There was no obvious liquid dark space in the gastric antrum. CHP administration improved postoperative thirst and hunger and resulted in increased albumin levels and decreased CRP concentrations and blood glucose fluctuations. CONCLUSIONS: Oral CHP before hip fracture surgery reduces the incidence of postoperative thirst and hunger and improves recovery in the aged.

DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network.

BACKGROUND: Fetal heart rate (FHR) monitoring is a screening tool used by obstetricians to evaluate the fetal state. Because of the complexity and non-linearity, a visual interpretation of FHR signals using common guidelines usually results in significant subjective inter-observer and intra-observer variability. OBJECTIVE: Therefore, computer aided diagnosis (CAD) systems based on advanced artificial intelligence (AI) technology have recently been developed to assist obstetricians in making objective medical decisions. METHODS: In this work, we present an 8-layer deep convolutional neural network (CNN) framework to automatically predict fetal acidemia. After signal preprocessing, the input 2-dimensional (2D) images are obtained using the continuous wavelet transform (CWT), which provides a better way to observe and capture the hidden characteristic information of the FHR signals in both the time and frequency domains. Unlike the conventional machine learning (ML) approaches, this work does not require the execution of complex feature engineering, i.e., feature extraction and selection. In fact, 2D CNN model can self-learn useful features from the input data with the prerequisite of not losing informative features, representing the tremendous advantage of deep learning (DL) over ML. RESULTS: Based on the test open-access database (CTU-UHB), after comprehensive experimentation, we achieved better classification performance using the optimal CNN configuration compared to other state-of-the-art methods: the averaged ten-fold cross-validation of the accuracy, sensitivity, specificity, quality index defined as the geometric mean of the sensitivity and specificity, and the area under the curve yielded results of 98.34, 98.22, 94.87, 96.53 and 97.82%, respectively CONCLUSIONS: Once the proposed CNN model is successfully trained, the corresponding CAD system can be served as an effective tool to predict fetal asphyxia objectively and accurately.

Single-Lead Fetal ECG Extraction Based on a Parallel Marginalized Particle Filter.

This paper presents a novel method for extracting the fetal ECG (FECG) from a single-lead abdominal signal. A dynamical model for a modified abdominal signal is proposed, in which both the maternal ECG (MECG) and the FECG are modeled, and then a parallel marginalized particle filter (par-MPF) is used for tracking the abdominal signal. Finally, the FECG and MECG are simultaneously separated. Several experiments are conducted using both simulated and clinical signals. The results indicate that the method proposed in this paper effectively extracts the FECG and outperforms other Bayesian filtering algorithms.

[Study on biological monitoring indicators of exposure to 1,2-dichloroethane and its determination method in blood].

OBJECTIVE: To investigate the feasibility of using the concentration of 1,2-DCE in blood as a biological monitoring indicators and build the determination method of 1,2-DCE in blood. METHODS: Dose-response relationship of the exposure of 1,2-DCE and the level of 1,2-DCE in rat blood were investigated using the Pearson's correlation analysis. The concentration of 1,2-DCE in blood was determined using Headspace Sampler-Gas Chromatography-Mass Spectrometer (HS-GC-MS). 3.0 ml blood sample diluting with 2.0 ml 1,2-DCE standard serial solution was placed in 15 headspace bottles respectively and heated at 80 ℃ for 20 min.The vapor upon the headspace bottle was separated by capillary column and the concentration of 1,2-DCE was determined by massspectrum in SIM mode to draw a standard work curve. The within-run precision and the between-run precision were calculated by the relative standard deviation (RSD) of the concentration of 1,2-DCE in blood which was determined 6 times in a day and 6 times within 3 days respectively. The recovery rate was calculated by P=(C2 -C0)/C1 × 100%. RESULTS: When the treatment groups were exposed at dosage of 1,472, 2,550, 3,093, 3,976, and 4 418 mg/m(3), the average concentration of 1,2-DCE in rat blood was 24.1,231.6,344.3,395.1,538.5 µg/L. There was a positive correlation between the concentration of 1,2-DCE in rat blood and the exposed level of 1,2-DCE.The equation of dose-response relationship was y=0.162x -195.8,r=0.982 2,P=0.003 and the precision of exposure experiments was 7.04% -13.15%. 1,2-DCE contents within 0.259 -2 587 µg/L showed a good linear relationship and the regression equation was y=47 901x -357 446, r= 0.999 8. When the blood containing 0.259 µg/L 1,2-DCE was determined for six times, the average peak/peak signal-to-noise ratio was 56.55. The limit of detection (LOD) was 0.014 µg/L and the limit of quantification (LOQ) was 0.046 µg/L. The within-run precision was 1.23% -2.76% and the between-run precision was 2.21% -4.64%. The average recovery rate was 93.3% - 98.6%. CONCLUSION: The concentration of 1,2-DCE in blood could be used as a biological monitoring indicator. The method of the concentration of 1,2-DCE in blood determining by HS-GC-MS was characterized by high sensitivity, wide linear range, small interference, high precision and easy operation.

[Establishment of a rat model of subacute toxic encephalopathy induced by 1, 2-dichloroethane].

OBJECTIVE: To establish a rat model of 1,2-dichloroethane (DCE)-induced subacute toxic encephalopathy. METHODS: Sixty Sprague-Dawley rats were randomly divided into five groups: negative control, positive control, low-dose DCE (1 472 mg/m(3)), middle-dose DCE (2 550 mg/m(3)), and high-dose DCE (4 418 mg/m(3)). The three DCE groups received static inhalation of DCE 6 hours a day for 6 consecutive days. The positive control group received intraperitoneal injection of lipopolysaccharide (5 mg/kg) and were sacrificed 8 hours after injection. Blood and brain tissue were collected, followed by determination of brain water content and HE staining for pathological examination of brain tissue. RESULTS: The rats in DCE groups suffered decreased body weight with increasing DCE dose (P < 0.01), and brain water content rose with increasing DCEdose. The brain water content of middle-dose DCE group (80.09 ± 0.14%) and high-dose DCE group (80.28±0.10%) increased significantly as compared with that of the negative control group (79.46±0.23%) (P < 0.001). Optical microscopy discovered loose structure and vasodilation in the brain tissue of middle-dose DCE group, indicating obvious brain edema; the high-dose DCE group and positive control group had spongiform and vacuolated brain tissues with severe vascular dilation, indicating severe brain edema. CONCLUSION: A rat model of subacute toxic encephalopathy induced by 1, 2-dichloroethane has been successfully established.

Individualized PEEP guided by EIT in patients undergoing general anesthesia: A systematic review and meta-analysis.

BACKGROUND: The determination of optimal positive end-expiratory pressure (PEEP) values in patients undergoing general anesthesia remains controversial. Electrical impedance tomography (EIT) directed individualized PEEP has emerged as a novel approach to PEEP setting and has garnered increasing attention. This meta-analysis aims to systematically assess the effect of EIT-guided PEEP setting compared to traditional fixed PEEP values or other PEEP titration strategies in patients undergoing general anesthesia. METHODS: A comprehensive search of electronic databases, including PubMed, Web of Science, EMBASE, and the Cochrane Library, was conducted from inception to January 2023, with no language restrictions. The search terms used were "EIT"and "PEEP" with their corresponding free words. Two researchers independently conducted literature screening, data extraction, and quality evaluation. The primary outcomes of interest were oxygenation index (OI), lung compliance, and number of postoperative pulmonary complications (PPCs). The secondary outcomes included mean arterial blood pressure (MAP) and number of vasoactive drug injections. RevMan 5.3 software was used to analyze the data and draw the forest plot, and Stata 14.2 software was used to conduct sensitivity analysis to assess the stability of the results. RESULTS: 5 studies involving 272 participants were included in this meta-analysis. Our findings suggest that EIT-guided individualized PEEP setting is superior to traditional fixed PEEP values and other individualized PEEP titration methods in terms of intraoperative OI(OR = 95.73, 95%CI: (49.10, 142.37); P < 0.0001) and lung compliance(OR = 7.69, 95%CI: (5.55, 9.83); P < 0.00001), without affecting intraoperative hemodynamic parameters such as MAP(OR = 2.07, 95%CI: (-1.00, 5.13); P = 0.19) and the number of intravenous vasoactive drugs(OR = 1.22, 95%CI: (0.68, 2.21); P = 0.51) or increasing the incidence of postoperative PPCs(OR = 0.87, 95%CI: (0.41, 1.82); P = 0.71). CONCLUSIONS: Our meta-analysis suggests potential benefits of EIT-guided individualized PEEP setting in improving intraoperative oxygenation and lung compliance in patients undergoing general anesthesia. However, further research is needed to establish conclusive evidence, and caution should be exercised in interpreting these findings as the current literature remains inconclusive regarding the impact on intraoperative hemodynamics and postoperative complications.

Plasma metabolomic profile in orthostatic intolerance children with high levels of plasma homocysteine.

BACKGROUND: Orthostatic intolerance, which includes vasovagal syncope and postural orthostatic tachycardia syndrome, is common in children and adolescents. Elevated plasma homocysteine levels might participate in the pathogenesis of orthostatic intolerance. This study was designed to analyze the plasma metabolomic profile in orthostatic intolerance children with high levels of plasma homocysteine. METHODS: Plasma samples from 34 orthostatic intolerance children with a plasma homocysteine concentration > 9 µmol/L and 10 healthy children were subjected to ultra-high-pressure liquid chromatography and quadrupole-time-of-flight mass spectrometry analysis. RESULTS: A total of 875 metabolites were identified, 105 of which were significantly differential metabolites. Choline, 1-stearoyl-2-linoleoyl-sn-glycero-3-phosphocholine, 1-(1Z-octadecenyl)-2-(4Z,7Z,10Z,13Z,16Z,19Z-docosahexaenoyl)-sn-glycero-3-phosphocholine, histidine, isocitric acid, and DL-glutamic acid and its downstream metabolites were upregulated, whereas 1-palmitoyl-sn-glycero-3-phosphocholine, 1-stearoyl-sn-glycerol 3-phosphocholine, sphingomyelin (d18:1/18:0), betaine aldehyde, hydroxyproline, and gamma-aminobutyric acid were downregulated in the orthostatic intolerance group compared with the control group. All these metabolites were related to choline and glutamate. Heatmap analysis demonstrated a common metabolic pattern of higher choline, 1-stearoyl-2-linoleoyl-sn-glycero-3-phosphocholine, and DL-glutamic acid, and lower sphingomyelin (d18:1/18:0), 1-stearoyl-sn-glycerol 3-phosphocholine, and 1-palmitoyl-sn-glycero-3-phosphocholine in patients with certain notable metabolic changes (the special group) than in the other patients (the common group). The maximum upright heart rate, the change in heart rate from the supine to the upright position, and the rate of change in heart rate from the supine to the upright position of vasovagal syncope patients were significantly higher in the special group than in the common group (P < 0.05). Choline, 1-stearoyl-2-linoleoyl-sn-glycero-3-phosphocholine, and DL-glutamic acid were positively correlated with the rate of change in heart rate from the supine to the upright position in vasovagal syncope patients (P < 0.05). CONCLUSIONS: The levels of choline-related metabolites and glutamate-related metabolites changed significantly in orthostatic intolerance children with high levels of plasma homocysteine, and these changes were associated with the severity of illness. These results provided new light on the pathogenesis of orthostatic intolerance.

[Investigation of screening methods for identifying population susceptible to noise-induced hearing loss].

OBJECTIVE: To investigate the screening methods for identifying the populations susceptible and resistant to noise-induced hearing loss (NIHL) and to provide a reference for future research. METHODS: Workers who were exposed to 75 ∼ 120 dB noise in enterprises were included in the study. Field investigation of occupational health was conducted; workers' basic information and data on hearing threshold levels were collected. Paired chi-square test was used to compare each two of three screening methods, which were used at home and abroad to identify noise-susceptible and noise-sensitive populations, in terms of noise exposure level, general information, and noise-induced hearing threshold shift. RESULTS: There were no significant differences in the noise exposure level, basic information, and left and right ears' hearing threshold levels of noise-susceptible and noise-sensitive populations between each two of the three screening methods (P > 0.05), according to the paired chi-square test. However, high-frequency hearing threshold had statistically significant difference among the three methods. As a whole, methods B and C were superior to method A. CONCLUSION: The workers in China are younger than before, with more awareness of self-protection, and individual protection is enhanced in them. Currently, method B is more suitable for screening out the population susceptible to NIHL in China.

A lightweight fetal distress-assisted diagnosis model based on a cross-channel interactive attention mechanism.

Fetal distress is a symptom of fetal intrauterine hypoxia, which is seriously harmful to both the fetus and the pregnant woman. The current primary clinical tool for the assessment of fetal distress is Cardiotocography (CTG). Due to subjective variability, physicians often interpret CTG results inconsistently, hence the need to develop an auxiliary diagnostic system for fetal distress. Although the deep learning-based fetal distress-assisted diagnosis model has a high classification accuracy, the model not only has a large number of parameters but also requires a large number of computational resources, which is difficult to deploy to practical end-use scenarios. Therefore, this paper proposes a lightweight fetal distress-assisted diagnosis network, LW-FHRNet, based on a cross-channel interactive attention mechanism. The wavelet packet decomposition technique is used to convert the one-dimensional fetal heart rate (FHR) signal into a two-dimensional wavelet packet coefficient matrix map as the network input layer to fully obtain the feature information of the FHR signal. With ShuffleNet-v2 as the core, a local cross-channel interactive attention mechanism is introduced to enhance the model's ability to extract features and achieve effective fusion of multichannel features without dimensionality reduction. In this paper, the publicly available database CTU-UHB is used for the network performance evaluation. LW-FHRNet achieves 95.24% accuracy, which meets or exceeds the classification results of deep learning-based models. Additionally, the number of model parameters is reduced many times compared with the deep learning model, and the size of the model parameters is only 0.33 M. The results show that the lightweight model proposed in this paper can effectively aid in fetal distress diagnosis.

PEEP titration by EIT strategies for patients with ARDS: A systematic review and meta-analysis.

OBJECTIVE: To determine which method of Positive End-expiratory Pressure (PEEP) titration is more useful, and to establish an evidence base for the clinical impact of Electrical Impedance Tomography (EIT) based individual PEEP setting which appears to be a promising method to optimize PEEP in Acute Respiratory Distress Syndrome (ARDS) patients. DESIGN: A systematic review and meta-analysis. SETTING: 4 databases (PUBMED, EMBASE, Web Of Science, and the Cochrane Library) from 1980 to December 2020 were performed. PARTICIPANTS: Randomized clinical trials patients with ARDS. MAIN VARIABLES: PaO2/FiO2-ratio and respiratory system compliance. INTERVENSION: The quality of the studies was assessed with the Cochrane risk and bias tool. RESULTS: 8 trials, including a total of 222 participants, were eligible for analysis. Meta-analysis demonstrates a significantly EIT-based individual PEEP setting for patients receiving higher PaO2/FiO2 ratio as compared to other PEEP titration strategies [5 trials, 202 patients, SMD 0.636, (95% CI 0.364-0.908)]. EIT-drived PEEP titration strategy did not significantly increase respiratory system compliance when compared to other peep titration strategies, [7 trials, 202 patients, SMD -0.085, (95% CI -0.342 to 0.172)]. CONCLUSIONS: The benefits of PEEP titration with EIT on clinical outcomes of ARDS in placebo-controlled trials probably result from the visible regional ventilation of EIT. These findings offer clinicians and stakeholders a comprehensive assessment and high-quality evidence for the safety and efficacy of the EIT-based individual PEEP setting as a superior option for patients who undergo ARDS.

Reconstruction of Missing Samples in Antepartum and Intrapartum FHR Measurements Via Mini-Batch-Based Minimized Sparse Dictionary Learning.

Fetal Heart Rate (FHR), an important recording in Cardiotocography (CTG)-based fetal health status monitoring, is the only information that clinical obstetricians can directly obtain and use. A challenge, however, is that missing samples are very common in FHR due to various causes such as fetal movements and sensor malfunctions. The aim is the development of an inpainting tool which is suitable for different missing lengths q and various total missing percentages Q, as well as for use in online mode. This study focused on two major impediments to existing inpainting methods: the longer the missing length, the more difficult it is to recover with mathematical methods; the reliance on tens of thousands of training samples, and the computational burden caused by full batch-based dictionary learning algorithms. We present a regularized minimization approach to signal recovery, which combines a L0.6 - norm minimized sparse dictionary learning algorithm (MSDL) and a model optimization strategy for using a mini-batch version for signal recovery. Using 100 FHR recordings with 2 protocols designed to simulate missing clinical data scenarios, the combined method performed favorably in terms of 5 data analysis metrics and 3 clinical indicators. Comparing 4 inpainting methods, we were able to prove the superiority of the proposed algorithm for both large q and large Q. The experimental results showed the lowest values (2.64 (MAE), 4.68 (RMSE)) when Q = 5% with short interval lengths. The developed architecture provides a reference value for the practical application of recovering missing samples online.

Anti-fatigue effect of phlorizin on exhaustive exercise-induced oxidative injury mediated by Nrf2/ARE signaling pathway in mice.

Oxidative stress plays a crucial role in fatigue, thus it is of significance to develop safe and efficient antioxidant to prevent fatigue. Phlorizin (PHZ) is a major active ingredient of dihydrochalcone from Lithocarpus polystachyus Rehd., which has already been approved as a new food material in China since 2017. The current study was designed to investigate the effect of PHZ on fatigue, and further to elucidate its possible underlying mechanism. Our results revealed that PHZ exerted beneficial effect on exhaustive exercise-induced fatigue in mice, as reflected by rotarod test and exhaustive swimming test. Moreover, PHZ also effectively decreased the levels of blood urea nitrogen, creatine kinase and plasma lactic acid, increased the liver glycogen and skeletal muscle glycogen of fatigued mice, as evidenced by enzyme linked immunosorbent assay. PHZ balanced the redox status through reducing generation of reactive oxygen species, enhancing the activities of antioxidative enzymes. Furthermore, PHZ not only increased the ratio of Bcl2/Bax, but also decreased the level of cleaved-caspase 3. Notably, PHZ facilitated nuclear factor erythroid 2-related factor 2 (Nrf2) translocated from cytoplasm to nucleus, and up-regulated its downstream antioxidant response element including heme oxygenase-1 and NADPH quinone oxidoreductase-1. Intriguingly, PHZ directly bound to Nrf2, as evidenced by molecular docking, and the anti-fatigue effects of PHZ were almost abolished in Nrf2 deficient mice. In summary, our findings suggest that PHZ might be a natural occurring antioxidant with safety profile to relieve fatigue via targeting Nrf2 to inhibit apoptosis.

Multimodal learning for fetal distress diagnosis using a multimodal medical information fusion framework.

Cardiotocography (CTG) monitoring is an important medical diagnostic tool for fetal well-being evaluation in late pregnancy. In this regard, intelligent CTG classification based on Fetal Heart Rate (FHR) signals is a challenging research area that can assist obstetricians in making clinical decisions, thereby improving the efficiency and accuracy of pregnancy management. Most existing methods focus on one specific modality, that is, they only detect one type of modality and inevitably have limitations such as incomplete or redundant source domain feature extraction, and poor repeatability. This study focuses on modeling multimodal learning for Fetal Distress Diagnosis (FDD); however, exists three major challenges: unaligned multimodalities; failure to learn and fuse the causality and inclusion between multimodal biomedical data; modality sensitivity, that is, difficulty in implementing a task in the absence of modalities. To address these three issues, we propose a Multimodal Medical Information Fusion framework named MMIF, where the Category Constrained-Parallel ViT model (CCPViT) was first proposed to explore multimodal learning tasks and address the misalignment between multimodalities. Based on CCPViT, a cross-attention-based image-text joint component is introduced to establish a Multimodal Representation Alignment Network model (MRAN), explore the deep-level interactive representation between cross-modal data, and assist multimodal learning. Furthermore, we designed a simple-structured FDD test model based on the highly modal alignment MMIF, realizing task delegation from multimodal model training (image and text) to unimodal pathological diagnosis (image). Extensive experiments, including model parameter sensitivity analysis, cross-modal alignment assessment, and pathological diagnostic accuracy evaluation, were conducted to show our models' superior performance and effectiveness.