Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.

BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combining chest X-ray (CXR) and electronic health record (EHR) data to screen patients with abnormal N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in emergency departments. METHODS: Using the open-source dataset MIMIC-IV and MIMICCXR, the study population consisted of 1,432 patients and 1,833 pairs of CXRs and EHRs. We processed the CXRs, extracted relevant features through lung-heart masks, and combined these with the vital signs at triage to predict corresponding NT-proBNP levels. RESULTS: The proposed method achieved a 0.89 area under the receiver operating characteristic curve by fusing predictions from single-modality models of heart size ratio, radiomic features, CXR, and the region of interest in the CXR. The model can accurately predict dyspneic patients with abnormal NT-proBNP concentrations, allowing physicians to reduce the risks associated with inappropriate treatment. CONCLUSION: The study provided new image features related to AHF and offered insights into future research directions. Overall, these models have great potential to improve patient outcomes and reduce risks in emergency departments.

Metabolomic analysis of Agkistrodon haly venom poisoning mouse treatment by Jidesheng snake pill based on GC-MS.

Introduction: Snakebites are acute systemic toxic diseases caused by snake venom entering the body through wounds. Failure to use antivenom immediately and difficulty in obtaining antivenoms are frequently responsible for worsening disease. Traditional Chinese medicine is commonly used to supplement and replace antivenom in treating snakebites. The Jidesheng snake pill (JDS) is a widely used traditional Chinese medicine that has achieved good clinical therapeutic effects; however, its mechanism remains unclear. Therefore, metabolomics techniques were employed to explore the pathophysiological mechanisms of JDS treatment of Agkistrodon halys (Ah) snake venom-poisoned mice. Methods: The Ah group mouse model was established by intramuscular injection of Ah venom into the hind legs of the mice. The Ah venom + JDS group model was established using JDS after the affected area was treated with Ah venom. Hematoxylin and eosin (HE) staining was used to evaluate the severity of gastrocnemius injury. Quantitative polymerase chain reaction (qPCR) was utilized to detect the mRNA expression of vascular cell adhesion molecule-1 (VCAM-1), muscle-specific creatine kinase (CKM), thrombin antithrombin complex (TAT), and tumor necrosis factor-alpha (TNF-α). Gas chromatography-mass spectrometry (GC-MS) was performed with multivariate statistical analysis to provide new insights into the global metabolic profile of Ah venom-poisoned mice. Results: HE staining revealed increased red cell necrosis, local hemorrhage, and neutrophil infiltration in the Ah venom group than in the control group. Several compounds were identified, including lipids, amino acids, peptides, and organooxygen. Eighty differential metabolites were screened between the control group and the Ah venom group, and 24 were screened between the Ah venom and JDS groups. The mechanism of Ah venom poisoning in mice may involve aminoacyl-tRNA biosynthesis, various amino acid metabolism disorders, tricarboxylic acid circulation disorders, and abnormal fatty acid metabolism. JDS may reduce symptoms by affecting long-chain fatty acid and amino acid metabolism and promoting nicotinamide-nicotinamide metabolism. Conclusion: Our results suggest that metabolomics has huge prospects for elucidating the pathophysiology of Agkistrodon haly venom poisoning and therapeutic mechanisms of JDS.

Circulating extracellular vesicle-derived miR-1299 disrupts hepatic glucose homeostasis by targeting the STAT3/FAM3A axis in gestational diabetes mellitus.

BACKGROUND: Extracellular vesicles (EVs) are membrane-enclosed structures containing lipids, proteins, and RNAs that play a crucial role in cell-to-cell communication. However, the precise mechanism through which circulating EVs disrupt hepatic glucose homeostasis in gestational diabetes mellitus (GDM) remains unclear. RESULTS: Circulating EVs isolated from human plasma were co-cultured with mammalian liver cells to investigate the potential induction of hepatic insulin resistance by GDM-EVs using glucose output assays, Seahorse assays, metabolomics, fluxomics, qRT-PCR, bioinformatics analyses, and luciferase assays. Our findings demonstrated that hepatocytes exposed to GDM-EVs exhibited increased gluconeogenesis, attenuated energy metabolism, and upregulated oxidative stress. Particularly noteworthy was the discovery of miR-1299 as the predominant miRNA in GDM-EVs, which directly targeting the 3'-untranslated regions (UTR) of STAT3. Our experiments involving loss- and gain-of-function revealed that miR-1299 inhibits the insulin signaling pathway by regulating the STAT3/FAM3A axis, resulting in increased insulin resistance through the modulation of mitochondrial function and oxidative stress in hepatocytes. Moreover, experiments conducted in vivo on mice inoculated with GDM-EVs confirmed the development of glucose intolerance, insulin resistance, and downregulation of STAT3 and FAM3A. CONCLUSIONS: These results provide insights into the role of miR-1299 derived from circulating GDM-EVs in the progression of insulin resistance in hepatic cells via the STAT3/FAM3A axis and downstream metabolic reprogramming.

Excessive palmitic acid disturbs macrophage α-ketoglutarate/succinate metabolism and causes adipose tissue insulin resistance associated with gestational diabetes mellitus.

Abnormal polarization of adipose tissue macrophages (ATMs) results in low-grade systemic inflammation and insulin resistance (IR), potentially contributing to the development of diabetes. However, the underlying mechanisms that regulate the polarization of ATMs associated with gestational diabetes mellitus (GDM) remain unclear. Thus, we aimed to determine the effects of abnormal fatty acids on macrophage polarization and development of insulin resistance in GDM. Levels of fatty acids and inflammation were assessed in the serum samples and adipose tissues of patients with GDM. An in vitro cell model treated with palmitic acid was established, and the mechanisms of palmitic acid in regulating macrophage polarization was clarified. The effects of excessive palmitic acid on the regulation of histone methylations and IR were also explored in the high-fat diet induced GDM mice model. We found that pregnancies with GDM were associated with increased levels of serum fatty acids, and inflammation and IR in adipose tissues. Increased palmitic acid could induce mitochondrial dysfunction and excessive ROS levels in macrophages, leading to abnormal cytoplasmic and nuclear metabolism of succinate and α-ketoglutarate (αKG). Specifically, a decreased nuclear αKG/succinate ratio could attenuate the enrichment of H3K27me3 at the promoters of pro-inflammatory cytokines, such as IL-1ß, IL-6, and TNF-α, leading to cytokine secretion. Importantly, GDM mice treated with GSK-J4, an inhibitor of histone lysine demethylase, were protected from abnormal pro-inflammatory macrophage polarization and excessive production of pro-inflammatory cytokines. Our findings highlight the importance of the metabolism of αKG and succinate as transcriptional modulators in regulating the polarization of ATMs and the insulin sensitivity of adipose tissue, ensuring a normal pregnancy. This novel insight sheds new light on gestational fatty acid metabolism and epigenetic alterations associated with GDM.

The attenuation of gut microbiota-derived short-chain fatty acids elevates lipid transportation through suppression of the intestinal HDAC3-H3K27ac-PPAR-γ axis in gestational diabetes mellitus.

Gut flora is considered to modulate lipid transport from the intestine into the bloodstream, and thus may potentially participate in the development of GDM. Although previous studies have shown that the intestinal microbiota influences lipid transport and metabolism in GDM, the precise mechanisms remain elusive. To address this, we used a high-fat diet (HFD)-induced GDM mouse model and conducted 16s rRNA sequencing and fecal metabolomics to assess gut microbial community shifts and associated metabolite changes. Western blot, ELISA, and chromatin immunoprecipitation (ChIP) were utilized to elucidate how gut microbiota affect intestinal lipid transport and the insulin sensitivity of hepatic, adipose, and skeletal muscle tissues. We found that HFD impaired the oral glucose tolerance test (OGTT) and insulin tolerance test (ITT) in pregnant mice. 16s rRNA sequencing demonstrated profound compositional changes, especially in the relative abundances of Firmicutes and Bacteroidetes. Metabolomics analysis presented a decline in the concentration of short-chain fatty acids (SCFAs) in the GDM group. Western blot analyses showed an upregulation of HDAC3 and a concurrent reduction in H3K27 acetylation in the intestine. ChIP-qPCR showed that PPAR-γ was inhibited, which in turn activated lipid-transporter CD36. ELISA and insulin signaling pathway detection in insulin-target organs showed high concentrations of circulating fatty acids and triglycerides and insulin resistance in insulin-target organs. Our results suggest that gut microbiota is closely associated with the development of GDM, partly because decreased gut flora-associated SCFAs activate CD36 by suppressing the HDAC3-H3K27ac-PPAR-γ axis to transport excessive fatty acids and triglycerides into blood circulation, thereby dysregulating the insulin sensitivity of insulin target organs.

Associations of air pollution exposures in preconception and pregnancy with birth outcomes and infant neurocognitive development: analysis of the Complex Lipids in Mothers and Babies (CLIMB) prospective cohort in Chongqing, China.

OBJECTIVES: To investigate the associations of traffic-related air pollution exposures in early pregnancy with birth outcomes and infant neurocognitive development. DESIGN: Cohort study. SETTING: Eligible women attended six visits in the maternity clinics of two centres, the First Affiliated Hospital of Chongqing Medical University and Chongqing Health Centre for Women and Children. PARTICIPANTS: Women who were between 20 and 40 years of age and were at 11-14 weeks gestation with a singleton pregnancy were eligible for participation. Women were excluded if they had a history of premature delivery before 32 weeks of gestation, maternal milk allergy or aversion or severe lactose intolerance. 1273 pregnant women enrolled in 2015-2016 and 1174 live births were included in this analysis. EXPOSURES: Air pollution concentrations at their home addresses, including particulate matter with diameter ≤2.5 µm (PM2.5) and nitrogen dioxide (NO2), during pre-conception and each trimester period were estimated using land-use regression models. OUTCOME MEASURES: Birth outcomes (ie, birth weight, birth length, preterm birth, low birth weight, large for gestational age and small for gestational age (SGA) status) and neurodevelopment outcomes measured by the Chinese version of Bayley Scales of Infant Development. RESULTS: An association between SGA and per-IQR increases in NO2 was found in the first trimester (OR: 1.57, 95% CI: 1.06 to 2.32) and during the whole pregnancy (OR: 1.33, 99% CI: 1.01 to 1.75). Both PM2.5 and NO2 exposure in the 90 days prior to conception were associated with lower Psychomotor Development Index scores (ß: -6.15, 95% CI: -8.84 to -3.46; ß: -2.83, 95% CI: -4.27 to -1.39, respectively). Increased NO2 exposure was associated with an increased risk of psychomotor development delay during different trimesters of pregnancy. CONCLUSIONS: Increased exposures to NO2 during pregnancy were associated with increased risks of SGA and psychomotor development delay, while increased exposures to both PM2.5 and NO2 pre-conception were associated with adverse psychomotor development outcomes at 12 months of age. TRIAL REGISTRATION NUMBER: ChiCTR-IOR-16007700.

Human Amniotic Epithelial Cells Improve Uterine Spiral Artery Remodeling to Ameliorate Preeclampsia in a Rat Model.

Preeclampsia (PE) is a multisystem pregnancy disorder characterized by impaired remodeling of placental spiral arteries, which leads to the release of pro-inflammatory cytokines and anti-angiogenic agents. However, treatment options for PE are limited, with termination of pregnancy being the only curative option. In this work, we investigated the effects of human amniotic epithelial cells (hAECs) in PE rat model. The rats were induced with Lipopolysaccharide (LPS) on gestational day (GD) 14.5 followed by injection of hAECs and human umbilical cord mesenchymal stem cells (hUC-MSCs) 24 hours later. The hAECs treatment resulted in a reduction in blood pressure and proteinuria in the PE rat model. Futhermore, hAECs treatmentdecreased levels of pro-inflammatory cytokines, reduced inflammatory cells aggregation, and alleviated the damage to placental spiral arteries by downregulating the expression of anti-angiogenic factor and upregulating proangiogenic factor. In vitro experiments comfirmed that hAECs treatment restored the proliferation, migration, and angiogenesis of LPS-damaged human umbilical vein endothelial cells (hUVECs). Additionally, hAECs treatmenthad positive effects on fetal weight and neurological development in the PE group, with no negative effects onthe physical development or fertility of offspring rats. These results suggested that hAECs transplantation may be a novel adjuvant therapeutic strategy for PE by reducing the inflammatory andenhancing placental spiral artery angiogenesis.

Gut dysbiosis contributes to SCFAs reduction-associated adipose tissue macrophage polarization in gestational diabetes mellitus.

AIMS: The prevalence of gestational diabetes mellitus (GDM) has spurred investigations into various interconnected factors, among which gut dysbiosis is notably prominent. Although gut dysbiosis is strongly associated with GDM, the specific role of the gut microbiome in the pathogenesis of GDM remains unknown. This study aims to explore the pathogenesis of GDM from gut microbiota. MATERIALS AND METHODS: In our study, we constructed two GDM mice models: one induced by a high-fat diet (HFD) and the other through fecal microbiota transplantation (FMT) from GDM patients. In vitro, we used a co-culture system of RAW264.7 and 3T3-L1 adipocytes. KEY FINDINGS: We induced a GDM-like state in pregnant mice by FMT from GDM patients, which was consistent with the HFD model. A potential mechanism identified involves the diminished abundance of SCFA-producing microbiota, which reduces SCFAs, particularly propionic acid and butyric acid. In vitro, butyric and propionic acids were observed to alleviate LPS-induced TLR4-NF-κB activation, thereby reducing inflammation levels and inhibiting adipose insulin resistance via the PI3K/AKT signaling pathway. This reduction appears to trigger the polarization of adipose tissue macrophages toward M1 and promote insulin resistance in adipose tissue. SIGNIFICANCE: Our study fills this knowledge gap by finding that alterations in gut microbiota have an independent impact on hyperglycemia and insulin resistance in the GDM state. In vivo and in vitro, gut dysbiosis is linked to adipose tissue inflammation and insulin resistance via the bacterial product SCFAs in the GDM state, providing new insights into the pathogenesis of GDM.

Application of a feedforward control-based intervention for preventing hypothermia in trauma patients in a pre-hospital emergency setting.

OBJECTIVE: To investigate the efficacy of a feedforward control-based intervention strategy for preventing hypothermia among trauma patients during pre-hospital emergency care. METHODS: We conducted a retrospective analysis comparing trauma patients treated before and after implementing the intervention, with 40 cases in each group. All patients received emergency care from the Fuzhou Emergency Center on the scene. Multivariate analysis was used to explore the risk factors for hypothermia. The effective rate, incidence of adverse reactions, quality of body temperature management, medical staff's knowledge, attitudes, and behaviors regarding mild hypothermia prevention, coagulation function, treatment time at various stages, prognosis score, and treatment situation were compared between the two groups. RESULTS: The adverse reactions, intervention methods, and degree of cognitive improvement were influencing factors for hypothermia. The effective rate (92.50%) in the feedforward control group was higher than that in the non-feedforward control group (65.00%), with a lower incidence of adverse reactions (2.50%). The temperature management quality score of the feedforward control group (6.23±0.62) was higher. The feedforward control group achieved a higher quality score for temperature management (6.23±0.62) and exhibited a greater understanding of hypothermia prevention among trauma patients (P<0.05). Compared to the non-feedforward control group, the feedforward control group showed improved coagulation function, better performance in treatment time at each node, and higher prognosis scores. CONCLUSION: The intervention model based on feedforward control can effectively improve the standard of pre-hospital emergency care and prevent the incidence of hypothermia in trauma patients.

The Influence of Sidedness in Unilateral Cleft Lip and Palate on Mid Facial Growth at Five Years of Age.

OBJECTIVE: To determine whether facial growth at five years is different for children with a left versus right sided cleft lip and palate. DESIGN: Retrospective cohort study. SETTING: Seven UK regional cleft centres. PATIENTS: Patients born between 2000-2014 with a complete unilateral cleft lip and palate (UCLP). MAIN OUTCOMES MEASURE: 5-Year-Old's Index scores. RESULTS: 378 children were included. 256 (68%) had a left sided UCLP and 122 (32%) had a right sided UCLP. 5-Year-Old's index scores ranged from 1 (good) to 5 (poor). There was a higher proportion of patients getting good scores (1 and 2) in left UCLP (43%) compared to right UCLP (37%) but there was weak evidence for a difference (Adjusted summary odds ratio 1.27, 95% CI 0.87 to 1.87; P = .22). CONCLUSIONS: Whilst maxillary growth may be different for left versus right sided UCLP, definitive analysis requires older growth indices and arch forms.

Unraveling implicit human behavioral effects on dynamic characteristics of Covid-19 daily infection rates in Taiwan.

We investigate the dynamic characteristics of Covid-19 daily infection rates in Taiwan during its initial surge period, focusing on 79 districts within the seven largest cities. By employing computational techniques, we extract 18 features from each district-specific curve, transforming unstructured data into structured data. Our analysis reveals distinct patterns of asymmetric growth and decline among the curves. Utilizing theoretical information measurements such as conditional entropy and mutual information, we identify major factors of order-1 and order-2 that influence the peak value and curvature at the peak of the curves, crucial features characterizing the infection rates. Additionally, we examine the impact of geographic and socioeconomic factors on the curves by encoding each of the 79 districts with two binary characteristics: North-vs-South and Urban-vs-Suburban. Furthermore, leveraging this data-driven understanding at the district level, we explore the fine-scale behavioral effects on disease spread by examining the similarity among 96 age-group-specific curves within urban districts of Taipei and suburban districts of New Taipei City, which collectively represent a substantial portion of the nation's population. Our findings highlight the implicit influence of human behaviors related to living, traveling, and working on the dynamics of Covid-19 transmission in Taiwan.

C-Reactive Protein-Albumin Ratio (CAR): A More Promising Inflammation-Based Prognostic Marker for Patients Undergoing Curative Hepatectomy for Hepatocellular Carcinoma.

Background: Systemic inflammatory response is a hallmark of cancer and plays a significant role in the development and progression of various malignant tumors. This research aimed to estimate the prognostic function of the C-reactive protein-albumin ratio (CAR) in patients undergoing hepatectomy for hepatocellular carcinoma (HCC) and compare it with other inflammation-based prognostic scores, including the neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, monocyte-lymphocyte ratio, systemic immune inflammation index, prognostic index, Glasgow prognostic score, and modified Glasgow prognostic score. Methods: Retrospective analysis was conducted on data from 1039 HCC cases who underwent curative liver resection. The prognostic performance of CAR was compared with other scores using the area under the time-dependent receiver operating characteristic (t-ROC) curve. Multivariable Cox regression analyses were performed to confirm independent predictors for disease-free survival (DFS) and overall survival (OS). Results: The area under the t-ROC curve for CAR in the evaluation of DFS and OS was significantly greater than that of other scores and alpha-fetoprotein (AFP). Patients were stratified based on the optimal cut-off value of CAR, and the data revealed that both DFS and OS were remarkably worse in the high-CAR set compared to the low-CAR set. Multivariable Cox analysis demonstrated that CAR was an independent prognostic parameters for assessing DFS and OS. Regardless of AFP levels, all patients were subsequently divided into significantly different subgroups of DFS and OS based on CAR risk stratification. Similar results were observed when applying CAR risk stratification to other scoring systems. CAR also showed good clinical applicability in patients with different clinical features. Conclusion: CAR is a more effective inflammation-based prognostic marker than other scores and AFP in predicting DFS as well as OS among patients with HCC after curative hepatectomy.

Manchester Intermittent Diet in Gestational Diabetes Acceptability Study (MIDDAS-GDM): a two-arm randomised feasibility protocol trial of an intermittent low-energy diet (ILED) in women with gestational diabetes and obesity in Greater Manchester.

INTRODUCTION: The prevalence of gestational diabetes mellitus (GDM) is rising in the UK and is associated with maternal and neonatal complications. National Institute for Health and Care Excellence guidance advises first-line management with healthy eating and physical activity which is only moderately effective for achieving glycaemic targets. Approximately 30% of women require medication with metformin and/or insulin. There is currently no strong evidence base for any particular dietary regimen to improve outcomes in GDM. Intermittent low-energy diets (ILEDs) are associated with improved glycaemic control and reduced insulin resistance in type 2 diabetes and could be a viable option in the management of GDM. This study aims to test the safety, feasibility and acceptability of an ILED intervention among women with GDM compared with best National Health Service (NHS) care. METHOD AND ANALYSIS: We aim to recruit 48 women with GDM diagnosed between 24 and 30 weeks gestation from antenatal clinics at Wythenshawe and St Mary's hospitals, Manchester Foundation Trust, over 13 months starting in November 2022. Participants will be randomised (1:1) to ILED (2 low-energy diet days/week of 1000 kcal and 5 days/week of the best NHS care healthy diet and physical activity advice) or best NHS care 7 days/week until delivery of their baby. Primary outcomes include uptake and retention of participants to the trial and adherence to both dietary interventions. Safety outcomes will include birth weight, gestational age at delivery, neonatal hypoglycaemic episodes requiring intervention, neonatal hyperbilirubinaemia, admission to special care baby unit or neonatal intensive care unit, stillbirths, the percentage of women with hypoglycaemic episodes requiring third-party assistance, and significant maternal ketonaemia (defined as ≥1.0 mmol/L). Secondary outcomes will assess the fidelity of delivery of the interventions, and qualitative analysis of participant and healthcare professionals' experiences of the diet. Exploratory outcomes include the number of women requiring metformin and/or insulin. ETHICS AND DISSEMINATION: Ethical approval has been granted by the Cambridge East Research Ethics Committee (22/EE/0119). Findings will be disseminated via publication in peer-reviewed journals, conference presentations and shared with diabetes charitable bodies and organisations in the UK, such as Diabetes UK and the Association of British Clinical Diabetologists. TRIAL REGISTRATION NUMBER: NCT05344066.

The metabolic role of the CD73/adenosine signaling pathway in HTR-8/SVneo cells: A Double-Edged Sword?

The ecto-5'-nucleotidase (CD73)/adenosine signaling pathway has been reported to regulate tumor epithelial-mesenchymal transition (EMT), migration and proliferation. However, little is known about the metabolic mechanisms underlying its role in trophoblast proliferation and migration. In this study, we aimed to investigate the metabolic role of the CD73/adenosine signaling pathway on the proliferation and migration of trophoblast. We found that CD73 levels were upregulated in preeclamptic placentas compared with the placentas of normotensive pregnant women. EMT and migration of HTR-8/SVneo cells were enhanced when treated with a CD73 inhibitor (100 µM) in vitro. Conversely, excessive adenosine (25 or 50 µM) suppressed trophoblast cell EMT, migration and proliferation. RNA-seq, metabolomics and seahorse findings showed that adenosine treatment resulted in increased expression of PDK1, suppression of aerobic respiration, glycolysis and amino acids synthesis, as well as increased utilization of short-chain fatty acids (SCFAs). Furthermore, the 13C-adenosine isotope tracking experiment demonstrated that adenosine served as a carbon source for the tricarboxylic acid (TCA) cycle. Our results reveal the role of adenosine in regulating trophoblast energy metabolism is like a double-edged sword - either inhibiting aerobic respiration or supplementing carbon sources into metabolic flux. CD73/adenosine signaling regulated trophoblast EMT, migration, and proliferation by modulating energy metabolism. This study indicates that CD73/adenosine signaling potentially plays a role in the occurrence of placenta-derived diseases, including preeclampsia.

Parameter-Free State Estimation Based on Kalman Filter with Attention Learning for GPS Tracking in Autonomous Driving System.

GPS-based maneuvering target localization and tracking is a crucial aspect of autonomous driving and is widely used in navigation, transportation, autonomous vehicles, and other fields.The classical tracking approach employs a Kalman filter with precise system parameters to estimate the state. However, it is difficult to model their uncertainty because of the complex motion of maneuvering targets and the unknown sensor characteristics. Furthermore, GPS data often involve unknown color noise, making it challenging to obtain accurate system parameters, which can degrade the performance of the classical methods. To address these issues, we present a state estimation method based on the Kalman filter that does not require predefined parameters but instead uses attention learning. We use a transformer encoder with a long short-term memory (LSTM) network to extract dynamic characteristics, and estimate the system model parameters online using the expectation maximization (EM) algorithm, based on the output of the attention learning module. Finally, the Kalman filter computes the dynamic state estimates using the parameters of the learned system, dynamics, and measurement characteristics. Based on GPS simulation data and the Geolife Beijing vehicle GPS trajectory dataset, the experimental results demonstrated that our method outperformed classical and pure model-free network estimation approaches in estimation accuracy, providing an effective solution for practical maneuvering-target tracking applications.

Few-shot transfer learning for personalized atrial fibrillation detection using patient-based siamese network with single-lead ECG records.

The proliferation of wearable devices has allowed the collection of electrocardiogram (ECG) recordings daily to monitor heart rhythm and rate. For example, 24-hour Holter monitors, cardiac patches, and smartwatches are widely used for ECG gathering and application. An automatic atrial fibrillation (AF) detector is required for timely ECG interpretation. Deep learning models can accurately identify AFs if large amounts of annotated data are available for model training. However, it is impractical to request sufficient labels for ECG recordings for an individual patient to train a personalized model. We propose a Siamese-network-based approach for transfer learning to address this issue. A pre-trained Siamese convolutional neural network is created by comparing two labeled ECG segments from the same patient. We sampled 30-second ECG segments with a 50% overlapping window from the ECG recordings of patients in the MIT-BIH Atrial Fibrillation Database. Subsequently, we independently detected the occurrence of AF in each patient in the Long-Term AF Database. By fine-tuning the model with the 1, 3, 5, 7, 9, or 11 ECG segments ranging from 30 to 180 s, our method achieved macro-F1 scores of 96.84%, 96.91%, 96.97%, 97.02%, 97.05%, and 97.07%, respectively.

Probiotic Escherichia coli Nissle 1917-derived outer membrane vesicles modulate the intestinal microbiome and host gut-liver metabolome in obese and diabetic mice.

Introduction: Obesity and diabetes are common chronic metabolic disorders which can cause an imbalance of the intestinal flora and gut-liver metabolism. Several studies have shown that probiotics, including Escherichia coli Nissle 1917 (EcN), promote microbial balance and metabolic health. However, there are no studies on how EcN outer membrane vesicles (EcN-OMVs) influence the intestinal microflora and affect the metabolic disorders of obesity and diabetes. Methods: In this study, we evaluated the effects of EcN-OMVs on high-fat diet (HFD)-induced obesity and HFD + streptozotocin (STZ)-induced diabetes. Results: EcN-OMVs could reduce body weight, decrease blood glucose, and increase plasma insulin in obese mice. Similarly, EcN-OMVs treatment could modify the ratio of Firmicutes/Bacteroidetes in the gut, elevate intestinal short-chain fatty acid (SCFA)-producing flora, and influence the SCFA content of the intestine. Furthermore, the intestinal metabolites ornithine and fumaric acid, hepatic ω-6 unsaturated fatty acids, and SCFAs were significantly increased after administering EcN-OMVs. Discussion: Overall, this study showed that EcN-OMVs might act as post-biotic agents that could modulate gut-liver metabolism and ameliorate the pathophysiology of obesity and diabetes.

Hair and cord blood element levels and their relationship with air pollution, dietary intake, gestational diabetes mellitus, and infant neurodevelopment.

BACKGROUND & AIMS: Exposure to a range of elements, air pollution, and specific dietary components in pregnancy has variously been associated with gestational diabetes mellitus (GDM) risk or infant neurodevelopmental problems. We measured a range of pregnancy exposures in maternal hair and/or infant cord serum and tested their relationship to GDM and infant neurodevelopment. METHODS: A total of 843 pregnant women (GDM = 224, Non-GDM = 619) were selected from the Complex Lipids in Mothers and Babies cohort study. Forty-eight elements in hair and cord serum were quantified using inductively coupled plasma-mass spectrometry analysis. Binary logistic regression was used to estimate the associations between hair element concentrations and GDM risk, while multiple linear regression was performed to analyze the relationship between hair/cord serum elements and air pollutants, diet exposures, and Bayley Scales of infant neurodevelopment at 12 months of age. RESULTS: After adjusting for maternal age, BMI, and primiparity, we observed that fourteen elements in maternal hair were associated with a significantly increased risk of GDM, particularly Ta (OR = 9.49, 95% CI: 6.71, 13.42), Re (OR = 5.21, 95% CI: 3.84, 7.07), and Se (OR = 5.37, 95% CI: 3.48, 8.28). In the adjusted linear regression model, three elements (Rb, Er, and Tm) in maternal hair and infant cord serum were negatively associated with Mental Development Index scores. For dietary exposures, elements were positively associated with noodles (Nb), sweetened beverages (Rb), poultry (Cs), oils and condiments (Ca), and other seafood (Gd). In addition, air pollutants PM2.5 (LUR) and PM10 were negatively associated with Ta and Re in maternal hair. CONCLUSIONS: Our findings highlight the potential influence of maternal element exposure on GDM risk and infant neurodevelopment. We identified links between levels of these elements in both maternal hair and infant cord serum related to air pollutants and dietary factors.

Metabolomics analysis of serum metabolites during endometrial transformation: association with recurrent implantation failure in hormonal replacement therapy-frozen embryo transfers cycles.

PURPOSE: The purpose of this study was to investigate alterations in serum metabolites during endometrial transformation and possible associations with recurrent implantation failure (RIF) in hormonal replacement therapy (HRT)-frozen embryo transfer (FET) cycles. METHODS: We performed a prospective study involving 100 patients scheduled for HRT-FET cycles during January 2022 to April 2022. Blood serum samples were collected on the day of progesterone administration (dPA) and on the third day of progesterone administration (d3PA). Gas chromatography-mass spectrometry (GC-MS) analysis was performed to identify and quantify serum metabolites. A nested case-control study including 19 RIF patients and 19 matching controls was conducted to explore the predictive value of serum metabolites for RIF. Partial least squares discriminant analysis (PLS-DA) and receiver operating characteristic (ROC) curve analysis were performed to establish prediction models. MAIN RESULTS: We identified 105 serum metabolites, with 76 of them exhibiting significant alterations during the initial 3 days of endometrial transformation. Metabolites involved in amino acid metabolism and tricarboxylic acid (TCA) cycle showed lower levels during endometrial transformation. In the nested case-control study, the prediction model based on the ratio of serum metabolites between d3PA and dPA showed the highest area under the ROC curve (AUC), accuracy, and R2 and Q2 values. Eight metabolites, including indol-3-propionic acid, beta-alanine, myristoleic acid, malic acid, indole, DL-isocitric acid, proline, and itaconic acid, exhibited high predictive values for RIF. CONCLUSION: This study demonstrates alterations in serum metabolites during endometrial transformation, particularly in amino acid metabolism and TCA cycle. The identified metabolites, especially indol-3-propionic acid and malic acid, show potential as predictive markers for RIF. These findings contribute to a better understanding of the metabolic changes associated with endometrial receptivity and provide insights for the development of personalized approaches to improve implantation outcomes in FET cycles.