The Plaque Analysis Classifies the Coronary Artery Disease-Reporting and Data System (CAD-RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification.

BACKGROUND: The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve. OBJECTIVE: To analyze plaque features of varying severity in patients with a combination of CAD-RADS stenosis and plaque burden categorization and establish a random forest classification model. METHODS: The data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD-RADS: CAD-RADS 1-2 + P0-2, CAD-RADS 3-4B + P0-2, and CAD-RADS 3-4B + P3-4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance. RESULTS: A total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT-FFR) (H = 23.921, p < 0.001), the volume of lipid component (H = 12.996, p = 0.002), the volume of fibro-lipid component (H = 8.692, p = 0.013), the proportion of lipid component volume (H = 22.038, p < 0.001), the proportion of fibro-lipid component volume (H = 11.731, p = 0.003), the proportion of calcification component volume (H = 11.049, p = 0.004), and plaque type (χ2 = 18.110, p = 0.001) was statistically significant. CONCLUSION: CT-FFR, volume and proportion of lipid and fibro-lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD-RADS stenosis + plaque burden classification, especially CT-FFR, volume, and proportion of lipid and fibro-lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).

Q negatively regulates wheat salt tolerance through directly repressing the expression of TaSOS1 and reactive oxygen species scavenging genes.

The Q transcription factor plays important roles in improving multiple wheat domestication traits such as spike architecture, threshability and rachis fragility. However, whether and how it regulates abiotic stress adaptation remain unclear. We found that the transcriptional expression of Q can be induced by NaCl and abscisic acid treatments. Using the q mutants generated by CRISPR/Cas9 and Q overexpression transgenic lines, we showed that the domesticated Q gene causes a penalty in wheat salt tolerance. Then, we demonstrated that Q directly represses the transcription of TaSOS1-3B and reactive oxygen species (ROS) scavenging genes to regulate Na+ and ROS homeostasis in wheat. Furthermore, we showed that wheat salt tolerance protein TaWD40 interacts with Q to competitively interfere with the interaction between Q and the transcriptional co-repressor TaTPL. Taken together, our findings reveal that Q directly represses the expression of TaSOS1 and some ROS scavenging genes, thus causing a harmful effect on wheat salt tolerance.

Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study.

BACKGROUND: This study investigates the associations between air pollution and colorectal cancer (CRC) risk and survival from an epigenomic perspective. METHODS: Using a newly developed Air Pollutants Exposure Score (APES), we utilized a prospective cohort study (UK Biobank) to investigate the associations of individual and combined air pollution exposures with CRC incidence and survival, followed by an up-to-date systematic review with meta-analysis to verify the associations. In epigenetic two-sample Mendelian randomization analyses, we examine the associations between genetically predicted DNA methylation related to air pollution and CRC risk. Further genetic colocalization and gene-environment interaction analyses provided different insights to disentangle pathogenic effects of air pollution via epigenetic modification. FINDINGS: During a median 12.97-year follow-up, 5767 incident CRC cases among 428,632 participants free of baseline CRC and 533 deaths in 2401 patients with CRC were documented in the UK Biobank. A higher APES score was associated with an increased CRC risk (HR, 1.03, 95% CI = 1.01-1.06; P = 0.016) and poorer survival (HR, 1.13, 95% CI = 1.03-1.23; P = 0.010), particularly among participants with insufficient physical activity and ever smokers (Pinteraction > 0.05). A subsequent meta-analysis of seven observational studies, including UK Biobank data, corroborated the association between PM2.5 exposure (per 10 µg/m3 increment) and elevated CRC risk (RR,1.42, 95% CI = 1.12-1.79; P = 0.004; I2 = 90.8%). Genetically predicted methylation at PM2.5-related CpG site cg13835894 near TMBIM1/PNKD and cg16235962 near CXCR5, and NO2-related cg16947394 near TMEM110 were associated with an increased CRC risk. Gene-environment interaction analysis confirmed the epigenetic modification of aforementioned CpG sites with CRC risk and survival. INTERPRETATION: Our study suggests the association between air pollution and CRC incidence and survival, underscoring the possible modifying roles of epigenomic factors. Methylation may partly mediate pathogenic effects of air pollution on CRC, with annotation to epigenetic alterations in protein-coding genes TMBIM1/PNKD, CXCR5 and TMEM110. FUNDING: Xue Li is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), the National Nature Science Foundation of China (No. 82204019) and Healthy Zhejiang One Million People Cohort (K-20230085). ET is supported by a Cancer Research UK Career Development Fellowship (C31250/A22804). MGD is supported by the MRC Human Genetics Unit Centre Grant (U127527198).

A wild rice CSSL population facilitated identification of salt tolerance genes and rice germplasm innovation.

Salt stress is one of the major factors that limits rice production. Therefore, identification of salt-tolerant alleles from wild rice is important for rice breeding. In this study, we constructed a set of chromosome segment substitution lines (CSSLs) using wild rice as the donor parent and cultivated rice Nipponbare (Nip) as the recurrent parent. Salt tolerance germinability (STG) was evaluated, and its association with genotypes was determined using this CSSL population. We identified 17 QTLs related to STG. By integrating the transcriptome and genome data, four candidate genes were identified, including the previously reported AGO2 and WRKY53. Compared with Nip, wild rice AGO2 has a structure variation in its promoter region and the expression levels were upregulated under salt treatments; wild rice WRKY53 also has natural variation in its promoter region, and the expression levels were downregulated under salt treatments. Wild rice AGO2 and WRKY53 alleles have combined effects for improving salt tolerance at the germination stage. One CSSL line, CSSL118 that harbors these two alleles was selected. Compared with the background parent Nip, CSSL118 showed comprehensive salt tolerance and higher yield, with improved transcript levels of reactive oxygen species scavenging genes. Our results provided promising genes and germplasm resources for future rice salt tolerance breeding.

Initial experience with radiomics of carotid perivascular adipose tissue in identifying symptomatic plaque.

Background: Carotid atherosclerotic ischemic stroke threatens human health and life. The aim of this study is to establish a radiomics model of perivascular adipose tissue (PVAT) around carotid plaque for evaluation of the association between Peri-carotid Adipose Tissue structural changes with stroke and transient ischemic attack. Methods: A total of 203 patients underwent head and neck computed tomography angiography examination in our hospital. All patients were divided into a symptomatic group (71 cases) and an asymptomatic group (132 cases) according to whether they had acute/subacute stroke or transient ischemic attack. The radiomic signature (RS) of carotid plaque PVAT was extracted, and the minimum redundancy maximum correlation, recursive feature elimination, and linear discriminant analysis algorithms were used for feature screening and dimensionality reduction. Results: It was found that the RS model achieved the best diagnostic performance in the Bagging Decision Tree algorithm, and the training set (AUC, 0.837; 95%CI: 0.775, 0.899), testing set (AUC, 0.834; 95%CI: 0.685, 0.982). Compared with the traditional feature model, the RS model significantly improved the diagnostic efficacy for identifying symptomatic plaques in the testing set (AUC: 0.834 vs. 0.593; Z = 2.114, p = 0.0345). Conclusion: The RS model of PVAT of carotid plaque can be used as an objective indicator to evaluate the risk of plaque and provide a basis for risk stratification of carotid atherosclerotic disease.

The coupling of anammox with microalgae-bacteria symbiosis: Nitrogen removal performance and microbial community.

The partial nitrification-anammox process for ammonia nitrogen wastewater treatment requires mechanical aeration to provide oxygen, which is not conducive to energy saving. The microalgae-bacteria symbiotic system (MaBS) has the advantages of low carbon and energy saving in wastewater biological nitrogen removal. Therefore, this study combined the MaBS with an anammox process to provide oxygen, through the photosynthesis of microalgae instead of mechanical aeration. We investigated the nitrogen removal efficiency and long-term operation of a co-culture system comprising microalgae, nitrifying bacteria (NB), denitrifying bacteria (DnB), and anaerobic ammonium-oxidation bacteria (AnAOB) in a sequencing batch reactor without mechanical aeration. The experiment was divided into three steps: firstly, cultivating NB; then, adding three kinds of microalgae which were Chlorella sp., Anabaena sp., and Navicula sp. to the bioreactor to construct a microalgae-bacteria symbiotic system; finally, adding anammox sludge to construct the anammox and microalgae-bacteria symbiosis (Anammox-MaBS) system. The results demonstrated that nitrification, denitrification, and anammox processes were coupled successfully, and the maximum TN removal efficiency of the stable Anammox-MaBS system was 99.51 % when the concentration of the influent NH4+-N was 100 mg/L. The addition of microalgae in ammonia wastewater promoted the enrichment of DnB and AnAOB, which were Denitratisoma, Haliangium, unclassified_Rhodocyclaceae, and Candidatus_Brocadia. Furthermore, the unique biofilm structure could effectively alleviate the photoinhibition of light-sensitive bacteria, which may be the reason for the long-term adaptation of Candidatus_Brocadia to light conditions. This research can provide a low-cost solution to bacterial photoinhibition in the coexistence system of microalgae and bacteria without mechanical aeration, offering theoretical support for low-carbon and energy-efficient treatment of wastewater.

Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models.

Gait analysis has been studied over the last few decades as the best way to objectively assess the technical outcome of a procedure designed to improve gait. The treating physician can understand the type of gait problem, gain insight into the etiology, and find the best treatment with gait analysis. The gait parameters are the kinematics, including the temporal and spatial parameters, and lack the activity information of skeletal muscles. Thus, the gait analysis measures not only the three-dimensional temporal and spatial graphs of kinematics but also the surface electromyograms (sEMGs) of the lower limbs. Now, the shoe-worn GaitUp Physilog® wearable inertial sensors can easily measure the gait parameters when subjects are walking on the general ground. However, it cannot measure muscle activity. The aim of this study is to measure the gait parameters using the sEMGs of the lower limbs. A self-made wireless device was used to measure the sEMGs from the vastus lateralis and gastrocnemius muscles of the left and right feet. Twenty young female subjects with a skeletal muscle index (SMI) below 5.7 kg/m2 were recruited for this study and examined by the InBody 270 instrument. Four parameters of sEMG were used to estimate 23 gait parameters. They were measured using the GaitUp Physilog® wearable inertial sensors with three machine learning models, including random forest (RF), decision tree (DT), and XGBoost. The results show that 14 gait parameters could be well-estimated, and their correlation coefficients are above 0.800. This study signifies a step towards a more comprehensive analysis of gait with only sEMGs.

Relationship Analysis Between Pericoronary Fat Attenuation Index and Parameters of Single Plaque.

OBJECTIVE: The aim of the study is to investigate the relationship between plaque parameters and pericoronary fat attenuation index (FAI). METHODS: A retrospective collection was performed on 227 patients with coronary heart disease who underwent coronary computed tomography angiography examinations in our hospital from May 2021 to April 2023, with a total of 254 right coronary or left anterior descending coronary arteries exhibiting solitary plaques within the FAI measurement area. Based on whether the proximal coronary FAI value was ≥ -70.0 HU, patients and coronary arteries were divided into FAI-positive group (67 cases, 73 coronary arteries) and FAI-negative group (160 cases, 181 coronary arteries). Quantitative parameters of coronary solitary plaques were collected, including stenosis severity, plaque length, plaque volume, plaque composition ratios, minimal luminal area, and calcification score, as well as qualitative parameters such as plaque types and high-risk plaques. Differences in plaque parameters between the FAI-positive and FAI-negative groups were compared. RESULTS: The proportion of positive remodeling in the FAI-positive group (73 coronary arteries) was higher than that in the FAI-negative group (181 coronary arteries) with statistical significance (89.0% vs 78.5%, P = 0.049). Multivariate analysis revealed that positive remodeling was a risk factor for abnormal FAI values in solitary plaques (odds ratio, 2.271, P = 0.049). CONCLUSIONS: The FAI-positive group had a higher proportion of positive remodeling, and positive remodeling was an independent risk factor for positive FAI values.

Diurnal switches in diazotrophic lifestyle increase nitrogen contribution to cereals.

Uncoupling of biological nitrogen fixation from ammonia assimilation is a prerequisite step for engineering ammonia excretion and improvement of plant-associative nitrogen fixation. In this study, we have identified an amino acid substitution in glutamine synthetase, which provides temperature sensitive biosynthesis of glutamine, the intracellular metabolic signal of the nitrogen status. As a consequence, negative feedback regulation of genes and enzymes subject to nitrogen regulation, including nitrogenase is thermally controlled, enabling ammonia excretion in engineered Escherichia coli and the plant-associated diazotroph Klebsiella oxytoca at 23 °C, but not at 30 °C. We demonstrate that this temperature profile can be exploited to provide diurnal oscillation of ammonia excretion when variant bacteria are used to inoculate cereal crops. We provide evidence that diurnal temperature variation improves nitrogen donation to the plant because the inoculant bacteria have the ability to recover and proliferate at higher temperatures during the daytime.

Beat-wise segmentation of electrocardiogram using adaptive windowing and deep neural network.

Timely detection of anomalies and automatic interpretation of an electrocardiogram (ECG) play a crucial role in many healthcare applications, such as patient monitoring and post treatments. Beat-wise segmentation is one of the essential steps in ensuring the confidence and fidelity of many automatic ECG classification methods. In this sense, we present a reliable ECG beat segmentation technique using a CNN model with an adaptive windowing algorithm. The proposed adaptive windowing algorithm can recognise cardiac cycle events and perform segmentation, including regular and irregular beats from an ECG signal with satisfactorily accurate boundaries.The proposed algorithm was evaluated quantitatively and qualitatively based on the annotations provided with the datasets and beat-wise manual inspection. The algorithm performed satisfactorily well for the MIT-BIH dataset with a 99.08% accuracy and a 99.08% of F1-score in detecting heartbeats along with a 99.25% of accuracy in determining correct boundaries. The proposed method successfully detected heartbeats from the European S-T database with a 98.3% accuracy and 97.4% precision. The algorithm showed 99.4% of accuracy and precision for Fantasia database. In summary, the algorithm's overall performance on these three datasets suggests a high possibility of applying this algorithm in various applications in ECG analysis, including clinical applications with greater confidence.

Development and validation of an inflammatory response-related gene and clinical factor-based signature for predicting prognosis in gastric cancer.

Background: Gastric cancer (GC) is an aggressive disease that requires prognostic tools to aid in clinical management. The prognostic power of clinical features is unsatisfactory, which might be improved by combining mRNA-based signatures. Inflammatory response is widely associated with cancer development and treatment response. It is worth exploring the prognostic performance of inflammatory-related genes plus clinical factors in GC. Methods: An 11-gene signature was trained using the least absolute shrinkage and selection operator (LASSO) based on the messenger RNA (mRNA) and overall survival (OS) data of The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort. A nomogram was established using the signature and clinical factors with a significant linkage with OS and was validated in 3 independent cohorts (GSE15419, GSE13861, and GSE66229) via calculating the area under the receiver operator characteristic curve (AUC). The association between the signature and immunotherapy efficacy was explored in the ERP107734 cohort. Results: A high risk score was associated with shorter OS in both the training and the validation sets (the AUC for 1-, 3-, 5-year in TCGA-STAD cohort: 0.691, 0.644, and 0.707; GSE15459: 0.602, 0.602, and 0.650; GSE13861: 0.648, 0.611, and 0.647; GSE66229: 0.661, 0.630, and 0.610). Its prognostic power was improved by combining clinical factors including age, sex, and tumor stage (the AUC for 1-, 3-, 5-year in TCGA-STAD cohort: 0.759, 0.706, and 0.742; GSE15459: 0.773, 0.786, and 0.803; GSE13861: 0.749, 0.881, and 0.795; GSE66229: 0.773, 0.735, and 0.722). Moreover, a low-risk score was associated with a favorable response to pembrolizumab monotherapy in the advanced setting (AUC =0.755, P=0.010). Conclusions: In GCs, the inflammatory response-related gene-based signature was related to immunotherapy efficacy, and its risk score plus clinical features yielded robust prognostic power. With prospective validation, this model may improve the management of GC by enabling risk stratification and the prediction of response to immunotherapy.

Gut-derived bacterial LPS attenuates incubation of methamphetamine craving via modulating microglia.

BACKGROUND: The microbiota-gut-brain axis plays a critical role in the pathophysiology of neuropsychiatric disorders, and the compositions of gut microbiota are altered by addictive drugs. However, the role of gut microbiota in the incubation of methamphetamine (METH) craving remains poorly understood. METHODS: 16S rRNA gene sequencing was performed to assess the richness and diversity of gut microbiota in METH self-administration model. Hematoxylin and eosin staining was performed to evaluate the integrity of intestinal barrier. Immunofluorescence and three-dimensional reconstruction were performed to assess the morphologic changes of microglia. Serum levels of lipopolysaccharide (LPS) were determined using the rat enzyme-linked immunosorbent assay kits. Quantitative real-time PCR was performed to assess transcript levels of dopamine receptor, glutamate ionotropic AMPA receptor 3 and brain-derived neurotrophic factor. RESULTS: METH self-administration induced gut microbiota dysbiosis, intestinal barrier damage and microglia activation in the nucleus accumbens core (NAcc), which was partially recovered after prolonged withdrawal. Microbiota depletion via antibiotic treatment increased LPS levels and induced a marked change in the microglial morphology in the NAcc, as indicated by the decreases in the lengths and numbers of microglial branches. Depleting the gut microbiota also prevented the incubation of METH craving and increased the population of Klebsiella oxytoca. Furthermore, Klebsiella oxytoca treatment or exogenous administration of the gram-negative bacterial cell wall component LPS increased serum and central LPS levels, induced microglial morphological changes and reduced the dopamine receptor transcription in the NAcc. Both treatments and NAcc microinjections of gut-derived bacterial LPS significantly decreased METH craving after prolonged withdrawal. CONCLUSIONS: These data suggest that LPS from gut gram-negative bacteria may enter circulating blood, activate microglia in the brain and consequently decrease METH craving after withdrawal, which may have important implications for novel strategies to prevent METH addiction and relapse.

Senescence-related genes define prognosis, immune contexture, and pharmacological response in gastric cancer.

As one of the prevalent tumors worldwide, gastric cancer (GC) has obtained sufficient attention in its clinical management and prognostic stratification. Senescence-related genes are involved in the tumorigenesis and progression of GC. A machine learning algorithm-based prognostic signature was developed from six senescence-related genes including SERPINE1, FEN1, PDGFRB, SNCG, TCF3, and APOC3. The TCGA-STAD cohort was utilized as a training set while the GSE84437 and GSE13861 cohorts were analyzed for validation. Immune cell infiltration and immunotherapy efficacy were investigated in the PRJEB25780 cohort. Data from the genomics of drug sensitivity in cancer (GDSC) database revealed pharmacological response. The GSE13861 and GSE54129 cohorts, single-cell dataset GSE134520, and The Human Protein Atlas (THPA) database were utilized for localization of the key senescence-related genes. Association of a higher risk-score with worse overall survival (OS) was identified in the training cohort (TCGA-STAD, P<0.001; HR = 2.03, 95% CI, 1.45-2.84) and the validation cohorts (GSE84437, P = 0.005; HR = 1.48, 95% CI, 1.16-1.95; GSE13861, P = 0.03; HR = 2.23, 95% CI, 1.07-4.62). The risk-score was positively correlated with densities of tumor-infiltrating immunosuppressive cells (P < 0.05) and was lower in patients who responded to pembrolizumab monotherapy (P = 0.03). Besides, patients with a high risk-score had higher sensitivities to the inhibitors against the PI3K-mTOR and angiogenesis (P < 0.05). Expression analysis verified the promoting roles of FEN1, PDGFRB, SERPINE1, and TCF3, and the suppressing roles of APOC3 and SNCG in GC, respectively. Immunohistochemistry staining and single-cell analysis revealed their location and potential origins. Taken together, the senescence gene-based model may potentially change the management of GC by enabling risk stratification and predicting response to systemic therapy.

Synthesis of 3,4,5-trisubstituted phenols via Rh(III)-catalyzed alkenyl C-H activation assisted by phosphonium cations.

An efficient method for the construction of various 3,4,5-trisubstituted phenol derivatives has been achieved via the Rh(III)-catalyzed coupling of phosphonium cations with internal alkynes. This protocol shows good substrate compatibility, as an array of structurally and electronically diverse phosphonium compounds react efficiently with up to 87% yield.

Tumor immune contexture predicts recurrence after prostatectomy and efficacy of androgen deprivation and immunotherapy in prostate cancer.

BACKGROUND: Prostate cancer is one of the most common cancers in men with notable interpatient heterogeneity. Implications of the immune microenvironment in predicting the biochemical recurrence-free survival (BCRFS) after radical prostatectomy and the efficacy of systemic therapies in prostate cancer remain ambiguous. METHODS: The tumor immune contexture score (TICS) involving eight immune contexture-related signatures was developed using seven cohorts of 1120 patients treated with radical prostatectomy (training: GSE46602, GSE54460, GSE70769, and GSE94767; validation: GSE70768, DKFZ2018, and TCGA). The association between the TICS and treatment efficacy was investigated in GSE111177 (androgen deprivation therapy [ADT]) and EGAS00001004050 (ipilimumab). RESULTS: A high TICS was associated with prolonged BCRFS after radical prostatectomy in the training (HR = 0.32, 95% CI 0.24-0.45, P < 0.001) and the validation cohorts (HR = 0.45, 95% CI 0.32-0.62, P < 0.001). The TICS showed stable prognostic power independent of tumor stage, surgical margin, pre-treatment prostatic specific antigen (PSA), and Gleason score (multivariable HR = 0.50, 95% CI 0.39-0.63, P < 0.001). Adding the TICS into the prognostic model constructed using clinicopathological features significantly improved its 1/2/3/4/5-year area under curve (P < 0.05). A low TICS was associated with high homologous recombination deficiency scores, abnormally activated pathways concerning DNA replication, cell cycle, steroid hormone biosynthesis, and drug metabolism, and fewer tumor-infiltrating immune cells (P < 0.05). The patients with a high TICS had favorable BCRFS with ADT (HR = 0.25, 95% CI 0.06-0.99, P = 0.034) or ipilimumab monotherapy (HR = 0.23, 95% CI 0.06-0.81, P = 0.012). CONCLUSIONS: Our study delineates the associations of tumor immune contexture with molecular features, recurrence after radical prostatectomy, and the efficacy of ADT and immunotherapy. The TICS may improve the existing risk stratification systems and serve as a patient-selection tool for ADT and immunotherapy in prostate cancer.

A potential application for life-related organics detection on Mars by diffuse reflectance infrared spectroscopy.

Life information searching is a hot point for Mars exploration. Ancient Mars was very likely to reach a habitable environment, and there was a real possibility of arising life on Mars. However, the current Mars has a harsh environment. Under such conditions, life materials on Mars are supposed to have taken the form of relatively primitive microbial or organic residues, which might be preserved in some mineral matrices. Detection of these remnants is of great significance for understanding the origin and evolution of life on Mars. The best detection method is in-situ detection or sample return. Herein, diffuse reflectance infrared spectroscopy (DRIFTS) was used to detect characteristic spectra and the limit of detection (LOD) of potential representative organic compounds with associated minerals. In view of high oxidation due to the electrostatic discharge (ESD) during dust actives on Martian surface. The degradation of organic matter by ESD process was studied under simulated Mars conditions. Our results show that the spectral characteristics of organic matter are significantly different from that of associated minerals. The different organic samples have different mass loss and color change after ESD reaction. And the signal intensity of infrared diffuse reflection spectrum can also reflect the changes of organic molecules after ESD reaction. Our results indicated that the degradation products of organics rather than organic itself are most likely to be founded on current Martian surface.

Using Ballistocardiogram and Impedance Plethysmogram for Minimal Contact Measurement of Blood Pressure Based on a Body Weight-Fat Scale.

Electronic health (eHealth) is a strategy to improve the physical and mental condition of a human, collecting daily physiological data and information from digital apparatuses. Body weight and blood pressure (BP) are the most popular and important physiological data. The goal of this study is to develop a minimal contact BP measurement method based on a commercial body weight-fat scale, capturing biometrics when users stand on it. The pulse transit time (PTT) is extracted from the ballistocardiogram (BCG) and impedance plethysmogram (IPG), measured by four strain gauges and four footpads of a commercial body weight-fat scale. Cuffless BP measurement using the electrocardiogram (ECG) and photoplethysmogram (PPG) serves as the reference method. The BP measured by a commercial BP monitor is considered the ground truth. Twenty subjects participated in this study. By the proposed model, the root-mean-square errors and correlation coefficients (r2s) of estimated systolic blood pressure and diastolic blood pressure are 7.3 ± 2.1 mmHg and 4.5 ± 1.8 mmHg, and 0.570 ± 0.205 and 0.284 ± 0.166, respectively. This accuracy level achieves the C grade of the corresponding IEEE standard. Thus, the proposed method has the potential benefit for eHealth monitoring in daily application.

Rh(III)-catalyzed [4 + 1] cyclization of aryl substituted pyrazoles with cyclopropanols via C-H activation.

A rhodium-catalyzed formal [4 + 1]-cyclization reaction of aryl substituted pyrazoles with cyclopropanols via C-H bond activation/cyclization processes to selectively construct a series of carbonyl functionalized pyrazolo[5,1-a]isoindoles is described. The reaction features good functional group compatibility and a broad substrate scope with respect to both cyclization components with up to 84% yields. Mechanistic studies indicated that the C-H cleavage might be the rate-determining step in this transformation.

Estimation of Left Ventricular Ejection Fraction Using Cardiovascular Hemodynamic Parameters and Pulse Morphological Characteristics with Machine Learning Algorithms.

It is estimated that 360,000 patients have suffered from heart failure (HF) in Taiwan, mostly those over the age of 65 years, who need long-term medication and daily healthcare to reduce the risk of mortality. The left ventricular ejection fraction (LVEF) is an important index to diagnose the HF. The goal of this study is to estimate the LVEF using the cardiovascular hemodynamic parameters, morphological characteristics of pulse, and bodily information with two machine learning algorithms. Twenty patients with HF who have been treated for at least six to nine months participated in this study. The self-constructing neural fuzzy inference network (SoNFIN) and XGBoost regression models were used to estimate their LVEF. A total of 193 training samples and 118 test samples were obtained. The recursive feature elimination algorithm is used to choose the optimal parameter set. The results show that the estimating root-mean-square errors (ERMS) of SoNFIN and XGBoost are 6.9 ± 2.3% and 6.4 ± 2.4%, by comparing with echocardiography as the ground truth, respectively. The benefit of this study is that the LVEF could be measured by the non-medical image method conveniently. Thus, the proposed method may arrive at an application level for clinical practice in the future.