Poly[(μ6-benzene-1,3,5-tricarboxyl­ato-κ6 O 1:O 1′:O 3:O 3′:O 5:O 5′)tris­(N,N-dimethyl­formamide-κO)tris­(μ3-formato-κ2 O:O′)trimagnesium(II)]

The title complex, [Mg3(CHO2)3(C9H3O6)(C3H7NO)3]n, exhib­its a two-dimensional structure parallel to (001), which is built up from the MgII atoms and bridging carboxyl­ate ligands (3 symmetry). The MgII atom is six-coordinated by one O atom from a dimethyl­formamide mol­ecule, two O atoms from two μ6-benzene-1,3,5-tricarboxyl­ate ligands and three O atoms from three μ3-formate ligands in a distorted octa­hedral geometry

The 2005 Ilan earthquake doublet and seismic crisis in northeastern Taiwan: evidence for dyke intrusion associated with on-land propagation of the Okinawa Trough

Northern Taiwan underwent mountain building in the early stage of the Taiwan orogeny but is currently subjected to post-collisional crustal extension. It may be related to gravitational collapse or to the rifting of the Okinawa Trough, which lies offshore northeastern Taiwan. The Ilan Plain, northeastern Taiwan, which is bounded by the normal fault systems and filled up with thick Pliocene–Pleistocene sedimentary sequences, formed under such an extension environment. Over there on 2005 March 5 two earthquakes with about the same magnitude (M_L = 5.9) occurred within 68 s and produced intense aftershocks activity according to the records of Central Weather Bureau Seismic Network of Taiwan. We relocated the earthquake sequence by the three-dimension earthquake location algorithm with the newly published 3-D Vp and Vp/Vs velocity model, and determined the first-polarity focal mechanisms of the earthquake doublet. One major cluster of aftershocks which trends E–W and dips steeply to the south can be identified and picked up as a potential fault plane. The focal mechanisms of the two main shocks are both classified as normal type by first-polarity but strike-slip by centroid moment tensor inversion; however two methods both yield consistent E–W strike. Static coseismic deformation was additionally determined from Global Positioning System (GPS) daily solutions at a set of continuous GPS stations and from strong-motion seismographs. These data show NW–SE extension at high angle to the fault plane, which cannot be explained from a simple strike-slip double-couple mechanism. On the other hand, the small vertical displacements and steep fault plane cannot be explained from a simple normal event as well. We present from elastic dislocation modelling that the geodetic data are best explained by significant component of tensile source with centimetre-scale of opening on a 15-km-long fault extending from 1 to 13 km depth. We therefore interpret the crisis as the result of dyke intrusion at the very tip of the Okinawa Trough, which is reasonably driven by backarc spreading

Genetic Analysis of Floral Symmetry Transition in African Violet Suggests the Involvement of Trans-acting Factor for CYCLOIDEA Expression Shifts

With the growing demand for its ornamental uses, the African violet (Saintpaulia ionantha) has been popular owing to its variations in color, shape and its rapid responses to artificial selection. Wild type African violet (WT) is characterized by flowers with bilateral symmetry yet reversals showing radially symmetrical flowers such as dorsalized actinomorphic (DA) and ventralized actinomorphic (VA) peloria are common. Genetic crosses among WT, DA, and VA revealed that these floral symmetry transitions are likely to be controlled by three alleles at a single locus in which the levels of dominance are in a hierarchical fashion. To investigate whether the floral symmetry gene was responsible for these reversals, orthologs of CYCLOIDEA (CYC) were isolated and their expressions correlated to floral symmetry transitions. Quantitative RT-PCR and in situ results indicated that dorsal-specific SiCYC1s expression in WT S. ionantha (SCYC1A and SiCYC1B) shifted in DA with a heterotopically extended expression to all petals, but in VA, SiCYC1s' dorsally specific expressions were greatly reduced. Selection signature analysis revealed that the major high-expressed copy of SCYC1A had been constrained under purifying selection, whereas the low-expressed helper SiCYC1B appeared to be relaxed under purifying selection after the duplication into SCYC1A and SiCYC1B. Heterologous expression of SCYC1A in Arabdiopsis showed petal growth retardation which was attributed to limited cell proliferation. While expression shifts of SCYC1A and SiCYC1B correlate perfectly to the resulting symmetry phenotype transitions in F1s of WT and DA, there is no certain allelic combination of inherited SiCYC1s associated with specific symmetry phenotypes. This floral transition indicates that although the expression shifts of SCYC1A/1B are responsible for the two contrasting actinomorphic reversals in African violet, they are likely to be controlled by upstream trans-acting factors or epigenetic regulations

Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care

ObjectiveTo implement an all-day online artificial intelligence (AI)-assisted detection of ST-elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) to facilitate patient triage for timely reperfusion therapy.MethodsThe proposed AI model combines a convolutional neural network and long short-term memory (CNN-LSTM) to predict STEMI on prehospital 12-lead ECGs obtained from mini-12-lead ECG devices equipped in ambulance vehicles in Central Taiwan. Emergency medical technicians (EMTs) from the 14 AI-implemented fire stations performed the on-site 12-lead ECG examinations using the mini portable device. The 12-lead ECG signals were transmitted to the AI center of China Medical University Hospital to classify the recordings as “STEMI” or “Not STEMI”. In 11 non-AI fire stations, the ECG data were transmitted to a secure network and read by available on-line emergency physicians. The response time was defined as the time interval between the ECG transmission and ECG interpretation feedback.ResultsBetween July 17, 2021, and March 26, 2022, the AI model classified 362 prehospital 12-lead ECGs obtained from 275 consecutive patients who had called the 119 dispatch centers of fire stations in Central Taiwan for symptoms of chest pain or shortness of breath. The AI's response time to the EMTs in ambulance vehicles was 37.2 ± 11.3 s, which was shorter than the online physicians' response time from 11 other fire stations with no AI implementation (113.2 ± 369.4 s, P < 0.001) after analyzing another set of 335 prehospital 12-lead ECGs. The evaluation metrics including accuracy, precision, specificity, recall, area under the receiver operating characteristic curve, and F1 score to assess the overall AI performance in the remote detection of STEMI were 0.992, 0.889, 0.994, 0.941, 0.997, and 0.914, respectively. During the study period, the AI model promptly identified 10 STEMI patients who underwent primary percutaneous coronary intervention (PPCI) with a median contact-to-door time of 18.5 (IQR: 16–20.8) minutes.ConclusionImplementation of an all-day real-time AI-assisted remote detection of STEMI on prehospital 12-lead ECGs in the field is feasible with a high diagnostic accuracy rate. This approach may help minimize preventable delays in contact-to-treatment times for STEMI patients who require PPCI

Local synergetic collaboration between Pd and local tetrahedral symmetric Ni oxide enables ultra-high-performance CO2 thermal methanation

Tetrahedral symmetric NiO2 and Pd respectively facilitate H2 splitting and CO2 to CO reduction and thus enable an ultra-high CH4 production yield performance in the epitaxial interfaces in the bimetallic NiO2@Pd NPs.</p

Transcriptome Changes in Relation to Manic Episode

Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs (MIR181B1 and MIR103A1) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including TAS2R5 and TAS2R3, may be mania state-specific markers. Additionally, four genes showed a nominal p-value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of MS4A14, PYHIN1, UTRN, and DMXL2, and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine–cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness

International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment

Background The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90- day and 1-year survival in patients with long-bone metastases undergoing surgical treatment and have demonstrated good discriminatory ability on internal validation. However, the performance of a prediction model could potentially vary by race or region, and the SORG-MLA must be externally validated in an Asian cohort. Furthermore, the authors of the original developmental study did not consider the Eastern Cooperative Oncology Group (ECOG) performance status, a survival prognosticator repeatedly validated in other studies, in their algorithms because of missing data. Questions/purposes (1) Is the SORG-MLA generalizable to Taiwanese patients for predicting 90-day and 1-year mortality? (2) Is the ECOG score an independent factor associated with 90-day and 1-year mortality while controlling for SORG-MLA predictions? Methods All 356 patients who underwent surgery for long-bone metastases between 2014 and 2019 at one tertiary care center in Taiwan were included. Ninety-eight percent (349 of 356) of patients were of Han Chinese descent. The median (range) patient age was 61 years (25 to 95), 52% (184 of 356) were women, and the median BMI was 23 kg/m2 (13 to 39 kg/m2). The most common primary tumors were lung cancer (33% [116 of 356]) and breast cancer (16% [58 of 356]). Fifty-five percent (195 of 356) of patients presented with a complete pathologic fracture. Intramedullary nailing was the most commonly performed type of surgery (59% [210 of 356]), followed by plate screw fixation (23% [81 of 356]) and endoprosthetic reconstruction (18% [65 of 356]). Six patients were lost to follow-up within 90 days; 30 were lost to follow-up within 1 year. Eighty-five percent (301 of 356) of patients were followed until death or for at least 2 years. Survival was 82% (287 of 350) at 90 days and 49% (159 of 326) at 1 year. The model's performance metrics included discrimination (concordance index [c-index]), calibration (intercept and slope), and Brier score. In general, a c-index of 0.5 indicates random guess and a c-index of 0.8 denotes excellent discrimination. Calibration refers to the agreement between the predicted outcomes and the actual outcomes, with a perfect calibration having an intercept of 0 and a slope of 1. The Brier score of a prediction model must be compared with and ideally should be smaller than the score of the null model. A decision curve analysis was then performed for the 90-day and 1-year prediction models to evaluate their net benefit across a range of different threshold probabilities. A multivariate logistic regression analysis was used to evaluate whether the ECOG score was an independent prognosticator while controlling for the SORG-MLA's predictions. We did not perform retraining/recalibration because we were not trying to update the SORG-MLA algorithm in this study. Results The SORG-MLA had good discriminatory ability at both timepoints, with a c-index of 0.80 (95% confidence interval 0.74 to 0.86) for 90-day survival prediction and a c-index of 0.84 (95% CI 0.80 to 0.89) for 1-year survival prediction. However, the calibration analysis showed that the SORG-MLAs tended to underestimate Taiwanese patients' survival (90-day survival prediction: Calibration intercept 0.78 [95% CI 0.46 to 1.10], calibration slope 0.74 [95% CI 0.53 to 0.96]; 1-year survival prediction: Calibration intercept 0.75 [95% CI 0.49 to 1.00], calibration slope 1.22 [95% CI 0.95 to 1.49]). The Brier score of the 90-day and 1-year SORG-MLA prediction models was lower than their respective null model (0.12 versus 0.16 for 90-day prediction; 0.16 versus 0.25 for 1-year prediction), indicating good overall performance of SORG-MLAs at these two timepoints. Decision curve analysis showed SORG-MLAs provided net benefits when threshold probabilities ranged from 0.40 to 0.95 for 90-day survival prediction and from 0.15 to 1.0 for 1-year prediction. The ECOG score was an independent factor associated with 90-day mortality (odds ratio 1.94 [95% CI 1.01 to 3.73]) but not 1-year mortality (OR 1.07 [95% CI 0.53 to 2.17]) after controlling for SORG-MLA predictions for 90-day and 1- year survival, respectively. Conclusion SORG-MLAs retained good discriminatory ability in Taiwanese patients with long-bone metastases, although their actual survival time was slightly underestimated. More international validation and incremental value studies that address factors such as the ECOG score are warranted to refine the algorithms, which can be freely accessed online at https://sorg-apps.shinyapps. io/extremitymetssurvival/

Non-nosocomial healthcare-associated infective endocarditis in Taiwan: an underrecognized disease with poor outcome

<p>Abstract</p> <p>Background</p> <p>Non-nosocomial healthcare-associated infective endocarditis (NNHCA-IE) is a new category of IE of increasing importance. This study described the clinical and microbiological characteristics and outcome of NNHCA-IE in Taiwan.</p> <p>Methods</p> <p>A retrospective study was conducted of all patients with IE admitted to the Kaohsiung Veterans General Hospital in Kaohsiung, Taiwan over a five-year period from July 2004 to July 2009. The clinical and microbiological features of NNHCA-IE were compared to those of community-acquired and nosocomial IE. Predictors for in-hospital death were determined.</p> <p>Results</p> <p>Two-hundred episodes of confirmed IE occurred during the study period. These included 148 (74%) community-acquired, 30 (15%) non-nosocomial healthcare-associated, and 22 (11%) nosocomial healthcare-associated IE. <it>Staphylococcus aureus </it>was the most frequent pathogen. Patients with NNHCA-IE compared to community-acquired IE, were older (median age, 67 vs. 44, years, <it>p </it>< 0.001), had more MRSA (43.3% vs. 9.5%, <it>p </it>< 0.001), more comorbidity conditions (median Charlson comorbidity index [interquartile range], 4[2-6] vs. 0[0-1], <it>p </it>< 0.001), a higher in-hospital mortality (50.0% vs. 17.6%, <it>p </it>< 0.001) and were less frequently recognized by clinicians on admission (16.7% vs. 47.7%, <it>p </it>= 0.002). The overall in-hospital mortality rate for all patients with IE was 25%. Shock was the strongest risk factor for in-hospital death (odds ratio 7.8, 95% confidence interval 2.4-25.2, <it>p </it>< 0.001).</p> <p>Conclusions</p> <p>NNHCA-IE is underrecognized and carries a high mortality rate. Early recognition is crucial to provide optimal management and improve outcome.</p