Sol-gel transition effect based on konjac glucomannan thermosensitive hydrogel for photo-assisted uranium extraction.

Exploiting the intelligent photocatalysts capable of phase separation provides a promising solution to the removal of uranium, which is expected to solve the difficulty in separation and the poor selectivity of traditional photocatalysts in carbonate-containing uranium wastewater. In this paper, the γ-FeOOH/konjac glucomannan grafted with phenolic hydroxyl groups/poly-N-isopropylacrylamide (γ-FeOOH/KGM(Ga)/PNIPAM) thermosensitive hydrogel is proposed as the photocatalysts for extracting uranium from carbonate-containing uranium wastewater. The dynamic phase transformation is demonstrated to confirm the arbitrary transition of γ-FeOOH/KGM(Ga)/PNIPAM thermosensitive hydrogel from a dispersed state with a high specific surface area at low temperatures to a stable aggregated state at high temperatures. Notably, the γ-FeOOH/KGM(Ga)/PNIPAM thermosensitive hydrogel achieves a remarkably high rate of 92.3% in the removal of uranium from the wastewater containing carbonates and maintains the efficiency of uranium removal from uranium mine wastewater at over 90%. Relying on electron spin resonance and free radical capture experiment, we reveal the adsorption-reduction-nucleation-crystallization mechanism of uranium on γ-FeOOH/KGM(Ga)/PNIPAM thermosensitive hydrogel. Overall, this strategy provides a promising solution to treating uranium-contaminated wastewater, showing a massive potential in water purification.

Endogenous p53 inhibitor TIRR dissociates systemic metabolic health from oncogenic activity.

It is unclear whether metabolic health corresponds to reduced oncogenesis or vice versa. We study Tudor-interacting repair regulator (TIRR), an inhibitor of p53 binding protein 1 (53BP1)-mediated p53 activation, and the physiological consequences of enhancing tumor suppressor activity. Deleting TIRR selectively activates p53, significantly protecting against cancer but leading to a systemic metabolic imbalance in mice. TIRR-deficient mice are overweight and insulin resistant, even under normal chow diet. Similarly, reduced TIRR expression in human adipose tissue correlates with higher BMI and insulin resistance. Despite the metabolic challenges, TIRR loss improves p53 heterozygous (p53HET) mouse survival and correlates with enhanced progression-free survival in patients with various p53HET carcinomas. Finally, TIRR's oncoprotective and metabolic effects are dependent on p53 and lost upon p53 deletion in TIRR-deficient mice, with glucose homeostasis and orexigenesis being primarily regulated by TIRR expression in the adipose tissue and the CNS, respectively, as evidenced by tissue-specific models. In summary, TIRR deletion provides a paradigm of metabolic deregulation accompanied by reduced oncogenesis.

Motif-Aware miRNA-Disease Association Prediction via Hierarchical Attention Network.

As post-transcriptional regulators of gene expression, micro-ribonucleic acids (miRNAs) are regarded as potential biomarkers for a variety of diseases. Hence, the prediction of miRNA-disease associations (MDAs) is of great significance for an in-depth understanding of disease pathogenesis and progression. Existing prediction models are mainly concentrated on incorporating different sources of biological information to perform the MDA prediction task while failing to consider the fully potential utility of MDA network information at the motif-level. To overcome this problem, we propose a novel motif-aware MDA prediction model, namely MotifMDA, by fusing a variety of high- and low-order structural information. In particular, we first design several motifs of interest considering their ability to characterize how miRNAs are associated with diseases through different network structural patterns. Then, MotifMDA adopts a two-layer hierarchical attention to identify novel MDAs. Specifically, the first attention layer learns high-order motif preferences based on their occurrences in the given MDA network, while the second one learns the final embeddings of miRNAs and diseases through coupling high- and low-order preferences. Experimental results on two benchmark datasets have demonstrated the superior performance of MotifMDA over several state-of-the-art prediction models. This strongly indicates that accurate MDA prediction can be achieved by relying solely on MDA network information. Furthermore, our case studies indicate that the incorporation of motif-level structure information allows MotifMDA to discover novel MDAs from different perspectives.

Enhancing Commercially Iron Powder Electron Transport by Surface Biosulfuration to Achieve Uranium Extraction from Uranium Ore Wastewater.

The zero-valent iron (ZVI) has attracted increasing attention due to the enhanced reactivity of ZVI to uranium wastewater. However, ZVI practical application is hampered due to its susceptibility to oxidation and the formation of passivation layers during storage and in situ restoration. To address these issues, we used a biosulfuration approach to modify ZVI for application in uranium ore wastewater treatment. A series of physicochemical characterization tools and photoelectronic analyses showed that BS-ZVI considerably increased carrier separation efficiency and visible light absorption capacity, resulting in a significant photoassisted enhancement effect on uranium extraction. Accordingly, the uranium removal efficiency of BS-ZVI reached 91% within 60 min, and its maximum adsorption capacity was 336.3 mg/g. By analyzing the mechanism, the improved U(VI) removal performance was mostly responsible on the dissolution of the passivation layer on the surface of ZVI, the generation of Fe(II) and FeS, and the important role of Shewanella putrefaciens extracellular polymers (EPS). Overall, the BS-ZVI biohybrid merges with the high activity of ZVI, bio-FeS, and self-regeneration ability of bacteria, expanding a promising new approach for sustainable treatment of uranium mine wastewater.

Acetylation of xenogeneic silencer H-NS regulates biofilm development through the nitrogen homeostasis regulator in Shewanella.

Adjusting intracellular metabolic pathways and adopting suitable live state such as biofilms, are crucial for bacteria to survive environmental changes. Although substantial progress has been made in understanding how the histone-like nucleoid-structuring (H-NS) protein modulates the expression of the genes involved in biofilm formation, the precise modification that the H-NS protein undergoes to alter its DNA binding activity is still largely uncharacterized. This study revealed that acetylation of H-NS at Lys19 inhibits biofilm development in Shewanella oneidensis MR-1 by downregulating the expression of glutamine synthetase, a critical enzyme in glutamine synthesis. We further found that nitrogen starvation, a likely condition in biofilm development, induces deacetylation of H-NS and the trimerization of nitrogen assimilation regulator GlnB. The acetylated H-NS strain exhibits significantly lower cellular glutamine concentration, emphasizing the requirement of H-NS deacetylation in Shewanella biofilm development. Moreover, we discovered in vivo that the activation of glutamine biosynthesis pathway and the concurrent suppression of the arginine synthesis pathway during both pellicle and attached biofilms development, further suggesting the importance of fine tune nitrogen assimilation by H-NS acetylation in Shewanella. In summary, posttranslational modification of H-NS endows Shewanella with the ability to respond to environmental needs by adjusting the intracellular metabolism pathways.

Enhancing patient-centred care in Taiwan's dental education system: Exploring the feasibility of doctor-patient communication education and training.

Background/purpose: Improved communication can optimize treatment outcomes and patient satisfaction. Findings emphasize the need for tailored communication strategies based on patient characteristics. Implementing communication courses can enhance patient-centered care and reduce conflicts. Therefore, this study examined the feasibility of integrating doctor-patient communication education in Taiwan's dental education system. Materials and methods: Using interviews and questionnaires, we conducted descriptive statistics and generalized linear mixed-effects model analysis on the importance of doctor-patient communication from the dentist and patient perspectives. Results: More than 600 patient surveys and four interviewed dentists with 20+ years of experience stressed doctor-patient communication in dentistry. Patients' age and income were positively related to the emphasis on physician-patient communication but negatively associated with dental assistants' communication. Dentists valued communication education but differed in its execution and importance. Conclusion: It is recommended to initiate dentist-patient communication education during university studies and continue its practice to adapt to the changing societal dynamics. Individuals with higher socioeconomic status and older age show a greater appreciation for dentist-patient communication, potentially driven by self-promotion, thereby highlighting the diverse nature of doctor-patient relationships. Based on our findings, we suggest to implement the doctor-patient communication courses in Taiwan.

Dynamics of the DYNLL1-MRE11 complex regulate DNA end resection and recruitment of Shieldin to DSBs.

The extent and efficacy of DNA end resection at DNA double-strand breaks (DSB) determine the repair pathway choice. Here we describe how the 53BP1-associated protein DYNLL1 works in tandem with the Shieldin complex to protect DNA ends. DYNLL1 is recruited to DSBs by 53BP1, where it limits end resection by binding and disrupting the MRE11 dimer. The Shieldin complex is recruited to a fraction of 53BP1-positive DSBs hours after DYNLL1, predominantly in G1 cells. Shieldin localization to DSBs depends on MRE11 activity and is regulated by the interaction of DYNLL1 with MRE11. BRCA1-deficient cells rendered resistant to PARP inhibitors by the loss of Shieldin proteins can be resensitized by the constitutive association of DYNLL1 with MRE11. These results define the temporal and functional dynamics of the 53BP1-centric DNA end resection factors in cells.

A Novel Fiber-Optic Ice Sensor to Identify Ice Types Based on Total Reflection.

To address the issues of not accurately identifying ice types and thickness in current fiber-optic ice sensors, in this paper, we design a novel fiber-optic ice sensor based on the reflected light intensity modulation method and total reflection principle. The performance of the fiber-optic ice sensor was simulated by ray tracing. The low-temperature icing tests validated the performance of the fiber-optic ice sensor. It is shown that the ice sensor can detect different ice types and the thickness from 0.5 to 5 mm at temperatures of -5 °C, -20 °C, and -40 °C. The maximum measurement error is 0.283 mm. The proposed ice sensor provides promising applications in aircraft and wind turbine icing detection.

Dynamics of the DYNLL1/MRE11 complex regulates DNA end resection and recruitment of the Shieldin complex to DSBs.

Extent and efficacy of DNA end resection at DNA double strand break (DSB)s determines the choice of repair pathway. Here we describe how the 53BP1 associated protein DYNLL1 works in tandem with Shieldin and the CST complex to protect DNA ends. DYNLL1 is recruited to DSBs by 53BP1 where it limits end resection by binding and disrupting the MRE11 dimer. The Shieldin complex is recruited to a fraction of 53BP1-positive DSBs hours after DYNLL1 predominantly in the G1 cells. Shieldin localization to DSBs is dependent on MRE11 activity and is regulated by the interaction of DYNLL1 with MRE11. BRCA1-deficient cells rendered resistant to PARP inhibitors by the loss of Shieldin proteins can be re-sensitized by the constitutive association of DYNLL1 with MRE11. These results define the temporal and functional dynamics of the 53BP1-centric DNA end resection factors in cells.

Tsuneonella litorea sp. nov., a novel carotenoid-producing bacterium isolated from coastal sediment.

A Gram-stain-negative, aerobic, non-motile and pleomorphic bacterium designated as YG55T was isolated from a coastal sediment sample. Growth was found to occur at 10-37 °C (optimum, 28 °C), at pH 6-9 (optimum, pH 8) and in 0-6 % NaCl (optimum, 1 %). The results of 16S rRNA gene-based analysis showed that strain YG55T was related to the members of the genus Tsuneonella and shared the highest identity of 99.4 % with Tsuneonella dongtanensis GDMCC 1.2307T, followed by Tsuneonella troitsensis JCM 17037T (98.4 %). The phylogenomic results indicated that strain YG55T formed an independent branch distinct from the reference type strains. The 22.7 and 21.8 % digital DNA-DNA hybridization (dDDH) values and 83.0 and 81.8 % average nucleotide identity (ANI) values between strain YG55T and the two relatives were below the species definition thresholds of 70 % (dDDH) and 95-96 % (ANI), indicating that the strain represents a novel genospecies. The results of chemotaxonomic characterization indicated that the major cellular fatty acids of strain YG55T were summed feature 8 (C18 : 1 ω6c and/or C18 : 1 ω7c), C14 : 0 2OH and C16 : 0; the main polar lipids comprised diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylcholine and sphingoglycolipid; the respiratory quinone was ubiquinone-10. The genomic size and DNA G+C contents were 3.03 Mbp and 66.98 %. The strain contained carotenoid biosynthesis genes and could produce carotenoids. Based on its genotypic and phenotypic characteristics, strain YG55T is concluded to represent a novel species of the genus Tsuneonella, for which the name Tsuneonella litorea sp. nov. is proposed. The type strain is YG55T (=GDMCC 1.2590 T=KCTC 82812T).

Contrast-Enhanced Ultrasonography Value for Early Prediction of Delayed Graft Function in Renal Transplantation Patients.

OBJECTIVES: Delayed graft function (DGF) is a common early complication after kidney transplantation. The aim of the present study was to evaluate the value of contrast-enhanced ultrasonography (CEUS) in the early prediction of DGF after kidney transplantation. METHODS: A total of 89 renal transplant recipients were retrospectively enrolled and divided into DGF group or normal graft function (NGF) group according to the allograft function. Conventional Doppler ultrasound and CEUS examination data on the first postoperative day were collected and analyzed. RESULTS: The resistive indices of segmental and interlobar artery in the DGF group were significantly higher than those in the NGF group (0.71 ± 0.17 versus 0.63 ± 0.08, P = .006; 0.70 ± 0.16 versus 0.62 ± 0.08, P = .004, respectively). The patients experiencing DGF had significantly lower PI-c (14.7 dB ± 6.1 dB versus 18.5 dB ± 3.3 dB, P = .001) and smaller AUC-c (779.8 ± 375.8 dB·seconds versus 991.0 ± 211.7 dB·seconds, P = .003), as well as significantly lower PI-m (12.6 dB ± 5.9 dB versus 15.9 dB ± 3.9 dB, P = .006), shorter MTT-m (30.7 ± 9.4 seconds versus 36.3 ± 7.1 seconds, P = .01), and smaller AUC-m (P = .007). Multivariate analysis demonstrated that PI-c, AUC-c, and MTT-m were independent risk factors for DGF. The area under the receiver operating characteristic curve values of the combined predicted value (PI-c + MTT-m, PI-c + AUC-c + MTT-m) of DGF incidence were bigger than that of PI-c, AUC-c, or MTT-m. CONCLUSIONS: CEUS parameters of the cortex and medulla have a good value for an early prediction of DGF after renal transplantation.

PPISB: A Novel Network-Based Algorithm of Predicting Protein-Protein Interactions With Mixed Membership Stochastic Blockmodel.

Protein-protein interactions (PPIs) play an essential role for most of biological processes in cells. Many computational algorithms have thus been proposed to predict PPIs. However, most of them heavily rest on the biological information of proteins while ignoring the latent structural features of proteins presented in a PPI network. In this paper, we propose an efficient network-based prediction algorithm, namely PPISB, based on a mixed membership stochastic blockmodel. By simulating the generative process of a PPI network, PPISB is able to capture the latent community structures. The inference procedure adopted by PPISB further optimizes the membership distributions of proteins over different complexes. After that, a distance measure is designed to compute the similarity between two proteins in terms of their likelihoods of being in the same complex, thus verifying whether they interact with each other or not. To evaluate the performance of PPISB, a series of extensive experiments have been conducted with five PPI networks collected from different species and the results demonstrate that PPISB has a promising performance when applied to predict PPIs in terms of several evaluation metrics. Hence, we reason that PPISB is preferred over state-of-the-art network-based prediction algorithms especially for predicting potential PPIs.

Non-targeted metabolomics and 16s rDNA reveal the impact of uranium stress on rhizosphere and non-rhizosphere soil of ryegrass.

As a radioactive heavy metal element with a long half-life, uranium causes environmental pollution when it enters the surrounding soil. This study analyzed the changes about soil enzyme activity, non-targeted metabolomics, microbial community structure and function microbial community structure and function to assess the differences in the effects of uranium stress on rhizosphere and non-rhizosphere soil. Results showed that uranium stress significantly inhibited the activities of urease and sucrase in rhizosphere and non-rhizosphere, which had less effect on rhizosphere. Compare to the non-rhizosphere soil, the uranium stress induced the production of gibberellin A1, to promoted several metabolic pathways, such as nitrogen and PTS (Phosphotransferase system) metabolic in rhizosphere soil. The species and abundance of Aspergillus, Acidobacter, and Synechococcus in both rhizosphere and non-rhizosphere soil were decreased by uranium stress. However, the microorganisms in rhizosphere soil were less inhibited according to the soil metabolism and microbial network map analysis. Furthermore, the Chujaibacter in rhizosphere soil under uranium stress was found significantly positively correlated with lipid and organic oxygen compounds. Overall, the results indicated that ryegrass roots significantly alleviated the effects of uranium stress on soil microbial activity and population abundances, thus playing a protective role. The study also provided a theoretical basis for in-depth understanding of the biological effects, prevention and control mechanisms of uranium-contaminated soil.

Incorporating higher order network structures to improve miRNA-disease association prediction based on functional modularity.

As microRNAs (miRNAs) are involved in many essential biological processes, their abnormal expressions can serve as biomarkers and prognostic indicators to prevent the development of complex diseases, thus providing accurate early detection and prognostic evaluation. Although a number of computational methods have been proposed to predict miRNA-disease associations (MDAs) for further experimental verification, their performance is limited primarily by the inadequacy of exploiting lower order patterns characterizing known MDAs to identify missing ones from MDA networks. Hence, in this work, we present a novel prediction model, namely HiSCMDA, by incorporating higher order network structures for improved performance of MDA prediction. To this end, HiSCMDA first integrates miRNA similarity network, disease similarity network and MDA network to preserve the advantages of all these networks. After that, it identifies overlapping functional modules from the integrated network by predefining several higher order connectivity patterns of interest. Last, a path-based scoring function is designed to infer potential MDAs based on network paths across related functional modules. HiSCMDA yields the best performance across all datasets and evaluation metrics in the cross-validation and independent validation experiments. Furthermore, in the case studies, 49 and 50 out of the top 50 miRNAs, respectively, predicted for colon neoplasms and lung neoplasms have been validated by well-established databases. Experimental results show that rich higher order organizational structures exposed in the MDA network gain new insight into the MDA prediction based on higher order connectivity patterns.

RLFDDA: a meta-path based graph representation learning model for drug-disease association prediction.

BACKGROUND: Drug repositioning is a very important task that provides critical information for exploring the potential efficacy of drugs. Yet developing computational models that can effectively predict drug-disease associations (DDAs) is still a challenging task. Previous studies suggest that the accuracy of DDA prediction can be improved by integrating different types of biological features. But how to conduct an effective integration remains a challenging problem for accurately discovering new indications for approved drugs. METHODS: In this paper, we propose a novel meta-path based graph representation learning model, namely RLFDDA, to predict potential DDAs on heterogeneous biological networks. RLFDDA first calculates drug-drug similarities and disease-disease similarities as the intrinsic biological features of drugs and diseases. A heterogeneous network is then constructed by integrating DDAs, disease-protein associations and drug-protein associations. With such a network, RLFDDA adopts a meta-path random walk model to learn the latent representations of drugs and diseases, which are concatenated to construct joint representations of drug-disease associations. As the last step, we employ the random forest classifier to predict potential DDAs with their joint representations. RESULTS: To demonstrate the effectiveness of RLFDDA, we have conducted a series of experiments on two benchmark datasets by following a ten-fold cross-validation scheme. The results show that RLFDDA yields the best performance in terms of AUC and F1-score when compared with several state-of-the-art DDAs prediction models. We have also conducted a case study on two common diseases, i.e., paclitaxel and lung tumors, and found that 7 out of top-10 diseases and 8 out of top-10 drugs have already been validated for paclitaxel and lung tumors respectively with literature evidence. Hence, the promising performance of RLFDDA may provide a new perspective for novel DDAs discovery over heterogeneous networks.

CCAR2 functions downstream of the Shieldin complex to promote double-strand break end-joining.

The 53BP1-RIF1 pathway restricts the resection of DNA double-strand breaks (DSBs) and promotes blunt end-ligation by non-homologous end joining (NHEJ) repair. The Shieldin complex is a downstream effector of the 53BP1-RIF1 pathway. Here, we identify a component of this pathway, CCAR2/DBC1, which is also required for restriction of DNA end-resection. CCAR2 co-immunoprecipitates with the Shieldin complex, and knockout of CCAR2 in a BRCA1-deficient cell line results in elevated DSB end-resection, RAD51 loading, and PARP inhibitor (PARPi) resistance. Knockout of CCAR2 is epistatic with knockout of other Shieldin proteins. The S1-like RNA-binding domain of CCAR2 is required for its interaction with the Shieldin complex and for suppression of DSB end-resection. CCAR2 functions downstream of the Shieldin complex, and CCAR2 knockout cells have delayed resolution of Shieldin complex foci. Forkhead-associated (FHA)-dependent targeting of CCAR2 to DSB sites re-sensitized BRCA1-/-SHLD2-/- cells to PARPi. Taken together, CCAR2 is a functional component of the 53BP1-RIF1 pathway, promotes the refill of resected DSBs, and suppresses homologous recombination.

Genome-wide identification and functional analysis of cupin_1 domain-containing members involved in the responses to Sclerotinia sclerotiorum and abiotic stress in Brassica napus.

Cupin_1 domain-containing proteins (CDPs) are ubiquitously present in higher plants, which are known to play essential roles in various biological processes. In this study, we carried out genome-wide characterization and systematic investigation of the CDP genes in Brassica napus. A total of 96 BnCDPs, including 71 germin-like proteins (GLPs; proteins with a single cupin_1 domain) and 25 CDP bicupins (proteins with two cupin_1 domains), were identified and clustered into six distinct subfamilies (I-VI) based on the phylogenic analysis, gene structure and motif distribution. Further analysis indicated that whole-genome duplication (WGD) and segmental duplication are main contributors to the species-specific expansion of the BnCDP gene family, and all the duplicated genes subsequently underwent strong purification selection. The promoter region of BnCDPs showed enrichment of cis-regulatory elements associated with development, hormone and stress, as well as transcription factor binding sites, which validates the prediction that BnCDPs are widely involved in plant growth and biotic and abiotic stress responses. The BnCDPs in different subfamilies exhibited obvious differences in expression among 30 developmental tissues/stages of B. napus, implying that BnCDPs may be involved in tissue- and stage-specific developmental processes. Similar trends in expression of most BnCDPs were observed under Sclerotinia sclerotiorum inoculation and four abiotic stresses (dehydration, cold, ABA and salinity), particularly the BnGLPs in subfamily I and III with single cupin_1 domain, revealing that BnCDPs are of great importance in the environmental adaption of B. napus. We then performed a genome-wide association study (GWAS) of 274 B. napus core germplasms on S. sclerotiorum resistance and identified four significantly associated loci harboring five BnGLPs. The expression levels of two candidate genes, BnGLP1.A08 and BnGLP1.C08, were significantly correlated with S. sclerotiorum resistance. Their functional responses to multiple stages of S. sclerotiorum inoculation and four abiotic stresses were further examined through qPCR. Overall, this study provides rich resources for research on the function and evolutionary playground of CDP genes.

Analysis of Tissue-Specific Defense Responses to Sclerotinia sclerotiorum in Brassica napus.

Sclerotinia stem rot (SSR) caused by Sclerotinia sclerotiorum (S. sclerotiorum) is the main disease threat of oilseed rape (Brassica napus), resulting in huge economic losses every year. SSR resistance manifests as quantitative disease resistance (QDR), and no gene with complete SSR resistance has been cloned or reported so far. Transcriptome analysis has revealed a large number of defense-related genes and response processes. However, the similarities and differences in the defense responses of different tissues are rarely reported. In this study, we analyzed the similarities and differences of different tissues in response to S. sclerotiorum at 24 h post inoculation (hpi) by using the published transcriptome data for respective leaf and stem inoculation. At 24 hpi, large differences in gene expression exist in leaf and stem, and there are more differentially expressed genes and larger expression differences in leaf. The leaf is more sensitive to S. sclerotiorum and shows a stronger response than stem. Different defense responses appear in the leaf and stem, and the biosynthesis of lignin, callose, lectin, chitinase, PGIP, and PR protein is activated in leaf. In the stem, lipid metabolism-mediated defense responses are obviously enhanced. For the common defense responses in both leaf and stem, the chain reactions resulting from signal transduction and biological process take the primary responsibility. This research will be beneficial to exploit the potential of different tissues in plant defense and find higher resistance levels of genotypic variability in different environments. Our results are significant in the identification of resistance genes and analysis of defense mechanisms.

Comparison of past and current dental school curricula for dental students of National Taiwan University.

Background/purpose: The complete curriculum schedule of the School of Dentistry, National Taiwan University (NTU) appeared in 1960. This study aimed to understand the development of dental education in Taiwan by comparing the past and current dental school curricula of NTU. Materials and methods: This study collected the 1960, 1990 and 2020 dental school curriculum schedules for dental students of NTU from the related websites and used the documentary and secondary data analyses to further compare the obtained data. Results: The number of credits for all the curricula offered by NTU to undergraduate dental students decreased from 264 in 1960 to 243 in 1990 and further to 242 in 2020 with a total decrease of 22 credits by 8.3%. The number (proportion) of credits of medicine courses decreased from 102 (38.6%) in 1960 to 52 (21.4%) in 1990, and then increased to 60 (24.8%) in 2020, with a total decrease of 42 credits by 41.2%, while those of dentistry courses increased from 70 (26.5%) in 1960 to 122 (50.2%) in 1990 and further to 132 (54.5%) in 2020, with a total increase of 62 credits by 88.6%. Among them, clinical practice of dentistry had the greatest growth with a total increase of 42 credits by 233.3%. Conclusion: The increase of dentistry courses and the decrease of medicine courses are the general trends for modern dental education. The dental school of NTU has the ability to provide more refined dentistry courses to catch the world trend of dental education.

Feasibility and discriminatory value of tissue motion annular displacement in sepsis-induced cardiomyopathy: a single-center retrospective observational study.

BACKGROUND: There is no formal diagnostic criterion for sepsis-induced cardiomyopathy (SICM), but left ventricular ejection fraction (LVEF) < 50% was the most commonly used standard. Tissue motion annular displacement (TMAD) is a novel speckle tracking indicator to quickly assess LV longitudinal systolic function. This study aimed to evaluate the feasibility and discriminatory value of TMAD for predicting SICM, as well as prognostic value of TMAD for mortality. METHODS: We conducted a single-center retrospective observational study in patients with sepsis or septic shock who underwent echocardiography examination within the first 24 h after admission. Basic clinical information and conventional echocardiographic data, including mitral annular plane systolic excursion (MAPSE), were collected. Based on speckle tracking echocardiography (STE), global longitudinal strain (GLS) and TMAD were, respectively, performed offline. The parameters acquisition rate, inter- and intra-observer reliability, time consumed for measurement were assessed for the feasibility analysis. Areas under the receiver operating characteristic curves (AUROC) values were calculated to assess the discriminatory value of TMAD/GLS/MAPSE for predicting SICM, defined as LVEF < 50%. Kaplan-Meier survival curve analysis was performed according to the cutoff values in predicting SICM. Cox proportional hazards model was performed to determine the risk factors for 28d and in-hospital mortality. RESULTS: A total of 143 patients were enrolled in this study. Compared with LVEF, GLS or MAPSE, TMAD exhibited the highest parameter acquisition rate, intra- and inter-observer reliability. The mean time for offline analyses with TMAD was significantly shorter than that with LVEF or GLS (p < 0.05). According to the AUROC analysis, TMADMid presented an excellent discriminatory value for predicting SICM (AUROC > 0.9). Patients with lower TMADMid (< 9.75 mm) had significantly higher 28d and in-hospital mortality (both p < 0.05). The multivariate Cox proportional hazards model revealed that BMI and SOFA were the independent risk factors for 28d and in-hospital mortality in sepsis cases, but TMAD was not. CONCLUSION: STE-based TMAD is a novel and feasible technology with promising discriminatory value for predicting SICM with LVEF < 50%.