Prophylactic Supplementation with Lactobacillus Reuteri or Its Metabolite GABA Protects Against Acute Ischemic Cardiac Injury

The gut microbiome has emerged as a potential target for the treatment of cardiovascular disease. Ischemia/reperfusion (I/R) after myocardial infarction is a serious complication and whether certain gut bacteria can serve as a treatment option remains unclear. Lactobacillus reuteri (L. reuteri) is a well-studied probiotic that can colonize mammals including humans with known cholesterol-lowering properties and anti-inflammatory effects. Here, the prophylactic cardioprotective effects of L. reuteri or its metabolite γ-aminobutyric acid (GABA) against acute ischemic cardiac injury caused by I/R surgery are demonstrated. The prophylactic gavage of L. reuteri or GABA confers cardioprotection mainly by suppressing cardiac inflammation upon I/R. Mechanistically, GABA gavage results in a decreased number of proinflammatory macrophages in I/R hearts and GABA gavage no longer confers any cardioprotection in I/R hearts upon the clearance of macrophages. In vitro studies with LPS-stimulated bone marrow-derived macrophages (BMDM) further reveal that GABA inhibits the polarization of macrophages toward the proinflammatory M1 phenotype by inhibiting lysosomal leakage and NLRP3 inflammasome activation. Together, this study demonstrates that the prophylactic oral administration of L. reuteri or its metabolite GABA attenuates macrophage-mediated cardiac inflammation and therefore alleviates cardiac dysfunction after I/R, thus providing a new prophylactic strategy to mitigate acute ischemic cardiac injury.

[Identification of key genes in Wilms tumor based on high-throughput RNA sequencing and their impacts on prognosis and immune responses]

OBJECTIVE

To identify the key genes differentially expressed in Wilms tumor and analyze their potential impacts on prognosis and immune responses of the patients.

METHODS

High-throughput RNA sequencing was used to identify the differentially expressed mRNAs in clinical samples of Wilms tumor and paired normal tissues, and their biological functions were analyzed using GO, KEGG and GSEA enrichment analyses. The hub genes were identified using STRING database, based on which a prognostic model was constructed using LASSO regression. The mutations of the key hub genes were analyzed and their impacts on immunotherapy efficacy was predicted using the cBioPortal platform. RT-qPCR was used to verify the differential expressions of the key hub genes in Wilms tumor.

RESULTS

Of the 1612 differentially expressed genes identified in Wilms tumor, 1030 were up-regulated and 582 were down-regulated, involving mainly cell cycle processes and immune responses. Ten hub genes were identified, among which 4 genes (TP53, MED1, CCNB1 and EGF) were closely related to the survival of children with Wilms tumor. A 3-gene prognostic signature was constructed through LASSO regression analysis, and the patients stratified into with high- and low-risk groups based on this signature had significantly different survival outcomes (HR=1.814, log-rank P=0.002). The AUCs of the 3-, 5- and 7-year survival ROC curves of this model were all greater than 0.7. The overall mutations in the key hub genes or the individual mutations in TP53/CCNB1 were strongly correlated with a lower survival rates, and a high TP53 expression was correlated with a poor immunotherapy efficacy. RT-qPCR confirmed that the key hub genes had significant differential expressions in Wilms tumor tissues and cells.

CONCLUSION

TP53 gene plays an important role in the Wilms tumor and may potentially serve as a new immunotherapeutic biomarker as well as a therapeutic target.

Multiple serous cavity effusion screening based on smear images using vision transformer

Serous cavity effusion is a prevalent pathological condition encountered in clinical settings. Fluid samples obtained from these effusions are vital for diagnostic and therapeutic purposes. Traditionally, cytological examination of smears is a common method for diagnosing serous cavity effusion, renowned for its convenience. However, this technique presents limitations that can compromise its efficiency and diagnostic accuracy. This study aims to overcome these challenges and introduce an improved method for the precise detection of malignant cells in serous cavity effusions. We have developed a transformer-based classification framework, specifically employing the vision transformer (ViT) model, to fulfill this objective. Our research involved collecting smear images and corresponding cytological reports from 161 patients who underwent serous cavity drainage. We meticulously annotated 4836 patches from these images, identifying regions with and without malignant cells, thus creating a unique dataset for smear image classification. The findings of our study reveal that deep learning models, particularly the ViT model, exhibit remarkable accuracy in classifying patches as malignant or non-malignant. The ViT model achieved an impressive area under the receiver operating characteristic curve (AUROC) of 0.99, surpassing the performance of the convolutional neural network (CNN) model, which recorded an AUROC of 0.86. Additionally, we validated our models using an external cohort of 127 patients. The ViT model sustained its high-level screening performance, achieving an AUROC of 0.98 at the patient level, compared to the CNN model's AUROC of 0.84. The visualization of our ViT models confirmed their capability to precisely identify regions containing malignant cells in multiple serous cavity effusion smear images. In summary, our study demonstrates the potential of deep learning models, particularly the ViT model, in automating the screening process for serous cavity effusions. These models offer significant assistance to cytologists in enhancing diagnostic accuracy and efficiency. The ViT model stands out for its advanced self-attention mechanism, making it exceptionally suitable for tasks that necessitate detailed analysis of small, sparsely distributed targets like cellular clusters in serous cavity effusions.

Spiking Neural Network for Ultralow-Latency and High-Accurate Object Detection

Spiking Neural Networks (SNNs) have attracted significant attention for their energy-efficient and brain-inspired event-driven properties. Recent advancements, notably Spiking-YOLO, have enabled SNNs to undertake advanced object detection tasks. Nevertheless, these methods often suffer from increased latency and diminished detection accuracy, rendering them less suitable for latency-sensitive mobile platforms. Additionally, the conversion of artificial neural networks (ANNs) to SNNs frequently compromises the integrity of the ANNs' structure, resulting in poor feature representation and heightened conversion errors. To address the issues of high latency and low detection accuracy, we introduce two solutions: timestep compression and spike-time-dependent integrated (STDI) coding. Timestep compression effectively reduces the number of timesteps required in the ANN-to-SNN conversion by condensing information. The STDI coding employs a time-varying threshold to augment information capacity. Furthermore, we have developed an SNN-based spatial pyramid pooling (SPP) structure, optimized to preserve the network's structural efficacy during conversion. Utilizing these approaches, we present the ultralow latency and highly accurate object detection model, SUHD. SUHD exhibits exceptional performance on challenging datasets like PASCAL VOC and MS COCO, achieving a remarkable reduction of approximately 750 times in timesteps and a 30% enhancement in mean average precision (mAP) compared to Spiking-YOLO on MS COCO. To the best of our knowledge, SUHD is currently the deepest spike-based object detection model, achieving ultralow timesteps for lossless conversion.

MG-Trans: Multi-Scale Graph Transformer With Information Bottleneck for Whole Slide Image Classification

Multiple instance learning (MIL)-based methods have become the mainstream for processing the megapixel-sized whole slide image (WSI) with pyramid structure in the field of digital pathology. The current MIL-based methods usually crop a large number of patches from WSI at the highest magnification, resulting in a lot of redundancy in the input and feature space. Moreover, the spatial relations between patches can not be sufficiently modeled, which may weaken the model's discriminative ability on fine-grained features. To solve the above limitations, we propose a Multi-scale Graph Transformer (MG-Trans) with information bottleneck for whole slide image classification. MG-Trans is composed of three modules: patch anchoring module (PAM), dynamic structure information learning module (SILM), and multi-scale information bottleneck module (MIBM). Specifically, PAM utilizes the class attention map generated from the multi-head self-attention of vision Transformer to identify and sample the informative patches. SILM explicitly introduces the local tissue structure information into the Transformer block to sufficiently model the spatial relations between patches. MIBM effectively fuses the multi-scale patch features by utilizing the principle of information bottleneck to generate a robust and compact bag-level representation. Besides, we also propose a semantic consistency loss to stabilize the training of the whole model. Extensive studies on three subtyping datasets and seven gene mutation detection datasets demonstrate the superiority of MG-Trans.

Norovirus outbreaks in hospitals in China: a systematic review

BACKGROUND

Norovirus outbreaks in hospitals can potentially impair patient care and result in significant financial expenses. There is currently limited information on hospital norovirus outbreaks in the Chinese mainland.

AIM

To systematically review the published literature to describe the characteristics of norovirus outbreaks in Chinese mainland hospitals to facilitate prompt identification and control of outbreaks.

METHODS

A systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis standards. Databases including PubMed, Web of Science, and Chinese Journals Online databases (China National Knowledge Infrastructure (CNKI), Chinese Wan Fang digital database (WANFANG) were searched from inception to July 18th, 2022.

FINDINGS

A total of 41 norovirus Chinese hospital outbreaks occurring before July 18th, 2022 were reported in 32 articles. Most reported outbreaks were from Shanghai and Beijing, and occurred in December and January. Cases were mainly adults. The male:female ratio was 1.22:1. The majority of cases in norovirus outbreaks were hospitalized patients (56.82%); medical staff were affected in 15 outbreaks. Norovirus outbreaks occurred in both private and public hospitals, and in secondary and tertiary care centres, and occurred mainly in internal medicine and geriatric departments. Person-to-person transmission was the primary transmission mode and GII was more prevalent.

CONCLUSION

Norovirus outbreaks in hospitals can affect both patients and healthcare workers, sometimes causing serious financial losses. In order to have a more complete understanding of the disease burden caused by norovirus outbreaks, surveillance needs to be established in hospitals.

[Epidemiological and clinical characteristics of human ocular helaziasis in China from 2011 to 2022 based on bibliometrics]

OBJECTIVE

To understand the clinical and epidemiological characteristics of human ocular thelaziasis patients in China.

METHODS

Case reports regarding human ocular thelaziasis cases in China were retrieved in international and national electronic databases, including CNKI, VIP, CBM, Traditional Chinese Medical Literature Analysis and Retrieval System, Wanfang Database, PubMed and Web of Science from 2011 to 2022. Patients' gender, age, clinical symptoms, treatment, recurrence, site of infections, time of onset, affected eye, affected sites, number of infected Thelazia callipaeda, sex of T. callipaeda and source of infections were extracted for descriptive analyses.

RESULTS

A total of 85 eligible publications were included, covering 101 cases of human ocular thelaziasis, including 57 males (56.44%) and 44 females (43.56%) and aged from 3 months to 85 years. The main clinical manifestations included foreign body sensation (56 case-times, 22.49%), eye itching (38 case-times, 15.26%), abnormal or increased secretions (36 case-times, 14.46%), tears (28 case-times, 11.24%) and eye redness (28 case-times, 11.24%), and conjunctival congestion (50 case-times, 41.67%) was the most common clinical sign. The most common main treatment (99/101, 98.02%) was removal of parasites from eyes using ophthalmic forceps, followed by administration with ofloxacin and pranoprofen. In publications presenting thelaziasis recurrence, there were 90 cases without recurrence (97.83%) and 2 cases with recurrence (2.17%). Of all cases, 51.96% were reported in four provinces of Hubei, Shandong, Sichuan, Hebei and Henan, and ocular thelaziasis predominantly occurred in summer (42.19%) and autumn (42.19%). In addition, 56.45% (35/62) had a contact with dogs.

CONCLUSIONS

The human thelaziasis cases mainly occur in the continental monsoon and subtropical monsoon climate areas such as the Yellow River and the Yangtze River basin, and people of all ages and genders have the disease, with complex clinical symptoms and signs. Personal hygiene is required during the contact with dogs, cats and other animals, and individual protection is required during outdoor activities to prevent thelaziasis.

Crystal Growth of Defect-Free Single-Crystalline Fibers in Super-High Supersaturation Solution

By controlling the supersaturation and choosing high-quality seeds, we successfully suppress the prismatic growth of the tetragonal potassium dihydrogen phosphate (KDP) SCFs, realize the rapid growth along the [001] direction, and obtain SCFs less than 10 μm in width with lengths of centimeters. The experimental results show that there exist critical supersaturation points, 22.40% and 41.41% at 25 °C, for initiating the growth of KDP SCF on its pyramidal and prismatic faces, respectively, which are quite different from those of the bulk crystals. We use the mechanism of 2D nucleation on smooth faces to explain the peculiar phenomena, assuming that there is no 2D or 3D defect on the surfaces of the seed fiber crystal. The assumption is supported by AFM observation of the surface micromorphology of the SCFs. Our solution growth technique developed can be used to grow ultrafine SCFs unable to be achieved by existing melt growth techniques.

Highly Stable Spatio-Temporal Prediction Network of Wavefront Sensor Slopes in Adaptive Optics

Adaptive Optics (AO) technology is an effective means to compensate for wavefront distortion, but its inherent delay error will cause the compensation wavefront on the deformable mirror (DM) to lag behind the changes in the distorted wavefront. Especially when the change in the wavefront is higher than the Shack-Hartmann wavefront sensor (SHWS) sampling frequency, the multi-frame delay will seriously limit its correction performance. In this paper, a highly stable AO prediction network based on deep learning is proposed, which only uses 10 frames of prior wavefront information to obtain high-stability and high-precision open-loop predicted slopes for the next six frames. The simulation results under various distortion intensities show that the prediction accuracy of six frames decreases by no more than 15%, and the experimental results also verify that the open-loop correction accuracy of our proposed method under the sampling frequency of 500 Hz is better than that of the traditional non-predicted method under 1000 Hz.

[Evaluation of the clinical manifestations of COVID-19 in patients with aplastic anemia undergoing immunosuppressive therapy: a prospective cohort study (NICHE)]

Objective: To investigate the clinical features of coronavirus disease 2019 (COVID-19) in patients with aplastic anemia (AA) undergoing immunosuppressive therapy (IST) . Methods: In this prospective cohort study, we collected the demographic and clinical data of patients with AA and COVID-19 from December 1, 2022, to January 31, 2023. We described the clinical features of COVID-19 among patients with AA and evaluated the effects of IST on the signs and severity of COVID-19. Results: A total of 170 patients with AA and COVID-19 were included. The common early symptoms, including fever, dizziness or headache, muscle or body aches, and sore throat, disappeared within 1-2 weeks. Approximately 25% of the patients had persistent fatigue within 2 weeks. Many patients experienced cough after an initial 1-3 days of infection, which lasted for more than 2 weeks. There were no differences in the duration of total fever episodes and maximum body temperature when patients were stratified according to whether or not they underwent IST, by IST duration, or by use of anti-lymphocyte globulin (ALG) (P>0.05). No differences were observed in the occurrence of symptoms in either the early or recovery stages when patients with AA were stratified according to whether or not they underwent IST, or by IST duration (P>0.05). However, patients who received ALG had fewer fever episodes within 1 week after infection (P=0.035) and more sore throat episodes within 2 weeks after infection (P=0.015). There were no other significant differences in clinical symptoms between patients who did and patients who did not receive ALG (P>0.05) . Conclusion: The majority of patients with AA and COVID-19 recovered within 2 weeks of noticing symptoms when treated with IST.

Dual-Role of Polyelectrolyte-Tethered Benzimidazolium Cation in Promoting CO2 /Pure Water Co-Electrolysis to Ethylene

Electrochemical CO2 reduction reaction (CO2 RR), as a promising route to realize negative carbon emissions, is known to be strongly affected by electrolyte cations (i.e., cation effect). In contrast to the widely-studied alkali cations in liquid electrolytes, the effect of organic cations grafted on alkaline polyelectrolytes (APE) remains unexplored, although APE has already become an essential component of CO2 electrolyzers. Herein, by studying the organic cation effect on CO2 RR, we find that benzimidazolium cation (Beim+ ) significantly outperforms other commonly-used nitrogenous cations (R4 N+ ) in promoting C2+ (mainly C2 H4 ) production over copper electrode. Cyclic voltammetry and in situ spectroscopy studies reveal that the Beim+ can synergistically boost the CO2 to *CO conversion and reduce the proton supply at the electrocatalytic interface, thus facilitating the *CO dimerization toward C2+ formation. By utilizing the homemade APE ionomer, we further realize efficient C2 H4 production at an industrial-scale current density of 331 mA cm-2 from CO2 /pure water co-electrolysis, thanks to the dual-role of Beim+ in synergistic catalysis and ionic conduction. This study provides a new avenue to boost CO2 RR through the structural design of polyelectrolytes.

A Structure-Aware Hierarchical Graph-Based Multiple Instance Learning Framework for pT Staging in Histopathological Image

Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to surrounding tissues, which relates to the prognosis and treatment choices. The pT staging relies on the field-of-views from multiple magnifications in the gigapixel images, which makes pixel-level annotation difficult. Therefore, this task is usually formulated as a weakly supervised whole slide image (WSI) classification task with the slide-level label. Existing weakly-supervised classification methods mainly follow the multiple instance learning paradigm, which takes the patches from single magnification as the instances and extracts their morphological features independently. However, they cannot progressively represent the contextual information from multiple magnifications, which is critical for pT staging. Therefore, we propose a structure-aware hierarchical graph-based multi-instance learning framework (SGMF) inspired by the diagnostic process of pathologists. Specifically, a novel graph-based instance organization method is proposed, namely structure-aware hierarchical graph (SAHG), to represent the WSI. Based on that, we design a novel hierarchical attention-based graph representation (HAGR) network to capture the critical patterns for pT staging by learning cross-scale spatial features. Finally, the top nodes of SAHG are aggregated by a global attention layer for bag-level representation. Extensive studies on three large-scale multi-center pT staging datasets with two different cancer types demonstrate the effectiveness of SGMF, which outperforms state-of-the-art up to 5.6% in the F1 score.

[Y-shaped osteotomy in the apical vertebra for treating congenital complex rigid scoliosis:at least 2-year follow-up]

Objective: To investigate the clinical outcome of the coronal Y-shaped osteotomy in the apical vertebra for treating congenital complex rigid scoliosis. Methods: A retrospective analysis was conducted on 66 cases who underwent Y-shaped osteotomy treatment for congenital complex rigid scoliosis in the uppermost vertebra at the Department of Orthopedics,the Second Hospital of Shanxi Medical University from June 2007 to August 2020. There were 19 males and 47 females,with an age of (13.1±5.3) years(range:2 to 30 years).Classification of congenital scoliosis:25 cases (37.9%) were incomplete,13 cases (19.7%) were dysarthritic,and 28 cases (42.4%) were mixed. There were 25 cases (37.9%) with thoracic or rib malformations. 45 cases (68.2%) were complicated with spinal cord malformation.The main radiological indicators included Cobb angle of the curvature,Cobb angle of the local bend,apical vertebral translation (AVT),trunk shift (TS),thoracic trunk shift (TTS),radiographic shoulder height (RSH),coronal balance and sagittal vertebral axis. The preoperative,postoperative immediate,and last follow-up radiological indicators were collected and the operation time,blood loss,hospitalization time,and operation-related complications were recorded. Data were compared by repeated measure ANOVA and paired-t test. Results: All patients underwent surgery successfully. The duration of the first surgery was (221.4±52.8) minutes,and the blood loss during the first surgery was (273.2±41.8) ml. The length of the first hospital stay was (8.8±1.7) days.Unilateral fixation was performed in 19 cases (28.8%),while bilateral fixation was performed in 47 cases (71.2%). The fused segments were 7.5±2.9,and the vertebral pedicle screw density was (68.5±20.6)%. The follow-up time for the 66 patients was (36.7±17.0) months(range:24 to 102 months).The main curve Cobb Angle was improved from (58.5±18.9)°before surgery to (21.1±11.8)°after surgery,and was (23.6±15.3) ° at the last follow-up(F=273.957,P<0.01),with a correction rate of 66.2%. Segmental curve Cobb Angle was improved from (47.9±18.0)° to (16.0±11.3)° after surgery,and was (16.8±12.8) °at the last follow-up (F=270.483,P<0.01)with a correction rate of 69.2%. The AVT,TS,TTS and RSH values improved significantly at the final follow-up (all P<0.05),while coronal balance and sagittal vertical axis were maintained without significant differences between pre-operation and post-operation(both P>0.05). A total of 5 patients underwent staged operation,all of which were residual scoliosis aggravated after the first stage of orthosis operation and had good prognosis after the second stage of operation. Conclusions: Y-shaped osteotomy for the treatment of congenital rigid scoliosis results in good clinical and radiological outcomes without serious complications. This procedure can be considered as an option for the treatment of congenital complex rigid scoliosis.

Object-independent wavefront sensing method based on an unsupervised learning model for overcoming aberrations in optical systems

This Letter introduces the idea of unsupervised learning into object-independent wavefront sensing for the first time, to the best of our knowledge, which can achieve fast phase recovery of arbitrary objects without labels. First, a fine feature extraction method which only depends on the wavefront aberrations is proposed. Then, a lightweight neural network and an optical feature system are combined to form an unsupervised learning model, and the neural network is promoted to be well trained by reversely outputting fine features. Simulation results prove that the proposed method can effectively overcome the aberrations (static or variable) existing in the optical system and achieve wavefront sensing of different objects with high precision and efficiency.

Applying machine learning methods for the analysis of two-dimensional mass spectra

In a measurement of isomeric yield-ratios in fission, the Phase-Imaging Ion-Cyclotron-Resonance technique, which projects the radial motions of ions in the Penning trap (JYFLTRAP) onto a position-sensitive micro-channel plate detector, has been applied. To obtain the yield ratio, that is the relative population of two states of an isomer pair, a novel analysis procedure has been developed to determine the number of detected ions in each state, as well as corrections for the detector efficiency and decay losses. In order to determine the population of the states in cases where their mass difference is too small to reach full separation, a Bayesian Gaussian Mixture model was implemented. The position-dependent efficiency of the micro-channel plate detector was calibrated by mapping it with 133 Cs+ ions, and a Gaussian Process was trained with the position data to construct an efficiency function that could be used to correct the recorded distributions. The obtained numbers of counts of excited and ground-state ions were used to derive the isomeric yield ratio, taking into account decay losses as well as feeding from precursors.

[Evaluation of the clinical efficacy of minimally invasive endoscopic surgery in the treatment of isolated non-syndromic sagittal synostosis in infants]

The current study aimed to evaluate the early efficacy in infants with isolated non-syndromic sagittal synostosis who underwent minimally invasive endoscopic-assisted surgery. The clinical data of infants with isolated non-syndromic sagittal synostosis who were admitted to the Department of Neurosurgery of the Children's Hospital of Nanjing Medical University and underwent endoscopic-assisted surgery from October 2018 to December 2021 were retrospectively analyzed. All the infants underwent minimally invasive endoscopic-assisted surgery, and were treated with supine sleeping position after surgery. Computer-aided reconstruction technique was used to reconstruct and measure the thin-slice CT scan images of the head before and 3 months after surgery, and the differences in cranial index (CI), cranial cavity volume and angle drawn between the cranial vertex, nasion, and opisthocranion (VNO angle) of preoperative and postoperative groups were analyzed. A total of 103 infants were included in the final analysis, including 85 males and 18 females. The age at surgery was (2.1±0.8) months, and the weight was (6.1±0.9) kg. The postoperative CI was (84±6)%, which increased obviously compared with the pre-operation [(70±5)%] (P<0.001). The cranial volume of post-operation was (947±130) cm³, which was larger than that of the pre-operation [(748±104) cm³] (P<0.001). The VNO angle after surgery was (45±4)°, which showed a significant reduction compared with the pre-operation [(55±4)°] (P<0.001). The correction of head shape was satisfactory. For the treatment of sagittal synostosis in infants, minimally invasive endoscopic-assisted surgery is safe and effective, and in the case of switching from an auxiliary helmet to a supine position, the postoperative correction efficacy of head shape is better.

Respiration-Responsive Colorful Room-Temperature Phosphorescent Materials and Assembly-Induced Phosphorescence Enhancement Strategies

It is still very challenging to obtain colorful and long-afterglow room-temperature phosphorescent (RTP) materials from pure organic polymers. Herein, it is found that chitosan (CS), a natural polymer, not only has its own RTP, but also reacts with different phosphorescent molecules to obtain a multicolor, long-afterglow RTP material. CS can emit RTP with a lifetime of 48 ms. In addition, CS is rich in amino groups, and grafting different phosphorescent molecules onto CS by an amidation reaction can modulate it to emit different colors of phosphorescence and obtain a series of colorful CS derivatives. The obtained polymer films also have ultra-long RTP due to the good film-forming ability. In addition, one of the CS derivatives selected with α-cyclodextrin is used to construct RTP materials with lifetimes of up to seconds. The host-guest interactions are used to suppress nonradiative relaxation and build crystalline domains, thus synergistically enhancing the RTP. Interestingly, the RTP properties of the CS derivative films are extremely sensitive to water and heat stimuli, because water broke the hydrogen bonds between adjacent CS molecules and thus altered the rigid environment in the material. Finally, they can be used as a stimuli-responsive ink and for monitoring environmental humidity.

[CD5L is elevated in the serum of patients with candidemia and promotes disease progression in mouse models]

OBJECTIVE

To investigate the changes of CD5L levels in patients with candidemia and explore the role of CD5L in progression of candidemia.

METHODS

Twenty healthy control individuals, 27 patients with bacteremia and 35 patients with candidemia were examined for serum CD5L levels using ELISA, and the correlations of CD5L level with other serological indicators were analyzed. A C57BL/6 mouse model of candidemia induced by intravenous injection of Candida albicans were treated with intraperitoneal injection of recombinant CD5L protein, and renal histopathological and serological changes were analyzed to assess renal injures. The effects of CD5L treatment on general condition, fungal burden, of survival of the mice were observed, and the changes in serum IL-6 and IL-8 levels of the mice were detected using ELISA.

RESULTS

CD5L levels were significantly elevated in patients with candidemia and positively correlated with WBC, BDG, Scr and PCT levels. The mouse model of candidemia also showed significantly increased serum and renal CD5L levels, and CD5L treatment significantly increased fungal burden in the renal tissue, elevated IL-6 and IL-8 levels in the serum and kidney, aggravated renal tissue damage, and reduced survival rate of candidemia mice.

CONCLUSION

Serum CD5L levels are increased in patients with candidemia, and treatment with CD5L aggravates candidemia in mouse models.

[Clinical features and long-term prognosis of diabetic patients with low or intermediate complexity coronary artery disease post percutaneous coronary intervention]

Objective: To investigate the clinical features and long-term prognostic factors of diabetic patients with low or intermediate complexity coronary artery disease (CAD) post percutaneous coronary intervention (PCI). Methods: This was a prospective, single-centre observational study. Consecutive diabetic patients with SYNTAX score (SS)≤32 undergoing PCI between January and December 2013 in Fuwai hospital were included in this analysis. The patients were divided into two groups based on SS, namely SS≤22 group and SS 23-32 group. Multivariate Cox regression analysis was performed to identify independent factors related to poor 5-year prognosis. The primary outcomes were cardiac death and recurrent myocardial infarction, the secondary outcomes were all cause death and revascularization. Results: Of the 3 899 patients included in the study, 2 888 were men (74.1%); mean age was 59.4±9.8 years. There were 3 450 patients in the SS≤22 group and 449 patients in the SS 23-32 group. Compared with SS≤22 group, the incidence of revascularization was higher in SS 23-32 group (18.9% (85/449) vs. 15.2% (524/3450), log-rank P=0.019). There was no significant difference in all-cause death, cardiac death and recurrent myocardial infarction between the two groups (log-rank P>0.05). Multivariate Cox regression analysis showed that age (HR=1.05, 95%CI 1.02-1.08, P<0.001), chronic obstructive pulmonary disease (HR=3.12, 95%CI 1.37-7.07, P=0.007) and creatinine clearance rate (CCr)<60 ml/min (HR=3.67, 95%CI 2.05-6.58, P<0.001) were independent risk factors for 5-year cardiac death, while left ventricular ejection fraction (HR=0.94, 95%CI 0.91-0.96, P<0.001) was a protective factor. Previous PCI (HR=2.04, 95%CI 1.38-3.00, P<0.001), blood glucose level≥11.1 mmol/L on admission (HR=2.49, 95%CI 1.32-4.70, P=0.005) and CCr<60 ml/min (HR=1.85, 95%CI 1.14-2.99, P=0.012) were independent risk factors for 5-year recurrent myocardial infarction. The SS of 23-32 was independently associated with risk of revascularization (HR=1.54, 95%CI 1.09-2.16, P=0.014), after adjusting for residual SS. Residual SS was not a risk factor for 5-year prognosis. Conclusions: In diabetic patients with low-or intermediate complexity CAD, SS 23-32 is associated with increased risk of 5-year revascularization; the clinical characteristics of the patients are associated with the long-term mortality and recurrent myocardial infarction, but not related to revascularization.

Childhood Leukemia Classification via Information Bottleneck Enhanced Hierarchical Multi-Instance Learning

Leukemia classification relies on a detailed cytomorphological examination of Bone Marrow (BM) smear. However, applying existing deep-learning methods to it is facing two significant limitations. Firstly, these methods require large-scale datasets with expert annotations at the cell level for good results and typically suffer from poor generalization. Secondly, they simply treat the BM cytomorphological examination as a multi-class cell classification task, thus failing to exploit the correlation among leukemia subtypes over different hierarchies. Therefore, BM cytomorphological estimation as a time-consuming and repetitive process still needs to be done manually by experienced cytologists. Recently, Multi-Instance Learning (MIL) has achievedmuch progress in data-efficient medical image processing, which only requires patient-level labels (which can be extracted from the clinical reports). In this paper, we propose a hierarchical MIL framework and equip it with Information Bottleneck (IB) to tackle the above limitations. First, to handle the patient-level label, our hierarchical MIL framework uses attention-based learning to identify cells with high diagnostic values for leukemia classification in different hierarchies. Then, following the information bottleneck principle, we propose a hierarchical IB to constrain and refine the representations of different hierarchies for better accuracy and generalization. By applying our framework to a large-scale childhood acute leukemia dataset with corresponding BM smear images and clinical reports, we show that it can identify diagnostic-related cells without the need for cell-level annotations and outperforms other comparison methods. Furthermore, the evaluation conducted on an independent test cohort demonstrates the high generalizability of our framework.

Dual Attention and Patient Similarity Network for drug recommendation

MOTIVATION

Artificially making clinical decisions for patients with multi-morbidity has long been considered a thorny problem due to the complexity of the disease. Drug recommendations can assist doctors in automatically providing effective and safe drug combinations conducive to treatment and reducing adverse reactions. However, the existing drug recommendation works ignored two critical information. (i) Different types of medical information and their interrelationships in the patient's visit history can be used to construct a comprehensive patient representation. (ii) Patients with similar disease characteristics and their corresponding medication information can be used as a reference for predicting drug combinations.

RESULTS

To address these limitations, we propose DAPSNet, which encodes multi-type medical codes into patient representations through code- and visit-level attention mechanisms, while integrating drug information corresponding to similar patient states to improve the performance of drug recommendation. Specifically, our DAPSNet is enlightened by the decision-making process of human doctors. Given a patient, DAPSNet first learns the importance of patient history records between diagnosis, procedure and drug in different visits, then retrieves the drug information corresponding to similar patient disease states for assisting drug combination prediction. Moreover, in the training stage, we introduce a novel information constraint loss function based on the information bottleneck principle to constrain the learned representation and enhance the robustness of DAPSNet. We evaluate the proposed DAPSNet on the public MIMIC-III dataset, our model achieves relative improvements of 1.33%, 1.20% and 2.03% in Jaccard, F1 and PR-AUC scores, respectively, compared to state-of-the-art methods.

AVAILABILITY AND IMPLEMENTATION

The source code is available at the github repository: https://github.com/andylun96/DAPSNet.

A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images

Cancer region detection (CRD) and subtyping are two fundamental tasks in digital pathology image analysis. The development of data-driven models for CRD and subtyping on whole-slide images (WSIs) would mitigate the burden of pathologists and improve their accuracy in diagnosis. However, the existing models are facing two major limitations. Firstly, they typically require large-scale datasets with precise annotations, which contradicts with the original intention of reducing labor effort. Secondly, for the subtyping task, the non-cancerous regions are treated as the same as cancerous regions within a WSI, which confuses a subtyping model in its training process. To tackle the latter limitation, the previous research proposed to perform CRD first for ruling out the non-cancerous region, then train a subtyping model based on the remaining cancerous patches. However, separately training ignores the interaction of these two tasks, also leads to propagating the error of the CRD task to the subtyping task. To address these issues and concurrently improve the performance on both CRD and subtyping tasks, we propose a semi-supervised multi-task learning (MTL) framework for cancer classification. Our framework consists of a backbone feature extractor, two task-specific classifiers, and a weight control mechanism. The backbone feature extractor is shared by two task-specific classifiers, such that the interaction of CRD and subtyping tasks can be captured. The weight control mechanism preserves the sequential relationship of these two tasks and guarantees the error back-propagation from the subtyping task to the CRD task under the MTL framework. We train the overall framework in a semi-supervised setting, where datasets only involve small quantities of annotations produced by our minimal point-based (min-point) annotation strategy. Extensive experiments on four large datasets with different cancer types demonstrate the effectiveness of the proposed framework in both accuracy and generalization.

Utility of trio-based prenatal exome sequencing incorporating splice-site and mitochondrial genome assessment in pregnancies with fetal ultrasound anomalies: prospective cohort study

OBJECTIVE

To evaluate the utility of trio-based prenatal exome sequencing (pES), incorporating splice-site and mitochondrial genome assessment, in the prenatal diagnosis of fetuses with ultrasound anomalies and normal copy-number variant sequencing (CNV-seq) results.

METHODS

This was a prospective study of 90 ongoing pregnancies with ultrasound anomalies that underwent trio-based pES after receiving normal CNV-seq results, from September 2020 to November 2021, in a single center in China. By using pES with a panel encompassing exome coding and splicing regions as well as mitochondrial genome for fetuses and parents, we identified the underlying genetic causes of fetal anomalies, incidental fetal findings and parental carrier status. Information on pregnancy outcome and the impact of pES findings on parental decision-making was collected.

RESULTS

Of the 90 pregnancies included, 28 (31.1%) received a diagnostic result that could explain the fetal ultrasound anomalies. The highest diagnostic yield was noted for brain abnormalities (3/6 (50.0%)), followed by hydrops (4/9 (44.4%)) and skeletal abnormalities (13/34 (38.2%)). Collectively, 34 variants of 20 genes were detected in the 28 diagnosed cases, with 55.9% (19/34) occurring de novo. Variants of uncertain significance (VUS) associated with fetal phenotypes were detected in six (6.7%) fetuses. Interestingly, fetal (n = 4) and parental (n = 3) incidental findings (IFs) were detected in seven (7.8%) cases. These included two fetuses carrying a de-novo likely pathogenic (LP) variant of the CIC and FBXO11 genes, respectively, associated with neurodevelopmental disorders, and one fetus with a LP variant in a mitochondrial gene. The remaining fetus presented with unilateral renal dysplasia and was incidentally found to carry a pathogenic PKD1 gene variant resulting in adult-onset polycystic kidney, which was later confirmed to be inherited from the mother. In addition, parental heterozygous variants associated with autosomal recessive diseases were detected in three families, including one with additional fetal diagnostic findings. Diagnostic results or fetal IFs contributed to parental decision-making about termination of the pregnancy in 26 families (26/72 (36.1%)), while negative pES results or identification of VUS encouraged 40 families (40/72 (55.6%)) to continue their pregnancy, which ended in a live birth in all cases.

CONCLUSION

Trio-based pES can provide additional genetic information for pregnancies with fetal ultrasound anomalies without a CNV-seq diagnosis. The incidental findings and parental carrier status reported by trio-based pES with splice-site and mitochondrial genome analysis extend its clinical application, but careful genetic counseling is warranted. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Unsupervised Representation Learning for Tissue Segmentation in Histopathological Images: From Global to Local Contrast

Tissue segmentation is an essential task in computational pathology. However, relevant datasets for such a pixel-level classification task are hard to obtain due to the difficulty of annotation, bringing obstacles for training a deep learning-based segmentation model. Recently, contrastive learning has provided a feasible solution for mitigating the heavy reliance of deep learning models on annotation. Nevertheless, applying contrastive loss to the most abstract image representations, existing contrastive learning frameworks focus on global features, therefore, are less capable of encoding finer-grained features (e.g., pixel-level discrimination) for the tissue segmentation task. Enlightened by domain knowledge, we design three contrastive learning tasks with multi-granularity views (from global to local) for encoding necessary features into representations without accessing annotations. Specifically, we construct: (1) an image-level task to capture the difference between tissue components, i.e., encoding the component discrimination; (2) a superpixel-level task to learn discriminative representations of local regions with different tissue components, i.e., encoding the prototype discrimination; (3) a pixel-level task to encourage similar representations of different tissue components within a local region, i.e., encoding the spatial smoothness. Through our global-to-local pre-training strategy, the learned representations can reasonably capture the domain-specific and fine-grained patterns, making them easily transferable to various tissue segmentation tasks in histopathological images. We conduct extensive experiments on two tissue segmentation datasets, while considering two real-world scenarios with limited or sparse annotations. The experimental results demonstrate that our framework is superior to existing contrastive learning methods and can be easily combined with weakly supervised and semi-supervised segmentation methods.

[Safety of an inactivated 2019-nCoV vaccine (Vero) in adults aged 60 years and older]

Objective: To analyze the safety of an inactivated 2019-nCoV vaccine (Vero cell) in adults aged 60 years and older. Methods: A randomized, double-blind, placebo-controlled clinical study was conducted in May 2020 The eligible residents aged 60 and above were recruited in Renqiu city, Hebei Province. A total of 422 subjects (phase Ⅰ/Ⅱ:72/350) were enrolled. Two doses of the trial vaccine or placebo were randomly administered according to a 0 and 28-day immunization schedule. Subjects were randomly divided into two groups in Phase Ⅰ. Within each group, participants received vaccine or placebo in a ratio of 2∶1. Subjects were randomly divided into four groups in phase Ⅱ to receive low-dose, medium-dose, high-dose vaccine and placebo, respectively, in a ratio of 2∶2∶2∶1. A combination of regular follow-up and active reporting was used to observe adverse reactions within 28 days after vaccination, and compare the incidence rate of adverse reactions in the trial and control groups. Results: 422 subjects were (66.45±4.70) years old, and 48.82% were male (206/422). There were 100, 124, 124 and 74 patients enrolled into the low-dose, medium-dose, high-dose vaccine groups and the placebo group, respectively. One person without the vaccination was removed, and 421 participants who received at least one dose of vaccine were included in the safety analysis. Within 28 days after the first or second dose, a total of 20.67% (87/421) subjects had adverse reactions (both solicitation and non-solicitation). About 76 patients suffered grade 1 adverse reactions [18.05% (76/421)] and 22 patients suffered grade 2 adverse reactions [5.23% (22/421)]. No grade 3 or above adverse reactions occurred. A total of 19.71% (83/421) subjects had solicited adverse reactions. The most common grade 1 adverse reaction was injection site pain, followed by fever and fatigue. The most common grade 2 adverse reactions were fever and fatigue, followed by muscle pain and injection site redness. A total of 2.61% (11/421) subjects had unsolicited adverse reactions. A total of 1.66% (7/421) subjects had serious adverse events after vaccination, and no serious vaccine-related adverse events were reported. Conclusions: The inactivated SARS-CoV-2 vaccine is safe for people aged 60 years and above.

HistoML, a markup language for representation and exchange of histopathological features in pathology images

The study of histopathological phenotypes is vital for cancer research and medicine as it links molecular mechanisms to disease prognosis. It typically involves integration of heterogenous histopathological features in whole-slide images (WSI) to objectively characterize a histopathological phenotype. However, the large-scale implementation of phenotype characterization has been hindered by the fragmentation of histopathological features, resulting from the lack of a standardized format and a controlled vocabulary for structured and unambiguous representation of semantics in WSIs. To fill this gap, we propose the Histopathology Markup Language (HistoML), a representation language along with a controlled vocabulary (Histopathology Ontology) based on Semantic Web technologies. Multiscale features within a WSI, from single-cell features to mesoscopic features, could be represented using HistoML which is a crucial step towards the goal of making WSIs findable, accessible, interoperable and reusable (FAIR). We pilot HistoML in representing WSIs of kidney cancer as well as thyroid carcinoma and exemplify the uses of HistoML representations in semantic queries to demonstrate the potential of HistoML-powered applications for phenotype characterization.

Feasibility of an ultra-low dose contrast media protocol for coronary CT angiography

AIM

To evaluate the feasibility of an ultra-low volume contrast media (CM) protocol for coronary computed tomography angiography (CTA).

MATERIALS AND METHODS

In total, 214 patients receiving coronary CTA were enrolled prospectively and divided into group A (n=107) receiving a conventional dose of CM and group B (n=107) receiving an ultra-low dose. CT values of the right coronary artery (RCA), left anterior descending artery (LAD), and left circumflex artery (LCX) were measured and radiation doses recorded. The image quality was compared between the groups. Changes in renal function indices and proteinuria before, 24, and 72 hours after coronary CTA among those with chronic kidney disease (CKD) were also assessed.

RESULTS

There were significant differences in CT values and radiation doses between groups A and B. In group A, the average RCA, LAD, and LCX CT values were 412.5 ± 79.2, 423.5 ± 73.7, and 422.0 ± 88.1 HU, respectively. In group B, the average RCA, LAD, and LCX CT values were 275.2 ± 16.2, 277.8 ± 16.4, and 278.9 ± 16.5 HU, respectively. The radiation dose in the ultra-low protocol recipients (118.70 ± 18.52 mGy·cm) was significantly lower than that used in conventional coronary CTA (131.75 ± 20.96 mGy·cm). The image quality of group B was comparable to that of group A, satisfying the diagnostic requirement. In patients with mild CKD, there were no significant differences in renal functions after coronary CTA.

CONCLUSION

An ultra-low CM protocol was established for coronary CTA, providing comparable image quality and diagnostic yields but significantly lower radiation dose compared with a conventional protocol. This new protocol might be applicable to patients with mild CKD.

A novel multi-objective optimization framework for urban green-gray infrastructure implementation under impacts of climate change

Frequent urban flooding disasters can cause severe economic and property losses. Accordingly, the construction of sponge city has become critical to alleviating urban flooding. However, the functional and structural integration of Green Infrastructure (GI) and Gray Drainage Facility (GDF) is still a matter of concern. This study proposed a novel implementation framework for GI and GDF synchronization optimization (G-GSOIF) based on the SWMM and SUSTAIN models, and used data from Beilin District in Xi'an, China to verify the effects. The results show that the spatiotemporal integrated optimization design of GI and GDF proves to be effective in stormwater management. The total investment was reduced by 16.7% and economic benefit was increased by 15.4% based on disaster risk control, and the utilization rate of rainwater resources exceeded 40%. The Staged optimization model (SSOM) based on the SUSTAIN model established in the G-GSOIF was demonstrated to effectively cope with the impact of future climate change by adjusting and optimizing the design scheme dynamically in different simulation scenarios. Integrated LID (I-LID) measures are conducive for simulation of large catchment areas, and have the same implementation effect as distributed LID measures. The results of this study could support decision-making for urban stormwater management and sponge city construction.

Preanodized Cu Surface for Selective CO2 Electroreduction to C1 or C2+ Products

The electrochemical CO₂ reduction over Cu catalysts has shown great potential in producing a wide range of valuable chemicals, but it is still plagued by a poor controllability on product distribution. Herein, we demonstrate an effective regulation of CO₂ reduction paths through a preanodization treatment of Cu foil electrodes in different electrolytes. The Cu electrode exhibits a superior C₁ and C₂₊ product selectivity after being preanodized in NaClO₄ (Cu-NaClO₄) and Na₂HPO₄ electrolyte (Cu-Na₂HPO₄), respectively. Combined with in situ electrochemical Raman, ATR-SEIRAS, and SEM characterizations, the preferential C₁ path is due to the deposition of many Cu nanocrystals with dominant Cu(111) facets on the Cu-NaClO₄ electrode. In contrast, the preferential C₂₊ path over the Cu-Na₂HPO₄ is attributed to formation of a unique Cu nanodendritic morphology, which strengthens the *CO intermediate adsorption and induces an environment of low local H₂O/CO₂ stoichiometric ratio, thus facilitating C-C coupling for C₂₊ production. Our findings may shed light on the rational control of the CO₂ reduction path through engineering of the Cu surface structure.

Single-Cell Analysis Reveals Transcriptomic Reprogramming in Aging Cardiovascular Endothelial Cells

The senescence of cardiovascular endothelial cells (ECs) is a major risk factor in the development of aging-related cardiovascular diseases. However, the molecular dynamics in cardiovascular EC aging are poorly understood. Here, we characterized the transcriptomic landscape of cardiovascular ECs during aging and observed that ribosome biogenesis, inflammation, apoptosis and angiogenesis-related genes and pathways changed with age. We also highlighted the importance of collagen genes in the crosstalk between ECs and other cell types in cardiovascular aging. Moreover, transcriptional regulatory network analysis revealed Jun as a candidate transcription factor involved in murine cardiovascular senescence and we validated the upregulation of Jun in aged cardiovascular ECs both in vitro and in vivo. Altogether, our study reveals the transcriptomic reprogramming in the aging murine cardiovascular ECs, which deepens the understanding of the molecular mechanisms of cardiovascular aging and provides new insights into potential therapeutic targets against age-related cardiovascular diseases.

Exerimental method and preliminary studies of the passive containment water film evaporation mass transfer

For larger containments and higher operation parameters, characteristics of the outside cooling of the PCCS are very important for the analysis on the containment integrity. A preliminary analysis was made and a four-step experimental method was used to numerically analyze the falling water film evaporation for the advanced passive containment. Then, the water flow stability along the outside wall of the containment was studied. The results fit well with those correlations without airflow when the air velocity is less than 5.0 m/s. However, when the air velocity is larger than 5.0 m/s, the influence of the air velocity on the water film will appear and the mean water film thickness will be thicker. Based on the prototype operation parameters, experimental studies were carried and the results were compared with the Dittus-Boelter correlation within the operation ranges. A modification factor was proposed for the conservative application of this correlation for nuclear safety analysis.

Effects of Alzheimer's disease of varying severity on cardiac and autonomic function

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases in the elderly. The aim of this study was to explore the effects of AD on cardiac function and autonomic nervous function, and the feasibility of electrocardiogram (ECG) in monitoring the development of AD. APP/PS1 double transgenic mice were used in the Morris water maze (MWM) experiment to evaluate the changes of cognitive ability of AD mice, then the non-invasive ECG acquisition system was used and the changes of ECG intervals and heart rate variability (HRV) were analyzed. AD mice already had cognitive dysfunction at the age of 5 months, reaching the level of mild dementia, and the degree of dementia increased with the course of disease. There were no significant changes in ECG intervals in the AD group at each month. The mean square of successive RR interval differences, percentage of intervals >6 ms different from preceding interval, and normalized high frequency power component in the AD group were decreased and low-to-high frequency power ratio and normalized low frequency power component were increased. Combined with the results of the MWM, it was shown that the regulation mechanism of sympathetic and parasympathetic nerves in mice was already imbalanced in early stage AD, which was manifested as the increase of excessive activity of sympathetic nerves and the inhibition of parasympathetic activities. Therefore, ECG-based analysis of HRV may become a means of daily monitoring of AD and provide an auxiliary basis for clinical diagnosis.

Lnc-AC145676.2.1-6-3 can influence STX3-induced abnormal autophagy by sponging hsa-miR-1292-3p in intestinal aGVHD

OBJECTIVE

Intestinal acute graft-versus-host disease (aGVHD) is a serious complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Abnormal autophagy levels in intestinal aGVHD have been confirmed in many studies. LncRNAs exert coregulatory functions and participate in a variety of intracellular regulatory processes. In this study, we investigated how lnc-AC145676.2.1-6-3 regulates dysregulated STX3-related autophagy in aGVHD.

MATERIALS AND METHODS

First, we established a mouse model of aGVHD by transplanting a mononuclear cell suspension from Balb/c donor mice treated with 60Co X-rays into CB6F1 recipient mice. STX3-related indicators were analyzed by Western blotting (WB) and immunohistochemistry which confirmed that STX3 plays an important role in dysregulating autophagy in intestinal aGVHD. TNF-αinduced Caco-2 cells, which is an in vitro model of intestinal barrier dysfunction, were established to verify the effect of STX3. The direct interaction between the partners of lnc-AC145676.2.1-6-3-mediated hsa-miR-1292-3p and STX3 axis was evaluated by the Dual-Luciferase activity assay. We performed PCR, WB, and immunofluorescence in Caco-2 cells to determine whether the abnormal autophagy levels were influenced by lnc-AC145676.2.1-6-3.

RESULTS

The results showed that lnc-AC145676.2.1-6-3 could significantly suppress the number of autophagic vacuoles, the LC3-II/I ratio, and beclin1 levels by increasing STX3 levels.

CONCLUSIONS

Lnc-AC145676.2.1-6-3 may play an important role in intestinal aGVHD by targeting STX3.

An application research for near-surface repository of strontium-90 sorption kinetic model on mudrocks

In this study,90Sr was used as the test radionuclide to characterize the sorption kinetics and effects of initial 90Sr activity and remaining 90Sr in solid concentration were simulated for a near-surface repository. The study focused on the sorption characteristics of radionuclides in unsaturated groundwater environment (or vadose zone) is the important information for investigating the near-surface disposal of intermediate and low-level radioactive waste (ILLW). Moreover, the 90Sr sorption experiments reached equilibrium within 56 h, which fit to the first order sorption kinetic model, and the remaining 90Sr in mudrock samples showed obvious sorption equilibrium hysteresis, which fit to the second order sorption kinetic model. Before reaching the maximum sorption capacity, the sorption rate constant increases with 90Sr increasing; the distribution coefficient (Kd) of 56 h decreases with the remaining 90Sr decreasing. In addition, it showed that the slow sorption process dominated before the sorption reaches equilibrium. In fact, a reliable safety assessment methodology for on-going near-surface repository required a lot of the radionuclides parameters with local environment including the radionuclides sorption/desorption rate constant and maximum sorption capacity.

A Nonlinear Optimal Control Approach for Multi-DOF Brachiation Robots

This paper proposes a nonlinear optimal control approach for mulitple degrees of freedom (DOF) brachiation robots, which are often used in inspection and maintenance tasks of the electric power grid. Because of the nonlinear and multivariable structure of the related state-space model, as well as because of underactuation, the control problem of these robots is nontrivial. The dynamic model of the brachiation robots undergoes first approximate linearization with the use of Taylor series expansion around a temporary operating point which is recomputed at each iteration of the control method. For the approximately linearized model, an H-infinity feedback controller is designed. The linearization procedure relies on the Jacobian matrices of the brachiation robots’ state-space model. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the brachiation robots, under model uncertainties and external perturbations. For the computation of the controller’s feedback gains an algebraic Riccati equation is solved at each time-step of the control method. The global stability properties of the control scheme are proven through Lyapunov analysis. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the brachiation robots, under moderate variations of the control inputs.

Value of low-dose spiral CT combined with circulating miR-200b and miR-200c examinations for lung cancer screening in physical examination population

OBJECTIVE

  The aim of this study is to investigate the clinical value of low-dose spiral CT (LDCT), plasma miR-200b, and miR-200c combined screening for lung cancer screening in the physical examination population.

PATIENTS AND METHODS

From January 2016 to December 2018, the Physical Examination Center of our hospital underwent low-dose spiral CT lung cancer screening for 10,823 people aged ≥40 years. The quantitative Real Time-Polymerase Chain Reaction (qRT-PCR) was used to detect the relative expressions of miR-200b and miR-200c in plasma, analyze the imaging characteristics of suspicious nodules in the lung and the relative expressions of miR-200b and miR-200c in plasma.

RESULTS

A total of 2,919 pulmonary nodules were detected in the 10823 physical examination population, with a total detection rate of 26.97%, including 1523 males and 1396 females. 1081 positive nodules were detected with a detection rate of 9.99%. According to the Lung-RADS classification, the number of type 2 nodules was the highest, with a detection rate of 22.13%. Meanwhile, the rate of type 3 nodules was 3.15%, and the rate of type 4 nodules was 1.69%. The sensitivity, accuracy, and negative predictive value of LDCT, miR-200b, and miR-200c in the diagnosis of lung cancer were significantly improved compared with the individual tests, which were 94.74%, 90.16%, and 95.88%, respectively.

CONCLUSIONS

Low-dose spiral CT combined with plasma miR-200b and miR-200c for lung cancer screening in the physical examination population can help to detect lung cancer patients with early symptoms that are not significant, and achieve early diagnosis and early treatment.

Degree of peripheral Thyroxin Deiodination and recurrent cardiovascular events in euthyroid patients undergoing PCI: five-year findings from a large single-center cohort study

Background

In euthyroid patients undergoing percutaneous coronary intervention (PCI), it is still unclear whether thyroxin deiodination level can predict the recurrence of cardiovascular events (CVEs). Using free triiodothyronine to free thyroxine (FT3/FT4) ratio, a marker of peripheral thyroxin deiodination, we aim to investigate its association with recurrent long-term adverse events in this population.

Methods

3549 euthyroid patients with prior CVEs history undergoing PCI were consecutively enrolled in our study and subsequently divided into three FT3/FT4 ratio tertiles (T1&lt;2.41, n=1170; 2.41≤T2&lt;2.75, n=1198; T3&gt;2.75, n=1181). The primary endpoint was major adverse cardiovascular and cerebrovascular event (MACCE), a composite of all-cause death, myocardial infarction, stroke and revascularization. The secondary endpoints were all-cause death and cardiac death.

Results

The median follow-up time was 5 years. The incidence of all-cause death, cardiac death and MACCE were significantly higher among patients in the lowest FT3/FT4 tertile (P&lt;0.05). After adjustment of confounding factors, decreased FT3/FT4 ratio was independently associated with an increased risk of all-cause death (HR 1.82, 95% CI 1.13–2.93, P=0.014), cardiac death (HR 1.90, 95% CI 1.04–3.46, P=0.036) and MACCE (HR 1.33, 95% CI 1.10–1.60, P=0.003).

Conclusions

In euthyroid patients undergoing PCI, FT3/FT4 ratio, a surrogate marker of peripheral thyroxin deiodination, demonstrates a strong association with long-term recurrent cardiovascular events. Routine assessment of FT3/FT4 ratio might be a simple and effective tool for risk stratification in this specific patient population.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Key Research and Development Program of China (No. 2016YFC1301300, 2016YFC1301301); National Natural Science Foundation of China (No. 81770365)

Prognostic utility of fibrinogen in patients with coronary artery disease and prediabetes or diabetes following percutaneous coronary intervention: five-year findings from a large single-center cohort

Background

The prognosis for patients with coronary artery disease (CAD) remains unfavorable despite advances in treatment. Fibrinogen (FIB) is an independent risk factor for mortality and cardiovascular events in general population. However, the relationship between FIB and long-term mortality among CAD patients undergoing PCI is less investigated, especially in individuals concomitated with diabetes mellitus (DM) and prediabetes (Pre-DM).

Methods

6140 patients with CAD undergoing PCI were consecutively enrolled in our study and subsequently divided into three groups according to FIB levels (FIB-L, FIB-M, FIB-H). These patients were further grouped by glycemic metabolism state [normoglycemia (NG), Pre-DM, DM]. The primary endpoint was all-cause mortality. The secondary endpoint was cardiac mortality.

Results

FIB was positively associated with hemoglobin A1c (HbA1c) and fasting blood glucose (FBG) both in CAD patients with and without DM. During a median follow-up time of 5.1 years, elevated FIB was significantly associated with long-term mortality from all-cause (adjusted HR: 1.86; 95% CI: 1.28–2.69; P=0.001) and cardiac specific (adjusted HR: 1.82; 95% CI: 1.15–2.89; P=0.011). Similarly, patients with DM but not Pre-DM had increased risk of all-cause and cardiac mortality (all P&lt;0.05). When grouped by both FIB levels and glycemic metabolism state, diabetic patients with medium and high FIB levels had higher risk of mortality [(adjusted HR: 2.57; 95% CI: 1.12–5.89), (adjusted HR: 3.04; 95% CI: 1.35–6.82), all P&lt;0.05]. Notably, prediabetic patients with high FIB also had higher mortality risk (adjusted HR: 2.27; 95% CI: 1.01–5.12).

Conclusion

FIB was strongly associated with long-term all-cause and cardiac mortality among CAD patients undergoing PCI, especially in persons concomitated with DM and Pre-DM, indicating FIB test may help identify high-risk individuals in this specific patient population.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Key Research and Development Program of China (No. 2016YFC1301300, 2016YFC1301301); National Natural Science Foundation of China (No. 81770365)