Astragaloside IV promotes exosome secretion of endothelial progenitor cells to regulate PI3KR2/SPRED1 signaling and inhibit pyroptosis of diabetic endothelial cells

BACKGROUND AIMS

Treating chronic non-healing diabetic wounds and achieving complete skin regeneration has always been a critical clinical challenge.

METHODS

In order to address this issue, researchers conducted a study aiming to investigate the role of miR-126-3p in regulating the downstream gene PIK3R2 and promoting diabetic wound repair in endothelial progenitor cell (EPC)-derived extracellular vesicles. The study involved culturing EPCs with astragaloside IV, transfecting them with miR-126-3p inhibitor or mock plasmid, interfering with high glucose-induced damage in human umbilical vein endothelial cells (HUVECs) and treating diabetic skin wounds in rats.

RESULTS

The healing of rat skin wounds was observed through histological staining. The results revealed that treatment with miR-126-3p-overexpressing EPC-derived extracellular vesicles accelerated the healing of rat skin wounds and resulted in better tissue repair with slower scar formation. In addition, the transfer of EPC-derived extracellular vesicles with high expression of miR-126-3p to high glucose-damaged HUVECs increased their proliferation and invasion, reduced necrotic and apoptotic cell numbers and improved tube formation. In this process, the expression of angiogenic factors vascular endothelial growth factor (VEGF)A, VEGFB, VEGFC, basic fibroblast growth factor and Ang-1 significantly increased, whereas the expression of caspase-1, NRLP3, interleukin-1β, inteleukin-18, PIK3R2 and SPRED1 was suppressed. Furthermore, miR-126-3p was able to target and inhibit the expression of the PIK3R2 gene, thereby restoring the proliferation and migration ability of high glucose-damaged HUVEC.

CONCLUSIONS

In summary, these research findings demonstrate the important role of miR-126-3p in regulating downstream genes and promoting diabetic wound repair, providing a new approach for treating chronic non-healing diabetic wounds.

Allisartan Isoproxil Promotes Uric Acid Excretion by Interacting with Intestinal Urate Transporters in Hyperuricemic Zebrafish (Danio rerio)

To evaluate the urate-lowering effect and potential drug targets of antihypertensive agent allisartan isoproxil (ALI) and its bioactive metabolite EXP3174, we developed an acute hyperuricemic zebrafish model using potassium oxonate and xanthine sodium salt. Losartan potassium served as the positive control (reference drug). In this model, ALI and losartan potassium exerted a greater urate-lowering effect than EXP3174 indicating that the latter is not the critical substance for elimination of uric acid. The quantitative real-time PCR showed that ALI upregulates the expression of intestinal urate transporters genes ABCG2, PDZK1, and SLC2A9 (p<0.01). Thus, we can suggest that this substance promotes uric acid excretion mainly by interacting with intestinal urate transporters.

A Study on the Mediating Role of Emotional Solidarity between Authenticity Perception Mechanism and Tourism Support Behavior Intentions within Rural Homestay Inn Tourism

Rural homestay inns are an important part of rural tourism, and tourists’ support behavior intentions are important factors affecting whether rural homestay inns can be developed sustainably. The local authentic life experiences and realization of actual communication between the host and tourists are the main influencing factors for tourists to revisit, recommend, or provide support. Although previous studies have confirmed the influence of authenticity perception on tourists’ support behavior intentions from different perspectives, they have not analyzed the influence mechanism between them from the perspective of micro interpersonal emotional attitude. To further understand the impact mechanism between the two, this study introduces the variable of emotional solidarity; constructs a relationship model of authenticity perception, emotional solidarity, and tourists’ support behavior intentions by adopting the theory of reasoned action; and verifies the established hypotheses through empirical analysis. The results show that both existential authenticity and objective authenticity positively influence tourism support behavior intentions, and the effect of objective authenticity on tourism support behavior intentions is greater than that of the presence of authenticity. Empathic understanding, feeling welcome, and emotional intimacy all play mediating roles between intrapersonal authenticity perception and tourism support behavior intentions. Findings also show empathic understanding and feeling welcome play mediating roles in objective authenticity perception and between the perception of objective authenticity and tourism support behavior intentions. Suggestions are also proposed for the development of homestay inn enterprises.

[Otologic disorders and management strategies in Turner syndrome]

Objective: To analyze the incidence and risk factors of otologic disorders in patients with Turner syndrome (TS), so as to provide management strategies for ear health. Methods: This study is a prospective study based on questionnaires and a cross-sectional study. The TS patients who visited our hospital from 2010 January to 2021 March were included (A total of 71 patients with TS were included in this study. the age of TS diagnosed was 3- to 11-year-old, age of visiting ENT department was 4- to 27-year-old) and the incidence of otologic diseases in different age groups was investigated by questionnaires. The cross-sectional study included ear morphology and auditory function assessment, and further analysis of the risk factors that related to ear disease. Prism was used for data analysis. Results: The investigation found that the incidence of acute otitis media in patients aged 3-6 and 7-12 years was higher than that of patients over 12 years old, which was 33.8%(24/71), 42.9%(30/70)and 23.5%(8/34), respectively; 21.1% (15/71) of patients were recurrent acute otitis media in patients aged 3-6 years, and about 46.6% (7/15)of them persisted beyond 6-year. The prevalence of otitis media with effusion in the three groups was 32.4%(23/71), 34.3%(24/70)and 38.2%(13/34), respectively; the recurrence rate of tympanocentesis was 100%(7/7), 42.9%(3/7)and 50.0%(1/2), which was significantly higher than that of grommet insertion. For age groups of 3-6 and 7-12 years, the prevalence of acute otitis media and secretory otitis media was lower in the X chromosome structure abnormal patients; while for patients older than 12 years, otitis media with effusion was the highest prevalence in Y-chromosome-containing karyotypes. In addition, the prevalence of acute otitis media and otitis media with effusion in patients with other system diseases were increased significantly. A cross-sectional study found that 7.0% (5/71)of the lower auricular, 4.2% (3/71)of the external auditory canal narrow, and 38.0% (27/71)of the tympanic membrane abnormality. 35.2%(25/71) had abnormal hearing, including 17 cases of conductive deafness, 6 cases of sensorineural hearing loss, and 2 cases of mixed deafness. The rest of the patients had normal hearing, but 6 of them had abnormalities in otoacoustic emission. Eustachian tube function assessment found that the eustachian tube dysfunction accounted for 38%(27/71). Hearing loss and abnormal Eustachian tube function were not significantly related to karyotype(Chi-square 2.83 and 2.84,P value 0.418 and 0.417), but significantly related to other system diseases(Chi-square 13.43 and 7.53,P value<0.001). Conclusions: The incidence of TS-related otitis media and auditory dysfunction is significantly higher than that of the general population. It not only occurs in preschool girls, but also persists or develops after school age. Accompanied by other system diseases are risk factors for ear diseases. Clinicians should raise their awareness of TS-related ear diseases and incorporate ear health monitoring into routine diagnosis and treatment.

Iodine Maps from Dual-Energy CT to Predict Extrathyroidal Extension and Recurrence in Papillary Thyroid Cancer Based on a Radiomics Approach

BACKGROUND AND PURPOSE

Accurate prediction of extrathyroidal extension and subsequent recurrence is crucial in papillary thyroid cancer clinical management. Our aim was to conduct iodine map-based radiomics to predict extrathyroidal extension and to explore its prognostic value for recurrence-free survival in papillary thyroid cancer.

MATERIALS AND METHODS

A total of 452 patients with papillary thyroid cancer were retrospectively recruited between June 2017 and June 2020. Radiomics features were extracted from noncontrast images, dual-phase mixed images, and iodine maps, respectively. Random forest and least absolute shrinkage and selection operator (LASSO) were applied to build 6 radiomics scores (noncontrast radiomics score_random forest; noncontrast rad-score_LASSO; mixed rad-score_random forest; mixed rad-score_LASSO; iodine radiomics score_random forest; iodine radiomics score_LASSO) respectively. Logistic regression was used to construct 6 radiomics models incorporating 6 radiomics scores with clinical risk factors and to compare them with the clinical model. A radiomics model that achieved the highest performance was presented as a nomogram and assessed by discrimination, calibration, clinical usefulness, and prognosis evaluation.

RESULTS

Iodine radiomics scores performed significantly better than mixed radiomics scores. Both of them outperformed noncontrast radiomics scores. Iodine map-based radiomics models significantly surpassed the clinical model. A radiomics nomogram incorporating size, capsule contact, and iodine radiomics score_random forest was built with the highest performance (training set, area under the curve = 0.78; validation set, area under the curve  = 0.84). Stratified analysis confirmed the nomogram stability, especially in group negative for CT-reported extrathyroidal extension (area under the curve  = 0.69). Nomogram-predicted extrathyroidal extension risk was an independent predictor of recurrence-free survival. A high risk for extrathyroidal extension portended significantly lower recurrence-free survival than low risk (P < .001).

CONCLUSIONS

Iodine map-based radiomics might be a supporting tool for predicting extrathyroidal extension and subsequent recurrence risk in patients with papillary thyroid cancer, thus facilitating clinical decision-making.

Anti-saccade as a Tool to Evaluate Neurocognitive Impairment in Alcohol Use Disorder

It has been widely shown that chronic alcohol use leads to cognitive dysfunctions, especially inhibitory control. In an extension of the traditional approach, this research field has benefited from the emergence of innovative measures, among which is an anti-saccade, allowing direct and sensitive measure of the eye movements indexing attention bias to alcohol-related cues and the capability of inhibiting the reflexive saccades to the cues. During the past decade, there are numerous reports showing that drinkers make more unwanted reflexive saccades and longer latency in the anti-saccade task. These increased errors are usually explained by the deficits in inhibitory control. It has been demonstrated that inhibitory control on eye movement may be one of the earliest biomarkers of the onset of alcohol-related cognitive impairments. This review summarizes how an anti-saccade task can be used as a tool to investigate and assess the cognitive dysfunctions and the early detection of relapsing risk of alcohol dependence.

A Sensitive Liquid Chromatography-Mass Spectrometry Method for Determination of Toosendanin in Rat Plasma and its Application to Pharmacokinetic Study

A simple, rapid and sensitive analytical method was developed for the determination of toosendanin in rat plasma using liquid chromatography tandem mass spectrometry (LC-MS/MS). Andrographolide was selected as the internal standard, and the plasma samples were extracted by liquid-liquid extraction with diethyl ether. Chromatographic separation was performed on a Dikma Spursil C18, 3.5 μm (150 × 2.1 mm i.d) analytical column with 85% methanol:water (v/v) containing 0.025% formic acid (pH = 3.9) as mobile phase. The flow rate was 0.25 mL/min, and the total run time was 3 min. Detection was performed with a triple-quadrupole tandem mass spectrometer using negative ion mode electrospray ionization (ESI) in the multiple reaction monitoring (MRM) mode. The MS/MS ion transitions monitored were m/z 573.1 → 531.1 and 349.0 → 287.0 for toosendanin and andrographolide, respectively. Good linearity was observed over the concentration range of 3.125-500 ng/mL in 100 μL of rat plasma with a correlation coefficient ˃0.9997. Intra- and inter-assay variabilities were ˂8.5% in plasma. The recovery and the matrix effect were in the range 71.8-73.5% and 96.4-103.8%, respectively. The analyte was stable under various conditions (at room temperature, during freeze-thaw settings, in the autosampler, and under deep-freeze conditions). The method was successfully applied to a pharmacokinetic study of toosendanin after its oral administration in rats at a dose of 10 mg/kg.

Emodin palliates high-fat diet-induced nonalcoholic fatty liver disease in mice via activating the farnesoid X receptor pathway

BACKGROUND

Cassia mimosoides Linn (CMD) is a traditional Chinese herb that clears liver heat and dampness. It has been widely administered in clinical practice to treat jaundice associated with damp-heat pathogen and obesity. Emodin (EMO) is a major bioactive constituent of CMD that has apparent therapeutic efficacy against obesity and fatty liver. Here, we investigated the protective effects and underlying mechanisms of EMO against high-fat diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD).

OBJECTIVE

We aimed to investigate whether EMO activates farnesoid X receptor (FXR) signaling to alleviate HFD-induced NAFLD.

MATERIALS AND METHODS

In vivo assays included serum biochemical indices tests, histopathology, western blotting, and qRT-PCR to evaluate the effects of EMO on glucose and lipid metabolism disorders in wild type (WT) and FXR knockout mice maintained on an HFD. In vitro experiments included intracellular triglyceride (TG) level measurement and Oil Red O staining to assess the capacity of EMO to remove lipids induced by oleic acid and palmitic acid in WT and FXR knockout mouse primary hepatocytes (MPHs). We also detected mRNA expression of FXR signaling genes in MPHs.

RESULTS

After HFD administration, body weight and serum lipid and inflammation levels were dramatically increased in the WT mice. The animals also presented with impaired glucose tolerance, insulin resistance, and antioxidant capacity, liver tissue attenuation, and pathological injury. EMO remarkably reversed the foregoing changes in HFD-induced mice. EMO improved HFD-induced lipid accumulation, insulin resistance, inflammation, and oxidative stress in a dose-dependent manner in WT mice by inhibiting FXR expression. EMO also significantly repressed TG hyperaccumulation by upregulating FXR expression in MPHs. However, it did not improve lipid accumulation, insulin sensitivity, or glucose tolerance in HFD-fed FXR knockout mice.

CONCLUSIONS

The present study demonstrated that EMO alleviates HFD-induced NAFLD by activating FXR signaling which improves lipid accumulation, insulin resistance, inflammation, and oxidative stress.

Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning

OBJECTIVE

Automated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression of rare but severe vaccine adverse events (AEs). This study implemented and evaluated state-of-the-art deep learning algorithms for named entity recognition to extract nervous system disorder-related events from vaccine safety reports.

MATERIALS AND METHODS

We collected Guillain-Barré syndrome (GBS) related influenza vaccine safety reports from the Vaccine Adverse Event Reporting System (VAERS) from 1990 to 2016. VAERS reports were selected and manually annotated with major entities related to nervous system disorders, including, investigation, nervous_AE, other_AE, procedure, social_circumstance, and temporal_expression. A variety of conventional machine learning and deep learning algorithms were then evaluated for the extraction of the above entities. We further pretrained domain-specific BERT (Bidirectional Encoder Representations from Transformers) using VAERS reports (VAERS BERT) and compared its performance with existing models.

RESULTS AND CONCLUSIONS

Ninety-one VAERS reports were annotated, resulting in 2512 entities. The corpus was made publicly available to promote community efforts on vaccine AEs identification. Deep learning-based methods (eg, bi-long short-term memory and BERT models) outperformed conventional machine learning-based methods (ie, conditional random fields with extensive features). The BioBERT large model achieved the highest exact match F-1 scores on nervous_AE, procedure, social_circumstance, and temporal_expression; while VAERS BERT large models achieved the highest exact match F-1 scores on investigation and other_AE. An ensemble of these 2 models achieved the highest exact match microaveraged F-1 score at 0.6802 and the second highest lenient match microaveraged F-1 score at 0.8078 among peer models.

Prediction of Health Risk Preventative Behavior of Amateur Marathon Runners: A Cross-Sectional Study

Introduction

Prevention of the health risk of amateur marathon runners is of great significance for the sustainable development of marathon. To reduce the psychological burden of amateur marathon runners and improve the participation experience, the current study used the health belief model to study the relationship among health beliefs, attitude to preventative behavior, self-efficacy, and health values of amateur marathon runners.

Methods

A total of 342 data were collected, and using the PROCESS (analytical procedures developed for mediating and moderating effects tests based on SPSS and SAS). A series of multiple linear regression models were established to study the relationship between variables, and the bootstrap confidence interval was selected to test the mediating and moderating effect.

Results

The results showed that perceived health threat (b = 0.463, p <0.05), health behavior expectations (b = 0.373, p <0.001), self-efficacy (b = 0.322, p <0.001), and behavioral attitudes (b = 0.230, p <0.001) can be regarded as antecedent variables for predicting preventative behaviors. In addition, the results also show that health behavior expectations, self-efficacy, and behavioral attitudes play chain-mediating role between perceived health threat and preventative behaviors. Health values appear to play a moderating role in the direct/indirect effects of perceived health threat on preventive behavior through a number of mediating variables.

Discussion

This study emphasizes that the amateur marathon runners must improve their health concept and take effective preventive measures before participating in the competition. According to this research, it is the responsibility of the event parties, public health officials and relevant departments of the host city to provide rich health information and risk education to amateur marathon runners. More public service advertisements or educational materials are needed to be placed on runners to enhance their awareness of the necessity and importance of taking preventive measures.

Extracting Concepts for Precision Oncology from the Biomedical Literature

This paper describes an initial dataset and automatic natural language processing (NLP) method for extracting concepts related to precision oncology from biomedical research articles. We extract five concept types: Cancer, Mutation, Population, Treatment, Outcome. A corpus of 250 biomedical abstracts were annotated with these concepts following standard double-annotation procedures. We then experiment with BERT-based models for concept extraction. The best-performing model achieved a precision of 63.8%, a recall of 71.9%, and an F1 of 67.1. Finally, we propose additional directions for research for improving extraction performance and utilizing the NLP system in downstream precision oncology applications.

Generalized and transferable patient language representation for phenotyping with limited data

The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing. In this work, we propose a multi-task pre-training and fine-tuning approach for learning generalized and transferable patient representations from medical language. The model is first pre-trained with different but related high-prevalence phenotypes and further fine-tuned on downstream target tasks. Our main contribution focuses on the impact this technique can have on low-prevalence phenotypes, a challenging task due to the dearth of data. We validate the representation from pre-training, and fine-tune the multi-task pre-trained models on low-prevalence phenotypes including 38 circulatory diseases, 23 respiratory diseases, and 17 genitourinary diseases. We find multi-task pre-training increases learning efficiency and achieves consistently high performance across the majority of phenotypes. Most important, the multi-task pre-training is almost always either the best-performing model or performs tolerably close to the best-performing model, a property we refer to as robust. All these results lead us to conclude that this multi-task transfer learning architecture is a robust approach for developing generalized and transferable patient language representations for numerous phenotypes.

Enhancing clinical concept extraction with contextual embeddings

OBJECTIVE

Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Recently, however, more advanced embedding methods and representations (eg, ELMo, BERT) have further pushed the state of the art in NLP, yet there are no common best practices for how to integrate these representations into clinical tasks. The purpose of this study, then, is to explore the space of possible options in utilizing these new models for clinical concept extraction, including comparing these to traditional word embedding methods (word2vec, GloVe, fastText).

MATERIALS AND METHODS

Both off-the-shelf, open-domain embeddings and pretrained clinical embeddings from MIMIC-III (Medical Information Mart for Intensive Care III) are evaluated. We explore a battery of embedding methods consisting of traditional word embeddings and contextual embeddings and compare these on 4 concept extraction corpora: i2b2 2010, i2b2 2012, SemEval 2014, and SemEval 2015. We also analyze the impact of the pretraining time of a large language model like ELMo or BERT on the extraction performance. Last, we present an intuitive way to understand the semantic information encoded by contextual embeddings.

RESULTS

Contextual embeddings pretrained on a large clinical corpus achieves new state-of-the-art performances across all concept extraction tasks. The best-performing model outperforms all state-of-the-art methods with respective F1-measures of 90.25, 93.18 (partial), 80.74, and 81.65.

CONCLUSIONS

We demonstrate the potential of contextual embeddings through the state-of-the-art performance these methods achieve on clinical concept extraction. Additionally, we demonstrate that contextual embeddings encode valuable semantic information not accounted for in traditional word representations.

Deep learning in clinical natural language processing: a methodical review

OBJECTIVE

This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the clinical domain, providing quantitative analysis to answer 3 research questions concerning methods, scope, and context of current research.

MATERIALS AND METHODS

We searched MEDLINE, EMBASE, Scopus, the Association for Computing Machinery Digital Library, and the Association for Computational Linguistics Anthology for articles using DL-based approaches to NLP problems in electronic health records. After screening 1,737 articles, we collected data on 25 variables across 212 papers.

RESULTS

DL in clinical NLP publications more than doubled each year, through 2018. Recurrent neural networks (60.8%) and word2vec embeddings (74.1%) were the most popular methods; the information extraction tasks of text classification, named entity recognition, and relation extraction were dominant (89.2%). However, there was a "long tail" of other methods and specific tasks. Most contributions were methodological variants or applications, but 20.8% were new methods of some kind. The earliest adopters were in the NLP community, but the medical informatics community was the most prolific.

DISCUSSION

Our analysis shows growing acceptance of deep learning as a baseline for NLP research, and of DL-based NLP in the medical community. A number of common associations were substantiated (eg, the preference of recurrent neural networks for sequence-labeling named entity recognition), while others were surprisingly nuanced (eg, the scarcity of French language clinical NLP with deep learning).

CONCLUSION

Deep learning has not yet fully penetrated clinical NLP and is growing rapidly. This review highlighted both the popular and unique trends in this active field.

Ethnic Disparities in Dental Caries among Adolescents in China

Comprehensive research on ethnic disparities in dental caries in China is limited. The aims of this cross-sectional study were to compare the levels of dental caries in adolescents between the Han ethnic group and ethnic minority groups in China and to explore the risk indicators for dental caries within ethnic subgroups. Data from the Fourth National Oral Health Survey in 2015, which covered all 31 province-level administrative divisions in mainland China, were used. The dental caries status in the permanent dentition of adolescents aged 12, 13, 14, and 15 y was measured using the decayed, missing, and filled teeth (DFMT) score, and sociodemographic characteristics and oral health-related behaviors were also collected. A total of 118,601 adolescents were included, with ethnic minority groups accounting for 13.15%. Of the Han and minority groups, the standardized prevalence of dental caries experience was 40.58% and 47.67%, and the mean DMFT scores were 0.97 and 1.28, respectively. According to the multivariate zero-inflated negative binomial regression analysis, the caries status of minorities was more severe than Han adolescents (adjusted prevalence rate ratio [PRR], 1.14; 95% confidence interval [CI], 1.10-1.18). This disparity was greater among adolescents who lived in rural areas, had mid-level economic status, and frequently consumed sugary beverages. After propensity score matchings, Uygur (PRR, 1.44; 95% CI, 1.25-1.67), Tibetan (PRR, 1.39; 95% CI, 1.3-1.48), and Yi (PRR, 1.24; 95% CI, 1.04-1.48) adolescents were significantly more likely to have caries than Han adolescents. Subgroup analyses revealed that gender, age, location of residence, economic status, region, consumption of sweet snacks and sugary beverages, and dental visit pattern were significantly associated with dental caries within ethnic minorities.

Understanding spatial language in radiology: Representation framework, annotation, and spatial relation extraction from chest X-ray reports using deep learning

Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Such spatial relationships are also linked to various differential diagnoses and often described through uncertainty phrases. Structured representation of this clinically significant spatial information has the potential to be used in a variety of downstream clinical informatics applications. Our focus is to extract these spatial representations from the reports. For this, we first define a representation framework based on the Spatial Role Labeling (SpRL) scheme, which we refer to as Rad-SpRL. In Rad-SpRL, common radiological entities tied to spatial relations are encoded through four spatial roles: Trajector, Landmark, Diagnosis, and Hedge, all identified in relation to a spatial preposition (or Spatial Indicator). We annotated a total of 2,000 chest X-ray reports following Rad-SpRL. We then propose a deep learning-based natural language processing (NLP) method involving word and character-level encodings to first extract the Spatial Indicators followed by identifying the corresponding spatial roles. Specifically, we use a bidirectional long short-term memory (Bi-LSTM) conditional random field (CRF) neural network as the baseline model. Additionally, we incorporate contextualized word representations from pre-trained language models (BERT and XLNet) for extracting the spatial information. We evaluate both gold and predicted Spatial Indicators to extract the four types of spatial roles. The results are promising, with the highest average F1 measure for Spatial Indicator extraction being 91.29 (XLNet); the highest average overall F1 measure considering all the four spatial roles being 92.9 using gold Indicators (XLNet); and 85.6 using predicted Indicators (BERT pre-trained on MIMIC notes). The corpus is available in Mendeley at http://dx.doi.org/10.17632/yhb26hfz8n.1 and https://github.com/krobertslab/datasets/blob/master/Rad-SpRL.xml.

Patient Representation Transfer Learning from Clinical Notes based on Hierarchical Attention Network

To explicitly learn patient representations from longitudinal clinical notes, we propose a hierarchical attention-based recurrent neural network (RNN) with greedy segmentation to distinguish between shorter and longer, more meaningful gaps between notes. The proposed model is evaluated for both a direct clinical prediction task (mortality) and as a transfer learning pre-training model to downstream evaluation (phenotype prediction of obesity and its comorbidities). Experimental results first show the proposed model with appropriate segmentation achieved the best performance on mortality prediction, indicating the effectiveness of hierarchical RNNs in dealing with longitudinal clinical text. Attention weights from the models highlight those parts of notes with the largest impact on mortality prediction and hopefully provide a degree of interpretability. Following the transfer learning approach, we also demonstrate the effectiveness and generalizability of pre-trained patient representations on target tasks of phenotyping.

Relation Extraction from Clinical Narratives Using Pre-trained Language Models

Natural language processing (NLP) is useful for extracting information from clinical narratives, and both traditional machine learning methods and more-recent deep learning methods have been successful in various clinical NLP tasks. These methods often depend on traditional word embeddings that are outputs of language models (LMs). Recently, methods that are directly based on pre-trained language models themselves, followed by fine-tuning on the LMs (e.g. the Bidirectional Encoder Representations from Transformers (BERT)), have achieved state-of-the-art performance on many NLP tasks. Despite their success in the open domain and biomedical literature, these pre-trained LMs have not yet been applied to the clinical relation extraction (RE) task. In this study, we developed two different implementations of the BERT model for clinical RE tasks. Our results show that our tuned LMs outperformed previous state-of-the-art RE systems in two shared tasks, which demonstrates the potential of LM-based methods on the RE task.

[Countermeasures and treatment for aortic acute syndrome with novel coronavirus pneumonia]

The novel coronavirus pneumonia (NCP) has cost a great loss to the health and economic property of Chines people. Under such a special circumstance, how to deal with such patients with acute aortic syndrome has become a serious challenge. Rapid diagnosis of concomitant NCP, safe and effective transportation, implementation of the interventional procedure, protection of vascular surgical team and postoperative management and follow-up of such patients have become urgent problems for us. Combined with the latest novel government documents, the literature and the experiences from Wuhan, we answered the above questions briefly and plainly. It also hopes to inspire the national vascular surgeons to manage critical emergencies in vascular surgery and even routine vascular diseases with NCP, as a final point to limit the severe epidemic situation, and minimize the damage of NCP.

[Biomechanical changes of sheep cervical spine after unilateral hemilaminectomy and different degrees of facetectomy]

OBJECTIVE

To establish animal models and investigate the impact of unilateral hemilaminectomy (ULHL) and different degrees of facetectomy (FT) on the cervical spinal biomechanics.

METHODS

Twenty sheep were randomly and evenly divided into 4 groups. No operation was performed for group A, right C4-C6 ULHL was performed for group B, right C4-C6 ULHL and 50% ipsilateral C4-C5 FT was performed for group C, right C4-C6 ULHL and 100% ipsilateral C4-C5 FT was performed for group D. Animals of group A, B, C and D were sacrificed 24 weeks after operating and fresh cervical spine specimens were acquired, biomechanically tested and these data were compared to determine whether ULHL and different degrees of FT led to long-term differences in range of motion.

RESULTS

(1) Changes of the total range of motion of cervical spine 24 weeks after surgery: the total range of motion of group D (60.2°±8.6°) was significantly greater than group A (40.7°±6.4°) and group B (41.2°±13.1°) under flexion-extension station, the total range of motion of group D (81.5°±15.7°) was significantly greater than that of group A (56.7°±12.2°) and group B (57.7°±12.8°) under lateral bending station, and the total range of motion of group D (38.5°±17.5°) had no obvious increase compared with group A (26.4°±9.9°) and group B (27.1°±10.9°) under axial rotation station. The total range of motion of group C had no obvious increase compared with group A and group B under flexion-extension station (44.1°±11.7°), lateral bending station (73.6°±11.4°) and axial rotation station (31.3°±11.5°). (2) Changes of the intersegmental motion 24 weeks after surgery: the intersegmental motion of group D (20.3°±4.6°) at C4-C5 was significantly greater than that of group A (11.7°±3.4°) and group B (11.9°±2.1°) under flexion-extension station, the intersegmental motion of group D (26.8°±3.5°) at C4-C5 was significantly greater than that of group A (15.2°±3.1°) and group B (16.2°±3.2°) under lateral bending station, the intersegmental motion of group D (15.2°±3.5°) at C4-C5 was significantly greater than that of group A (6.6°±2.3°) and group B (7.1°±1.9°) under axial rotation station. The intersegmental motion of group C (21.2°±4.1°) at C4-C5 was significantly greater than that of group A and group B under lateral bending station, the intersegmental motion of group C at C4-C5 had no obvious increase compared with group A and group B under flexion-extension station (15.7°±3.7°) and axial rotation station (10.3°±3.1°).

CONCLUSION

ULHL does not affect cervical stability, ULHL and 50% ipsilateral FT does not affect the long-term cervical stability, ULHL and 100% ipsilateral FT can lead to long-term instability under lateral bending and flexion-extension station.

Deep Patient Representation of Clinical Notes via Multi-Task Learning for Mortality Prediction

We propose a deep learning-based multi-task learning (MTL) architecture focusing on patient mortality predictions from clinical notes. The MTL framework enables the model to learn a patient representation that generalizes to a variety of clinical prediction tasks. Moreover, we demonstrate how MTL enables small but consistent gains on a single classification task (e.g., in-hospital mortality prediction) simply by incorporating related tasks (e.g., 30-day and 1-year mortality prediction) into the MTL framework. To accomplish this, we utilize a multi-level Convolutional Neural Network (CNN) associated with a MTL loss component. The model is evaluated with 3, 5, and 20 tasks and is consistently able to produce a higher-performing model than a single-task learning (STL) classifier. We further discuss the effect of the multi-task model on other clinical outcomes of interest, including being able to produce high-quality representations that can be utilized to great effect by simpler models. Overall, this study demonstrates the efficiency and generalizability of MTL across tasks that STL fails to leverage.

Clinical, neuroimaging and prognostic study of 127 cases with infarction of the corpus callosum

Background and purpose

The aim of this study was to retrospectively investigate clinical and neuroimaging characteristics in the largest sample size of patients with corpus callosum infarction to date and then to follow up these patients for 1 year to clarify the prognosis of this rare stroke entity.

Methods

A total of 127 patients with acute callosal infarction out of 5584 acute ischaemic stroke patients were included in this study. The recruited patients were divided into a pure callosal infarction group and a complex callosal infarction group (coupled with other infarct locations simultaneously), and clinical and neuroimaging features were analyzed. Some of the patients were followed up for 1 year to evaluate recurrence rate and mortality.

Results

The incidence of acute callosal infarction was 2.3%. Most patients presented with advanced neurological dysfunction with or without mild to moderate motor or sensory disorders on admission. The negative rate of computed tomography scan was still 76.4% even at >24 h after onset. Large‐artery atherosclerosis was the most common etiological type. Compared with complex callosal infarction, the pure callosal infarction group had more mental disorders (P = 0.030). Compared with common basal ganglia infarction, the pure callosal infarction group had better short‐term recovery (P = 0.016) but higher 1‐year mortality (P = 0.037). Age and mental disorders were independent risk factors for death in callosal infarction.

Conclusions

Callosal infarction is a white matter stroke that occurs with low incidence. Elderly patients with vascular risk factors showed sudden mental or cognitive disorders and callosal infarction could not be excluded. More attention should be paid to the early diagnosis and secondary prevention of callosal infarction because of its poor long‐term outcome.

Time-sensitive clinical concept embeddings learned from large electronic health records

BACKGROUND

Learning distributional representation of clinical concepts (e.g., diseases, drugs, and labs) is an important research area of deep learning in the medical domain. However, many existing relevant methods do not consider temporal dependencies along the longitudinal sequence of a patient's records, which may lead to incorrect selection of contexts.

METHODS

To address this issue, we extended three popular concept embedding learning methods: word2vec, positive pointwise mutual information (PPMI) and FastText, to consider time-sensitive information. We then trained them on a large electronic health records (EHR) database containing about 50 million patients to generate concept embeddings and evaluated them for both intrinsic evaluations focusing on concept similarity measure and an extrinsic evaluation to assess the use of generated concept embeddings in the task of predicting disease onset.

RESULTS

Our experiments show that embeddings learned from information within one visit (time window zero) improve performance on the concept similarity measure and the FastText algorithm usually had better performance than the other two algorithms. For the predictive modeling task, the optimal result was achieved by word2vec embeddings with a 30-day sliding window.

CONCLUSIONS

Considering time constraints are important in training clinical concept embeddings. We expect they can benefit a series of downstream applications.

A Frame-Based NLP System for Cancer-Related Information Extraction

We propose a frame-based natural language processing (NLP) method that extracts cancer-related information from clinical narratives. We focus on three frames: cancer diagnosis, cancer therapeutic procedure, and tumor description. We utilize a deep learning-based approach, bidirectional Long Short-term Memory (LSTM) Conditional Random Field (CRF), which uses both character and word embeddings. The system consists of two constituent sequence classifiers: a frame identification (lexical unit) classifier and a frame element classifier. The classifier achieves an F₁ of 93.70 for cancer diagnosis, 96.33 for therapeutic procedure, and 87.18 for tumor description. These represent improvements of 10.72, 0.85, and 8.04 over a baseline heuristic, respectively. Additionally, we demonstrate that the combination of both GloVe and MIMIC-III embeddings has the best representational effect. Overall, this study demonstrates the effectiveness of deep learning methods to extract frame semantic information from clinical narratives.

Dexmedetomidine attenuation of renal ischaemia-reperfusion injury requires sirtuin 3 activation

BACKGROUND

Dexmedetomidine attenuates renal ischaemia and reperfusion (I/R) injury, but its mechanism of action is unclear. As sirtuin 3 (SIRT3) activation can alleviate acute kidney injury, we investigated whether dexmedetomidine acts through SIRT3 to reduce renal I/R injury.

METHODS

The potential involvement of SIRT3 in dexmedetomidine attenuation of renal I/R injury was tested in HK2 cells subjected to hypoxia/reoxygenation and C57BL/6J mice subjected to renal I/R. A short interfering RNA targeting SIRT3 was used in some experiments to examine the potential role of SIRT3. Cell death and mitochondrial membrane potential (Δψm) were analysed in cultured cells. Mitochondrial damage in mice was assessed using electron microscopy and markers for renal function. Expression of cyclophilin D, cytochrome c, and SIRT3, and the level of cyclophilin D acetylation were determined.

RESULTS

Hypoxia/reoxygenation of HK2 cells increased cell death, cytochrome C expression, and cyclophilin D acetylation, and decreased Δψm and SIRT3 expression (P<0.05). Dexmedetomidine attenuated these changes. The dexmedetomidine effects were enhanced by SIRT3 overexpression and eliminated by SIRT3 knockdown. I/R in mice damaged renal function, and increased histological lesions, mitochondrial damage, cytochrome c expression, and cyclophilin D acetylation, while SIRT3 activity was decreased by 51% (P<0.05). Dexmedetomidine inhibited these changes in mice expressing normal levels of SIRT3, but not in SIRT3-knockdown mice.

CONCLUSIONS

Dexmedetomidine appears to act, at least in part, by up-regulating SIRT3 to inhibit mitochondrial damage and cell apoptosis and thereby protect against renal I/R injury.

Downregulation of HCN1 channels in hippocampus and prefrontal cortex in methamphetamine re-exposed mice with enhanced working memory

The hyperpolarization-activated cyclic-nucleotide-gated non-selective cation (HCN) channels play a potential role in the neurological basis underlying drug addiction. However, little is known about the role of HCN channels in methamphetamine (METH) abuse. In the present study, we examined the changes in working memory functions of METH re-exposed mice through Morris water maze test, and investigated the protein expression of HCN1 channels and potential mechanisms underlying the modulation of HCN channels by Western blotting analysis. Mice were injected with METH (1 mg/kg, i.p.) once per day for 6 consecutive days. After 5 days without METH, mice were re-exposed to METH at the same concentration. We found that METH re-exposure caused an enhancement of working memory, and a decrease in the HCN1 channels protein expression in both hippocampus and prefrontal cortex. The phosphorylated extracellular regulated protein kinase 1/2 (p-ERK1/2), an important regulator of HCN channels, was also obviously reduced in hippocampus and prefrontal cortex of mice with METH re-exposure. Meanwhile, acute METH exposure did not affect the working memory function and the protein expressions of HCN1 channels and p-ERK1/2. Overall, our data firstly showed the aberrant protein expression of HCN1 channels in METH re-exposed mice with enhanced working memory, which was probably related to the down-regulation of p-ERK1/2 protein expression.

The Data Gap in the EHR for Clinical Research Eligibility Screening

Much effort has been devoted to leverage EHR data for matching patients into clinical trials. However, EHRs may not contain all important data elements for clinical research eligibility screening. To better design research-friendly EHRs, an important step is to identify data elements frequently used for eligibility screening but not yet available in EHRs. This study fills this knowledge gap. Using the Alzheimer's disease domain as an example, we performed text mining on the eligibility criteria text in Clinicaltrials.gov to identify frequently used eligibility criteria concepts. We compared them to the EHR data elements of a cohort of Alzheimer's Disease patients to assess the data gap by usingthe OMOP Common Data Model to standardize the representations for both criteria concepts and EHR data elements. We identified the most common SNOMED CT concepts used in Alzheimer 's Disease trials, andfound 40% of common eligibility criteria concepts were not even defined in the concept space in the EHR dataset for a cohort of Alzheimer 'sDisease patients, indicating a significant data gap may impede EHR-based eligibility screening. The results of this study can be useful for designing targeted research data collection forms to help fill the data gap in the EHR.

[Utilization of dental services for children: a review of the influencing factors and the possible improvements]

It has been reported that children's oral health conditions are correlated with their attendance to dental health services. Evaluating the influencing factors of utilization of dental services for children may give ways to improve the services per se, and furtherly the children's oral health. The present review retrieved and summarized domestic and foreign studies on the utilization of oral health services for children based on the Andersen behavior model. It was concluded that the utilization of dental services for children was affected by demographic characteristics, social structure, health belief, family factors, community factors and perceived/evaluated needs. To improve the utilization of dental services for children, effort should be made by means of changing caregivers' health belief, developing oral health insurance system, setting up regular oral health resources and increasing the financial support for oral health services by government.

An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria

Eligibility criteria are important for clinical research protocols or clinical practice guidelines for determining who qualify for studies and to whom clinical evidence is applicable, but the free-text format is not amenable for computational processing. In this paper, we described a practical method for transforming free-text clinical research eligibility criteria of Alzheimer's clinical trials into a structured relational database compliant with standards for medical terminologies and clinical data models. We utilized a hybrid natural language processing system and a concept normalization tool to extract medical terms in clinical research eligibility criteria and represent them using the OMOP Common Data Model (CDM) v5. We created a database schema design to store syntactic relations to facilitate efficient cohort queries. We further discussed the potential of applying this method to trials on other diseases and the promise of using it to accelerate clinical research with electronic health records.

Extracellular DNA traps released by acute promyelocytic leukemia cells through autophagy

Acute promyelocytic leukemia (APL) cells exhibit disrupted regulation of cell death and differentiation, and therefore the fate of these leukemic cells is unclear. Here, we provide the first evidence that a small percentage of APL cells undergo a novel cell death pathway by releasing extracellular DNA traps (ETs) in untreated patients. Both APL and NB4 cells stimulated with APL serum had nuclear budding of vesicles filled with chromatin that leaked to the extracellular space when nuclear and cell membranes ruptured. Using immunofluorescence, we found that NB4 cells undergoing ETosis extruded lattice-like structures with a DNA-histone backbone. During all-trans retinoic acid (ATRA)-induced cell differentiation, a subset of NB4 cells underwent ETosis at days 1 and 3 of treatment. The levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were significantly elevated at 3 days, and combined treatment with TNF-α and IL-6 stimulated NB4 cells to release ETs. Furthermore, inhibition of autophagy by pharmacological inhibitors or by small interfering RNA against Atg7 attenuated LC3 autophagy formation and significantly decreased ET generation. Our results identify a previously unrecognized mechanism for death in promyelocytes and suggest that ATRA may accelerate ET release through increased cytokines and autophagosome formation. Targeting this cellular death pathway in addition to conventional chemotherapy may provide new therapeutic modalities for APL.

[Scalp surface skin grafts in reconstruction of external auditory meatus in congenital aural atresia]

OBJECTIVE

To investigate the clinical application of scalp skin grafts in reconstruction of external auditory meatus in congenital aural atresia.

METHODS

We conducted a retrospective study on 85 patients of congenital aural atresia, all of whom were unilateral, operated from March of 2008 to December of 2010 in ENT department of the Sun Yat-Sen Memorial Hospital. The patients enrolled in the study were between 6 to 37 years old (median age 12 years), 55 male and 30 female. Scalp surface graft in ipsilateral temporal region was harvested to cover the bony external auditory meatus.

RESULTS

All of these scalp split-thickness skin grafts survived without necrosis, no restenosis was found in these external auditory meatus. Neither scar nor alopecia was found in the skin-harvesting region, and hairs grew well. Granulations occurred in 27 cases in the first to sixth month posteroperatively, 20 cases recovered after local treatment. In the first year, 30 cases obtained hearing improvement more than 15 dB, 36 cases gained more than 25 dB and 19 cases gained more than 35 dB. Totally 8 patients were lost in the 4 to 5 years of follow-up, 70 cases (70/77, 90.9%) developed new external auditory meatus, 7 cases (7/77, 9.1%) suffered from stenosis in different degrees, but no atresia was found in these patients.

CONCLUSION

Scalp split-thickness skin grafts has significant clinical advantage in meatoplasty of congenital aural atresia.

TGF-β/Smad3 inhibit vascular smooth muscle cell apoptosis through an autocrine signaling mechanism involving VEGF-A

We have previously shown that in the presence of elevated Smad3, transforming growth factor-β (TGF-β) transforms from an inhibitor to a stimulant of vascular smooth muscle cell (SMC) proliferation and intimal hyperplasia (IH). Here we identify a novel mechanism through which TGF-β/Smad3 also exacerbates IH by inhibiting SMC apoptosis. We found that TGF-β treatment led to inhibition of apoptosis in rat SMCs following viral expression of Smad3. Conditioned media from these cells when applied to naive SMCs recapitulated this effect, suggesting an autocrine pathway through a secreted factor. Gene array of TGF-β/Smad3-treated cells revealed enhanced expression of vascular endothelial growth factor (VEGF), a known inhibitor of endothelial cell apoptosis. We then evaluated whether VEGF is the secreted mediator responsible for TGF-β/Smad3 inhibition of SMC apoptosis. In TGF-β/Smad3-treated cells, VEGF mRNA and protein as well as VEGF secretion were increased. Moreover, recombinant VEGF-A inhibited SMC apoptosis and a VEGF-A-neutralizing antibody reversed the inhibitory effect of conditioned media on SMC apoptosis. Stimulation of SMCs with TGF-β led to the formation of a complex of Smad3 and hypoxia-inducible factor-1α (HIF-1α) that in turn activated the VEGF-A promoter and transcription. In rat carotid arteries following arterial injury, Smad3 and VEGF-A expression were upregulated. Moreover, Smad3 gene transfer further enhanced VEGF expression as well as inhibited SMC apoptosis. Finally, blocking either the VEGF receptor or Smad3 signaling in injured carotid arteries abrogated the inhibitory effect of Smad3 on vascular SMC apoptosis. Taken together, our study reveals that following angioplasty, elevation of both TGF-β and Smad3 leads to SMC secretion of VEGF-A that functions as an autocrine inhibitor of SMC apoptosis. This novel pathway provides further insights into the role of TGF-β in the development of IH.

Traumatic wound microbiome workshop

On May 9-10, 2011, the Walter Reed Army Institute of Research, as the Army Center of Excellence for Infectious Disease, assembled over a dozen leaders in areas related to research into the communities of microorganisms which colonize and infect traumatic wounds. The objectives of the workshop were to obtain guidance for government researchers, to spur research community involvement in the field of traumatic wound research informed by a microbiome perspective, and to spark collaborative efforts serving the Wounded Warriors and similarly wounded civilians. During the discussions, it was made clear that the complexity of these infections will only be met by developing a new art of clinical practice that engages the numerous microbes and their ecology. It requires the support of dedicated laboratories and technologists who advance research methods such as community sequencing, as well as the kinds of data analysis expertise and facilities. These strategies already appear to be bearing fruit in the clinical management of chronic wounds. There are now funding announcements and programs supporting this area of research open to extramural collaborators.

Causes of death among people with convulsive epilepsy in rural West China: a prospective study

BACKGROUND

Epilepsy is a serious health problem associated with an increased risk of premature mortality. Few studies have investigated risk factors for this. Understanding these risks may enable the implementation of preventative measures to reduce premature mortality.

METHODS

A management program for convulsive forms of epilepsy has been in place at the primary health care level in rural West China since May 2005. Demographic data and putative causes of death of attendees of the program since inception to the end of December 2009 have been recorded. Case fatality (CF), the proportional mortality ratios (PMRs) for each cause, and standardized mortality ratios (SMRs) for each age and cause were estimated based on the 2007 Chinese rural population.

RESULTS

There were 106 reported deaths (70 male) among 3,568 people. CF was 2.97% during a median of 28 months' follow-up. The highest PMRs were for accidental death (59%) including drowning (45.1%); probable sudden unexpected death in epilepsy (SUDEP) (14.7%); status epilepticus (6.9%), and neoplasm (6.9%). The overall SMR was 4.92 (95% confidence interval 4.0-6.1); the risks were high in young people. The risk of drowning was 82-fold higher in the cohort than the general population.

CONCLUSION

In rural West China, the risk of premature death is nearly 5 times higher in people with convulsive epilepsy than in the general Chinese population and especially high among young people. Accidental death, including drowning, and probable SUDEP are the leading putative causes of death in people with convulsive epilepsy in rural West China.

Inhibition of expression of rna polymerase with small interfering RNAs targeting a conserved motif in the respective viral genes in viruses of the family Flaviviridae

The RNA-dependent RNA polymerase (RdRp) in viruses of the family Flaviviridae plays an important role in the viral replication process and in the forming of a replicase complex. We used small interfering RNAs (siRNAs) corresponding to the highly conservative Motif V of RdRp gene of different viruses to examine their role in modulating the expression of RdRp. Evaluation of the expression of RdRps was performed by the fluorescence, flow cytometry, Western blotting, and real-time PCR. We found that Classical swine fever virus (CSFV) siRNA could completely block the transcription and expression of RdRp. Additionally, Hepatitis C virus (HCV) siRNA could cause effective inhibition of RdRp, whereas Japanese encephalitis virus siRNA did not show significant repression of corresponding RdRp. These results demonstrated that siRNAs inhibited the expression of tested RdRps at the transcription level or at the posttranscriptional processing to a different extent.

[A new method for study of the effect of drugs on cancer cells--31PNMR with perfused cell system]

31P NMR was performed for the studies on the metabolic changes of endogenous phosphorus-containing molecules in KB and HCT-8 cells exposed to taxol at a concentration of 10(-6) mol.L-1. Using the perfusion method, the cells can be detected for a longer time by NMR, so as to give continuous spectra of the two cell-lines during the perfusion with and without the drug. The spectra showed that the levels of ATP peaks for both cells enhanced during the perfusion with the drug, but the change of the level is more prominent in KB cells than in HCT-8 cells. This shows that KB cells are more sensitive to taxol than HCT-8 cells. This is in coincident with the result in the cytotoxicity studies. However, the experiment using vincristine at the same concentrations demonstrated that the level of the ATP peak was not changed significantly.

[The species and the distribution of officinal nettles in Sichuan Province]

OBJECTIVE

To study the resource of officinal nettles in Sichuan.

METHODS

Investigating at the wild spots and consulting the relating specimens.

RESULTS

It has been found that there are 11 spieces and subspieces of genus Urtica in Sichuan Province, of which 8 nettles are commonly used for treatment of rheumatism.

CONCLUSION

This paper can provide scientific reference for further study of officinal nettles in Sichuan.

A dynamic study and modeling of the formation of polyhydroxyalkanoates combined with treatment of high strength wastewater

Production of biodegradable thermoplastics, polyhydroxyalkanoates (PHAs), from organic wastes may provide multiple benefits to environmental conservation efforts. In this study, microfiltration-coupled reactors were set up to study the dynamic behavior of a typical PHA-producing bacteria, Ralstonia eutropha, fed with a real acidic solution from starch acidogenesis in a continuous flow system. The majorfermentation acids (butyric and acetic acids) were utilized by the PHA producers at a high conversion rate (>95%) when the cells were suspended in a small volume of mineral solution (pH 7), but at a low conversion rate (<10%) when the cells were suspended in an acidic solution (pH 4). The acids were consumed mainly for PHA synthesis and maintenance energy, which resulted in slow growth of PHA-producing cells and a washout of the cells in the continuous flow system. PHAs, however, were continuously synthesized and accumulated during the washout. A simple dynamic model is proposed for estimation of specific growth rates and PHA formation rates during the washout at two hydraulic retention times (HRT) or dilution rates. The net specific growth rate of PHA-producing cells was near zero at a hydraulic retention time (HRT) of around 30 h, but it increased to 0.01 h(-1) when the HRT was reduced to 18 h. The model also reveals that PHA was synthesized faster based on the active biomass (ABM) during the short HRT (10.3 mg PHA/g ABM.h) than during the long HRT (3.4 mg PHA/g ABM.h).

[Surgery treatment of retinal detachment with Marfan syndrome]

PURPOSE

To detect the reattachment rate and visual function outcome of Pars Plana Lensectomy, vitrectomy and scleral encircling (PPL + PPV + SE) to treat retinal detachment (RD) with Marfan syndrome.

METHODS

A retrospective study of 11 cases of 14 eyes with Marfan syndrome who submitted to PPL + PPV + SE.

RESULTS

All the cases were followed up for four - 46 months (means 31.2 months). Retinal reattachment rate was 85.7%, visual acuity were 0.3 or better in eight cases.

CONCLUSION

PPL + PPV + SE is a safe and effective treatment for retinal detachment with Marfan syndrome.

[Effect of soil moisture and wetting-drying on Mn release in Ca(NO3)2-amended soils]

A study on the effects of two moisture levels (200 and 400 g.kg-1) and wetting-drying on the solubility of Mn in Ca(NO3)2-amended soils showed that water regime was a factor affecting Mn availability. Easily reducible Mn was transformed into soluble and exchangeable Mn, when soil water content was high. Salt had a definite effect on the transformation of easily reducible Mn. NO3- could decrease soil redox potential, and inhibit the transformation of easily reducible Mn. Wetting-drying significantly(alpha < 0.05) decreased the content of soil water-soluble and exchangeable Mn, while Ca(NO3)2 increased the insolubility of Mn, which might eventually lead to the deficiency of soil Mn.

[Genetic polymorphism of eight STR loci in the Han population in Henan province]

OBJECTIVE

To investigate the allele frequencies of eight short tandem repeats(STR) loci: TH01, FES, D19S400, D7S820, D16S539, D20S161, D3S1545 and D5S818 in Han population in Henan province.

METHODS

DNA was extracted with phenol-chloroform from EDTA-blood samples of the unrelated individuals in Henan province and amplified with PCR technique. The PCR product was analyzed with the undenatured PAGE vertical electrophoresis and silver-stain.

RESULTS

The authors got the frequencies of the eight loci. The heterozygosities of the eight loci are 0.66, 0.67, 0.80, 0.76, 0.79, 0.79, 0.78 and 0.78; the discrimination powers are 0.83, 0.83, 0.94, 0.91, 0.93, 0.93, 0.92 and 0.92.

CONCLUSION

The heterozygosities of the eight loci are high and the frequencies are in good agreement with Hardy-Weinberg equilibrium, so the eight loci can be used in individual identification testing.