Safety and efficacy of intracoronary artery administration of human bone marrow-derived mesenchymal stem cells in STEMI of Lee-Sung pigs-A preclinical study for supporting the feasibility of the OmniMSC-AMI phase I clinical trial.

Background: This study tested whether early left intracoronary arterial (LAD) administration of human bone marrow-derived mesenchymal stem cells (hBMMSCs, called OmniMSCs) in acute ST-segment elevation myocardial infarction (STEMI) of Lee-Sung pigs induced by 90 min balloon-occluded LAD was safe and effective. Methods and results: Young male Lee-Sung pigs were categorized into SC (sham-operated control, n = 3), AMI-B (STEMI + buffer/21 cc/administered at 90 min after STEMI, n = 6), and AMI-M [acute myocardial infarction (AMI) + hBMMSCs/1.5 × 107/administered at 90 min after STEMI, n = 6] groups. By 2 and 5 months after STEMI, the cardiac magnetic resonance imaging demonstrated that the muscle scar score (MSS) and abnormal cardiac muscle exercise score in the infarct region were significantly increased in the AMI-B than in the SC group that were significantly reversed in the AMI-M group, whereas the left ventricular ejection function by each month (from 1 to 5) displayed an opposite pattern of MSS among the groups (all p < 0.001). By 5 months, histopathological findings of infarct and fibrosis areas and isolectin-B4 exhibited an identical pattern, whereas the cellular expressions of troponin-I/troponin-T/von Willebrand factor exhibited an opposite pattern of MSS among the groups (all p < 0.001). The ST-segment resolution (>80%) was significantly earlier (estimated after 6-h AMI) in the AMI-M group than in the AMI-B group (p < 0.001). The protein expressions of inflammation (IL-1ß/TNF-α/NF-κB)/oxidative stress (NOX-1/NOX-2/oxidized protein)/apoptosis (cleaved caspase-3/cleaved PARP)/DNA damage (γ-H2AX) displayed an identical pattern to MSS among the groups, whereas the protein expressions of angiogenesis factors (SDF-1α/VEGF) were significantly and progressively increased from SC, AMI-B, to AMI-M groups (all p < 0.001). Conclusion: Early intra-LAD transfusion of OmniMSC treatment effectively reduced the infarct size and preserved LV function in porcine STEMI.

Probiotics' Efficacy in Preventing Asthmatic Allergic Reaction Induced by Air Particles: An Animal Study.

Global air pollution and diesel exhaust particles (DEPs) generated by intratracheal instillation aggravate asthma. In this study, we evaluated the effect of probiotics via tracheal- or oral-route administration on allergies or asthma. We continuously perfused rats daily, using the oral and tracheal routes, with approximately 106-108 CFU probiotics, for 4 weeks. During this period, we used OVA-sensitized rats to build the asthma models. We orally or intratracheally administered Lactobacillus paracasei 33 (LP33) to the rats, which reduced the number of total inflammatory cells, lymphocytes, and eosinophils in the bronchoalveolar-lavage fluid, the IgE concentration, and the cytokine levels of TH2 cells, but we found no significant difference in the cytokine levels of TH1 cells. LP33 can be used to prevent asthmatic allergic reactions induced by aerosol particles. Nevertheless, the dosage form or use of LP33 needs to be adjusted to reduce the irritation of lung tissues, which may produce lesions of the trachea. We observed that DEP dosage can alleviate emphysema, and that LP33 has a substantial effect on improving or slowing allergic asthma.

Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model Development and Validation Study.

BACKGROUND: The automatic coding of clinical text documents by using the International Classification of Diseases, 10th Revision (ICD-10) can be performed for statistical analyses and reimbursements. With the development of natural language processing models, new transformer architectures with attention mechanisms have outperformed previous models. Although multicenter training may increase a model's performance and external validity, the privacy of clinical documents should be protected. We used federated learning to train a model with multicenter data, without sharing data per se. OBJECTIVE: This study aims to train a classification model via federated learning for ICD-10 multilabel classification. METHODS: Text data from discharge notes in electronic medical records were collected from the following three medical centers: Far Eastern Memorial Hospital, National Taiwan University Hospital, and Taipei Veterans General Hospital. After comparing the performance of different variants of bidirectional encoder representations from transformers (BERT), PubMedBERT was chosen for the word embeddings. With regard to preprocessing, the nonalphanumeric characters were retained because the model's performance decreased after the removal of these characters. To explain the outputs of our model, we added a label attention mechanism to the model architecture. The model was trained with data from each of the three hospitals separately and via federated learning. The models trained via federated learning and the models trained with local data were compared on a testing set that was composed of data from the three hospitals. The micro F1 score was used to evaluate model performance across all 3 centers. RESULTS: The F1 scores of PubMedBERT, RoBERTa (Robustly Optimized BERT Pretraining Approach), ClinicalBERT, and BioBERT (BERT for Biomedical Text Mining) were 0.735, 0.692, 0.711, and 0.721, respectively. The F1 score of the model that retained nonalphanumeric characters was 0.8120, whereas the F1 score after removing these characters was 0.7875-a decrease of 0.0245 (3.11%). The F1 scores on the testing set were 0.6142, 0.4472, 0.5353, and 0.2522 for the federated learning, Far Eastern Memorial Hospital, National Taiwan University Hospital, and Taipei Veterans General Hospital models, respectively. The explainable predictions were displayed with highlighted input words via the label attention architecture. CONCLUSIONS: Federated learning was used to train the ICD-10 classification model on multicenter clinical text while protecting data privacy. The model's performance was better than that of models that were trained locally.

Automatic International Classification of Diseases Coding System: Deep Contextualized Language Model With Rule-Based Approaches.

BACKGROUND: The tenth revision of the International Classification of Diseases (ICD-10) is widely used for epidemiological research and health management. The clinical modification (CM) and procedure coding system (PCS) of ICD-10 were developed to describe more clinical details with increasing diagnosis and procedure codes and applied in disease-related groups for reimbursement. The expansion of codes made the coding time-consuming and less accurate. The state-of-the-art model using deep contextual word embeddings was used for automatic multilabel text classification of ICD-10. In addition to input discharge diagnoses (DD), the performance can be improved by appropriate preprocessing methods for the text from other document types, such as medical history, comorbidity and complication, surgical method, and special examination. OBJECTIVE: This study aims to establish a contextual language model with rule-based preprocessing methods to develop the model for ICD-10 multilabel classification. METHODS: We retrieved electronic health records from a medical center. We first compared different word embedding methods. Second, we compared the preprocessing methods using the best-performing embeddings. We compared biomedical bidirectional encoder representations from transformers (BioBERT), clinical generalized autoregressive pretraining for language understanding (Clinical XLNet), label tree-based attention-aware deep model for high-performance extreme multilabel text classification (AttentionXLM), and word-to-vector (Word2Vec) to predict ICD-10-CM. To compare different preprocessing methods for ICD-10-CM, we included DD, medical history, and comorbidity and complication as inputs. We compared the performance of ICD-10-CM prediction using different preprocesses, including definition training, external cause code removal, number conversion, and combination code filtering. For the ICD-10 PCS, the model was trained using different combinations of DD, surgical method, and key words of special examination. The micro F1 score and the micro area under the receiver operating characteristic curve were used to compare the model's performance with that of different preprocessing methods. RESULTS: BioBERT had an F1 score of 0.701 and outperformed other models such as Clinical XLNet, AttentionXLM, and Word2Vec. For the ICD-10-CM, the model had an F1 score that significantly increased from 0.749 (95% CI 0.744-0.753) to 0.769 (95% CI 0.764-0.773) with the ICD-10 definition training, external cause code removal, number conversion, and combination code filter. For the ICD-10-PCS, the model had an F1 score that significantly increased from 0.670 (95% CI 0.663-0.678) to 0.726 (95% CI 0.719-0.732) with a combination of discharge diagnoses, surgical methods, and key words of special examination. With our preprocessing methods, the model had the highest area under the receiver operating characteristic curve of 0.853 (95% CI 0.849-0.855) and 0.831 (95% CI 0.827-0.834) for ICD-10-CM and ICD-10-PCS, respectively. CONCLUSIONS: The performance of our model with the pretrained contextualized language model and rule-based preprocessing method is better than that of the state-of-the-art model for ICD-10-CM or ICD-10-PCS. This study highlights the importance of rule-based preprocessing methods based on coder coding rules.

Predicting Postoperative Mortality With Deep Neural Networks and Natural Language Processing: Model Development and Validation.

BACKGROUND: Machine learning (ML) achieves better predictions of postoperative mortality than previous prediction tools. Free-text descriptions of the preoperative diagnosis and the planned procedure are available preoperatively. Because reading these descriptions helps anesthesiologists evaluate the risk of the surgery, we hypothesized that deep learning (DL) models with unstructured text could improve postoperative mortality prediction. However, it is challenging to extract meaningful concept embeddings from this unstructured clinical text. OBJECTIVE: This study aims to develop a fusion DL model containing structured and unstructured features to predict the in-hospital 30-day postoperative mortality before surgery. ML models for predicting postoperative mortality using preoperative data with or without free clinical text were assessed. METHODS: We retrospectively collected preoperative anesthesia assessments, surgical information, and discharge summaries of patients undergoing general and neuraxial anesthesia from electronic health records (EHRs) from 2016 to 2020. We first compared the deep neural network (DNN) with other models using the same input features to demonstrate effectiveness. Then, we combined the DNN model with bidirectional encoder representations from transformers (BERT) to extract information from clinical texts. The effects of adding text information on the model performance were compared using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). Statistical significance was evaluated using P<.05. RESULTS: The final cohort contained 121,313 patients who underwent surgeries. A total of 1562 (1.29%) patients died within 30 days of surgery. Our BERT-DNN model achieved the highest AUROC (0.964, 95% CI 0.961-0.967) and AUPRC (0.336, 95% CI 0.276-0.402). The AUROC of the BERT-DNN was significantly higher compared to logistic regression (AUROC=0.952, 95% CI 0.949-0.955) and the American Society of Anesthesiologist Physical Status (ASAPS AUROC=0.892, 95% CI 0.887-0.896) but not significantly higher compared to the DNN (AUROC=0.959, 95% CI 0.956-0.962) and the random forest (AUROC=0.961, 95% CI 0.958-0.964). The AUPRC of the BERT-DNN was significantly higher compared to the DNN (AUPRC=0.319, 95% CI 0.260-0.384), the random forest (AUPRC=0.296, 95% CI 0.239-0.360), logistic regression (AUPRC=0.276, 95% CI 0.220-0.339), and the ASAPS (AUPRC=0.149, 95% CI 0.107-0.203). CONCLUSIONS: Our BERT-DNN model has an AUPRC significantly higher compared to previously proposed models using no text and an AUROC significantly higher compared to logistic regression and the ASAPS. This technique helps identify patients with higher risk from the surgical description text in EHRs.

Automatic ICD-10 Coding and Training System: Deep Neural Network Based on Supervised Learning.

BACKGROUND: The International Classification of Diseases (ICD) code is widely used as the reference in medical system and billing purposes. However, classifying diseases into ICD codes still mainly relies on humans reading a large amount of written material as the basis for coding. Coding is both laborious and time-consuming. Since the conversion of ICD-9 to ICD-10, the coding task became much more complicated, and deep learning- and natural language processing-related approaches have been studied to assist disease coders. OBJECTIVE: This paper aims at constructing a deep learning model for ICD-10 coding, where the model is meant to automatically determine the corresponding diagnosis and procedure codes based solely on free-text medical notes to improve accuracy and reduce human effort. METHODS: We used diagnosis records of the National Taiwan University Hospital as resources and apply natural language processing techniques, including global vectors, word to vectors, embeddings from language models, bidirectional encoder representations from transformers, and single head attention recurrent neural network, on the deep neural network architecture to implement ICD-10 auto-coding. Besides, we introduced the attention mechanism into the classification model to extract the keywords from diagnoses and visualize the coding reference for training freshmen in ICD-10. Sixty discharge notes were randomly selected to examine the change in the F1-score and the coding time by coders before and after using our model. RESULTS: In experiments on the medical data set of National Taiwan University Hospital, our prediction results revealed F1-scores of 0.715 and 0.618 for the ICD-10 Clinical Modification code and Procedure Coding System code, respectively, with a bidirectional encoder representations from transformers embedding approach in the Gated Recurrent Unit classification model. The well-trained models were applied on the ICD-10 web service for coding and training to ICD-10 users. With this service, coders can code with the F1-score significantly increased from a median of 0.832 to 0.922 (P<.05), but not in a reduced interval. CONCLUSIONS: The proposed model significantly improved the F1-score but did not decrease the time consumed in coding by disease coders.

Utilizing Xenogeneic Cells As a Therapeutic Agent for Treating Diseases.

The utilization of biologically produced cells to treat diseases is a revolutionary invention in modern medicine after chemically synthesized small molecule drugs and biochemically made protein drugs. Cells are basic units of life with diverse functions in mature and developing organs, which biological properties could be utilized as a promising therapeutic approach for currently intractable and incurable diseases. Xenogeneic cell therapy utilizing animal cells other than human for medicinal purpose has been studied as a new way of treating diseases. Xenogeneic cell therapy is considered as a potential regenerative approach to fulfill current unmet medical needs because xenogeneic cells could be isolated from different animal organs and expanded ex vivo as well as maintain the characteristics of original organs, providing a versatile and plenty cell source for cell-based therapeutics beside autologous and allogeneic sources. The swine species is considered the most suitable source because of the similarity with humans in size and physiology of many organs in addition to the economic and ethical reasons plus the possibility of genetic modification. This review discusses the old proposed uses of xenogeneic cells such as xenogeneic pancreatic islet cells, hepatocytes and neuronal cells as a living drug for the treatment of degenerative and organ failure diseases. Novel applications of xenogeneic mesenchymal stroma cells and urothelial cells are also discussed. There are formidable immunological barriers toward successful cellular xenotransplantation in clinic despite major progress in the development of novel immunosuppression regimens and genetically multimodified donor pigs. However, immunological barriers could be turn into immune boosters by using xenogeneic cells of specific tissue types as a novel immunotherapeutic agent to elicit bystander antitumor immunity due to rejection immune responses. Xenogeneic cells have the potential to become a safe and efficacious option for intractable diseases and hard-to-treat cancers, adding a new class of cellular medicine in our drug armamentarium.

A resorbable hyaluronic acid hydrogel to prevent adhesion in porcine model under laparotomy pelvic surgery.

Surgical post-operative adhesions can lead to serious clinical complications. Barrier agent is the broad usage for the prevention of post-operative adhesions. This study aimed to evaluate the reducing adhesion efficacy of non-animal hyaluronic acid (HA) hydrogel in pigs undergoing conventional laparotomy pelvic surgery. HA hydrogel was applied to eighteen female pigs who underwent conventional laparotomy. The adhesion degrees and histopathology were evaluated in bilateral uterine horns as well as peritoneal sidewall excision. In the present study, all animals survived and had no complications after the surgery. The histopathological observations were demonstrated that HA obviously improved laparotomy pelvic surgery-induced adhesion in peritoneal sidewall and uterine horn. The anastomotic healing score of injury + HA group was significantly lower than the injury alone group. We conclude HA hydrogel can attenuate the post-operative adhesions in porcine.

Hair growth is promoted by BeauTop via expression of EGF and FGF­7.

Minoxidil and finasteride have been approved to treat hair loss by the Food and Drug Administration. However, the further elucidation of treatments for hair loss, including those using Chinese herbal medicine, remains important clinically. BeauTop (BT) is a health food supplement which contains Ginseng radix, Astragali radix, Radix Angelicae sinensis, Ligustri fructus, Rehmannia glutinosa and Eclipta prostrata (Linn). Susbsequent to oral administration of BT at 0.6 g/kg/day to wax/rosin­induced alopecia in C57BL/6 mice, BT significantly induced hair growth at day 8 compared with control treatment (P<0.05). The expression levels of epidermal growth factor (EGF), and fibroblast growth factor (FGF)­7 were increased compared with control animals on day 8. In contrast, levels of FGF­5 of the BT group were reduced compared with the control on day 12. There were no effects on the expression of insulin­like growth factor 1. The results demonstrated that the mechanism of BT improving alopecia is potentially associated with modulation of EGF and FGF­7 levels. Taken together, it is suggested that BT may have a potential effect of the promotion of hair growth.

Angiotensin receptor blockers are associated with lower mortality than ACE inhibitors in predialytic stage 5 chronic kidney disease: A nationwide study of therapy with renin-angiotensin system blockade.

Dual renin angiotensin system (RAS) blockade using angiotensin-receptor blockers (ARBs) in combination with angiotensin converting enzyme inhibitors (ACEIs) is reported to improve proteinuria in both diabetic and non-diabetic patients. However, its renoprotective effect and safety remain uncertain in patients with advanced chronic kidney disease (CKD). From January 1, 2000 through June 30, 2009, we enrolled 14,117 pre-dialytic stage 5 CKD patients with serum creatinine >6mg/dL and hematocrit <28% under the treatment with erythropoiesis stimulating agents and RAS blockade. We used Cox proportional hazards regression models to estimate the hazard ratios (HRs) against the commencement of long-term dialysis and all-cause mortality for ACEI/ARB users. Over a median follow-up of 7 months, 9,867 patients (69.9%) required long-term dialysis and 2,805 (19.9%) died before progression to end-stage renal disease requiring dialysis. In comparison with the ARB-only users, dual blockade with ACEIs and ARBs was associated with a significantly higher risk of (1) death in all CKD patients (HR = 1.49, [95%CI, 1.30-1.71]; P = 0.02) and in diabetic subgroup (HR = 1.58, [95%CI, 1.34-1.86]; P = 0.02); (2) composite endpoint of long-term dialysis or death in diabetic subgroup (HR = 1.10, [95%CI, 1.01-1.20]; P = 0.04); (3) hyperkalemia-associated hospitalization in non-diabetic subgroup (HR, 2.74, [95%CI, 1.05-7.15]; P = 0.04). However, ACEIs users were associated with higher mortality than ARBs users in all CKD patients (HR = 1.17, [95%CI, 1.07-1.27]; P = 0.03) and in diabetic subgroup (HR = 1.32, [95%CI, 1.18-1.48]; P = 0.03). Monotherapy of RAS blockade, especially ARB, is more effective and safer than dual RAS blockade in pre-dialytic stage 5 CKD patients.

Evaluation of LPS-Induced Acute Lung Injury Attenuation in Rats by Aminothiazole-Paeonol Derivatives.

Paeonol is a key phenolic compound in the root bark of Moutan Cortex Radicis that has been used in traditional Chinese Medicine to ameliorate inflammation. A series of aminothiazole-paeonol derivatives (APDs) were synthesized in this work and subjected to preliminary evaluation in cells followed by verification in animals. Quantification of monocyte chemotactic protein-1 (MCP-1) and interleukin-6 (IL-6) in culture media of LPS-activated A549 cells, a lung epithelial adenocarcinoma cell line, were used to investigate the anti-inflammatory capability of APDs. ALI-bearing rats were employed to verify therapeutic efficacy of APDs according to observations of total cells, protein amounts, MCP-1 and IL-6 in bronchoalveolar lavage fluid (BALF). Histopathological examinations of lung tissues were consequently applied for validation of APDs. Among these compounds, 2-(2-aminothiazol-4-yl)-5-methoxyphenol (4) had the most potent activity, showing comparable inhibition of MCP-1/IL-6 and superior elimination of neutrophil infiltration and protein exudation in lungs compared to others as well as dexamethasone. This study demonstrated a comprehensive strategy to evaluate APDs through integration of cell-based screening and animal-based verification. In order to fulfill unmet needs of treating acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), APDs introduced in this work could be promising lead compounds to develop high potent anti-inflammation agents.

Carthamus tinctorius L. ameliorates brain injury followed by cerebral ischemia-reperfusion in rats by antioxidative and anti-inflammatory mechanisms.

OBJECTIVES: Carthamus tinctorius L. (CT) or safflower is widely used in traditional Chinese medicine. This study investigated the effects of CT extract (CTE) on ischemia-reperfusion (I/R) brain injury and elucidated the underlying mechanism. MATERIALS AND METHODS: The I/R model was conducted by occlusion of both common carotid arteries and right middle cerebral artery for 90 min followed by 24 hr reperfusion in Sprague-Dawley rats. CTE (0.2-0.6 g/kg) was administered intraperitoneally before and during ischemia, and during reperfusion period. The cerebral infarction area, neurological deficit scores, free radicals (lucigenin chemiluminescence counts) and pro-inflammatory cytokines expression were measured. RESULTS: Pretreatment and treatment with CTE significantly reduced the cerebral infarction area and neurological deficits. CTE (0.4 g/kg) also reduced blood levels of free radicals and expression of tumor necrosis factor-α and interleukin-1ß in the cerebral infarction area. CONCLUSION: The reduction in I/R cerebral infarction caused by CTE is possibly associated with its antioxidation and anti-inflammatory properties.

A New Molecular Design Based on Thermally Activated Delayed Fluorescence for Highly Efficient Organic Light Emitting Diodes.

Two benzoylpyridine-carbazole based fluorescence materials DCBPy and DTCBPy, bearing two carbazolyl and 4-(t-butyl)carbazolyl groups, respectively, at the meta and ortho carbons of the benzoyl ring, were synthesized. These molecules show very small ΔEST of 0.03 and 0.04 eV and transient PL characteristics indicating that they are thermally activated delayed fluorescence (TADF) materials. In addition, they show extremely different photoluminescent quantum yields in solution and in the solid state: in cyclohexane the value are 14 and 36%, but in the thin films, the value increase to 88.0 and 91.4%, respectively. The OLEDs using DCBPy and DTCBPy as dopants emit blue and green light with EQEs of 24.0 and 27.2%, respectively, and with low efficiency roll-off at practical brightness level. The crystal structure of DTCBPy reveals a substantial interaction between the ortho donor (carbazolyl) and acceptor (4-pyridylcarbonyl) unit. This interaction between donor and acceptor substituents likely play a key role to achieve very small ΔEST with high photoluminescence quantum yield.

Anti-human hepatoma Hep-G2 proliferative, apoptotic, and antimutagenic activity of tagitinin C from Tithonia diversifolia leaves.

Tagitinin C, a major sesquiterpenoid, was isolated from the leaves of Tithonia diversifolia. The high morbidity and mortality rate of hepatoma in Taiwan motivated our interest in the investigation of tagitinin C's mechanism against the human hepatocellular carcinoma. The methanolic extract of leaves of T. diversifolia (TDM) and tagitinin C were found to have cytotoxic activities against human hepatoma Hep-G2 cells in the MTT assay with IC(50) values of 40.0 ± 2.0 and 2.0 ± 0.1 µg/mL, respectively. This compound induced population increase in the sub-G(1) phase and S phase arrest. Treatment with tagitinin C isolated from TDM resulted in activation of both caspase 3 and caspase 8 which suggested that the antiproliferative effect of this compound was caspase-dependent apoptosis. Magnetic resonance techniques indicated that the tumorigenisity of xenografts derived from Hep-G2 cells was retarded by the delivery of tagitinin C (15 µg/mouse/day) relative to the control counterparts.

Moutan cortex radicis improves lipopolysaccharide-induced acute lung injury in rats through anti-inflammation.

Moutan cortex radicis (MCR) is a Chinese herbal medicine that was widely used over a long period as an analgesic, antipyretic, and anti-inflammatory agent in China. Lipopolysaccharide (LPS)-induced acute lung injury (ALI) in rat models is considered similar to adult respiratory distress syndrome (ARDS) in humans. Therefore, the present study investigates the effect of MCR on ALI. The ALI model was developed through the intra-tracheal (IT) administration of LPS (16mg/kg) to Sprague-Dawley (SD) rats, which formed the LPS group. MCR was orally administered before and after LPS was introduced into rats (MCR-LPS group and LPS-MCR group, respectively). In the MCR-LPS group, rats received MCR 2g/kg/times 3 times before LPS challenge; the LPS-MCR group received MCR 2g/kg/times 3 times after LPS challenge. The results of this experiment indicate that the number of total cells and neutrophils and the concentration of protein exudation in bronchoalveolar lavage fluid (BALF) significantly decreased in the MCR-LPS group. Cytokine levels, including levels of interleukin (IL)-1ß, macrophage-inflammatory peptide (MIP)-2, IL-6, and IL-10, in BALF were also significantly inhibited at 16h after LPS administration in the MCR-LPS group. Myeloperoxidase (MPO) activity in lung tissue was reduced in the MCR-LPS and LPS-MCR groups at 16h after LPS administration. Furthermore, leukocyte infiltration and protein exudation in the alveolar space were less severe in the MCR-LPS group than in the LPS group. Therefore, the findings of this study suggest that the administration of MCR prior to LPS improves ALI, possibly mediating ALI through anti-inflammation.

Detection of asymptomatic paroxysmal atrial fibrillation with the trans-telephonic electrocardiograph system.

Paroxysmal atrial fibrillation (PAF) carries an equally high annual stroke rate as chronic atrial fibrillation (AF). Furthermore, the frequency and duration of PAF are thought to be associated with stroke risk. In this pilot study, a trans-telephonic electrocardiograph (TTE) monitoring system was used to detect asymptomatic PAF and to study the relationship between ischemic stroke and the frequency of PAF. Between December 2004 and April 2006, 70 patients enrolled in the TTE monitoring program. Patients either transmitted electrocardiograms (ECGs) daily or upon experiencing cardiac symptoms. Of the 70 patients included, 25 were diagnosed with PAF. In total, 11% (855/7,768) of the recordings were diagnosed as PAF, yet less than 2% of total calls collected and less than 17% of all the calls with PAF were associated with obvious symptoms. Four patients developed five ischemic strokes resulting in a calculated annual stroke rate of 0.56%. Patients with stroke had more episodes of AF (56.5±106.3 versus 6.7±85.9, p=0.685) and symptomatic AF episodes (9.8±17.5 versus 4.9±8.1, p=0.381) than the patients who did not have a stroke, but the differences were not statistically significant because of the low numbers of patients and episodes. Most PAF episodes were asymptomatic, and the TTE system could easily detect these episodes. Furthermore, these four patients tended to have more episodes of PAF and more symptomatic attacks of PAF than patients who did not have a stroke.

Sustained release of transgenic human factor IX: preparation, characterization, and in vivo efficacy.

The current regimen of factor IX (FIX) injection is of an episodic format, which leads to limited efficacy. A sustained release dosage form is beneficial in terms of reducing the injection frequency and improving the therapeutic effectiveness. The aim of this study was to formulate a new microsphere form of a FIX-containing preparation to diminish these shortcomings. Using the water-in-oil-in-water (W/O/W) double emulsion technique, injectable long-acting FIX microspheres were prepared with transgenic recombinant human FIX (rhFIX) and poly(lactic-co-glycolic acid) (PLGA) polymer. The rhFIX microspheres prepared had diameters ranging between 25-350 µm and easily passed through a small-gauge-number needle for subcutaneous injection. In in vitro release testing, the microspheres had a sustained release profile featuring an initial burst and sustained release spanning a 5-day period. In in vivo pharmacodynamic testing, normalization of the bleeding of hemophilic mice was maintained for 5 days with microsphere injection as compared with 2 days with native rhFIX. Taken together, these results indicated that long-acting FIX microspheres were successfully prepared for potential use in hemophilic prophylaxis.

The detrended fluctuation analysis of acute-phase heart-rate variability in acute coronary syndromes - a pilot study.

Heart-rate variability (HRV) analyzed by detrended fluctuation analysis (DFA), which resulted in a short-term fractal exponent - alpha, has prognostic implication in chronic phase of heart failure and survivors of myocardial infarction. We adopted DFA to study the acute-phase HRV in acute coronary syndromes (ACS) by recruiting 30 age- and co-morbidity-matched adults in acute-stress simulation in comparison with 33 consecutive ACS patients. The 30 volunteers got stepwise elevated alpha with increased intensity of exercise (0.95+/-0.050 to 1.07+/-0.084 to 1.20+/-0.083, p<0.05). The alpha of 33 ACS patients correlated with the complexity of post-MI course (1.004+/-0.0080 in non-complicated vs. 1.216+/-0.058 in complicated p<0.05). No significance existed in categories of age, ACS type, numbers of diseased vessel, infarct-related artery or Killip classification. The increased alpha value of DFA may imply unresolved cardiac stress which demands further attention.

Impact of an audit program and other factors on door-to-balloon times in acute ST-elevation myocardial infarction patients destined for primary coronary intervention.

OBJECTIVES: This before-after study investigated the association between an audit program and door-to-balloon times in patients with acute ST-elevation myocardial infarction (STEMI) and explored other factors associated with the door-to-balloon time. METHODS: An audit program that collected time data for essential time intervals in acute STEMI was developed with data feedback to both the Department of Emergency Medicine and the Department of Cardiology. The door-to-balloon times for 76 consecutive acute STEMI patients were collected from February 16, 2007, through October 31, 2007, after the implementation of the audit program, as the intervention group. The control group was defined by 104 consecutive acute STEMI patients presenting from April 1, 2006, through February 15, 2007, before the audit was applied. A multivariate linear regression model was used for analysis of factors associated with the door-to-balloon time. RESULTS: The geometric mean 95% CI of the door-to-balloon time decreased from 164.9 (150.3, 180.9) minutes to 141.9 (127.4, 158.2) minutes (p = 0.039) in the intervention phase. The median door-to-balloon time was 147.5 minutes in the control group and 136.0 minutes in the intervention group (p = 0.09). In the multivariate regression model, the audit program was associated with a shortening of the door-to-balloon time by 35.5 minutes (160.4 minutes vs. 195.9 minutes, p = 0.004); female gender was associated with a mean delay of 58.4 minutes (208.9 minutes vs. 150.5 minutes; p = 0.001); posterolateral wall infarction was associated with a mean delay of 70.5 minutes compared to anterior wall infarction (215.4 minutes vs. 144.9 minutes; p = 0.037) and a mean delay of 69.5 minutes compared to inferior wall infarction (215.4 minutes vs. 145.9 minutes; p = 0.044). The use of a glycoprotein IIb/IIIa inhibitor was associated with a 46.1 minutes mean shortening of door-to-balloon time (155.7 minutes vs. 201.8 minutes; p < 0.001). CONCLUSIONS: The implementation of an audit program was associated with a significant reduction in door-to-balloon times among patients with acute STEMI. In addition, female patients, posterolateral wall infarction territory, and nonuse of glycoprotein IIb/IIIa inhibitor were associated with longer door-to-balloon times.