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OBJECTIVE: To investigate the predictive value of cervical Hounsfiled Unit (HU) values for postoperative titanium mesh cage (TMC) subsidence. METHODS: Clinical data of patients who underwent ACCF surgery for degenerative cervical myelopathy between January 2016 and August 2018 were analyzed. Among the 126 patients included, 74 were male and 52 were female, with a mean age of 61.0 ± 9.9 years. The mean follow-up was 37.1 ± 11.2 months. Preoperative vertebral HU values were measured and the degree of TMC subsidence during follow-up was assessed. Patients were divided into two groups according to the presence or absence of subsidence: the subsidence group and the control group. Vertebral HU values were compared between the two groups, and correlation analysis was performed between HU values and TMC subsidence values. In addition, the predictive value and threshold of HU were analyzed by using ROC. RESULTS: There were 22 patients (14 males and 8 females) who developed TMC subsidence (subsidence group), while 104 patients (60 males and 44 females) did not develop TMC subsidence (control group) during follow-up. Comparative analysis of demographic characteristics between the two groups showed no significant differences in gender, age, BMI, diagnosis, surgical levels, and follow-up duration (all P values > 0.05). There was a significant difference in mean HU between the subsidence group (287.6 ± 49.6) and the control group (342.4 ± 61.4) (t = -3.92, P < 0.01). In the subsidence group, there was a significant correlation between subsidence values and HU values (r = -0.52, P = 0.01), whereas no such correlation was observed in the control group (r = - 0.07, P = 0.51). ROC analysis indicated that vertebral HU values could potentially be used to predict subsidence after ACCF, with an area under the ROC curve of 0.77 (95% CI 0.66-0.87; P < 0.01). The optimal HU threshold was found to be 298, with a sensitivity of 76.9% and specificity of 68.2%. CONCLUSION: Preoperative vertebral HU values were associated with postoperative TMC subsidence. Vertebral HU may be a valuable predictor of postoperative subsidence.

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KEY MESSAGE: Efficient selectable marker gene autoexcision in transgenic plants of soybean, cotton, canola, and maize is achieved by effective Cre recombinase expression. Selectable marker genes are often required for efficient generation of transgenic plants in plant transformation but are not desired once the transgenic events are obtained. We have developed Cre/loxP autoexcision systems to remove selectable marker genes in soybean, cotton, canola and maize. We tested a set of vectors with diverse promoters and identified promising promoters to drive cre expression for each of the four crops. We evaluated both the efficiency of generating primary transgenic events with low transgene copy numbers, and the frequency of marker-free progeny in the next generation. The best performing vectors gave no obvious decrease in the transformation frequency in each crop and generated homozygous marker-free progeny in the next generation. We found that effective expression of Cre recombinase for marker gene autoexcision can be species dependent. Among the vectors tested, the best autoexcision frequency (41%) in soybean transformation came from using the soybean RSP1 promoter for cre expression. The cre gene expressed by soybean RSP1 promoter with an Arabidopsis AtpE intron delivered the best autoexcision frequency (69%) in cotton transformation. The cre gene expressed by the embryo-specific eUSP88 promoter from Vicia faba conferred the best marker excision frequency (32%) in canola transformation. Finally, the cre gene expressed by the rice CDC45-1 promoter resulted in 44% autoexcision in maize transformation. The Cre/loxP recombinase system enables the generation of selectable marker-free transgenic plants for commercial product development in four agriculturally important crops and provides further improvement opportunities for more specific and better marker excision efficiency.

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Osteosarcoma (OS) is a primary malignant tumor of the bone, with a tendency to metastasize early. Despite the advances in treatment options, more than 30% of patients develop distant metastases, and the prognosis of these patients with metastases is extremely poor. Celastrol has been demonstrated to manifest multiple pharmacological activities, including induction of apoptosis in numerous types of cancer cell lines. Our previous studies have also suggested that Celastrol is capable of inducing apoptosis of human osteosarcoma cells via the mitochondrial-dependent pathway. The purpose of this study was to investigate the effects of Celastrol on the migration and invasion of human osteosarcoma U-2OS cells in vitro. Cell migration and invasion were investigated using wound healing and Boyden chamber Transwell assays. We observed that Celastrol suppressed cell invasion and migration in human osteosarcoma U-2OS cells. Furthermore, protein expression levels of phosphorylated phosphatidylinositol 3-kinase (PI3K), Akt, inhibitor of κB kinase α/ß, inhibitor of κB α, nuclear factor-κB (NF-κB subunit p65) and matrix metalloproteinase (MMP)-2 and -9 were measured by western blot analysis. We observed that the PI3K/Akt/NF-κB signaling pathway was inhibited following Celastrol treatment. In addition, the expression levels of MMP-2 and -9 proteins were also reduced significantly following Celastrol treatment. Therefore, we confirmed that Celastrol suppressed osteosarcoma U-2OS cell metastasis via downregulation of the PI3K/Akt/NF-κB signaling pathway in vitro.

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BACKGROUND: Before performing spine non-fusion surgery that retains the facet joints, choosing an accurate radiographic method to evaluate the degree of facet joint degeneration is extremely important. Therefore, the objective of this study was to determine the accuracy and reliability of different radiographic classifications by analyzing the correlation between radiographic and pathologic grading of lumbar facet joint degeneration. Taking the pathologic examination as standard, the consistency of computed tomography (CT) and magnetic resonance imaging (MRI) assessment of lumbar facet joint degeneration was compared. METHODS: A total of 74 facet joints obtained from 42 patients who underwent posterior lumbar surgery were evaluated. All patients underwent CT and MRI before surgery. The pathologic grade was evaluated with a method based on hematoxylin-eosin and toluidine blue staining. The radiographic grade was evaluated using the methods proposed by different authors. RESULTS: There was a moderate consistency between pathologic and radiographic grading for facet joint degeneration. The weighted kappa coefficients comparing pathologic with radiographic grading were 0.506 for CT, 0.561 for MRI, and 0.592 for CT combined with MRI, respectively. Taking the pathologic examination as standard, the consistency of CT and MRI examination was also moderate, and the weighted kappa coefficient was 0.459. CONCLUSION: The radiographic examination has moderate accuracy and reliability for evaluating degeneration of facet joints. Therefore, a more accurate method for evaluating the degeneration of facet joints is necessary before performing spine non-fusion surgery that retains the facet joints.

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BACKGROUND: Estimating patient risk of future emergency department (ED) revisits can guide the allocation of resources, e.g. local primary care and/or specialty, to better manage ED high utilization patient populations and thereby improve patient life qualities. METHODS: We set to develop and validate a method to estimate patient ED revisit risk in the subsequent 6 months from an ED discharge date. An ensemble decision-tree-based model with Electronic Medical Record (EMR) encounter data from HealthInfoNet (HIN), Maine's Health Information Exchange (HIE), was developed and validated, assessing patient risk for a subsequent 6 month return ED visit based on the ED encounter-associated demographic and EMR clinical history data. A retrospective cohort of 293,461 ED encounters that occurred between January 1, 2012 and December 31, 2012, was assembled with the associated patients' 1-year clinical histories before the ED discharge date, for model training and calibration purposes. To validate, a prospective cohort of 193,886 ED encounters that occurred between January 1, 2013 and June 30, 2013 was constructed. RESULTS: Statistical learning that was utilized to construct the prediction model identified 152 variables that included the following data domains: demographics groups (12), different encounter history (104), care facilities (12), primary and secondary diagnoses (10), primary and secondary procedures (2), chronic disease condition (1), laboratory test results (2), and outpatient prescription medications (9). The c-statistics for the retrospective and prospective cohorts were 0.742 and 0.730 respectively. Total medical expense and ED utilization by risk score 6 months after the discharge were analyzed. Cluster analysis identified discrete subpopulations of high-risk patients with distinctive resource utilization patterns, suggesting the need for diversified care management strategies. CONCLUSIONS: Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. It promises to provide increased opportunity for high ED utilization identification, and optimized resource and population management.

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OBJECTIVES: Identifying patients at risk of a 30-day readmission can help providers design interventions, and provide targeted care to improve clinical effectiveness. This study developed a risk model to predict a 30-day inpatient hospital readmission for patients in Maine, across all payers, all diseases and all demographic groups. METHODS: Our objective was to develop a model to determine the risk for inpatient hospital readmission within 30 days post discharge. All patients within the Maine Health Information Exchange (HIE) system were included. The model was retrospectively developed on inpatient encounters between January 1, 2012 to December 31, 2012 from 24 randomly chosen hospitals, and then prospectively validated on inpatient encounters from January 1, 2013 to December 31, 2013 using all HIE patients. RESULTS: A risk assessment tool partitioned the entire HIE population into subgroups that corresponded to probability of hospital readmission as determined by a corresponding positive predictive value (PPV). An overall model c-statistic of 0.72 was achieved. The total 30-day readmission rates in low (score of 0-30), intermediate (score of 30-70) and high (score of 70-100) risk groupings were 8.67%, 24.10% and 74.10%, respectively. A time to event analysis revealed the higher risk groups readmitted to a hospital earlier than the lower risk groups. Six high-risk patient subgroup patterns were revealed through unsupervised clustering. Our model was successfully integrated into the statewide HIE to identify patient readmission risk upon admission and daily during hospitalization or for 30 days subsequently, providing daily risk score updates. CONCLUSIONS: The risk model was validated as an effective tool for predicting 30-day readmissions for patients across all payer, disease and demographic groups within the Maine HIE. Exposing the key clinical, demographic and utilization profiles driving each patient's risk of readmission score may be useful to providers in developing individualized post discharge care plans.

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BACKGROUND: In order to proactively manage congestive heart failure (CHF) patients, an effective CHF case finding algorithm is required to process both structured and unstructured electronic medical records (EMR) to allow complementary and cost-efficient identification of CHF patients. METHODS AND RESULTS: We set to identify CHF cases from both EMR codified and natural language processing (NLP) found cases. Using narrative clinical notes from all Maine Health Information Exchange (HIE) patients, the NLP case finding algorithm was retrospectively (July 1, 2012-June 30, 2013) developed with a random subset of HIE associated facilities, and blind-tested with the remaining facilities. The NLP based method was integrated into a live HIE population exploration system and validated prospectively (July 1, 2013-June 30, 2014). Total of 18,295 codified CHF patients were included in Maine HIE. Among the 253,803 subjects without CHF codings, our case finding algorithm prospectively identified 2411 uncodified CHF cases. The positive predictive value (PPV) is 0.914, and 70.1% of these 2411 cases were found to be with CHF histories in the clinical notes. CONCLUSIONS: A CHF case finding algorithm was developed, tested and prospectively validated. The successful integration of the CHF case findings algorithm into the Maine HIE live system is expected to improve the Maine CHF care.

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Celastrol is an active compound extracted from the root bark of Triptergium wilfordii Hook F., also known as ̔Thunder of God Vine̓. It is a well-known Chinese medicinal herb that was found to inhibit tumor cell growth and promote apoptosis in several tumor cell lines. However, research into its effects on osteosarcoma cell apoptosis is still extremely limited. The present study was undertaken to determine the effect of celastrol on viability and apoptosis of osteosarcoma cells and furthermore, to illuminate the molecular mechanism of celastrol-induced osteosarcoma cell apoptosis. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) colorimetric assay was used to evaluate the viability of the cells following treatment with celastrol. The effect of celastrol on the apoptotic rate of the cells was evaluated by flow cytometry using Annexin V-PE/7-AAD staining assay. Fluorescence microscopy was used to detect the morphological changes in the human osteosarcoma U-2OS cell lines. The expression of Bcl-2 family proteins, caspase-3, caspase-8, caspase-9, cytochrome c and PARP was measured by western blotting. We found that celastrol significantly inhibited the growth of osteosarcoma cells in a dose-dependent manner, particularly U-2OS cells. Furthermore, we observed that celastrol upregulated the expression of the pro-apoptotic proteins Bax and cytochrome c and altered the ratio of Bax/Bcl-2, and triggered the mitochondrial apoptotic pathway, resulting in caspase-3 and -9 activation and PARP cleavage. To conclude, the results indicate that celastrol inhibits the proliferation of human osteosarcoma cancer cells by inducing apoptosis via the mitochondrial-dependent pathway.

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To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably developed after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In our controlled rat model study, matched ENU- and saline-exposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150 days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. Future characterization of the critical transition state (P60) during the brain tumor progression may reveal the underlying pathophysiology to device novel therapeutics preventing tumor formation. More detailed method and information are accessible through our website at http://translationalmedicine.stanford.edu.

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BACKGROUND: An easily accessible real-time Web-based utility to assess patient risks of future emergency department (ED) visits can help the health care provider guide the allocation of resources to better manage higher-risk patient populations and thereby reduce unnecessary use of EDs. OBJECTIVE: Our main objective was to develop a Health Information Exchange-based, next 6-month ED risk surveillance system in the state of Maine. METHODS: Data on electronic medical record (EMR) encounters integrated by HealthInfoNet (HIN), Maine's Health Information Exchange, were used to develop the Web-based surveillance system for a population ED future 6-month risk prediction. To model, a retrospective cohort of 829,641 patients with comprehensive clinical histories from January 1 to December 31, 2012 was used for training and then tested with a prospective cohort of 875,979 patients from July 1, 2012, to June 30, 2013. RESULTS: The multivariate statistical analysis identified 101 variables predictive of future defined 6-month risk of ED visit: 4 age groups, history of 8 different encounter types, history of 17 primary and 8 secondary diagnoses, 8 specific chronic diseases, 28 laboratory test results, history of 3 radiographic tests, and history of 25 outpatient prescription medications. The c-statistics for the retrospective and prospective cohorts were 0.739 and 0.732 respectively. Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. Cluster analysis in both the retrospective and prospective analyses revealed discrete subpopulations of high-risk patients, grouped around multiple "anchoring" demographics and chronic conditions. With the Web-based population risk-monitoring enterprise dashboards, the effectiveness of the active case finding algorithm has been validated by clinicians and caregivers in Maine. CONCLUSIONS: The active case finding model and associated real-time Web-based app were designed to track the evolving nature of total population risk, in a longitudinal manner, for ED visits across all payers, all diseases, and all age groups. Therefore, providers can implement targeted care management strategies to the patient subgroups with similar patterns of clinical histories, driving the delivery of more efficient and effective health care interventions. To the best of our knowledge, this prospectively validated EMR-based, Web-based tool is the first one to allow real-time total population risk assessment for statewide ED visits.

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BACKGROUND: Necrotizing Enterocolitis (NEC) is a major source of neonatal morbidity and mortality. There is an ongoing need for a sensitive diagnostic instrument to discriminate NEC from neonatal sepsis. We hypothesized that magnetic nanopartile-based biosensor analysis of gut injury-associated biomarkers would provide such an instrument. STUDY DESIGN: We designed a magnetic multiplexed biosensor platform, allowing the parallel plasma analysis of C-reactive protein (CRP), matrix metalloproteinase-7 (MMp7), and epithelial cell adhesion molecule (EpCAM). Neonatal subjects with sepsis (n=5) or NEC (n=10) were compared to control (n=5) subjects to perform a proof of concept pilot study for the diagnosis of NEC using our ultra-sensitive biosensor platform. RESULTS: Our multiplexed NEC magnetic nanoparticle-based biosensor platform was robust, ultrasensitive (Limit of detection LOD: CRP 0.6 pg/ml; MMp7 20 pg/ml; and EpCAM 20 pg/ml), and displayed no cross-reactivity among analyte reporting regents. To gauge the diagnostic performance, bootstrapping procedure (500 runs) was applied: MMp7 and EpCAM collectively differentiated infants with NEC from control infants with ROC AUC of 0.96, and infants with NEC from those with sepsis with ROC AUC of 1.00. The 3-marker panel comprising of EpCAM, MMp7 and CRP had a corresponding ROC AUC of 0.956 and 0.975, respectively. CONCLUSION: The exploration of the multiplexed nano-biosensor platform shows promise to deliver an ultrasensitive instrument for the diagnosis of NEC in the clinical setting.

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BACKGROUND: Among patients who are discharged from the Emergency Department (ED), about 3% return within 30 days. Revisits can be related to the nature of the disease, medical errors, and/or inadequate diagnoses and treatment during their initial ED visit. Identification of high-risk patient population can help device new strategies for improved ED care with reduced ED utilization. METHODS AND FINDINGS: A decision tree based model with discriminant Electronic Medical Record (EMR) features was developed and validated, estimating patient ED 30 day revisit risk. A retrospective cohort of 293,461 ED encounters from HealthInfoNet (HIN), Maine's Health Information Exchange (HIE), between January 1, 2012 and December 31, 2012, was assembled with the associated patients' demographic information and one-year clinical histories before the discharge date as the inputs. To validate, a prospective cohort of 193,886 encounters between January 1, 2013 and June 30, 2013 was constructed. The c-statistics for the retrospective and prospective predictions were 0.710 and 0.704 respectively. Clinical resource utilization, including ED use, was analyzed as a function of the ED risk score. Cluster analysis of high-risk patients identified discrete sub-populations with distinctive demographic, clinical and resource utilization patterns. CONCLUSIONS: Our ED 30-day revisit model was prospectively validated on the Maine State HIN secure statewide data system. Future integration of our ED predictive analytics into the ED care work flow may lead to increased opportunities for targeted care intervention to reduce ED resource burden and overall healthcare expense, and improve outcomes.

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Molecular cloning is utilized in nearly every facet of biological and medical research. We have developed a method, termed Hot Fusion, to efficiently clone one or multiple DNA fragments into plasmid vectors without the use of ligase. The method is directional, produces seamless junctions and is not dependent on the availability of restriction sites for inserts. Fragments are assembled based on shared homology regions of 17-30 bp at the junctions, which greatly simplifies the construct design. Hot Fusion is carried out in a one-step, single tube reaction at 50 °C for one hour followed by cooling to room temperature. In addition to its utility for multi-fragment assembly Hot Fusion provides a highly efficient method for cloning DNA fragments containing inverted repeats for applications such as RNAi. The overall cloning efficiency is in the order of 90-95%.

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BACKGROUND: RNA interference (RNAi) has emerged as a powerful tool for the targeted knockout of genes for functional genomics, system biology studies and drug discovery applications. To meet the requirements for high throughput screening in plants we have developed a new method for the rapid assembly of inverted repeat-containing constructs for the in vivo production of dsRNAs. METHODOLOGY/PRINCIPAL FINDINGS: The procedure that we describe is based on tagging the sense and antisense fragments with unique single-stranded (ss) tails which are then assembled in a single tube Ligase Independent Cloning (LIC) reaction. Since the assembly reaction is based on the annealing of unique complementary single stranded tails which can only assemble in one orientation, greater than ninety percent of the resultant clones contain the desired insert. CONCLUSION/SIGNIFICANCE: Our single-tube reaction provides a highly efficient method for the assembly of inverted repeat constructs for gene suppression applications. The single tube assembly is directional, highly efficient and readily adapted for high throughput applications.

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As an increasing number of genes and open reading frames of unknown function are discovered, expression of the encoded proteins is critical toward establishing function. Accordingly, there is an increased need for highly efficient, high-fidelity methods for directional cloning. Among the available methods, site-specific recombination-based cloning techniques, which eliminate the use of restriction endonucleases and ligase, have been widely used for high-throughput (HTP) procedures. We have developed a recombination cloning method, which uses truncated recombination sites to clone PCR products directly into destination/expression vectors, thereby bypassing the requirement for first producing an entry clone. Cloning efficiencies in excess of 80% are obtained providing a highly efficient method for directional HTP cloning.

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