Migrating a Large Scale Legacy Application to SOA: Challenges and Lessons Learned

Abstract—This paper presents the findings of a case study of a large scale legacy to service-oriented architecture migration process in the payments domain of a Dutch bank. The paper presents the business drivers that initiated the migration, and describes a 4-phase migration process. For each phase, the paper details benefits of using the techniques, best practices that contribute to the success, and possible challenges that are faced during migration. Based on these observations, the findings are discussed as lessons learned, including the implications of using reverse engineering techniques to facilitate the migration process, adopting a pragmatic migration realization approach, emphasizing the organizational and business perspectives, and harvesting knowledge of the system throughout the system’s life cycle. I

An updated systematic review and meta-analysis of brain network organization in focal epilepsy: Looking back and forth

Abnormalities of the brain network organization in focal epilepsy have been extensively quantified. However, the extent and directionality of abnormalities are highly variable and subtype insensitive. We conducted meta-analyses to obtain a more accurate and epilepsy type-specific quantification of the interictal global brain network organization in focal epilepsy. By using random-effects models, we estimated differences in average clustering coefficient, average path length, and modularity between patients with focal epilepsy and controls, based on 45 studies with a total sample size of 1,468 patients and 1,021 controls. Structural networks had a significant lower level of integration in patients with epilepsy as compared to controls, with a standardized mean difference of -0.334 (95% confidence interval -0.631 to -0.038; p-value 0.027). Functional networks did not differ between patients and controls, except for the beta band clustering coefficient. Our meta-analyses show that differences in the brain network organization are not as well defined as individual studies often propose. We discuss potential pitfalls and suggestions to enhance the yield and clinical value of network studies

Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study.

BACKGROUND For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal. METHODS This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions. RESULTS Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44). CONCLUSIONS Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate

The importance of discriminative power rather than significance when evaluating potential clinical biomarkers in epilepsy research

OBJECTIVE: The quest for epilepsy biomarkers is on the rise. Variables with statistically significant group-level differences are often misinterpreted as biomarkers with sufficient discriminative power. This study aimed to demonstrate the relationship between significant group-level differences and a variable's power to discriminate between individuals. METHODS: We simulated normal-distributed datasets from hypothetical populations with varying sample sizes (25-800), effect sizes (Cohen's d: .25-2.50), and variability (standard deviation: 10-35) to assess the impact of these parameters on significance and discriminative power. The simulation data were illustrated by assessing the discriminative power of a potential real-case biomarker-the EEG beta band power-to diagnose generalized epilepsy, using data from 66 children with generalized epilepsy and 385 controls. Additionally, we evaluated recently reported epilepsy biomarkers by comparing their effect sizes to our simulation-derived effect size criterion. RESULTS: Group size affects significance but not discriminative power. Discriminative power is much more related to variability and effect size. Our real data example supported these simulation results by demonstrating that group-level significance does not translate, one to one, into discriminative power. Although we found a significant difference in the beta band power between children with and without epilepsy, the discriminative power was poor due to a small effect size. A Cohen's d of at least 1.25 is required to reach good discriminative power in univariable prediction modeling. Slightly over 60% of the biomarkers in our literature search met this criterion. SIGNIFICANCE: Rather than statistical significance of group-level differences, effect size should be used as an indicator of a variable's biomarker potential. The minimal required effects size for individual biomarkers-a Cohen's d of 1.25-is large. This calls for multivariable approaches, in which combining multiple variables with smaller effect sizes could increase the overall effect size and discriminative power

Antiseizure medication withdrawal risk estimation and recommendations: A survey of American Academy of Neurology and EpiCARE members

Objective Choosing candidates for antiseizure medication (ASM) withdrawal in well‐controlled epilepsy is challenging. We evaluated (a) the correlation between neurologists' seizure risk estimation (“clinician predictions”) vs calculated predictions, (b) how viewing calculated predictions influenced recommendations, and (c) barriers to using risk calculation.MethodsWe asked US and European neurologists to predict 2‐year seizure risk after ASM withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before vs after viewing calculated predictions, using generalized linear models. Results Three‐hundred and forty‐six neurologists responded. There was moderate correlation between clinician and calculated predictions (Spearman coefficient 0.42). Clinician predictions varied widely, for example, predictions ranged 5%‐100% for a 2‐year seizure‐free adult without epileptiform abnormalities. Mean clinician predictions exceeded calculated predictions for vignettes with epileptiform abnormalities (eg, childhood absence epilepsy: clinician 65%, 95% confidence interval [CI] 57%‐74%; calculated 46%) and surgical vignettes (eg, focal cortical dysplasia 6‐month seizure‐free mean clinician 56%, 95% CI 52%‐60%; calculated 28%). Clinicians overestimated the influence of epileptiform EEG findings on withdrawal risk (26%, 95% CI 24%‐28%) compared with calculators (14%, 95% 13%‐14%). Viewing calculated predictions slightly reduced willingness to withdraw (−0.8/10 change, 95% CI −1.0 to −0.7), particularly for vignettes without epileptiform abnormalities. The greatest barrier to calculator use was doubting its accuracy (44%). Significance Clinicians overestimated the influence of abnormal EEGs particularly for low‐risk patients and overestimated risk and the influence of seizure‐free duration for surgical patients, compared with calculators. These data may question widespread ordering of EEGs or time‐based seizure‐free thresholds for surgical patients. Viewing calculated predictions reduced willingness to withdraw particularly without epileptiform abnormalities

Mixture models for analysis of melting temperature data

<p>Abstract</p> <p>Background</p> <p>In addition to their use in detecting undesired real-time PCR products, melting temperatures are useful for detecting variations in the desired target sequences. Methodological improvements in recent years allow the generation of high-resolution melting-temperature (T_m) data. However, there is currently no convention on how to statistically analyze such high-resolution T_mdata.</p> <p>Results</p> <p>Mixture model analysis was applied to T_mdata. Models were selected based on Akaike's information criterion. Mixture model analysis correctly identified categories in T_mdata obtained for known plasmid targets. Using simulated data, we investigated the number of observations required for model construction. The precision of the reported mixing proportions from data fitted to a preconstructed model was also evaluated.</p> <p>Conclusion</p> <p>Mixture model analysis of T_mdata allows the minimum number of different sequences in a set of amplicons and their relative frequencies to be determined. This approach allows T_mdata to be analyzed, classified, and compared in an unbiased manner.</p

The human cytomegalovirus-encoded G protein- coupled receptor UL33 exhibits oncomodulatory properties

Herpesviruses can rewire cellular signaling in host cells by expressing viral G protein- coupled receptors (GPCRs). These viral receptors exhibit homology to human chemokine receptors, but some display constitutive activity and promiscuous G protein coupling. Human cytomegalovirus (HCMV) has been detected in multiple cancers, including glioblastoma, and its genome encodes four GPCRs. One of these receptors, US28, is expressed in glioblastoma and possesses constitutive activity and oncomodulatory properties. UL33, another HCMV-encoded GPCR, also displays constitutive signaling via Gαq, Gαi, and Gαs proteins. However, little is known about the nature and functional effects of UL33-driven signaling. Here, we assessed UL33's signaling repertoire and oncomodulatory potential. UL33 activated multiple proliferative, angiogenic, and inflammatory signaling pathways in HEK293T and U251 glioblastoma cells. Notably, upon infection, UL33 contributed to HCMV-mediated STAT3 activation. Moreover, UL33 increased spheroid growth in vitro and accelerated tumor growth in different in vivo tumor models, including an orthotopic glioblastoma xenograft model. UL33-mediated signaling was similar to that stimulated by US28; however, UL33-induced tumor growth was delayed. Additionally, the spatiotemporal expression of the two receptors only partially overlapped in HCMV-infected glioblastoma cells. In conclusion, our results unveil that UL33 has broad signaling capacity and provide mechanistic insight into its functional effects. UL33, like US28, exhibits oncomodulatory properties, elicited via constitutive activation of multiple signaling pathways. UL33 and US28 might contribute to HCMV's oncomodulatory effects through complementing and converging cellular signaling, and hence UL33 may represent a promising drug target in HCMV-associated malignancies

Comparison of two protective lung ventilatory regimes on oxygenation during one-lung ventilation: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>The efficacy of protective ventilation in acute lung injury has validated its use in the operating room for patients undergoing thoracic surgery with one-lung ventilation (OLV). The purpose of this study was to investigate the effects of two different modes of ventilation using low tidal volumes: pressure controlled ventilation (PCV) vs. volume controlled ventilation (VCV) on oxygenation and airway pressures during OLV.</p> <p>Methods</p> <p>We studied 41 patients scheduled for thoracoscopy surgery. After initial two-lung ventilation with VCV patients were randomly assigned to one of two groups. In one group OLV was started with VCV (tidal volume 6 mL/kg, PEEP 5) and after 30 minutes ventilation was switched to PCV (inspiratory pressure to provide a tidal volume of 6 mL/kg, PEEP 5) for the same time period. In the second group, ventilation modes were performed in reverse order. Airway pressures and blood gases were obtained at the end of each ventilatory mode.</p> <p>Results</p> <p>PaO₂, PaCO₂and alveolar-arterial oxygen difference did not differ between PCV and VCV. Peak airway pressure was significantly lower in PCV compared with VCV (19.9 ± 3.8 cmH₂O vs 23.1 ± 4.3 cmH₂O; p < 0.001) without any significant differences in mean and plateau pressures.</p> <p>Conclusions</p> <p>In patients with good preoperative pulmonary function undergoing thoracoscopy surgery, the use of a protective lung ventilation strategy with VCV or PCV does not affect the oxygenation. PCV was associated with lower peak airway pressures.</p

Clinical outcomes in typhoid fever: adverse impact of infection with nalidixic acid-resistant Salmonella typhi

BACKGROUND: Widespread use of fluoroquinolones has resulted in emergence of Salmonella typhi strains with decreased susceptibility to fluoroquinolones. These strains are identifiable by their nalidixic acid-resistance. We studied the impact of infection with nalidixic acid-resistant S. typhi (NARST) on clinical outcomes in patients with bacteriologically-confirmed typhoid fever. METHODS: Clinical and laboratory features, fever clearance time and complications were prospectively studied in patients with blood culture-proven typhoid fever, treated at a tertiary care hospital in north India, during the period from November 2001 to October 2003. Susceptibility to amoxycillin, co-trimoxazole, chloramphenicol, ciprofloxacin and ceftriaxone were tested by disc diffusion method. Minimum inhibitory concentrations (MIC) of ciprofloxacin and ceftriaxone were determined by E-test method. RESULTS: During a two-year period, 60 patients (age [mean ± SD]: 15 ± 9 years; males: 40 [67%]) were studied. All isolates were sensitive to ciprofloxacin and ceftriaxone by disc diffusion and MIC breakpoints. However, 11 patients had clinical failure of fluoroquinolone therapy. Infections with NARST isolates (47 [78%]) were significantly associated with longer duration of fever at presentation (median [IQR] 10 [7-15] vs. 4 [3-6] days; P = 0.000), higher frequency of hepatomegaly (57% vs. 15%; P = 0.021), higher levels of aspartate aminotransferase (121 [66–235] vs. 73 [44–119] IU/L; P = 0.033), and increased MIC of ciprofloxacin (0.37 ± 0.21 vs. 0.17 ± 0.14 μg/mL; P = 0.005), as compared to infections with nalidixic acid-susceptible isolates. All 11 patients with complications were infected with NARST isolates. Total duration of illness was significantly longer in patients who developed complications than in patients who did not (22 [14.8–32] vs. 12 [9.3–20.3] days; P = 0.011). Duration of prior antibiotic intake had a strong positive correlation with the duration of fever at presentation (r = 0.61; P = 0.000) as well as the total duration of illness (r = 0.53; P = 0.000). CONCLUSION: Typhoid fever caused by NARST infection is associated with poor clinical outcomes, probably due to delay in initiating appropriate antibiotic therapy. Fluoroquinolone breakpoints for S. typhi need to be redefined and fluoroquinolones should no longer be used as first-line therapy, if the prevalence of NARST is high