A Theology of Ministerial Practice

Competing agendas and changing culture create a need for churches to consciously determine why they will do what they do the way they do. This project develops four doctrinal bases for a theology of ministerial practice. It summarizes literature on philosophy of ministry. Research in five Lutheran churches identifies gaps in the way people view ministry. Chapter four provides a comprehensive rationale and definition for a theology of ministerial practice. One church\u27s experience demonstrates the value of thinking through and developing guiding principles that apply a church\u27s theology to its culture in shaping ministerial practice

A Valuable Tool for Risk Stratification in Septic Patients Admitted to ICU

The lactate/albumin ratio has been reported to be associated with mortality in pediatric patients with sepsis. We aimed to evaluate the lactate/albumin ratio for its prognostic relevance in a larger collective of critically ill (adult) patients admitted to an intensive care unit (ICU). A total of 348 medical patients admitted to a German ICU for sepsis between 2004 and 2009 were included. Follow-up of patients was performed retrospectively between May 2013 and November 2013. The association of the lactate/albumin ratio (cut-off 0.15) and both in-hospital and post-discharge mortality was investigated. An optimal cut-off was calculated by means of Youden’s index. The lactate/albumin ratio was elevated in non-survivors (p < 0.001). Patients with an increased lactate/albumin ratio were of similar age, but clinically in a poorer condition and had more pronounced laboratory signs of multi-organ failure. An increased lactate/albumin ratio was associated with adverse in-hospital mortality. An optimal cut-off of 0.15 was calculated and was associated with adverse long-term outcome even after correction for APACHE2 and SAPS2. We matched 99 patients with a lactate/albumin ratio >0.15 to case-controls with a lactate/albumin ratio <0.15 corrected for APACHE2 scores: The group with a lactate/albumin ratio >0.15 evidenced adverse in-hospital outcome in a paired analysis with a difference of 27% (95%CI 10–43%; p < 0.01). Regarding long- term mortality, again, patients in the group with a lactate/albumin ratio >0.15 showed adverse outcomes (p < 0.001). An increased lactate/albumin ratio was significantly associated with an adverse outcome in critically ill patients admitted to an ICU, even after correction for confounders. The lactate/albumin ratio might constitute an independent, readily available, and important parameter for risk stratification in the critically ill. View Full- Tex

Pharmacosimulation of delays and interruptions during administration of tirofiban: a systematic comparison between EU and US dosage regimens.

Tirofiban is a glycoproteine (GP) IIb/IIIa receptor antagonist, which inhibits platelet-platelet aggregation and is a potential adjunctive antithrombotic treatment in patients with acute coronary syndromes (ACS) or high-risk percutaneous coronary interventions (PCI). It is administered intravenously as a bolus followed by continuous infusion. However, the dosage recommendations in the United States (US) and European Union (EU) differ considerably. Furthermore, in routine clinical practice, deviations from the recommendations may occur. The objective of the present study was to investigate the impact of different alterations on tirofiban plasma concentrations in US and EU administration regimens and to give suggestions for delay management in clinical practice. We therefore mathematically simulated the effects of different bolus-infusion delays and infusion interruptions in different scenarios according to the renal function. Here, we provide a systematic assessment of concentration patterns of tirofiban in the US versus EU dosage regimens. We show that differences between the two regimens have important effects on plasma drug levels. Furthermore, we demonstrate that deviations from the proper administration mode affect the concentration of tirofiban. Additionally, we calculated the optimal dosage of a second bolus to rapidly restore the initial concentration without causing overdosage. In conclusion, differences in tirofiban dosing regimens between the U.S and EU and potential infusion interruptions have important effects on drug levels that may impact on degrees of platelet inhibition and thus antithrombotic effects. Thus, the findings of our modelling studies may help to explain differences in clinical outcomes observed in previous clinical trials on tirofiban

Myelin-associated Glycoprotein Interacts with Neurons via a Sialic Acid Binding Site at ARG118 and a Distinct Neurite Inhibition Site

Inhibitory components in myelin are largely responsible for the lack of regeneration in the mammalian CNS. Myelin-associated glycoprotein (MAG), a sialic acid binding protein and a component of myelin, is a potent inhibitor of neurite outgrowth from a variety of neurons both in vitro and in vivo. Here, we show that MAG's sialic acid binding site is distinct from its neurite inhibitory activity. Alone, sialic acid–dependent binding of MAG to neurons is insufficient to effect inhibition of axonal growth. Thus, while soluble MAG-Fc (MAG extracellular domain fused to Fc), a truncated form of MAG-Fc missing Ig-domains 4 and 5, MAG(d1-3)-Fc, and another sialic acid binding protein, sialoadhesin, each bind to neurons in a sialic acid– dependent manner, only full-length MAG-Fc inhibits neurite outgrowth. These results suggest that a second site must exist on MAG which elicits this response. Consistent with this model, mutation of arginine 118 (R118) in MAG to either alanine or aspartate abolishes its sialic acid–dependent binding. However, when expressed at the surface of either CHO or Schwann cells, R118-mutated MAG retains the ability to inhibit axonal outgrowth. Hence, MAG has two recognition sites for neurons, the sialic acid binding site at R118 and a distinct inhibition site which is absent from the first three Ig domains

Utility of spherical human liver microtissues for prediction of clinical drug-induced liver injury.

Drug-induced liver injury (DILI) continues to be a major source of clinical attrition, precautionary warnings, and post-market withdrawal of drugs. Accordingly, there is a need for more predictive tools to assess hepatotoxicity risk in drug discovery. Three-dimensional (3D) spheroid hepatic cultures have emerged as promising tools to assess mechanisms of hepatotoxicity, as they demonstrate enhanced liver phenotype, metabolic activity, and stability in culture not attainable with conventional two-dimensional hepatic models. Increased sensitivity of these models to drug-induced cytotoxicity has been demonstrated with relatively small panels of hepatotoxicants. However, a comprehensive evaluation of these models is lacking. Here, the predictive value of 3D human liver microtissues (hLiMT) to identify known hepatotoxicants using a panel of 110 drugs with and without clinical DILI has been assessed in comparison to plated two-dimensional primary human hepatocytes (PHH). Compounds were treated long-term (14 days) in hLiMT and acutely (2 days) in PHH to assess drug-induced cytotoxicity over an 8-point concentration range to generate IC50 values. Regardless of comparing IC50 values or exposure-corrected margin of safety values, hLiMT demonstrated increased sensitivity in identifying known hepatotoxicants than PHH, while specificity was consistent across both assays. In addition, hLiMT out performed PHH in correctly classifying hepatotoxicants from different pharmacological classes of molecules. The hLiMT demonstrated sufficient capability to warrant exploratory liver injury biomarker investigation (miR-122, HMGB1, α-GST) in the cell-culture media. Taken together, this study represents the most comprehensive evaluation of 3D spheroid hepatic cultures up to now and supports their utility for hepatotoxicity risk assessment in drug discovery

The M/GP5 Glycoprotein Complex of Porcine Reproductive and Respiratory Syndrome Virus Binds the Sialoadhesin Receptor in a Sialic Acid-Dependent Manner

The porcine reproductive and respiratory syndrome virus (PRRSV) is a major threat to swine health worldwide and is considered the most significant viral disease in the swine industry today. In past years, studies on the entry of the virus into its host cell have led to the identification of a number of essential virus receptors and entry mediators. However, viral counterparts for these molecules have remained elusive and this has made rational development of new generation vaccines impossible. The main objective of this study was to identify the viral counterparts for sialoadhesin, a crucial PRRSV receptor on macrophages. For this purpose, a soluble form of sialoadhesin was constructed and validated. The soluble sialoadhesin could bind PRRSV in a sialic acid-dependent manner and could neutralize PRRSV infection of macrophages, thereby confirming the role of sialoadhesin as an essential PRRSV receptor on macrophages. Although sialic acids are present on the GP3, GP4 and GP5 envelope glycoproteins, only the M/GP5 glycoprotein complex of PRRSV was identified as a ligand for sialoadhesin. The interaction was found to be dependent on the sialic acid binding capacity of sialoadhesin and on the presence of sialic acids on GP5. These findings not only contribute to a better understanding of PRRSV biology, but the knowledge and tools generated in this study also hold the key to the development of a new generation of PRRSV vaccines

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery