The simulation experiment description markup language (SED-ML): language specification for level 1 version 5.

Modern biological research is increasingly informed by computational simulation experiments, which necessitate the development of methods for annotating, archiving, sharing, and reproducing the conducted experiments. These simulations increasingly require extensive collaboration among modelers, experimentalists, and engineers. The Minimum Information About a Simulation Experiment (MIASE) guidelines outline the information needed to share simulation experiments. SED-ML is a computer-readable format for the information outlined by MIASE, created as a community project and supported by many investigators and software tools. Level 1 Version 5 of SED-ML expands the ability of modelers to define simulations in SED-ML using the Kinetic Simulation Algorithm Onotoloy (KiSAO). While it was possible in Version 4 to define a simulation entirely using KiSAO, Version 5 now allows users to define tasks, model changes, ranges, and outputs using the ontology as well. SED-ML is supported by a growing ecosystem of investigators, model languages, and software tools, including various languages for constraint-based, kinetic, qualitative, rule-based, and spatial models, and many simulation tools, visual editors, model repositories, and validators. Additional information about SED-ML is available at https://sed-ml.org/.

N-cadherin: A diagnostic marker to help discriminate primary liver carcinomas from extrahepatic carcinomas.

Distinguishing primary liver cancer (PLC), namely hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), from liver metastases is of crucial clinical importance. Histopathology remains the gold standard, but differential diagnosis may be challenging. While absent in most epithelial, the expression of the adherens junction glycoprotein N-cadherin is commonly restricted to neural and mesenchymal cells, or carcinoma cells that undergo the phenomenon of epithelial-to-mesenchymal transition (EMT). However, we recently established N- and E-cadherin expression as hallmarks of normal hepatocytes and cholangiocytes, which are also preserved in HCC and iCCA. Therefore, we hypothesized that E- and/or N-cadherin may distinguish between carcinoma derived from the liver vs carcinoma of other origins. We comprehensively evaluated E- and N-cadherin in 3359 different tumors in a multicenter study using immunohistochemistry and compared our results with previously published 882 cases of PLC, including 570 HCC and 312 iCCA. Most carcinomas showed strong positivity for E-cadherin. Strong N-cadherin positivity was present in HCC and iCCA. However, except for clear cell renal cell carcinoma (23.6% of cases) and thyroid cancer (29.2%), N-cadherin was only in some instances faintly expressed in adenocarcinomas of the gastrointestinal tract (0%-0.5%), lung (7.1%), pancreas (3.9%), gynecological organs (0%-7.4%), breast (2.2%) as well as in urothelial (9.4%) and squamous cell carcinoma (0%-5.6%). As expected, N-cadherin was detected in neuroendocrine tumors (25%-75%), malignant melanoma (46.2%) and malignant mesothelioma (41%). In conclusion, N-cadherin is a useful marker for the distinction of PLC vs liver metastases of extrahepatic carcinomas (P < .01).

Persister cell phenotypes contribute to poor patient outcomes after neoadjuvant chemotherapy in PDAC.

Neoadjuvant chemotherapy can improve the survival of individuals with borderline and unresectable pancreatic ductal adenocarcinoma; however, heterogeneous responses to chemotherapy remain a significant clinical challenge. Here, we performed RNA sequencing (n = 97) and multiplexed immunofluorescence (n = 122) on chemo-naive and postchemotherapy (post-CTX) resected patient samples (chemoradiotherapy excluded) to define the impact of neoadjuvant chemotherapy. Transcriptome analysis combined with high-resolution mapping of whole-tissue sections identified GATA6 (classical), KRT17 (basal-like) and cytochrome P450 3A (CYP3A) coexpressing cells that were preferentially enriched in post-CTX resected samples. The persistence of GATA6hi and KRT17hi cells post-CTX was significantly associated with poor survival after mFOLFIRINOX (mFFX), but not gemcitabine (GEM), treatment. Analysis of organoid models derived from chemo-naive and post-CTX samples demonstrated that CYP3A expression is a predictor of chemotherapy response and that CYP3A-expressing drug detoxification pathways can metabolize the prodrug irinotecan, a constituent of mFFX. These findings identify CYP3A-expressing drug-tolerant cell phenotypes in residual disease that may ultimately inform adjuvant treatment selection.

The pH-dependent lactose metabolism of Lactobacillus delbrueckii subsp. bulgaricus: An integrative view through a mechanistic computational model.

The fermentation process of milk to yoghurt using Lactobacillus delbrueckii subsp. bulgaricus in co-culture with Streptococcus thermophilus is hallmarked by the breakdown of lactose to organic acids such as lactate. This leads to a substantial decrease in pH - both in the medium, as well as cytosolic. The latter impairs metabolic activities due to the pH-dependence of enzymes, which compromises microbial growth. To quantitatively elucidate the impact of the acidification on metabolism of L. bulgaricus in an integrated way, we have developed a proton-dependent computational model of lactose metabolism and casein degradation based on experimental data. The model accounts for the influence of pH on enzyme activities as well as cellular growth and proliferation of the bacterial population. We used a machine learning approach to quantify the cell volume throughout fermentation. Simulation results show a decrease in metabolic flux with acidification of the cytosol. Additionally, the validated model predicts a similar metabolic behaviour within a wide range of non-limiting substrate concentrations. This computational model provides a deeper understanding of the intricate relationships between metabolic activity and acidification and paves the way for further optimization of yoghurt production under industrial settings.

Farnesoid X receptor activation inhibits pancreatic carcinogenesis.

Farnesoid X receptor (FXR), a member of the nuclear receptor superfamily that controls bile acid (BA) homeostasis, has also been proposed as a tumor suppressor for breast and liver cancer. However, its role in pancreatic ductal adenocarcinoma (PDAC) tumorigenesis remains controversial. We recently found that FXR attenuates acinar cell autophagy in chronic pancreatitis resulting in reduced autophagy and promotion of pancreatic carcinogenesis. Feeding Kras-p48-Cre (KC) mice with the BA chenodeoxycholic acid (CDCA), an FXR agonist, attenuated pancreatic intraepithelial neoplasia (PanIN) progression, reduced cell proliferation, neoplastic cells and autophagic activity, and increased acinar cells, elevated pro-inflammatory cytokines and chemokines, with a compensatory increase in the anti-inflammatory response. Surprisingly, FXR-deficient KC mice did not show any response to CDCA, suggesting that CDCA attenuates PanIN progression and decelerate tumorigenesis in KC mice through activating pancreatic FXR. FXR is activated in pancreatic cancer cell lines in response to CDCA in vitro. FXR levels were highly increased in adjuvant and neoadjuvant PDAC tissue compared to healthy pancreatic tissue, indicating that FXR is expressed and potentially activated in human PDAC. These results suggest that BA exposure activates inflammation and suppresses autophagy in KC mice, resulting in reduced PanIN lesion progression. These data suggest that activation of pancreatic FXR has a protective role by reducing the growth of pre-cancerous PDAC lesions in response to CDCA and possibly other FXR agonists.

A fast and sensitive high-throughput assay to assess polysorbate-degrading hydrolytic activity in biopharmaceuticals.

Hydrolysis of polysorbate in biopharmaceutical products has been ascribed to the enzymatic activity from trace levels of residual host cell proteins. In recent years, significant efforts to identify the causative enzymes typically used elaborate, material-intensive and time-consuming approaches. Therefore, the lack of fast and sensitive assays to monitor their activity remains a major bottleneck for supporting process optimization and troubleshooting activities where time and sample throughput are crucial constraints. To address this bottleneck, we developed a novel Electrochemiluminescence-based Polysorbase Activity (EPA) assay to measure hydrolytic activities in biotherapeutics throughout the drug substance manufacturing process. By combining the favorable features of an in-house designed surrogate substrate with a well-established detection platform, the method yields fast (∼36 h turnaround time) and highly sensitive readouts compatible with high-throughput testing. The assay capability for detecting substrate conversion in a precise and reliable manner was demonstrated by extensive qualification studies and by employing a number of recombinant hydrolases associated with polysorbate hydrolysis. In addition, high assay sensitivity and wide applicability were confirmed for in-process pool samples of three different antibody products by performing a head-to-head comparison between this method and an established liquid chromatography - mass spectrometry based assay for the quantification of free fatty acids. Overall, our results suggest that this new approach is well-suited to resolve differences in hydrolytic activity through all stages of purification.

EnzymeML: seamless data flow and modeling of enzymatic data.

The design of biocatalytic reaction systems is highly complex owing to the dependency of the estimated kinetic parameters on the enzyme, the reaction conditions, and the modeling method. Consequently, reproducibility of enzymatic experiments and reusability of enzymatic data are challenging. We developed the XML-based markup language EnzymeML to enable storage and exchange of enzymatic data such as reaction conditions, the time course of the substrate and the product, kinetic parameters and the kinetic model, thus making enzymatic data findable, accessible, interoperable and reusable (FAIR). The feasibility and usefulness of the EnzymeML toolbox is demonstrated in six scenarios, for which data and metadata of different enzymatic reactions are collected and analyzed. EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling of enzyme kinetics, publication platforms and enzymatic reaction databases. EnzymeML is open and transparent, and invites the community to contribute. All documents and codes are freely available at https://enzymeml.org .

A Stepped Health Services Intervention to Improve Care for Mental and Neurological Diseases: Protocol for a Prospective Cohort Trial.

BACKGROUND: Mental and neurological disorders cause a large proportion of morbidity burden and require adequate health care structures. However, deficits in the German health care system like long waiting times for access to specialized care and a lack of coordination between health care providers lead to suboptimal quality of care and elevated health care costs. OBJECTIVE: To overcome these deficits, we implement and evaluate a unique stepped and coordinated model of care (the Neurologisch-psychiatrische und psychotherapeutische Versorgung [NPPV] program) for patients with mental and neurological diseases. METHODS: Patients included in the program receive an appropriate treatment according to medical needs in a multiprofessional network of ambulatory health care providers. The therapy is coordinated by a managing physician and complemented by additional therapy modules, such as group therapy, internet-based cognitive behavioral therapy, and a case management. Statutory health insurance (SHI) routine data and data from a longitudinal patient survey will be used to compare the program with regular care and evaluate SHI expenditures and patient-related outcomes. A health care provider survey will evaluate the quality of structure and processes and provider satisfaction. Finally, an analysis of ambulatory claims data and drug prescription data will be used to evaluate if health care providers follow a needs-led approach in therapy. Ethics approval for this trial was obtained from the ethics committee of the chamber of physicians in North Rhine (September 13, 2017, reference No. 2017287). RESULTS: Patient enrollment of NPPV ended in September 2021. Data analysis has been completed in 2022. The results of this study will be disseminated through scientific publications, academic conferences, and a publicly available report to the German Federal Joint Committee, which is expected to be available in the first half of 2023. CONCLUSIONS: The NPPV program is the first intervention to implement a stepped model of care for both mental and neurological diseases in Germany. The analysis of several data sources and a large sample size (more than 14,000 patients) enable a comprehensive evaluation of the NPPV program. TRIAL REGISTRATION: German Clinical Trials Register DRKS00022754; https://tinyurl.com/3mx9pz5z. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37569.

Oncological Outcome of Conversion Surgery After Preoperative Chemotherapy for Metastatic Pancreatic Cancer.

OBJECTIVE: To investigate the outcome of conversion surgery in patients with metastatic pancreatic cancer (mPDAC) and to identify patients who may benefit from this approach. BACKGROUND: The role of conversion surgery in patients with mPDAC and exceptional response to chemotherapy remains unclear. METHODS: Patients who underwent surgical exploration for mPDAC following chemotherapy between 2006 and 2019 were included. Data on demographics, oncologic treatment, pathology, and postoperative outcomes were analyzed. Univariate and multivariate survival analyses were performed. RESULTS: Some 173 patients received preoperative chemotherapy and underwent surgical exploration. Ninety-three patients underwent resection of the primary tumor and metastatic sites, 80 patients underwent exploration only. In the resection subgroup, 45 patients had complete pathological response of metastases (ypM0) and 48 patients had residual metastases (ypM1). ypM0 status was associated with lower carcinoembryonic antigen levels and lower ypN stage. Overall survival after resection was 25.5 months in ypM0, 10.7 months in ypM1, and 8.1 months in patients without resection ( P <0.001). Additional adjuvant chemotherapy was significantly associated with prolonged survival in resected patients (29.0 vs 14.8 mo, P =0.024) as well as in ypM0 (29.1 vs 19.2 mo, P =0.047). Multivariable analysis identified conversion surgery, carbohydrate antigen 19-9 (CA19-9) and time of resection as independent prognostic markers for the entire cohort. CA19-9, ypM0 and adjuvant treatment were independent predictors of survival in the resection subgroup. CONCLUSION: In patients with mPDAC and ypM0 status after chemotherapy, surgical resection is associated with encouraging survival. mPDAC patients with exceptional response to chemotherapy may be candidates for exploration and for resection in ypM0. Adjuvant chemotherapy may provide an additional survival advantage.

Presence of low-grade IPMN at the pancreatic transection margin does not have prognostic significance after resection of IPMN-associated pancreatic adenocarcinoma.

INTRODUCTION: Resection margin status is a well-established prognosticator in pancreatic cancer. The prognostic impact of IPMN dysplasia at the pancreatic transection margin in IPMN-associated carcinoma (IPMN-Ca) remains unclear, hence institutional practices on additional resections vary. METHODS: Patients undergoing partial pancreatectomy or attempted partial pancreatectomy converted to total pancreatectomy for IPMN-Ca between 04/2002 and 12/2018 were identified. Final pathology of the definitive pancreatic transection margin was identified. The association between the presence of IPMN dysplasia at the margin and overall survival (OS) was assessed. RESULTS: Of 302 patients with IPMN-Ca, 181 (59.9%) patients received partial pancreatoduodenectomy, 61 (20.2%) distal pancreatectomy, and 60 (19.9%) were converted to total pancreatectomy. Median OS was 98.6 months in R0 (≥1 mm), 39.3 months in R1 (<1 mm), and 22.0 months in R1(direct) resected patients, respectively (p < 0.0001). No IPMN dysplasia at the definitive margin was present in 103 (34.1%), low-grade in 131 (43.4%), and high-grade/R1 in 8 (2.6%) patients. Low-grade dysplasia or total pancreatectomy were not associated with shorter OS compared to dysplasia-free margin across the entire cohort. Sensitivity analyses confirmed a lack of prognostic relevance of low-grade IPMN dysplasia at the pancreatic margin in R0 resected IPMN-Ca and in R0 resected UICC stage IA/IB IPMN-Ca. CONCLUSIONS: Low-grade IPMN at the transection margin is not associated with shorter overall survival after partial pancreatectomy for IPMN-Ca. Additional resections for low-grade dysplasia, up to total pancreatectomy do not result in a survival benefit and should be omitted. Due to limited sample size, high-grade dysplasia could not be analyzed.

A histopathological study of artery wall involvement in pancreatic cancer surgery.

PURPOSE: This study aims to study the depth of artery wall tumour invasion in patients undergoing surgery for pancreatic ductal adenocarcinoma. METHODS: Specimens from 47 pancreatic cancer patients with major arterial (splenic, SA; celiac, CA; common hepatic, CHA) invasion were examined: 45 left (distal) pancreatectomies, including 11 celiac artery resections, and two total pancreatectomies. Dissection of tumour-invaded arteries in 25 fresh specimens was attempted ex vivo using the sub-adventitial dissection technique (SDT). Tumour invasion of 66 arteries was graded using the tumour-free distance (TFD) from the external elastic lamina (EEL): 0 = no arterial invasion; I = TFD ≥ 1 mm; II = TFD < 1 mm; and grade III = EEL invasion. RESULTS: AJCC TNM staging was IA = 1 (2%), IB = 4 (9%), IIA = 5 (11%), IIB = 17(36%) and III = 20 (43%). Grade III tumour invasion was found in 17/47(36%) SAs, in 5/11 (45%) CAs and in 1/8 (13%) CHAs (p = 0.318). Attempted ex vivo SDT undertaken in 33 arteries from 25 specimens was complete in 16 and incomplete in 17 arteries. The median (IQR) TFD was 0.97 (0.11-2.54) mm in dissected and 0.14 (0.10, 0.14) mm in non-dissected SAs (p = 0.034). EEL tumour invasion occurred in 0/12 (0%) dissected compared to 7/13 (54%) non-dissected SAs (p = 0.005). Grades 0, I, II and III invasion were found in four (33%), two (17%) and six (50%), respectively, of 12 dissected SAs and grades II and III in six 6 (46%) and seven (54%), respectively, of 13 non-dissected SAs (p = 0.002). CONCLUSIONS: The grading system described may form the basis for classification to further develop arterial dissection techniques for pancreatic cancer.

BioSimulators: a central registry of simulation engines and services for recommending specific tools.

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations.

The link between menin and pleiotrophin in the tumor biology of pancreatic neuroendocrine neoplasms.

MEN1, which encodes menin protein, is the most frequently mutated gene in pancreatic neuroendocrine neoplasms (pNEN). Pleiotrophin (PTN) has been reported as a downstream factor of menin that promotes metastasis in different tumor entities. In this study, the effect of menin and its link to PTN were assessed using features of pNEN cells and the outcome of patients with pNEN. The expression levels of menin and PTN in tissues from patients with pNEN were examined using qRT-PCR and western blot and compared with their metastasis status. Functional assays, including transwell migration/invasion and scratch wound-healing assays, were performed on specifically designed CRISPR/Cas9-mediated MEN1-knockout (MEN1-KO) pNEN cell lines (BON1MEN1-KO and QGP1MEN1-KO ) to study the metastasis of pNEN. Among 30 patients with menin-negative pNEN, 21 revealed a strong protein expression of PTN. This combination was associated with metastasis and shorter disease-free survival. Accordingly, in BON1MEN1-KO and QGP1MEN1-KO cells, PTN protein expression was positively associated with enhanced cell migration and invasion, which could be reversed using PTN silencing. PTN is a predicting factor of metastatic behavior of menin-deficient-pNEN. In vitro, menin is able to both promote and suppress the metastasis of pNEN by regulating PTN expression depending on the tumoral origin of pNEN cells.

Inspecting the Solution Space of Genome-Scale Metabolic Models.

Genome-scale metabolic models are frequently used in computational biology. They offer an integrative view on the metabolic network of an organism without the need to know kinetic information in detail. However, the huge solution space which comes with the analysis of genome-scale models by using, e.g., Flux Balance Analysis (FBA) poses a problem, since it is hard to thoroughly investigate and often only an arbitrarily selected individual flux distribution is discussed as an outcome of FBA. Here, we introduce a new approach to inspect the solution space and we compare it with other approaches, namely Flux Variability Analysis (FVA) and CoPE-FBA, using several different genome-scale models of lactic acid bacteria. We examine the extent to which different types of experimental data limit the solution space and how the robustness of the system increases as a result. We find that our new approach to inspect the solution space is a good complementary method that offers additional insights into the variance of biological phenotypes and can help to prevent wrong conclusions in the analysis of FBA results.

Actual Five-year Survival After Upfront Resection for Pancreatic Ductal Adenocarcinoma: Who Beats the Odds?

OBJECTIVE: To determine actual five-year survival (5YS) rates associated with a strategy of upfront surgery and adjuvant therapy in pancreatic ductal adenocarcinoma (PDAC). BACKGROUND: The rate of actual 5YS in PDAC remains controversial. Available data is restricted to cohorts acquired over several decades and series of resection after patient selection by neoadjuvant therapy. METHODS: All patients undergoing upfront resection for resectable and borderline-resectable PDAC from 10/2001 to 12/2011 were identified from a prospective database. Actual overall survival was assessed after a follow-up of at least 5 years. Uni- and multivariable logistic regression analyses were performed. RESULTS: Median survival of 937 patients was 22.1 months. The actual 5YS rate was 17.0% (n = 159) including 89 (9.5%) patients without evidence of disease >5 years after resection. 5YS rates in patients with or without adjuvanttherapy were 18.8% vs. 12.2%, respectively. Tumorgrading, number of positive lymph nodes, a context of intraductal papillary mucinous neoplasia, and vascular resections were independently associated with 5YS. Patient-related parameters and CA 19-9 levels were associated with observed survival up to 3 years, but lost relevance thereafter. The extent of lymph node involvement was the strongest predictor of 5YS. Patients with pN0R0 had a 5YS rate of 38.2%. in patients with exclusively favorable factors the observed 5YS rate was above 50%. CONCLUSIONS: This is the largest series of long-term survivors with histologically confirmed PDAC. With upfront resection and adjuvant therapy an actual overall 5YS rate of 18.8% can be expected. in favorable subgroups actual 5YS is above 50%.

Refined prognostic staging for resected pancreatic cancer by modified stage grouping and addition of tumour grade.

BACKGROUND: With changes in T and N categories the 8th edition of the AJCC/UICC TNM staging system for pancreatic cancer resulted in improved prognostic staging, but inconsistencies were observed with specific stage groups. Tumour grading remains disregarded in prognostic staging. We aimed to validate the current staging system and to investigate the possibility of further optimization by integration of grading. METHODS: 1946 patients undergoing upfront surgical resection for pancreatic adenocarcinoma from 10/2001 to 12/2015 were identified from a prospective institutional database. Survival analyses based on the 8th UICC TNM edition were performed and rare TNM subgroups were reallocated based on survival. The impact of tumour grade on stage-specific survival was assessed and a TNMG staging system was developed. RESULTS: The 8th UICC staging system accurately stratified prognosis except for comparable survival in stages IB (pT2N0M0) and IIA (pT3N0M0). Regrouping of pT3N0M0 and pT1N1M0 to IB and of pT1N2M0 to II resulted in a modified staging system with higher consistency. High tumour grade (G3&G4 vs G1&G2) was associated with a significantly shorter survival in all new stage groups except for stage IV modified UICC. A TNMG-based prognostic stage grouping in which high tumour grade results in grouping with tumours of the next higher pTNM-stage resulted in improvement of prognostication in non-metastatic pancreatic cancer. CONCLUSIONS: The 8th edition of the UICC TNM staging system leaves room for improvement. A TNMG staging system with adjustments in group-allocation of specific rarely occurring pTNM subgroups and integration of tumour grade results in improved prognostic stratification.

IPMN-associated pancreatic cancer: Survival, prognostic staging and impact of adjuvant chemotherapy.

BACKGROUND: Intraductal papillary mucinous neoplasm (IPMN)-associated carcinoma is a subtype of pancreatic cancer for which prognostic factors, the validity of the AJCC/UICC staging system and the role of adjuvant chemotherapy remain unknown. MATERIALS AND METHODS: Clinicopathological, treatment and follow-up data of patients with IPMN-associated carcinoma undergoing resection between 2002 and 2018 were analyzed. Uni- and multivariable survival analyses were performed to identify prognostic factors. RESULTS: Of 424 patients undergoing resection for IPMN-associated carcinoma, 77% patients had pancreatic ductal adenocarcinoma (IPMN-PDAC) and 23% had colloid carcinoma (IPMN-CC). Compared to IPMN-CC, IPMN-PDAC was diagnosed at more advanced tumor stages, more frequently involved lymph nodes, more frequently showed poor differentiation and were associated with higher rates of R1 resections. Resected IPMN-PDAC showed markedly shorter median overall survival than IPMN-CC (26.7 months vs. 91.3 months). The current AJCC/UICC staging system was validated for IPMN-associated carcinoma and for both of its subtypes. In multivariable analysis age ≥70 years, diabetes mellitus, high levels of Ca 19-9, IPMN-PDAC subtype, G3 tumors and higher AJCC/UICC stage were independently associated with shorter survival. Adjuvant therapy was not associated with improved survival in IPMN-associated carcinoma. Overall survival was comparable in patients receiving vs. not receiving adjuvant therapy. CONCLUSIONS: Survival after resection of IPMN-associated carcinoma depends on tumor stage, on histologic tumor subtype, grading, and Ca 19-9 levels. The current 8th edition of the AJCC/UICC staging system is applicable for IPMN-associated carcinoma and for both of its subtypes IPMN-PDAC and IPMN-CC. The role of adjuvant therapy for IPMN-associated carcinoma remains unclear.

EnzymeML-a data exchange format for biocatalysis and enzymology.

EnzymeML is an XML-based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO-RK.

Collagen Organization Does Not Influence T-Cell Distribution in Stroma of Human Pancreatic Cancer.

The dominant intrastromal T-cell infiltration in pancreatic cancer is mainly caused by the contact guidance through the excessive desmoplastic reaction and could represent one of the obstacles to an effective immune response in this tumor type. This study analyzed the collagen organization in normal and malignant pancreatic tissues as well as its influence on T-cell distribution in pancreatic cancer. Human pancreatic tissue was analyzed using immunofluorescence staining and multiphoton and SHG microscopy supported by multistep image processing. The influence of collagen alignment on activated T-cells was studied using 3D matrices and time-lapse microscopy. It was found that the stroma of malignant and normal pancreatic tissues was characterized by complex individual organization. T-cells were heterogeneously distributed in pancreatic cancer and there was no relationship between T-cell distribution and collagen organization. There was a difference in the angular orientation of collagen alignment in the peritumoral and tumor-cell-distant stroma regions in the pancreatic ductal adenocarcinoma tissue, but there was no correlation in the T-cell densities between these regions. The grade of collagen alignment did not influence the directionality of T-cell migration in the 3D collagen matrix. It can be concluded that differences in collagen organization do not change the spatial orientation of T-cell migration or influence stromal T-cell distribution in human pancreatic cancer. The results of the present study do not support the rationale of remodeling of stroma collagen organization for improvement of T-cell-tumor cell contact in pancreatic ductal adenocarcinoma.