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Abstract Background Kallikrein-related peptidase 7 (KLK7) is a chymotrypsin-like serine protease which is essential for the desquamation of corneocytes and thus plays a pivotal role in maintaining skin homeostasis. In cancer, KLK7 overexpression was suggested to represent a route for metastasis through cleavage of cell junction and extracellular matrix proteins of cancer cells. Methods To comprehensively determine KLK7 protein expression in normal and neoplastic tissues, a tissue microarray containing 13,447 samples from 147 different tumor types and subtypes as well as 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry. Results KLK7 positivity was found in 64 of 147 tumor categories, including 17 tumor categories with at least one strongly positive case. The highest rate of KLK7 positivity was found in squamous cell carcinomas from various sites of origin (positive in 18.1%-63.8%), ovarian and endometrium cancers (4.8%-56.2%), salivary gland tumors (4.8%-13.7%), bilio-pancreatic adenocarcinomas (20.0%-40.4%), and adenocarcinomas of the upper gastrointestinal tract (3.3%-12.5%). KLK7 positivity was linked to nodal metastasis (p = 0.0005), blood vessel infiltration (p = 0.0037), and lymph vessel infiltration (p

Simulation models of social processes may require data that are not readily available, have low accuracy, are incomplete or biased. The paper presents a formal process for collating, assessing, selecting, and using secondary data as part of creating, validating, and documenting an agent-based simulation model of a complex social process, in this case, asylum seekers’ journeys to Europe. The process starts by creating an inventory of data sources, and the associated metadata, followed by assessing different aspects of data quality according to pre-defined criteria. As a result, based on the typology of available data, we are able to produce a thematic map of the area under study, and assess the uncertainty of key data sources, at least qualitatively. We illustrate the process by looking at the data on Syrian migration to Europe in 2011–21. In parallel, successive stages of the development of a simulation model allow for identifying key types of information which are needed as input into empirically grounded modelling analysis. Juxtaposing the available evidence and model requirements allows for identifying knowledge gaps that need filling, preferably by collecting additional primary data, or, failing that, by carrying out a sensitivity analysis for the assumptions made. By doing so, we offer a way of formalising the data collection process in the context of model-building endeavours, while allowing the modelling to be predominantly question-driven rather than purely data-driven. The paper concludes with recommendations with respect to data and evidence, both for modellers, as well as model users in practice-oriented applications.

Social simulation studies are complex. They typically combine various data sources and hypotheses about the system’s mechanisms that are integrated by intertwined processes of model building, simulation experiment execution and analysis. Various documentation approaches exist to increase the transparency and traceability of complex social simulation studies. Provenance standards enable the formalization of information on sources and activities, which contribute to the generation of an entity, in a queryable and computationally accessible manner. Provenance patterns can be defined as constraints on the relationships between specific types of activities and entities of a simulation study. In this paper, we refine the provenance pattern-based approach to address specific challenges of social agent-based simulation studies. Specifically, we focus on the activities and entities involved in collecting and analysing primary data about human decisions, and the collection and quality assessment of secondary data. We illustrate the potential of this approach by applying it to central activities and results of an agent-based simulation project and by presenting its implementation in a web-based tool.

Abstract Background Prostein (P501S), also termed solute carrier family 45 member 3 (SLC45A3) is an androgen regulated protein which is preferentially expressed in prostate epithelial cells. Because of its frequent expression in prostate cancer, prostein was suggested a diagnostic prostate cancer marker. Methods In order to comprehensively assess the diagnostic utility of prostein immunohistochemistry, a tissue microarray containing 19,202 samples from 152 different tumor types and subtypes as well as 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry. Results Prostein immunostaining was typically cytoplasmic, granular and perinuclear. Prostein positivity was seen in 96.7% of 419 prostate cancers including 78.3% with strong staining. In 16,709 extra-prostatic tumors, prostein positivity was observed in 7.2% of all cases but only 0.3% had a strong staining. Overall, 50 different extra-prostatic tumor categories were prostein positive, 12 of which included at least one strongly positive case. Extra-prostatic tumors with highest rates of prostein positivity included different subtypes of salivary gland tumors (7.6-44.4%), neuroendocrine neoplasms (15.8-44.4%), adenocarcinomas of the gastrointestinal tract (7.3-14.8%), biliopancreatic adenocarcinomas (3.6-38.7%), hepatocellular carcinomas (8.1%), and adenocarcinomas of other organs (up to 21%). Conclusions Our data provide a comprehensive overview on prostein expression in human cancers. Prostein is a highly sensitive prostate cancer marker occurring in > 96% of prostate cancers. Because prostein can also be expressed in various other tumor entities, classifying of a tumor mass as a prostate cancer should not be based on prostein positivity alone.

The quest for efficient green hydrogen production through Alkaline Water Electrolysis (AWE) is a critical aspect of the clean energy transition. The hydrogen evolution reaction (HER) in alkaline media is central to this process, with the performance of electrocatalysts being a determining factor for overall efficiency. Theoretical studies using energy-based descriptors are essential for designing high-performance alkaline HER electrocatalysts. This review summarizes various descriptors, including water adsorption energy, water dissociation barrier, and Gibbs free energy changes of hydrogen and hydroxyl adsorption. Examples of how to apply these descriptors to identify the active site of materials and better design high-performance alkaline HER electrocatalysts are provided, highlighting the previously underappreciated role of hydroxyl adsorption-free energy changes. As research progresses, integrating these descriptors with experimental data will be paramount in advancing AWE technology for sustainable hydrogen production.

Abstract Cadherin-16 (CDH16) plays a role in the embryonal development in kidney and thyroid. Downregulation of CDH16 RNA was found in papillary carcinomas of the thyroid. To determine the expression of CDH16 in tumors and to assess the diagnostic utility a tissue microarray containing 15,584 samples from 152 different tumor types as well as 608 samples of 76 different normal tissue types was analyzed. A membranous CDH16 immunostaining was predominantly seen in thyroid, kidney, cauda epididymis, and mesonephric remnants. In the thyroid, CDH16 staining was seen in 100% of normal samples, 86% of follicular adenomas, 60% of follicular carcinomas, but only 7% of papillary carcinomas (p

Stimulator of interferon genes protein (STING) activates the immune response in inflammatory cells. STING expression in cancer cells is less well characterized, but STING agonists are currently being evaluated as anticancer drugs. A tissue microarray containing 18,001 samples from 139 different tumor types was analyzed for STING by immunohistochemistry. STING-positive tumor cells were found in 130 (93.5%) of 139 tumor entities. The highest STING positivity rates occurred in squamous cell carcinomas (up to 96%); malignant mesothelioma (88.5%–95.7%); adenocarcinoma of the pancreas (94.9%), lung (90.3%), cervix (90.0%), colorectum (75.2%), and gallbladder (68.8%); and serous high-grade ovarian cancer (86.0%). High STING expression was linked to adverse phenotypes in breast cancer, clear cell renal cell carcinoma, colorectal adenocarcinoma, hepatocellular carcinoma, and papillary carcinoma of the thyroid (p < 0.05). In pTa urothelial carcinomas, STING expression was associated with low-grade carcinoma (p = 0.0002). Across all tumors, STING expression paralleled PD-L1 positivity of tumor and inflammatory cells (p < 0.0001 each) but was unrelated to the density of CD8+ lymphocytes. STING expression is variable across tumor types and may be related to aggressive tumor phenotype and PD-L1 positivity. The lack of relationship with tumor-infiltrating CD8+ lymphocytes argues against a significant IFN production by STING positive tumor cells.

EpCAM is expressed in many epithelial tumors and is used for the distinction of malignant mesotheliomas from adenocarcinomas and as a surrogate pan-epithelial marker. A tissue microarray containing 14,832 samples from 120 different tumor categories was analyzed by immunohistochemistry. EpCAM staining was compared with TROP2 and CKpan. EpCAM staining was detectable in 99 tumor categories. Among 78 epithelial tumor types, the EpCAM positivity rate was ≥90% in 60 categories—including adenocarcinomas, neuroendocrine neoplasms, and germ cell tumors. EpCAM staining was the lowest in hepatocellular carcinomas, adrenocortical tumors, renal cell neoplasms, and in poorly differentiated carcinomas. A comparison of EpCAM and CKpan staining identified a high concordance but EpCAM was higher in testicular seminomas and neuroendocrine neoplasms and CKpan in hepatocellular carcinomas, mesotheliomas, and poorly differentiated non-neuroendocrine tumors. A comparison of EpCAM and TROP2 revealed a higher rate of TROP2 positivity in squamous cell carcinomas and lower rates in many gastrointestinal adenocarcinomas, testicular germ cell tumors, neuroendocrine neoplasms, and renal cell tumors. These data confirm EpCAM as a surrogate epithelial marker for adenocarcinomas and its diagnostic utility for the distinction of malignant mesotheliomas. In comparison to CKpan and TROP2 antibodies, EpCAM staining is particularly common in seminomas and in neuroendocrine neoplasms.

Context.--Special AT-rich sequence-binding protein 2 (SATB2) induces local chromatin loops to facilitate transcription. SATB2 immunostaining is commonly used as a marker for colorectal adenocarcinoma and osteosarcoma. Objective.--To extend our knowledge on the diagnostic value of SATB2 analysis in a comprehensive set of human tumors. Design.--Tissue microarrays with 15 012 samples from 120 tumor types and 608 samples of 76 different normal tissues were analyzed. Results.--SATB2 positivity was found in 89 of 120 different tumor types (74%), including 59 of 120 (49%) with at least 1 moderately positive tumor and 38 of 120 tumor types (32%) with at least 1 strongly positive tumor. Expression was frequent in adenomas (44/42-47/44; 94%9-6% positive), adenocarcinomas (1747 of 2023; 86%), and various subtypes of neuroendocrine neoplasms (3/7-12/12; 43%-100%) of the colorectum and appendix, Merkel cell carcinoma (25 of 34, 74%), osteosarcomas (15 of 25; 60%), and papillary renal cell carcinoma (RCC) (121 of 235; 52%). Associations to clinicopathologic tumor features were assessed in colorectal and kidney cancers. In colorectal cancer, weak SATB2 expression was linked to high pT (P < .001), nodal metastasis (P < .001), right-sided tumor location (P < .001), microsatellite instability (P < .001), and BRAF mutations (P = .02). In papillary RCC, low SATB2 expression was associated with high pT (P = .02), distant metastasis (P = .04), and reduced tumor-specific survival (P = .04). In clear cell RCC, low SATB2 expression was linked to high pT (P < .001), high Union for International Cancer Control stage (P < .001), high Thoenes grade (P = .02), and reduced recurrence-free survival (P = .02). Conclusions.--Strong SATB2 expression argues for a colorectal origin within adenocarcinomas and neuroendocrine neoplasms. Weak SATB2 expression reflects progression and poor prognosis in colorectal and kidney cancer. doi: 10.5858/arpa.2021-0317-OA, Special AT-rich sequence-binding protein 2 (SATB2) is an 82.5-kDa protein encoded by the SATB2 gene on 2q33. The protein is very highly conserved during evolution with only 3 of 733 [...]

Simulation models of social processes may require data that are not readily available, have low accuracy, are incomplete or biased. The paper presents a formal process for collating, assessing, selecting, and using secondary data as part of creating, validating, and documenting an agent-based simulation model of a complex social process, in this case, asylum migration to Europe. The process starts by creating an inventory of data sources, and the associated metadata, followed by assessing different aspects of data quality according to pre-defined criteria. As a result, based on the typology of available data, we are able to produce a thematic map of the area under study, and assess the uncertainty of key data sources, at least qualitatively. We illustrate the process by looking at the data on Syrian migration to Europe in 2011–21. In parallel, successive stages of the development of a simulation model allow for identifying key types of information which are needed as input into empirically grounded modelling analysis. Juxtaposing the available evidence and model requirements allows for identifying knowledge gaps that need filling, preferably by collecting additional primary data, or, failing that, by carrying out a sensitivity analysis for the assumptions made. By doing so, we offer a way of formalising the data collection process in the context of model-building endeavours, while allowing the modelling to be predominantly question-driven rather than purely data-driven. The paper concludes with recommendations with respect to data and evidence, both for modellers, as well as model users in practice-oriented applications.

Nanoscale zero‐valent iron (nZVI) has demonstrated high potential for the remediation of contaminated groundwater. Its lifetime is directly related to the hydrophobicity of nZVI. A promising approach to enhance the lifetime of nZVI is through sulfidation. Herein, the density functional theory (DFT) is applied to understand the impact of sulfidation on the hydrophobicity of stepped Fe surfaces. Adsorption properties of sulfur (S) at different coverages on the flat Fe(110) and stepped Fe(210) and Fe(211) surfaces are investigated. Sulfur has the stronger adsorption at a low surface coverage due to limited S–S repulsion. At the highest coverage (⊖ = 1 ML) on Fe(210) and Fe(211), the atoms at the step edges catalyze the formation of iron sulfides. The DFT results show surface hydrophobicity is mainly determined by the S coverage. At the low S coverage, the surface may become more hydrophilic due to the enhanced adsorption strength of water on the surface. However, an increase in the S coverage can efficiently block water adsorption, which is further evidenced by ab initio molecular dynamics (AIMD) results. The findings show that controlling S coverages is essential to engineer the hydrophobicity of nZVI surfaces for practical water remediation applications.