Predictive Testing Research Articles

Experiences of Discrimination and Interest in Alzheimer’s Disease Predictive Testing in the Health and Retirement Study

AbstractBackgroundRapid developments in Alzheimer’s disease (AD) biomarker research suggest predictive testing may soon become a feasible option available to the public. Future reduction of racial and ethnic disparities in AD requires understanding of potential differences in drivers of interest in AD diagnostic testing. Experiences of discrimination may influence attitude toward AD testing, particularly among racially and ethnically minoritized populations. This study examines whether everyday or lifetime discrimination shapes interest in AD predictive testing.MethodData were collected from 1,472 participants in the 2010 and 2012 waves of the Health and Retirement Study who answered a module on interest in receiving a free test that could tell whether they would develop AD in the future, along with measures of Everyday Discrimination and Lifetime Discrimination. Logistic models were controlled for deciles of propensity scores (estimated using demographic and socioeconomic variables) and odds ratios were re‐expressed as risk differences (RD). The RD is the difference in the probability a person expressed interest in receiving a future AD predictive test based on past experiences of discrimination.ResultThe mean age of the sample was 67 (SD = 10.2), 65.9% were white, and 80% endorsed interest in AD predictive testing. Most (64.1%) participants indicated experiencing everyday discrimination in at least one domain, and 34.8% experienced major lifetime discrimination in at least one domain. Those interested in predictive testing were younger (66 vs 70 years) and more likely to be Black (20% vs 15%) or Latinx (14% vs 8%) than participants uninterested in testing. The probability of wanting an AD test was not associated with discrimination experiences for Black (RD everyday discrimination = 0.104, p = 0.285; RD lifetime discrimination = ‐0.038; p = 0.626) or Latinx (RD everyday discrimination = ‐0.003, p = 0.974; RD lifetime discrimination = ‐0.053; p = 0.692) participants.ConclusionDespite historical and contemporary experiences of discrimination, Black and Latinx individuals express interest in AD testing. This finding implicates structural and systemic barriers, such as systemic racism and institutional gaps in access to clinical research, as likely explanations for underrepresentation of racially and ethnically minoritized persons in research on AD testing.

Data driven criteria for genetic testing result in an efficient selection of patients with genetic dementia in a clinical setting

AbstractBackgroundIdentification of patients with familial dementia is important as this may explain disease in families, raises the possibility of predictive testing for relatives and enables participation in trials. Previously proposed clinical criteria to offer genetic testing based on diagnosis, age, and familial history do not capture the diversity of clinical presentation of patients. We aimed to develop data‐derived clinical criteria and prospectively validated these by applying them in a memory clinic.MethodIn a 2,5‐year period (1‐1‐2010 until 30‐6‐2012) 1138 patients visited the Alzheimer Center Amsterdam and underwent routine diagnostic work‐up (van der Flier et al 2018). The average age of individuals was 62 years, 41% of the patients being female. Patients provided DNA for research purposes, which allowed us to test 1022 (90%) of the patients for variants in 54 dementia related genes (exome sequencing), APP duplications and C9orf72‐repeat expansions. Data driven clinical criteria for genetic testing were formulated to optimally identify carriers of a causal mutation. Subsequently, we offered genetic testing according to the new clinical criteria to all patients in the Alzheimer Center Amsterdam for 1 year (9‐2021 to 9‐2022).ResultWe identified genetic mutations causing dementia in 34 patients, which accounted for 3.3% of all patients. Previous criteria would have selected 23% of these patients for testing and identified 47% of the mutation carriers. We formulated optimized clinical criteria(as shown in Figure 1), that would have identified 88% of mutation carriers(30/34 carriers) in 26% of all patients. This efficient selection was prospectively validated in 2021. A 149 out of 517 patients(29%) were eligible for genetic testing based on the new criteria. Of these 90 patients(60.4%) opted for testing and 59(39.6%) declined testing or clinicians decided against offering the test. We found 12 out of 90(13%) to carry a mutation. This confirms the efficient selection as 10 mutation carriers were anticipated in the tested group based on our research data.ConclusionData driven clinical criteria for genetic testing efficiently selected individuals with genetic dementia in a real‐life implementation. Memory clinics can adopt these clinical criteria to offer genetic testing to the patients most likely to benefit.

Motivation vs. Hopelessness: The Well-Being Following Predictive Testing for Huntington’s Disease

Predictive genetic testing for Huntington’s Disease, a fatal and progressive neurodegenerative disorder with no cure, can lead to a multitude of favorable and unfavorable responses, impacts, and experiences. Utilizing many qualitative studies, participants’ reactions to their gene-positive test results were categorized into the opposing psychological states of motivation vs. hopelessness. Key milestones of adulthood, such as education and career, romantic and familial relationships, reproductive choices, and financial investments, were used as metrics for the two categories. By studying the psychological well-being of at-risk individuals for Huntington’s, this literature review also argues for the use and improvement of long-term, tailored genetic counseling.

Co-design of patient information leaflets for germline predisposition to cancer: recommendations for clinical practice from the UK Cancer Genetics Group (UKCGG), Cancer Research UK (CRUK) funded CanGene-CanVar Programme and the Association of Genetic Nurse Counsellors (AGNC)

BackgroundTesting for germline pathogenic variants (GPVs) in cancer predisposition genes is increasingly offered as part of routine care for patients with cancer. This is often urgent in oncology clinics due...

Conceptualization and Development of a Scale for Brand Experience in Extended Reality

Purpose: This study aims to conceptualize the brand experience that users' avatars can experience on an XR platform and develop items to measure it.
 Design/methodology/approach: The author presents both a conceptual analysis of brand experience in XR (BXIXR) and a BXIXR scale by conducting a review of marketing research and immersive technology. Adhering to the relevant theory and psychometric principles, the BXIXR scale was developed and validated through a literature review and item generation process, followed by confirmatory factor analysis, reliability analysis, and predictive validity testing.
 Findings: This research demonstrates that BXIXR can be broken down into four dimensions that are differentially evoked by various brand spaces in XR: search, entertainment, relations, and assembly.
 Research limitations/implications: This research suggested that the brand experience that users have at the boundary between the physical and virtual worlds may differ from brand experience in the physical world. In this study, it is expected that meaningful implications can be proposed in that it attempts to derive a brand experience based on an immersive economy.
 Originality/value: The results of this study suggest that the BXIXR scale is a reliable and valid measure of BXIXR. The four-factor structure of the scale is consistent with the theoretical framework, and the results of the reliability and validity testing provide evidence for its robustnes.

Optimizing tissue stewardship in non-small cell lung cancer to support molecular characterization and treatment selection: statement from a working group of thoracic pathologists.

Many patients with non-small cell lung cancer do not receive guideline-recommended, biomarker-directed therapy, despite the potential for improved clinical outcomes. Access to timely, accurate, and comprehensive molecular profiling, including targetable protein overexpression, is essential to allow fully informed treatment decisions to be taken. In turn, this requires optimal tissue management to protect and maximize the use of this precious finite resource. Here, a group of leading thoracic pathologists recommend factors to consider for optimal tissue management. Starting from when lung cancer is first suspected, keeping predictive biomarker testing in the front of the mind should drive the development of practices and procedures that conserve tissue appropriately to support molecular characterization and treatment selection.

Abstract 15631: A Precision Medicine Approach to Predicting Pathogenicity Among Population Variants in Hypertrophic Cardiomyopathy-Associated Genes in the UK Biobank

Introduction: Genomic and precision medicine have opened the door to predictive genetic testing to identify those at risk of cardiac disease before its development. This is important for hypertrophic cardiomyopathy (HCM), the most prevalent heritable heart muscle disease. A major hurdle to accurate predictive testing is the markedly higher prevalence of HCM-associated variants than of disease. New approaches are needed to discern which disease-causative, “actionable,” variants. Objective: To develop and validate a precision medicine approach for predicting pathogenicity of population-identified HCM-associated variants. Methods: We used phenotypic and genotypic data from the UK Biobank (UKBB). We filtered for missense variants in “definitive” (ClinGen) HCM genes. Our novel precision medicine tool, DiscoVari , provides signal-to-noise (S:N) analysis comparing disease to population variant frequency to identify pathogenic genetic ’hotspots’. We used reverse phenotyping to correlate evidence of HCM and sequelae (sudden death, heart failure, ventricular arrhythmias, atrial fibrillation, chest pain, pacemaker/ICD) to S:N hotspots. Variants were re-evaluated using American College of Medical Genetics and Genomics (ACMG) criteria; those in S:N hotspots met PM1 criteria. Results: Variants of uncertain significance (VUSs) in HCM genes had a prevalence of 21.8% in the UKBB, with PM1 determining variant call in 25.7% [24.9-26.6] of HCM-gene variants. Using SN enriched for HCM (0.35% with HCM without PM1 and 0.83% with PM1, p < 0.01). InterVar did not enrich for HCM (0.71% with HCM with PM1 and 0.51% without PM1). DiscoVari reduced the likely pathogenic/pathogenic (LPP) variant burden in individuals without HCM (11.8% compared to InterVar (25.9%, p < 0.0001). DiscoVari enriched for LPP variants in those with HCM (36.1%, p < 0.0001) compared to healthy individuals, while InterVar did not. Conclusion: VUSs are common in HCM genes in the population and PM1 is crucial for accurate variant classification. Incorporating DiscoVari S:N into ACMG guidelines improves prediction of variants associated with HCM, or subclinical cardiomyopathy.

Unravelling host-pathogen interactions by biofilm infected human wound models

Approximately 80 % of persistent wound infections are affected by the presence of bacterial biofilms, resulting in a severe clinical challenge associated with prolonged healing periods, increased morbidity, and high healthcare costs. Unfortunately, in vitro models for wound infection research almost exclusively focus on early infection stages with planktonic bacteria. In this study, we present a new approach to emulate biofilm-infected human wounds by three-dimensional human in vitro systems. For this purpose, a matured biofilm consisting of the clinical key wound pathogen Pseudomonas aeruginosa was pre-cultivated on electrospun scaffolds allowing for non-destructive transfer of the matured biofilm to human in vitro wound models. We infected tissue-engineered human in vitro skin models as well as ex vivo human skin explants with the biofilm and analyzed structural tissue characteristics, biofilm growth behavior, and biofilm-tissue interactions. The structural development of biofilms in close proximity to the tissue, resulting in high bacterial burden and in vivo-like morphology, confirmed a manifest wound infection on all tested wound models, validating their applicability for general investigations of biofilm growth and structure. The extent of bacterial colonization of the wound bed, as well as the subsequent changes in molecular composition of skin tissue, were inherently linked to the characteristics of the underlying wound models including their viability and origin. Notably, the immune response observed in viable ex vivo and in vitro models was consistent with previous in vivo reports. While ex vivo models offered greater complexity and closer similarity to the in vivo conditions, in vitro models consistently demonstrated higher reproducibility. As a consequence, when focusing on direct biofilm-skin interactions, the viability of the wound models as well as their advantages and limitations should be aligned to the particular research question of future studies. Altogether, the novel model allows for a systematic investigation of host-pathogen interactions of bacterial biofilms and human wound tissue, also paving the way for development and predictive testing of novel therapeutics to combat biofilm-infected wounds.

Standardized and quality-assured predictive PD-L1 testing in the upper gastrointestinal tract.

As a result of the high approval dynamics and the growing number of immuno-oncological concepts, the complexity of treatment decisions and control in the area of cancers of the esophagus, gastroesophageal junction and stomach is constantly increasing. Since the treatment indication for PD-1 inhibitors that are currently approved in the European Union is often linked to the expression of PD-L1 (programmed cell death-ligand 1), the evaluation of tissue-based predictive markers by the pathologist is of crucial importance for treatment stratification. Even though the immunohistochemical analysis of the PD-L1 expression status is one of the best studied, therapy-relevant biomarkers for an immuno-oncological treatment, due to the high heterogeneity of carcinomas of the upper gastrointestinal tract, there are challenges in daily clinical diagnostic work with regard to implementation, standardization and interpretation of testing. An interdisciplinary group of experts from Germany has taken a position on relevant questions from daily pathological and clinical practice, which concern the starting material, quality-assured testing and the interpretation of pathological findings, and has developed recommendations for structured reporting.

Comprehensive Genomic Profiling in Predictive Testing of Cancer.

Despite the rapid progress in the field of personalized medicine and the efforts to apply specific treatment strategies to patients based on the presence of pathogenic variants in one, two, or three genes, patient response to the treatment in terms of positive benefit and overall survival remains heterogeneous. However, advances in sequencing and bioinformatics technologies have facilitated the simultaneous examination of somatic variants in tens to thousands of genes in tumor tissue, enabling the determination of personalized management based on the patient's comprehensive genomic profile (CGP). CGP has the potential to enhance clinical decision-making and personalize innovative treatments for individual patients, by providing oncologists with a more comprehensive molecular characterization of tumors. This study aimed to highlight the utility of CGP in routine clinical practice. Here we present three patient cases with various advanced cancer indicated for CGP analysis using a combination of SOPHiA Solid Tumor Solution (STS, 42 genes) for DNA and SOPHiA RNAtarget Oncology Solution (ROS, 45 genes and 17 gene fusions with any random partners) for RNA. We were able to identify actionable genomic alterations in all three cases, thereby presenting valuable information for future management of these patients. This approach has the potential to transform clinical practice and greatly improve patient outcomes in the field of oncology.

Tumour area infiltration and cell count in endoscopic biopsies of therapy-naive upper GI tract carcinomas by QuPath analysis: implications for predictive biomarker testing

Guidelines regulate how many (tumour-bearing) tissue particles should be sampled during gastric cancer biopsy to obtain representative results in predictive biomarker testing. Little is known about how well these guidelines are applied, how the number of tissue particles correlates with the actual tumour-infiltrated area and how many absolute tumour cells are captured. The study included endoscopic biopsies of untreated carcinomas of the upper gastrointestinal (GI)-tract during the 2016–2020 review period. Archival (H&E)-stained histological sections were digitised and the tumour areas were manually annotated. The tumour-bearing tissue area and absolute carcinoma cell count per case were determined by image analysis and compared with a reference primary surgical specimen. Biopsies from 253 patients were analysed. The following mean values were determined: (a) tumour tissue particle number: 6.5 (range: 1–25, standard deviation (SD) = 3.33), (b) number of tumour-bearing tissue particles: 4.7 (range: 1–20, SD = 2.80), (c) tumour-infiltrated area: 7.5 mm2 (range: 0.18–59.46 mm2, SD = 6.67 mm2), (d) absolute tumour cell count: 13,492 (range: 193–92,834, SD = 14,185) and (e) tumour cell count in a primary surgical specimen (tumour size: 6.7 cm): 105,200,176. The guideline-recommended tissue particle count of 10 was not achieved in 208 patients (82.2%) and the required tumour-bearing tissue particle count of 5 was not achieved in 133 patients (52.6%). Tissue particle count, tumour-infiltrated area and tumour cell count were only weakly correlated. Most cases featured an infiltrated area ≥ 4.5 mm2 (156, 61.7%). Cases with more tissue particles showed only a moderate increase in infiltrated area and tumour cells compared to cases with fewer particles. Biopsies are often used to determine predictive biomarkers, particularly Her2/neu and PD-L1. Diagnostic standards to ensure representative material have been suggested in guidelines to reduce false-negative predictions. However, the real-world practice seems to substantially deviate from recommended standards. To the best of our knowledge, this is the first systematic study describing the relationships between endoscopic tissue fragment number, actual infiltrated tumour area and carcinoma cell number. The data question the tissue particle number as a quality assessment parameter. We advocate histopathological reports indicating on which basis statements on therapy-relevant biomarkers were made. Digital pathology has the potential to objectively quantify the tissue for documentation, quality assessment and future clinical studies.

Deep learning‐based robust hybrid approaches for brain tumor classification in magnetic resonance images

AbstractThe classification of brain images is an immensely challenging task and one of the most valuable and frequently employed procedures in the field of medical diagnostics. Deep Learning (DL), which falls under the umbrella of artificial intelligence, has introduced novel techniques for automated analysis of medical images. The objective of this study was to develop two hybrid DL models for the segmentation and classification of brain magnetic resonance imaging (MRI) data. The first hybrid model combines fully convolutional networks (FCNs) and residual networks (ResNets) for both segmentation and classification purposes. The second model is a hybrid of SegNet for segmentation and MobileNet for classification. Rest assured, it will provide you with a dependable and promising performance. The analysis was conducted on a labeled dataset comprising images of glioma, meningioma, pituitary, and no‐tumor cases. Python was utilized to implement the aforementioned hybrid models. The proposed models achieved remarkable accuracies of 93.9% and 91.3%, respectively, when evaluated on a brain tumor MRI dataset. Additionally, a comprehensive evaluation of the proposed models was conducted, comparing them with other existing hybrid models in terms of metrics such as the dice score, Jaccard index, positive predictive value (PPV), false predictive value (FPV), testing time, precision, recall, specificity, and F1 score. The results demonstrated that the proposed DL technique can significantly assist doctors and radiologists in the early detection of brain tumor cells.

Item development and pre-testing of an Osteoarthritis Conceptualisation Questionnaire to assess knowledge and beliefs in people with knee pain.

Many people with osteoarthritis hold beliefs that physical activity is unhelpful or dangerous for their joints, despite high-level evidence suggesting otherwise. Recent advances in scientific understanding of osteoarthritis have led to new treatments that target an individual's understanding both of their condition and the importance of best-practice management strategies, such as physical activity. Conceptual change has been proposed as an important mechanism by which cognitive interventions, such as pain science education, may reduce pain and improve function. There are currently no specific assessments of osteoarthritis conceptualisation to determine the effectiveness of cognitive interventions in effecting conceptual change in people with knee osteoarthritis. Therefore, we aimed to develop an item bank, as the first phase of developing a questionnaire to assess people's conceptualisations about their knee osteoarthritis and the role of physical activity in managing their osteoarthritis. Using a guideline-informed mixed method design, a panel of experts identified domains relevant to conceptualisation about knee osteoarthritis and physical activity (knowledge, beliefs, understanding) based upon available evidence. The panel created 33 provisional items. Qualitative and quantitative pretesting were used to explore how people with knee osteoarthritis understood the provisional items. Eighteen people with knee osteoarthritis completed cognitive interviews about their comprehension of the wording/grammar of each provisional item. The provisional item bank was field tested with 100 people with knee osteoarthritis. Readability was adequate with a Flesch reading ease score of 57.7. Although 14.7% used the 'Strongly agree' response option, only 3.4% of responses used the 'Strongly disagree' option, suggesting possible response bias. Predictive quality testing identified relevant modifications to the questionnaire instructions. The panel of experts appraised the qualitative data to assess whether and how items should be modified to address the problems identified, resulting in a final item bank of 45 items that can be evaluated for psychometric properties in future research.

Factors associated with adherence to BRCA1/2 mutation testing after oncogenetic counseling in long-surviving patients with a previous diagnosis of breast or ovarian cancer

BRCA1/2 mutations account for 5 to 10% of breast and 15% of ovarian cancers. Various guidelines on BRCA1/2 genetic counseling and testing have been issued, and the criteria have evolved over the years. Oncogenetic counseling aims to inform patients about the possibility and implications of undergoing predictive testing and risk management programs. We analyzed a cohort of 50 subjects with a previous personal history of breast or ovarian cancer who had not been tested for BRCA1/2 mutations at the time of diagnosis but were found eligible according to the most recent guidelines. All patients were offered pre-test oncogenetic counseling and BRCA1/2 genetic testing. The mean time from cancer diagnosis to genetic counseling was over 10 years. We analyzed socio-demographic and psychological parameters associated with the decision to undergo BRCA1/2 genetic testing or the reasons behind the withdrawal. Thirty-nine patients underwent BRCA1/2 genetic testing. Patients who accept the genetic test communicate more easily with family members than those who refuse. Factors associated with test refusal are having a long-term partner and having a negative perception of life. There is a trend, although not statistically significant, toward younger age at cancer diagnosis, more likely to participate in cancer screening programs (71.8% vs. 45.5%), and more likely to have daughters (63.3% vs. 37.5%) in the group that accepted the test. The offer of BRCA testing was well accepted by our study population, despite the many years since the cancer diagnosis. With the perspective of further broadening the access criteria to genetic testing, it is important to understand how to best approach pre-test counseling in long-surviving patients with a previous diagnosis of cancer.

Adequacy of cytology and small biopsy samples obtained with rapid onsite evaluation (ROSE) for predictive biomarker testing in non-small cell lung cancer

Complete biomarker workup of non-small cell lung cancer (NSCLC) specimens is essential for appropriate and timely clinical management decisions. This can be challenging to achieve from small cytology and histology specimens, with increasing numbers of molecular and immunohistochemical biomarkers required. We conducted a 5 year retrospective audit of cases at our institution to assess the diagnostic and biomarker testing adequacy rates, particularly those specimens obtained with rapid onsite evaluation (ROSE), performed by a cytopathologist and a cytology scientist or pathology trainee, including all endobronchial ultrasound guided transbronchial needle aspirations (EBUS-TBNA), CT guided lung fine needle aspirations (FNA) and CT guided lung core biopsies. A total of 5,354 cases were identified, of which 92.2% had sufficient material for diagnosis. Of the 1506 cases identified with a recorded diagnosis of lung adenocarcinoma or NSCLC, not otherwise specified, 1001 (66.5%) had biomarker testing requested. Sufficient material was available in 89.5% of cases for a complete biomarker workup which included EGFR and KRAS mutational testing (all cases), ALK, ROS1 and PD-L1 immunohistochemistry (all cases), and ALK and ROS1 FISH (as required). For EGFR and KRAS mutational testing across both cytology and histology specimens, 99% of cases were sufficient. Of the samples in which a complete biomarker workup was unable to be performed, approximately half were only insufficient due to inadequate numbers of tumour cells for PD-L1 immunohistochemistry. Excluding PD-L1 IHC, 952 (95.1%) of samples obtained with ROSE were sufficient for the remainder of the testing requirements. Next generation sequencing using a 33 gene custom AmpliSeq panel was achieved in up to 72% of cases. In conclusion, small cytology and histology specimens obtained with ROSE are suitable for predictive biomarker testing in NSCLC, although attention needs to be paid to obtaining sufficient cells (>100) for PD-L1 immunohistochemistry.

Calibrating variant curation by clinical context based on factors that influence patients’ tolerance of uncertainty

PurposeShared decision making manages genomic uncertainty by integrating molecular and clinical uncertainties with patient values to craft a person-centered management plan. Laboratories seek genomic report consistency, agnostic to clinical context. Molecular reports often mask laboratory-managed uncertainties from clinical decision making. Better integration of these uncertainty management strategies requires a nuanced understanding of patients’ perceptions and reactions to test uncertainties. We explored patients’ tolerance to variant uncertainty in 3 parameters: (1) relative causal significance, (2) risk accuracy, and (3) classification validity. MethodDeliberative forums were undertaken with 18 patients with predictive testing experience. Uncertainty deliberations were elicited for each parameter. A thematic framework was first developed, and then mapped to whether they justified tolerance to more or less parameter-specific uncertainty. ResultsSix identified themes mapped to clinical and personal domains. These domains generated opposing forces when calibrating uncertainty. Personal themes justified tolerance of higher uncertainty and clinical themes lower uncertainty. Decision making in uncertainty focused on reducing management regret. Open communication increased tolerance of classification validity and risk accuracy uncertainty. Using these data, we have developed a nascent clinical algorithm integrating molecular uncertainty with clinical context through a targeted communication framework. ConclusionMaximizing test utility necessitates context-specific recalibration of uncertainty management and communication.

Prognostic Biomarkers of Cell Proliferation in Colorectal Cancer (CRC): From Immunohistochemistry to Molecular Biology Techniques.

Colorectal cancer (CRC) is one of the most common and severe malignancies worldwide. Recent advances in diagnostic methods allow for more accurate identification and detection of several molecular biomarkers associated with this cancer. Nonetheless, non-invasive and effective prognostic and predictive testing in CRC patients remains challenging. Classical prognostic genetic markers comprise mutations in several genes (e.g., APC, KRAS/BRAF, TGF-β, and TP53). Furthermore, CIN and MSI serve as chromosomal markers, while epigenetic markers include CIMP and many other candidates such as SERP, p14, p16, LINE-1, and RASSF1A. The number of proliferation-related long non-coding RNAs (e.g., SNHG1, SNHG6, MALAT-1, CRNDE) and microRNAs (e.g., miR-20a, miR-21, miR-143, miR-145, miR-181a/b) that could serve as potential CRC markers has also steadily increased in recent years. Among the immunohistochemical (IHC) proliferative markers, the prognostic value regarding the patients' overall survival (OS) or disease-free survival (DFS) has been confirmed for thymidylate synthase (TS), cyclin B1, cyclin D1, proliferating cell nuclear antigen (PCNA), and Ki-67. In most cases, the overexpression of these markers in tissues was related to worse OS and DFS. However, slowly proliferating cells should also be considered in CRC therapy (especially radiotherapy) as they could represent a reservoir from which cells are recruited to replenish the rapidly proliferating population in response to cell-damaging factors. Considering the above, the aim of this article is to review the most common proliferative markers assessed using various methods including IHC and selected molecular biology techniques (e.g., qRT-PCR, in situ hybridization, RNA/DNA sequencing, next-generation sequencing) as prognostic and predictive markers in CRC.

J-GAIN v1.1: a flexible tool to incorporate aerosol formation rates obtained by molecular models into large-scale models

Abstract. New-particle formation from condensable gases is a common atmospheric process that has significant but uncertain effects on aerosol particle number concentrations and aerosol–cloud–climate interactions. Assessing the formation rates of nanometer-sized particles from different vapors is an active field of research within atmospheric sciences, with new data being constantly produced by molecular modeling and experimental studies. Such data can be used in large-scale climate and air quality models through parameterizations or lookup tables. Molecular cluster dynamics modeling, ideally benchmarked against measurements when available for the given precursor vapors, provides a straightforward means to calculate high-resolution formation rate data over wide ranges of atmospheric conditions. Ideally, the incorporation of such data should be easy, efficient and flexible in the sense that same tools can be conveniently applied for different data sets in which the formation rate depends on different parameters. In this work, we present a tool to generate and interpolate lookup tables of formation rates for user-defined input parameters. The table generator primarily applies cluster dynamics modeling to calculate formation rates from an input quantum chemistry data set defined by the user, but the interpolator may also be used for tables generated by other models or data sources. The interpolation routine uses a multivariate interpolation algorithm, which is applicable to different numbers of independent parameters, and gives fast and accurate results with typical interpolation errors of up to a few percent. These routines facilitate the implementation and testing of different aerosol formation rate predictions in large-scale models, allowing the straightforward inclusion of new or updated data without the need to apply separate parameterizations or routines for different data sets that involve different chemical compounds or other parameters.

Adaptive Market Hypothesis and Predictability: Evidence in Latin American Stock Indices

AbstractThis article examines the adaptive market hypothesis in the five most important Latin American stock indices. To that end, we apply three versions of the variance ratio test, as well as the Brock-Dechert-Scheinkman test for nonlinear predictability. Additionally, we perform the Dominguez-Lobato and generalized spectral tests to evaluate the Martingale difference hypothesis. Moreover, we consider salient news related to the plausible market inefficiencies detected by these four tests. Finally, we apply a GARCH-M model to assess the risk-return relationship through time. Our results suggest that the predictability of stock returns varies over time. Furthermore, the efficiency in each market behaves differently over time. All in all, the analyzed emerging market indices satisfy the adaptive market hypothesis, given the switching behavior between periods of efficiencies and inefficiencies, since the adaptive market hypothesis suggests that market efficiency and market anomalies might coexist in capital markets.

Does a proactive procedure lead to a higher uptake of predictive testing in families with a pathogenic BRCA1/BRCA2 variant? A family cancer clinic evaluation.

The uptake of genetic counseling and predictive genetic testing by family members at risk for hereditary tumor syndromes is generally below 50%. To address this issue, a new guideline was introduced in the Netherlands in 2019 that aims to improve the sharing of information within families. In addition to cascade screening supported by follow-up telephone calls with the proband, municipal records were accessed to allow the geneticist to contact at-risk family members directly. We evaluated this procedure in 32 families with a (likely) pathogenic germline BRCA1/BRCA2 variant diagnosed at our hospital between May 1, 2020, and July 31, 2021, comparing current uptake with outcomes achieved for 33 families diagnosed in 2014. Fifteen months after diagnostic testing of the proband, the uptake was 43% (120/277), comparable to the 44% (87/200) registered previously. Among a subgroup of women at 50% risk aged 25-75 years, 71% (47/66) were tested, comparable to an earlier uptake of 69% (59/86). Of the 34 at-risk relatives we contacted directly, 17 (50%) underwent predictive testing. In conclusion, we found no evidence that the new procedure leads to a substantially increased uptake. Future research should be primarily aimed at understanding intrafamilial communication barriers.