Scientific publications of the Saarland University
Not a member yet
14321 research outputs found
Sort by
Spectators lead to overconfidence and risk-taking in males in a motor task
Get PDFWe often perform motor tasks in front of other people, and this may help or hinder our performances.
Previous research mainly focused on changes in motor performance, and less is known about
spectator influences on performance predictions. An accurate performance prediction in motor tasks is
important, as it supports optimal performance. The present study examined whether being observed
by spectators influences not only performance, but also performance predictions in a motor task.
We tested 341 participants on a speeded cup-stacking task in a within-subjects design: co-acting
(performing concurrently with others) versus performing alone in front of an audience. In half of
the trials, participants predicted how many cups they would be able to stack in the upcoming trial.
Overconfidence, by predicting performances that were too high, resulted in failed trials. Being watched
by others led to motor performance decrements. Both males and females left a safety margin in their
performance predictions in the co-acting condition. Being watched by others led males to increase
their overconfidence and failure rate, whereas females left a safety margin in their predictions,
maintaining a stable failure rate in front of spectators. Our results indicate that spectators not only
influence motor performance, but also performance predictions
How to predict effective drug combinations - moving beyond synergy scores
Get PDFTo improve our understanding of multi-drug therapies, cancer cell line panels screened with drug combinations are frequently studied using machine learning (ML). ML models trained on such data typically focus on predicting synergy scores that support drug development and repurposing efforts but have limitations when deriving personalized treatment recommendations. To simulate a more realistic personalized treatment scenario, we pioneer ML models that make dose-specific predictions of the relative growth inhibition (instead of synergy scores), and that can be applied to previously unseen cell lines. Our approach is highly flexible: it enables the reconstruction of dose-response curves and matrices, as well as various measures of drug sensitivity (and synergy) from model predictions, which can finally even be used to derive cell line-specific prioritizations of both mono- and combination therapies
Machine learning strategies for drug sensitivity prediction and treatment optimization in cancer
Get PDFThe heterogeneity of cancer is a primary challenge for its treatment. Thus, analyzing large multi-omics and drug-screening datasets of cancer cells with machine learning (ML) is promising to study how cellular properties impact drug response and to apply this knowledge for treatment optimization. In this thesis, we used cell line data to build accurate, reliable, and interpretable ML models for personalizing cancer treatment: We conducted the largest benchmarking to date for drug response prediction, investigating various ML and dimension reduction methods. With SAURON-RF, we developed a novel method that, compared to state-of-the-art approaches, strongly improves predictions for drug-sensitive samples, which are particularly relevant for treatment optimization. To enhance model reliability, we built a pipeline that, for the first time, ensures that sensitivity predictions meet user-defined certainty levels for classification and regression. A major goal in treatment optimization is prioritizing treatment options based on their predicted effectiveness. To enable prioritization, we propose a novel sensitivity measure that is comparable across drugs and drug combinations, overcoming the limitations of existing measures. Additionally, we pioneer ML models predicting dose-specific responses to multi-drug therapies for cell lines unseen during model training. Lastly, we developed highly accurate models for predicting muscle invasion in bladder cancer to guide therapy decisions.Tumor-Heterogenität stellt eine erhebliche Herausforderung für die Krebsbehandlung dar. Die Untersuchung großer Krebszelldatensätze mittels maschinellen Lernens (ML) ist daher vielversprechend, um Zusammenhänge zwischen genetischen Zelleigenschaften und Medikamentenwirksamkeit zu untersuchen und zur Therapieoptimierung zu nutzen. In dieser Arbeit präsentieren wir zelllinienbasierte ML-Modelle zur Personalisierung der Krebsbehandlung: Zunächst haben wir das bisher umfangreichste ML-Benchmarking zur Wirksamkeitsvorhersage von Krebsmedikamenten durchgeführt. Wir haben einen neuartigen ML-Ansatz entwickelt, der Vorhersagen für wirkstoffempfindliche Proben, die hochrelevant für die Therapieoptimierung sind, signifikant verbessert. Zudem haben wir ein Framework implementiert, welches garantiert, dass Klassifikations- und Regressionsmodelle benutzerdefinierte Zuverlässigkeitskriterien erfüllen. Ein Hauptziel personalisierter Medizin ist das Priorisieren von Medikamenten nach ihrer Wirksamkeit. Um die Effizienz verschiedener Medikamente vergleichbar zu machen, schlagen wir ein neues Sensitivitätsmaß vor, das Defizite existierender Maße behebt. Für Kombinationstherapien haben wir Modelle entworfen, die erstmals Dosis-spezifische Wirksamkeitsvorhersagen für Zelllinien ermöglichen, die nicht zum Modelltraining genutzt wurden. Zuletzt haben wir akkurate Modelle zur Vorhersage der Muskelinvasion in Blasentumoren entwickelt, um die Wahl einer geeigneten Behandlung zu unterstützen
Predicting complex drug interactions of CYP3A4, CYP3A5, and CYP2D6 substrates: Physiologically based pharmacokinetic modeling for individualized therapy
No full textPersonalized medicine and precision dosing strive to maximize therapeutic efficacy and safety by considering inter-patient variability in treatment decisions. Drug-gene (DGIs) and drug-drug interactions (DDIs) are leading causes of variability in drug response and adverse drug reactions. Clinical practice is complicated by their frequent co-occurrence, resulting in complex drug-drug-gene interactions (DDGIs). Due to the vast number of potential interactions, it is impossible to investigate all scenarios in clinical DD(G)I studies. Physiologically based pharmacokinetic (PBPK) modeling enables mechanistic predictions of clinically untested DD(G)Is and supports model-informed dose adaptations. In this thesis, new whole-body PBPK models are presented for the cytochrome P450 (CYP) 3A substrates tacrolimus, imatinib, and dasatinib. In addition, a comprehensive PBPK model network centered around CYP2D6 was built. The models’ and network’s predictive performance was evaluated across numerous complex DD(G)I scenarios. Beyond this, simulation of multiple clinically untested DD(G)Is and model-informed dose adaptations were conducted. Overall, this thesis showcases PBPK modeling as a promising framework to advance individualized therapy by bridging critical knowledge gaps between interaction study results and complex real-world scenarios.Die personalisierte Medizin und Präzisionsdosierung zielen darauf ab, die therapeutische Wirksamkeit und Sicherheit zu maximieren, indem sie interindividuelle Variabilität bei Behandlungsentscheidungen berücksichtigen. Arzneimittel-Gen- (DGIs) und Arzneimittel-Arzneimittel-Interaktionen (DDIs) sind Hauptursachen für ein variables Arzneimittelansprechen und unerwünschte Arzneimittelwirkungen. Ihr häufiges gemeinsames Auftreten als komplexe Arzneimittel-Arzneimittel-Gen-Interaktionen (DDGIs) erschwert die klinische Praxis. Die Vielzahl potenzieller Interaktionen macht es unmöglich, alle Szenarien in klinischen DD(G)I-Studien zu untersuchen. Die Physiologie-basierte Pharmakokinetik (PBPK) Modellierung ermöglicht mechanistische Vorhersagen klinisch ungetesteter DD(G)Is und unterstützt modellbasierte Dosisanpassungen. In dieser Arbeit werden neue Ganzkörper-PBPK-Modelle für die Cytochrom P450 (CYP) 3A-Substrate Tacrolimus, Imatinib und Dasatinib vorgestellt. Zudem wurde ein umfassendes PBPK-Modellnetzwerk rund um CYP2D6 gebaut. Die Vorhersageleistung der Modelle und des Netzwerks wurde in komplexen DD(G)I-Szenarien evaluiert. Darüber hinaus wurden mehrere klinisch ungetestete DD(G)Is und modellgestützte Dosisanpassungen simuliert. Insgesamt zeigt die Arbeit die PBPK-Modellierung als vielversprechenden Rahmen zur Weiterentwicklung der individualisierten Therapie durch die Überbrückung kritischer Wissenslücken zwischen Interaktionsstudienergebnissen und komplexen realen Szenarien
Party competition on European issues in the 2024 EP elections
Get PDFRecent developments have turned European integration from a “sleeping giant” into an active political issue. The Maastricht Treaty politicized Europe in national and European Parliament elections. Cross-border crises, like migration and environmental challenges, have further increased the importance of coordinated EU responses. Moreover, an entirely new family of Eurosceptic parties has emerged and consolidated over the past decade. Given that one of their main aims is to challenge and criticise the European Union (EU), Eurosceptic parties have a particular interest in European issues - the European polity as well as major European policies. Against this background, this paper examines whether and how political parties have emphasised these issues during the 2024 EP elections, compared to 2019, and contrasting Eurosceptic and mainstream parties. Drawing on annotated data from the 2019 Euromanifesto project, we fine-tune transformer-based deep learning multilingual models to detect parties' salience and positions on European polity and policy issues in nine countries during the 2024 EP elections. Our analyses show that the salience of European issues has increased on average, in particular for the EU polity. In terms of positions, we detect a pattern of increasing negativity of mainstream parties on European policy issues, such as migration and the environment, whereas Eurosceptic parties (in particular of the far-right) appear to have become less negative on the EU. In sum, our results suggest an increasing relevance of EU-wide issues, with different patterns of polarisation
Effekte eines zehnwöchigen individualisierten Kraft- und Ausdauertrainings auf ausgewählte Symptome des Post-COVID-Syndroms
Get PDFBeim Post-COVID-Syndrom handelt es sich um eine multisystemische chronische Erkran-kung, die nach einer Infektion mit SARS-CoV-2 auftreten kann. Obwohl eine Vielzahl unter-schiedlicher Symptome beschrieben wird, gilt chronische Fatigue als Leitsymptom. Etwa die Hälfte der Betroffenen zeigt zudem Anzeichen einer Post-exertionellen Malaise, die sich typi-scherweise in Form von Zustandsverschlechterungen nach körperlicher Belastung präsen-tiert. Trotz erster Befunde zu den Pathomechanismen ist die Pathophysiologie bisher noch nicht abschließend geklärt. Aktuelle Leitlinien empfehlen individualisiertes körperliches Trai-ning als Möglichkeit der Krankheitsbewältigung. Obwohl erste Studien die Wirksamkeit von körperlichem Training bestätigen, liegen auch Berichte von Zustandsverschlechterungen in-folge körperlicher Belastung vor. Bisher fehlen evidenzbasierte Ansätze zur Individualisierung der Trainingstherapie beim Post-COVID-Syndrom.
Aus diesem Grund wurde eine zehnwöchige randomisiert-kontrollierte Multicenter-Studie durchgeführt, die die Wirksamkeit eines individualisierten und symptomorientierten Kraft- und Ausdauertrainings bei Post-COVID-Betroffenen untersucht. Hierfür wurden Personen, die die Diagnosekriterien des Post-COVID-Syndroms erfüllten und chronische Fatigue aufwiesen, in zwei Gruppen randomisiert. Die Interventionsgruppe (INT) trainierte über zehn Wochen in einer von 19 kommerziellen Fitness- und Gesundheitseinrichtungen, während die Warte-Kontrollgruppe (KON) in dieser Zeit ihre Lebensgewohnheiten beibehielt. Hauptzielparameter waren Fatigue (Fatigue Severity Scale, FSS), gesundheitsbezogene Lebensqualität (Short Form 12, SF-12) sowie die funktionelle Ausdauer (Chester Step Test, CST) und Para-meter der Handgriffkraft. Darüber hinaus wurden Parameter der objektiven Fatigability sowie der Post-exertionellen Malaise (DePaul Symptom Questionnaire-Post Exertional Malaise, DSQ-PEM) erfasst. In die finale Datenauswertung wurden 118 Personen (KON: n = 60, INT: n = 58) eingeschlossen. Die individuelle Trainingsbelastung wurde entsprechend der ta-gesaktuellen Fatigue angepasst. Die Ergebnisse zeigten eine signifikante Reduktion der Fati-gue (FSS: -1,14) sowie signifikante Verbesserungen der psychischen (SF-12: 5,94) und phy-sischen gesundheitsbezogenen Lebensqualität (SF-12: 4,33) in der Interventionsgruppe im Vergleich zur Kontrollgruppe. Auch die funktionelle Ausdauer (CST: 22,72 Schritte) sowie die maximale (1,45 kg) und mittlere Handgriffkraft (1,97 kg) verbesserte sich in INT signifikant im Vergleich zu KON. Die Intervention hatte keinen Effekt auf die Fatigability sowie den DSQ-PEM. Das Training war nicht mit einem erhöhten Risiko für eine Zustandsverschlechterung assoziiert.
Die Studie weist nach, dass ein individualisiertes und symptomorientiertes Kraft- und Ausdau-ertraining in kommerziellen Fitness- und Gesundheitseinrichtungen eine effektive Maßnahme zur Verbesserung der Fatigue, der gesundheitsbezogenen Lebensqualität und der körperli-chen Leistungsfähigkeit beim Post-COVID-Syndrom darstellt. Erhöhte DSQ-PEM-Werte stel-len dabei keine absolute Kontraindikation dar, sofern das Training individualisiert und symp-tomorientiert erfolgt. Die Anpassung der Belastung an die tagesaktuelle Fatigue hat sich als praktikabler und wirksamer Ansatz zur Steuerung der Belastung bei dieser Patientengruppe erwiesen.Post-COVID syndrome is a multisystemic chronic condition that can occur following an infec-tion with SARS-CoV-2. Although a wide variety of symptoms have been described, chronic fatigue is considered the leading symptom. Around half of those affected also show signs of post-exertional malaise, which typically manifests as a worsening of symptoms following physical exertion. Despite first findings on the underlying mechanisms, the pathophysiology is not yet fully understood. Current guidelines recommend individualized physical training as a way to alleviate symptoms. While initial studies confirm the effectiveness of physical exer-cise, there are also reports of deteriorations in condition due to exertion. So far, evidence-based approaches for individualizing exercise therapy in post-COVID syndrome are lacking.
For this reason, a ten-week randomized controlled multicentre study was conducted to exam-ine the effectiveness of individualized and symptom-titrated resistance and aerobic training in individuals affected by post-COVID. Participants who met the diagnostic criteria for post-COVID syndrome and reported chronic fatigue were randomly assigned to two groups. The intervention group (INT) trained over ten weeks in one of 19 commercial fitness and health centres, while the waitlist control group (KON) maintained their usual lifestyle during this time. Primary outcome measures included fatigue (Fatigue Severity Scale, FSS), health-related quality of life (Short Form 12, SF-12), as well as functional aerobic capacity (Chester Step Test, CST) and handgrip strength parameters. Additionally, parameters of objective fatigability and post-exertional malaise (DePaul Symptom Questionnaire–Post Exertional Malaise, DSQ-PEM) were obtained. A total of 118 individuals (KON: n = 60, INT: n = 58) were included in the final data analysis. Training intensity was adapted to the participants’ daily fatigue levels.
The results showed a significant reduction in fatigue (FSS: -1.14) as well as significant im-provements in mental (SF-12: 5.94) and physical health-related quality of life (SF-12: 4.33) in the intervention group compared to the control group. Functional aerobic capacity (CST: +22.72 steps) as well as maximum (1.45 kg) and average handgrip strength (1.97 kg) also improved significantly in INT compared to KON. The intervention had no effect on fa-tigability or the DSQ-PEM scores. The training was not associated with an increased risk of symptom worsening.
The study demonstrates that individualized and symptom-titrated resistance and aerobic train-ing in commercial fitness and health facilities is an effective intervention to improve fatigue, health-related quality of life, and physical performance in individuals with post-COVID syn-drome. Elevated DSQ-PEM scores do not represent an absolute contraindication, provided that training is individualized and symptom-titrated. Adjusting the training load according to daily fatigue has proven to be a practical and effective approach for load management in this patient population
Analyse akuter respiratorischer Infektionen in den beiden saarländischen Häusern der Maximalversorgung zur Entwicklung einer Sentinel-Infektions-Surveillance schwerer akuter respiratorischer Erkrankungen
Get PDFZiel dieser Analyse akuter respiratorischer Infektionen in den beiden
saarländischen Häusern der Maximalversorgung dient der Entwicklung eines
ganzjährigen saarländischen Überwachungssystems schwerer akuter
respiratorischer Erkrankungen (SARI). Des Weiteren soll ein effizientes
Frühmeldewarnsystem in die vorhandenen Überwachungsmaßnahmen akuter
respiratorischer Erkrankungen (ARE) integriert werden, sowie die nötigen
Strukturen dazu geschaffen und ausgebaut werden.
Im Hinblick auf Relevanz und Aussagekraft dieser Sentinel-Surveillance ergibt sich
dabei als Erfordernis, dass diese Strukturanpassung die bundesweiten Standards
zur Überwachung schwerer akuter respiratorischer Erkrankungen erreicht.
Mittels anonymisierter Patientendaten der beiden saarländischen Häuser der
Maximalversorgung, dem Universitätsklinikum des Saarlandes sowie dem
Winterbergklinikum Saarbrücken, wurde eine syndromische ICD-10-Code basierte
Auswertung schwerer akuter respiratorischer Infektionen (ICOSARI) der Jahre
2015 bis 2019 durchgeführt. Die Entwicklung des Frühmeldewarnsystems erfolgte
über Anwendung deskriptiver sowie induktiver statistischer Verfahren.
Die Ergebnisse zeigen, dass es zwischen den Häusern keine Unterschiede
bezüglich der Infektionsdynamik gab. Generell ist die Gruppe der über 60-jährigen
Patienten für schwere respiratorische Erkrankungen prädisponiert. Weiterhin
konnte gezeigt werden, dass Patienten, die innerhalb von sieben Tagen entlassen
wurden, ein geringeres Risiko haben, intensivmedizinisch betreut zu werden oder
sogar zu sterben. Eine Übersterblichkeit auf Grund von SARI konnte für keines der
beiden Krankenhäuser nachgewiesen werden.
Auf Grund der geographischen Lage des Universitätsklinikum des Saarlandes und
des Winterbergklinikums Saarbrücken wurden die meisten Fälle schwerer akuter
respiratorischer Erkrankungen besonders im süd-östlichen Saarland
nachgewiesen. Außerdem konnte anhand der zeitlichen Darstellung der Fälle pro
Kalenderwoche erkannt werden, dass es zwar Schwankungen in der Schwere
einer Infektionssaison gibt, es jedoch immer um die 10. Kalenderwoche zum Peak
an Fällen mit schweren akuten respiratorischen Erkrankungen kam.
Auffällig bei der Auswertung der Grenzwerte des Frühmeldewarnsystems war,
dass gewisse Ausreißer permanent außerhalb der Grenzbereiche liegen - und das
unabhängig von der Reichweite des Grenzbereiches.
In Kombination der Grenzwerte mit der Regressionsformel konnte ein Bereich
definiert werden, der einen Großteil der Daten in Bezug auf den saisonalen SARI-Verlauf schätzen lässt, so dass Werte, die zwischen Regressionskurve und oberem
Grenzwert liegen, als auffällig markiert werden können. Dadurch steht ein
Instrument zur Früherkennung und Vorhersagbarkeit schwerer Saisonverläufe
akuter respiratorischer Erkrankungen zur Verfügung.The aim of this study is to develop a year-round surveillance system for severe
acute respiratory illnesses (SARI) in Saarland. Furthermore, an efficient early
warning system is to be integrated into the existing surveillance measures for acute
respiratory illnesses (ARE) and the necessary structures are to be created and
expanded.
This structural adjustment must therefore meet the nationwide standards for
monitoring severe acute respiratory diseases in terms of compatibility and
comparability.
A syndromic ICD-10 code-based evaluation was carried out using anonymized
patients from the two maximum care centers in Saarland, the Saarland University
Hospital and the Saarbrücken Clinic. The early warning system was installed using
descriptive and inductive statistical methods.
The results show that there were no differences in infection dynamics between the
houses. In general, the group of patients over 60 years old is predisposed to severe
respiratory diseases. It has been shown that patients who are discharged within 7
days have a lower risk of needing intensive care or even dying. Excess mortality
due to SARI could not be identified at either hospital
Severe acute respiratory illnesses were particularly noted in the areas surrounding
hospitals. In addition, based on the temporal representation of the cases per
calendar week, it could be seen that there are fluctuations in the severity of an
infection season, but that the peak of cases of severe respiratory cases always
occurred around the 10th calendar week.
What is striking when evaluating the limit values of the early warning system is that,
regardless of the range of the limit area, certain outliers are permanently outside
the limit areas.
In combination with the regression formula, a range could be defined that can
estimate a large part of the data, so that values that lie between the regression
curve and the upper limit can be marked as suspicious. This provides an instrument
for the early detection of severe seasonal courses of acute respiratory disease
Strongyloides stercoralis Infection in Humans in West Africa, 1975–2024: Systematic Review and Meta-Analysis
Get PDFStrongyloidiasis is an underappreciated helminth infection that belongs to a group of
neglected tropical diseases. The aim of this systematic review and meta-analysis was to
determine the pooled prevalence of Strongyloides stercoralis infection in humans in 16 West
African countries. We searched African Journals Online, Embase, Horizon, Google Scholar,
ProQuest, PubMed, Scopus, and Web of Science to identify articles assessing S. stercoralis
prevalence data. The search was restricted to articles published between 1 January 1975
and 31 December 2024 without language restriction. We followed the PRISMA guidelines.
A total of 21,250 articles were identified, 336 of which met the inclusion criteria. The most
frequently used diagnostic tools were Kato-Katz (35.1%) and formol-ether coprological
methods (23.4%). Strongyloidiasis was reported in 15 of the 16 West African countries;
Mali was the only country where it was absent. The S. stercoralis regional prevalence was
4.4%, ranging from 0.2% in Burkina Faso to 18.9% in The Gambia. S. stercoralis infection
prevalence decreased from 14.0% (1975–1984) to 4.1% (2015–2024). S. stercoralis prevalence
showed strong heterogeneity with the highest prevalence mainly observed in countries
in the Gulf of Guinea. Most of the employed diagnostic techniques were inappropriate;
the reported S. stercoralis prevalence is, thus, likely an underestimation of the true situa tion. Our observations call for more sensitive S. stercoralis diagnostic tools and strategies
for strongyloidiasis control that are tailored to the different social-ecological settings of
West Africa
Influenza Immunization in Very-Low-Birth-Weight Infants: Epidemiology and Long-Term Outcomes
Get PDFBackground: Very-low-birth-weight infants (VLBWIs; birth weight < 1500 g)
are at an increased risk of complicated influenza infection, which frequently includes
pneumonia, encephalitis or even death. Data on influenza immunization and its outcome
in VLBWIs are scarce. This study aimed to provide epidemiological data on influenza
immunization for German VLBWIs and hypothesized that immunization would protect
VLBWIs from infection-mediated neurodevelopmental impairment and preserves lung
function at early school age. Methods: In this observational population-based German
Neonatal Network (GNN) study, infants born between 2009 and 2015 were invited to partake in a 6-year follow-up investigation including lung function and developmental testing.
Uni- and multivariate analyses were performed to evaluate the clinical characteristics and
outcomes of influenza-immunized VLBWIs compared to non-immunized VLBWIs. Results:
Influenza immunization was performed in 871 out of the 3358 VLBWIs (26%) with six-year
follow-up. Immunized infants were characterized by a low gestational age and higher rates
of morbidity, particularly bronchopulmonary dysplasia. Although early immunization
showed no safety signals and had protective effects on the long-term risk of bronchitis
(OR: 0.2; CI: 0.1–0.6; p = 0.002), most VLBWIs (88.0%) were unimmunized in their first
influenza season. Conclusions: Influenza immunization was not associated with improved
lung function (forced expiratory volume in one second and forced vital capacity) or a better
neurocognitive outcome (intelligence quotient and strengths and difficulties questionnaire) at early school age. In Germany, only one quarter of 6-year-old VLBWIs were immunized
against influenza, particularly those born <28 gestational weeks and/or BPD. Specific influenza immunization guidelines that define evidence-based recommendations are needed
for this vulnerable group
AlkaPhos: a novel fluorescent probe as a potential point-of-care diagnostic tool to estimate recurrence risk of meningiomas
Get PDFDeletion of the short arm of chromosome 1 (1p) increases recurrence rates in meningiomas by up to 33%, regardless of
tumor grade, correlating with absence of intracellular alkaline phosphatase enzyme activity. Current screening methods for
1p deletion like fluorescence in situ hybridization (FISH) and loss of heterozygosity (LOH) analysis are resource-intensive.
This study evaluated AlkaPhos, a novel fluorescent probe, for detecting alkaline phosphatase in meningioma cells and
compared findings with FISH, LOH, and histochemical analysis. AlkaPhos sensitivity in detecting alkaline phosphatase
on BEN-MEN-1 cells and primary meningioma cultures was assessed via microscopic fluorescent ratio measurements.
FISH and LOH were conducted on the same tumors to detect 1p deletions. Histochemical analysis served as a reference.
AlkaPhos results were compared with FISH, LOH, and histochemical analysis. AlkaPhos effectively indicated alkaline
phosphatase activity in BEN-MEN-1 cells and correctly identified 1p deletion in 8/14 primary meningioma cultures,
matching FISH and LOH findings, respectively. AlkaPhos showed potential superiority over histochemical analysis in
identifying tumors with 1p deletion and LOH of 1p. AlkaPhos bears potential as a future diagnostic tool for identifying
alkaline phosphatase absence in meningiomas, indicative of 1p deletion. Further evaluation on a larger sample size is
necessary for routine clinical application