Non-Universal Critical Behaviour of Two-Dimensional Ising Systems

Two conditions are derived for Ising models to show non-universal critical behaviour, namely conditions concerning 1) logarithmic singularity of the specific heat and 2) degeneracy of the ground state. These conditions are satisfied with the eight-vertex model, the Ashkin-Teller model, some Ising models with short- or long-range interactions and even Ising systems without the translational or the rotational invariance.Comment: 17 page

Prospective evaluation of NGS-based sequencing in epilepsy patients: results of seven NASGE-associated diagnostic laboratories

BackgroundEpilepsy is one of the most common and disabling neurological disorders. It is highly prevalent in children with neurodevelopmental delay and syndromic diseases. However, epilepsy can also be the only disease-determining symptom. The exact molecular diagnosis is essential to determine prognosis, comorbidity, and probability of recurrence, and to inform therapeutic decisions.Methods and materialsHere, we describe a prospective cohort study of patients with epilepsy evaluated in seven diagnostic outpatient centers in Germany. Over a period of 2 months, 07/2022 through 08/2022, 304 patients (317 returned result) with seizure-related human phenotype ontology (HPO) were analyzed. Evaluated data included molecular results, phenotype (syndromic and non-syndromic), and sequencing methods.ResultsSingle exome sequencing (SE) was applied in half of all patients, followed by panel (P) testing (36%) and trio exome sequencing (TE) (14%). Overall, a pathogenic variant (PV) (ACMG cl. 4/5) was identified in 22%; furthermore, a significant number of patients (12%) carried a reported clinically meaningful variant of unknown significance (VUS). The average diagnostic yield in patients ≤ 12 y was higher compared to patients >12 y cf. Figure 2B vs. Figure 3B. This effect was more pronounced in cases, where TE was applied in patients ≤ 12 vs. >12 y [PV (PV + VUS): patients ≤ 12 y: 35% (47%), patients > 12 y: 20% (40%)]. The highest diagnostic yield was achieved by TE in syndromic patients within the age group ≤ 12 y (ACMG classes 4/5 40%). In addition, TE vs. SE had a tendency to result in less VUS in patients ≤ 12 y [SE: 19% (22/117) VUS; TE: 17% (6/36) VUS] but not in patients >12 y [SE: 19% (8/42) VUS; TE: 20% (2/10) VUS]. Finally, diagnostic findings in patients with syndromic vs. non-syndromic symptoms revealed a significant overlap of frequent causes of monogenic epilepsies, including SCN1A, CACNA1A, and SETD1B, confirming the heterogeneity of the associated conditions.ConclusionIn patients with seizures—regardless of the detailed phenotype—a monogenic cause can be frequently identified, often implying a possible change in therapeutic action (36.7% (37/109) of PV/VUS variants); this justifies early and broad application of genetic testing. Our data suggest that the diagnostic yield is highest in exome or trio-exome-based testing, resulting in a molecular diagnosis within 3 weeks, with profound implications for therapeutic strategies and for counseling families and patients regarding prognosis and recurrence risk

Gambling kick or content motivation - what is really initialized by the introduction of software into medical biometry lessons???

Bachground: Teaching statistics to members of non-mathematical disciplines becomes increasingly based on the involvement of interactive learning software. The latter is expected to both increase understanding and motivation and thereby as well studential acceptance. The teaching model implemented at the Medical Biometry Department in Mainz will be used to consider the value of introducing an interactive software like SPSS® into biometry lessons by means of studential evaluations.Methods: After an introductory lecture series, the participants of the Medical Biometry (formerly "Biomathematics") practical courses are requested to solve real data exercises by means of the software SPSS®, where each lessons aims to the derivation of a result synopsis summarizing the results of the performed statistical analyses. In summer 2002 the students of this course were asked to fill out a standardized teaching quality assessment questionnaire on the acceptance of the previous lecture series, the practical course lessons and the involvement of the software.Results: Between the 7 parallel courses the fraction of students reporting "good management with SPSS" varies between 43% and 88% (pooled estimate 58%), but among these students only 30% report a good / very good understanding of the lessons' context and only 15% a good / very good learning effect. Among students with "problems in SPSS management" these fractions both turned out 13%. Among the students with "good management with SPSS", however, 70% considered the understanding during the lecture series as good / very good, 73% reported a good / very good learning effect for the lectures; among the other students both fractions were 13%. These subgrupus only differed significantly for the questionnaire dimension "content motivation" (Likelihood Ratio p<0.001 after correction for teacher effects). Neither the lessons' structure (p=0.362), their relation to the introductory lecture series (p=0.165) nor the teachers' personal and didactical skills (p=0.407) differed significantly between the subgroups of students with and without acceptance of SPSS®.Conclusion: Introduction of a software like SPSS® can only slightly raise studential understanding and subject-associated motivation, but can hardly create them. However, it must be considered by means of independent evaluations, how far these findings can be transferred to the impact of interactive learning tools on students' motivation and acceptance.Hintergrund: Derzeit werden vor allem im Statistik-Unterricht für Anwender zahlreiche interaktive Software- und Lernsysteme entwickelt, von welchen sich neben einer Erhöhung des Verständnisses auch eine Steigerung der Motivation und damit auch der Akzeptanz des Unterrichts bei den Anwendern versprochen wird. Am Mainzer Unterrichtsmodell, welches seit mehreren Jahren die Kurse der Medizinischen Biometrie mit der Software SPSS® durchführt, sollte anhand studentischer Bewertung diese Hoffnung überprüft werden.Methoden: Nach einer vorbereitenden Intensivvorlesung werden im Praktikum der Medizinischen Biometrie (ehemals "Biomathematik") in Mainz von den Studierenden Aufgaben mittels SPSS® bearbeitet, wobei das Ziel jeder Doppelstunde im wesentlichen die Erstellung einer Ergebnissynopse ist. Im Rahmen des Qualitätsmanagements in der Lehre wurden im Sommersemester 2002 von den Studierenden des ersten klinischen Semesters Angaben zur Akzeptanz dieses Kurses, der vorbereitenden Vorlesung und vor allem des den Kurs unterstützenden SPSS® mittels eines standardisierten Evaluationsbogens erhoben.Ergebnisse: Der Anteil Studierender, die nach eigener Einschätzung "gut mit SPSS zurecht gekommen" sind, variiert in den 7 parallelen Kursen zwischen 43% und 88% (gepoolter Anteil 58%). Unter diesen Studierenden berichten jedoch nur 30% ein gutes / sehr gutes Verständnis des Praktikumsstoffes, 15% einen guten / sehr guten Lerneffekt im Praktikum. Unter den Studierenden, die nach eigener Angabe "nicht gut mit SPSS zurecht gekommen" sind, betragen diese Anteile jeweils 13%. Unter den Studierenden, die "gut mit SPSS zurecht gekommen" sind, attestieren ferner 70% der einführenden Vorlesung eine gute / sehr gute Verständlichkeit sowie 73% einen guten / sehr guten Lerneffekt; unter den anderen Studierenden betragen diese Anteile jeweils 66%. Nur im Fragebogen-Aspekt "inhaltliche Motivation" zeigt sich beim Vergleich dieser beiden Gruppen Studierender ein signifikanter Unterschied (Likelihood Ratio p<0.001 nach Korrektur für Kursleitereffekte). Weder für die Struktur des Praktikums (p=0.362), dessen Verknüpfung mit der Vorlesung (p=0.165) noch die Kommunikation und Didaktik (p=0.407) zeigten sich nach Korrektur für Dozenteneffekte nennenswerte Tendenzen zugunsten einer positiveren Bewertung des Kurs bei Akzeptanz von SPSS®.Schlussfolgerung: Mit dem Einbezug einer Software wie SPSS® in den Unterricht können Verständnis und Motivation des für Anwender zumeist schwer zugänglichen Stoffes der Medizinischen Biometrie bestenfalls gesteigert, aber in keinem relevanten Maß geweckt werden. Wie weit diese Erkenntnisse auf explizit für den Unterricht konzipierte Lernsoftware übertragen werden können, muss in unabhängigen Evaluationen überprüft werden