Improving Patient Pre-screening for Clinical Trials: Assisting Physicians with Large Language Models

Physicians considering clinical trials for their patients are met with the laborious process of checking many text based eligibility criteria. Large Language Models (LLMs) have shown to perform well for clinical information extraction and clinical reasoning, including medical tests, but not yet in real-world scenarios. This paper investigates the use of InstructGPT to assist physicians in determining eligibility for clinical trials based on a patient's summarised medical profile. Using a prompting strategy combining one-shot, selection-inference and chain-of-thought techniques, we investigate the performance of LLMs on 10 synthetically created patient profiles. Performance is evaluated at four levels: ability to identify screenable eligibility criteria from a trial given a medical profile; ability to classify for each individual criterion whether the patient qualifies; the overall classification whether a patient is eligible for a clinical trial and the percentage of criteria to be screened by physician. We evaluated against 146 clinical trials and a total of 4,135 eligibility criteria. The LLM was able to correctly identify the screenability of 72% (2,994/4,135) of the criteria. Additionally, 72% (341/471) of the screenable criteria were evaluated correctly. The resulting trial level classification as eligible or ineligible resulted in a recall of 0.5. By leveraging LLMs with a physician-in-the-loop, a recall of 1.0 and precision of 0.71 on clinical trial level can be achieved while reducing the amount of criteria to be checked by an estimated 90%. LLMs can be used to assist physicians with pre-screening of patients for clinical trials. By forcing instruction-tuned LLMs to produce chain-of-thought responses, the reasoning can be made transparent to and the decision process becomes amenable by physicians, thereby making such a system feasible for use in real-world scenarios.Comment: 11 pages, 4 tables, 2 figure

Gene expression-based classification of non-small cell lung carcinomas and survival prediction

Background: Current clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Gene expression profiling holds promise to improve clinical stratification, thus paving the way for individualized therapy. Methodology and Principal Findings:A genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples. We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of non-small cell lung cancer. Correlation analysis identified 17 genes which showed the best association with post-surgery survival time. This signature was used for stratification of all patients in two risk groups. Kaplan-Meier survival curves show that the two groups display a significant difference in post-surgery survival time (p = 5.6E-6). The performance of the signatures was validated using a patient cohort of similar size (Duke University, n = 96). Compared to previously published prognostic signatures for NSCLC, the 17 gene signature performed well on these two cohorts. Conclusions:The gene signatures identified are promising tools for histo-pathological classification of non-small cell lung cancer, and may improve the prediction of clinical outcome

Dnmt3bregulates DUX4 expression in a tissue-dependent manner in transgenic D4Z4 mice

Background Facioscapulohumeral muscular dystrophy (FSHD) is a skeletal muscle disorder that is caused by derepression of the transcription factor DUX4 in skeletal muscle cells. Apart from SMCHD1, DNMT3B was recently identified as a disease gene and disease modifier in FSHD. However, the exact role of DNMT3B at the D4Z4 repeat array remains unknown. Methods To determine the role of Dnmt3b on DUX4 repression, hemizygous mice with a FSHD-sized D4Z4 repeat array (D4Z4-2.5 mice) were cross-bred with mice carrying an in-frame exon skipping mutation inDnmt3b(Dnmt3b(MommeD14)mice). Additionally, siRNA knockdowns ofDnmt3bwere performed in mouse embryonic stem cells (mESCs) derived from the D4Z4-2.5 mouse model. Results In mESCs derived from D4Z4-2.5 mice, Dnmt3b was enriched at the D4Z4 repeat array and DUX4 transcript levels were upregulated after a knockdown ofDnmt3b. In D4Z4-2.5/Dnmt3b(MommeD14)mice, Dnmt3b protein levels were reduced; however, DUX4 RNA levels in skeletal muscles were not enhanced and no pathology was observed. Interestingly, D4Z4-2.5/Dnmt3b(MommeD14)mice showed a loss of DNA methylation at the D4Z4 repeat array and significantly higher DUX4 transcript levels in secondary lymphoid organs. As these lymphoid organs seem to be more sensitive to epigenetic modifiers of the D4Z4 repeat array, different immune cell populations were quantified in the spleen and inguinal lymph nodes of D4Z4-2.5 mice crossed with Dnmt3b(MommeD14)mice or Smchd1(MommeD1)mice. Only in D4Z4-2.5/Smchd1(MommeD1)mice the immune cell populations were disturbed. Conclusions Our data demonstrates that loss of Dnmt3b results in derepression of DUX4 in lymphoid tissues and mESCs but not in myogenic cells of D4Z4-2.5/Dnmt3b(MommeD14)mice. In addition, the Smchd1(MommeD1)variant seems to have a more potent role in DUX4 derepression. Our studies suggest that the immune system is particularly but differentially sensitive to D4Z4 chromatin modifiers which may provide a molecular basis for the yet underexplored immune involvement in FSHD.Functional Genomics of Muscle, Nerve and Brain Disorder

Deconfinement Transition and Bound States in Frustrated Heisenberg Chains: Regimes of Forced and Spontaneous Dimerization

We use recently developed strong-coupling expansion methods to study the two-particle spectra for the frustrated alternating Heisenberg model, consisting of an alternating nearest neighbor antiferromagnetic exchange and a uniform second neighbor antiferromagnetic exchange. Starting from the limit of weakly coupled dimers, we develop high order series expansions for the effective Hamiltonian in the two-particle subspace. In the limit of a strong applied dimerization, we calculate accurately various properties of singlet and triplet bound states and quintet antibound states. We also develop series expansions for bound state energies in various sectors, which can be extrapolated using standard methods to cases where the external bond-alternation goes to zero. We study the properties of singlet and triplet bound states in the latter limit and suggest a crucial role for the bound states in the unbinding of triplets and deconfinement of spin-half excitations.Comment: 17 figures, revte

The Hamiltonian limit of (3+1)D SU(3) lattice gauge theory on anisotropic lattices

The extreme anisotropic limit of Euclidean SU(3) lattice gauge theory is examined to extract the Hamiltonian limit, using standard path integral Monte Carlo (PIMC) methods. We examine the mean plaquette and string tension and compare them to results obtained within the Hamiltonian framework of Kogut and Susskind. The results are a significant improvement upon previous Hamiltonian estimates, despite the extrapolation procedure necessary to extract observables. We conclude that the PIMC method is a reliable method of obtaining results for the Hamiltonian version of the theory. Our results also clearly demonstrate the universality between the Hamiltonian and Euclidean formulations of lattice gauge theory. It is particularly important to take into account the renormalization of both the anisotropy, and the Euclidean coupling $\beta_E$, in obtaining these results.Comment: 10 pages, 11 figure

Systemic delivery of a DUX4-targeting antisense oligonucleotide to treat facioscapulohumeral muscular dystrophy

Facioscapulohumeral muscular dystrophy (FSHD) is one of the most prevalent skeletal muscle dystrophies. Skeletal muscle pathology in individuals with FSHD is caused by inappropriate expression of the transcription factor DUX4, which activates different myotoxic pathways. At the moment there is no molecular therapy that can delay or prevent skeletal muscle wasting in FSHD. In this study, a systemically delivered antisense oligonucleotide (ASO) targeting the DUX4 transcript was tested in vivo in ACTA1-MCM;FLExDUX4 mice that express DUX4 in skeletal muscles. We show that the DUX4 ASO was well tolerated and repressed the DUX4 transcript, DUX4 protein, and mouse DUX4 target gene expression in skeletal muscles. In addition, the DUX4 ASO alleviated the severity of skeletal muscle pathology and partially prevented the dysregulation of inflammatory and extracellular matrix genes. DUX4 ASOtreated ACTA1-MCM;FLExDUX4 mice performed better on a treadmill; however, the hanging grid and four-limb grip strength tests were not improved compared to control ASOtreated ACTA1-MCM;FLExDUX4 mice. This study shows that systemic delivery of ASOs targeting DUX4 is a promising therapeutic strategy for FSHD and strategies that further improve the ASO efficacy in skeletal muscle are warranted.Functional Genomics of Muscle, Nerve and Brain Disorder

Ground State Magnetization of Polymerized Spin Chains

We investigate the ground state magnetization plateaus appearing in spin 1/2 polymerized Heisenberg chains under external magnetic fields. The associated fractional quantization scenario and the exponents which characterize the opening of gapful excitations are analyzed by means of abelian bosonization methods. Our conclusions are fully supported by the extrapolated results obtained from Lanczos diagonalizations of finite systems.Comment: 5 pages, 6 figures, final version to appear in Phys.Rev.

The Critical Behaviour of the Spin-3/2 Blume-Capel Model in Two Dimensions

The phase diagram of the spin-3/2 Blume-Capel model in two dimensions is explored by conventional finite-size scaling, conformal invariance and Monte Carlo simulations. The model in its $\tau$-continuum Hamiltonian version is also considered and compared with others spin-3/2 quantum chains. Our results indicate that differently from the standard spin-1 Blume-Capel model there is no multicritical point along the order-disorder transition line. This is in qualitative agreement with mean field prediction but in disagreement with previous approximate renormalization group calculations. We also presented new results for the spin-1 Blume-Capel model.Comment: latex 18 pages, 4 figure

Smchd1 haploinsufficiency exacerbates the phenotype of a transgenic FSHD1 mouse model

Functional Genomics of Muscle, Nerve and Brain Disorder

Dynamic Critical Behavior of a Swendsen-Wang-Type Algorithm for the Ashkin-Teller Model

We study the dynamic critical behavior of a Swendsen-Wang-type algorithm for the Ashkin--Teller model. We find that the Li--Sokal bound on the autocorrelation time ($\tau_{{\rm int},{\cal E}} \ge {\rm const} \times C_H$) holds along the self-dual curve of the symmetric Ashkin--Teller model, and is almost but not quite sharp. The ratio $\tau_{{\rm int},{\cal E}} / C_H$ appears to tend to infinity either as a logarithm or as a small power ($0.05 \leq p \leq 0.12$). In an appendix we discuss the problem of extracting estimates of the exponential autocorrelation time.Comment: 59 pages including 3 figures, uuencoded g-compressed ps file. Postscript size = 799740 byte