LLM-Powered Conversational Voice Assistants: Interaction Patterns, Opportunities, Challenges, and Design Guidelines

Conventional Voice Assistants (VAs) rely on traditional language models to discern user intent and respond to their queries, leading to interactions that often lack a broader contextual understanding, an area in which Large Language Models (LLMs) excel. However, current LLMs are largely designed for text-based interactions, thus making it unclear how user interactions will evolve if their modality is changed to voice. In this work, we investigate whether LLMs can enrich VA interactions via an exploratory study with participants (N=20) using a ChatGPT-powered VA for three scenarios (medical self-diagnosis, creative planning, and debate) with varied constraints, stakes, and objectivity. We observe that LLM-powered VA elicits richer interaction patterns that vary across tasks, showing its versatility. Notably, LLMs absorb the majority of VA intent recognition failures. We additionally discuss the potential of harnessing LLMs for more resilient and fluid user-VA interactions and provide design guidelines for tailoring LLMs for voice assistance

Diagnostic accuracy of tumor necrosis factor-alpha, interferon-gamma, interlukine-10 and adenosine deaminase 2 in differential diagnosis between tuberculous pleural effusion and malignant pleural effusion

BACKGROUND: The current study was performed to investigate the potential biomarkers for the differential diagnosis of tuberculous pleural effusion (TPE) and malignant pleural effusions (MPE). METHODS: Among ninety patients (n = 90) involved in the study, 47 with tuberculous pleural effusion aged from 18 to 70 and 43 with secondary malignant pleural effusion aged from 34 to 78. We tested the pleural levels of TNF-α, IFN-γ and IL-10 as well as the enzyme activity of ADA(2), and then we compared the differential diagnostic efficiencies of those biochemical parameters with ADA between the two groups. RESULTS: Our results show that, the concentrations of pleural TNF-α (45.55 ± 15.85 ng/L), IFN-γ (114.97 ± 27.85 ng/L) as well as activities of ADA(2) (35.71 ± 10.00 U/L) and ADA (39.39 ± 10.60 U/L) in tuberculous group were significantly higher compared to malignant group. Furthermore, according to the ROC curve analysis the thresholds of TNF-α, IFN-γ, ADA(2) and ADA were found to be 30.3 ng/L, 103.65 ng/L, 29.45 U/L, and 39.00 U/L, respectively. TNF-α, IFN-γ and ADA(2) yielded better sensitivity, specificity, and accuracy of the diagnosis than ADA. Our investigation further revealed that the combinations of TNF-α and ADA(2) further increased the specificity and accuracy for the differential diagnosis. CONCLUSION: In conclusion, we found that TNF-α, IFN-γ, ADA and ADA(2) all increased in TPE. Combinations of the TNF-α and ADA(2) yielded the best specificity and accuracy for the differential diagnosis of TPE from MPE. Our investigation suggests that the applications of TNF-α together with ADA(2) may contribute to more efficient diagnosis strategies in the management of discrimination between tuberculous and malignant pleural effusions

Tensor-network-assisted variational quantum algorithm

Near-term quantum devices generally suffer from shallow circuit depth and hence limited expressivity due to noise and decoherence. To address this, we propose tensor-network-assisted parametrized quantum circuits, which concatenate a classical tensor-network operator with a quantum circuit to effectively increase the circuit's expressivity without requiring a physically deeper circuit. We present a framework for tensor-network-assisted variational quantum algorithms that can solve quantum many-body problems using shallower quantum circuits. We demonstrate the efficiency of this approach by considering two examples of unitary matrix-product operators and unitary tree tensor networks, showing that they can both be implemented efficiently. Through numerical simulations, we show that the expressivity of these circuits is greatly enhanced with the assistance of tensor networks. We apply our method to two-dimensional Ising models and one-dimensional time-crystal Hamiltonian models with up to 16 qubits and demonstrate that our approach consistently outperforms conventional methods using shallow quantum circuits.Comment: 12 pages, 8 figures, 37 reference

Constitutive model for the rheology of biological tissue

The rheology of biological tissue is key to processes such as embryo development, wound healing and cancer metastasis. Vertex models of confluent tissue monolayers have uncovered a spontaneous liquid-solid transition tuned by cell shape; and a shear-induced solidification transition of an initially liquid-like tissue. Alongside this jamming/unjamming behaviour, biological tissue also displays an inherent viscoelasticity, with a slow time and rate dependent mechanics. With this motivation, we combine simulations and continuum theory to examine the rheology of the vertex model in nonlinear shear across a full range of shear rates from quastistatic to fast, elucidating its nonlinear stress-strain curves after the inception of shear of finite rate, and its steady state flow curves of stress as a function of strain rate. We formulate a rheological constitutive model that couples cell shape to flow and captures both the tissue solid-liquid transition and its rich linear and nonlinear rheology.Comment: 5 pages, 3 figures; plus supplemental materia

Cell-Free DNA Sequencing of Intraocular Fluid as Liquid Biopsy in the Diagnosis of Vitreoretinal Lymphoma

PurposeTo seek novel diagnostic approaches, we improved the workflow of cell-free DNA (cfDNA) sequencing and evaluated its feasibility in vitreoretinal lymphoma (VRL) specimens; the profile of mutations was preliminarily analyzed for potential diagnostic value.MethodsThe study was a diagnostic trial. 23 eyes of 23 patients with VRL and 25 eyes of 25 patients with inflammatory eye diseases were enrolled. Approximate 500μl undiluted vitreous humor and 10ml diluted vitreous fluid was obtained through diagnostic vitrectomy and sent for cytopathological examinations. 500μl of the diluted vitreous fluid was spared for cfDNA sequencing. For cfDNA sequencing, DNA fragmentation procedure was added to the workflow to improve the extraction efficiency; mutations detected were analyzed for potential diagnostic model. The sensitivity and specificity of the cytopathology and cfDNA sequencing were compared. The clinical manifestations were preliminarily analyzed for potential correlations with the genotypes.ResultsCfDNA sequencing was accomplished in 23 eyes with VRL and 20 eyes with inflammatory eye diseases. VRL-related mutated genes included MYD88 (18 eyes, 78%), ETV6 (11 eyes, 48%), PIM1 (11 eyes,48%), BTG2 (7 eyes, 30%), IRF4 (7 eyes, 30%), CD79B (6 eyes, 26%), LRP1B (6 eyes, 26%), etc. Logistic regression based on the mutations of MYD88 and ETV6 was of the potential for the diagnosis of VRL (P<0.001, adjusted R2 = 0.789, sensitivity 0.913, specificity 0.950); by comparison, the sensitivity and specificity of the vitreous cytopathology were 0.826 and 1.000, respectively. Further analysis of the mutation profile showed that patients carrying CD79B mutation tended to have higher intraocular interleukin-10 level (P=0.030), that CARD11 mutation was correlated with younger age at ocular onset (P=0.039), and that patients with intracranial involvement carried more multiple-site mutations in the BTG2 gene (P=0.013).ConclusionsThe improved workflow of CfDNA sequencing is of sound feasibility in a limited amount of vitreous humor. The logistic model based on the mutations could help to provide reliable clues for the diagnosis of VRL

Disrupted Brain Structural Network Connection in de novo Parkinson's Disease With Rapid Eye Movement Sleep Behavior Disorder

ObjectiveTo explore alterations in white matter network topology in de novo Parkinson's disease (PD) patients with rapid eye movement sleep behavior disorder (RBD).Materials and MethodsThis study included 171 de novo PD patients and 73 healthy controls (HC) recruited from the Parkinson's Progression Markers Initiative (PPMI) database. The patients were divided into two groups, PD with probable RBD (PD-pRBD, n = 74) and PD without probable RBD (PD-npRBD, N = 97), according to the RBD screening questionnaire (RBDSQ). Individual structural network of brain was constructed based on deterministic fiber tracking and analyses were performed using graph theory. Differences in global and nodal topological properties were analyzed among the three groups. After that, post hoc analyses were performed to explore further differences. Finally, correlations between significant different properties and RBDSQ scores were analyzed in PD-pRBD group.ResultsAll three groups presented small-world organization. PD-pRBD patients exhibited diminished global efficiency and increased shortest path length compared with PD-npRBD patients and HCs. In nodal property analyses, compared with HCs, the brain regions of the PD-pRBD group with changed nodal efficiency (Ne) were widely distributed mainly in neocortical and paralimbic regions. While compared with PD-npRBD group, only increased Ne in right insula, left middle frontal gyrus, and decreased Ne in left temporal pole were discovered. In addition, significant correlations between Ne in related brain regions and RDBSQ scores were detected in PD-pRBD patients.ConclusionsPD-pRBD patients showed disrupted topological organization of white matter in the whole brain. The altered Ne of right insula, left temporal pole and left middle frontal gyrus may play a key role in the pathogenesis of PD-RBD

Generation of a Urine-Derived Ips Cell Line from a Patient with a Ventricular Septal Defect and Heart Failure and the Robust Differentiation of These Cells to Cardiomyocytes via Small Molecules

Background/Aims: Ventricular septal defects (VSDs) are one of the most common types of congenital heart malformations. Volume overload resulting from large VSDs can lead to heart failure (HF) and constitutes a major cause of pediatric HF with a series of often-fatal consequences. The etiology of VSD with HF is complex, and increasing evidence points toward a genetic basis. Indeed, we identified an L2483R mutation in the ryanodine receptor type 2 (RyR2) in a 2-month-old male patient with VSD with HF. Methods: We generated integration-free induced pluripotent stem cells from urine samples (UiPSCs) of this patient using Sendai virus containing the Yamanaka factors and characterized these cells based on alkaline phosphatase activity, pluripotency marker expression, and teratoma formation. Then, we induced the derived UiPSCs to rapidly and efficiently differentiate into functional cardiomyocytes through temporal modulation of canonical Wnt signaling with small molecules. Real-time PCR and immunofluorescence were used to verify the expression of myocardium-specific markers in the differentiated cardiomyocytes. The ultrastructure of the derived myocardial cells was further analyzed by using transmission electron microscopy. Results: The established UiPSC lines were positive for alkaline phosphatase activity, retained the RyR2 mutation, expressed pluripotency markers, and displayed differentiation potential to three germ layers in vivo. The UiPSC-derived cells showed hallmarks of cardiomyocytes, including spontaneous contraction and strong expression of cardiac-specific proteins and genes. However, compared with cardiomyocytes derived from H9 cells, they had a higher level of autophagy, implying that autophagy may play an important role in the development of VSD with HF. Conclusion: The protocol described here yields abundant myocardial cells and provides a solid platform for further investigation of the pathogenesis, pharmacotherapy, and gene therapy of VSD with HF

Roadmap on Label-Free Super-resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles that need to be overcome to break the classical diffraction limit of the label-free imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability that are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.Peer reviewe