Faculty Bibliography

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease characterized by high levels of cellular heterogeneity and pronounced microenvironmental remodelling. Dynamic changes during its initiation and progression contribute to resistance to conventional therapies. Building upon key molecular catalogues established by bulk and single-cell profiling studies that have advanced our understanding of PDAC biology, recent advances in spatial biology have provided much-needed insights by elucidating regionally compartmentalized transcriptomic and proteomic programmes within the PDAC microenvironment. In parallel, emerging computational frameworks in digital pathology and artificial intelligence have advanced the field into a high-dimensional, quantitative discipline, particularly for classifying molecular and clinical features from histopathology images. Despite these advancements, integration of these two modalities remains a major challenge. Here, we summarize the convergence of molecular features identified through spatially resolved profiling in PDAC and its precursor lesions, as well as current developments in AI-powered pathology in cancer research. We further propose a multi-modal integration framework that maps molecular states onto morphological and architectural phenotypes, offering a roadmap for spatially informed patient stratification beyond descriptive tissue characterization. We posit that the path forward relies on disciplined cross-scale integration of spatial, histological, and clinical data to ensure meaningful translation into clinical practice.

BACKGROUND:We investigated whether OPE urinary concentrations during pregnancy were associated with child's autism-related outcomes. METHODS:We included 4159 mother-child pairs from 15 cohorts in the NIH Environmental influences on Child Health Outcomes (ECHO) Consortium, with children born from 2006-2020 (median age [interquartile range]: 6 [4,10] years). Nine OPE biomarkers were measured in urine samples collected mid- to late pregnancy. Dilution-adjusted biomarkers were modeled continuously, categorically (high [>median], moderate [≤median], nondetect), or as detect/nondetect depending on their detection frequency. We assessed child autism-related traits via a) parent report on the Social Responsiveness Scale (SRS) and b) clinical autism diagnosis. We examined associations of OPEs with child outcomes, including modification by child sex, using generalized estimating equations to account for clustering by ECHO cohort. RESULTS:Compared with nondetectable concentrations, high exposure to bis-(butoxyethyl) phosphate (BBOEP) was associated with higher autistic trait scores (adj-β 0.97, 95% confidence interval [CI]: 0.42, 1.52) and greater odds of autism diagnosis (adjusted odds ratio [adj-OR]: 1.27, 95% CI: 1.07, 1.50). Bis-(1-chloro-2-propyl) phosphate (BCPP) showed associations with autistic trait scores (BCPP adj-β for high exposure vs nondetect: 0.34, 95% CI: -0.46, 1.13; BCPP adj-β for moderate exposure vs nondetect: 0.72, 95% CI: 0.24, 1.20). High exposure to bis-(2-chloroethyl) phosphate (BCETP) was associated with lower odds of autism diagnosis (adj-OR: 0.76, 95% CI: 0.60, 0.95). Other OPEs showed no associations in adjusted models. Associations between BBOEP and higher autistic trait scores were stronger in males than females. DISCUSSION:Prenatal exposure to OPEs, specifically BCPP and BBOEP, may be associated with a higher risk of autism diagnosis and related traits in childhood.

OBJECTIVE:To assess guselkumab + golimumab combination therapy versus guselkumab monotherapy in participants with active psoriatic arthritis (PsA) and inadequate response to tumor necrosis factor inhibitors (TNFi-IR). METHODS:Adults with active TNFi-IR PsA (three or more tender/swollen joints) were randomized (2:1) to subcutaneous guselkumab (100 mg) + golimumab (50 mg) combination therapy (n = 59) or guselkumab monotherapy (n = 32) every 4 weeks through week 20. The primary endpoint was week 24 minimal disease activity (MDA) achievement. Additional endpoints included ≥20%/50%/70% improvement in American College of Rheumatology response criteria (ACR20/50/70): improvements in psoriasis, dactylitis, and enthesitis; changes in patient-reported physical function; and impact of screening C-reactive protein (CRP) on MDA/ACR50 response. RESULTS:At baseline, participants had a median of 13 tender and 8 swollen joints and psoriatic body surface area of 3%; 23% had dactylitis. At week 24, 29% and 22% of participants achieved MDA with guselkumab + golimumab combination therapy and guselkumab monotherapy, respectively (odds ratio [OR] 1.4 [90% confidence interval 0.6-3.3]; P = 0.557); 44% and 22% achieved ACR50 (nominal P = 0.034). Participants with CRP levels ≥0.3mg/dL (intended enrollment population) receiving combination therapy (n = 40; monotherapy n = 22) had greater odds of achieving MDA (OR 12.3; nominal P = 0.025; 32% vs 5%) and ACR50 (OR 9.6; nominal P = 0.003; 55% vs 14%) at week 24. Combination therapy was associated with higher ACR20 (66% vs 44%) and ACR70 (27% vs 16%) responses and greater physical function improvements than monotherapy. Improvements in psoriasis, dactylitis, and enthesitis were similar across groups. No new safety signals and no tuberculosis/opportunistic infections occurred through week 36. CONCLUSION/CONCLUSIONS:Although the primary endpoint was not achieved, secondary endpoints and exploratory analyses suggest that participants with TNFi-IR PsA, particularly those with elevated CRP levels, could derive clinically meaningful benefits with guselkumab + golimumab combination therapy, with no new safety concerns, warranting further investigation.

Understanding the genetic regulation of RNA abundance is essential for defining disease mechanisms. Conventional expression quantitative trait locus (eQTL) studies measure steady-state RNA and capture effects across the entire transcript lifecycle. While most eQTL likely affect transcription by altering promoter or enhancer function within the nucleus, others may act post-transcriptionally through RNA modification or stability in the cytosol. To distinguish these mechanisms, we compare eQTL from mature cellular RNA and recently transcribed nuclear RNA in brain and kidney. We identify distinct causal variants underlying cellular and nuclear eQTL at the same eGenes. Cellular eQTL are enriched in transcribed regions (P = 3.3×10⁻¹²⁶), suggesting post-transcriptional regulation, whereas nuclear eQTL are enriched in distal regulatory elements (P = 7.0×10⁻³²), consistent with transcriptional control. For example, stop-gain variants likely acting through nonsense-mediated decay appear only in cellular eQTL. Conversely, nuclear eQTL variants (e.g., TUBGCP4) within enhancers sometimes uniquely colocalize with disease loci (schizophrenia), revealing distinct regulatory mechanisms.

External cervical resorption is a disease entity with an idiopathic etiology by which osteoclastic invasion cavitates teeth near the cementoenamel junction. The lesion, if left untreated, has the potential to progress and compromise tooth maintainability. Treatment of these lesions requires access (often surgical), removal of the affected tissue, and placement of a restorative material. This case series documents 10 external cervical resorption lesions that were treated by surgical crown lengthening with concurrent placement of a resin-modified glass-ionomer restoration and followed up for a period ranging from July 2020 to July 2024. This case series offers evidence that external cervical resorption can be treated with a high expectancy of tooth survival. Longer-term follow-ups are needed to see if this treatment remains stable and predictable.

Full-arch implant rehabilitation-necessitating a holistic, transdisciplinary approach-has been one of the most rapidly advancing disciplines in implant dentistry, driven by rising standards and modern technologic advancements. Despite indicated cases and genuine efforts to improve efficiency, the current trend of an immediacy (or 'teeth-in-a-day') protocol may have unintentionally veiled a more conservative, predictable, and practical potential in wound healing process, esthetics, and occlusion. Through an approach that is more phased and utilizes terminal dentitions as strategic abutments, this case report with 3 years of follow-up emphasizes the leverage of natural biologic phenomena in tissue maturation, remodeling, and condensation, along with prosthetic sophistications focusing on its meticulousness in execution and long-range trajectory success. This workflow actualizes a high-quality level of craftsmanship with surgical and prosthetic innovations, introduced as a 'retightening bilateral sling periosteal mattress suture' concept for intermittent tensocompressive mechanotransduction-induced guided bone regeneration and 'LegOvate' protocol for seamless loading of prosthetic conversions, emphasizing the intricate reciprocity between physiology and biomechanics for a primary goal of a nondestructive equilibrium.

BACKGROUND:Effective screening and cohort enrichment remain major challenges in clinical trials for Alzheimer's disease (AD), where traditional diagnostic pathways rely on costly, invasive, and time-consuming procedures. Speech and language analysis has emerged as a scalable, low-burden approach for detecting subtle cognitive-linguistic and motor-speech changes that may appear early in the disease course. SUMMARY/CONCLUSIONS:This review synthesizes current evidence on acoustic, prosodic, lexical, semantic, and syntactic speech features associated with AD and mild cognitive impairment (MCI) and evaluates their reported utility across a range of elicitation tasks including picture description, verbal fluency, narrative recall, spontaneous speech, and reading. Across studies, machine-learning models trained on speech and language features have reported consistent performance, although results vary substantially depending on task design, feature sets, and cohort characteristics. Task-dependent variability is evident, with picture description and verbal fluency tasks capturing lexical-semantic and timing markers, while narrative and spontaneous speech tasks capture impairments in coherence, information content, and prosody. Hybrid approaches integrating hand-crafted and machine-extracted features have also been explored to improve interpretability and model performance. Speech and language analytics may support digital prescreening, cohort enrichment, and quality-assurance monitoring within clinical trials; however, their application depends on methodological considerations and validation across diverse settings. KEY MESSAGES/CONCLUSIONS:Despite encouraging findings, several methodological challenges persist, including interindividual variability, limited dataset sizes, differences in recording conditions, and limitations in automatic speech recognition performance in cognitively impaired populations. Continued development of standardized protocols, disorder-adapted speech models, and multimodal analytic pipelines is needed to support clinical translation. Collectively, current evidence suggests that speech and language features represent candidate digital markers that may improve screening efficiency and support clinical trial enrichment in AD, although further validation is required to establish their reliability and generalizability.