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Key Points Automated cyst segmentation in autosomal dominant polycystic kidney disease could transform care by enabling precise monitoring of cyst progression with minimal manual effort. This technology can facilitate more consistent assessments of cyst burden across patients. Translating these segmentation models from magnetic resonance imaging to computed tomography is crucial for providing comprehensive, modality-independent evaluations. Background Total kidney and liver volumes are key image-based biomarkers to predict the severity of kidney and liver phenotype in autosomal dominant polycystic kidney disease (ADPKD). However, magnetic resonance (MR) imaging-based advanced biomarkers like total cyst number and cyst parenchyma surface area have been shown to more accurately assess cyst burden and improve the prediction of disease progression. The main aim of this study was to extend the calculation of advanced biomarkers to other imaging modalities; thus, we propose a fully automated model to segment kidney and liver cysts in computed tomography (CT) images. Methods Abdominal CTs of patients with ADPKD were gathered retrospectively between 2001 and 2018. A three-dimensional deep learning method using the nnU-Net architecture was trained to learn cyst edges-cores and the noncystic kidney/liver parenchyma. Separate segmentation models were trained for kidney cysts in contrast-enhanced CTs and liver cysts in noncontrast CTs using an active learning approach. Two experienced research fellows manually generated the reference standard segmentation, which were reviewed by an expert radiologist for accuracy. Results Two-hundred CT scans from 148 patients (mean age, 51.2±14.1 years; 48% male) were used for model training (80%) and testing (20%). In the test set, both models showed good agreement with the reference standard segmentations, similar to the agreement between two independent human readers (model versus reader: TCN kidney/liver r =0.96/0.97 and CPSA kidney r =0.98, inter-reader: TCN kidney/liver r =0.96/0.98 and CPSA kidney r =0.99). Conclusions Our study demonstrates that automated models can segment kidney and liver cysts accurately in CT scans of patients with ADPKD.

Despite improvements in kidney transplantation rates, the shortage of donor kidneys remains a critical issue, exacerbated by non-utilization of recovered kidneys due to quality concerns, necessitating advancements in perfusion methods to enhance graft outcomes and usage. Although static cold storage remains the default standard for kidney preservation, newer methods like hypothermic machine perfusion have shown improved outcomes, including reduced delayed graft function and better survival rates. Hypothermic oxygenated machine perfusion and normothermic machine perfusion offer some potential clinical benefits but studies to date have demonstrated mixed results. In the United States, LifePort and the XVIVO’s Kidney Assist Transport are the most popular hypothermic perfusion devices, with NMP devices mostly in trials. Combining perfusion with biomarkers such as mitochondrial flavin mononucleotide, neutrophil gelatinase-associated lipocalin, and osteopontin shows promise in assessing kidney viability and predicting post-transplant outcomes, though further research is also needed. Emphasis on repair biomarkers, such as uromodulin and osteopontin, aims to better predict graft outcomes and develop new therapies. While notable advancements have been made in the use of machine perfusion and viability testing for liver transplantation, additional research with larger sample sizes is essential to substantiate these results and enhance kidney transplantation outcomes.

We describe the first use of phage therapy in Canada for the treatment of a life-threatening periprosthetic joint infection (PJI), with successful outcome. PJI is a devastating complication of joint replacement surgery, with high morbidity and mortality. Our patient presented with early sepsis from a chronic recalcitrant multidrug-resistant (MDR) Staphylococcus epidermidis hip PJI which had repeatedly failed standard therapy. She had previously undergone 10 operations of the right hip, and only three weeks after completing a prolonged course of daptomycin following her most recent hip revision, she developed a draining sinus tract. Given the high burden of disease, inability to achieve surgical source control, and lack of antibiotic treatment options for long-term suppressive therapy, bacteriophage (phage) therapy was pursued. The patient underwent irrigation and debridement with complex flap reconstruction: intraoperative tissue cultures again yielded MDR S. epidermidis. We developed a novel phage therapy protocol for this patient, with twice daily, intra-articular and intravenous (7 × 109 PFU/dose) phage delivery over a planned 14-day course. Complete healing of the wound with cessation of drainage occurred within one month after treatment. A marked improvement in right hip pain and mobility occurred within three months after treatment. Twelve months following phage treatment, there is normalization of serum inflammatory markers with diminished pain, increased mobility, and no recurrent surgery. Our patient continues to improve and is currently living independently at home, with sustained clinical control of infection.

We present Liquid Adaptive AI as a theoretical framework and mathematical basis for artificial intelligence systems capable of continuous structural adaptation and autonomous capability development. This work explores the conceptual boundaries of adaptive AI by formalizing three interconnected mechanisms: (1) entropy-guided hyperdimensional knowledge graphs that could autonomously restructure based on information-theoretic criteria; (2) a self-development engine using hierarchical Bayesian optimization for runtime architecture modification; and (3) a federated multi-agent framework with emergent specialization through distributed reinforcement learning. We address fundamental limitations in current AI systems through mathematically formalized processes of dynamic parameter adjustment, structural self-modification, and cross-domain knowledge synthesis, while immediate implementation faces substantial computational challenges requiring infrastructure on the scale of current large language model training facilities, we provide architectural specifications, theoretical convergence bounds, and evaluation criteria as a foundation for future research. This theoretical exploration establishes mathematical foundations for a potential new paradigm in artificial intelligence that would transition from episodic training to persistent autonomous development, offering a long-term research direction for the field. A comprehensive Supplementary Materials document provides detailed technical analysis, computational requirements, and an incremental development roadmap spanning approximately a decade.

Abstract Pancreatic ductal adenocarcinoma (PDAC), one of the most aggressive forms of pancreatic cancer, is associated with poor survival outcomes and currently ranks as the third leading cause of cancer-related death in the United States. Despite its clinical significance, the mechanisms of PDAC development and progression remain, in part, poorly understood. In this study, we provide evidence of a novel role of sorting nexin 10 (SNX10), a member of the sorting nexin family, in the regulation of KRAS-induced pancreatic carcinogenesis. We demonstrate that SNX10 is downregulated in PDAC, especially in advanced cases. Furthermore, mutational analysis revealed SNX10 genetic alterations in PDAC cases. Functional studies demonstrated that SNX10 overexpression in human PDAC cells inhibited cell proliferation and colony formation. Moreover, SNX10 overexpression induced G1-phase cell-cycle arrest and decreased KRAS signaling activity. Using a novel Snx10 knockout mouse crossed with a Kras-driven PDAC model, we observed reduced survival, increased tumor cell proliferation, enhanced aggression, and heightened inflammation. Collectively, these findings highlight SNX10 as a tumor suppressor candidate in PDAC and underscore its promise as a foundation for new therapeutic approaches. Significance: SNX10 plays a crucial role in reducing pancreatic tumorigenesis. This discovery offers valuable insights into PDAC’s biology and the development of new effective treatments.

BACKGROUND: Hemorrhoidal disease and immunosuppression are prevalent. Management of hemorrhoidal disease in this patient population is challenging. Most societies recommend conservative management due to the presumed risks of morbid complications, including sepsis and impaired healing. Data on the risks of office-based and operative procedures in immunocompromised patients are scant. OBJECTIVE: To evaluate postoperative outcomes after both office-based procedures and operative intervention for hemorrhoidal disease in immunocompromised patients. DESIGN: Retrospective medical record review. SETTINGS: Single-center, tertiary referral center. PATIENTS: Adult patients were included who had hemorrhoidal disease and primarily medication-induced immunosuppression and were undergoing an office-based procedure or operative intervention for hemorrhoidal disease while on immunosuppression at Mayo Clinic in Rochester between 2010 and 2023. MAIN OUTCOME MEASURES: The primary outcome was the development of infectious complications or wound complications. RESULTS: Fifty-five immunocompromised patients, with a median age of 60 years, underwent a total of 68 hemorrhoidal procedures during the study time frame. All patients had immunosuppression induced by medication, except for 1 patient with bone marrow failure syndrome. The most common reason for immunosuppression was rheumatoid arthritis, followed by prior kidney transplant. The most common medications were chronic corticosteroids and methotrexate in more than one-third of patients each. Of 68 total interventions, hemorrhoidectomy (32%) and excision of a thrombosed hemorrhoid (26%) were the 2 most common operations performed. Sixteen adverse events were reported in 14 patients (25%). Three cases of postoperative cellulitis were documented after thrombosed external hemorrhoid excision, hemorrhoidopexy, and Whitehead hemorrhoidectomy. No postoperative intravenous antibiotics were administered. No cases of pelvic sepsis were documented. LIMITATIONS: The retrospective nature of the study and the heterogeneity of the study population. CONCLUSIONS: These data suggest that office-based and surgical procedures are safe and feasible in patients with immunosuppression. See Video Abstract . SEGURIDAD DE LOS PROCEDIMIENTOS PARA EL TRATAMIENTO DE HEMORROIDES EN PACIENTES INMUNODEPRIMIDOS: LA EXPERIENCIA DE LA CLÍNICA MAYO ANTECEDENTES: La enfermedad hemorroidal y la inmunosupresión son prevalentes. El tratamiento de la enfermedad hemorroidal en esta población de pacientes es difícil. La mayoría de las sociedades recomiendan un tratamiento conservador debido a los riesgos presuntos de complicaciones mórbidas, como sepsis y alteración de la cicatrización. Los datos sobre los riesgos de los procedimientos ambulatorios y quirúrgicos en pacientes inmunodeprimidos son escasos. OBJETIVO: Evaluar los resultados posoperatorios tras procedimientos ambulatorios y cirugía para la enfermedad hemorroidal en pacientes inmunodeprimidos. DISEÑO: Revisión retrospectiva de historias clínicas. ENTORNO: Centro terciario de referencia único. PACIENTES: Pacientes adultos con enfermedad hemorroidal e inmunosupresión inducida principalmente por medicamentos que se sometieron a un procedimiento ambulatorio o a una intervención quirúrgica para la enfermedad hemorroidal mientras estaban en tratamiento inmunosupresor en la Clínica Mayo de Rochester entre 2010 y 2023. PPRINCIPALES MEDIDAS DE RESULTADO: El resultado principal fue la aparición de complicaciones infecciosas o complicaciones de la herida. RESULTADOS: Cincuenta y cinco pacientes inmunodeprimidos, con una mediana de edad de 60 años, se sometieron a un total de 68 procedimientos hemorroidales durante el periodo de estudio. Todos los pacientes presentaban inmunosupresión inducida por medicación, excepto uno con síndrome de insuficiencia medular. La causa más frecuente de inmunosupresión fue la artritis reumatoide, seguida de un trasplante renal previo. Los medicamentos más frecuentes fueron los corticosteroides crónicos y el metotrexato, en más de un tercio de los pacientes. De las 68 intervenciones totales, la hemorroidectomía (32 %) y la extirpación de una hemorroide trombosada (26 %) fueron las dos operaciones más comunes realizadas. Se notificaron 16 eventos adversos en 14 (25 %) pacientes. Se documentaron tres casos de celulitis posoperatoria tras la extirpación de una hemorroide externa trombosada, una hemorroidopexia y una hemorroidectomía de Whitehead. No se administraron antibióticos intravenosos postoperatorios. No se documentaron casos de sepsis pélvica. LIMITACIONES: El carácter retrospectivo del estudio y la heterogeneidad de la población estudiada. CONCLUSIONES: Estos datos sugieren que los procedimientos ambulatorios y quirúrgicos son seguros y viables en pacientes con inmunosupresión. (AI-generated translation )

Abstract Nociplastic pain is defined by altered nociceptive processing in the absence of clear peripheral damage or somatosensory lesions. The Fibromyalgia Index (FMI), derived from the 2016 diagnostic criteria, is increasingly used as a marker of nociplastic pain severity in clinical studies, yet its neurobiological validity remains untested at scale. Using multimodal neuroimaging data from over 40 000 participants in UK Biobank, we examined whether FMI scores were associated with altered functional and structural connectivity within the descending pain modulatory system (DPMS), a brain network involved in endogenous pain control and implicated in nociplastic pain conditions. Functional connectivity was assessed using resting-state functional MRI (rfMRI), and structural connectivity using diffusion-weighted MRI (dMRI) tractography. Connectivity was quantified between seven DPMS regions: periaqueductal grey (PAG), rostral ventromedial medulla (RVM), hypothalamus, amygdala, rostral and subgenual anterior cingulate cortex (rACC, sgACC), and dorsolateral prefrontal cortex (dlPFC). Multi-group structural equation models tested associations between FMI scores and connectivity, stratified by chronic pain status. Mediation models evaluated which aspects of nociplastic pain accounted for the observed associations: widespread pain and SPACE symptoms (sleep disturbance, pain, affect, cognitive problems, and low energy). To assess specificity, we repeated analyses using the Douleur Neuropathique 4 (DN4), a measure of neuropathic pain, and average pain intensity as comparison outcomes. In 22 139 individuals with chronic pain (58% female; mean age 64.8, standard deviation 7.59), FMI scores were associated with altered structural connectivity between the PAG and amygdala [β = 0.023, 95% confidence interval (CI): 0.0087 to 0.039; Pcorr = 0.0125] and between the PAG and hypothalamus (β = −0.029, 95% CI: −0.043 to −0.015; Pcorr = 0.0013). Functional connectivity in the same circuits showed smaller effects. These associations were not observed in individuals without chronic pain. Mediation analyses revealed that PAG-amygdala and PAG-hypothalamus connectivity were partially explained by fatigue, sleep duration, and widespread pain. DPMS connectivity was not significantly associated with neuropathic pain or average pain intensity. These findings suggest that FMI scores reflect biologically meaningful changes in brain connectivity, particularly in subcortical DPMS circuits implicated in affective and homeostatic dimensions of pain. Structural connectivity was more strongly associated with FMI than functional measures, possibly reflecting cumulative effects of chronic pain on white matter architecture. The absence of similar associations for other pain outcomes supports the specificity of FMI as a marker of nociplastic pain severity. These results provide a neurobiological basis for the FMI and support its use in population research and biomarker development for nociplastic pain.

Abstract INTRODUCTION We investigated associations of plasma proteins with blood‐based amyloid/tau/neurodegeneration/inflammation (A/T/N/I) biomarkers for Alzheimer's disease (AD). METHODS Plasma proteomics and clinical data from the Indiana AD Research Center ( N = 498) were used. Association analysis of plasma proteins with blood A/T/N/I biomarkers as well as diagnosis was performed, followed by replication in an independent cohort ( N = 323), network analysis, pathway enrichment, and machine learning classification to identify proteins and pathways related to AD risk. RESULTS We identified 35 proteins associated with AD, 20 of which were replicated in the independent cohort. We identified 150, 448, and 219 proteins associated with T/N/I biomarkers, respectively, revealing biomarker‐specific pathways. Network analysis identified two modules associated with T/N/I biomarkers, preserved in cerebrospinal fluid (CSF), and their enriched pathways. The classification model of proteins effectively differentiated AD (area under the curve [AUC] = 0.930). CONCLUSION Our findings suggest dysregulated plasma proteins and pathways in AD, enhancing our understanding of molecular mechanisms and diagnostic strategies for AD. Highlights Plasma proteins were identified as being associated with Alzheimer's disease (AD) and plasma biomarkers. The identified proteins were replicated in both plasma and cerebrospinal fluid (CSF) proteomics. The identified proteins were associated with AD biomarker‐specific pathways. The identified proteins improved the performance of the AD classification. Protein network analysis identified network modules and their enriched pathways.