Publications by Year: 2025

Background: Autism spectrum disorder (ASD) and related neurodevelopmental conditions are a significant public health concern, with diagnostic delays hindering timely intervention. Traditional assessments often lead to waiting times exceeding a year. Advances in artificial intelligence (AI) and biomarker-based screening offer objective, efficient alternatives for early identification. Objective: This review synthesizes the latest evidence for AI-enabled technologies aimed at improving early ASD identification. Modalities covered include eye-tracking, acoustic analysis, video- and sensor-based behavioral screening, neuroimaging, molecular/genetic assays, electronic health record prediction, and home-based digital applications or apps. This manuscript critically evaluates their diagnostic accuracy, clinical feasibility, scalability, and implementation hurdles, while highlighting regulatory and ethical considerations. Findings: Across modalities, machine learning approaches demonstrate strong accuracy and specificity in ASD detection. Eye-tracking and voice-acoustic classifiers reliably differentiate for autistic children, while home-video analysis and Electronic Health Record (EHR)-based algorithms show promise for scalable screening. Multimodal integration significantly enhances predictive power. Several tools have received Food and Drug Administration clearance, signaling momentum for wider clinical deployment. Issues persist regarding equity, data privacy, algorithmic bias, and real-world performance. Conclusions: AI-enabled screeners and diagnostic aids have the potential to transform ASD detection and access to early intervention. Integrating these technologies into clinical workflows must safeguard equity, privacy, and clinician oversight. Ongoing longitudinal research and robust regulatory frameworks are essential to ensure these advances benefit diverse populations and deliver meaningful outcomes for children and families.

Background: The best treatment for children with KD who fail to respond to the first dose of IVIG (refractory KD) is currently unknown. The purpose of this study was to determine treatment practices of pediatric rheumatologists in North America who manage IVIG-refractory KD. Methods: A 34-item web-based survey was sent to 102 randomly selected members of the Childhood Arthritis and Rheumatology Research Alliance (CARRA). The anonymous survey addressed the use of primary intensification as well as the treatment of IVIG-refractory KD. Results: The response rate was 82%; 56% (all pediatric rheumatologists) completed the survey. Primary intensification was used for macrophage activation syndrome (MAS), KD shock, and those at high risk for coronary artery aneurysms (CAAs) by 84%, 76% and 52% of responders, respectively, with corticosteroids (CSs) used most frequently. For IVIG-refractory KD without CAA, a second dose of IVIG was used most often (63% alone; 23% plus CS). With non-giant CAAs, only 15% used a second IVIG alone, 40% used IVIG plus CS, and 35% took infliximab, usually with CS/IVIG. With giant CAA, treatments used most frequently were CS, a second IVIG, and infliximab (91%, 69%, and 58%, respectively), usually as combinations of two or more medications. Conclusions: Treatment of IVIG-refractory KD varies significantly among North American pediatric rheumatologists, particularly in the presence of CAAs. Our findings emphasize the need for research to identify the most effective therapy for this KD subgroup. The current use of primary intensification and the presence and size of the CAA will need to be considered as consensus treatment plans are developed.

Background/Objectives: Hemodynamic stressors, including abnormal wall shear stress (low or high) or oscillatory shear index are recognized as contributors to the pathogenesis, growth, and rupture of intracranial aneurysms (IAs). Computational fluid dynamics (CFD) has therefore become an essential tool for their quantitative assessment. This systematic review aimed to identify the most frequently analyzed hemodynamic and morphological parameters in recent CFD studies and summarize the methodological strategies employed. Methods: A systematic review was conducted following the PRISMA guidelines, including original studies published between 2019 and 2024 in PubMed, Scopus, Web of Science, and Embase databases. Eligible studies applied CFD to human saccular aneurysms addressing rupture or growth. Exclusion criteria comprised stent-assisted treatments, idealized or phantom models, and non-human or in vitro analyses. Extracted data included study characteristics, CFD software, meshing and solver approaches, and reported parameters. Results: Thirty-five studies met the eligibility criteria. Commercial software predominated across the segmentation, meshing, and solver stages. The most frequently evaluated wall shear stress metrics were the oscillatory shear index (OSI, 91.43%), time-averaged wall shear stress (TAWSS, 71.43%), low shear area ratio (LSAR, 60.00%), normalized wall shear stress (NWSS, 51.43%), and relative residence time (RRT, 45.71%). Morphological parameters such as the aspect ratio (AR, 74.29%), size ratio (SR, 68.57%), and volume (42.86%), reflecting aneurysm shape and relative size, were the most consistently evaluated and demonstrated strong associations with rupture and growth. Conclusions: A core set of morphological and hemodynamic parameters (AR, SR, TAWSS, OSI, RRT, and LSAR) was consistently identified as potential discriminators for the rupture and growth of intracranial aneurysms. However, substantial methodological heterogeneity and the absence of unified standards hinder reproducibility and clinical translation. Future research must urgently standardize computational frameworks, parameter definitions, and boundary conditions to enhance the consistency, comparability, and clinical applicability of CFD in aneurysm risk assessment.

Background: Circulating sphingolipids have been implicated in central nervous system degenerative disorders, but their relationship with peripheral neuropathy remains unclear. Objectives: To evaluate associations between plasma sphingolipid levels and subsequent loss of vibration and light pressure sensation in the lower limbs of older adults. Methods: Plasma concentrations of 11 ceramide (Cer) and sphingomyelin (SM) species were measured in stored samples from 4612 participants in the Cardiovascular Health Study. Vibration sensation was assessed 4-6 years later in 2208 individuals using tuning fork testing, and light pressure sensation was evaluated 11-13 years later in 815 participants using monofilament testing. Sensory impairment was graded on a 3-point scale, with higher scores indicating greater loss. Ordinal logistic regression models examined associations between a doubling of sphingolipid levels and sensory decline, with stratification by diabetes status. Results: In primary models, no sphingolipid species showed significant associations with sensory outcomes. However, after adjusting for inflammatory markers, higher SM-16 levels were linked to increased odds of vibration sensation loss (OR 2.08; 95% CI: 1.11-3.90), while higher SM-24 levels were associated with reduced odds (OR 0.68; 95% CI: 0.46-0.998). Significant interactions with diabetes status were observed for light pressure sensation: SM-14 was associated with increased odds of sensory loss in participants with incident diabetes (OR 5.22; 95% CI: 1.58-17.29), and Cer-18 was associated with increased odds in those with prevalent diabetes (OR 2.38; 95% CI: 1.18-4.78). Conclusions: Elevated levels of specific ceramide and sphingomyelin species may be predictive of future peripheral sensory loss in older adults, with diabetes status influencing these associations.

Background: The US Food and Drug Administration (FDA) authorized over 690 machine learning (ML)-enabled medical devices between 1995 and 2023. In 2024, new guidance enabled the inclusion of Predetermined Change Control Plans (PCCPs), raising expectations for transparency, equity, and safety under the Good Machine Learning Practice (GMLP) framework. Objective: The objective was to assess regulatory pathways, predicate lineage, demographic transparency, performance reporting, and PCCP uptake among ML-enabled devices approved by the FDA in 2024. Methods: We conducted a cross-sectional analysis of all FDA-authorized ML-enabled devices in 2024. Data extracted from FDA summaries included regulatory pathway, predicate genealogy, performance metrics, demographic disclosures, PCCPs, and cybersecurity statements. Descriptive and nonparametric statistics were used. Results: The FDA authorized 168 ML-enabled Class II devices in 2024. Most (94.6%) were cleared via 510(k); 5.4% were cleared via De Novo. Radiology dominated (74.4%), followed by cardiovascular (6.5%) and neurology (6.0%). Non-US sponsors accounted for 57.7% of clearances. Among 159 510(k) devices, 97.5% cited an identifiable predicate; the median predicate age was 2.2 years (IQR 1.2-4.1), and 64.5% ML-enabled. Predicate reuse remained uncommon (9.9%). Median review time was 162 days (151 days for 510(k) vs. 372 days De Novo; p < 0.001). A total of 49 devices (29.2%) reported both sensitivity and specificity; 15.5% provided demographic data. PCCPs appeared in 16.7% of summaries, and cybersecurity considerations appeared in 54.2%. Conclusions: While 2024 marked a record year for ML-enabled device approvals and internationalization, uptake of PCCPs and transparent performance and demographic reporting remained limited. Policy efforts to standardize disclosures and strengthen post market oversight are critical for realizing the promises of GMLP.

Background/Objectives: Anterior cruciate ligament (ACL) injuries frequently lead to long-term quadriceps impairments despite surgical repair. There is growing evidence that these deficits are caused in part by alterations in the central nervous system. Thus, transcranial neuromodulation (TNM) could be valuable in ACL rehabilitation. To systematically review randomized controlled trials (RCTs) assessing the effects of TNM on neurophysiological, functional, and safety outcomes in patients with ACL injury or reconstruction. Methods: We conducted searches on PubMed, Scopus, Web of Science, and Cochrane. We considered all original studies evaluating TNM, including transcranial current stimulation (tCS) and transcranial magnetic stimulation (TMS), in patients with ACL reconstruction or injury. Measures of corticospinal excitability, safety, balance, and muscle strength were assessed. We employed the Cochrane RoB 2 method to assess the risk of bias. Results: Seven studies comprising 129 participants (64 TNM, 65 controls) were included. Most studies applied transcranial direct current stimulation (tDCS) over the primary motor cortex contralateral to the ACL injury in conjunction with physical rehabilitation. Single-session protocols demonstrated minimal effects, whereas repeated sessions resulted in improvements in corticospinal excitability, quadriceps strength, and balance. No serious adverse events were reported; minor effects included transient headache or scalp tingling. The risk of bias was assessed as low to moderate across the studies. Conclusions: TNM appears to be safe and may enhance functional recovery in individuals with ACL injuries when administered in multiple sessions alongside standard rehabilitation. Further high-quality trials are necessary to determine optimal protocols and long-term outcomes.

Background/Objectives: Although clinicopathologic correlation with integration of clinical and radiographic data is the gold standard in distinguishing primary extramammary Paget disease (EMPD) from secondary EMPD, immunoprofiling of EMPD tumors enables distinction between primary and secondary EMPD. Methods: We evaluated the immunoprofiles of previously published cases in the literature as well as 12 secondary EMPD cases from our archives in order to construct a diagnostic algorithm that enables the distinction between primary and secondary EMPD. Results: Immunoprofiles of 480 primary (published cases) and 132 secondary (120 published cases and 12 institutional cases) EMPD cases were compared. CK7, CK20, CDX2, GATA3, GCDFP15, TRPS1, and SATB2 expression was significantly different in primary EMPD versus colonic secondary EMPD (p < 0.001 for all except SATB2, p = 0.036). CK20, GCDFP15, TRPS1, p63 and uroplakin II/III expression was significantly different in primary EMPD versus urothelial secondary EMPD (p < 0.001). CK7, CDX2, SATB2, GATA3 and p63 expression was significantly different in colonic versus urothelial secondary EMPD. CK20, CDX2, and GCDFP15 expression was significantly different in colonic versus prostatic secondary EMPD. CK20 expression was significantly different in colonic versus prostatic secondary EMPD (p = 0.018). CK20, GCDFP15 and TRPS1 are helpful in the distinction of primary EMPD versus colonic and urothelial secondary EMPD (p < 0.001). Conclusions: We propose that the initial IHC panel should include TRPS1, CK7 and CK20. In TRPS1-negative cases, additional immunostains should be performed: CDX2 and SATB2 for colonic; p63, GATA3 and uroplakin II/III for urothelial; and PSA and NKX3.1 for prostatic secondary EMPD.

Multiple myeloma (MM) is a plasma cell malignancy that disrupts bone homeostasis by suppressing osteogenesis and promoting osteoclast activity. While most therapeutic interventions to date have focused on targeting tumor cells and reducing osteolysis, we investigate whether osteoinductive strategies can restore bone formation and counteract disease progression. Using a human bone marrow-like scaffold model that enables direct in vivo evaluation of tumor-stroma interactions and human bone formation, we demonstrate that MM-derived mesenchymal stromal cells (MSCs) retain osteogenic potential but are functionally suppressed by MM cells. Transcriptomic profiling of MM-primed MSCs revealed the downregulation of small leucine-rich proteoglycans (SLRPs), ASPN, OGN, and OMD, key mediators of bone morphogenetic protein (BMP) signaling, which governs osteoblast differentiation. Among the BMPs analyzed, BMP6 emerged as a potent inducer of osteogenesis and regulator of the expression of these SLRPs. Notably, BMP6 selectively promoted bone formation without enhancing osteoclastogenesis and attenuated inflammatory and tumor-supportive MSC phenotypes. BMP6 also directly inhibited MM cell proliferation and suppressed IL6-induced growth. These findings highlight BMP6 as a distinct multifunctional regulator warranting further investigation as a potential therapeutic approach, while establishing the humanized model as a valuable platform for dissecting tumor-bone interactions in MM.

OBJECTIVE: In recent years, the study of macrophages has gained prominence as a promising avenue for understanding the pathogenesis and therapeutic prospects of acute kidney injury (AKI). In this work, we utilize a bibliometric analysis to map the existing research landscape concerning macrophages in the context of AKI. We aim to provide valuable insights and scholarly references that can facilitate the advancement of comprehensive research and innovation in this field. Our goal is to provide valuable knowledge and academic sources that support the progress of thorough research and breakthroughs in connected fields.

METHODS: We incorporated studies focused on macrophages in AKI that were retrieved from the Web of Science Core Collection. All publications were exported in plaintext full-record format and subsequently analyzed using CiteSpace 6.4.R1 for bibliometric evaluation.

RESULTS: A total of 1483 records meeting the inclusion criteria were analyzed. The number of publications in the 1st 12 years was relatively low, but there was a notable increase in publications in 2019 and 2021. The research, encompassing contributions from 56 countries and 437 institutions, is led by China and US Department of Veterans Affairs. The authors with the highest number of publications are Hans-Joachim Anders and Mark D. Okusa, and Bonventre JV was the most frequently cited author. The journal with the highest number of co-citations is Kidney International. Prominent keywords in the literature include macrophages, inflammation, and extracellular vesicles. Keywords extracted from the analysis mainly focus on AKI, expression, acute renal failure, activation, inflammation, and macrophages.

CONCLUSION: This research provides a comprehensive bibliometric evaluation, thereby enhancing our understanding of the current state of macrophage studies in AKI. As a result, it assists both experienced researchers and newcomers by facilitating quick access to crucial information and promoting the extraction of innovative concepts within this specialized field.

A growing body of recent work suggests the possibility of heterogeneous ribosomal composition. We recently observed subtype-specific mRNA and copy number variation signatures of human ribosomal proteins (RPs) in cancers from human adults, but whether such subtype-specific RP mRNA signatures are also present in human pediatric cancers is currently unknown. In this study, we analyzed mRNA expression data from multiple large pediatric cancer datasets to test for heterogeneity in RP mRNA signatures. We found that different pediatric cancer types have different RP mRNA signatures, sometimes multiple RP mRNA signatures within the same pediatric cancer type, which can be subgroup/subtype-specific (e.g., in Medulloblastoma) or cell-of-origin-specific (e.g., in Acute Lymphoblastic Leukemia (ALL)). In B-cell ALL, we found two RP mRNA subtypes with significantly different prognoses. Consistent with our recent findings in adult cancers, the RP mRNA signature in pediatric cancer is heterogeneous and subtype-specific and may have clinical relevance.