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Immunological mechanisms and emerging therapeutic targets in alcohol-associated liver disease
No full textAlcohol-associated liver disease (ALD) is a major global health challenge, with inflammation playing a central role in its progression. As inflammation emerges as a critical therapeutic target, ongoing research aims to unravel its underlying mechanisms. This review explores the immunological pathways of ALD, highlighting the roles of immune cells and their inflammatory mediators in disease onset and progression. We also examine the complex interactions between inflammatory cells and non-parenchymal liver cells, as well as their crosstalk with extra-hepatic organs, including the gut, adipose tissue, and nervous system. Furthermore, we summarize current clinical research on anti-inflammatory therapies and discuss promising therapeutic targets. Given the heterogeneity of ALD-associated inflammation, we emphasize the need for precision medicine to optimize treatment strategies and improve patient outcomes
Pathological mechanisms of motor dysfunction in familial Danish dementia: insights from a knock-in rat model
No full textFamilial Danish Dementia (FDD) is a rare autosomal dominant neurodegenerative disorder caused by a mutation in the integral membrane protein 2B (ITM2b) gene. Clinically, FDD is characterized by cerebral amyloid angiopathy (CAA), cerebellar ataxia, and dementia. Notably, FDD shares several neuropathological features with Alzheimer's disease (AD), including CAA, neuroinflammation, and neurofibrillary tangles. In this study, we investigate the pathological mechanisms linking CAA, white matter damage, and motor dysfunction using a recently developed FDD knock-in (FDD-KI) rat model. This model harbors the Danish mutation in the endogenous rat Itm2b gene, along with an App gene encoding humanized amyloid-β (Aβ). Our analysis revealed substantial vascular Danish amyloid (ADan) deposition in the cerebellar subpial and leptomeningeal vessels of FDD-KI rats, showing an age-related increase comparable to that observed in human FDD patients. Additionally, vascular Aβ deposits (Aβ-CAA) were present in FDD-KI rats, but Aβ-CAA patterns showed some differences between species: in FDD patients, Aβ-CAAs were more abundant in subpial large vessels, while in FDD-KI rats, Aβ-CAA was mostly observed in capillaries. Motor function assessments in FDD-KI rats demonstrated age-accelerated motor deficits and gait abnormalities, mirroring the clinical characteristics of FDD patients. To further explore the mechanisms underlying these deficits, we examined cerebellar pathology and found age-related myelin disruption and axonal fiber loss, consistent with postmortem human FDD pathology. Cerebellar demyelination appeared to be driven by neuroinflammation, marked by increased microglial/macrophage activation in response to vascular amyloid deposition. Additionally, we observed extravascular fibrinogen leakage, indicating widespread vascular permeability in both white and gray matter, with fibrinogen deposits surrounding amyloid-positive vessels in aged FDD-KI rats and postmortem FDD cerebellum. These findings suggest that CAA and fibrinogen leakage in FDD may drive neuroinflammation, demyelination, and axonal damage in the cerebellum, potentially contributing to the motor and gait impairments observed in FDD
Developing Interpretable Data Mining Frameworks for Addressing Biomedical Challenges in Genomics and Imaging
No full textIUIThe global burden of disease has evolved significantly in recent decades. Since the early 2000s, we have witnessed multiple widespread outbreaks of respiratory viruses including Influenza A and SARS-CoV-2, alongside a marked increase in chronic conditions such as diabetic retinopathy (DR). These diseases pose serious health threats – respiratory infections can progress to fatal multi-organ failure, while untreated DR may result in vision impairment or complete blindness. Given the impacts of these conditions on individual quality of life and healthcare systems worldwide, it is imperative to develop a comprehensive set of computational methods for studying and detecting these diseases.
This dissertation highlights the need for accessible and interpretable data visualization techniques and models in studying respiratory viruses and DR. My work extends previous approaches that have been developed for studying SARS-CoV-2 host-pathogen interactions, diagnostic assays for respiratory virus detection, and analysis of spatiotemporal trends in SARS-CoV-2 variant transmission. My work also focuses on developing explainable deep learning models that extract latent and explicit information from retina fundus images to detect DR and identify DR stages. The methods discussed in this dissertation contribute to the research community by consolidating information and extracting hidden insights from publicly available data sources through interpretable data visualization approaches and models. Moreover, my efforts in DR detection and grading demonstrate the utility of using clinically grounded data in both model design and post-model decision analysis. Taken together, these approaches show how novel computational methods and models can be used to provide valuable insights and drive innovation in diverse biomedical domains
Sex Differences in the Diffusion of Tau Neurofibrillary Tangles Across Functional Brain Networks
No full textBackground:
Alzheimer's disease is characterized by the accumulation and spread of tau neurofibrillary tangles across cortical regions, driving cognitive decline. However, many cortical regions exhibit little tau, despite their functional connections to regions with high levels. In fact, recent evidence links elevated tau to hypoconnectivity in the default mode network (DMN) during early phases of disease, suggesting possible differential tau diffusion across functional networks. Therefore, the aim of this study is to examine tau diffusion (spreading of tau across functionally connected regions) and whether this is differentiated by functional network. To do this, novel multilevel network diffusion models are proposed to compare diffusion across functional networks and examine whether this differs by sex.
Method:
Included are 321 subjects from the third phase of the Alzheimer's Disease Neuroimaging Initiative (ADNI 3). Multilevel network diffusion models, first proposed by Frank et al. as social influence models to study the dynamics of teacher interactions, were adapted to examine diffusion. Diffusion is defined as the spreading of tau via neighboring (functionally connected) regions. Functional networks include DMN, limbic system (LSN), frontoparietal (FPN), dorsal attention (DAN), sensorimotor (SMN), visual (VISN), and ventral attention (VAN), which were parcellated according to the Desikan‐Killiany Atlas. We compared diffusion across these networks and investigated its interactions with sex.
Result:
Analyses reveal significant diffusion differences within DAN (Estimate=.243, p <.001), LSN (Estimate=‐.038, p <.001), SMN (Estimate=.084, p <.001), VAN (Estimate=‐.039, p = .004), and VISN (Estimate=‐.079, p <.001) compared to the DMN. Figure 1 illustrates the rate of diffusion across networks with highest diffusion found in FPN and DMN, and lowest in SMN and VISN. Additionally, we found sex differences in LSN diffusion (Estimate=.047, p = .037; see Figure 2), with stronger diffusion in females, suggesting that tau spreads faster in females than males. These findings are based on two models: one for diffusion differences across networks and another for sex‐based diffusion differences across networks.
Conclusion:
This study represents an in‐depth investigation of tau diffusion, showing highest diffusion in the FPN and DMN, consistent with previous research on network‐specific glucose metabolism. Additionally, higher tau diffusion in the LSN of females supports prior studies showing greater tau distribution in limbic regions of women
Development of an HPV 16 rapid test founded in user-centered design with primary care clinicians
No full textDespite effective screening modalities, cervical cancer remains a leading cause of cancer-related death among women in the United States aged 20 to 39 years old, and incidence is rising in women aged 30-44 years old. Up to 25% of patients who are screened for cervical cancer by testing for human papillomavirus (HPV) do not receive necessary follow-up care with current laboratory-based testing. Applying a user-centered design approach, we surveyed and interviewed practicing clinicians to establish the use case, value proposition, and user requirements of a cervical cancer screening test for use in Indiana, USA. Insights from these stakeholders directly informed design specifications for a point-of-care HPV test capable of providing same-visit results to improve patient follow-up and retention. Guided by these requirements, we designed an isothermal nucleic acid amplification platform suitable for outpatient clinics. The test accepts swabbed endocervical cells, amplifies HPV16 L1 DNA via recombinase polymerase amplification, and provides results within 40 minutes on a lateral flow assay. Further, the test achieves a clinically relevant limit of detection of 1000 HPV 16 copies per reaction and verifies swabbing technique and test operation with a sample adequacy control. The test operation was designed for a minimally-trained user and decreases time-sensitive steps that would interfere with clinical flow. By integrating clinician input to inform development decisions, our device is uniquely tailored to meet the context-specific needs of primary care clinics. This work exemplifies how user-centered design can yield novel diagnostic technologies with greater clinical impact and adoption potential
Exploratory Study on the Challenges of Newborn Screening for Lysosomal Storage Disorders Emphasizes the Need for Multitier Testing and Collaborative Approaches to Management
No full textInnovative treatments have allowed the introduction of conditions such as lysosomal storage disorders (LSDs) to newborn screening (NBS). This study explored the challenges healthcare providers faced with the addition of LSDs to NBS and identified adjustments that minimized the burden of such challenges. An online survey was distributed to healthcare providers with experience working with patients with LSDs. The most common anticipated challenges were interpreting NBS results (75%) and having adequate screening protocols (63%). After the addition of LSDs, interpretation of newborn screen results (64%) remained a challenge, but adequate screening protocols were less frequent (25%). Collaboration of care with additional subspecialty providers was the most common change in clinic structure (68%) and individual practice (54%) after the addition of LSDs to NBS. Given the interpretation of results remained a challenge most providers faced, we advocate the implementation of multitier screening protocols is key to improving sensitivity and specificity of NBS for LSDs. This allows for the identification of at-risk infants and provides clarity on expected phenotypes and healthcare needs. These results indicate collaboration between healthcare providers is a key factor in providing optimal care. The findings of this study may benefit clinics that are implementing NBS for LSDs as the adoption of these practices preemptively may reduce the burden of that challenge
Representing the Cognitive Impairment Continuum of Alzheimer's Disease and Lewy Body Dementia with a Novel Finer‐Scale Cortical Representation via Disease Embedding Tree
No full textBackground:
Alzheimer's Disease (AD) and Lewy Body Dementia (LBD) often exhibit overlapping neuropathological features and symptoms, posing significant challenges for differential diagnosis. While many studies focus on leveraging machine learning with neuroimaging data for early dementia diagnosis, investigating the progression and interactions between AD and LBD offers an opportunity to uncover valuable insights into their shared features and hidden connections.
Method:
We propose the Disease Embedding Tree (DET) framework to model continuous relationships among AD, Cognitively Normal (CN), and LBD subjects on T1‐weighted structural MRI data from 106 subjects (36 AD: 15 females, 21 males; 78.25 ± 5.76 years; 35 CN: 15 females, 20 males; 76.74 ± 5.15 years; 35 LBD: 8 females, 27 males; 78.37 ± 6.94 years).
For each subject, we reconstructed cortical surfaces and adopted a novel cortical folding pattern representation, Gyral Network, to identify the potential cortical hubs, known as 3 hinge gyri (3HGs). Cortical features, including cortical thickness, curvature, sulcal depth, fractal dimension, and local gyrification index, were extracted from 3HGs and used to train the DET model.
The DET model projects the extracted features of each subject to a high‐dimensional embedding space. The order constraint conditions the inter‐group relationship while the Mini‐Mental State Examination (MMSE) scores are incorporated to model the inter‐subject continuous relationship in embedding space, shown in Figure 1. Additionally, our model supports the classification task based on the proximity of the subjects in the embedding space, providing both continuous relationship and diagnostic capability.
Result:
The DET framework has achieved superior performance on the classification task across all the evaluation metrics compared to the traditional machine learning based methods, as demonstrated in Table 1. Figure 2 shows that the CN, AD patients, LBD patients are projected to the DET based on the learned representations in the embedding space.
Conclusion:
The DET framework effectively models the continuous relationships among CN, AD, and LBD subjects and outperforms the traditional models in the classification task. By leveraging cortical features of the cortical hubs and the MMSE‐based constraints, it provides valuable insights into disease progression
eSLOE 2.0: Examining Data From the First 2 Application Cycles of the Updated Emergency Medicine Electronic Standardized Letter of Evaluation
No full textBackground: The emergency medicine (EM) Standardized Letter of Evaluation (SLOE) was created to provide a standardized, concise, and differentiated evaluation of EM residency applicants. It was revised in 2022 (eSLOE 2.0) to better align with the shift toward competency-based evaluations in undergraduate and graduate medical education.
Objective: To investigate how applicants were rated by evaluators on the new competency-based component and revised normative-based components of the eSLOE 2.0 and to establish preliminary validity for the new letter format.
Methods: Data from the first 2 application cycles utilizing the eSLOE 2.0 (2022-2023, 2023-2024) were accessed via a national EM database. The data specifically from parts A (core EM clinical skills), B (professionalism and interpersonal skills), and C (anticipated guidance during residency and rank list placement) were examined.
Results: Data from the 11 789 letters, representing 6543 unique applicants, revealed that 44.8% to 71.7% of applicants were designated as fully entrustable, and 27% to 50.7% as mostly entrustable on part A skills. Most applicants (81.7% to 85.7%) were placed as either 4 or 5 (1-5 Likert scale) in each part B skill. Nearly fifty-two percent (n=6076) were anticipated to need standard guidance in residency, while 32.8% (n=3872) were anticipated to need minimal guidance and 15.6% (n=1841) to need moderate or most guidance. In part C, 20.5% (n=2414) were designated as being in the top 10% on the rank list, 37.2% (n=4381) in the top third, 31.6% (n=3727) in the middle third, and 10.0% (n=1178) in the lower third.
Conclusions: The findings from the first 2 years of utilizing the eSLOE 2.0 format offer preliminary validity data on this new letter format
Metabolic Phenotype of Stage 1 and Stage 2 Type 1 Diabetes Using Modeling of β Cell Function
No full textBackground: Staging preclinical type 1 diabetes (T1D) and monitoring the response to disease-modifying treatments rely on the oral glucose tolerance test (OGTT). However, it is unknown whether OGTT-derived measures of beta cell function can detect subtle changes in metabolic phenotype, thus limiting their usability as endpoints in prevention trials.
Objective: To describe the metabolic phenotype of people with Stage 1 and Stage 2 T1D using metabolic modelling of β cell function.
Methods: We characterized the metabolic phenotype of individuals with islet autoimmunity in the absence (Stage 1) or presence (Stage 2) of dysglycemia. Participants were screened at a TrialNet site and underwent a 5-point, 2-hour OGTT. Standard measures of insulin secretion (area under the curve, C-peptide, Homeostatic Model Assessment [HOMA] 2-B) and sensitivity (HOMA Insulin Resistance, HOMA2-S, Matsuda Index) and oral minimal model-derived insulin secretion (φ total), sensitivity (sensitivity index), and clearance were adopted to characterize the cohort.
Results: Thirty participants with Stage 1 and 27 with Stage 2T1D were selected. Standard metrics of insulin secretion and sensitivity did not differ between Stage 1 and Stage 2 T1D, while the oral minimal model revealed lower insulin secretion (P < .001) and sensitivity (P = .034) in those with Stage 2 T1D, as well as increased insulin clearance (P = .006). A higher baseline φ total was associated with reduced odds of disease progression, independent of stage (OR 0.92 [0.86, 0.98], P = .016).
Conclusion: The oral minimal model describes the differential metabolic phenotype of Stage 1 and Stage 2 T1D and identifies the φ total as a progression predictor. This supports its use as a sensitive tool and endpoint for T1D prevention trials
Assessment and classification of sex cord-stromal tumours of the testis: recommendations from the testicular sex cord-stromal tumour (TESST) group, an Expert Panel of the Genitourinary Pathology Society (GUPS) and International Society of Urological Pathology (ISUP)
No full textAims: Testicular sex cord-stromal tumours (TSCSTs) are relatively rare, accounting for ~5% of all testicular neoplasms. They were historically classified into Leydig cell tumour, Sertoli cell tumour, granulosa cell tumour, and unclassified sex cord-stromal tumour. More recently, classification was expanded to incorporate additional histologic types, including some associated with inherited cancer predisposition syndromes. However, the classification of TSCSTs still relies entirely on morphology, with some tumour types being defined based on their resemblance to ovarian counterparts. In recent years, molecular studies have identified drivers and genomic alterations associated with aggressive behaviour and progression; however, these findings have not yet impacted classification and management.
Methods and results: Under sponsorship of the International Society of Urological Pathology (ISUP) and the Genitourinary Pathology Society (GUPS), a group of genitourinary pathologists was assembled in 2023 with the aim of assessing how to use these new data to improve the classification and management of TSCSTs.
Conclusions: This paper summarizes the recommendations derived from the consensus activities and the first meeting of the testicular sex cord-stromal tumour (TESST) group (held at Johns Hopkins Hospital, Baltimore, USA, 3/23/2024)