Citations

Significance Repression of the large number of transposable elements in eukaryotic genomes is essential for genome stability. The Piwi-interacting RNA and short interfering RNA pathways are critical for repressing transposable elements in germlines, but the repression of transposable elements in somatic tissues involves other components. While the mammalian Hinfp has been shown to regulate Histone4 and cell-cycle progression, our manuscript provides evidence that a function of the Drosophila Hinfp is to maintain Histone1 expression to repress most transposable elements in somatic genomes. This Hinfp–Histone1 axis provides a venue to study maintenance of genome stability and progression of pathological outcomes.

ABSTRACT Background Hospitalized patients with hypokalemia are heterogeneous and cluster analysis, an unsupervised machine learning methodology, may discover more precise and specific homogeneous groups within this population of interest. Our study aimed to cluster patients with hypokalemia at hospital admission using an unsupervised machine learning approach and assess the mortality risk among these distinct clusters. Methods We performed consensus clustering analysis based on demographic information, principal diagnoses, comorbidities and laboratory data among 4763 hospitalized adult patients with admission serum potassium ≤3.5 mEq/L. We calculated the standardized mean difference of each variable and used the cutoff of ±0.3 to identify each cluster's key features. We assessed the association of the hypokalemia cluster with hospital and 1-year mortality. Results Consensus cluster analysis identified three distinct clusters that best represented patients’ baseline characteristics. Cluster 1 had 1150 (32%) patients, cluster 2 had 1344 (28%) patients and cluster 3 had 1909 (40%) patients. Based on the standardized difference, patients in cluster 1 were younger, had less comorbidity burden but higher estimated glomerular filtration rate (eGFR) and higher hemoglobin; patients in cluster 2 were older, more likely to be admitted for cardiovascular disease and had higher serum sodium and chloride levels but lower eGFR, serum bicarbonate, strong ion difference (SID) and hemoglobin, while patients in cluster 3 were older, had a greater comorbidity burden, higher serum bicarbonate and SID but lower serum sodium, chloride and eGFR. Compared with cluster 1, cluster 2 had both higher hospital and 1-year mortality, whereas cluster 3 had higher 1-year mortality but comparable hospital mortality. Conclusion Our study demonstrated the use of consensus clustering analysis in the heterogeneous cohort of hospitalized hypokalemic patients to characterize their patterns of baseline clinical and laboratory data into three clinically distinct clusters with different mortality risks.

Abstract The TDP-43 type C pathological form of frontotemporal lobar degeneration is characterized by the presence of immunoreactive TDP-43 short and long dystrophic neurites, neuronal cytoplasmic inclusions, neuronal loss and gliosis and the absence of neuronal intranuclear inclusions. Frontotemporal lobar degeneration-TDP-type C cases are commonly associated with the semantic variant of primary progressive aphasia or behavioural variant frontotemporal dementia. Here, we provide detailed characterization of regional distributions of pathological TDP-43 and neuronal loss and gliosis in cortical and subcortical regions in 10 TDP-type C cases and investigate the relationship between inclusions and neuronal loss and gliosis. Specimens were obtained from the first 10 TDP-type C cases accessioned from the Northwestern Alzheimer’s Disease Research Center (semantic variant of primary progressive aphasia, n = 7; behavioural variant frontotemporal dementia, n = 3). A total of 42 cortical (majority bilateral) and subcortical regions were immunostained with a phosphorylated TDP-43 antibody and/or stained with haematoxylin–eosin. Regions were evaluated for atrophy, and for long dystrophic neurites, short dystrophic neurites, neuronal cytoplasmic inclusions, and neuronal loss and gliosis using a semiquantitative 5-point scale. We calculated a ‘neuron-to-inclusion’ score (TDP-type C mean score – neuronal loss and gliosis mean score) for each region per case to assess the relationship between TDP-type C inclusions and neuronal loss and gliosis. Primary progressive aphasia cases demonstrated leftward asymmetry of cortical atrophy consistent with the aphasic phenotype. We also observed abundant inclusions and neurodegeneration in both cortical and subcortical regions, with certain subcortical regions emerging as particularly vulnerable to dystrophic neurites (e.g. amygdala, caudate and putamen). Interestingly, linear mixed models showed that regions with lowest TDP-type C pathology had high neuronal dropout, and conversely, regions with abundant pathology displayed relatively preserved neuronal densities (P < 0.05). This inverse relationship between the extent of TDP-positive inclusions and neuronal loss may reflect a process whereby inclusions disappear as their associated neurons are lost. Together, these findings offer insight into the putative substrates of neurodegeneration in unique dementia syndromes.

Background: We aimed to cluster patients with acute kidney injury at hospital admission into clinically distinct subtypes using an unsupervised machine learning approach and assess the mortality risk among the distinct clusters. Methods: We performed consensus clustering analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 4289 hospitalized adult patients with acute kidney injury at admission. The standardized difference of each variable was calculated to identify each cluster’s key features. We assessed the association of each acute kidney injury cluster with hospital and one-year mortality. Results: Consensus clustering analysis identified four distinct clusters. There were 1201 (28%) patients in cluster 1, 1396 (33%) patients in cluster 2, 1191 (28%) patients in cluster 3, and 501 (12%) patients in cluster 4. Cluster 1 patients were the youngest and had the least comorbidities. Cluster 2 and cluster 3 patients were older and had lower baseline kidney function. Cluster 2 patients had lower serum bicarbonate, strong ion difference, and hemoglobin, but higher serum chloride, whereas cluster 3 patients had lower serum chloride but higher serum bicarbonate and strong ion difference. Cluster 4 patients were younger and more likely to be admitted for genitourinary disease and infectious disease but less likely to be admitted for cardiovascular disease. Cluster 4 patients also had more severe acute kidney injury, lower serum sodium, serum chloride, and serum bicarbonate, but higher serum potassium and anion gap. Cluster 2, 3, and 4 patients had significantly higher hospital and one-year mortality than cluster 1 patients (p < 0.001). Conclusion: Our study demonstrated using machine learning consensus clustering analysis to characterize a heterogeneous cohort of patients with acute kidney injury on hospital admission into four clinically distinct clusters with different associated mortality risks.

Intestinal fibrosis is considered an inevitable complication of Crohn’s disease (CD) that results in symptoms of obstruction and stricture formation. Endoscopic or surgical treatment is required to treat the majority of patients. Progress in the management of stricturing CD is hampered by the lack of effective antifibrotic therapy; however, this situation is likely to change because of recent advances in other fibrotic diseases of the lung, liver, and skin. In this review, we summarize data from randomized controlled trials (RCTs) of antifibrotic therapies in these conditions. Multiple compounds have been tested for antifibrotic effects in other organs. According to their mechanisms, they were categorized into growth factor modulators, inflammation modulators, 5-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitors, intracellular enzymes and kinases, renin-angiotensin system (RAS) modulators, and others. From our review of the results from the clinical trials and discussion of their implications in the gastrointestinal tract, we have identified several molecular candidates that could serve as potential therapies for intestinal fibrosis in CD.

Background: The goal of this study was to categorize patients with abnormal serum phosphate upon hospital admission into distinct clusters utilizing an unsupervised machine learning approach, and to assess the mortality risk associated with these clusters. Methods: We utilized the consensus clustering approach on demographic information, comorbidities, principal diagnoses, and laboratory data of hypophosphatemia (serum phosphate ≤ 2.4 mg/dL) and hyperphosphatemia cohorts (serum phosphate ≥ 4.6 mg/dL). The standardized mean difference was applied to determine each cluster’s key features. We assessed the association of the clusters with mortality. Results: In the hypophosphatemia cohort (n = 3113), the consensus cluster analysis identified two clusters. The key features of patients in Cluster 2, compared with Cluster 1, included: older age; a higher comorbidity burden, particularly hypertension; diabetes mellitus; coronary artery disease; lower eGFR; and more acute kidney injury (AKI) at admission. Cluster 2 had a comparable hospital mortality (3.7% vs. 2.9%; p = 0.17), but a higher one-year mortality (26.8% vs. 14.0%; p < 0.001), and five-year mortality (20.2% vs. 44.3%; p < 0.001), compared to Cluster 1. In the hyperphosphatemia cohort (n = 7252), the analysis identified two clusters. The key features of patients in Cluster 2, compared with Cluster 1, included: older age; more primary admission for kidney disease; more history of hypertension; more end-stage kidney disease; more AKI at admission; and higher admission potassium, magnesium, and phosphate. Cluster 2 had a higher hospital (8.9% vs. 2.4%; p < 0.001) one-year mortality (32.9% vs. 14.8%; p < 0.001), and five-year mortality (24.5% vs. 51.1%; p < 0.001), compared with Cluster 1. Conclusion: Our cluster analysis classified clinically distinct phenotypes with different mortality risks among hospitalized patients with serum phosphate derangements. Age, comorbidities, and kidney function were the key features that differentiated the phenotypes.

Background and Objectives: Despite the association between hyperchloremia and adverse outcomes, mortality risks among patients with hyperchloremia have not consistently been observed among all studies with different patient populations with hyperchloremia. The objective of this study was to characterize hyperchloremic patients at hospital admission into clusters using an unsupervised machine learning approach and to evaluate the mortality risk among these distinct clusters. Materials and Methods: We performed consensus cluster analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 11,394 hospitalized adult patients with admission serum chloride of >108 mEq/L. We calculated the standardized mean difference of each variable to identify each cluster’s key features. We assessed the association of each hyperchloremia cluster with hospital and one-year mortality. Results: There were three distinct clusters of patients with admission hyperchloremia: 3237 (28%), 4059 (36%), and 4098 (36%) patients in clusters 1 through 3, respectively. Cluster 1 was characterized by higher serum chloride but lower serum sodium, bicarbonate, hemoglobin, and albumin. Cluster 2 was characterized by younger age, lower comorbidity score, lower serum chloride, and higher estimated glomerular filtration (eGFR), hemoglobin, and albumin. Cluster 3 was characterized by older age, higher comorbidity score, higher serum sodium, potassium, and lower eGFR. Compared with cluster 2, odds ratios for hospital mortality were 3.60 (95% CI 2.33–5.56) for cluster 1, and 4.83 (95% CI 3.21–7.28) for cluster 3, whereas hazard ratios for one-year mortality were 4.49 (95% CI 3.53–5.70) for cluster 1 and 6.96 (95% CI 5.56–8.72) for cluster 3. Conclusions: Our cluster analysis identified three clinically distinct phenotypes with differing mortality risks in hospitalized patients with admission hyperchloremia.

Abstract BackgroundThe presence of white matter hyperintensities (WMH) in migraine is well-documented, but the location of brain WMH in patients with migraine are insufficiently researched. Although recent semi-automatic software packages have been developed for calculating WMH, visual inspection remains the gold standard for measuring WMH. The goal of this study was to assess WMH in patients with migraine using a modified version of the Scheltens visual rating scale, a semiquantitative scale for categorizing WMH in the following brain regions: periventricular, lobar (frontal, temporal, parietal, occipital), basal ganglia, and infratentorial regions.Methods263 patients with migraine (31 male/232 female; mean age: 48.0) who were enrolled in the American Registry for Migraine Research from Mayo Clinic with a diagnosis of episodic (n = 46; 17.5%) or chronic migraine (n = 217; 82.5%) and who had brain magnetic resonance imaging were included in this study. Those with imaging evidence for gross anatomical abnormalities other than WMH were excluded. WMH were identified on axial T2 and FLAIR sequences by a board certified neuroradiologist. WMH were characterized via manual inspection and categorized according to the scale’s criteria.Results95 patients (36.1 %: mean age: 41.8) had no WMH on axial T2 and FLAIR imaging and 168 patients (63.9%, mean age: 51.4) had WMH. Of those with WMH, 94.1% (n = 158) had lobar hyperintensities (frontal: 148/158, 93.7%; parietal: 57/158, 36.1%; temporal: 35/158, 22.1%; occipital: 9/158, 5.7%), 13/168, 7.7% had basal ganglia WMH, 49/168, 29.1% had periventricular WMH, and 17/168, 10.1% had infratentorial WMH. 101/168 patients (60.1%) had bilateral WMH and 67/168 (39.9%) had unilateral WMH (34 right hemisphere /33 left hemisphere). 30.0% of patients with WMH did not have WMH reported in their clinical radiology reports.DiscussionNearly 2/3 of patients with migraine had WMH. They were most common in the lobar regions, specifically in the frontal lobe. The categorization of WMH in migraine using the modified Scheltens visual rating scale could help in future studies to clarify the relationship between WMH and headache features and might be a useful method for developing classifiers that differentiate between migraine-specific WMH and other causes of WMH.

Background: The objective of this study was to characterize patients with hyponatremia at hospital admission into clusters using an unsupervised machine learning approach, and to evaluate the short- and long-term mortality risk among these distinct clusters. Methods: We performed consensus cluster analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 11,099 hospitalized adult hyponatremia patients with an admission serum sodium below 135 mEq/L. The standardized mean difference was utilized to identify each cluster’s key features. We assessed the association of each hyponatremia cluster with hospital and one-year mortality using logistic and Cox proportional hazard analysis, respectively. Results: There were three distinct clusters of hyponatremia patients: 2033 (18%) in cluster 1, 3064 (28%) in cluster 2, and 6002 (54%) in cluster 3. Among these three distinct clusters, clusters 3 patients were the youngest, had lowest comorbidity burden, and highest kidney function. Cluster 1 patients were more likely to be admitted for genitourinary disease, and have diabetes and end-stage kidney disease. Cluster 1 patients had the lowest kidney function, serum bicarbonate, and hemoglobin, but highest serum potassium and prevalence of acute kidney injury. In contrast, cluster 2 patients were the oldest and were more likely to be admitted for respiratory disease, have coronary artery disease, congestive heart failure, stroke, and chronic obstructive pulmonary disease. Cluster 2 patients had lowest serum sodium and serum chloride, but highest serum bicarbonate. Cluster 1 patients had the highest hospital mortality and one-year mortality, followed by cluster 2 and cluster 3, respectively. Conclusion: We identified three clinically distinct phenotypes with differing mortality risks in a heterogeneous cohort of hospitalized hyponatremic patients using an unsupervised machine learning approach.

The mammalian liver's regenerative ability has led researchers to engineer animals as incubators for expansion of human hepatocytes. The expansion properties of human hepatocytes in immunodeficient mice are well known. However, little has been reported about larger animals that are more scalable and practical for clinical purposes. Therefore, we engineered immunodeficient swine to support expansion of human hepatocytes and identify barriers to their clinical application. Immunodeficient swine were engineered by knockout of the recombinase-activating gene 2 ( RAG2 ) and fumarylacetoacetate hydrolase (FAH). Immature human hepatocytes (ihHCs) were injected into fetal swine by intrauterine cell transplantation (IUCT) at day 40 of gestation. Human albumin was measured as a marker of engraftment. Cytotoxicity against ihHCs was measured in transplanted piglets and control swine. We initially detected higher levels of human albumin in cord blood of newborn FAH/ RAG2 -deficient (FR) pigs compared with immunocompetent controls (196.26 ng/dL vs. 39.29 ng/dL, p = 0.008), indicating successful engraftment of ihHCs after IUCT and adaptive immunity in the fetus. Although rare hepatocytes staining positive for human albumin were observed, levels of human albumin did not rise after birth, but declined, suggesting rejection of xenografted ihHCs. Cytotoxicity against ihHCs increased after birth by 3.8% (95% CI: [2.1%–5.4%], p < 0.001) and inversely correlated with declining levels of human albumin ( p = 2.1 × 10 −5 , R 2 = 0.17). Circulating numbers of T cells and B cells were negligible in FR pigs. However, circulating natural killer (NK) cells exerted cytotoxicity against ihHCs. NK cell activity was lower in immunodeficient piglets after IUCT than in naive controls (30.4% vs. 40.1%, p = 0.011, 95% CI for difference [2.7%–16.7%]). In conclusion, ihHCs were successfully engrafted in FR swine after IUCT. NK cells were a significant barrier to expansion of hepatocytes. New approaches are needed to overcome this hurdle and allow large-scale expansion of human hepatocytes in immunodeficient swine. Impact statement There is currently a need for robust expansion of human hepatocytes. We describe an immunodeficient swine model into which we engrafted immature human hepatocytes (ihHCs). We identified the mechanism of the eventual graft rejection by the intact NK cell population, which has not been previously shown to have a significant role in xenograft rejection. By both improving engraftment and reducing NK cell-mediated cytotoxicity toward the graft through intrauterine cell transfer, we confirmed the presence of residual adaptive immunity in this model of immunodeficiency and the ability to induce hyposensitization in the NK cell population by taking advantage of the fetal microenvironment.