📚 Journal Papers

Abstract Addison’s disease (AD) results in glucocorticoid and mineralocorticoid deficiencies and is often immune-mediated. While AD is uncommon in dogs, Nova Scotia Duck Tolling Retrievers (NSDTRs) exhibit increased incidence, suggesting genetic predisposition. Detailed clinical evaluation of 24 juvenile-onset cases revealed that while all dogs presented with adrenal insufficiency, at least 10 dogs (41.7%) had concurrent autoimmune conditions. This suggests juvenile-onset AD in NSDTRs represents part of a broader multiple autoimmune syndrome (MAS) with variable expressivity. Strikingly, NSDTRs affected by juvenile-onset AD had severely decreased lifespans, with a median survival of 2 years despite appropriate treatment. Genome-wide association identified a significant association on chromosome 27 (chr27:29,724,286, p  = 6.96 × 10 − 13 ). Whole-genome, short-read sequencing identified a recessive missense variant in RESF1 (Chr27:29,736,795). The variant exhibited 76% penetrance for early-onset disease, and the decreased penetrance was not attributable to differences in Dog Leukocyte Antigen (DLA) haplotypes. Immunohistochemistry confirmed T cell infiltration in the adrenal cortex of two unrelated affected dogs, with necropsy findings including severe bilateral lymphocytic adrenalitis, multisystemic granulomatous inflammation, and lymphoplasmacytic conjunctivitis supporting autoimmune pathogenesis. This study identifies RESF1 as a novel gene associated with autoimmune disease in NSDTRs, ranging from isolated juvenile-onset AD to multi-organ autoimmune manifestations. The findings represent a rare example of monogenic autoimmune disease and establish RESF1 as a candidate gene for further investigation of immune tolerance mechanisms.

Abstract Soil erosion poses a significant challenge to environmental sustainability, especially in regions with varying land-use patterns and topography. Soil erosion is a major environmental threat affecting soil quality, reservoir sedimentation, agricultural land, and watershed hydrology. This study aims to identify and classify homogeneous sub-watersheds in a mountainous watershed in Iran using GIS. Forty years of climate data, a high-resolution DEM, land-use maps, soil texture, and NDVI were applied to derive the main factors, while the P factor was determined based on slope classes and land-use types. The RUSLE results showed that annual soil erosion in the watershed had an average of about 7-ton ha⁻¹ year⁻¹, with more than 65% of the watershed area falling into the moderate to very high erosion classes. Average key factors were R  = 78.08 MJ·mm/ha·hr·year, K = 0.28 t·ha·h/MJ·mm·ha, LS = 1.62, and C = 0.39. The highest erosion occurred in areas with heavy rainfall, steep and long slopes, fine-textured soils, and sparse vegetation. Spatial autocorrelation analysis using Moran’s I and the Getis–Ord Gi* statistic showed a clustered spatial pattern of erosion. High–high (HH) clusters, indicating severe erosion hotspots, were found in the southwest, while low–low (LL) clusters, representing minimal erosion coldspots, occurred in the north and northeast. These results support sub-watershed prioritization and indicate the need for targeted erosion control in high-rate zones. These results contribute to the development of more targeted and sustainable land management practices to mitigate soil erosion rates and improve watershed conservation efforts.

Abstract The decomposition of walnut litter components (leaves, husks, and male inflorescences) were studied to understand the decomposition process and its role in the soil fertility in walnut plantation in the southern Taihang Mountains of Hebei Province, China. The experiment was carried out at a walnut plantation in the southern Taihang Mountains of Hebei Province, China. The analysis focused on the dynamic changes of four mineral elements, trace elements, and lignin. The results showed that during the 300-day decomposition period, the mass residue percentages of the three types of litter were leaves (64.92%), husks (37.90%), and male inflorescences (21.33%). The 120th day was a turning point in the decomposition process. Before this, the decomposition process was active and relatively rapid; after reaching this inflection point, the rate of decomposition tended to stabilize. The Olson model was used to simulate and predict the decomposition process of three types of litter. The order of the decomposition coefficient k for litter types was male inflorescence > husks > leaves. The higher the k value, the greater the decomposition rate. The 50% decomposition time estimates for leaves, husks, and male inflorescences were 1.28a, 0.53a, and 0.39a, respectively, with values of 5.54a, 2.28a, and 1.68a for 95% decomposition, respectively. After 300 days, according to the criterion of NR < 100%, the C, N, P, K, and lignin contents of the three types of litter showed a net release state, with a wave release decomposition form and a small enrichment phenomenon occurring during the process. Compared with the initial state of decomposition, the four trace elements generally exhibited a net release state.

Abstract Regional genomic surveillance is essential for tracking viral evolution and informing targeted public health responses. During the COVID-19 pandemic, we established a collaborative genomic surveillance pipeline for SARS-CoV-2 in Southeast Michigan to support national surveillance efforts and guide local pandemic response strategies. This work aims to present the methods and resources we have achieved during this effort and demonstrates the feasibility of such a collaboration. A partnership between Wayne State University (WSU), the Detroit Health Department (DHD), Henry Ford Health (HFH), the Wayne Health Mobile Unit (WHMU), and the Michigan Department of Health and Human Services (MDHHS) was established to collect, sequence, and analyze SARS-CoV-2 samples. Samples underwent automated nucleic acid extraction, RT-qPCR testing, and whole genomic sequencing at WSU’s integrative biosciences center (IBio). We analyzed consensus genome sequences using high-performance computing infrastructure for lineage assignment and variant identification. Between January 2022 and July 2024, we collected and archived 7508 samples, with 6235 (83.0%) successfully sequenced. A sub-analysis of 4637 HFH samples explored geographic distributions across 295 Michigan ZIP codes. Compared to the overall proportion of deaths among all people with SARS-CoV-2 positive tests in the sample (3.6% [95% CI (3.1, 4.2)]), the case-fatality rate was significantly increased with the 19 A + B [7.69%, 95% CI (5.03, 11.58)] and 20A (European 2 lineage: EU2) [9.65%, 95% CI (7.72, 11.99)] variants. The frequency distributions of variants showed a strong correlation ( r  = 0.98) with Michigan’s statewide data reported in GISAID. Omicron was the most prevalent variant detected (64% of cases). Our program demonstrated capacity for academic-public health partnerships to detect SARS-CoV-2 variant circulation in Southeast Michigan. This framework provides a replicable model for future pathogen surveillance programs to build on in response to infectious disease outbreaks.

Abstract Mycoplasma anserisalpingitidis is a facultative pathogenic bacterium affecting waterfowl, predominantly geese and sporadically ducks. Understanding the molecular basis of antimicrobial resistance mechanisms is crucial in the preservation of antibiotic efficiency. This study aimed to elucidate the genetic background of antibiotic susceptibility profiles of 110 M . anserisalpingitidis strains against nine antimicrobial agents. Significant associations between k-mers and five (tylvalosin, tilmicosin, enrofloxacin, lincomycin, spectinomycin) of the nine antimicrobial agents were identified by pyseer. Significant associations were found in multiple coding sequences that encode various members of efflux pumps, epigenetic regulation and topoisomerases among many other groups of functions. Certain k-mers associated with genes found putative prophage-like sequences suggest potential horizontal gene transfer events that could facilitate the acquisition of novel resistance mechanisms. Based on our findings, the genetic background of antimicrobial resistance of M. anserisalpingitidis is composed of multiple factors. Our results not only correlated with the majority of known antibiotic resistance mechanisms (e.g. drug target modification, efflux pumps, methyltransferases) but also showed potentially novel genes that could play a significant role in antimicrobial resistance. The results may serve to expedite the diagnosis of M. anserisalpingitidis antibiotic susceptibility profiles and support the fight against the spreading of resistance.