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Six dogs were diagnosed with protein-losing enteropathy (PLE). There was no evidence of inappropriate inflammatory infiltrates or lymphangiectasia in multiple mucosal biopsies of the small intestine of 4 of the dogs. The 5th and 6th dogs had obvious lymphangiectasia and a moderate infiltrate of inflammatory cells in the intestinal mucosa. All 6 dogs had a large number of dilated intestinal crypts that were filled with mucus, sloughed epithelial cells, and/or inflammatory cells. Whether PLE occurs in these dogs because of protein lost from the dilated crypts into the intestinal lumen or whether the dilated crypts are a mucosal reaction due to another undetermined lesion that is responsible for alimentary tract protein loss is unknown. However, when large numbers of dilated intestinal crypts are present, they appear to be associated with PLE even if there are no other remarkable lesions in the intestinal mucosa.Key words: Gastroduodenoscopy; Hypoalbuminemia; Intestinal biopsy; Lymphangiectasia P rotein-losing enteropathy (PLE) is a syndrome in which there is excessive loss of protein from the gastrointestinal tract. In general, PLE is only recognized after animals become hypoalbuminemic, 1,2 although enteropathies in people can produce excessive alimentary protein loss without causing abnormal serum protein concentrations. PLE has been well described in the dog, and certain breeds, such as the Lundehund, 3 Basenji, 4 and Soft-coated Wheaten Terrier 5 appear to be at increased risk of PLE. Various intestinal lesions may be associated with PLE, including lymphangiectasia, immunoproliferative enteropathy, lymphocyticplasmacytic enteritis, eosinophilic enteritis, gastrointestinal ulceration/erosion, giardiasis, chronic intussusception, small intestinal bacterial overgrowth, neoplasia, hypoalbuminemia causing mucosal edema, increased activation of tissue plasminogen activator, systemic lupus erythematosus, vascular lesions in the intestinal mucosa, and chemotherapy/ radiation therapy. [6][7][8][9][10][11][12][13][14][15][16][17][18][19] Most of these diseases can be diagnosed by gross examination or by light microscopic examination of small intestinal tissue samples. However, some of these diseases such as systemic lupus erythematosus or small intestinal bacterial overgrowth cannot reliably be identified with biopsy and routine histopathology. 15,20 Although lesions of small intestinal crypts have been associated with PLE in 1 dog, this dog also had absence of villi and large areas of mucosal ulceration. 21 In this paper, we describe 6 dogs with PLE in which a large number of intestinal crypts were dilated and filled with mucus, with or without inflammatory cellular debris. None of our dogs had discernable ulceration or lack of villi. The purpose of this report is to document this histologic lesion and its apparent association with PLE in the dog. Materials and MethodsThe cases reported were examined at Texas A&M University between 1989 and 1999, and at Michigan State University in 1997. All dogs had panhypoproteinemia...

Six dogs were diagnosed with protein losing enteropathy (PLE). There was no evidence of inappropriate inflammatory infiltrates or lymphangiectasia in multiple mucosal biopsies of the small intestine of 4 of the dogs. The 5th and 6th dogs had obvious lymphangiectasia and a moderate infiltrate of inflammatory cells in the intestinal mucosa. All 6 dogs had a large number of dilated intestinal crypts that were filled with mucus, sloughed epithelial cells, and/or inflammatory cells. Whether PLE occurs in these dogs because of protein lost from the dilated crypts into the intestinal lumen or whether the dilated crypts are a mucosal reaction due to another undetermined lesion that is responsible for alimentary tract protein loss is unknown. However, when large numbers of dilated intestinal crypts are present, they appear to be associated with PLE even if there are no other remarkable lesions in the intestinal mucosa.

The COVID-19 pandemic led to suspension of in-person learning at many higher education institutions (HEIs) in March 2020. In response, HEIs transitioned most courses to online formats immediately and continued this mode of instruction through the 2020-2021 academic year. In fall 2021, numerous HEIs resumed in-person courses and some hybrid courses, and faculty began noting academic-related behavior deficiencies not previously observed in students. Focus groups of teaching faculty (n=8) from one university department were conducted to gather information on changes in student academic-related behaviors attributed to the disruption of teaching and learning due to COVID-19, and to compare observed deficiencies with the university's undergraduate learning goals. Mind mapping software was utilized to capture themes and subthemes. Identified themes were related to: problem-solving skills, grades, time management, attendance, and interpersonal communication, both in terms of student-to-student and student-to-faculty communication. For these identified areas, outcomes during the return to in-person learning were mostly undesirable. Based on these identified issues, suggested modifications that HEIs could use to modify course content and delivery to offset skill gaps and improve interpersonal communication were identified. Furthermore, observations may indicate that fully remote learning inhibited student learning and skill development during the 2020-2021 academic year. Future work should examine the effectiveness of the proposed modifications on student success.

Transition cow diseases can negatively impact animal welfare and reduce dairy herd profitability. Transition cow disease incidence has remained relatively stable over time despite monitoring and management efforts aimed to reduce the risk of developing diseases. Dairy cattle disease risk is monitored by assessing multiple factors, including certain biomarker test results, health records, feed intake, body condition score, and milk production. However, these factors, which are used to make herd management decisions, are often reviewed separately without considering the correlation between them. In addition, the biomarkers that are currently used for monitoring may not be representative of the complex physiological changes that occur during the transition period. Predictive modeling, which uses data to predict future or current outcomes, is a method that can be used to combine the most predictive variables and their interactions efficiently. The use of an effective predictive model with relevant predictors for transition cow diseases will result in better targeted interventions, and therefore lower disease incidence. This review will discuss predictive modeling methods and candidate variables in the context of transition cow diseases. The next step is to investigate novel biomarkers and statistical methods that are best suited for the prediction of transition cow diseases.