Evaluation of endometrial echotexture and cervical cytology in cows during and after treatment of endometritis

A lung cancer risk warning model based on tongue images

Objective: To investigate the tongue image features of patients with lung cancer and benign pulmonary nodules and to construct a lung cancer risk warning model using machine learning methods. Methods: From July 2020 to March 2022, we collected 862 participants including 263 patients with lung cancer, 292 patients with benign pulmonary nodules, and 307 healthy subjects. The TFDA-1 digital tongue diagnosis instrument was used to capture tongue images, using feature extraction technology to obtain the index of the tongue images. The statistical characteristics and correlations of the tongue index were analyzed, and six machine learning algorithms were used to build prediction models of lung cancer based on different data sets. Results: Patients with benign pulmonary nodules had different statistical characteristics and correlations of tongue image data than patients with lung cancer. Among the models based on tongue image data, the random forest prediction model performed the best, with a model accuracy of 0.679 ± 0.048 and an AUC of 0.752 ± 0.051. The accuracy for the logistic regression, decision tree, SVM, random forest, neural network, and naïve bayes models based on both the baseline and tongue image data were 0.760 ± 0.021, 0.764 ± 0.043, 0.774 ± 0.029, 0.770 ± 0.050, 0.762 ± 0.059, and 0.709 ± 0.052, respectively, while the corresponding AUCs were 0.808 ± 0.031, 0.764 ± 0.033, 0.755 ± 0.027, 0.804 ± 0.029, 0.777 ± 0.044, and 0.795 ± 0.039, respectively. Conclusion: The tongue diagnosis data under the guidance of traditional Chinese medicine diagnostic theory was useful. The performance of models built on tongue image and baseline data was superior to that of the models built using only the tongue image data or the baseline data. Adding objective tongue image data to baseline data can significantly improve the efficacy of lung cancer prediction models.

Differences in mean grey levels of uterine ultrasonographic images between non-pregnant and pregnant ewes may serve as a tool for early pregnancy diagnosis

The aim of this study was to determine how physiological and hormonal changes in the uterus during the estrous cycle and early gestational period affect the average grey values of pixels when conducting computer-assisted analysis of uterine ultrasonic images in ewes. For this purpose, 60 ewes on which there had been an estrous synchrony regimen imposed were included in the study. Animals were assigned to two groups with ewes not being mated and assessments occurred during the subsequent estrous cycle (Group 1; n = 25) and ewes being mated and assessments occurring during the subsequent early gestational period (Group 2; n = 35). Ewes were examined utilizing real time ultrasonic procedures and uterine images were obtained. Digital analysis of uterine ultrasonographic images was performed using image J program and mean grey levels (MGL) were determined. Values for progesterone concentrations were consistent with those previously reported in non-pregnant and pregnant ewes. There was a close association between MGL values in ewes of both Group I (P < 0.05) and II (P < 0.05) and days of the estrous cycle. There was also an association between MGL values and day of the gestational period in ewes of Group 2(P < 0.001). In conclusion, there are differences in MGL values between non-pregnant and pregnant ewes with there being changes as days of the estrous cycle and day of gestation period advances, therefore, this procedure could be used as a pregnancy diagnostic criterion during the early period of gestation in ewes.

Effect of Intrauterine Infusion of Momordica Charantia L. on Oxidative Stress and Pregnancy Rate in Infertile Cows

Introduction

The effect of intrauterine administration of Momordica charantia L. (MC) extract on oxidative changes and pregnancy rate in infertile cows was investigated.

Material and Methods

Endometrial smear specimens were taken from 40 cows with fertility problems for cytological examination, and the cows were randomly divided into two groups: group I (n = 20) was subjected to intrauterine administration of 40 mL (0.25 g/mL) of MC extract, group II (n = 20) was subjected to intrauterine administration of 40 mL of pure olive oil. Blood samples were taken starting from the day of administration of MC extract or olive oil (day 0) and then for three weeks at weekly intervals (days 7, 14, 21). Blood serum samples were evaluated for total antioxidant capacity (TAS), total oxidant level (TOS), oxidative stress index (OSI), lipid hydroperoxide (LOOH), and nitric oxide (NO) levels. In addition, on the 14^th day following treatment, two doses of PGF2α were administrated to all cows at 14-day intervals. Following the second PGF2α administration, insemination and GnRH administration was performed at the 60^th h after PGF2α treatment. Smear samples were stained with Giemsa and immunohistochemically to determine cytological changes and inflammatory status.

Results

According to cytological findings, subclinical endometritis was a prevalent disorder in cows with infertility problem (82.5%; 33/40). Additionally, 60.6% (20/33) of the cows with subclinical endometritis had acute inflammation, whereas remaining 13 cows had chronic endometritis. Of the cows with subclinical endometritis, 50% (8/16) and 35% (6/17) became pregnant in group I and II, respectively (P > 0.05). Although the oxidative stress parameters showed similarities between both groups (P > 0.05), there was a significant difference (P < 0.001) between the groups in terms of mean NO and LOOH levels (NO - 31.20 ± 11.38 vs 44.53 ± 11.50 μmol/L and LOOH - 1.22 ± 0.37 vs 1.89 ± 0.36 μmol/L).

Conclusion

The obtained results indicated that MC administration, especially in the presence of active inflammation, may improve the pregnancy rate by positive reduction of oxidative changes.

Characterization of inflammatory responses by cervical cytology, cytokine expression and ultrastructure changes in a goat subclinical endometritis model

Endometritis is a common puerperal disease in livestock. Thus, a practical clinical test for the establishment of diagnosis is needed. We developed a goat model for subclinical endometritis diagnosis by examining cytological, ultrastructural features and molecular expression in cervical discharge collected by cervical cytobrush method. A suspension of E. coli was infused into the uterine horn of goats, and cervical discharge, peripheral blood and endomertrial biopsy samples were collected before inoculation and at 3, 6, 12, 24, 72, 120 and 168 hr post-inoculation (pi). In experimental goats, total leukocytes increased at 6-12 hr pi in hematological examinations, abundant neutrophils were observed in cervical discharge smears, and some micro-villi shortened or were lost from the epithelium at 3 hr pi, with some inflammatory cells infiltrated into the uterine glands and lamina propria. The mRNA expression levels of the Toll-like receptor 4 (TLR4), cytokines and β-defensin-2 increased significantly within 12 hr pi and returned to pre-inoculation levels at 7 day pi. The results showed that subclinical endometritis was simulated in this bacterial infusion goat model, and the evaluation of cervical cytology was in good agreement with molecular changes of cytokines in cervical discharge, hematology and histology. We thus conclude that the simple cervical cytobrush technique can effectively obtain cervical discharge samples for cytology examination in the early diagnosis of subclinical endometritis in goats.

Endometrial echotexture variables in postpartum cows with subclinical endometritis

The aim of this study was to evaluate endometrial echotexture changes on ultrasonographic digital images during subclinical endometritis using a computer-assisted image analysis program. Endometrial samples were collected from 140 Brown Swiss cows (days in milk = 35 ± 3) using a cytobrush method and classified as having a non-inflamed uterus (n = 66) and uterus with acute (n = 42), subacute (n = 21), and chronic (n = 11) inflammations. The mean cellular infiltration density was 0%, 31 ± 5%, 37 ± 6%, and 16 ± 8% for cows with non-inflamed uterus and cows with acute, subacute, and chronic uterine inflammations (P < 0.0001). As the cell infiltration density increased, both cervical diameter and mean gray level did not change. There were a liner decrease in homogeneity and a linear increase in contrast in response to increased cellular infiltration density. The sensitivity and specificity were 79.73% and 46.97% for the homogeneity value and 59.46% and 69.70% for the contrast value, respectively. In conclusion, monitoring endometrial echotexture alterations, especially homogeneity and contrast, changed depending on the cellular density and inflammation status and may be potential diagnostic markers for subclinical endometritis in cows.