Construction and Validation of Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Patients with Primary Anaplastic Oligodendroglioma.

OBJECTIVE: Anaplastic oligodendroglioma (AOD) is a rare high-grade central nervous system tumor. The current research on prognostic prediction of AOD remains limited. This study aimed to identify prognostic factors and establish the nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with AOD. METHODS: Patients diagnosed with AOD between 1992 and 2020 were extracted from the Surveillance, Epidemiology, and End Result database. We performed univariate and multivariate Cox regression analyses to identify independent prognostic factors based on the training group. Kaplan-Meier survival curves were used to compare the impact of various independent factors on patient prognosis. For OS and CSS, the nomograms were constructed and verified by the validation group. Harrell''s concordance index, receiver operating characteristic curves, calibration curves, and decision curve analyses were used to assess the discrimination, consistency, and clinical value of the nomograms. RESULTS: A total of 1202 AOD patients were enrolled, being randomly divided into training (n = 841) and validation (n = 361) groups (7:3 ratio). Univariate and multivariate Cox analysis identified 4 significant independent factors (tumor site, age, surgery, and chemotherapy). For OS and CSS, Harrell''s concordance index were 0.731 (0.705-0.757) and 0.728 (0.701-0.754) in the training group, 0.688 (0.646-0.731) and 0.684 (0.639-0.729) in the validation group, respectively. Receiver operating characteristic curves and Calibration curves showed good discrimination and consistency, respectively. In addition, the decision curve analyses curves showed the nomograms have good clinical benefits. CONCLUSIONS: We successfully established the nomograms to predict the OS and CSS for AOD patients. The nomograms showed good performance in prognostic prediction, assisting clinicians in evaluating patient prognosis and personalizing treatment plans.

Effect of cloprostenol on luteolysis and comparison of different estrus synchronization protocols in jennies.

Estrus synchronization is necessary for intensive donkey farming. Studies on estrus synchronization in jennies are, however, scarce. We aimed to investigate the susceptibility of the donkey corpus luteum to cloprostenol and design a successful estrus synchronization protocol. Firstly, the effects of different cloprostenol doses and the timing effect of cloprostenol treatment on estrous cycle was investigated. The time from treatment to luteolysis, the ovulation interval, pre-ovulatory diameter, and ovulation rates were compared between groups. Secondly, to identify the best protocol, eight estrus synchronization protocols from three categories were examined. In the first category, jennies in groups A (n = 55) and B (n = 30) received a progesterone releasing intra-vaginal device (JVID®) and cloprostenol treatment. In the second category (group C to F), jennies were pretreated with deslorelin, and then treated with JVID and cloprostenol, including groups C (n = 50), D (n = 50), E (n = 70), and F (n = 65). In the third category, jennies were treated with deslorelin and cloprostenol, including groups G (n = 40) and H (n = 40). Comparisons were made among groups regarding the degree of synchronization, ovulation, and pregnancy rates. Treatment with 0.4 mg cloprostenol on the third day following ovulation minimized the length of the luteal phase and estrous cycle. Synchronization rate varied from 60.0% to 88.6% among groups and was highest in group E. Pregnancy rates did not differ among the eight protocols. In conclusion, cloprostenol effectively induced luteolysis in jennies and a treatment protocol combining deslorelin, cloprostenol, and JVID is efficient for estrus synchronization in donkeys.

Analysis of Prognostic Factors and Surgical Management of Elderly Patients with Low-Grade Gliomas.

BACKGROUND: The number of elderly patients with low-grade glioma (LGG) is increasing, but their prognostic factors and surgical treatment are still controversial. This paper aims to investigate the prognostic factors of overall survival and cancer-specific survival in elderly patients with LGG and analyze the optimal surgical treatment strategy. METHODS: Patients in the study were obtained from the Surveillance, Epidemiology, and End Results database and patients were randomized into a training and a test set (7:3). Clinical variables were analyzed by univariate and multivariate Cox regression analysis to screen for significant prognostic factors, and nomograms visualized the prognosis. In addition, survival analysis of elderly patients regarding different surgical management was also analyzed by Kaplan-Meier curves. RESULTS: Six prognostic factors were screened by univariate and multivariate Cox regression analysis on the training set: tumor site, laterality, histological type, the extent of surgery, radiotherapy, and chemotherapy, and all factors were visualized by nomogram. And we evaluated the accuracy of the nomogram model using consistency index, calibration plots, receiver operator characteristic curves, and decision curve analysis, showing that the nomogram has strong accuracy and applicability. We also found that gross total resection improved overall survival and cancer-specific survival in patients with LGG aged ≥65 years relative to those who did not undergo surgery (P < 0.001). CONCLUSIONS: Based on the Surveillance, Epidemiology, and End Results database, we created and validated prognostic nomograms for elderly patients with LGG, which can help clinicians to provide personalized treatment services and clinical decisions for their patients. More importantly, we found that older age alone should not preclude aggressive surgery for LGGs.

A Novel Cuprotosis-Related lncRNA Signature Effectively Predicts Prognosis in Glioma Patients.

Cuprotosis is a novel and different cell death mechanism from the existing known ones that can be used to explore new approaches to treating cancer. Just like ferroptosis and pyroptosis, cuprotosis-related genes regulate various types of tumorigenesis, invasion, and metastasis. However, the relationship between cuprotosis-related long non-coding RNA (cuprotosis-related lncRNA) in glioma development and prognosis has not been investigated. We obtained relevant data from the Genotype-Tissue Expression (GTEx), Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and published articles. First, we identified 365 cuprotosis-related lncRNAs based on 10 cuprotosis-related differential genes (|R2|> 0.4, p < 0.001). Then using Lasso and Cox regression analysis methods, 12 prognostic cuprotosis-related lncRNAs were obtained and constructed the CuLncSigi risk score formula. Our next step was to divide the tumor gliomas into two groups (high risk and low risk) based on the median risk score, and we found that patients in the high-risk group had a significantly worse prognosis. We used internal and external validation methods to simultaneously analyze and validate that the risk score model has good predictive power for patients with glioma. Next, we also performed enrichment analyses such as GSEA and aaGSEA and evaluated the relationship between immune-related drugs and tumor treatment. In conclusion, we successfully constructed a formula of cuprotosis-related lncRNAs with a powerful predictive function. More importantly, our study paves the way for exploring cuprotosis mechanisms in glioma occurrence and development and helps to find new relevant biomarkers for glioma early identification and diagnosis and to investigate new therapeutic approaches.

M7G-related LncRNAs: A comprehensive analysis of the prognosis and immunity in glioma.

Today, numerous international researchers have demonstrated that N7-methylguanosine (m7G) related long non-coding RNAs (m7G-related lncRNAs) are closely linked to the happenings and developments of various human beings' cancers. However, the connection between m7G-related lncRNAs and glioma prognosis has not been investigated. We did this study to look for new potential biomarkers and construct an m7G-related lncRNA prognostic signature for glioma. We identified those lncRNAs associated with DEGs from glioma tissue sequences as m7G-related lncRNAs. First, we used Pearson's correlation analysis to identify 28 DEGs by glioma and normal brain tissue gene sequences and predicated 657 m7G-related lncRNAs. Then, eight lncRNAs associated with prognosis were obtained and used to construct the m7G risk score model by lasso and Cox regression analysis methods. Furthermore, we used Kaplan-Meier analysis, time-dependent ROC, principal component analysis, clinical variables, independent prognostic analysis, nomograms, calibration curves, and expression levels of lncRNAs to determine the model's accuracy. Importantly, we validated the model with external and internal validation methods and found it has strong predictive power. Finally, we performed functional enrichment analysis (GSEA, aaGSEA enrichment analyses) and analyzed immune checkpoints, associated pathways, and drug sensitivity based on predictors. In conclusion, we successfully constructed the formula of m7G-related lncRNAs with powerful predictive functions. Our study provides instructional value for analyzing glioma pathogenesis and offers potential research targets for glioma treatment and scientific research.

Practical protocols for timed artificial insemination of jennies using cooled or frozen donkey semen.

BACKGROUND: With the expansion of the donkey industry, timed artificial insemination (TAI) is becoming increasingly important in the reproductive management of jennies, however, TAI has not been widely investigated in donkeys. OBJECTIVES: To develop efficient TAI protocols for cooled or frozen semen in jennies, based around ovulation induction with a GnRH analogue. STUDY DESIGN: Experimental exploratory study. METHODS AND RESULTS: In experiment 1, the effects of different GnRH analogue (deslorelin) doses, follicle diameter (FD) at induction, repeated use of a GnRH analogue, and the influence of season on induction efficiency, as well as distribution of ovulations over time after induction were investigated. Induction efficiency was sufficient with 2.2 mg deslorelin (≥90% ovulation within 48 hours of treatment). Ovulation rate between 24 and 48 hours was highest when the FD at treatment was 31-35 mm, as compared to 25-30 mm or 36-40 mm. Repeated use of deslorelin or treatment during different seasons had no effect on induction efficiency. About 70% of ovulations occurred between 32 and 48 hours, and highest incidence of ovulation was at 36-38 hours after induction. In experiment 2, TAI using cooled semen (1 × 109 motile sperm in a 10 mL volume) was performed once at 8 hours after induction (n = 59). Pregnancy rate after TAI with cooled semen was 49.2% (29/59). In experiment 3, jennies were inseminated twice with 10 (n = 23), 5 (n = 31), 3 (n = 32), 2 (n = 82) and 1 (n = 66) straws (more than 50 × 106 motile spermatozoa in each 0.5 mL straw) of frozen semen at 34 and 42 hours after induction. The pregnancy rates were 30.4%, 35.5%, 34.4%, 29.3% and 28.8%, respectively (P > 0.05). MAIN LIMITATIONS: In the frozen semen trial, 22.5% (68/302) jennies were excluded after failure to ovulate during the appropriate time interval. In addition, there were no control groups for the AI trials. CONCLUSION: When FD reaches 31-35 mm, a donkey jenny can be inseminated once using cooled semen at 8 hours or twice using frozen semen at 34 and 42 hours after deslorelin treatment. The frozen semen TAI protocol resulted in acceptable pregnancy rates using 1 × 108 motile spermatozoa per cycle.

Characteristics of follicular dynamics and reproductive hormone profiles during oestrous cycles of jennies over an entire year.

Although donkeys have been domesticated for over 6,000 years, limited information is available concerning their reproductive physiology, especially under intensive rearing conditions. The aims of this experiment were to study follicular dynamics and reproductive hormone variation in jennies during the inter-ovulatory interval in different seasons. A total of 12 continuous cycles of six Dezhou Black (DB) donkey jennies were examined in four different seasons. The diameters of the six largest follicles of each jenny were measured daily by ultrasonography, and blood samples were collected at fixed times for reproductive hormone assays. The results demonstrated that most jennies displayed regular oestrous cycles in all seasons. The follicular dynamics were similar in Spring, Summer and Winter, while the jennies had longer oestrous cycles with delayed follicular deviation and dominant selection in Autumn. At least two follicular waves were observed in each oestrous cycle, throughout the study, but two jennies presented oestrous cycles with three follicular waves in the Autumn. The numbers of follicular waves were consistent with the numbers of FSH surges. Oestrous characteristics of the jennies in a large herd were also analysed. The results showed that the rates of regular oestrous cycles were 83.1% (265/319), 89.6% (215/240), 80.2% (235/293) and 77.1% (178/231), with 26.4% (70/265), 19.5% (42/215), 22.1% (52/235) and 23.0% (41/178) double ovulation rates in Spring, Summer, Autumn and Winter, respectively. The results presented may be useful for donkey farms in the design of breeding strategies.

A novel role of transient receptor potential mucolipin1 (TRPML1) in protecting against imidazole-induced cytotoxicity.

Lysosomotropic amines cause serious side effects such as cytoplasmic vacuolation and cell death. TRPML1 (also known as mucolipin1), a member of the transient receptor potential (TRP) protein family, may regulate fusion/fission of vesicles along the endocytic pathway and some aspects of lysosomal ion homeostasis. Nevertheless, it is still unknown whether TRPML1 is involved in death of mammalian cells induced by lysosomotropic agents. In this study, imidazole was used as a model to investigate the role of TRPML1 in the cytotoxicity of lysosomotropic agents. Overexpression of wild-type TRPML1 inhibited imidazole-induced vacuole formation and cell death in human endometrial adenocarcinoma (HEC-1B) cells. In contrast, siRNA-mediated TRPML1 knockdown increased the cell death induced by imidazole. Bafilomycin A1 raises the pH of acidic organelles and therefore suppresses accumulation of weak bases in them. Similarly, lysosomal pH was raised in TRPML1-overexpressing cells; therefore, we inferred that TRPML1 protected against imidazole toxicity by regulating the pH of acidic organelles. We concluded that TRPML1 had a novel role in protecting against lysosomotropic amine toxicity.