Prevalence, risk factors and genotyping of chlamydia trachomatis from endocervical specimens of infertile women at a tertiary care hospital, Vietnam.

BACKGROUND: To our knowledge, the prevalence, risk factors and distribution of C. trachomatis genotypes are rarely mentioned in Vietnam. This study aimed to find the prevalence, risk factors and distribution of C. trachomatis genotypes in infertile Vietnamese women. METHODS: Endocervical swabs were collected from infertile women at the National Hospital of Obstetrics and Gynecology, Vietnam, between January 2020 and December 2021. All samples were analyzed for C. trachomatis presence by Cobas 4800 CT/NG Test. Sequencing methods of ompA gene were used to determine the C. trachomatis genotypes. An approximately 1200 bp ompA fragment was aligned with reference sequences from GenBank to identify the corresponding genotype. RESULTS: The prevalence of endocervical C. trachomatis infection was 15.6% of 761 participants. Factors independently associated with CT infection among infertile women, obtained by multivariate analysis, included abnormal vaginal discharge, cervicitis, lower abdominal pain, a history of ectopic pregnancy, having more than one sex partner, and age at first intercourse. Among the samples, genotype E (25.93%) was most frequently found, followed by genotypes D/Da (22.23%), F (13.58%), G/Ga (12.35%), J (12.35%), H (6.17%), K (3.70%), B/Ba (2.47%), and I/Ia (1.23%), respectively. Genotype F was related to types of infertility, and genotype H was associated with a history of miscarriage. CONCLUSIONS: The present study indicated a high prevalence of C. trachomatis in infertile Vietnamese women. The most common genotypes found in this population were E, D, and F. Our findings suggest that routine screening is necessary for early detection and performance of infection control methods.

A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening.

RNA-sequencing has been proposed as a valuable technique to develop individualized therapy concepts for cancer patients based on their tumor-specific mutational profiles. Here, we aimed to identify drugs and inhibitors in an individualized therapy-based drug repurposing approach focusing on missense mutations for 35 biopsies of cancer patients. The missense mutations belonged to 9 categories (ABC transporter, apoptosis, angiogenesis, cell cycle, DNA damage, kinase, protease, transcription factor, tumor suppressor). The highest percentages of missense mutations were observed in transcription factor genes. The mutational profiles of all 35 tumors were subjected to hierarchical heatmap clustering. All 7 leukemia biopsies clustered together and were separated from solid tumors. Based on these individual mutation profiles, two strategies for the identification of possible drug candidates were applied: Firstly, virtual screening of FDA-approved drugs based on the protein structures carrying particular missense mutations. Secondly, we mined the Drug Gene Interaction (DGI) database (https://www.dgidb.org/) to identify approved or experimental inhibitors for missense mutated proteins in our dataset of 35 tumors. In conclusion, our approach based on virtual drug screening of FDA-approved drugs and DGI-based inhibitor selection may provide new, individual treatment options for patients with otherwise refractory tumors that do not respond anymore to standard chemotherapy.

Closed-Form Expression for the Symbol Error Probability in Full-Duplex Spatial Modulation Relay System and Its Application in Optimal Power Allocation.

Full-duplex (FD) communication and spatial modulation (SM) are two promising techniques to achieve high spectral efficiency. Recent works in the literature have investigated the possibility of combining the FD mode with SM in the relay system to benefit their advantages. In this paper, we analyze the performance of the FD-SM decode-and-forward (DF) relay system and derive the closed-form expression for the symbol error probability (SEP). To tackle the residual self-interference (RSI) due to the FD mode at the relay, we propose a simple yet effective power allocation algorithm to compensate for the RSI impact and improve the system SEP performance. Both numerical and simulation results confirm the accuracy of the derived SEP expression and the efficacy of the proposed optimal power allocation.