Teratomas originate from pluripotent germ cells and differentiate into the 3 germ cell layers: endoderm, mesoderm, and ectoderm. Hence, these tumors arise most often in the gonads. Extragonadal teratomas are rare in veterinary medicine. Congenital oropharyngeal teratoma, also known as epignathus, is a neoplasm that has been reported in humans and a few veterinary species. We describe the clinical, gross, cytologic, and histopathologic features of an oropharyngeal teratoma in a neonatal Boer × Nigerian Dwarf goat that died within 4 h of birth, and briefly review extragonadal teratomas in veterinary species.

To investigate the clinical distribution patterns and clinicopathological characteristics of basal cell carcinoma (BCC) in Southwest China.

A retrospective analysis was conducted among 2016 patients diagnosed with BCC between April 2003 and May 2025. The study focused on lesion locations, facial distribution patterns, presentations of multiple BCCs, and histopathological features of BCC.

A total of 2016 patients with 2138 BCC lesions were included, comprising 881 males (43.70%) and 1135 females (56.30%). The median age at initial diagnosis was 65 years (range, 17-101 years). Only 70 (3.50%) patients were younger than 35 years, whereas 663 (32.89%) were older than 70 years. The incidence of BCC increased with age from the fifth to the eighth decade of life. Most lesions were located on the head/face (88.59%, 1894), and 80.64% (1724) occurred on the faces. The nose/perinasal area was the most common facial subregion (31.15%, 666), followed by the cheeks (20.91%), indicating a midface predilection. Clinically, nodular/ulcerative presentations predominated (65.20%, 1394). Histopathologically, the nodular cystic subtype was most common (71.94%, 1538). Multiple tumors (two to ten lesions) were observed in 36 patients, including three cases with basal cell nevus syndrome. Surgical resection was performed in 97.82% (1972) of patients, while Mohs micrographic surgery was used in 25 (1.24%) cases. The 5-year recurrence rate was 4.10%.

BCC predominantly affects older adults, with an increasing incidence in those aged 50-80 years, and shows a striking predilection for sun-exposed midfacial sites. Nodular/ulcerative lesions are the predominant clinical presentation, and nodular cystic type is the most common histological subtype. Surgery remains the mainstay of treatment; although recurrences were infrequent, their distribution supports risk-adapted management and long-term follow-up.

While cisplatin-based chemotherapy is pivotal for advanced bladder cancer, acquired resistance remains a major obstacle. This study investigates key molecular drivers of this resistance and potential reversal strategies.

We established GC (Gemcitabine and Cisplatin)-resistant T24-R and UC3-R cell lines from T24 and UM-UC-3 (UC3) cells. Transcriptomic and proteomic analyses identified differentially expressed molecules. Apoptosis and cell viability were assessed by flow cytometry and CCK-8 (Cell Counting Kit-8) assays, while RT-qPCR (Reverse Transcription Quantitative Polymerase Chain Reaction) and Western blot analyzed gene and protein expression. Immunofluorescence evaluated FAK (Focal Adhesion Kinase) phosphorylation, and a xenograft mouse model validated the findings in vivo.

Integrated transcriptomic and proteomic analysis identified FN1 (fibronectin) as a consistently upregulated top candidate in resistant cells (T24-R transcript log₂FC = 2.8, protein log₂FC = 0.9; UC3-R transcript log₂FC = 3.7; all p < 0.001). Knockdown of FN1 reduced chemoresistance (Resistance Index: 5.2 in T24-R and 2.0 in UC3-R cells, p < 0.001) and enhanced apoptosis (approximately 4.5-fold in T24-R and 7.5-fold in UC3-R, p < 0.001). ITGB4 (Integrin Subunit Beta 4) was upregulated in resistant cells (transcript log₂FC: 4.2 in T24-R and 3.03 in UC3-R; protein log₂FC: 0.67 in T24-R; all p < 0.01). Critically, ITGB4 knockdown abolished the chemoresistance promoted by exogenous FN1, which was associated with increased FAK (Y397) phosphorylation.

Our results demonstrate that the FN1-ITGB4 axis drives chemoresistance in bladder cancer via FAK signaling. Targeting this axis represents a promising strategy to overcome chemoresistance.

The current treatment options and therapeutic targets for triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer (BrCA), are limited. This study aimed to identify novel biomarkers and transcriptional regulatory networks (TRN) inherent in TNBC samples.

We analyzed pan-cancer BrCA datasets from The Cancer Genome Atlas (TCGA) to compare triple-positive breast cancer (TPBC) with TNBC. TRN algorithms and virtual inference of protein-enriched regulon (VIPER) were used to identify master regulators and their target genes. Utilizing TNBC cells (MDA-MB-231 and MDA-MB-468), we validated the relationship of nuclear factor erythroid 2-like 3 (NFE2L3) and basic helix-loop-helix family member E 40 (BHLHE40) by performing a luciferase assay. The expression levels of these targets were measured after transfections with plasmid and siRNA via qRT-PCR and western blots. The effect of these genes on cell proliferation and migration was studied using phenotypic assays.

Using computational approaches, we identified NFE2L3 as a master regulator with BHLHE40 as its target gene. NFE2L3 protein binds to the promoter region of BHLHE40 and regulates its transcriptional activity. Additionally, silencing and overexpressing NFE2L3 and BHLHE40 in TNBC cell lines MDA-MB-231 and MDA-MB-468 showed that NFE2L3 directly regulates BHLHE40 at both transcriptional and translational levels. We found that BHLHE40 requires NFE2L3 for cell proliferation and migration in TNBC.

These findings underscore the significance of NFE2L3 and BHLHE40 in TNBC, highlighting NFE2L3's role in regulating the oncogenic activity of BHLHE40 in TNBC cells.

A 79-year-old man in the United States with large B-cell lymphoma and chronic obstructive pulmonary disease had disseminated Nocardia ignorata infection involving the brain and spleen. Despite antimicrobial therapy, he died from complications. This rare manifestation highlights the need to consider Nocardia in immunocompromised patients with central nervous system and abdominal lesions.

Both pulmonary tuberculosis (PTB) and sarcoidosis (SA) are chronic, systemic, granulomatous diseases. Due to their similar clinical and radiological features, as well as similar pathological characteristics, it is difficult to distinguish. This study aims to explore the pathological correlation between PTB and SA and the impact of nodules formation on the occurrence of PTB.

We retrospective enrolled 307 patients admitted to the tuberculosis department between January 2022 and March 2024. After applying the inclusion and exclusion criteria, 170 patients were divided into three groups and analyzed: sarcoid tuberculosis group (TB-N, n=59), non-sarcoid tuberculosis group (TB-NoN, n=74), and sarcoidosis group (SA, n=37). Comparative analysis was performed on the clinical characteristics, pathogen profiles, and pulmonary microbial composition differences among the three groups.

Patients in the TB-N and SA group predominantly presented with multiple nodules. Among samples testing positive by both mNGS and conventional microbiological tests (CMT), the proportion of partially matched results was higher in the TB-N group than in the TB-NoN group, with a greater diversity of pathogenic bacteria detected in the TB-N group. ACE index analysis revealed significantly higher microbial richness in the TB-NoN group compared to both SA and TB-N groups. Regarding treatment regimens, combination therapy was more frequently administered in the TB-N group, while single drug treatment predominated in the TB-NoN group. Although the duration of anti-tuberculosis treatment was longer in the TB-N group, this difference did not reach statistical significance.

Significant differences in imaging manifestations were observed between TB-N and SA groups. The presence of nodules was associated with a more complex pathogen profile in PTB patients; however, the pulmonary microbial diversity was lower in TB-N than in TB-NoN. PTB patients with nodules predominantly received combination therapy.

Severe community-acquired pneumonia (SCAP) remains a major cause of mortality in the paediatric population, with current diagnostic and treatment approaches often proving insufficient and contributing to the growing challenge of antibiotic resistance. This study explored the potential of metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid as a tool to enhance the precision of antibiotic management in children with SCAP.

A retrospective cohort study of 202 paediatric patients with community-acquired pneumonia (aged 1 month-18 years) admitted to the First Affiliated Hospital of Xinxiang Medical University (November 2020-March 2023) was conducted. Patients were grouped by severity (intensive care unit [ICU]/non-ICU) and mNGS timing (early: ≤72 hours post-admission; late: >72 hours). The diagnostic efficacy of mNGS versus conventional microbiological techniques (CMT) was evaluated using sensitivity, specificity, positive/negative predictive values and area under the receiver operating characteristic curve (AUC) analysis. Antibiotic adjustments and clinical outcomes were analysed via survival statistics.

Metagenomic next-generation sequencing showed a higher positive detection rate (98.51%) than CMT (47.52%) (AUC = 0.82, 95%CI: 0.76-0.88). Of the 202 patients, 127 (62.87%) were male, with a median age of 1.88 years (interquartile range: 0.29-7 years). Early mNGS was associated with fewer extrapulmonary complications (69.63% vs 55.22% in the late group, p < 0.05), and shorter hospitalisation (median 13 vs 15 days, p <0.01). Antibiotic escalation occurred in 50 (24.75%) cases, de-escalation in 22 (10.89%) and same-level adjustment in 25 (12.38%).

Metagenomic next-generation sequencing outperforms CMT in pathogen detection. Early mNGS is associated with improved clinical outcomes, suggesting its potential utility in paediatric SCAP management.

Even with the development of the Pfizer-BioNTech BNT162b2 vaccine, which provides protection against COVID-19 and demonstrates high efficacy in generating immune responses, the complexities of the dynamics linking pro- and anti-inflammatory cytokine profiles with anti-spike IgG production remain unclear. The study aims to elucidate these immune dynamics after vaccination. This prospective cohort research was done at the University of Diyala from January 2022 to January 2023, evaluating the immunological response to the Pfizer-BNT162b2 mRNA vaccine in 180 healthy students. Pro- and anti-inflammatory cytokines and anti-spike IgG antibodies were measured before vaccination, 1 month after the second dose, and 4 months after the second dose. Biomarkers were analyzed via ELISA and CRP assays. The study involved 180 healthy participants (80 males, 100 females; median age, 21 years; BMI, 25.7 kg/m²). After the first Pfizer-BNT162b2 vaccine dose, the level of anti-spike IgG increased by 330-fold, and the levels of pro- and anti-inflammatory markers, such as IL-1β, IL-10, and CRP, increased significantly. Four months after the second dose, anti-spike IgG levels were 136-fold above baseline. Significant correlations emerged between cytokine and IgG levels, with anti-spike IgG/IL-10 ratios elevated and sustained over the long term. Pfizer-BNT162b2 vaccine elicits a significant immune response associated with changes in pro-inflammatory cytokines, and the interaction between these cytokines and anti-spike IgG suggests a potential role for immune regulation in enhancing humoral immunity. Based on these findings, the IgG/IL-17 ratio may serve as a viable exploratory biomarker for assessing short- and medium-term vaccination efficacy.

The aim was to examine which factors contribute to the willingness to pay (WTP) for health insurance in Germany.

Cross-sectional data are taken from a large, population-based study (GESIS panel, wave 50, n = 4,447; November 2022 to January 2023). Willingness to pay for health insurance served as outcome measure. Socioeconomic, health-related, coronavirus-related, and political spectrum-related factors were included as independent variables. Multiple linear regressions with cluster-robust standard errors were used.

Monthly average WTP for health insurance was €258 (SD: €210). A higher WTP for health insurance was associated with being male (female vs. male: β = -0.56.6, 95% CI: -67.7 to -45.5), being older (β = 2.1, 95% CI: 1.6-2.6), higher education (e.g., intermediary school leaving certificate vs. general/subject-specific university entrance qualification: β = -67.3, 95% CI: -80.7 to -53.8), higher income group (e.g., 1,700-2,300 € vs. under 900 €: β = 79.8, 95% CI: 36.1-123.5), not being married and living together with spouse (e.g., single vs. married/partner living together: β = 28.9, 95% CI: 12.4-45.4) as well as being politically more right-wing oriented (e.g., right-wing vs. left-wing: β = 33.4, 95% CI: 4.5-62.3).

In contrast to health- and coronavirus-related factors, socioeconomic and political spectrum-related factors were significantly associated with WTP for health insurance in Germany. Moreover, based on the average WTP, one can conclude that individuals do not fully agree with the present contributions to statutory health insurance in Germany as a whole during the Covid-19 pandemic. Future research could focus on cross-country comparisons (with varying healthcare systems and also between individualistic and collectivistic cultures).

Since the end of 2019, a novel coronavirus known as COVID-19 has caused a severe outbreak worldwide. Due to the complexity of epidemic data, traditional algorithms have struggled to accurately predict the development of the pandemic. The Autoregressive Integrated Moving Average (ARIMA) model is capable of capturing time-based trends in epidemic data, including seasonality, cyclic patterns, and long-term trends, which helps improve the accuracy of forecasting future epidemic trajectories. The Bidirectional Long Short-Term Memory (BiLSTM) network, a variant of the Recurrent Neural Network (RNN), is highly effective in handling sequential data. In epidemic data analysis, BiLSTM models can be applied to forecast future trends or conduct time series predictions. BiLSTM is able to capture temporal relationships and sequential patterns within data, thereby providing more accurate predictions. Genetic Algorithms (GA), inspired by biological evolution through operations such as selection, crossover, and mutation, offer an efficient approach to identifying the best-fit models and parameter configurations. By using GA, we can iteratively optimize epidemic forecasting models and enhance their performance over time. In this study, we proposed a hybrid model called GA-BiLSTM-ARIMA. Using COVID-19 case data from Japan, we calculated the GA-BiLSTM-ARIMA model's evaluation metrics: RMSE, MAE, MAPE, and R ², which were 2,262.42, 1,672.07, 6.81, and 0.9764, respectively. The results demonstrate that the hybrid model outperforms both the standalone BiLSTM and ARIMA models in predictive performance. The GA-BiLSTM-ARIMA model successfully integrates the strengths of different models through a systematic and intelligently optimized hybrid strategy. When forecasting infectious disease time series data, this model achieves higher and more robust predictive accuracy compared to traditional single models or partial hybrid models. This type of analysis supports the development of more effective prevention and control strategies and delivers accurate information and early warnings to the public and policymakers, contributing to a better global response to pandemic challenges.