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Female and latent genital tuberculosis (FGTB and LGTB) in young women may lead to infertility by damaging ovarian reserve function, but the regulatory mechanisms remain unclear. In this study, we investigated the effects of FGTB and LGTB on ovarian reserve function and potential regulatory mechanisms by untargeted metabolomics of follicular fluid, aiming to provide insights for the clinical management and treatment approaches for afflicted women. We recruited 19 patients with FGTB, 16 patients with LGTB, and 16 healthy women as a control group. Clinical data analysis revealed that both the FGTB and LGTB groups had significantly lower ovarian reserve marker levels compared to the control group, including lower anti-Müllerian hormone levels (FGTB: 0.82 [0.6, 1.1] μg/L; LGTB: 1.57 [1.3, 1.8] μg/L vs. control: 3.29 [2.9, 3.5] μg/L), reduced antral follicular counts (FGTB: 6 [5.5, 9.5]; LGTB: 10.5 [7, 12.3] vs. control: 17 [14.5, 18]), and fewer retrieved oocytes (FGTB: 3 [2, 5]; LGTB: 8 [4, 8.3] vs. control: 14.5 [11.5, 15.3]). Conversely, these groups exhibited higher ovarian response marker levels, such as longer gonadotropin treatment days (FGTB: 12 [10.5, 12.5]; LGTB: 11 [10.8, 11.3] vs. control: 10 [8.8, 10]) and increased gonadotropin dosage requirements (FGTB: 3300 [3075, 3637.5] U; LGTB: 3037.5 [2700, 3225] U vs. control: 2531.25 [2337.5, 2943.8] U). All comparisons were statistically significant at P < 0.05. The results suggested that FGTB and LGTB have adverse effects on ovarian reserve and response. Untargeted metabolomic analysis identified 92 and 80 differential metabolites in the control vs. FGTB and control vs. LGTB groups, respectively. Pathway enrichment analysis revealed significant alterations in metabolic pathways in the FGTB and LGTB groups compared to the control group (P < 0.05), with specific changes noted in galactose metabolism, biotin metabolism, steroid hormone biosynthesis, and nicotinate and nicotinamide metabolism in the FGTB group, and caffeine metabolism, primary bile acid biosynthesis, steroid hormone biosynthesis, and glycerophospholipid metabolism in the LGTB group. The analysis of metabolic levels has revealed the potential mechanisms by which FGTB and LGTB affect ovarian reserve function, namely through alterations in metabolic pathways. The study emphasizes the importance of comprehending the metabolic alterations associated with FGTB and LGTB, which is of considerable relevance for the clinical management and therapeutic approaches in afflicted women.

Background The impact of tumor size on prognosis for surgically treated patients with pancreatic ductal adenocarcinoma (PDAC) remains controversial. A systematic review and meta-analysis was performed to evaluate this issue. Methods Relevant studies published from January 2000 to June 2017 were identified through EMBASE and PUBMED. Data were pooled for meta-analysis using Review Manager 5.3. Results Twenty eight observational studies involving a total of 23,945 patients were included. Tumors > 2 cm was associated with poor prognosis: the pooled hazard ratio (HR) estimate for overall survival was 1.52 (95% confidence interval [CI]: 1.41–1.64; P  < 0.0001) by univariate analysis and 1.61 (95% CI: 1.35–1.91; P  < 0.0001) by multivariate analysis; the pooled HR estimate for disease-free survival was 1.74 (95% CI: 1.46–2.07; P  < 0.0001) by univariate analysis and 1.38 (95% CI: 1.12–1.68; P  = 0.002) by multivariate analysis. When compared with patients with tumors ≤2 cm, those with the tumors > 2 cm had higher incidences of lymph node metastasis, poor tumor differentiation, lymph vessel invasion, vascular invasion, perineural invasion, and positive intraoperative peritoneal cytology. Conclusion These data demonstrate that PDAC size > 2 cm is an independent predictive factor for poor prognosis after surgical resection and associated with more aggressive tumor biology.

5-Fluorouracil (5-FU) is a widely used chemotherapeutic agent whose incorporation into nucleic acid plays an essential role in its therapeutic efficacy. 5-FU induces severe reproductive toxicity, which has been shown to be reversible. However, the underlying mechanisms have not been fully elucidated. Since single-strand-selective monofunctional uracil-DNA glycosylase 1 (Smug1) is a key enzyme in the excision of 5-FU, we investigated its potential role in the reversible reproductive toxicity of 5-FU by integrating knockdown, overexpression and LC‒MS/MS approaches. 5-FU treatment increased Smug1 and Dkc1 expression but blocked rRNA maturation in preimplantation embryos. Smug1 knockdown inhibited Dkc1 expression and impaired rRNA maturation, leading to reduced preimplantation embryo development. In contrast, Smug1 overexpression alleviated the inhibitory effects of 5-FU on rRNA and oocyte maturation and partially rescued 5-FU-induced developmental defects in preimplantation embryos. LC‒MS/MS analysis further revealed that overexpression of Smug1 reduced the levels of RNA incorporated 5-FUrd, the metabolite of 5-FU, indicating that Smug1 potentially alleviates reproductive toxicity by excising 5-FU from RNA. Our findings revealed the active involvement of Smug1 in counteracting 5-FU-induced reproductive toxicity and provide valuable references for the development of new strategies to reduce the adverse effects of 5-FU.

Long non-coding RNA (LncRNA) emerges as a regulator in various diseases, including endometriosis (EM). This study aims to uncover the role of long non-coding RNA BRAF-activated non-protein coding RNA (lncRNA BANCR)-mediated competing endogenous RNA mechanism in endometrial stromal cell (ESC) proliferation and invasion in EM by regulating miR-15a-5p/TRIM59. ESCs were isolated from eutopic and ectopic endometrial tissues, followed by the determination of Cytokeratin 19 and Vimentin expressions in cells. Then, expressions of lncRNA BANCR, microRNA (miR)-15a-5p, and tripartite motif-containing 59 (TRIM59) in tissues and cells were determined by real-time quantitative polymerase chain reaction or Western blot assay, and cell proliferation and invasion were evaluated by cell counting kit-8 and transwell assays. After that, the subcellular localization of lncRNA BANCR and binding of miR-15a-5p to lncRNA BANCR or TRIM59 were analyzed. LncRNA BANCR was upregulated in ectopic endometrial tissues and ectopic ESCs (Ect-ESCs). Silencing lncRNA BANCR suppressed Ect-ESC proliferation and invasion. LncRNA BANCR inhibited miR-15a-5p to promote TRIM59 expression. miR-15a-5p downregulation or TRIM59 overexpression both reversed the effects of silencing lncRNA BANCR on Ect-ESC proliferation and invasion. In summary, our findings suggested that lncRNA BANCR facilitated Ect-ESC proliferation and invasion by inhibiting miR-15a-5p and promoting TRIM59.

BackgroundThe survival benefit of additional surgery after non-curative endoscopic resection of early gastric cancer is a matter of debate. This meta-analysis is intended to draw a convincing conclusion on this issue based on data currently available.MethodsA systematic review of PubMed/Medline database was performed from 2010 to 2018 for studies comparing survival outcomes of additional surgery versus simple follow-up after non-curative endoscopic resection for early gastric cancer. Differences between groups were calculated using either the fixed effects model or random effects model.ResultsTen retrospective studies with 4225 patients met the inclusion criteria. Additional surgery significantly provided better 5 years overall survival [odds ratios (OR) 3.50, 95% confidence interval (95% CI) 2.89–4.24] and disease-specific survival (OR 3.99, 95% CI 2.50–6.36).ConclusionsAdditional surgery offers survival benefits to patients undergoing non-curative endoscopic resection of early gastric cancer.

Purpose The aim of this study was to evaluate the safety and efficacy of en bloc right hemicolectomy with pancreaticoduodenectomy (RHCPD) for locally advanced right-sided colon cancer (LARCC). Method A pooled data analysis was performed on individual patients identified from the literature and the authors’ institutions. The short- and long-term outcomes were assessed. Results Recruited in this study were 81 LARCC patients undergoing RHCPD, including 75 patients reported in the literature and 6 patients from our own institutions. R0 resection was achieved in 97.5% cases. Morbidity and the 30-day mortality rate were 53.8 and 3.7%, respectively. The median survival duration was 70.4 months, and the 1-, 3- and 5-year overall survival rates were 77.8, 64.6, and 55.2%, respectively. Multivariable analysis identified only lymph node metastasis (hazard ratio 3.474, 95% confidence interval 1.323–9.120; P  = 0.011) as independent predictors of poor survival. Conclusion En bloc RHCPD for LARCC can be performed safely with a high proportion of R0 resection and a good postoperative survival outcome.

This paper investigates a solution for enabling in-context capabilities of video diffusion transformers, with minimal tuning required for activation. Specifically, we propose a simple pipeline to leverage in-context generation: (\\(i\\)) concatenate videos along spacial or time dimension, (\\(ii\\)) jointly caption multi-scene video clips from one source, and (\\(iii\\)) apply task-specific fine-tuning using carefully curated small datasets. Through a series of diverse controllable tasks, we demonstrate qualitatively that existing advanced text-to-video models can effectively perform in-context generation. Notably, it allows for the creation of consistent multi-scene videos exceeding 30 seconds in duration, without additional computational overhead. Importantly, this method requires no modifications to the original models, results in high-fidelity video outputs that better align with prompt specifications and maintain role consistency. Our framework presents a valuable tool for the research community and offers critical insights for advancing product-level controllable video generation systems. The data, code, and model weights are publicly available at: https://github.com/feizc/Video-In-Context.

This paper presents a powerful framework to customize video creations by incorporating multiple specific identity (ID) photos, with video diffusion Transformers, referred to as Ingredients. Generally, our method consists of three primary modules: (i) a facial extractor that captures versatile and precise facial features for each human ID from both global and local perspectives; (ii) a multi-scale projector that maps face embeddings into the contextual space of image query in video diffusion transformers; (iii) an ID router that dynamically combines and allocates multiple ID embedding to the corresponding space-time regions. Leveraging a meticulously curated text-video dataset and a multi-stage training protocol, Ingredients demonstrates superior performance in turning custom photos into dynamic and personalized video content. Qualitative evaluations highlight the advantages of proposed method, positioning it as a significant advancement toward more effective generative video control tools in Transformer-based architecture, compared to existing methods. The data, code, and model weights are publicly available at: https://github.com/feizc/Ingredients.

In this paper, we present DiT-MoE, a sparse version of the diffusion Transformer, that is scalable and competitive with dense networks while exhibiting highly optimized inference. The DiT-MoE includes two simple designs: shared expert routing and expert-level balance loss, thereby capturing common knowledge and reducing redundancy among the different routed experts. When applied to conditional image generation, a deep analysis of experts specialization gains some interesting observations: (i) Expert selection shows preference with spatial position and denoising time step, while insensitive with different class-conditional information; (ii) As the MoE layers go deeper, the selection of experts gradually shifts from specific spacial position to dispersion and balance. (iii) Expert specialization tends to be more concentrated at the early time step and then gradually uniform after half. We attribute it to the diffusion process that first models the low-frequency spatial information and then high-frequency complex information. Based on the above guidance, a series of DiT-MoE experimentally achieves performance on par with dense networks yet requires much less computational load during inference. More encouragingly, we demonstrate the potential of DiT-MoE with synthesized image data, scaling diffusion model at a 16.5B parameter that attains a new SoTA FID-50K score of 1.80 in 512\\(\\)512 resolution settings. The project page: https://github.com/feizc/DiT-MoE.

Transformers have catalyzed advancements in computer vision and natural language processing (NLP) fields. However, substantial computational complexity poses limitations for their application in long-context tasks, such as high-resolution image generation. This paper introduces a series of architectures adapted from the RWKV model used in the NLP, with requisite modifications tailored for diffusion model applied to image generation tasks, referred to as Diffusion-RWKV. Similar to the diffusion with Transformers, our model is designed to efficiently handle patchnified inputs in a sequence with extra conditions, while also scaling up effectively, accommodating both large-scale parameters and extensive datasets. Its distinctive advantage manifests in its reduced spatial aggregation complexity, rendering it exceptionally adept at processing high-resolution images, thereby eliminating the necessity for windowing or group cached operations. Experimental results on both condition and unconditional image generation tasks demonstrate that Diffison-RWKV achieves performance on par with or surpasses existing CNN or Transformer-based diffusion models in FID and IS metrics while significantly reducing total computation FLOP usage.