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Abstract Background In recent years, with benefits from the continuous improvement of clinical technology and the advantage of fertility preservation, the application of embryo cryopreservation has been growing rapidly worldwide. However, amidst this growth, concerns about its safety persist. Numerous studies have highlighted the elevated risk of perinatal complications linked to frozen embryo transfer (FET), such as large for gestational age (LGA) and hypertensive disorders during pregnancy. Thus, it is imperative to explore the potential risk of embryo cryopreservation and its related mechanisms. Methods Given the strict ethical constraints on clinical samples, we employed mouse models in this study. Three experimental groups were established: the naturally conceived (NC) group, the fresh embryo transfer (Fresh-ET) group, and the FET group. Blastocyst formation rates and implantation rates were calculated post-embryo cryopreservation. The impact of FET on fetal growth was evaluated upon fetal and placental weight. Placental RNA-seq was conducted, encompassing comprehensive analyses of various comparisons (Fresh-ET vs. NC, FET vs. NC, and FET vs. Fresh-ET). Results Reduced rates of blastocyst formation and implantation were observed post-embryo cryopreservation. Fresh-ET resulted in a significant decrease in fetal weight compared to NC group, whereas FET reversed this decline. RNA-seq analysis indicated that the majority of the expression changes in FET were inherited from Fresh-ET, and alterations solely attributed to embryo cryopreservation were moderate. Unexpectedly, certain genes that showed alterations in Fresh-ET tended to be restored in FET. Further analysis suggested that this regression may underlie the improvement of fetal growth restriction in FET. The expression of imprinted genes was disrupted in both FET and Fresh-ET groups. Conclusion Based on our experimental data on mouse models, the impact of embryo cryopreservation is less pronounced than other in vitro manipulations in Fresh-ET. However, the impairment of the embryonic developmental potential and the gene alterations in placenta still suggested it to be a risky operation.

ObjectiveThe identification of agricultural activities plays a crucial role for greenhouse vegetables production, particularly in the precise management of cucumber cultivation. By monitoring and analyzing the timing and procedures of agricultural operations, effective guidance can be provided for agricultural production, leading to increased crop yield and quality. However, in practical applications, the recognition of agricultural activities in cucumber cultivation faces significant challenges. The complex and ever-changing growing environment of cucumbers, including dense foliage and internal facility structures that may obstruct visibility, poses difficulties in recognizing agricultural activities. Additionally, agricultural tasks involve various stages such as planting, irrigation, fertilization, and pruning, each with specific operational intricacies and skill requirements. This requires the recognition system to accurately capture the characteristics of various complex movements to ensure the accuracy and reliability of the entire recognition process. To address the complex challenges, an innovative algorithm: SlowFast-SMC-ECA (SlowFast-Spatio-Temporal Excitation, Channel Excitation, Motion Excitation-Efficient Channel Attention) was proposed for the recognition of agricultural activity behaviors in cucumber cultivation within facilities.MethodsThis algorithm represents a significant enhancement to the traditional SlowFast model, with the goal of more accurately capturing hand motion features and crucial dynamic information in agricultural activities. The fundamental concept of the SlowFast model involved processing video streams through two distinct pathways: the Slow Pathway concentrated on capturing spatial detail information, while the Fast Pathway emphasized capturing temporal changes in rapid movements. To further improve information exchange between the Slow and Fast pathways, lateral connections were incorporated at each stage. Building upon this foundation, the study introduced innovative enhancements to both pathways, improving the overall performance of the model. In the Fast Pathway, a multi-path residual network (SMC) concept was introduced, incorporating convolutional layers between different channels to strengthen temporal interconnectivity. This design enabled the algorithm to sensitively detect subtle temporal variations in rapid movements, thereby enhancing the recognition capability for swift agricultural actions. Meanwhile, in the Slow Pathway, the traditional residual block was replaced with the ECA-Res structure, integrating an effective channel attention mechanism (ECA) to improve the model's capacity to capture channel information. The adaptive adjustment of channel weights by the ECA-Res structure enriched feature expression and differentiation, enhancing the model's understanding and grasp of key spatial information in agricultural activities. Furthermore, to address the challenge of class imbalance in practical scenarios, a balanced loss function (Smoothing Loss) was developed. By introducing regularization coefficients, this loss function could automatically adjust the weights of different categories during training, effectively mitigating the impact of class imbalance and ensuring improved recognition performance across all categories.Results and DiscussionsThe experimental results significantly demonstrated the outstanding performance of the improved SlowFast-SMC-ECA model on a specially constructed agricultural activity dataset. Specifically, the model achieved an average recognition accuracy of 80.47%, representing an improvement of approximately 3.5% compared to the original SlowFast model. This achievement highlighted the effectiveness of the proposed improvements. Further ablation studies revealed that replacing traditional residual blocks with the multi-path residual network (SMC) and ECA-Res structures in the second and third stages of the SlowFast model leads to superior results. This highlighted that the improvements made to the Fast Pathway and Slow Pathway played a crucial role in enhancing the model's ability to capture details of agricultural activities. Additional ablation studies also confirmed the significant impact of these two improvements on improving the accuracy of agricultural activity recognition. Compared to existing algorithms, the improved SlowFast-SMC-ECA model exhibited a clear advantage in prediction accuracy. This not only validated the potential application of the proposed model in agricultural activity recognition but also provided strong technical support for the advancement of precision agriculture technology. In conclusion, through careful refinement and optimization of the SlowFast model, it was successfully enhanced the model's recognition capabilities in complex agricultural scenarios, contributing valuable technological advancements to precision management in greenhouse cucumber cultivation.ConclusionsBy introducing advanced recognition technologies and intelligent algorithms, this study enhances the accuracy and efficiency of monitoring agricultural activities, assists farmers and agricultural experts in managing and guiding the operational processes within planting facilities more efficiently. Moreover, the research outcomes are of immense value in improving the traceability system for agricultural product quality and safety, ensuring the reliability and transparency of agricultural product quality.

In this study, headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and gas chromatography-olfactory (GC-O) were applied to identify and analyze the volatile aroma compounds of the ethanol extract of figs. Its key characteristic flavor compounds were analyzed by odor activity (OAV) and aroma recombination and omission tests. The results showed that a total of 40 volatile aroma components were identified, of which 18 compounds, such as isobutyrate, γ-butyl lactone, aromatic camphor, nonaldehyde, vanillin and furfural, were important aroma components in the fig extract (OAV > 1). The aroma recombination experiments showed that the sensory properties of the recombined samples, which had typical aroma characteristics such as fruity, sweet, baked and burnt sweet with slight sour, ointment-like and milky, were similar to those of the fig extract. Furthermore, the aroma omission experiments identified gamma-hexanoate, ethyl palmitate, phenmethanol, aromatic camphor, vanillin, benzaldehyde, 4-hydroxy-2,5-dimethyl-3 (2H)-furan, 5-hydroxymyfuran, and methyl cyclopentanolone as key characteristic flavor compounds of the fig extract. The findings of this study provide a theoretical basis for the development and quality control of fig characteristic flavorings.

Abstract Background Significant lower genital tract (LGT) dysbiosis and an associated lower rate of clinical pregnancy after in vitro fertilization–frozen embryo transfer (IVF-FET) among polycystic ovary syndrome (PCOS) patients have been previously reported by our group. We aimed to assess whether transvaginal Lactobacillus supplementation can reverse LGT dysbiosis and further improve perinatal outcomes in PCOS patients after IVF-FET. Methods/design This is a protocol for a multicenter, open-label, randomized controlled trial in China. Women diagnosed with PCOS who are undergoing IVF-FET treatment will be recruited. Allocation to the intervention/control arms at a ratio of 1:1 will be executed by an electronic randomization system. Participants in the intervention arm will receive the live Lactobacillus capsule vaginally for 10 consecutive days before embryo transfer, while those in the control arm will receive standard individualized care. The primary outcomes will be the clinical pregnancy rate, implantation rate, and live birth rate. 16S rRNA sequencing and liquid chromatography–mass spectrometry will be conducted to evaluate the LGT microbiome and systemic metabonomics before and after the intervention. A sample of 260 participants will provide 95% power to detect a 20% increase in the rate of clinical pregnancy (α = 0.025, one-tailed test, 15% dropout rate). A total of 300 participants will be recruited. Discussion This is the first large and multicenter randomized controlled trial aimed at assessing the efficacy of transvaginal Lactobacillus supplementation on restoring the LGT microbiome and improving perinatal outcomes in PCOS patients after IVF-FET. This pragmatic trial is promising for increasing the rates of clinical pregnancy and live birth in PCOS patients after IVF-FET. Ethics and dissemination Ethical review approval was obtained from the Medical Research Ethics Committees of the International Peace Maternity and Child Health Hospital of Shanghai Jiao Tong University (15 October 2020, GKLW 2020-29). To maximize dissemination, these findings will be reported in open access publications in journals with high impact, and oral and poster conference presentations will be performed. Trial registration ChiCTR ChiCTR2000036460. Registered on 13 September 2020, https://www.chictr.org.cn/showproj.html?proj=59549 .

Background: Whether the effect of the unfixed mesh during laparoscopic total extraperitoneal (TEP) inguinal hernia repair can lead to hernia recurrence remains controversial. Methods: The PubMed, Cochrane Library, and EMBASE databases were searched to retrieve clinical randomized controlled trials (RCTs) comparing nonfixation of mesh and fixation of mesh in TEP inguinal hernia repair, and we performed a metaanalysis with RevMan 5.3 software. Results: Fifteen RCTs were included in the metaanalysis, which showed that the operation time (P = 0.001) of the unfixed mesh group was shorter than that of the fixed mesh group; additionally, the postoperative 24-h pain score (P = 0.04) and incidence of urinary retention (P = 0.001) were lower in the unfixed mesh group. There was no significant difference between the unfixed mesh group and the fixed mesh group in terms of hospital stay (P = 0.47), time to resume normal activities (P = 0.51), incidence of haematoma (P = 0.96), incidence of chronic pain (P = 0.20), and recurrence rate (P = 0.09). Conclusion: Unfixed mesh in TEP inguinal hernia repair shows no elevated recurrence rates compared to fixed mesh and is clinically safe.

Abstract Follicle-stimulating hormone (FSH) is involved in mammalian reproduction via binding to FSH receptor (FSHR). However, several studies have found that FSH and FSHR play important roles in extragonadal tissue. Here, we identified the expression of FSHR in human and mouse pancreatic islet β-cells. Blocking FSH signaling by Fshr knock-out led to impaired glucose tolerance owing to decreased insulin secretion, while high FSH levels caused insufficient insulin secretion as well. In vitro, we found that FSH orchestrated glucose-stimulated insulin secretion (GSIS) in a bell curve manner. Mechanistically, FSH primarily activates Gαs via FSHR, promoting the cAMP/protein kinase A (PKA) and calcium pathways to stimulate GSIS, whereas high FSH levels could activate Gαi to inhibit the cAMP/PKA pathway and the amplified effect on GSIS. Our results reveal the role of FSH in regulating pancreatic islet insulin secretion and provide avenues for future clinical investigation and therapeutic strategies for postmenopausal diabetes.