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Modulation of sperm function by estrogen and progesterone using in vitro experiments: A systematic review
Background The steroid hormones progesterone (P4) and Estrogen (E2) are essential for reproduction in both male and female mammals. Steroid hormones can alter sperm function in vitro via several mechanisms, thereby facilitating fertilization of female germ cells. The purpose of this systematic review is to investigate the in vitro experimental models that are used to understand the functionality of sperm after receiving supplementation with E2 and P4 in samples obtained from animal species using sperm oviductal epithelial cells (OECs) co-cultures and cultures of sperm in culture media only without OECs. Methodology A systematic literature search was conducted using Web of Science, Google Scholar, and PubMed to examine in vitro experimental models involving E2 and P4, aiming to understand sperm functionality in animals with or without OECs in culture media. A total of 32 out of 660 retrieved articles met the inclusion criteria, from which data were extracted, synthesized, and presented in a descriptive format. Results Sperm and oviducts from hamsters, mice, rats, monkeys, porcine, ovine, and bovine were used. Steroids E2 and P4 were administered at varying doses, either individually or in combination, with several studies observing dose-dependent effects on sperm function. In sperm-OECs co-cultures, P4 consistently promoted sperm hyperactivation, capacitation, and acrosome reaction (AR) via CatSper channel mechanisms, facilitating sperm release from OECs. Contrastingly, E2 delayed capacitation while enhancing sperm binding to the OECs. Similarly, supplementation of P4 in culture media alone without OECs induced sperm AR and capacitation, altered sperm motility, and improved in vitro fertilization (IVF) rates. Variations in motility and the binding ability of sperm to the isthmus and ampulla were reported in some studies. Conclusion The in vitro studies revealed that E2 and P4 alter sperm behavior dependent on dose, and improve sperm fertilizing ability in IVF programs across species. Future studies should focus on investigating and clarifying the species-specific sperm mechanisms following steroid hormone supplementation to enhance our understanding and improve the assisted reproductive technology outcomes.
CRISPR screening reveals that RNA helicase DDX41 triggers ribosome biogenesis and cancer progression through R-loop-mediated RPL/RPS transcription
Validation of a potency assay for CD34 + cell based therapy
A novel multi-modal retrieval framework for tracking vehicles using natural language descriptions
Recent advances in multimodal and contrastive learning have significantly enhanced image and video retrieval capabilities. This fusion provides numerous opportunities for multi-dimensional and multi-view retrieval, especially in multi-camera surveillance scenarios in traffic environments. This paper introduces a novel Multi-modal Vehicle Retrieval (MVR) system designed to retrieve the trajectories of tracked vehicles using natural language descriptions. The MVR system integrates an end-to-end text-video comparison learning model, utilizes CLIP for feature extraction, and uses a matching control system and multi-context-based attributes. Post-processing techniques are used to eliminate erroneous information. By comprehensively understanding vehicle characteristics, the MVR system can effectively identify trajectories based on natural language descriptions. Our method achieves a mean reciprocal ranking (MRR) score of 0.8966 on the test data set of the 7th AI City Challenge Track 2 for retrieving tracked vehicles through natural language descriptions, surpassing the previous top-ranked result on the public leaderboard.
Author Correction: Plants interfere with non-self recognition of a phytopathogenic fungus via proline accumulation to facilitate mycovirus transmission
AI microscope facilitates accurate interpretation of HER2 immunohistochemical scores 0 and 1+ in invasive breast cancer
Comparison and selection of light-emitting diodes (LEDs) for disease assays on plant pathogenic viruses and bacteria in greenhouses
Supplemental lighting in greenhouses has traditionally been dominated by high-pressure sodium (HPS) lights. However, a shift towards light-emitting diode (LED) technology is gaining momentum due to its energy efficiency, customizable light spectra, and adjustable light intensity, which together allow for more precise control over plant development. In plant pathogen diagnostics, where symptom expression is essential, HPS lights have typically been used in greenhouse settings. Since LEDs are generally optimized to promote plant growth and quality, they may affect plant physiology, including responses to pathogens. To investigate how different lighting sources affect the expression of viral and bacterial disease symptoms, two types of LEDs with different spectra were compared with the traditionally used HPS lights. LEDs with a “daylight” spectrum, featuring pronounced blue and red peaks resulted in poor virus symptom expression, though the expression of bacterial symptoms was less affected. In contrast, LEDs with a broad spectrum – characterized by a modest blue peak, a prominent red peak, and a small far-red peak – elicited virus and bacterial symptoms similar to those observed under HPS lights, when adjusted at equal light intensity level. This study provides insights into symptom development in plants inoculated with viruses and bacteria under various lighting conditions, highlighting the influence of light intensity and spectrum. Based on the results of this comparative study, “broad spectrum with far-red” LEDs were identified that are suitable for disease assays on plant pathogenic viruses and bacteria.
SLAMseq reveals potential transfer of RNA from liver to kidney in the mouse
Abstract Extracellular RNA (exRNA) mediates intercellular communication in lower animals; whether it serves a signalling function in mammals is uncertain. Reductionist experiments, in which a single RNA is over-expressed or tagged, have shown RNA transfer between tissues but may not be relevant to normal physiology. Here, we seek to determine the scale of RNA transfer between liver and kidney using metabolic RNA labelling in mice. We use 4-thiouracil to label RNA in hepatocytes and then detect labelled RNA in the kidney using SLAMseq: SH-Linked Alkylation for Metabolic RNA sequencing. We show that in the kidney, 5% of mRNA transcripts are labelled in health, increasing to 34% after acute hepatocellular injury. In the kidney, we do not detect labelled small RNA, but do find higher levels of the liver-enriched miRNA, miR-122 after liver injury. Our results show potential transfer of RNA from liver to kidney: a phenomenon that is augmented by liver injury. There were important limitations: we could not confidently identify transferred RNA transcripts at the single-gene level and we did not assess the physiological consequences of any RNA transfer.
Emergent behaviors in multiagent pursuit evasion games within a bounded 2D grid world
Two refined creep calculation methods of two-way prestressed concrete
With the advancement of engineering technology, prestressed concrete has been increasingly applied in various structures. To accurately and efficiently evaluate the long-term performance of prestressed concrete members, this paper proposes trapezoidal and difference methods for long-term deformation calculation based on the principle of creep superposition. Compared with existing creep refinement approaches and experimental data, the methods presented in this study demonstrate higher accuracy. Moreover, they significantly reduce computational complexity, offering a practical theoretical foundation for creep analysis in large-scale structures. These methods are further extended to two-way prestressed concrete members, addressing the engineering need for accurate long-term performance evaluation in such systems. The findings indicate that the creep development in two-way prestressed members is slower than that in one-way members.
An RNA modification prevents extended codon-anticodon interactions from facilitating +1 frameshifting
COVID-19 pandemic resulted in more metastatic breast cancer cases at diagnosis
Secure analysis in cognitive satellite-terrestrial networks with untrusted LEO relaying and friendly jamming
This study examines physical layer security in a cognitive satellite-terrestrial network where a ground user (GU) transmits confidential data to a Geostationary Earth Orbit (GEO) satellite via an untrusted Low Earth Orbit (LEO) relay adopting the Amplify-and-Forward (AF) relay strategy. To counter eavesdropping risks from the relaying LEO satellite, a friendly LEO jammer emits artificial noise. The secrecy rate is analyzed under cognitive radio constraints, considering interference thresholds, relay gain, and GU-LEO link shadowing. Numerical results show that increasing the interference threshold initially improves the secrecy rate but saturates when the maximum transmit power constraint at the GU is reached. When this maximum power constraint is removed, the interference threshold can be adjusted to optimize the secrecy rate. Additionally, we observe that lighter shadowing conditions generally enhance the secrecy rate, even though they improve the untrusted relay’s channel. These findings offer valuable insights into optimizing security in cognitive satellite-terrestrial networks.
Decoupling polarization and coercive field in AlScN/AlN/AlScN stack for enhanced performance in ferroelectric thin-film transistors
Differential plasma proteome analysis reveals key proteins associated with insulin resistance in acne vulgaris patients
A rolling bearing fault diagnosis method based on an improved parallel one-dimensional convolutional neural network
As a critical component of industrial equipment, the fault diagnosis of rolling bearings is essential for reducing unplanned downtime and improving equipment reliability. Existing methods achieve an accuracy of no more than 92% in low signal-to-noise ratio environments. To address this issue, this paper proposes an improved parallel one-dimensional convolutional neural network model, which integrates a parallel dual-channel convolutional kernel, a gated recurrent unit, and an attention mechanism. The classification is performed using a global max-pooling layer followed by a Softmax layer. This dual-channel configuration captures both global and local features, decreases parameter redundancy, and reduces overfitting risk. Meanwhile, the GRU addresses the vanishing gradient issue and models long-term dependencies. Additionally, the attention mechanism emphasizes crucial features dynamically, improving feature selection and generalization. The global max-pooling layer replaces the fully connected layer, reducing the number of parameters, improving computational efficiency, and lowering the risk of overfitting. Experimental results demonstrate that the proposed model achieves superior performance in fault diagnosis, attaining an accuracy of 99.62%, significantly outperforming traditional CNNs and other benchmark methods.
Philippine archipelago and South China Sea monsoon plus ocean cooling buffer Northwestern Pacific super typhoons
Carbon sequestration, emission reduction, and technical strategies of rice-crayfish farming in central China
Barriers to osteopathic manipulative medicine use: A qualitative study of physician attitudes and experiences
Purpose Despite growing recognition of osteopathic manipulative medicine (OMM) as an effective treatment for chronic pain, little is known about the real-world barriers clinicians face when attempting to integrate OMM into their clinical practice. Fewer than half of practicing Doctors of Osteopathic Medicine (DOs) incorporate OMM into patient care. Understanding the barriers that hinder OMM use is critical to bridging this gap and expanding access to this evidence-based treatment. Methods A survey was distributed to DOs from Mayo Clinic and Mayo Clinic Health System, inviting volunteers for semi-structured interviews about their attitudes and experiences with OMM. The interviews were audio-recorded, professionally transcribed, and analyzed using inductive reflexive thematic analysis. A thematic map was developed through investigator triangulation to connect key themes and subthemes. Results Among 27 survey respondents who volunteered, 16 completed in-depth interviews, representing diverse clinical roles and experiences. Analysis identified six overarching themes: system, capability, utility, training, attitudes and beliefs, and resources. These themes were supported by direct quotes and linked through subthemes that illustrated nuanced barriers and facilitators influencing OMM integration. Conclusions This study provides important qualitative insights into how DOs perceive the systemic, practical, and perceptual barriers that hinder implementation of OMM into clinical practice. Time constraints, scheduling complexity, and limited patient awareness emerged as significant barriers, compounded by broader systemic issues such as patient panel management and practice autonomy. Addressing these barriers through intentional support from institutional leadership could improve access to this valuable treatment.