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Abstract Sexual dysfunction is common in males with chronic kidney disease (CKD), but yet the prevalence and specific relationship between CKD and sexual dysfunction, especially premature ejaculation (PE), remain to be investigated in China; This study aims to examine the prevalence and association between CKD and sexual dysfunction in male patients in China; In this cross-sectional, non-interventional, observational study conducted at a single center. 72 male patients with CKD were enrolled. Data collection included socio-demographic information, assessments via the 5-item version of the International Index of Erectile Function (IIEF-5), the Chinese version of the Premature Ejaculation Diagnostic Tool, the Patient Health Quentionnnaire-9 and the General Anxiety Disorder-7. Data analysis was performed using R version 3.5.2 and SPSS software version 25.0; Among the 72 CKD patients, 56.9% experienced erectile dysfunction and 29.2% had PE. Various factors including estimated Glomerular Filtration Rate, Albumin-to-Creatinine Ratio, psychological aspects, medication use were found to be associated with sexual dysfunction in these CKD patients; Sexual dysfunction is prevalent in males with CKD and is, influenced by multiple factors. It is important for clinicians to focus on sexual dysfunction in this patient group and further investigate its underlying mechanisms.

Accurate identification of small tea buds is a key technology for tea harvesting robots, which directly affects tea quality and yield. However, due to the complexity of the tea plantation environment and the diversity of tea buds, accurate identification remains an enormous challenge. Current methods based on traditional image processing and machine learning fail to effectively extract subtle features and morphology of small tea buds, resulting in low accuracy and robustness. To achieve accurate identification, this paper proposes a small object detection algorithm called STF-YOLO (Small Target Detection with Swin Transformer and Focused YOLO), which integrates the Swin Transformer module and the YOLOv8 network to improve the detection ability of small objects. The Swin Transformer module extracts visual features based on a self-attention mechanism, which captures global and local context information of small objects to enhance feature representation. The YOLOv8 network is an object detector based on deep convolutional neural networks, offering high speed and precision. Based on the YOLOv8 network, modules including Focus and Depthwise Convolution are introduced to reduce computation and parameters, increase receptive field and feature channels, and improve feature fusion and transmission. Additionally, the Wise Intersection over Union loss is utilized to optimize the network. Experiments conducted on a self-created dataset of tea buds demonstrate that the STF-YOLO model achieves outstanding results, with an accuracy of 91.5% and a mean Average Precision of 89.4%. These results are significantly better than other detectors. Results show that, compared to mainstream algorithms (YOLOv8, YOLOv7, YOLOv5, and YOLOx), the model improves accuracy and F1 score by 5-20.22 percentage points and 0.03-0.13, respectively, proving its effectiveness in enhancing small object detection performance. This research provides technical means for the accurate identification of small tea buds in complex environments and offers insights into small object detection. Future research can further optimize model structures and parameters for more scenarios and tasks, as well as explore data augmentation and model fusion methods to improve generalization ability and robustness.

The recent emergence of human coronaviruses (CoVs) causing severe acute respiratory syndrome (SARS) is posing a great threat to global public health. Therefore, the rapid and accurate identification of pathogenic viruses plays a vital role in selecting appropriate treatments, saving people's lives and preventing epidemics. Nucleic acids, including deoxyribonucleic acid (DNA) and ribonucleic acid (RNA), are natural biopolymers composed of nucleotides that store, transmit, and express genetic information. Applications of nucleic acid detection range from genotyping and genetic prognostics, to expression profiling and detection of infectious disease. The nucleic acid detection for infectious diseases is widely used, as evidenced by the widespread use of COVID-19 tests for the containment of the pandemic. Nanotechnology influences all medical disciplines and has been considered as an essential tool for novel diagnostics, nanotherapeutics, vaccines, medical imaging, and the utilization of biomaterials for regenerative medicine. In this review, the recent advances in the development of nanotechnology-based diagnostic methods for coronavirus, and their applications in nucleic acid detection are discussed in detail. The techniques for the amplification of nucleic acids are summarized, as well as the use of magnetic nanoparticles for nucleic acid extraction. Besides, current challenges and future prospects are proposed, along with the great potential of nanotechnology for the effective diagnosis of coronavirus.

The accuracy of fish farming and real-time monitoring are essential to the development of “intelligent” fish farming. Although the existing instance segmentation networks (such as Maskrcnn) can detect and segment the fish, most of them are not effective in real-time monitoring. In order to improve the accuracy of fish image segmentation and promote the accurate and intelligent development of fish farming industry, this article uses YOLOv5 as the backbone network and object detection branch, combined with semantic segmentation head for real-time fish detection and segmentation. The experiments show that the object detection precision can reach 95.4% and the semantic segmentation accuracy can reach 98.5% with the algorithm structure proposed in this article, based on the golden crucian carp dataset, and 116.6 FPS can be achieved on RTX3060. On the publicly available dataset PASCAL VOC 2007, the object detection precision is 73.8%, the semantic segmentation accuracy is 84.3%, and the speed is up to 120 FPS on RTX3060.

Background: Hydrophilic dental implants are gaining increasing interest for their ability to accelerate bone formation. However, commercially available hydrophilic implants, such as SLActive™, have some major limitations due to their time-dependent biological aging and lower cost-effectiveness. The non-thermal atmospheric plasma (NTAP) treatment is a reliable way to gain a hydrophilic surface and enhance osseointegration. However, a few studies have been carried out to compare the osseointegration of NTAP-functionalized titanium implants and commercially available hydrophilic implants.Purpose: In this study, we compare the osseointegration abilities of the NTAP-functionalized titanium implant and Straumann SLActive.Material and methods: The NTAP effectiveness was examined using in vitro cell experiments. Then, six beagle dogs were included in the in vivo experiment. Straumann SLActive implants, SLA implants, and SLA implants treated with NTAP were implanted in the mandibular premolar area of dogs. After 2 w, 4 w, and 8 w, the animals were sacrificed and specimens were collected. Radiographic and histological analyses were used to measure osseointegration.Results: NTAP treatment accelerated the initial attachment and differentiation of MC3T3-E1 cells. In the in vivo experiment, bone parameters (e.g., BIC value and BV/TV) and volume of new bone of NTAP groups were close to those of the SLActive group. Additionally, although there was no statistical difference, the osseointegration of SLActive and NTAP groups was evidently superior to that of the SLA group.Conclusion: NTAP-functionalized implants enhanced cell interaction with material and subsequent bone formation. The osseointegration of the NTAP-functionalized implant was comparable to that of the SLActive implant at the early osseointegration stage.

Non-thermal atmospheric plasma (NTAP) modification to induce a hydrophilic titanium (Ti) surface with less carbon contamination, has been demonstrated to boost the osteogenic responses. In this study, we investigated the underlying bone formation mechanism of NTAP-Ti, and the involvement of PI3K/Akt signaling pathway in regulating osteogenic activities on NTAP-Ti surfaces. NTAP was employed for Ti activation, and PI3K inhibitor, LY294002, was applied to the suppression of PI3K/Akt pathway. We systematically and quantitatively detected the cell morphology, attachment, proliferation, osteogenic differentiation and mineralization of MC3T3-E1 mouse preosteoblasts, and molecular expressions involved in osteogenesis and PI3K/Akt signaling pathway in vivo and in vitro. A descent in osteoblast proliferation on Ti surfaces in relation to LY294002. Alkaline phosphatase (ALP) activity, as well as matrix mineralization, was mitigated by PI3K inhibitor in NTAP-Ti. Likewise, the expression levels of osteogenesis-related genes [ALP, osteocalcin (Ocn), osteopontin (Opn) and runt-related transcription factor 2 (Runx2)] on NTAP-Ti were notably attenuated by LY294002, as confirmed by the results of osteogenesis-related proteins (ALP, and Runx2) expression analysis. In addition, the expression of PI3K/Akt signal pathway proteins further verified the inhibition of LY294002 on Ti surfaces modified by NTAP. Collectively, the PI3K/Akt signal pathway was involved in the amelioration of osteogenesis induced by NTAP modification. NTAP treatment for Ti activation is promising in augmented osteogenic potential through the activation of PI3K/Akt signal pathway.

Dental implantation is currently the optimal solution for tooth loss. However, the health and stability of dental implants have emerged as global public health concerns. Dental implant placement, healing of the surgical site, osseointegration, stability of bone tissues, and prevention of peri-implant diseases are challenges faced in achieving the long-term health and stability of implants. These have been ongoing concerns in the field of oral implantation. Probiotics, as beneficial microorganisms, play a significant role in the body by inhibiting pathogens, promoting bone tissue homeostasis, and facilitating tissue regeneration, modulating immune-inflammatory levels. This review explores the potential of probiotics in addressing post-implantation challenges. We summarize the existing research regarding the importance of probiotics in managing dental implant health and advocate for further research into their potential applications.

To reduce the error of a Hall current sensor caused by the variation of the conductor position, a new symmetrical dual-core four-air-gap magnetic circuit structure is designed. The proposed structure includes two symmetrically placed dual-air-gap magnetic cores and four Hall devices, where the two symmetrically placed dual-air-gap magnetic cores are used as the sensor magnetic circuit and the average voltage output from the four Hall devices is used as the output of the sensor. First, the output error of a traditional Hall current sensor caused by the variation of the conductor position is discussed, and the principle of reducing the error by using a symmetrical dual-core four-air-gap magnetic circuit structure is analyzed. Then, a finite element simulation was performed to mimic the magnetic induction intensity at the air gap of a single-core single-air-gap magnetic core and that of the proposed circuit structure. Then, the relative error of these two circuits was calculated. Finally, a prototype of the proposed circuit structure was manufactured. The simulation and experimental results show that the proposed circuit structure can significantly reduce the measurement error caused by the position deviation of the measured conductor, and the maximum measurement error is only 0.566% when the measured current ranges from 10 to 50 A. [ABSTRACT FROM AUTHOR]