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The reproduction toxicity of pubertal exposure to Microcystin-LR (MC-LR) and the underlying mechanism needs to be further investigated. In the current study, pubertal male ICR mice were intraperitoneally injected with 2 μg/kg MC-LR for four weeks. Pubertal exposure to MC-LR decreased epididymal sperm concentration and blocked spermatogonia proliferation. In-vitro studies found MC-LR inhibited cell proliferation of GC-1 cells and arrested cell cycle in G2/M phase. Mechanistically, MC-LR exposure evoked excessive reactive oxygen species (ROS) and induced DNA double-strand break in GC-1 cells. Besides, MC-LR inhibited DNA repair by reducing PolyADP-ribosylation (PARylation) activity of PARP1. Further study found MC-LR caused proteasomal degradation of SIRT6, a monoADP-ribosylation enzyme which is essential for PARP1 PARylation activity, due to destruction of SIRT6-USP10 interaction. Additionally, MG132 pretreatment alleviated MC-LR-induced SIRT6 degradation and promoted DNA repair, leading to the restoration of cell proliferation inhibition. Correspondingly, N-Acetylcysteine (NAC) pre-treatment mitigated the disturbed SIRT6-USP10 interaction and SIRT6 degradation, causing recovered DNA repair and subsequently restoration of cell proliferation inhibition in MC-LR treated GC-1 cells. Together, pubertal exposure to MC-LR induced spermatogonia cell cycle arrest and sperm count reduction by oxidative DNA damage and simultaneous SIRT6-mediated DNA repair failing. This study reports the effect of pubertal exposure to MC-LR on spermatogenesis and complex mechanism how MC-LR induces spermatogonia cell proliferation inhibition.

Our previous study showed 1-Nitropyrene (1-NP) exposure disrupted testicular testosterone synthesis in mouse, but the exact mechanism needs further investigation. The present research found 4-phenylbutyric acid (4-PBA), an endoplasmic reticulum (ER) stress inhibitor, recovered 1-NP-induced ER stress and testosterone synthases reduction in TM3 cells. GSK2606414, a protein kinase-like ER kinase (PERK) kinase inhibitor, attenuated 1-NP-induced PERK-eukaryotic translation initiation factor 2α (eIF2α) signaling activation and downregulation of steroidogenic proteins in TM3 cells. Both 4-PBA and GSK2606414 attenuated 1-NP-induced steroidogenesis disruption in TM3 cells. Further studies used N-Acetyl-L-cysteine (NAC) as a classical antioxidant to explore whether oxidative stress-activated ER stress mediated 1-NP-induced testosterone synthases reduction and steroidogenesis disruption in TM3 cells and mouse testes. The results showed NAC pretreatment mitigated oxidative stress, and subsequently attenuated ER stress, particularly PERK-eIF2α signaling activation, and downregulation of testosterone synthases in 1-NP-treated TM3 cells. More importantly, NAC extenuated 1-NP-induced testosterone synthesis in vitro and in vivo. The current work indicated that oxidative stress-caused ER stress, particularly PERK-eIF2α pathway activation, mediates 1-NP-downregulated steroidogenic proteins and steroidogenesis disruption in TM3 cells and mouse testes. Significantly, the current study provides a theoretical basis and demonstrates the experimental evidence for the potential application of antioxidant, such as NAC, in public health prevention, particularly in 1-NP-induced endocrine disorder.

Plant height is an important agronomic trait, which is governed by multiple genes with major or minor effects. Of numerous QTLs for plant height reported in soybean, most are in large genomic regions, which results in a still unknown molecular mechanism for plant height. Increasing the density of molecular markers in genetic maps will significantly improve the efficiency and accuracy of QTL mapping. This study constructed a high-density genetic map using 4 011 recombination bin markers developed from whole genome re-sequencing of 241 recombinant inbred lines (RILs) and their bi-parents, Zhonghuang 13 (ZH) and Zhongpin 03-5373 (ZP). The total genetic distance of this bin map was 3 139.15 cM, with an average interval of 0.78 cM between adjacent bin markers. Comparative genomic analysis indicated that this genetic map showed a high collinearity with the soybean reference genome. Based on this bin map, nine QTLs for plant height were detected across six environments, including three novel loci (qPH-b_11, qPH-b_17 and qPH-b_18). Of them, two environmentally stable QTLs qPH-b_13 and qPH-b_19-1 played a major role in plant height, which explained 10.56–32.7% of the phenotypic variance. They were fine-mapped to 440.12 and 237.06 kb region, covering 54 and 28 annotated genes, respectively. Via the function of homologous genes in Arabidopsis and expression analysis, two genes of them were preferentially predicted as candidate genes for further study.

Freshwater fungi, growing on submerged wood, can promote the degradation of organisms and the reuse of rotten wood energy and play key roles in freshwater ecosystems. Here, a new hyphomycetous fungus, Sporidesmiella lignicola, was isolated and identified from submerged wood samples collected in a small stream in Jiangxi Province, south-eastern China.The new taxon was studied, based on morphological characters and phylogenetic analyses combined with LSU, ITS, TEF1α and RPB2 sequences data. Sporidesmiella lignicola was morphologically characterised by its pink colonies on PDA medium in prophase, macronematous, mononematous, solitary, brown, septate, unbranched, straight or slightly flexuous conidiophores with holoblastic, polyblastic, integrated, terminal, pale brown conidiogenous cells and cylindrical, narrowly clavate, broadly obovoid to cuneiform, 3–4-distoseptate, olivaceous brown or brown conidia with rounded apex. A phylogenetic tree was constructed, based on the combination of LSU, ITS, TEF1α and RPB2 sequences data.

Furcation defects pose a significant challenge in the diagnosis and treatment planning of periodontal diseases. The accurate detection of furcation involvements (FI) on periapical radiographs (PAs) is crucial for the success of periodontal therapy. This research proposes a deep learning-based approach to furcation defect detection using convolutional neural networks (CNN) with an accuracy rate of 95%. This research has undergone a rigorous review by the Institutional Review Board (IRB) and has received accreditation under number 202002030B0C505. A dataset of 300 periapical radiographs of teeth with and without FI were collected and preprocessed to enhance the quality of the images. The efficient and innovative image masking technique used in this research better enhances the contrast between FI symptoms and other areas. Moreover, this technology highlights the region of interest (ROI) for the subsequent CNN models training with a combination of transfer learning and fine-tuning techniques. The proposed segmentation algorithm demonstrates exceptional performance with an overall accuracy up to 94.97%, surpassing other conventional methods. Moreover, in comparison with existing CNN technology for identifying dental problems, this research proposes an improved adaptive threshold preprocessing technique that produces clearer distinctions between teeth and interdental molars. The proposed model achieves impressive results in detecting FI with identification rates ranging from 92.96% to a remarkable 94.97%. These findings suggest that our deep learning approach holds significant potential for improving the accuracy and efficiency of dental diagnosis. Such AI-assisted dental diagnosis has the potential to improve periodontal diagnosis, treatment planning, and patient outcomes. This research demonstrates the feasibility and effectiveness of using deep learning algorithms for furcation defect detection on periapical radiographs and highlights the potential for AI-assisted dental diagnosis. With the improvement of dental abnormality detection, earlier intervention could be enabled and could ultimately lead to improved patient outcomes.

Freshwater fungi are highly diverse and ecologically important in freshwater systems. In China, more than 1000 species of freshwater fungi are known. Here, we present a brown-spored hyphomycetes that was collected on a submerged decaying bamboo culm in a forest stream in China.Phylogenetic analyses of combined LSU, ITS and TUB2 sequences confirm the placement of our new strain in Veronaea (Herpotrichiellaceae), sister to V. japonica. Veronaea aquatica sp. nov. differs from related taxa V. compacta and V. japonica in having longer conidiophores and cylindrical to pyriform or subclavate conidia with 0–2 septa. Veronaea aquatica also has darker brown hyphae compared to V. japonica. A morphological description and detailed illustrations of V. aquatica are provided.

BackgroundThe risk and prognosis of pancreatic cancer with lung metastasis (PCLM) are not well-defined. Thus, this study aimed to identify the risk and prognostic factors for these patients, and establish predictive nomogram models.MethodsPatients diagnosed with PCLM between 2010 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Independent risk factors and prognostic factors were identified using logistic regression and Cox regression analyses. Nomograms were constructed to predict the risk and survival of PCLM, and the area under the curve (AUC), C-index, and calibration curve were used to determine the predictive accuracy and discriminability of the established nomogram, while the decision curve analysis was used to confirm the clinical effectiveness.ResultsA total of 11287 cases with complete information were included; 601 (5.3%) patients with PC had lung metastases. Multivariable logistic analysis demonstrated that primary site, histological subtype, and brain, bone, and liver metastases were independent risk factors for lung metastases. We constructed a risk prediction nomogram model for the development of lung metastases among PC patients. The c-index of the established diagnostic nomogram was 0.786 (95%CI 0.726-0.846). Multivariable Cox regression analysis demonstrated that primary site, liver metastases, surgery, and chemotherapy were independent prognostic factors for both overall survival (OS) and cancer-specific survival (CSS), while bone metastases were independent prognostic factors for CSS. The C-indices for the OS and CSS prediction nomograms were 0.76 (95% CI 0.74-0.78) and 0.76 (95% CI 0.74-0.78), respectively. Based on the AUC of the receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis (DCA), we concluded that the risk and prognosis model of PCBM exhibits excellent performance.ConclusionsThe present study identified the risk and prognostic factors of PCLM and further established nomograms, which can help clinicians effectively identify high-risk patients and predict their clinical outcomes.

As the popularity of dental implants continues to grow at a rate of about 14% per year, so do the risks associated with the procedure. Complications such as sinusitis and nerve damage are not uncommon, and inadequate cleaning can lead to peri-implantitis around the implant, jeopardizing its stability and potentially necessitating retreatment. To address this issue, this research proposes a new system for evaluating the degree of periodontal damage around implants using Periapical film (PA). The system utilizes two Convolutional Neural Networks (CNN) models to accurately detect the location of the implant and assess the extent of damage caused by peri-implantitis. One of the CNN models is designed to determine the location of the implant in the PA with an accuracy of up to 89.31%, while the other model is responsible for assessing the degree of Peri-implantitis damage around the implant, achieving an accuracy of 90.45%. The system combines image cropping based on position information obtained from the first CNN with image enhancement techniques such as Histogram Equalization and Adaptive Histogram Equalization (AHE) to improve the visibility of the implant and gums. The result is a more accurate assessment of whether peri-implantitis has eroded to the first thread, a critical indicator of implant stability. To ensure the ethical and regulatory standards of our research, this proposal has been certified by the Institutional Review Board (IRB) under number 202102023B0C503. With no existing technology to evaluate Peri-implantitis damage around dental implants, this CNN-based system has the potential to revolutionize implant dentistry and improve patient outcomes.

The epithelial ingrowth under corneal flap is one of the complications after keratorefractive surgery, of which the incidence has declined dramatically with the improvement of relevant facilities and surgical techniques. However, epithelial ingrowth results from traumatic flap displacement has been describing in the literatures from time to time. If the prompt and efficient treatment cannot be taken, the severe complications of epithelial ingrowth will occur such as the alternation of refraction and cornea keratolysis. In this article, we reviewed the research progress of epithelial ingrowth after keratorefractive surgery.

Styrax zhejiangensis has been treated as a synonym of S. macrocarpus. Examination of herbarium specimens and observation of wild living plants demonstrates that S. zhejiangensis is a distinct species and is clearly distinguishable from S. macrocarpus through its flowering phenology in which leaves and flowers open simultaneously, its smaller corolla lobes and filaments, and its white-stellate-pubescent seeds. On this basis, we reinstate S. zhejiangensis as an accepted species. Photographic images and a distribution map of the two species are provided. A lectotype of S. zhejiangensis is also designated.

Background: Alkylating agents are critical therapeutic options for melanoma, while dacarbazine (DTIC)-based chemotherapy showed poor sensitivity in clinical trials. Long non-coding RNAs (lncRNAs) were highlighted in the progression of malignant tumors in recent years, whereas little was known about their involvement in melanoma.Methods: The functional role and molecular mechanism of lncRNA POU3F3 were evaluated on DTIC-resistant melanoma cells. Further studies analyzed its clinical role in the disease progression of melanoma.Results: We observed elevated the expression of lncRNA POU3F3 in the DTIC-resistant melanoma cells. Gain-of-function assays showed that the overexpression of lncRNA POU3F3 maintained cell survival with DTIC treatment, while the knockdown of lncRNA POU3F3 restored cell sensitivity to DTIC. A positive correlation of the expression O6-methylguanine-DNA-methyltransferase (MGMT) was observed with lncRNA POU3F3 in vitro and in vivo. Bioinformatic analyses predicted that miR-650 was involved in the lncRNA POU3F3-regulated MGMT expression. Molecular analysis indicated that lncRNA POU3F3 worked as a competitive endogenous RNA to regulate the levels of miR-650, and the lncRNA POU3F3/miR-650 axis determined the transcription of MGMT in melanoma cells to a greater extent. Further clinical studies supported that lncRNA POU3F3 was a risk factor for the disease progression of melanoma.Conclusion: LncRNA POU3F3 upregulated the expression of MGMT by sponging miR-650, which is a crucial way for DTIC resistance in melanoma. Our results indicated that lncRNA POU3F3 was a valuable biomarker for the disease progression of melanoma.

As one of the most common diseases, dry eye in adults has been extensively investigated in the past decades. However, research on dry eye in children are very limited, leading to missed diagnosis or poor treatment in clinical work. Understanding the etiology and related factors of dry eye in children is of great significance for improving clinicians' attention in the diagnosis and the treatment. Herein, the current progress of dry eye in children are reviewed.

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion.

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early, the treatment will be relatively easy, which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However, the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu’s threshold image enhancement technology, this research solves the problem that the original cutting technology cannot extract certain single teeth, and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN), which can identify caries and restorations from the bitewing images. Moreover, it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image, which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization, (2) a dental image cropping procedure to obtain individually separated tooth samples, and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks, namely, AlexNet, GoogleNet, Vgg19, and ResNet50, experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%, respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film.

The effect of Sr and cooling rate on the microstructure of Al-2.5%Mn alloy was studied by OM, SEM and XRD. The results showed that Sr not only refined the primary phase, but also refined eutectic microstructures. However, there was obvious delamination in the alloy. When the content of Sr was 0.2%–0.65%, the primary phase in the upper part of alloy changed from coarse needle and lath-shaped to fine block and needle-like. With the Sr content increased, the needle-like structure in the alloy tended to be more and longer, but the size of α -Al tended to be finer. At the bottom, there were many large massive phases, which were much more refined than the primary phase without Sr With the cooling rate increased, the primary phase was refined greatly and almost all of them transformed into eutectic microstructure. Besides, the delamination of microstructure disappeared.