Genome-wide identification of GH28 family and insight into its contributions to pod shattering resistance in Brassica napus L.

Rapeseed (Brassica napus L.), accounts for nearly 16% of vegetable oil, is the world's second produced oilseed. However, pod shattering has caused significant yield loses in rapeseed production, particularly during mechanical harvesting. The GH28 genes can promote pod shattering by changing the structure of the pod cell wall in Arabidopsis. However, the role of the GH28 gene family in rapeseed was largely unknown. Therefore, a genome-wide comprehensive analysis was conducted to classify the role of GH28 gene family on rapeseed pod shattering. A total of 37 BnaGH28 genes in the rapeseed genome were identified. These BnaGH28s can be divided into five groups (Group A-E), based on phylogenetic and synteny analysis. Protein property, gene structure, conserved motif, cis-acting element, and gene expression profile of BnaGH28 genes in the same group were similar. Specially, the expression level of genes in group A-D was gradually decreased, but increased in group E with the development of silique. Among eleven higher expressed genes in group E, two BnaGH28 genes (BnaA07T0199500ZS and BnaC06T0206500ZS) were significantly regulated by IAA or GA treatment. And the significant effects of BnaA07T0199500ZS variation on pod shattering resistance were also demonstrated in present study. These results could open a new window for insight into the role of BnaGH28 genes on pod shattering resistance in rapeseed.

Genome-wide characterization of SDR gene family and its potential role in seed dormancy of Brassica napus L.

Rapeseed (Brassica napus L.) with short or no dormancy period are easy to germinate before harvest (pre-harvest sprouting, PHS). PHS has seriously decreased seed weight and oil content in B. napus. Short-chain dehydrogenase/ reductase (SDR) genes have been found to related to seed dormancy by promoting ABA biosynthesis in rice and Arabidopsis. In order to clarify whether SDR genes are the key factor of seed dormancy in B. napus, homology sequence blast, protein physicochemical properties, conserved motif, gene structure, cis-acting element, gene expression and variation analysis were conducted in present study. Results shown that 142 BnaSDR genes, unevenly distributed on 19 chromosomes, have been identified in B. napus genome. Among them, four BnaSDR gene clusters present in chromosome A04、A05、C03、C04 were also identified. These 142 BnaSDR genes were divided into four subfamilies on phylogenetic tree. Members of the same subgroup have similar protein characters, conserved motifs, gene structure, cis-acting elements and tissue expression profiles. Specially, the expression levels of genes in subgroup A, B and C were gradually decreased, but increased in subgroup D with the development of seeds. Among seven higher expressed genes in group D, six BnaSDR genes were significantly higher expressed in weak dormancy line than that in nondormancy line. And the significant effects of BnaC01T0313900ZS and BnaC03T0300500ZS variation on seed dormancy were also demonstrated in present study. These findings provide a key information for investigating the function of BnaSDRs on seed dormancy in B. napus.

Artificial intelligence in wound care: diagnosis, assessment and treatment of hard-to-heal wounds: a narrative review.

OBJECTIVE: The effective assessment of wounds, both acute and hard-to-heal, is an important component in the delivery by wound care practitioners of efficacious wound care for patients. Improved wound diagnosis, optimising wound treatment regimens, and enhanced prevention of wounds aid in providing patients with a better quality of life (QoL). There is significant potential for the use of artificial intelligence (AI) in health-related areas such as wound care. However, AI-based systems remain to be developed to a point where they can be used clinically to deliver high-quality wound care. We have carried out a narrative review of the development and use of AI in the diagnosis, assessment and treatment of hard-to-heal wounds. We retrieved 145 articles from several online databases and other online resources, and 81 of them were included in this narrative review. Our review shows that AI application in wound care offers benefits in the assessment/diagnosis, monitoring and treatment of acute and hard-to-heal wounds. As well as offering patients the potential of improved QoL, AI may also enable better use of healthcare resources.

The correlation between blood lipids and intrahepatic cholestasis syndrome during pregnancy.

BACKGROUND: To analyse changes in lipid levels during the development of intrahepatic cholestasis of pregnancy (ICP) and identify new biomarkers for predicting ICP. METHODS: A retrospective case-control study was conducted to analyse 473 pregnant women who underwent regular prenatal examinations and delivered at the Women and Children's Hospital, School of Medicine, Xiamen University, between June 2020 and June 2023, including 269 normal pregnancy controls and 204 pregnant women with cholestasis. RESULTS: Patients with ICP with gestational diabetes mellitus (GDM) have lower high-density lipoprotein (HDL) levels than in those without GDM. Total bile acid (TBA) levels were significantly higher in pregnant women with GDM than those without. The apolipoprotein A (APOA) level was lower in patients with ICP and hypothyroidism than those without hypothyroidism. TBA levels were significantly higher in pregnant women with hypothyroidism than those without. Triglyceride (TG) levels were significantly higher in patients with preeclampsia (PE) than those without. HDL and APOA levels were lower in women with ICP complicated by preterm delivery than those with normal delivery. The AUC (area under the curve) of the differential diagnosis of cholestasis of pregnancy for the APOA/APOB (apolipoprotein B) ratio was 0.727, with a sensitivity of 85.9% and specificity of 47.5%. CONCLUSIONS: The results suggested that dyslipidaemia is associated with an increased risk of ICP and its complications. The timely detection of blood lipid and bile acid levels can assist in the diagnosis of ICP and effectively prevent ICP and other complications.

Intrahepatic cholestasis of pregnancy (ICP) is recognized as one of the most severe complications during pregnancy. Currently, elevated fasting serum total bile acid (TBA) levels are commonly used as diagnostic markers for ICP. However, it has been observed that women diagnosed with ICP often do not exhibit elevated TBA levels. Additionally, other medical conditions can also lead to increased TBA levels. Our study has revealed a potential correlation between abnormal lipid metabolism and the occurrence and progression of ICP and its associated complications. Specifically, we found that patients with ICP who have higher serum bile acid levels tend to have more disrupted lipid metabolism, as well as a higher risk of complications and adverse pregnancy outcomes. This manuscript is the first to investigate the link between dyslipidemia and ICP, as well as other pregnancy complications. As a result, our findings offer a foundation for the clinical diagnosis and treatment of ICP and its comorbidities during pregnancy, while also highlighting the need for further research in this area.

Scalable Swin Transformer network for brain tumor segmentation from incomplete MRI modalities.

BACKGROUND: Deep learning methods have shown great potential in processing multi-modal Magnetic Resonance Imaging (MRI) data, enabling improved accuracy in brain tumor segmentation. However, the performance of these methods can suffer when dealing with incomplete modalities, which is a common issue in clinical practice. Existing solutions, such as missing modality synthesis, knowledge distillation, and architecture-based methods, suffer from drawbacks such as long training times, high model complexity, and poor scalability. METHOD: This paper proposes IMS2Trans, a novel lightweight scalable Swin Transformer network by utilizing a single encoder to extract latent feature maps from all available modalities. This unified feature extraction process enables efficient information sharing and fusion among the modalities, resulting in efficiency without compromising segmentation performance even in the presence of missing modalities. RESULTS: Two datasets, BraTS 2018 and BraTS 2020, containing incomplete modalities for brain tumor segmentation are evaluated against popular benchmarks. On the BraTS 2018 dataset, our model achieved higher average Dice similarity coefficient (DSC) scores for the whole tumor, tumor core, and enhancing tumor regions (86.57, 75.67, and 58.28, respectively), in comparison with a state-of-the-art model, i.e. mmFormer (86.45, 75.51, and 57.79, respectively). Similarly, on the BraTS 2020 dataset, our model scored higher DSC scores in these three brain tumor regions (87.33, 79.09, and 62.11, respectively) compared to mmFormer (86.17, 78.34, and 60.36, respectively). We also conducted a Wilcoxon test on the experimental results, and the generated p-value confirmed that our model's performance was statistically significant. Moreover, our model exhibits significantly reduced complexity with only 4.47 M parameters, 121.89G FLOPs, and a model size of 77.13 MB, whereas mmFormer comprises 34.96 M parameters, 265.79 G FLOPs, and a model size of 559.74 MB. These indicate our model, being light-weighted with significantly reduced parameters, is still able to achieve better performance than a state-of-the-art model. CONCLUSION: By leveraging a single encoder for processing the available modalities, IMS2Trans offers notable scalability advantages over methods that rely on multiple encoders. This streamlined approach eliminates the need for maintaining separate encoders for each modality, resulting in a lightweight and scalable network architecture. The source code of IMS2Trans and the associated weights are both publicly available at https://github.com/hudscomdz/IMS2Trans.

CircORC2 promoted proliferation and inhibited the sensitivity of osteosarcoma cell lines to cisplatin by regulating the miR-485-3p/TRIM2 axis.

Resistance to chemotherapy leads to poor prognosis for osteosarcoma (OS) patients. However, due to the high metastasis of tumor and the decrease in sensitivity of tumor cells to cisplatin (DDP), the 5-year survival rate of OS patients is still unsatisfactory. This study explored a mechanism for improving the sensitivity of OS cells to DDP. A DDP-resistant OS cell model was established, and we have found that circORC2 and TRIM2 were upregulated in DDP-resistant OS cells, but miR-485-3p was downregulated. The cell viability and proliferation of the OS cells decreased gradually with the increase of DDP dose, but a gradual increase in apoptosis was noted. CircORC2 promoted OS cell proliferation and DDP resistance and upregulated TRIM2 expression by targeting miR-485-3p. Functionally, circORC2 downregulated miR-485-3p to promote OS cell proliferation and inhibit DDP sensitivity. Additionally, it promoted cell proliferation and inhibited the sensitivity of DDP by regulating the miR-485-3p/TRIM2 axis. In conclusion, circORC2 promoted cell proliferation and inhibited the DDP sensitivity in OS cells via the miR-485-3p/TRIM2 axis. These findings indicated the role of circORC2 in regulating the sensitivity of OS cells to DDP.

EGCG Restores Keratinocyte Autophagy to Promote Diabetic Wound Healing through the AMPK/ULK1 Pathway.

BACKGROUND: Delayed wound healing, a common problem in patients with diabetes mellitus (DM), is associated with impaired keratinocyte autophagy. Epigallocatechin gallate (EGCG), a catechin, has been proven to promote diabetic wound healing. This study aims to explore the therapeutic mechanism of EGCG on diabetic wound healing. METHODS: High glucose (HG)-induced keratinocytes and streptozotocin (STZ)-induced DM rats were prepared and intervened with EGCG to examine its therapeutic effects in in vivo and in vitro settings. The AMPK inhibitor, Compound C, was utilized to determine whether EGCG exerted its therapeutic effects through the AMPK/ULK1 pathway. RESULTS: In vitro, EGCG improved HG-induced autophagy impairment in keratinocytes by increasing LC3II/LC3I, Becline1, and ATG5 levels and decreasing p62 level. Mechanically, EGCG activated the AMPK/ULK1 pathway, thereby promoting keratinocyte autophagy through the phosphorylation of AMPK and ULK1. Notably, EGCG promoted the proliferation, migration, synthesis and release of C-C motif chemokine ligand 2 (CCL2) in HG-treated keratinocytes. Furthermore, EGCG indirectly promoted the activation of fibroblasts, as evidenced by increased alpha-smooth muscle actin (α-SMA) and Collagen I levels. In vivo, EGCG promoted wound healing in DM rats, primarily by reducing inflammatory infiltration and increasing granulation tissue to promote wound epithelialization. Besides, EGCG promoted ATG5, KRT10, KRT14, TGF-ß1, Collagen I, and α-SMA expressions in the neonatal epithelial tissues of DM rats. However, the use of Compound C reversed the effects of EGCG. CONCLUSIONS: These findings indicated that EGCG restored keratinocyte autophagy to promote diabetic wound healing through the AMPK/ULK1 pathway.

Detection Method of Fungal Spores Based on Fingerprint Characteristics of Diffraction-Polarization Images.

The most significant aspect of promoting greenhouse productivity is the timely monitoring of disease spores and applying proactive control measures. This paper introduces a method to classify spores of airborne disease in greenhouse crops by using fingerprint characteristics of diffraction-polarized images and machine learning. Initially, a diffraction-polarization imaging system was established, and the diffraction fingerprint images of disease spores were taken in polarization directions of 0°, 45°, 90° and 135°. Subsequently, the diffraction-polarization images were processed, wherein the fingerprint features of the spore diffraction-polarization images were extracted. Finally, a support vector machine (SVM) classification algorithm was used to classify the disease spores. The study's results indicate that the diffraction-polarization imaging system can capture images of disease spores. Different spores all have their own unique diffraction-polarization fingerprint characteristics. The identification rates of tomato gray mold spores, cucumber downy mold spores and cucumber powdery mildew spores were 96.02%, 94.94% and 96.57%, respectively. The average identification rate of spores was 95.85%. This study can provide a research basis for the identification and classification of disease spores.

Recognition of heart sound based on distribution of Choi-Williams

IntroductionTo realize noninvasive diagnosis and early diagnosis of coronary heart disease, the study proposes a new time-frequency method for analyzing heart sound signals. This method is based on Choi-Williams Distribution (CWD).MethodsCWD distribution is developed and modified from Wigner Ville distribution (WVD). To solve the problem of cross-term interference existing in WVD there is an improved version of WVD, called Choi-Williams Distribution (CWD), which introduces the smoothing window as the kernel function and deals with the time-frequency analysis of heart sound signal.ResultsThe improved method has good performance and can be implemented simply without much increase of operation complexity.ConclusionIn this paper, 21 cases of heart sound signals are acquired from the outpatients and hospitalized patients with coronary heart diseases. The research results of 21 cases show that the CWD method can be used to analyze heart sounds. It accurately identifies the 9 cases of heart sounds of health people and 12 cases of heart sounds of patients with coronary heart disease. Besides, the CWD displays obvious differences between heart sounds of healthy people and abnormal heart sounds. The contour line of heart sounds from healthy people shows the following characteristics: concise, columnar and non-divergence; while the contour line of abnormal heart sounds is divergent and has many columnar links. These research shows that CWD method can effectively distinguish heart sounds between healthy people and patients with coronary heart disease.