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Fuzheng Huayu recipe (FZHYR) is a Chinese patent medicine for the treatment of fibrosis. The effects of FZHYR on pulmonary fibrosis and macrophage polarization were investigated in vitro. FZHYR inhibited pulmonary inflammation and fibrosis and M2 polarization of macrophages in bleomycin-induced pulmonary fibrosis (BPF) of rat model. Differentially expressed genes were screened by high-throughput mRNA sequencing and GSEA showed that oxidative phosphorylation (OXPHOS) was correlated with BPF. FZHYR inhibited expressions of Ndufa2 and Ndufa6 in lung tissues of BPF rats. These findings suggest that OXPHOS pathway serves as a possible target for pulmonary fibrosis therapy by FZHYR.
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Infrared small target detection plays a crucial role in maritime security. However, detecting small targets within heavy sea clutter environments remains challenging. Existing methods often fail to deliver satisfactory performance in the presence of substantial clutter interference. This paper analyzes the spatial-temporal appearance characteristics of small targets and sea clutter. Based on this analysis, we propose a novel detection method based on the appearance stable isotropy measure (ASIM). First, the original images are processed using the Top-Hat transformation to obtain the salient regions. Next, a preliminary threshold operation is employed to extract the candidate targets from these salient regions, forming a candidate target array image. Third, to distinguish between small targets and sea clutter, we introduce two characteristics: the gradient histogram equalization measure (GHEM) and the local optical flow consistency measure (LOFCM). GHEM evaluates the isotropy of the candidate targets by examining their gradient histogram equalization, while LOFCM assesses their appearance stability based on local optical flow consistency. To effectively combine the complementary information provided by GHEM and LOFCM, we propose ASIM as a fusion characteristic, which can effectively enhance the real target. Finally, a threshold operation is applied to determine the final targets. Experimental results demonstrate that our proposed method exhibits superior comprehensive performance compared to baseline methods.
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Introduction: Thalictrum fargesii is a medicinal plant belonging to the genus Thalictrum of the Ranunculaceae family and has been used in herbal medicine in the Himalayan regions of China and India. This species is taxonomically challenging because of its morphological similarities to other species within the genus. Thus, herbal drugs from this species are frequently adulterated, substituted, or mixed with other species, thereby endangering consumer safety. Methods: The present study aimed to sequence and assemble the entire chloroplast (cp) genome of T. fargesii using the Illumina HiSeq 2500 platform to better understand the genomic architecture, gene composition, and phylogenetic relationships within the Thalictrum. Results and discussion: The cp genome was 155,929 bp long and contained large single-copy (85,395 bp) and small single-copy (17,576 bp) regions that were segregated by a pair of inverted repeat regions (26,479 bp) to form a quadripartite structure. The cp genome contains 133 genes, including 88 protein-coding genes (PCGs), 37 tRNA genes, and 8 rRNA genes. Additionally, this genome contains 64 codons that encode 20 amino acids, the most preferred of which are alanine and leucine. We identified 68 SSRs, 27 long repeats, and 242 high-confidence C-to-U RNA-editing sites in the cp genome. Moreover, we discovered seven divergent hotspot regions in the cp genome of T. fargesii, among which ndhD-psaC and rpl16-rps3 may be useful for developing molecular markers for identifying ethnodrug species and their contaminants. A comparative study with eight other species in the genus revealed that pafI and rps19 had highly variable sites in the cp genome of T. fargesii. Additionally, two special features, (i) the shortest length of the ycf1 gene at the IRA-SSC boundary and (ii) the distance between the rps19 fragment and trnH at the IRA-LSC junction, distinguish the cp genome of T. fargesii from those of other species within the genus. Furthermore, phylogenetic analysis revealed that T. fargesii was closely related to T. tenue and T. petaloidium. Conclusion: Considering all these lines of evidence, our findings offer crucial molecular and evolutionary information that could play a significant role in further species identification, evolution, and phylogenetic studies on T. fargesii.
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BACKGROUND: The occurrence, development, and outbreak of tea diseases and pests pose a significant challenge to the quality and yield of tea, necessitating prompt identification and control measures. Given the vast array of tea diseases and pests, coupled with the intricacies of the tea planting environment, accurate and rapid diagnosis remains elusive. In addressing this issue, the present study investigates the utilization of transfer learning convolution neural networks for the identification of tea diseases and pests. Our objective is to facilitate the accurate and expeditious detection of diseases and pests affecting the Yunnan Big leaf kind of tea within its complex ecological niche. RESULTS: Initially, we gathered 1878 image data encompassing 10 prevalent types of tea diseases and pests from complex environments within tea plantations, compiling a comprehensive dataset. Additionally, we employed data augmentation techniques to enrich the sample diversity. Leveraging the ImageNet pre-trained model, we conducted a comprehensive evaluation and identified the Xception architecture as the most effective model. Notably, the integration of an attention mechanism within the Xeption model did not yield improvements in recognition performance. Subsequently, through transfer learning and the freezing core strategy, we achieved a test accuracy rate of 98.58% and a verification accuracy rate of 98.2310%. CONCLUSIONS: These outcomes signify a significant stride towards accurate and timely detection, holding promise for enhancing the sustainability and productivity of Yunnan tea. Our findings provide a theoretical foundation and technical guidance for the development of online detection technologies for tea diseases and pests in Yunnan.
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The receptor for advanced glycation end products (RAGE) contributes to diabetes-associated cognitive dysfunction (DACD) through the interaction of its C-terminal AAs 2-5 with mitogen-activated protein kinase kinase 3 (MKK3). However, the associated MKK3 binding site is unknown. Here, db/db mice were used as a model for type 2 diabetes. GST pull-down assays and AutoDock Vina simulations were conducted to identify the key RAGE binding site in MKK3. This binding site was mutated to investigate its effects on DACD and to elucidate the underlying mechanisms. The interaction of MKK3 and RAGE, the levels of inflammatory factors, and the activation of microglia and astrocytes were tested. Synaptic morphology and plasticity in hippocampal neurons were assessed via electrophysiological recordings and Golgi staining. Behavioral tests were used to assess cognitive function. In this study, MKK3 bound directly to RAGE via its lysine 329 (K329), leading to the activation of the nuclear factor-κB (NF-κB) signaling pathway, which in turn triggered neuroinflammation and synaptic dysfunction, and ultimately contributed to DACD. MKK3 mutation at K329 reversed synaptic dysfunction and cognitive deficits by downregulating the NF-κB signaling pathway and inhibiting neuroinflammation. These results confirm that neuroinflammation and synaptic dysfunction in the hippocampus rely on the direct binding of MKK3 and RAGE. We conclude that MKK3 K329 binding to C-terminal RAGE (ct-RAGE) is a key mechanism by which neuroinflammation and synaptic dysfunction are induced in the hippocampus. This study presents a novel mechanism for DACD and proposes a novel therapeutic avenue for neuroprotection in DACD.
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Background: The occult lymph node metastasis (LNM) of laryngeal squamous cell carcinoma (LSCC) affects the treatment and prognosis of patients. This study aimed to comprehensively compare the performance of the three-dimensional and two-dimensional deep learning models, radiomics model, and the fusion models for predicting occult LNM in LSCC. Methods: In this retrospective diagnostic study, a total of 553 patients with clinical N0 stage LSCC, who underwent surgical treatment without distant metastasis and multiple primary cancers, were consecutively enrolled from four Chinese medical centres between January 01, 2016 and December 30, 2020. The participant data were manually retrieved from medical records, imaging databases, and pathology reports. The study cohort was divided into a training set (n = 300), an internal test set (n = 89), and two external test sets (n = 120 and 44, respectively). The three-dimensional deep learning (3D DL), two-dimensional deep learning (2D DL), and radiomics model were developed using CT images of the primary tumor. The clinical model was constructed based on clinical and radiological features. Two fusion strategies were utilized to develop the fusion model: the feature-based DLRad_FB model and the decision-based DLRad_DB model. The discriminative ability and correlation of 3D DL, 2D DL and radiomics features were analysed comprehensively. The performances of the predictive models were evaluated based on the pathological diagnosis. Findings: The 3D DL features had superior discriminative ability and lower internal redundancy compared to 2D DL and radiomics features. The DLRad_DB model achieved the highest AUC (0.89-0.90) among all the study sets, significantly outperforming the clinical model (AUC = 0.73-0.78, P = 0.0001-0.042, Delong test). Compared to the DLRad_DB model, the AUC values for the DLRad_FB, 3D DL, 2D DL, and radiomics models were 0.82-0.84 (P = 0.025-0.46), 0.86-0.89 (P = 0.75-0.97), 0.83-0.86 (P = 0.029-0.66), and 0.79-0.82 (P = 0.0072-0.10), respectively in the study sets. Additionally, the DLRad_DB model exhibited the best sensitivity (82-88%) and specificity (79-85%) in the test sets. Interpretation: The decision-based fusion model DLRad_DB, which combines 3D DL, 2D DL, radiomics, and clinical data, can be utilized to predict occult LNM in LSCC. This has the potential to minimize unnecessary lymph node dissection and prophylactic radiotherapy in patients with cN0 disease. Funding: National Natural Science Foundation of China, Natural Science Foundation of Shandong Province.
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PURPOSE: To investigate the feasibility and effect of free latissimus dorsi myocutaneous flap in the reconstruction of giant head and neck defects. METHODS: Free latissimus dorsi myocutaneous flap on the cadaver was simulated dissected, and measured by Image-Pro Plus 6.0 to assess the feasibility of repairing giant head and neck defects. Between May 2011 and September 2022, seven patients with giant head and neck defects of different causes repaired with the latissimus dorsi myocutaneous flap were retrospectively analyzed. RESULTS: The diameter of the initiating thoracodorsal artery was (4.03±0.56) mm, and the mean lengths of the arteriolar and venous pedicles of the latissimus dorsi myocutaneous flaps obtained from human specimens were (85.5±10.5) mm and (104±4.2) mm, respectively. Among 7 patients, 5 cases had scalp defects, the remaining 2 cases had neck defects. There were no substantial postoperative problems in the donor site, and all seven latissimus dorsi myocutaneous flaps were successfully transplanted. CONCLUSIONS: For the treatment of considerable head and neck deformities, the latissimus dorsi myocutaneous flap is an optimal muscle flap due to its abundance of tissue, enough length of vascular pedicles, and sufficient venous drainage.
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Colgajo Miocutáneo , Procedimientos de Cirugía Plástica , Músculos Superficiales de la Espalda , Humanos , Músculos Superficiales de la Espalda/trasplante , Colgajo Miocutáneo/trasplante , Procedimientos de Cirugía Plástica/métodos , Estudios Retrospectivos , Cuello/cirugía , Cuello/anatomía & histología , Cabeza/cirugía , Cabeza/anatomía & histología , Neoplasias de Cabeza y Cuello/cirugía , Cadáver , Cuero Cabelludo/cirugía , MasculinoRESUMEN
Incontinentia pigmenti (IP) is a rare X-linked dominant neuroectodermal dysplasia that primarily affects females. The only known causative gene is IKBKG, and the most common genetic cause is the recurrent IKBKGâ³4-10 deletion resulting from recombination between two MER67B repeats. Detection of variants in IKBKG is challenging due to the presence of a highly homologous non-pathogenic pseudogene IKBKGP1. In this study, we successfully identified four pathogenic variants in four IP patients using a strategy based on single-tube long fragment read (stLFR) sequencing with a specialized analysis pipeline. Three frameshift variants (c.519-3_519dupCAGG, c.1167dupC, and c.700dupT) were identified and subsequently validated by Sanger sequencing. Notably, c.519-3_519dupCAGG was found in both IKBKG and IKBKGP1, whereas the other two variants were only detected in the functional gene. The IKBKGâ³4-10 deletion was identified and confirmed in one patient. These results demonstrate that the proposed strategy can identify potential pathogenic variants and distinguish whether they are derived from IKBKG or its pseudogene. Thus, this strategy can be an efficient genetic testing method for IKBKG. By providing a comprehensive understanding of the whole genome, it may also enable the exploration of other genes potentially associated with IP. Furthermore, the strategy may also provide insights into other diseases with detection challenges due to pseudogenes.
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Background: Intrahepatic cholangiocarcinoma (ICC) poses a significant clinical challenge, demanding a thorough understanding of prognostic indicators for effective patient management. Despite reports suggesting the impact of perineural invasion (PNI) on the prognosis of early-stage ICC patients, there has been a dearth of comprehensive research specifically targeting this subgroup. This study seeks to investigate the influence of PNI on survival outcomes in early-stage ICC patients and aims to enhance the prognostic value of the American Joint Committee on Cancer (AJCC) T category. Methods: A cohort of 268 early-stage (T1-T2N0M0) ICC patients, who underwent curative-intent resection (R0) between 2011 and 2015 at the Eastern Hepatobiliary Surgery Hospital, were enrolled in this study. Lasso and Cox regression analyses were employed to explore differences in clinical and prognostic data. Kaplan-Meier curves were generated to illustrate the clinical significance of the combination of PNI and T category. Results: Among the 268 patients, 24.6% exhibited PNI. Patients with PNI demonstrated shorter recurrence-free survival (RFS) [median RFS: 16 months (interquartile range, 9.5-19 months)] and overall survival (OS) [median OS: 16.53 months (interquartile range, 10-25 months)]. PNI emerged as an independent risk factor for both RFS and OS in T1- and T2-stage patients (all P<0.05), whereas tumor size was only an independent risk factor for OS (P=0.004). PNI was associated with all prognostic markers for ICC patients, including gender, jaundice, cholangitis, hepatitis B virus (HBV) infection, cancer antigen 199 (CA199), preoperative serum albumin, and preoperative platelet count (all P<0.05). However, there was no significant difference in RFS (P=0.270) and OS (P=0.360) between T2 patients without PNI and T1 patients with PNI. Conclusions: This study underscores PNI as a robust prognostic factor in early-stage ICC, emphasizing the necessity of incorporating PNI into the AJCC T category for precise risk stratification. Clinically, understanding the impact of PNI on survival outcomes can guide tailored treatment strategies for early ICC patients.