Search

The precise identification of disease traits in the complex sugarcane planting environment not only effectively prevents the spread and outbreak of common diseases but also allows for the real-time monitoring of nutrient deficiency syndrome at the top of sugarcane, facilitating the supplementation of relevant nutrients to ensure sugarcane quality and yield. This paper proposes a human–machine collaborative sugarcane disease detection method in complex environments. Initially, data on five common sugarcane diseases—brown stripe, rust, ring spot, brown spot, and red rot—as well as two nutrient deficiency conditions—sulfur deficiency and phosphorus deficiency—were collected, totaling 11,364 images and 10 high-definition videos captured by a 4K drone. The data sets were augmented threefold using techniques such as flipping and gamma adjustment to construct a disease data set. Building upon the YOLOv8 framework, the EMA attention mechanism and Focal loss function were added to optimize the model, addressing the complex backgrounds and imbalanced positive and negative samples present in the sugarcane data set. Disease detection models EF-yolov8s, EF-yolov8m, EF-yolov8n, EF-yolov7, and EF-yolov5n were constructed and compared. Subsequently, five basic instance segmentation models of YOLOv8 were used for comparative analysis, validated using nutrient deficiency condition videos, and a human–machine integrated detection model for nutrient deficiency symptoms at the top of sugarcane was constructed. The experimental results demonstrate that our improved EF-yolov8s model outperforms other models, achieving mAP_0.5, precision, recall, and F1 scores of 89.70%, 88.70%, 86.00%, and 88.00%, respectively, highlighting the effectiveness of EF-yolov8s for sugarcane disease detection. Additionally, yolov8s-seg achieves an average precision of 80.30% with a smaller number of parameters, outperforming other models by 5.2%, 1.9%, 2.02%, and 0.92% in terms of mAP_0.5, respectively, effectively detecting nutrient deficiency symptoms and addressing the challenges of sugarcane growth monitoring and disease detection in complex environments using computer vision technology.

IntroductionThalictrum 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.MethodsThe 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 discussionThe 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.ConclusionConsidering 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.

Ti/Fe clad plate had attracted extensive attention because of its important application. In order to reduce the titanium layer thickness, the explosive welding of TA1 titanium foil to Q235 steel plate was carried out. The interfacial bonding performance was analyzed by micromorphology analysis and mechanical property test, and the formation process of interfacial wave and molten block in the vortex was simulated by smoothed particle hydrodynamics (SPH) method. The results showed that salt as pressure transfer layer used in explosive welding could play a good buffer effect on the collision between flyer and base layers. Regular waveforms were formed on the bonding interface, and the titanium foil/steel clad plate exhibited good welding quality and bonding property. The crest of the observed interfacial wave moved 200 μm from the beginning to the final formation, and it was important of jet on the formation of interfacial waveform. The interface was mainly bonded in the form of molten layer, and the grains near the interface were streamlined. Molten block containing intermetallic compounds and metal oxides appeared in the vortex of wave crest.

Abstract Head and neck squamous cell carcinoma (HNSC) is the most common malignant tumor of head and neck. Due to the insidious nature of HNSC and the lack of effective early diagnostic indicators, the development of novel biomarkers to improve patient prognosis is particularly urgent. In this study, we explored and validated the correlation between cytochrome P450 family 4 subfamily F member 12 (CYP4F12) expression levels and HNSC progression using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) datasets and collected patient samples. We analyzed the association of CYP4F12 expression with clinicopathological features, immune correlation and prognosis. Finally, we analyzed the correlation between CYP4F12 and pathways, and verified by experiments. The results showed that CYP4F12 was low expressed in tumor tissues, participated in a variety of phenotypic changes of HNSC and affected immune cell infiltration. Pathway analysis indicated that CYP4F12 may play a key role in tumor cell migration and apoptosis. Experimental results showed that over-expression of CYP4F12 inhibited cell migration and enhanced the adhesion between cells and matrix by inhibiting epithelial-mesenchymal transition (EMT) pathway in HNSC cells. In conclusion, our study provided insights into the role of CYP4F12 in HNSC and revealed that CYP4F12 may be a potential therapeutic target for HNSC.

Shopping complexes are widely built for their convenience and multiple functions. However, their complex functional areas, result in significantly different thermal environments and various customers’ thermal perception. To explain the influence of functional related parameters on the thermal perception of customers in shopping complexes, we selected two typical functional related parameters, including customers’ thermal expectation level of indoor environment in their current area and the area where the customer was ten minutes before taking the survey. 851 valid questionnaires were obtained in two typical shopping complexes during July. Customers’ thermal neutral temperature, thermal preference temperature and thermal comfort temperature range were calculated in different functional areas. Customers’ thermal expectation level was quantified by using expectancy factor. The results showed that customers’ thermal expectation level in entertainment areas was the highest, followed by food courts, retail areas, and transition spaces. Customers’ thermal expectation level would influence their thermal neutral temperature and thermal sensitivity. Customers with different thermal experience differed significantly in their thermal sensation voting (p< 0.01). The highest thermal sensitivity, about 0.41/°C, was found in customers moving from high-temperature areas to low-temperature areas. These findings help to clarify how functional related parameters affect the thermal comfort of customers and provide the guidance for designing the indoor temperature in shopping complexes.

Summary: 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.

Immune cells are indispensable defenders of the human body, clearing exogenous pathogens and toxicities or endogenous malignant and aging cells. Immune cell dysfunction can cause an inability to recognize, react, and remove these hazards, resulting in cancers, inflammatory diseases, autoimmune diseases, and infections. Immune cells regulation has shown great promise in treating disease, and immune agonists are usually used to treat cancers and infections caused by immune suppression. In contrast, immunosuppressants are used to treat inflammatory and autoimmune diseases. However, the key to maintaining health is to restore balance to the immune system, as excessive activation or inhibition of immune cells is a common complication of immunotherapy. Nanoparticles are efficient drug delivery systems widely used to deliver small molecule inhibitors, nucleic acid, and proteins. Using nanoparticles for the targeted delivery of drugs to immune cells provides opportunities to regulate immune cell function. In this review, we summarize the current progress of nanoparticle-based strategies for regulating immune function and discuss the prospects of future nanoparticle design to improve immunotherapy.

Abstract Background Dietary bamboo leaf flavonoids (BLFs) are rarely used in poultry production, and it is unknown whether they influence meat texture profile, perceived color, or microstructure. Results A total of 720 one-day-old Arbor Acres broilers were supplemented with a basal diet with 20 mg bacitracin/kg, 50 mg BLFs/kg, or 250 mg BLFs/kg or without additions. Data showed that the dietary BLFs significantly (P