Explore the vast range of titles available.

Growth traits, such as fresh weight, diameter, and leaf area, are pivotal indicators of growth status and the basis for the quality evaluation of lettuce. The time-consuming, laborious and inefficient method of manually measuring the traits of lettuce is still the mainstream. In this study, a three-stage multi-branch self-correcting trait estimation network (TMSCNet) for RGB and depth images of lettuce was proposed. The TMSCNet consisted of five models, of which two master models were used to preliminarily estimate the fresh weight (FW), dry weight (DW), height (H), diameter (D), and leaf area (LA) of lettuce, and three auxiliary models realized the automatic correction of the preliminary estimation results. To compare the performance, typical convolutional neural networks (CNNs) widely adopted in botany research were used. The results showed that the estimated values of the TMSCNet fitted the measurements well, with coefficient of determination ( R 2 ) values of 0.9514, 0.9696, 0.9129, 0.8481, and 0.9495, normalized root mean square error (NRMSE) values of 15.63, 11.80, 11.40, 10.18, and 14.65% and normalized mean squared error (NMSE) value of 0.0826, which was superior to compared methods. Compared with previous studies on the estimation of lettuce traits, the performance of the TMSCNet was still better. The proposed method not only fully considered the correlation between different traits and designed a novel self-correcting structure based on this but also studied more lettuce traits than previous studies. The results indicated that the TMSCNet is an effective method to estimate the lettuce traits and will be extended to the high-throughput situation. Code is available at https://github.com/lxsfight/TMSCNet.git .

An ectopic origin of the right coronary artery from the pulmonary artery is an extremely rare congenital malformation. This case report aimed to review our experience in the diagnosis and treatment of coronary artery anomalies. We report a case of ectopic origin of the right coronary artery from the pulmonary artery. We analyzed the taxonomy and clinical implications of the ectopic origin of the coronary artery. The findings of this case may increase patients’ and clinicians’ awareness of this anomaly.

Background Adolescence is a critical period for the onset of mental health issues. In China, high school students face significant academic and social pressures, leading to high rates of mental health challenges. Gender differences in the manifestation of these symptoms have been observed, with boys and girls exhibiting distinct psychological profiles. Objective This study aims to explore the structure of psychological symptoms among Chinese high school students using network analysis, focusing on identifying core symptoms and gender differences in symptom networks. The key objectives are to: 1) identify the central psychological symptoms for boys and girls, and 2) uncover the interactions between symptoms to inform targeted interventions. Methods A cluster sampling method was used to recruit 3,769 high school students (2,206 males and 1,563 females) in Shanghai. The Middle School Students Mental Health Scale (MSSMHS) was administered, and network analysis was conducted using the R packages bootnet and qgraph to assess symptom network edges, centrality, and network strength. Comparisons between male and female networks were made. Results Network analysis showed tightly connected symptom networks for both genders, with 43 non-zero edges for boys (sparsity 0.04) and 39 for girls (sparsity 0.13). Depression was the core symptom for boys (centrality 1.20), while anxiety was central for girls (centrality 1.46). Boys showed a stronger link between interpersonal sensitivity and depression (edge value 0.20), while girls exhibited a stronger connection between anxiety and obsessive-compulsive symptoms (edge value 0.16). Network comparison tests revealed no significant differences in overall network strength between boys (4.625) and girls (4.660), with P-values greater than 0.05 across all comparisons. Conclusion This study highlights significant gender differences in the psychological symptom networks of Chinese high school students. Depression and anxiety emerged as core symptoms for boys and girls, respectively. These findings provide a foundation for developing gender-sensitive mental health interventions, emphasizing the need for tailored approaches based on gender-specific symptom profiles. Highlights Significant gender differences in the symptom networks of adolescents, with depression and anxiety as key central nodes. A tight link between anxiety and depression in female students, whereas a strong connection exists between depression and interpersonal sensitivity in male students. Emphasizes the importance of designing targeted educational and mental health interventions.

In view of the mechanical safety risks of industrial robots, AGVs and other mobile devices that are widely used in smart factories, a mechanical safety risk analysis of smart factories method is carried out. First, it analyzes the mechanical safety risks of CNC machine tools, industrial robots, AGVs, and warehouses in smart factories. Then, a specific seal production workshop is taken as an example. It conducts a mechanical safety risk analysis and gives a safety plan to reduce the risk. The mechanical safety of the personalized seal workshop has achieved sufficient risk reduction. This article can provide a certain reference for conducting mechanical safety risk analysis during the construction of smart factories.

Primary malignant melanoma of the lung (PMML) is an extremely rare and refractory tumor, and its diagnosis is a significant challenge. The current study presents the case of a 62-year-old man who presented to the Department of Cardiothoracic Surgery (Lishui Municipal Central Hospital, Lishui, China) with chest tightness and fatigue for 3 months. Chest computed tomography (CT) revealed a 1.5- × 1.9-cm mass with irregular borders and heterogenous density located in the right lower lung lobe. Contrast-enhanced CT revealed slight enhancement of the mass, but there was no clear evidence of malignancy. Positron emission tomography (PET)/CT revealed a defined-margin mass, with slightly high uptake (standardized uptake value [SUV]: 3.6). The patient underwent video-assisted thoracoscopic surgery (VATS), and the final diagnosis was PMML on the basis of the results of the pathological examination. The patient received four courses of immunotherapy after the operation, and eventually declined further immunotherapy owing to the high cost. The patient was followed-up for 1 year without metastasis or recurrence.

Non-small cell lung cancer (NSCLC) is frequently associated with oncogenic driver mutations, which play an important role in carcinogenesis and cancer progression. Targeting epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase rearrangements has become standard therapy for patients with these aberrations because of the greater improvement of survival, tolerance, and quality-of-life compared to chemotherapy. Clinical trials for emerging therapies that target other less common driver genes are generating mixed results. Here, we review the literature on rare drivers in NSCLC with frequencies lower than 5% (e.g., ROS1, RET, MET, BRAF, NTRK, HER2, NRG1, FGFR1, PIK3CA, DDR2, and EGFR exon 20 insertions). In summary, targeting rare oncogenic drivers in NSCLC has achieved some success. With the development of new inhibitors that target these rare drivers, the spectrum of targeted therapy has been expanded, although acquired resistance is still an unavoidable problem.

The cyclic signal amplification technology has been widely applied for the ultrasensitive detection of many important biomolecules, such as nucleic acids, proteins, enzymes, adenosine triphosphate (ATP), metal ions, exosome, etc. Due to their low content in the complex biological samples, traditional detection methods are insufficient to satisfy the requirements for monitoring those biomolecules. Therefore, effective and sensitive biosensors based on cyclic signal amplification technology are of great significance for the quick and simple diagnosis and treatment of diseases. Fluorescent biosensor based on cyclic signal amplification technology has become a research hotspot due to its simple operation, low cost, short time, high sensitivity and high specificity. This paper introduces several cyclic amplification methods, such as rolling circle amplification (RCA), strand displacement reactions (SDR) and enzyme-assisted amplification (EAA), and summarizes the research progress of using this technology in the detection of different biomolecules in recent years, in order to provide help for the research of more efficient and sensitive detection methods. Graphical Abstract

The oriental latrine fly, Chrysomya megacephala (Diptera: Calliphoridae), is a medically important synanthropic blow fly species characterized by its necrophagy and coprophagy, often observed near carrion and animal feces. Notably, C. megacephala always arrives at carcass earlier than other species. To elucidate the underlying mechanisms behind the host choice in C. megacephala , we present the chromosome-scale genome assembly for this species. The genome size is 816.79 Mb, with a contig N50 of 1.60 Mb. The Hi-C data were anchored to six chromosomes, accounting for 99.93% of the draft assembled genome. Comparative genomic analysis revealed significant expansions in pathways of ligand-gated ion channel activity, passive transmembrane transporter activity, and protein methyltransferase activity, which may be closely associated with host localization and oviposition. After identifying 69 odor-binding proteins (OBPs) in the assembled genome, phylogenetic analysis showed that DmelOBP99b and CmegOBP99b exhibited high homology. Transcriptome analysis demonstrated that the relative expression of CmegOBP99b was consistently the highest during the metamorphosis, and RT-qPCR further confirmed the similar results. Additionally, CmegOBP99b exhibited a strong binding affinity to DMDS (dimethyl disulfide) as determined by molecular docking. To determine the protein expression level of CmegOBP99b in various body parts, we prepared recombinant CmegOBP99b protein and anti- CmegOBP99b polyclonal antibodies. Western blot analysis showed that CmegOBP99b was significantly expressed in the female’s head compared to other parts, which is consistent with RT-qPCR results. Therefore, CmegOBP99b may be the primary odor-binding protein responsible for olfactory recognition and the behavioral coordination of C. megacephala . This study not only provides valuable insights into the molecular mechanisms of oviposition localization in C. megacephala but also facilitates further research into the genetic diversity and phylogeny of the Calliphoridae family.

Sarcophaga peregrina (Robineau-Desvoidy, 1830) (Diptera: Sarcophagidae) is a forensically important flesh fly that has potential value in estimating the PMImin. The precise pupal age estimation has great implications for PMImin estimation. During larval development, the age determination is straightforward by the morphological changes and variation of length and weight, however, the pupal age estimation is more difficult due to anatomical and morphological changes not being visible. Thus, it is necessary to find new techniques and methods that can be implemented by standard experiments for accurate pupal age estimation. In this study, we first investigated the potential of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and cuticular hydrocarbons (CHCs) for the age estimations of S. peregrina pupae at different constant temperatures (20 °C, 25 °C, and 30 °C). The orthogonal projections latent structure discrimination analysis (OPLS-DA) classification model was used to distinguish the pupae samples of different developmental ages. Then, a multivariate statistical regression model, partial least squares (PLS), was established with the spectroscopic and hydrocarbon data for pupal age estimations. We identified 37 CHCs with a carbon chain length between 11 and 35 in the pupae of S. peregrina. The results of the OPLS-DA model show a significant separation between different developmental ages of pupae (R2X > 0.928, R2Y > 0.899, Q2 > 0.863). The PLS model had a satisfactory prediction with a good fit between the actual and predicted ages of the pupae (R2 > 0.927, RMSECV < 1.268). The results demonstrate that the variation tendencies of spectroscopy and hydrocarbons were time-dependent, and ATR-FTIR and CHCs may be optimal for the age estimations of pupae of forensically important flies with implications for PMImin estimation in forensic practice.

Background Drug adverse events (AEs), or called adverse drug events (ADEs), are ranked one of the leading causes of mortality. The Ontology of Adverse Events (OAE) has been widely used for adverse event AE representation, standardization, and analysis. OAE-based ADE-specific ontologies, including ODNAE for drug-associated neuropathy-inducing AEs and OCVDAE for cardiovascular drug AEs, have also been developed and used. However, these ADE-specific ontologies do not consider the effects of other factors (e.g., age and drug-treated disease) on the outcomes of ADEs. With more ontological studies of ADEs, it is also critical to develop a general purpose ontology for representing ADEs for various types of drugs. Results Our survey of FDA drug package insert documents and other resources for 224 neuropathy-inducing drugs discovered that many drugs (e.g., sirolimus and linezolid) cause different AEs given patients’ age or the diseases treated by the drugs. To logically represent the complex relations among drug, drug ingredient and mechanism of action, AE, age, disease, and other related factors, an ontology design pattern was developed and applied to generate a community-driven open-source Ontology of Drug Adverse Events (ODAE). The ODAE development follows the OBO Foundry ontology development principles (e.g., openness and collaboration). Built on a generalizable ODAE design pattern and extending the OAE and NDF-RT ontology, ODAE has represented various AEs associated with the over 200 neuropathy-inducing drugs given different age and disease conditions. ODAE is now deposited in the Ontobee for browsing and queries. As a demonstration of usage, a SPARQL query of the ODAE knowledge base was developed to identify all the drugs having the mechanisms of ion channel interactions, the diseases treated with the drugs, and AEs after the treatment in adult patients. AE-specific drug class effects were also explored using ODAE and SPARQL. Conclusion ODAE provides a general representation of ADEs given different conditions and can be used for querying scientific questions. ODAE is also a robust knowledge base and platform for semantic and logic representation and study of ADEs of more drugs in the future.