Atypical Adams-Oliver syndrome with typical ocular signs of familial exudative vitreoretinopathy

AIM: To report an atypical Adams-Oliver syndrome (AOS) family with typical ocular signs of familial exudative vitreoretinopathy (FEVR). METHODS: A patient with visible avascular area and obvious non-perfusion zone in the peripheral retina with systemic signs of AOS was reported. Familial and personal characteristics were collected for the patient and his sister. Gene sequencing and ophthalmic examinations including fluorescein angiography were all performed for the whole family. RESULTS: Two novel mutations of DOCK6 (c.1396C>T and c.4796G>A) were identified in the proband and his family, and two compound heterozygous mutations were revealed in the proband and his sister. The patient and his sister showed physical deformities and mental abnormalities while FEVR mimicking retinal disorder can also be defined. No remarkable ocular or systemic abnormality can be observed for their parents. Peripheral retinal non-perfusion area, obvious abnormal vascularization or even retinal fold were observed in the proband and his sister, while only small avascular zone was identified for their parents. CONCLUSION: This is the first genetic authenticated AOS case mimicked as FEVR with genetic sequencing of a family. For the patients with ocular phenotype of FEVR, further examination should be performed if the systemic or mental abnormalities exist

Multi-scenario pear tree inflorescence detection based on improved YOLOv7 object detection algorithm

Efficient and precise thinning during the orchard blossom period is a crucial factor in enhancing both fruit yield and quality. The accurate recognition of inflorescence is the cornerstone of intelligent blossom equipment. To advance the process of intelligent blossom thinning, this paper addresses the issue of suboptimal performance of current inflorescence recognition algorithms in detecting dense inflorescence at a long distance. It introduces an inflorescence recognition algorithm, YOLOv7-E, based on the YOLOv7 neural network model. YOLOv7 incorporates an efficient multi-scale attention mechanism (EMA) to enable cross-channel feature interaction through parallel processing strategies, thereby maximizing the retention of pixel-level features and positional information on the feature maps. Additionally, the SPPCSPC module is optimized to preserve target area features as much as possible under different receptive fields, and the Soft-NMS algorithm is employed to reduce the likelihood of missing detections in overlapping regions. The model is trained on a diverse dataset collected from real-world field settings. Upon validation, the improved YOLOv7-E object detection algorithm achieves an average precision and recall of 91.4% and 89.8%, respectively, in inflorescence detection under various time periods, distances, and weather conditions. The detection time for a single image is 80.9 ms, and the model size is 37.6 Mb. In comparison to the original YOLOv7 algorithm, it boasts a 4.9% increase in detection accuracy and a 5.3% improvement in recall rate, with a mere 1.8% increase in model parameters. The YOLOv7-E object detection algorithm presented in this study enables precise inflorescence detection and localization across an entire tree at varying distances, offering robust technical support for differentiated and precise blossom thinning operations by thinning machinery in the future

Perturbed autophagy intervenes systemic lupus erythematosus by active ingredients of traditional Chinese medicine

Systemic lupus erythematosus (SLE) is a common multisystem, multiorgan heterozygous autoimmune disease. The main pathological features of the disease are autoantibody production and immune complex deposition. Autophagy is an important mechanism to maintain cell homeostasis. Autophagy functional abnormalities lead to the accumulation of apoptosis and induce the autoantibodies that result in immune disorders. Therefore, improving autophagy may alleviate the development of SLE. For SLE, glucocorticoids or immunosuppressive agents are commonly used in clinical treatment, but long-term use of these drugs causes serious side effects in humans. Immunosuppressive agents are expensive. Traditional Chinese medicines (TCMs) are widely used for immune diseases due to their low toxicity and few side effects. Many recent studies found that TCM and its active ingredients affected the pathological development of SLE by regulating autophagy. This article explains how autophagy interferes with immune system homeostasis and participates in the occurrence and development of SLE. It also summarizes several studies on TCM-regulated autophagy intervention in SLE to generate new ideas for basic research, the development of novel medications, and the clinical treatment of SLE

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe