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Background In the multiple ligament injury of the knee joint, apart from the anterior cruciate ligament and the posterior cruciate ligament, the Posterolateral Corner and the Posteromedial Corner are two structures that are easily overlooked. If not properly identified and repaired in one stage, the knee joint may be unstable, even failure of cruciate ligament reconstruction. The purpose of this article was to evaluate the effect of knee joint recovery after PLC (Posterolateral Corner) with or without PMC (Posteromedial Corner) injury. Methods From 2016 to 2020, we screened a total of 2564 patients, of which 292 patients met the inclusion and exclusion criteria. In the end, a total of 44 people completed the study. Follow‐up was performed at 1, 3, 6, 9, and 12 months after surgery. We used pain visual analog scale (VAS) for pain, IKDC score, Lysholm score, Tegner score. Opti‐knee (a portable motion analysis system) was used to evaluate the stability of the knee joint at 1 year. In our prospective cohort study, we used the unpaired Student's t‐test for statistical analysis. Results The knee joint function of PLC group and PLC combined PMC group was better than that before operation at 3 or 6 months after operation. Except for IKDC at 9‐month follow‐up and Tegner score at 9‐month and 12‐month follow‐up, there was no significant difference between the other groups. Conclusions PLC and PLC combined with PMC injury showed similar prognostic effects, although the PLC group was numerically superior to the other group. We recommend primary repair and reconstruction in patients with confirmed PLC and PMC injuries to achieve the best postoperative recovery. This study assesses knee recovery after PLC/PLC+PMC injury repair: 44 patients followed up for 12 months, similar outcomes, PLC group numerically better; primary repair/reconstruction advised for optimal recovery.

The Chinese tongue sole ( Cynoglossus semilaevis ) is widely cultured in the coastal region of East Asia and has excellent economic value. However, the high albino rate of the breeding population has caused a significant loss to the aquaculture industry. To study the molecular mechanism of albinism, the present study used an albino Chinese tongue sole family to construct three simple sequence repeat (SSR) linkage groups, and draft a preliminary linkage map related to albinism. After albinism-related loci mapping, 18 albinism-related loci were detected under two models (containing 2407 genes) compared to the Chinese tongue sole genome. One of these loci, the tyrosinase related protein ( tyrp2 ), which has been reported previously as an important gene regulating both eumelanin and phaeomelanin levels, was indicated to be the possible cause of albinism. Thirty-five Gene Ontology (GO) terms and 14 Kyoto Encyclopedia of Genes and Genome pathways were annotated via bioinformatic analyses. One GO term with protein tyrosine kinase activity, which contained 10 genes, was previously suggested to affect fish albinism. These results establish a foundation for further in-depth study of albinism in Chinese tongue sole.

In recent years, Edwardsiella tarda has become one of the most deadly pathogens of Japanese flounder (Paralichthys olivaceus), causing serious annual losses in commercial production. In contrast to the rapid advances in the aquaculture of P. olivaceus, the study of E. tarda resistance-related markers has lagged behind, hindering the development of a disease-resistant strain. Thus, a marker-trait association analysis was initiated, combining bulked segregant analysis (BSA) and quantitative trait loci (QTL) mapping. Based on 180 microsatellite loci across all chromosomes, 106 individuals from the F1333 (♀: F0768 ×♂: F0915) (Nomenclature rule: F+year+family number) were used to detect simple sequence repeats (SSRs) and QTLs associated with E. tarda resistance. After a genomic scan, three markers (Scaffold 404-21589, Scaffold 404-21594 and Scaffold 270-13812) from the same linkage group (LG)-1 exhibited a significant difference between DNA, pooled/bulked from the resistant and susceptible groups (P <0.001). Therefore, 106 individuals were genotyped using all the SSR markers in LG1 by single marker analysis. Two different analytical models were then employed to detect SSR markers with different levels of significance in LG1, where 17 and 18 SSR markers were identified, respectively. Each model found three resistance-related QTLs by composite interval mapping (CIM). These six QTLs, designated qE1–6, explained 16.0%–89.5% of the phenotypic variance. Two of the QTLs, qE-2 and qE-4, were located at the 66.7 cM region, which was considered a major candidate region for E. tarda resistance. This study will provide valuable data for further investigations of E. tarda resistance genes and facilitate the selective breeding of disease-resistant Japanese flounder in the future.

In this paper, we give some rigidity results for complete self-shrinking surfaces properly immersed in ℝ4 under some assumptions regarding their Gauss images. More precisely, we prove that this has to be a plane, provided that the images of either Gauss map projection lies in an open hemisphere or S2(1/2)¯+1(1/2) . We also give the classification of complete self-shrinking surfaces properly immersed in ℝ4 provided that the images of Gauss map projection lies in some closed hemispheres. As an application of the above results, we give a new proof for the result of Zhou. Moreover, we establish a Bernstein-type theorem.

In this paper, we investigate an eigenvalue problem for the Dirichlet Laplacian on a domain in an n-dimensional compact Riemannian manifold. First we give a general inequality for eigenvalues. As one of its applications, we study eigenvalues of the Laplacian on a domain in an n-dimensional complex projective space, on a compact complex submanifold in complex projective space and on the unit sphere. By making use of the orthogonalization of Gram–Schmidt (QR-factorization theorem), we construct trial functions. By means of these trial functions, estimates for lower order eigenvalues are obtained.

For a bounded domain Ω in a complete Riemannian manifold M, we investigate the Dirichlet weighted eigenvalue problem of quadratic polynomial operator Δ2 − aΔ + b of the Laplacian Δ, where a and b are the nonnegative constants. We obtain an inequality for eigenvalues which contains a constant that only depends on the mean curvature of M. It yields an upper bound of the (k + 1)th eigenvalue Λk + 1. As their applications, some inequalities and bounds of eigenvalues on a complete minimal submanifold in a Euclidean space and a unit sphere are obtained.

The Japanese flounder is one of the most widely farmed economic flatfish species throughout eastern Asia including China, Korea, and Japan. Edwardsiella tarda is a major species of pathogenic bacteria that causes ascites disease and, consequently, a huge economy loss for Japanese flounder farming. After generation selection, traditional breeding methods can hardly improve the E. tarda resistance effectively. Genomic selection is an effective way to predict the breeding potential of parents and has rarely been used in aquatic breeding. In this study, we chose 931 individuals from 90 families, challenged by E. tarda from 2013 to 2015 as a reference population and 71 parents of these families as selection candidates. 1,934,475 markers were detected via genome sequencing and applied in this study. Two different methods, BayesCπ and GBLUP, were used for genomic prediction. In the reference population, two methods led to the same accuracy (0.946) and Pearson’s correlation results between phenotype and genomic estimated breeding value (GEBV) of BayesCπ and GBLUP were 0.912 and 0.761, respectively. In selection candidates, GEBVs from two methods were highly similar (0.980). A comparison of GEBV with the survival rate of families that were structured by selection candidates showed correlations of 0.662 and 0.665, respectively. This study established a genomic selection method for the Japanese flounder and for the first time applied this to E. tarda resistance breeding.

For a compact complex spin manifold M with a holomorphic isometric embedding into the complex projective space, the authors obtain the extrinsic estimates from above and below for eigenvalues of the Dirac operator, which depend on the data of an isometric embedding of M. Further, from the inequalities of eigenvalues, the gaps of the eigenvalues and the ratio of the eigenvalues are obtained.

Three‐dimensional global precipitation observation is crucial for understanding climate and weather dynamics. While spaceborne precipitation radars provide precise but limited observations, passive microwave imagers are available much more frequently. In this study, we propose a deep learning approach to reconstruct active radar observations using passive microwave radiances. We introduce the Hybrid Deep Neural Network (HDNN) model, which utilizes reflectivity profiles from the Dual‐frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) Core Observatory Satellite as the “target” and combines radiances from the GPM Microwave Imager (GMI) with supplementary reanalysis data to serve as the “features.” Results underscore the HDNN's exemplary performance, with a root mean square error below 4 dBZ across all altitude levels, and a consistent accuracy across different precipitation types. Its efficacy is further illustrated when applied to typhoon cases of Haishen and Khanun, emerging as a superior tool for capturing 3D structures of expansive precipitation systems. Plain Language Summary This research explores a novel way to improve our ability to observe precipitation from space. The study focuses on two instruments aboard a satellite: one that provides detailed 3D images of precipitation (DPR), and another (GMI) that covers a wider area but with less vertical resolution. The challenge is to combine the strengths of both instruments to get a more complete picture of precipitation. To address this, a HDNN was proposed to understand and interpret the data from both instruments. The detailed reflectivity profile from DPR was used as the label data, while the data from GMI with wider coverage along with additional information are used as the input. Evaluations based on validation set show that the model performed well, giving accurate and consistent measurements across different types of precipitation and at all altitudes. It also proved effective when applied to tropical cyclone cases, like Typhoons Haishen and Khanun, showcasing its potential for enhancing our understanding of such weather phenomena. Key Points Proposed deep learning method expands radar coverage from 245 to 885 km using passive microwave imager The model shows high precision across varied precipitation types and in real‐world applications on Typhoon Haishen (2020) and Typhoon Khanun (2023)

The small size of the Cas nuclease fused with various effector domains enables a broad range of function. Although there are several ways of reducing the size of the Cas nuclease complex, no efficient or generalizable method has been demonstrated to achieve protein miniaturization. In this study, we establish an Interaction, Dynamics and Conservation (IDC) strategy for protein miniaturization and generate five compact variants of Cas13 with full RNA binding and cleavage activity comparable the wild-type enzymes based on a combination of IDC strategy and AlphaFold2. In addition, we construct an RNA base editor, mini-Vx, and a single AAV (adeno-associated virus) carrying a mini-RfxCas13d and crRNA expression cassette, which individually shows efficient conversion rate and RNA-knockdown activity. In summary, these findings highlight a feasible strategy for generating downsized CRISPR/Cas13 systems based on structure predicted by AlphaFold2, enabling targeted degradation of RNAs and RNA editing for basic research and therapeutic applications. Small Cas enzymes are required for therapeutic use. Here the authors report an Interaction, Dynamics and Conservation (IDC) strategy for protein miniaturisation and use this to generate five compact variants of Cas13 based on a combination of IDC strategy and AlphaFold2.