Broadly neutralizing antibodies derived from the earliest COVID-19 convalescents protect mice from SARS-CoV-2 variants challenge.

Coronavirus disease 2019 (COVID-19) was first reported three years ago, when a group of individuals were infected with the original SARS-CoV-2 strain, based on which vaccines were developed. Here, we develop six human monoclonal antibodies (mAbs) from two elite convalescents in Wuhan and show that these mAbs recognize diverse epitopes on the receptor binding domain (RBD) and can inhibit the infection of SARS-CoV-2 original strain and variants of concern (VOCs) to varying degrees, including Omicron strains XBB and XBB.1.5. Of these mAbs, the two most broadly and potently neutralizing mAbs (7B3 and 14B1) exhibit prophylactic activity against SARS-CoV-2 WT infection and therapeutic effects against SARS-CoV-2 Delta variant challenge in K18-hACE2 KI mice. Furthermore, post-exposure treatment with 7B3 protects mice from lethal Omicron variants infection. Cryo-EM analysis of the spike trimer complexed with 14B1 or 7B3 reveals that these two mAbs bind partially overlapped epitopes onto the RBD of the spike, and sterically disrupt the binding of human angiotensin-converting enzyme 2 (hACE2) to RBD. Our results suggest that mAbs with broadly neutralizing activity against different SARS-CoV-2 variants are present in COVID-19 convalescents infected by the ancestral SARS-CoV-2 strain, indicating that people can benefit from former infections or vaccines despite the extensive immune escape of SARS-CoV-2.

Sound Reception in the Yangtze Finless Porpoise and Its Extension to a Biomimetic Receptor.

Sound reception was investigated in the Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis) at its most sensitive frequency. The computed tomography scanning, sound speed, and density results were used to develop a three-dimensional numerical model of the porpoise sound-reception system. The acoustic fields showed that sounds can reach the ear complexes from various pathways, with distinct receptivity peaks on the forward, left, and right sides. Reception peaks were identified on the ipsilateral sides of the respective ears and found on the opposite side of the ear complexes. These opposite maxima corresponded to subsidiary hearing pathways in the whole head, especially the lower head, suggesting the complexity of the sound-reception mechanism in the porpoise. The main and subsidiary sound-reception pathways likely render the whole head a spatial receptor. The low-speed and -density mandibular fats, compared to other acoustic structures, are significant energy enhancers for strengthening forward sound reception. Based on the porpoise reception model, a biomimetic receptor was developed to achieve directional reception, and in parallel to the mandibular fats, the silicon material of low speed and density can significantly improve forward reception. This bioinspired and biomimetic model can bridge the gap between animal sonar and artificial sound control systems, which presents potential to be exploited in manmade sonar.

Call properties of the large yellow croaker (Larimichthys crocea) during reproduction with insight into directivity.

The investigation of the large yellow croaker (Larimichthys crocea) deserves more attention due to its high commercial value as an important aquaculture fish species. This study was initiated by deploying a passive acoustic monitoring device to record the calls from the L. crocea during the spawning process in an aquaculture facility. The subsequent analysis suggested the croakers produced at least two types of calls with considerable energy distributed up to 1000 Hz. The acoustic data and the computed tomography scanning of an adult croaker were used to develop a numerical model to address the directivity of the calls at frequencies up to 1000 Hz. The radiation patterns at all frequencies were assigned with respective weights and then combined to estimate an overall acoustic radiation pattern for both types of the calls. The backward transmission was greater for both types of calls by 1.85 dB on average. The reduction of size by 20% in the swim bladder resulted in a stronger sidelobe in the frontal direction, indicating its influence on call directivity. These results provided information on the directivity of the croaker calls and understanding of fish acoustics.

A DNA origami nanostructure embedded with NQO1-activated prodrugs for precision drug delivery.

A rectangle DNA origami nanostructure equipped with doxorubicin-derived prodrugs targeting a tumor cell-specific enzyme (NQO1) is constructed. Combining the high prodrug payload of DNA origami and NQO1-activated chemotherapy, this nanosystem presents therapeutic selectivity for NQO1-overexpressing MCF-7 cells over healthy L02 cells, offering a potent strategy for precision cancer therapy.

Lyophilized mRNA-lipid nanoparticle vaccines with long-term stability and high antigenicity against SARS-CoV-2.

Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, most current mRNA delivery platforms need to be stored at -20 °C or -70 °C due to their poor stability, which severely restricts their availability. Herein, we develop a lyophilization technique to prepare SARS-CoV-2 mRNA-lipid nanoparticle vaccines with long-term thermostability. The physiochemical properties and bioactivities of lyophilized vaccines showed no change at 25 °C over 6 months, and the lyophilized SARS-CoV-2 mRNA vaccines could elicit potent humoral and cellular immunity whether in mice, rabbits, or rhesus macaques. Furthermore, in the human trial, administration of lyophilized Omicron mRNA vaccine as a booster shot also engendered strong immunity without severe adverse events, where the titers of neutralizing antibodies against Omicron BA.1/BA.2/BA.4 were increased by at least 253-fold after a booster shot following two doses of the commercial inactivated vaccine, CoronaVac. This lyophilization platform overcomes the instability of mRNA vaccines without affecting their bioactivity and significantly improves their accessibility, particularly in remote regions.

Joint optic disk and cup segmentation for glaucoma screening using a region-based deep learning network.

OBJECTIVES: To develop and validate an end-to-end region-based deep convolutional neural network (R-DCNN) to jointly segment the optic disc (OD) and optic cup (OC) in retinal fundus images for precise cup-to-disc ratio (CDR) measurement and glaucoma screening. METHODS: In total, 2440 retinal fundus images were retrospectively obtained from 2033 participants. An R-DCNN was presented for joint OD and OC segmentation, where the OD and OC segmentation problems were formulated into object detection problems. We compared R-DCNN's segmentation performance on our in-house dataset with that of four ophthalmologists while performing quantitative, qualitative and generalization analyses on the publicly available both DRISHIT-GS and RIM-ONE v3 datasets. The Dice similarity coefficient (DC), Jaccard coefficient (JC), overlapping error (E), sensitivity (SE), specificity (SP) and area under the curve (AUC) were measured. RESULTS: On our in-house dataset, the proposed model achieved a 98.51% DC and a 97.07% JC for OD segmentation, and a 97.63% DC and a 95.39% JC for OC segmentation, achieving a performance level comparable to that of the ophthalmologists. On the DRISHTI-GS dataset, our approach achieved 97.23% and 94.17% results in DC and JC results for OD segmentation, respectively, while it achieved a 94.56% DC and an 89.92% JC for OC segmentation. Additionally, on the RIM-ONE v3 dataset, our model generated DC and JC values of 96.89% and 91.32% on the OD segmentation task, respectively, whereas the DC and JC values acquired for OC segmentation were 88.94% and 78.21%, respectively. CONCLUSION: The proposed approach achieved very encouraging performance on the OD and OC segmentation tasks, as well as in glaucoma screening. It has the potential to serve as a useful tool for computer-assisted glaucoma screening.

Automatic segmentation of multitype retinal fluid from optical coherence tomography images using semisupervised deep learning network.

BACKGROUND/AIMS: To develop and validate a deep learning model for automated segmentation of multitype retinal fluid using optical coherence tomography (OCT) images. METHODS: We retrospectively collected a total of 2814 completely anonymised OCT images with subretinal fluid (SRF) and intraretinal fluid (IRF) from 141 patients between July 2018 and June 2020, constituting our in-house retinal OCT dataset. On this dataset, we developed a novel semisupervised retinal fluid segmentation deep network (Ref-Net) to automatically identify SRF and IRF in a coarse-to-refine fashion. We performed quantitative and qualitative analyses on the model's performance while verifying its generalisation ability by using our in-house retinal OCT dataset for training and an unseen Kermany dataset for testing. We also determined the importance of major components in the semisupervised Ref-Net through extensive ablation. The main outcome measures were Dice similarity coefficient (Dice), sensitivity (Sen), specificity (Spe) and mean absolute error (MAE). RESULTS: Our model trained on a handful of labelled OCT images manifested higher performance (Dice: 81.2%, Sen: 87.3%, Spe: 98.8% and MAE: 1.1% for SRF; Dice: 78.0%, Sen: 83.6%, Spe: 99.3% and MAE: 0.5% for IRF) over most cutting-edge segmentation models. It obtained expert-level performance with only 80 labelled OCT images and even exceeded two out of three ophthalmologists with 160 labelled OCT images. Its satisfactory generalisation capability across an unseen dataset was also demonstrated. CONCLUSION: The semisupervised Ref-Net required only la few labelled OCT images to generate outstanding performance in automate segmentation of multitype retinal fluid, which has the potential for providing assistance for clinicians in the management of ocular disease.

Nutrient variation induced by rodent disturbance in Haloxylon ammodendron as a target transfer strategy.

Nutrients form a link between herbivores and plant. This study explored the physiological and ecological response mechanism of Haloxylon ammodendron population to rodent disturbance in Gurbantunggut Desert from the perspective of nutrient cycle. Through field investigation, we quantified rodent disturbance intensity (DI) to H. ammodendron and analyzed the ecological response mechanism of H. ammodendron population to rodent disturbance from the perspective of plant and soil nutrient cycling and changes. The results indicated that moderate rodent DI (number of effective burrows = 3-6) was the maximum limit that can be tolerated by H. ammodendron; the threshold for optimal H. ammodendron response to rodent disturbance was mild (number of burrows = 1-3). Meanwhile, the rodent disturbance caused significant nutrient enrichment (e.g., organic carbon, available phosphorus, and available potassium) in the deeper soil (at 20-40 and 40-60 cm depth) and significantly reduced the soil total salt content (p < .05). Furthermore, as the DI increased, the branches of H. ammodendron showed significantly increased soluble total sugar, crude fiber, and total nitrogen contents (p < .05) but significantly decreased crude fat and crude protein contents (p < .05); these results are related to the nutritional target transfer strategy evolved by H. ammodendron for long-term resistance to rodent disturbance. The current study clarified the optimal disturbance model for mutually beneficial H. ammodendron-great gerbil relationship, on the basis of which the ecological response mechanism of H. ammodendron population to rodent disturbance in deserts was illustrated. The current study provides a scientific basis for the protection mechanisms of desert plants to rodent disturbance.