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Background Patients with airway stenosis (AS) are associated with considerable morbidity and mortality after lung transplantation (LTx). This study aims to develop and validate machine learning (ML) models to predict AS requiring clinical intervention in patients after LTx. Methods Patients who underwent LTx between January 2017 and December 2019 were reviewed. The conventional logistic regression (LR) model was fitted by the independent risk factors which were determined by multivariate LR. The optimal ML model was determined based on 7 feature selection methods and 8 ML algorithms. Model performance was assessed by the area under the curve (AUC) and brier score, which were internally validated by the bootstrap method. Results A total of 381 LTx patients were included, and 40 (10.5%) patients developed AS. Multivariate analysis indicated that male, pulmonary arterial hypertension, and postoperative 6-min walking test were significantly associated with AS (all P  < 0.001). The conventional LR model showed performance with an AUC of 0.689 and brier score of 0.091. In total, 56 ML models were developed and the optimal ML model was the model fitted using a random forest algorithm with a determination coefficient feature selection method. The optimal model exhibited the highest AUC and brier score values of 0.760 (95% confidence interval [CI], 0.666–0.864) and 0.085 (95% CI, 0.058–0.117) among all ML models, which was superior to the conventional LR model. Conclusions The optimal ML model, which was developed by clinical characteristics, allows for the satisfactory prediction of AS in patients after LTx.

Four phenylfuropyridone racemates, (±)-tersones A-C and E (1–3, 5), one phenylpyridone racemate, (±)-tersone D (4), one new pyridine alkaloid, tersone F (6), single new phenylfuropyridone, tersone G (7) and two known analogs 8 and 9 were isolated from the deep-sea fungus Phomopsis tersa. Their structures and absolute configurations were characterized on the basis of comprehensive spectroscopic analyses, single-crystal X-ray diffraction experiments, and electronic circular dichroism (ECD) calculations. Moreover, compounds 1–9 were evaluated for in vitro antimicrobial and cytotoxic activity. Compounds 5b and 8b exhibited antibacterial activity against S. aureus with the MIC value of 31.5 μg/mL, while compound 5b showed cytoxic activities against SF-268, MCF-7, HepG-2 and A549 cell lines with IC50 values of 32.0, 29.5, 39.5 and 33.2 μM, respectively.

Five new chromone-derived polyketides phaseolorins A-F (1–5), together with nine known compounds, were isolated from the deep-sea derived fungus Diaporthe phaseolorum FS431. The structures of new compounds were determined by analysis of their NMR and high-resolution electrospray ionization mass spectroscopy (HRESIMS) spectroscopic data. The absolute configurations were confirmed by chemical transformations, extensively experimental electron capture detection (ECD) calculations, or X-ray crystallography. Among them, compound 2 represented the first example for a new family of chromone derivative possessing an unprecedented recombined five-member γ-lactone ring. Moreover, the new compounds (1–5) were evaluated for in vitro cytotoxic activities against a panel of human cancer cell lines.

Importance Although numerous prognostic factors have been found for patients after lung transplantation (LTx) over the years, an accurate prognostic tool for LTx recipients remains unavailable. Objective To develop and validate a prognostic model for predicting overall survival in patients after LTx using random survival forests (RSF), a machine learning algorithm. Design, Setting, and Participants This retrospective prognostic study included patients who underwent LTx between January 2017 and December 2020. The LTx recipients were randomly assigned to training and test sets in accordance with a ratio of 7:3. Feature selection was performed using variable importance with bootstrapping resampling. The prognostic model was fitted using the RSF algorithm, and a Cox regression model was set as a benchmark. The integrated area under the curve (iAUC) and integrated Brier score (iBS) were applied to assess model performance in the test set. Data were analyzed from January 2017 to December 2019. Main Outcomes And Measures Overall survival in patients after LTx. Results A total of 504 patients were eligible for this study, consisting of 353 patients in the training set (mean [SD] age, 55.03 [12.78] years; 235 [66.6%] male patients) and 151 patients in the test set (mean [SD] age, 56.79 [10.95] years; 99 [65.6%] male patients). According to the variable importance of each factor, 16 were selected for the final RSF model, and postoperative extracorporeal membrane oxygenation time was identified as the most valuable factor. The RSF model had excellent performance with an iAUC of 0.879 (95% CI, 0.832-0.921) and an iBS of 0.130 (95% CI, 0.106-0.154). The Cox regression model fitted by the same modeling factors to the RSF model was significantly inferior to the RSF model with an iAUC of 0.658 (95% CI, 0.572-0.747; P < .001) and an iBS of 0.205 (95% CI, 0.176-0.233; P < .001). According to the RSF model predictions, the patients after LTx were stratified into 2 prognostic groups displaying significant difference, with mean overall survival of 52.91 months (95% CI, 48.51-57.32) and 14.83 months (95% CI, 9.44-20.22; log-rankP < .001), respectively. Conclusions and relevance In this prognostic study, the findings first demonstrated that RSF could provide more accurate overall survival prediction and remarkable prognostic stratification than the Cox regression model for patients after LTx.

Background Thermostability is a fundamental property of proteins to maintain their biological functions. Predicting protein stability changes upon mutation is important for our understanding protein structure–function relationship, and is also of great interest in protein engineering and pharmaceutical design. Results Here we present mutDDG-SSM, a deep learning-based framework that uses the geometric representations encoded in protein structure to predict the mutation-induced protein stability changes. mutDDG-SSM consists of two parts: a graph attention network-based protein structural feature extractor that is trained with a self-supervised learning scheme using large-scale high-resolution protein structures, and an eXtreme Gradient Boosting model-based stability change predictor with an advantage of alleviating overfitting problem. The performance of mutDDG-SSM was tested on several widely-used independent datasets. Then, myoglobin and p53 were used as case studies to illustrate the effectiveness of the model in predicting protein stability changes upon mutations. Our results show that mutDDG-SSM achieved high performance in estimating the effects of mutations on protein stability. In addition, mutDDG-SSM exhibited good unbiasedness, where the prediction accuracy on the inverse mutations is as well as that on the direct mutations. Conclusion Meaningful features can be extracted from our pre-trained model to build downstream tasks and our model may serve as a valuable tool for protein engineering and drug design.

Large-scale populations in the world have been vaccinated with COVID-19 vaccines, however, breakthrough infections of SARS-CoV-2 are still growing rapidly due to the emergence of immune-evasive variants, especially Omicron. It is urgent to develop effective broad-spectrum vaccines to better control the pandemic of these variants. Here, we present a mosaic-type trimeric form of spike receptor-binding domain (mos-tri-RBD) as a broad-spectrum vaccine candidate, which carries the key mutations from Omicron and other circulating variants. Tests in rats showed that the designed mos-tri-RBD, whether used alone or as a booster shot, elicited potent cross-neutralizing antibodies against not only Omicron but also other immune-evasive variants. Neutralizing antibody ID50 titers induced by mos-tri-RBD were substantially higher than those elicited by homo-tri-RBD (containing homologous RBDs from prototype strain) or the BIBP inactivated COVID-19 vaccine (BBIBP-CorV). Our study indicates that mos-tri-RBD is highly immunogenic, which may serve as a broad-spectrum vaccine candidate in combating SARS-CoV-2 variants including Omicron. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues to pose a serious threat to public health and has so far resulted in over six million deaths worldwide. Mass vaccination programs have reduced the risk of serious illness and death in many people, but the virus continues to persist and circulate in communities across the globe. Furthermore, the current vaccines may be less effective against the new variants of the virus, such as Omicron and Delta, which are continually emerging and evolving. Therefore, it is urgent to develop effective vaccines that can provide broad protection against existing and future forms of SARS-CoV-2. There are several different types of SARS-CoV-2 vaccine, but they all work in a similar way. They contain molecules that induce immune responses in individuals to help the body recognize and more effectively fight SARS-CoV-2 if they happen to encounter it in the future. These immune responses may be so specific that new variants of a virus may not be recognized by them. Therefore, a commonly used strategy for producing vaccines with broad protection is to make multiple vaccines that each targets different variants and then mix them together before administering to patients. Here, Zhang et al. took a different approach by designing a new vaccine candidate against SARS-CoV2 that contained three different versions of part of a SARS-CoV2 protein – the so-called spike protein – all linked together as one molecule. The different versions of the spike protein fragment were designed to include key features of the fragments found in Omicron and several other SARS-CoV-2 variants. The experiments found that this candidate vaccine elicited a much higher immune response against Omicron and other SARS-CoV-2 variants in rats than an existing SARS-CoV-2 vaccine. It was also effective as a booster shot after a first vaccination with the existing SARS-CoV-2 vaccine. These findings demonstrate that the molecule developed by Zhang et al. induces potent and broad immune responses against different variants of SARS-CoV-2 including Omicron in rats. The next steps following on from this work are to evaluate the safety and immunogenicity of this vaccine candidate in clinical trials. In the future, it may be possible to use a similar approach to develop new broad-spectrum vaccines against other viruses.

The continuous emergence of SARS-CoV-2 variants highlights the need of developing vaccines with broad protection. Here, according to the immune-escape capability and evolutionary convergence, the representative SARS-CoV-2 strains carrying the hotspot mutations were selected. Then, guided by structural and computational analyses, we present a mutation-integrated trimeric form of spike receptor-binding domain (mutI-tri-RBD) as a broadly protective vaccine candidate, which combined heterologous RBDs from different representative strains into a hybrid immunogen and integrated immune-escape hotspots into a single antigen. When compared with a homo-tri-RBD vaccine candidate in the stage of phase II trial, of which all three RBDs are derived from the SARS-CoV-2 prototype strain, mutI-tri-RBD induced significantly higher neutralizing antibody titers against the Delta and Beta variants, and maintained a similar immune response against the prototype strain. Pseudo-virus neutralization assay demonstrated that mutI-tri-RBD also induced broadly strong neutralizing activities against all tested 23 SARS-CoV-2 variants. The in vivo protective capability of mutI-tri-RBD was further validated in hACE2-transgenic mice challenged by the live virus, and the results showed that mutI-tri-RBD provided potent protection not only against the SARS-CoV-2 prototype strain but also against the Delta and Beta variants.

Respiratory syncytial virus (RSV) is one of the most important pathogens causing respiratory tract infection in humans, especially in infants and the elderly. The identification and structural resolution of the potent neutralizing epitopes on RSV fusion (F) protein enable an “epitope-focused” vaccine design. However, the display of RSV F epitope II on the surface of the widely-used human hepatitis B virus core antigen (HBcAg) has failed to induce neutralizing antibody response in mice. Here, we used the hepadnavirus core protein (HcAg) from different mammalian hosts as scaffolds to construct chimeric virus-like particles (VLPs) presenting the RSV F epitope II. Mouse immunization showed that different HcAg-based chimeric VLPs elicited significantly different neutralizing antibody responses, among which the HcAg derived from roundleaf bat (RBHcAg) is the most immunogenic. Furthermore, RBHcAg was used as the scaffold platform to present multiple RSV F epitopes, and the immunogenicity was further improved in comparison to that displaying a single epitope II. The designed RBHcAg-based multiple-epitope-presenting VLP formulated with MF59-like adjuvant elicited a potent and balanced Th1/Th2 immune response, and offered substantial protection in mice against the challenge of live RSV A2 virus. The designed chimeric VLPs may serve as the potential starting point for developing epitope-focused vaccines against RSV. Our study also demonstrated that RBHcAg is an effective VLP carrier for presenting foreign epitopes, providing a promising platform for epitope-focused vaccine design.

The genomic sequence of a rice (Oryza sativa L.) glycine-rich protein (GRP) gene, designated Osgrp-2, has been previously determined (GenBank U40708). Primer extension analysis indicated that transcription starts 47 bp upstream of the translation start codon. To gain an insight into the transcriptional regulation of this gene, the 2,401-bp promoter sequence and a series of its 5′ deletions were transcriptionally fused to the β-glucuronidase (GUS) gene. GUS activity was subsequently assayed in a transient expression system of tobacco (Nicotiana tabacum L.) protoplasts, which revealed the presence of a positive regulatory region (-2290 to -1406) and two negative regulatory regions (-2401 to -2291 and -1405 to -1022) in the Osgrp-2 promoter for the promoter activity. The positive regulatory region displayed an enhancer-like activity when fused to the cauliflower mosaic virus (CaMV) 35S minimal promoter (-89 to +6) to drive GUS expression and assayed on tobacco leaves by the Agrobacterium-mediated transient expression technique (agroinfiltration). Histochemical staining for GUS activity on transgenic tobacco plants has further indicated a preferential expression in vascular tissues of stems and leaves conferred by the positive regulatory region. A 1,023-bp fragment of the Osgrp-2 promoter (-1021 to +2) fused with GUS was transformed into tobacco and proved to be capable of conferring vascular-specific expression. Further 5′ and 3′ deletion analysis of the 1,023-bp promoter revealed that a 99-bp fragment located from -497 to -399 contained cis-elements responsible for vascular-specific expression.

Porcine skin is frequently used as a substitute of human skin to cover large wounds in clinic practice of wound care. In our previous work, we found that transgenic expression of human cytoxicT-lymphocyte associated antigen4-immunoglobulin (hCTLA4Ig) in murine skin graft remarkably prolonged its survival in xenogeneic wounds without extensive immunosuppression in recipients, suggesting that transgenic hCTLA4Ig expression in skin graft may be an effective and safe method to prolong xenogeneic skin graft survival. In this work, using a transgene construct containing hCTLA4Ig coding sequence under the drive of human Keratine 14 (k14) promoter, hCTLA4Ig transgenic pigs were generated by somatic nuclear transfer. The derived transgenic pigs were healthy and exhibited no signs of susceptibility to infection. The hCTLA4Ig transgene was stably transmitted through germline over generations, and thereby a transgenic pig colony was established. In the derived transgenic pigs, hCTLA4Ig expression in skin was shown to be genetically stable over generations, and detected in heart, kidney and corneal as well as in skin. Transgenic hCTLA4Ig protein in pigs exhibited expected biological activity as it suppressed human lymphocyte proliferation in human mixed lymphocyte culture to extents comparable to those of commercially purchased purified hCTLA4Ig protein. In skin grafting from pigs to rats, transgenic porcine skin grafts exhibited remarkably prolonged survival compared to the wild-type skin grafts derived from the same pig strain (13.33 ± 3.64 vs. 6.25 ± 2.49 days, P  < 0.01), further indicating that the transgenic hCTLA4Ig protein was biologically active and capable of extending porcine skin graft survival in xenogeneic wounds. The transgenic pigs generated in this work can be used as a reproducible resource to provide porcine skin grafts with extended survival for wound coverage, and also as donors to investigate the impacts of hCTLA4Ig on xenotransplantation of other organs (heart, kidney and corneal) due to the ectopic transgenic hCTLA4Ig expression.