The role of exosomes in cancer-related programmed cell death.

Cancer arises from the growth and division of uncontrolled erroneous cells. Programmed cell death (PCD), or regulated cell death (RCD), includes natural processes that eliminate damaged or abnormal cells. Dysregulation of PCD is a hallmark of cancer, as cancer cells often evade cell death and continue to proliferate. Exosomes nanoscale extracellular vesicles secreted by different types of cells carrying a variety of molecules, including nucleic acids, proteins, and lipids, to have indispensable role in the communication between cells, and can influence various cellular processes, including PCD. Exosomes have been shown to modulate PCD in cancer cells by transferring pro- or antideath molecules to neighboring cells. Additionally, exosomes can facilitate the spread of PCD to surrounding cancer cells, making them promising in the treatment of various cancers. The exosomes' diagnostic potential in cancer is also an active area of research. Exosomes can be isolated from a wide range of bodily fluids and tissues, such as blood and urine, and can provide a noninvasive way to monitor cancer progression and treatment response. Furthermore, exosomes have also been employed as a delivery system for therapeutic agents. By engineering exosomes to carry drugs or other therapeutic molecules, they can be targeted specifically to cancer cells, reducing toxicity to healthy tissues. Here, we discussed exosomes in the diagnosis and prevention of cancers, tumor immunotherapy, and drug delivery, as well as in different types of PCD.

PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.

PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a long period of time. Until October 2020, a novel grading system was proposed to quantify the whole landscape of histologic subtypes and proportions of pulmonary adenocarcinomas. This study aims to develop a deep learning grading signature (DLGS) based on positron emission tomography/computed tomography (PET/CT) to personalize surgical treatments for clinical stage I invasive lung adenocarcinoma and explore the biologic basis under its prediction. METHODS: A total of 2638 patients with clinical stage I invasive lung adenocarcinoma from 4 medical centers were retrospectively included to construct and validate the DLGS. The predictive performance of the DLGS was evaluated by the area under the receiver operating characteristic curve (AUC), its potential to optimize surgical treatments was investigated via survival analyses in risk groups defined by the DLGS, and its biological basis was explored by comparing histologic patterns, genotypic alternations, genetic pathways, and infiltration of immune cells in microenvironments between risk groups. RESULTS: The DLGS to predict grade 3 achieved AUCs of 0.862, 0.844, and 0.851 in the validation set (n = 497), external cohort (n = 382), and prospective cohort (n = 600), respectively, which were significantly better than 0.814, 0.810, and 0.806 of the PET model, 0.813, 0.795, and 0.824 of the CT model, and 0.762, 0.734, and 0.751 of the clinical model. Additionally, for DLGS-defined high-risk population, lobectomy yielded an improved prognosis compared to sublobectomy p = 0.085 for overall survival [OS] and p = 0.038 for recurrence-free survival [RFS]) and systematic nodal dissection conferred a superior prognosis to limited nodal dissection (p = 0.001 for OS and p = 0.041 for RFS). CONCLUSION: The DLGS harbors the potential to predict the histologic grade and personalize the surgical treatments for clinical stage I invasive lung adenocarcinoma. Its applicability to other territories should be further validated by a larger international study.

Spin coated ultrathin PEDOT:PSS/SWCNT film with high electronic conductivity.

Conductive Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) has been extensively used as non-metallic electrodes. However, the relatively low electrical conductivity of pristine PEDOT:PSS film restricts its further application. Although doping high content conductive filler or increasing the film thickness are effective for enhancing the electrical property, the transparency is sacrificed, which limits the application of PEDOT:PSS films. In this study, preparing PEDOT:PSS composite film with highly conductive and transparent property was the primary purpose. To achieve this goal, single-walled carbon nanotubes (SWCNTs) and dimethyl sulfoxide (DMSO) was chosen to composite with PEDOT:PSS. The spin-coated SWCNT/PEDOT:PSS composite film exhibited excellent electrical conductivity and transparency. The electrical conductivity of composite film with desired transmittance property (78%) reached the highest value (1060.96 S cm-1) at the SWCNTs content was 6 wt%. Under the modification process applied in this work, the non-conductive PSS was partially removed by incorporated DMSO and SWCNTs. Then, the molecular chains of PEDOT stretched and adsorbed onto the surface of SWCNTs, forming a highly efficient three-dimensional conductive structure, which contributed to the enhancement of electrical conductivity and transparency. Additionally, the spin-coating process allowed for the reduction of film thickness, ensuring better transparency. This research contributed to expanding the further applications of PEDOT:PSS films in high-performance transparent film electrodes.

Increased prevalence and stable clustering rate of HIV-1 transmitted drug resistance strains after 'treat-all' in a megacity of China.

OBJECTIVES: The 'treat-all' strategy was implemented in Shenzhen, China in 2016. The effect of this extensive treatment on transmitted drug resistance (TDR) of HIV is unclear. METHODS: TDR analysis was performed, based on the partial HIV-1 pol gene obtained from the newly reported HIV-1 positive cases from 2011 to 2019 in Shenzhen, China. The HIV-1 molecular transmission networks were inferred to analyse the spread of TDR. Logistic regression was used to identify the potential risk factors with TDR mutations (TDRMs) to cluster. RESULTS: A total of 12 320 partial pol sequences were included in this study. The prevalence of TDR was 2.95% (363/12 320), which increased from 2.57% to 3.52% after 'treat-all'. The TDR prevalence was increased in populations with the characteristics of CRF07_BC, being single, educated to junior college level and above, MSM and male. The sensitivities of viruses to six antiretroviral drugs were decreased. The clustering rate of TDRMs remained stable, and the sequences in the three drug resistance transmission clusters (DRTCs) were mainly found during 2011-16. CRF07_BC and CRF55_01B were the factors associated with TDRMs clustering in the networks. CONCLUSIONS: The 'treat-all' strategy might have contributed to a small increase in TDR, while most of the TDRMs were distributed sporadically, which implies that the 'treat-all' strategy is helpful for the control of TDR in high-risk populations.

Natural products in digestive tract tumors metabolism: Functional and application prospects.

Digestive tract diseases are presently the hotspot of clinical diagnosis and treatment, and the incidence of digestive tract tumor is increasing annually. Surgery remains the main therapeutic schedule for digestive tract tumor. Though benefits were brought by neoadjuvant chemotherapy, a part of patients lose the chance of surgery because of late detection or inappropriate intervention. Therefore, the treatment of inoperable patients has become an urgent need. At the same time, tumor metabolism is an extremely complex and diverse process. Natural products are confirmed effective to inhibit the development of tumors in vitro and in vitro. There are many kinds of natural products and their functions remain not clear. However, some natural products such as polyphenols have been proven to have definite anti-cancer effects, and some terpenoids have definite anti-inflammatory, anti-ulcer, anti-tumor, and other effects. Therefore, the anti-tumor characteristics of natural products should arouse our high attention. Although there are many obstacles to study the activities of natural products in tumor, including the difficulty in detection or distinguishing each component due to their low levels in tumor tissue, etc., the emergence of highly sensitive and locatable spatial metabolomics make the research and application of natural products a big step forward. In this review, natural products such as phenols, terpenoids and biotinoids were summarized to further discuss the development and therapeutic properties of natural metabolites on digestive tract tumors.

Phenolic metabolites as therapeutic in inflammation and neoplasms: Molecular pathways explaining their efficacy.

Polyphenols, also known as phenolic compounds, are chemical substances containing aromatic rings as well as at least two hydroxyl groups. Natural phenolic compounds exist widely in plants, which protect plants from ultraviolet radiation and other insults. Phenolic compounds have superior pharmacological and nutritional properties (antimicrobial, antibacterial, antiviral, anti-sclerosis, antioxidant, and anti-inflammatory activities), which have been paid more and more attention by the scientific community. Phenols can protect key cellular components from reactive free radical damage, which is mainly due to their property to activate antioxidant enzymes and alleviate oxidative stress and inflammation. It can also inhibit or isolate reactive oxygen species and transfer electrons to free radicals, thereby avoiding cell damage. It has a regulatory role in glucose metabolism, which has a promising prospect in the prevention and intervention of diabetes. It also prevents cardiovascular disease by regulating blood pressure and blood lipids. Polyphenols can inhibit cell proliferation by affecting Erk1/2, CDK, and PI3K/Akt signaling pathways. Polyphenols can function as enhancers of intrinsic defense systems, including superoxide dismutase (SOD) and glutathione peroxidase (GPX). Simultaneously, they can modulate multiple proteins and transcription factors, making them promising candidates in the investigation of anti-cancer medications. This review focuses on multiple aspects of phenolic substances, including their natural origins, production process, disinfection activity, oxidative and anti-inflammatory functions, and the effects of different phenolic substances on tumors.

Ileum tissue single-cell mRNA sequencing elucidates the cellular architecture of pathophysiological changes associated with weaning in piglets.

BACKGROUND: In mammals, transitioning from sole milk uptake to the intake of solid feed results in dramatic developmental changes in intestinal function and immunological status. In fact, weaning stress is often accompanied by intestinal inflammatory processes. To develop effective intervention strategies, it is necessary to characterize the developmental pattern and immune response that occurs on weaning, as we have done in this study for piglets. RESULTS: To comprehensively delineate cell heterogeneity in ileum tissues and the underlying mechanisms in weaning-induced intestinal inflammation of piglets, we have analyzed the transcriptomes of 42,149 cells from ileum mucosa of normally suckling and post-weaned piglets. There were 31 cell subtypes including epithelial, stromal, and immune cells. A bifurcating trajectory was inferred to separate secretory and absorptive lineages. Integrated cross-species datasets showed well-conserved cellular architectures and transcription signatures between human and pig. Comparative analyses of cellular components, cell-cell communications, and molecular states revealed that T cell subpopulations were significantly altered in weaned piglets. We found that T helper (Th) 17 functional plasticity across changes in the cytokine milieu and the enrichment of granzyme B (GZMB)-expressing cytotoxic T cells potentially exacerbate mucosal inflammation via mitochondrial dysfunction in epithelial cells. CONCLUSIONS: Our work has elucidated the single-cell molecular characteristics of the piglet ileum before and after weaning. We have provided an atlas that portrays the landscape of the intestinal pathophysiological inflammatory process associated with weaning, finding a level of conservation between human and pig that support the use of piglets as a model for human infants.

Rapid Identification by Resequencing-Based QTL Mapping of a Novel Allele RGA1-FH Decreasing Grain Length in a Rice Restorer Line 'Fuhui212'.

Grain size is one of the most frequently selected traits during domestication and modern breeding. The continued discovery and characterization of new genes and alleles in controlling grain size are important in safeguarding the food supply for the world's growing population. Previously, a small grain size was observed in a rice restorer line 'Fuhui212', while the underlying genetic factors controlling this trait were unknown. In this study, by combining QTL mapping, variant effect prediction, and complementation experiments, we recovered a novel allele RGA1-FH that explains most of the phenotypic changes. The RGA1-FH allele contains an A-to-T splicing site variant that disrupts the normal function of RGA1. While population analysis suggests extremely strong artificial selection in maintaining a functional allele of RGA1, our study is the first, to the best of our knowledge, to prove that a dysfunctional RGA1 allele can also be beneficial in real agricultural production. Future breeding programs would benefit from paying more attention to the rational utilization of those overlooked 'unfavored' alleles.

A design concept of big data analytics model for managers in hospitality industries.

The hospitality and tourism sector has long played a significant role in Australia's economy, especially in regional areas. Due to the onslaught of COVID-19, numerous businesses have experienced lockdowns, restrictions, and closures due to the fact that people's activity in restaurants, shopping centers, and recreational destinations was restricted, and many other places went into hibernation. After about 2 years since the outbreak, businesses in this sector are gradually starting to reopen and revitalize themselves, but in order to have better decision support about the future of this sector, thus being able to plan, businesses are suffering from an effective analytics solution due to the lack of broken data trends. Starting from fresh day-to-day real-time big data, the study aims to develop a new data analytics model, adopting the design science research methodology, which can provide invaluable options and techniques to make prediction easier from immediate past datasets. This study introduces an innovative design artifact as a big data solution for hospitality managers to utilize analytics for predictive strategic decision-making in post-COVID situation. The artifact can also be generalized for other sectors with tailoring aspects which are subject to further studies. The proposed artifact is then compared with other design artifacts related to big data solutions where it outperforms them in terms of comprehensiveness. The proposed artifact also shows promises for primarily available UGC in managers' decision support aids.

Adoption of AI in response to COVID-19-a configurational perspective.

Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology-organization-environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm's competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm's competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm's competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages.

Base-Modulated 1,3-Regio- and Stereoselective Carboboration of Cyclohexenes.

While chain-walking stimulates wide interest in both polymerization and organic synthesis, site- and stereoselective control of chain-walking on rings is still a challenging task in the realm of organometallic catalysis. Inspired by a controllable chain-walking on cyclohexane rings in olefin polymerization, we have developed a set of chain-walking carboborations of cyclohexenes based on nickel catalysis. Different from the 1,4-trans-selectivity disclosed in polymer science, a high level of 1,3-regio- and cis-stereoselectivity is obtained in our reactions. Mechanistically, we discovery that the base affects the reduction ability of B2 pin2 and different bases lead to different catalytic cycles and different regioselective products (1,2- Vs 1,3-addition). This study provides a concise and modular method for the synthesis of 1,3-disubstituted cyclohexylboron compounds. The incorporation of a readily modifiable boronate group greatly enhances the value of this method, the synthetic potential of which was highlighted by the synthesis of a series of high-valued commercial chemicals and pharmaceutically interesting molecules.

Radiomics for Survival Risk Stratification of Clinical and Pathologic Stage IA Pure-Solid Non-Small Cell Lung Cancer.

Background Radiomics-based biomarkers enable the prognostication of resected non-small cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA pure-solid tumors requires further determination. Purpose To construct an efficient radiomics signature for survival risk stratification personalized for patients with clinical stage and pathologic stage IA pure-solid NSCLC. Materials and Methods In this retrospective study, six radiomics signatures were constructed for patients with stage IA pure-solid NSCLC who underwent resection between January 2011 and December 2013 at authors' institution and were tested in the radiogenomics data set. The radiomics features were extracted from the intratumoral two-dimensional region, three-dimensional volume, and peritumoral area using PyRadiomics. The discriminative abilities of the signatures were quantified using the area under the time-dependent receiver operating characteristic curve (AUC), and the optimal signature was selected for patient stratification. Results The study included 592 patients with stage IA pure-solid NSCLC (median age, 61 years; interquartile range, 55-66 years; 269 women) for radiomics analysis: 381 patients for training, 163 for internal validation, and 48 for external validation. The radiomics signature combining three-region features yielded the highest 3- and 5-year AUCs of 0.77 and 0.78, respectively, in the internal validation set and 0.76 and 0.75, respectively, in the external validation set. Multivariable analysis suggested that the radiomics signature remained an independent prognostic factor (hazard ratio, 6.2; 95% CI: 3.5, 11.0; P < .001) and improved the discriminative ability and clinical usefulness of conventional clinical predictors. Conclusion The radiomics signature with multiregional features helped stratify the survival risk of patients with clinical stage and pathologic stage IA pure-solid non-small cell lung cancer. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Hsu and Sohn in this issue.

Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non-small cell lung cancer (NSCLC). Purpose To develop a deep learning signature for N2 metastasis prediction and prognosis stratification in clinical stage I NSCLC. Materials and Methods In this retrospective study conducted from May 2020 to October 2020 in a population with clinical stage I NSCLC, an internal cohort was adopted to establish a deep learning signature. Subsequently, the predictive efficacy and biologic basis of the proposed signature were investigated in an external cohort. A multicenter diagnostic trial (registration number: ChiCTR2000041310) was also performed to evaluate its clinical utility. Finally, on the basis of the N2 risk scores, the instructive significance of the signature in prognostic stratification was explored. The diagnostic efficiency was quantified with the area under the receiver operating characteristic curve (AUC), and the survival outcomes were assessed using the Cox proportional hazards model. Results A total of 3096 patients (mean age ± standard deviation, 60 years ± 9; 1703 men) were included in the study. The proposed signature achieved AUCs of 0.82, 0.81, and 0.81 in an internal test set (n = 266), external test cohort (n = 133), and prospective test cohort (n = 300), respectively. In addition, higher deep learning scores were associated with a lower frequency of EGFR mutation (P = .04), higher rate of ALK fusion (P = .02), and more activation of pathways of tumor proliferation (P < .001). Furthermore, in the internal test set and external cohort, higher deep learning scores were predictive of poorer overall survival (adjusted hazard ratio, 2.9; 95% CI: 1.2, 6.9; P = .02) and recurrence-free survival (adjusted hazard ratio, 3.2; 95% CI: 1.4, 7.4; P = .007). Conclusion The deep learning signature could accurately predict N2 disease and stratify prognosis in clinical stage I non-small cell lung cancer. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Park and Lee in this issue.

Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study.

Our aim was to validate and analyze the prognostic impact of the novel International Association for the Study of Lung Cancer (IASLC) Pathology Committee grading system for invasive pulmonary adenocarcinomas (IPAs) in Chinese patients and to evaluate its utility in predicting a survival benefit from adjuvant chemotherapy (ACT). In this multicenter, retrospective, cohort study, we included 926 Chinese patients with completely resected stage I IPAs and classified them into three groups (Grade 1, n = 119; Grade 2, n = 431; Grade 3, n = 376) according to the new grading system proposed by the IASLC. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method, and prognostic factors were assessed using univariable and multivariable Cox proportional hazards models. All included cohorts were well stratified in terms of RFS and OS by the novel grading system. Furthermore, the proposed grading system was found to be independently associated with recurrence and death in the multivariable analysis. Among patients with stage IB IPA (N = 490), the proposed grading system identified patients who could benefit from ACT but who were undergraded by the adenocarcinoma (ADC) classification. The novel grading system not only demonstrated prognostic significance in stage I IPA in a multicenter Chinese cohort but also offered clinical value for directing therapeutic decisions regarding adjuvant chemotherapy.

Lung cancer with PET/CT-defined occult nodal metastasis yields favourable prognosis and benefits from adjuvant therapy: a multicentre study.

PURPOSE: To investigate the surgical prognosis and efficacy of adjuvant therapy in non-small cell lung cancer (NSCLC) with occult lymph node metastasis (ONM) defined by positron emission tomography/computed tomography (PET/CT). METHODS: A total of 3537 NSCLC patients receiving surgical resection were included in this study. The prognosis between patients with ONM and evident nodal metastasis, ONM patients with and without adjuvant therapy was compared, respectively. RESULTS: ONM was associated with significantly better prognosis than evident nodal metastasis whether for patients with N1 (5-year OS: 56.8% versus 52.3%, adjusted p value = 0.267; 5-year RFS: 44.7% versus 33.2%, adjusted p value = 0.031) or N2 metastasis (5-year OS: 42.8% versus 32.3%, adjusted p value = 0.010; 5-year RFS: 31.3% versus 21.6%, adjusted p value = 0.025). In ONM population, patients receiving adjuvant therapy yielded better prognosis comparing to those without adjuvant therapy (5-year OS: 50.1% versus 33.5%, adjusted p value < 0.001; 5-year RFS: 38.4% versus 22.1%, adjusted p value < 0.001). CONCLUSIONS: ONM defined by PET/CT identifies a unique clinical subtype of lung cancer, ONM is a favorable prognostic factor whether for pathological N1 or N2 NSCLC and adjuvant therapy could provide additional survival benefits for ONM patients.

Global Incidence, Progression, and Risk Factors of Age-Related Macular Degeneration and Projection of Disease Statistics in 30 Years: A Modeling Study.

OBJECTIVE: Age-related macular degeneration(AMD) has become a major cause of visual impairment worldwide, especially in the elderly. Estimates of incidence, progression rates, and risk factors of AMD vary among studies, complicating the understanding of its epidemiology. METHODS: For this systematic review and meta-analysis, literature published up to March 1, 2021, was searched in both English and Chinese databases. Hierarchical Bayesian approaches were used to estimate pooled incidence, progression, and 95% credible intervals (CrIs). RESULTS: Thirty studies were included. The pooled annual early and late AMD incidence rates were 1.59 (95% CrI: 1.18-2.11) and 0.23 (95% CrI: 0.14-0.34) per 100 person-years, respectively. The annual progression rate of AMD was 5.5 (95% CrI: 2.3-8.8) per 100 person-years. Smoking was an independent risk factor for both early and late AMD, whereas age, high-density lipoprotein cholesterol, and alcohol consumption were risk factors for early AMD incidence only. The projected number of new cases of early and late AMD in 2050 would be 39.05 million (95% CrI: 23.12-63.57) and 6.41 million (95% CrI: 3.37-13.22), respectively. CONCLUSION: The prediction the number of new cases of AMD is not equal across the globe. Our findings indicate the need for more rigorous control and prevention measures in AMD focus on its risk factors for early intervention. The epidemiological estimates reported in this study could inform to identify effective strategies for preventing AMD worldwide.

Sustainable finance and renewable energy: Promoters of carbon neutrality in the United States.

This investigation explores whether sustainable finance and renewable energy could facilitate U.S. carbon neutrality. We perform the time-varying parameter-stochastic volatility-vector auto-regression (TVP-SV-VAR) model to obtain the changing relations among U.S. sustainable finance (SF), renewable energy (RE) and carbon dioxide emission (CO2). The empirical outcomes reveal a short-term negative effect from RE to CO2, indicating that renewable energy consumption could promote U.S. carbon neutrality. This effect is asymmetrical, and it could be observed that RE increase has a greater effect on CO2 than RE reduction. Also, the development of sustainable finance could facilitate U.S. carbon neutrality, and the direct impact is longer and more significant than RE, but the indirect effect of SF on CO2 by influencing RE is hysteretic. Besides, the asymmetric effect reveals that the negative direct impact of SF increase on CO2 is smaller than SF reduction, and the latter's indirect effect is more rapid than the former. Against the backdrop of global warming and frequent extreme weather, the above conclusions have meaningful practical applications for the U.S. to achieve carbon neutrality targets through developing sustainable finance and renewable energy.

Multi-omics analyses on Kandelia obovata reveal its response to transplanting and genetic differentiation among populations.

BACKGROUND: Restoration through planting is the dominant strategy to conserve mangrove ecosystems. However, many of the plantations fail to survive. Site and seeding selection matters for planting. The process of afforestation, where individuals were planted in a novel environment, is essentially human-controlled transplanting events. Trying to deepen and expand the understanding of the effects of transplanting on plants, we have performed a seven-year-long reciprocal transplant experiment on Kandelia obovata along a latitudinal gradient. RESULTS: Combined phenotypic analyses and next-generation sequencing, we found phenotypic discrepancies among individuals from different populations in the common garden and genetic differentiation among populations. The central population with abundant genetic diversity and high phenotypic plasticity had a wide plantable range. But its biomass was reduced after being transferred to other latitudes. The suppressed expression of lignin biosynthesis genes revealed by RNA-seq was responsible for the biomass reduction. Moreover, using whole-genome bisulfite sequencing, we observed modification of DNA methylation in MADS-box genes that involved in the regulation of flowering time, which might contribute to the adaptation to new environments. CONCLUSIONS: Taking advantage of classical ecological experiments as well as multi-omics analyses, our work observed morphology differences and genetic differentiation among different populations of K. obovata, offering scientific advice for the development of restoration strategy with long-term efficacy, also explored phenotypic, transcript, and epigenetic responses of plants to transplanting events between latitudes.

A newly identified linear epitope on non-RBD region of SARS-CoV-2 spike protein improves the serological detection rate of COVID-19 patients.

BACKGROUND: Serological test is helpful in confirming and tracking infectious diseases in large population with the advantage of fast and convenience. Using the specific epitope peptides identified from the whole antigen as the detection antigen is sensitive and relatively economical. The development of epitope peptide-based detection kits for COVID-19 patients requires comprehensive information about epitope peptides. But the data on B cell epitope of SARS-CoV-2 spike protein is still limited. More importantly, there is a lack of serological data on the peptides in the population. In this study, we aimed to identify the B cell epitope peptides of spike protein and detect the reactivity in serum samples, for further providing data support for their subsequent serological applications. RESULTS: Two B cell linear epitopes, P104 and P82, located in non-RBD region of SARS-CoV-2 S protein were identified by indirect ELISA screening of an overlapping peptide library of the S protein with COVID-19 patients' convalescent serum. And the peptides were verified by testing with 165 serum samples. P104 has not been reported previously; P82 is contained in peptide S21P2 reported before. The positive reaction rates of epitope peptides S14P5 and S21P2, the two non-RBD region epitopes identified by Poh et al., and P82 and P104 were 77.0%, 73.9%, 61.2% and 30.3%, respectively, for 165 convalescent sera, including 30 asymptomatic patients. Although P104 had the lowest positive rate for total patients (30.3%), it exhibited slight advantage for detection of asymptomatic infections (36.7%). Combination of epitopes significantly improved the positive reaction rate. Among all combination patterns, (S14P5 + S21P2 + P104) pattern exhibited the highest positive reaction rate for all patients (92.7%), as well as for asymptomatic infections (86.7%), confirming the feasibility of P104 as supplementary antigen for serological detection. In addition, we analyzed the correlation between epitopes with neutralizing antibody, but only S14P5 had a medium positive correlation with neutralizing antibody titre (rs = 0.510, P < 0.01). CONCLUSION: Our research proved that epitopes on non-RBD region are of value in serological detection especially when combination more than one epitope, thus providing serological reaction information about the four epitopes, which has valuable references for their usage.

Prevention of non-recurrent laryngeal nerve injury in robotic thyroidectomy: imaging and technique.

INTRODUCTION: The aim of this report was to summarize observations, evaluate the feasibility, provide detailed information concerning proper techniques, and address limitations for non-recurrent laryngeal nerve (NRLN) dissection and release during the robotic bilateral axillo-breast approach (BABA) for thyroidectomy. MATERIALS AND METHODS: The BABA approach was used in two cases of thyroidectomy in the setting of NRLN. Preoperative CT imaging findings suggesting the aberrant anatomy are reviewed and technical planning, inclusive of intraoperative nerve monitoring, was employed. Intraoperative videos with narrative discussion of technique for safe dissection are provided, along with supplementary video of additional technical guidance. RESULTS: In both cases, the NRLNs were identified, dissected, and preserved. We dissected the proximal segment of each NRLN to its origin. We determined that the use of only the NRLN proximal to distal robotic dissection jeopardized the nerve. The BABA approach with the Type I NRLN is similar to the dissection of the recurrent laryngeal nerve (RLN) in transoral thyroidectomy. Due to interference with endoscopic viewing caused by the thyroid cartilage, the Type I NRLN is more challenging to manage both at the laryngeal entry point and its origin from the vagus nerve (VN). For the Type II NRLN, it is essential to identify its point of origin and the reflection of the nerve from the VN. Therefore, modification of nerve dissection to mirror open surgery with bidirectional nerve dissection assisted in avoidance of traction injury to the nerve. CONCLUSIONS: We presented a video, a detailed description of methods, and discussed limits for NRLN management in robotic BABA. This report included (i) a description of the aberrant anatomy and CT scans to inform surgeons of the possible NRLN locations, (ii) a description of a technique for using the nerve monitor in the robotic surgeries, and (iii) a description of the techniques used to isolate and protect the NRLN during the robotic surgery. In robotic BABA, our NRLN-sparing technique and degree included mainly a multi-directional nerve dissection (i.e., medial-grade, later-grade approach together with proximal to/from distal) using athermal technique. The NRLN-sparing technique is predominantly carried out in an anterior dissection plane.