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Abstract Developing broad-spectrum influenza vaccines is crucial for influenza control and potential pandemic preparedness. Here, we reported a novel vaccine design utilizing circular RNA (circRNA) as a delivery platform for multi-subtype neuraminidases (NA) (influenza A N1, N2, and influenza B Victoria lineage NA) immunogens. Individual NA circRNA lipid nanoparticles (LNP) elicited robust NA-specific antibody responses with neuraminidase inhibition activity (NAI), preventing the virus from egressing and infecting neighboring cells. Additionally, the administration of circRNA LNP induced cellular immunity in mice. To achieve a universal influenza vaccine, we combined all three subtypes of NA circRNA-LNPs to generate a trivalent circRNA vaccine. The trivalent vaccine elicited a balanced antibody response against all three NA subtypes and a Th1-biased immune response in mice. Moreover, it protected mice against the lethal challenge of matched and mismatched H1N1, H3N2, and influenza B viruses, encompassing circulating and ancestral influenza virus strains. This study highlights the potential of delivering multiple NA antigens through circRNA-LNPs as a promising strategy for effectively developing a universal influenza vaccine against diverse influenza viruses.

IntroductionThe frequent occurrence of mutations in the SARS-CoV-2 Spike (S) protein, with up to dozens of mutations, poses a severe threat to the current efficacy of authorized COVID-19 vaccines. Membrane (M) protein, which is the most abundant viral structural protein, exhibits a high level of amino acid sequence conservation. M protein ectodomain could be recognized by specific antibodies; however, the extent to which it is immunogenic and provides protection remains unclear.MethodsWe designed and synthesized multiple peptides derived from coronavirus M protein ectodomains, and determined the secondary structure of specific peptides using circular dichroism (CD) spectroscopy. Enzyme-linked immunosorbent assay (ELISA) was utilized to detect IgG responses against the synthesized peptides in clinical samples. To evaluate the immunogenicity of peptide vaccines, BALB/c mice were intraperitoneally immunized with peptide-keyhole limpet hemocyanin (KLH) conjugates adjuvanted with incomplete Freund’s adjuvant (IFA). The humoral and T-cell immune responses induced by peptide-KLH conjugates were assessed using ELISA and ELISpot assays, respectively. The efficacy of the S2M2-30-KLH vaccine against SARS-CoV-2 variants was evaluated in vivo using the K18-hACE2 transgenic mouse model. The inhibitory effect of mouse immune serum on SARS-CoV-2 virus replication in vitro was evaluated using microneutralization assays. The subcellular localization of the M protein was evaluated using an immunofluorescent staining method, and the Fc-mediated antibody-dependent cellular cytotoxicity (ADCC) activity of the S2M2-30-specific monoclonal antibody (mAb) was measured using an ADCC reporter assay.ResultsSeroconversion rates for ectodomain-specific IgG were observed to be high in both SARS-CoV-2 convalescent patients and individuals immunized with inactivated vaccines. To assess the protective efficacy of the M protein ectodomain-based vaccine, we initially identified a highly immunogenic peptide derived from this ectodomain, named S2M2-30. The mouse serum specific to S2M2-30 showed inhibitory effects on the replication of SARS-CoV-2 variants in vitro. Immunizations of K18-hACE2-transgenic mice with the S2M2-30-keyhole limpet hemocyanin (KLH) vaccine significantly reduced the lung viral load caused by B.1.1.7/Alpha (UK) infection. Further mechanism investigations reveal that serum neutralizing activity, specific T-cell response and Fc-mediated antibody-dependent cellular cytotoxicity (ADCC) correlate with the specific immuno-protection conferred by S2M2-30.DiscussionThe findings of this study suggest that the antibody responses against M protein ectodomain in the population most likely exert a beneficial effect on preventing various SARS-CoV-2 infections.

ABSTRACT Background Cornelia de Lange syndrome (CdLS) is an uncommon congenital developmental disorder distinguished by intellectual disorder and distinctive facial characteristics, with a minority of cases attributed to RAD21 variants. Methods A patient was admitted to the endocrinology department at Peking Union Medical College Hospital, where 2 mL of peripheral venous blood was collected from the patient and his parents. DNA was extracted for whole‐exome sequencing (WES) analysis, and the genetic variation of the parents was confirmed through Sanger sequencing. Results A 13.3‐year‐old male patient with a height of 136.5 cm (−3.5 SDS) and a weight of 28.4 kg (−3.1 SDS) was found to have typical craniofacial features. WES revealed a pathogenic variant c.1143G>A (p.Trp381*) in the RAD21 gene. He was diagnosed with CdLS type 4 (OMIM #614701). We reviewed 36 patients with CdLS related to RAD21 gene variants reported worldwide from May 2012 to March 2024. Patient's variant status, clinical characteristics, and rhGH treatment response were summarized. Frameshift variants constituted the predominant variant type, representing 36% (13/36) of cases. Clinical features included verbal developmental delay and intellectual disorder observed in 94% of patients. Conclusion This study reported the third case of CdLS type 4 in China caused by a RAD21 gene variant, enriching the genetic mutational spectrum.

Background: Diminished ovarian reserve (DOR), a triggering factor for female infertility, affects 10% ∼ 35% of women of reproductive age. It is still unclear whether exposure to toxic metals (including metalloid) is associated with DOR risk, especially with respect to their relationships with the clinical phenotypes of DOR. Methods: A case–control study including 439 patients was conducted, and Ba, Ni, As, Tl, Cd, Pb, Hg, Al and Cr levels in BL and FF were measured. Subsequent analyses were focused on Ba, Ni, As and Tl, which had the highest weights in the associations of the nine toxic metals (including metalloid) with DOR risk, by integrating weighted quantile sum (WQS) regression and bayesian kernel machine regression (BKMR) models. Conditional logistic regression models and BKMR models were used to assess the individual and combined effects of Ba, Ni, As and Tl exposures on DOR risk. Multiple linear regression models were used to investigate the relationships between toxic metal (including metalloid) levels in BL and FF and the clinical characteristics of DOR. Results: The levels of Ba [second vs. lowest tertile: adjusted odds ratio (aOR) and 95 % confidence interval (CI) = 1.97 (1.13, 3.44); highest vs. lowest tertile: aOR (95 % CI) = 2.38 (1.32, 4.26)], Ni [highest vs. lowest tertile: aOR (95 % CI) = 2.59 (1.45, 4.65)] and As [highest vs. lowest tertile: aOR (95 % CI) = 1.96 (1.18, 3.25)] in BL, and Ba [highest vs. lowest tertile: aOR (95 % CI) = 4.60 (1.68, 12.61)] in FF were significantly associated with a higher risk of DOR, respectively. The significantly positive combined effect of the four toxic metals (including metalloid) on DOR risk was exhibited when their BL levels exceeded the 25th percentile compared with their median levels. Among these, As (0.9822) and Ba (0.9704) were the primary contributors to this relationship. Similarly, this finding was confirmed by the statistical results from FF samples, with a linear positive correlation between combined exposure and DOR risk, where Ba (0.9440) was the primary contributor. Finally, elevated levels of Ba, Ni, and As in BL and Ba in FF were significantly linked to the higher follicle–stimulating hormone (FSH) levels. The levels of Ba in BL and FF, as well as As in BL, were significantly associated with the lower luteinizing hormone (LH)/FSH ratio values. Conclusion: Overall, the results of this study indicate that elevated levels of Ba, Ni, As and Tl are associated with a higher risk of DOR, whether individually or in combination, and that Ba levels in BL and FF are stable contributors. In addition, exposure to Ba, Ni, As and Tl is linked to various clinical phenotype parameters of DOR. Further research is needed to confirm these associations and to identify potential mechanisms involved.

Background: Endometriosis is a common gynecological disease that affects approximately 5 %∼10 % of reproductive-aged women. Zinc (Zn), selenium (Se), copper (Cu), cobalt (Co) and molybdenum (Mo) are essential trace elements and are very important for human health. However, studies on the relationship between mixtures of essential trace elements and the risk of endometriosis are limited and inconsistent. In particular, studies confirming the association via different sample types are limited. Objective: This study aimed to investigate the associations between Zn, Se, Cu, Co and Mo concentrations in blood and follicular fluid (FF) and endometriosis risk in a Chinese population. Methods: A total of 609 subjects undergoing in vitro fertilization (IVF) were recruited; 836 samples were analyzed, including 451 blood samples (234 controls and 217 cases) and 385 FF samples (203 controls and 182 cases). In addition, 227 subjects provided both blood and FF samples. Zn, Se, Cu, Co and Mo concentrations in blood and FF were quantified via inductively coupled plasma−mass spectrometry (ICP−MS). The associations between the levels of Zn, Se, Cu, Co and Mo and the risk of endometriosis were assessed using single-element models (logistic regression models), and the combined effect of the trace elements on endometriosis risk was assessed using multielement models (Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression). Results: Based on the single-element models, significant associations of Zn concentrations in blood (high-level vs. low-level group: aOR = 14.17, 95 % CI: 7.31, 27.50) and FF (first tertile vs. second tertile group: aOR = 0.34, 95 % CI: 0.16, 0.71; third tertile vs. second tertile group: aOR = 2.32, 95 % CI: 1.38, 3.91, respectively) and Co concentrations in blood (first tertile vs. second tertile group, aOR = 0.24, 95 % CI: 0.12, 0.48) and FF (third tertile vs. second tertile group: aOR = 3.87, 95 % CI: 2.19, 6.84) with endometriosis risk were found after adjustment for all confounders. In FF, Cu and Mo levels were significantly greater among the cases than among the controls, with a positive association with endometriosis risk (Cu (first tertile vs. second tertile group: aOR = 0.39, 95 % CI: 0.19, 0.81; third tertile vs. second tertile group: aOR = 2.73, 95 % CI: 1.61, 4.66, respectively) and Mo (high-level vs. low-level group: aOR = 14.93, 95 % CI: 7.16, 31.12)). However, similar associations between blood Cu and Mo levels and endometriosis risk were not found. In addition, the levels of these five essential trace element mixtures in blood and in FF were significantly and positively associated with endometriosis risk according to the BKMR analyses; the levels of Zn and Cu in blood and the levels of Mo in FF were significantly related to the risk of endometriosis, and the posterior inclusion probabilities (PIPs) were 1.00, 0.99 and 1.00 for Zn and Cu levels in blood and Mo levels in FF, respectively. Furthermore, Zn and Mo were the highest weighted elements in blood and FF, respectively, according to WQS analyses. Conclusion: The risk of endometriosis was associated with elevated levels of several essential trace elements (Zn, Cu and Co). Elevated levels of these elements may be involved in the pathomechanism of endometriosis. However, further studies with larger sample sizes will be necessary to confirm these associations.

Summary: Background: The use of artificial intelligence (AI) in detecting colorectal neoplasia during colonoscopy holds the potential to enhance adenoma detection rates (ADRs) and reduce adenoma miss rates (AMRs). However, varied outcomes have been observed across studies. Thus, this study aimed to evaluate the potential advantages and disadvantages of employing AI-aided systems during colonoscopy. Methods: Using Medical Subject Headings (MeSH) terms and keywords, a comprehensive electronic literature search was performed of the Embase, Medline, and the Cochrane Library databases from the inception of each database until October 04, 2023, in order to identify randomized controlled trials (RCTs) comparing AI-assisted with standard colonoscopy for detecting colorectal neoplasia. Primary outcomes included AMR, ADR, and adenomas detected per colonoscopy (APC). Secondary outcomes comprised the poly missed detection rate (PMR), poly detection rate (PDR), and poly detected per colonoscopy (PPC). We utilized random-effects meta-analyses with Hartung-Knapp adjustment to consolidate results. The prediction interval (PI) and I2 statistics were utilized to quantify between-study heterogeneity. Moreover, meta-regression and subgroup analyses were performed to investigate the potential sources of heterogeneity. This systematic review and meta-analysis is registered with PROSPERO (CRD42023428658). Findings: This study encompassed 33 trials involving 27,404 patients. Those undergoing AI-aided colonoscopy experienced a significant decrease in PMR (RR, 0.475; 95% CI, 0.294–0.768; I2 = 87.49%) and AMR (RR, 0.495; 95% CI, 0.390–0.627; I2 = 48.76%). Additionally, a significant increase in PDR (RR, 1.238; 95% CI, 1.158–1.323; I2 = 81.67%) and ADR (RR, 1.242; 95% CI, 1.159–1.332; I2 = 78.87%), along with a significant increase in the rates of PPC (IRR, 1.388; 95% CI, 1.270–1.517; I2 = 91.99%) and APC (IRR, 1.390; 95% CI, 1.277–1.513; I2 = 86.24%), was observed. This resulted in 0.271 more PPCs (95% CI, 0.144–0.259; I2 = 65.61%) and 0.202 more APCs (95% CI, 0.144–0.259; I2 = 68.15%). Interpretation: AI-aided colonoscopy significantly enhanced the detection of colorectal neoplasia detection, likely by reducing the miss rate. However, future studies should focus on evaluating the cost-effectiveness and long-term benefits of AI-aided colonoscopy in reducing cancer incidence. Funding: This work was supported by the Heilongjiang Provincial Natural Science Foundation of China (LH2023H096), the Postdoctoral research project in Heilongjiang Province (LBH-Z22210), the National Natural Science Foundation of China’s General Program (82072640) and the Outstanding Youth Project of Heilongjiang Natural Science Foundation (YQ2021H023).

【Objective】Digital economy has a profound impact on China's economic development and can accelerate the process of agricultural modernization. The research theoretically explores how the digital economy drives agricultural modernization, constructs a comprehensive evaluation index system of digital economy and agricultural modernization, analyzes the impact of digital economy on agricultural modernization from a national perspective, and puts forward relevant policy recommendations.【Method】Based on the panel data of 31 provinces (cities, autonomous regions) in China from 2011 to 2020, the levels of digital economy and agricultural modernization were calculated respectively, the internal mechanism of the impact of digital economy on agricultural modernization was analyzed, and the heterogeneity and sub-test of digital economy on agricultural modernization were empirically tested.【Result】(1) Digital economy can drive agricultural modernization; (2) Digital economy can indirectly promote agricultural modernization through labor transfer and human capital investment of farmers; (3) In terms of various dimensions of agricultural modernization, digital economy can promote agricultural production modernization, agricultural modernization output and sustainable development of agricultural modernization, however, its impact on agricultural management modernization is not obvious; (4) Focusing on the development of agricultural modernization in various regions, compared with the eastern and central regions, the western regions have gained higher dividends through digital economy.【Conclusion】The digital economy has shown obvious differences in the process of deepening agricultural modernization in various regions of the whole country. On the basis of the existing achievements in the development and construction of the digital economy, we should continue to promote digital technology to empower agriculture, improve the quality of agricultural talents, deepen the concept of green and organic agriculture, develop digital management strategies in the operation and management of the digital economy that has not yet reflected the achievements, widely adopt e-commerce and online marketing models, push the branding, industrialized and scaled development of agricultural products according to local conditions and local characteristics, deepen the influence of digital economy on agricultural operation and management, and improve the internal mechanism of digital economy to drive agricultural modernization. In addition, the government should adopt different policies according to the development degree of agricultural modernization in different regions, and implement a differentiated and stepwise development strategy.

Dynamic changes of the paired heavy and light chain B cell receptor (BCR) repertoire provide an essential insight into understanding the humoral immune response post-SARS-CoV-2 infection and vaccination. However, differences between the endogenous paired BCR repertoire kinetics in SARS-CoV-2 infection and previously recovered/naïve subjects treated with the inactivated vaccine remain largely unknown. We performed single-cell V(D)J sequencing of B cells from six healthy donors with three shots of inactivated SARS-CoV-2 vaccine (BBIBP-CorV), five people who received the BBIBP-CorV vaccine after having recovered from COVID-19, five unvaccinated COVID-19 recovered patients and then integrated with public data of B cells from four SARS-CoV-2-infected subjects. We discovered that BCR variable (V) genes were more prominently used in the SARS-CoV-2 exposed groups (both in the group with active infection and in the group that had recovered) than in the vaccinated groups. The VH gene that expanded the most after SARS-CoV-2 infection was IGHV3-33, while IGHV3-23 in the vaccinated groups. SARS-CoV-2-infected group enhanced more BCR clonal expansion and somatic hypermutation than the vaccinated healthy group. A small proportion of public clonotypes were shared between the SARS-CoV-2 infected, vaccinated healthy, and recovered groups. Moreover, several public antibodies had been identified against SARS-CoV-2 spike protein. We comprehensively characterize the paired heavy and light chain BCR repertoire from SARS-CoV-2 infection to vaccination, providing further guidance for the development of the next-generation precision vaccine.

SARS-CoV Spike (S) protein shares considerable homology with SARS-CoV-2 S, especially in the conserved S2 subunit (S2). S protein mediates coronavirus receptor binding and membrane fusion, and the latter activity can greatly influence coronavirus infection. We observed that SARS-CoV S is less effective in inducing membrane fusion compared with SARS-CoV-2 S. We identify that S813T mutation is sufficient in S2 interfering with the cleavage of SARS-CoV-2 S by TMPRSS2, reducing spike fusogenicity and pseudoparticle entry. Conversely, the mutation of T813S in SARS-CoV S increased fusion ability and viral replication. Our data suggested that residue 813 in the S was critical for the proteolytic activation, and the change from threonine to serine at 813 position might be an evolutionary feature adopted by SARS-2-related viruses. This finding deepened the understanding of Spike fusogenicity and could provide a new perspective for exploring Sarbecovirus' evolution.

The G protein–coupled receptor melanocortin-4 receptor (MC4R) and its associated protein melanocortin receptor–associated protein 2 (MRAP2) are essential for the regulation of food intake and body weight in humans. MC4R localizes and functions at the neuronal primary cilium, a microtubule-based organelle that senses and relays extracellular signals. Here, we demonstrate that MRAP2 is critical for the weight-regulating function of MC4R neurons and the ciliary localization of MC4R. More generally, our study also reveals that GPCR localization to primary cilia can require specific accessory proteins that may not be present in heterologous cell culture systems. Our findings further demonstrate that targeting of MC4R to neuronal primary cilia is essential for the control of long-term energy homeostasis and suggest that genetic disruption of MC4R ciliary localization may frequently underlie inherited forms of obesity.

The melanocortin 4 receptor (MC4R) plays a critical role in the long-term regulation of energy homeostasis, and mutations in the MC4R are the most common cause of monogenic obesity. However, the precise molecular and cellular mechanisms underlying the maintenance of energy balance within MC4R-expressing neurons are unknown. We recently reported that the MC4R localizes to the primary cilium, a cellular organelle that allows for partitioning of incoming cellular signals, raising the question of whether the MC4R functions in this organelle. Here, using mouse genetic approaches, we found that cilia were required specifically on MC4R-expressing neurons for the control of energy homeostasis. Moreover, these cilia were critical for pharmacological activators of the MC4R to exert an anorexigenic effect. The MC4R is expressed in multiple brain regions. Using targeted deletion of primary cilia, we found that cilia in the paraventricular nucleus of the hypothalamus (PVN) were essential to restrict food intake. MC4R activation increased adenylyl cyclase (AC) activity. As with the removal of cilia, inhibition of AC activity in the cilia of MC4R-expressing neurons of the PVN caused hyperphagia and obesity. Thus, the MC4R signaled via PVN neuron cilia to control food intake and body weight. We propose that defects in ciliary localization of the MC4R cause obesity in human inherited obesity syndromes and ciliopathies. [ABSTRACT FROM AUTHOR]