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Abstract Lettuce is one of the most widely cultivated and consumed dicotyledonous vegetables globally. Despite the availability of its reference genome sequence, lettuce gene annotation remains incomplete, impeding comprehensive research and the broad application of genomic resources. Long-read RNA isoform sequencing (Iso-Seq) offers substantial advantages for analyzing RNA alternative splicing and aiding gene annotation, yet it faces throughput limitations. We present the HIT-ISOseq method tailored for bulk sample analysis, significantly enhancing RNA sequencing throughput on the PacBio platform by concatenating cDNA. Here we show, HIT-ISOseq generates 3-4 cDNA molecules per CCS read in lettuce, yielding 15.7 million long reads per PacBio Sequel II SMRT Cell 8 M. We validate its effectiveness in analyzing six lettuce tissue samples, including roots, stems, and leaves, revealing tissue-specific gene expression patterns and RNA isoforms. Leveraging diverse tissue long-read RNA sequencing, we refine the transcript annotation of the lettuce reference genome, expanding its GO and KEGG annotation repertoire. Collectively, this study serves as a foundational reference for genome annotation and the analysis of multi-sample isoform expression, utilizing high-throughput long-read transcriptome sequencing.

In this paper a novel face recognition algorithm, based on wavelet kernel non-negative matrix factorization (WKNMF), is proposed. By utilizing features from multi-resolution analysis, the nonlinear mapping capability of kernel nonnegative matrix factorization could be improved by the method proposed. The proposed face recognition method combines wavelet kernel non-negative matrix factorization and RBF network. Extensive experimental results on ORL and YALE face database show that the suggested method possesses much stronger analysis capability than the comparative methods. Compared with PCA, non-negative matrix factorization, kernel PCA and independent component analysis, the proposed face recognition method with WKNMF and RBF achieves over 10 % improvement in recognition accuracy.

Objective To analyze the clinical characteristics of anti - neuronal antibody positive paraneoplastic neurological syndrome related to immune checkpoint inhibitors (ICI - PNS). Methods and Results A total of 5 patients with anti - neuronal antibody positive ICI - PNS in Peking Union Medical College Hospital from January 2012 to March 2024 were included. Tumor types included small cell lung cancer (2 cases), malignant melanoma (one case), Hodgkin lymphoma (one case) and cervical cancer (one case). Immune checkpoint inhibitors (ICIs) included programmed death 1 (PD - 1) inhibitors (3 cases), programmed cell death ligand 1 (PD-L1) inhibitors (one case) and bispecific PD-1/cytotoxic T lymphocyte- associated antigen 4 (CTLA -4) inhibitors (one case). All 5 patients presented with high -risk neurologic phenotypes of paraneoplastic neurological syndrome (PNS), of which 4 presented with limbic encephalitis and one presented with rapidly progressive cerebellar syndrome. Anti - neuronal antibodies detected in serum and/or cerebrospinal fluid of patients included anti - Hu, γ - aminobutyric acid receptor type B (GABABR), sex-determining region of Y chromosome-related high mobility group box 1 (SOX1), metabotropic glutamate receptor 5 (mGluR5) and Yo antibodies. Neurological syndromes occurred within 2 weeks after receiving ICIs in 4 patients. The modified Rankin Score (mRS) of 4 patients was 3 at peak of illness, and one patient was 5 at peak of illness. The Common Terminology Criteria for Adverse Events (CTCAE) was grade 3 in all 5 patients. After withdrawal of ICIs and treatment with glucocorticoids and intravenous immunoglobulin (IVIg), the neurological symptoms of the patients were improved. Conclusions High/ intermediate - risk anti - neuronal antibodies are diagnostic markers of ICI - PNS. Evaluation of ICI - PNS clinical phenotypes and CTCAE grading are important for immunotherapy. Discontinuation of ICIs, administration of glucocorticoids and IVIg can improve the prognosis of patients.

As the need for effective antiviral treatment intensifies, such as with the coronavirus disease 19 (COVID-19) infection, it is crucial to understand that while the mechanisms of action of these drugs or compounds seem apparent, they might also interact with unexplored targets, such as cell membrane ion channels in diverse cell types. In this review paper, we demonstrate that many different drugs or compounds, in addition to their known interference with viral infections, may also directly influence various types of ionic currents on the surface membrane of the host cell. These agents include artemisinin, cannabidiol, memantine, mitoxantrone, molnupiravir, remdesivir, SM-102, and sorafenib. If achievable at low concentrations, these regulatory effects on ion channels are highly likely to synergize with the identified initial mechanisms of viral replication interference. Additionally, the immediate regulatory impact of these agents on the ion-channel function may potentially result in unintended adverse effects, including changes in cardiac electrical activity and the prolongation of the QTc interval. Therefore, it is essential for patients receiving these related agents to exercise additional caution to prevent unnecessary complications.

● Utilizing optimization technology in crop and livestock systems can enhance food production.● Numerous technologies have the potential to contribute to the mitigation of environmental impacts within food systems.● Three potential pathways are proposed that could transform the current food system to align with SDGs and agricultural green development.A recent UN Sustainable Development Goals (SDGs) analysis indicated a significant regression in the global SDG goal scores, particularly in SDG 2—Zero Hunger. The emissions of environmental pollution caused by meeting food demands have prompted some countries to intensify their climate change mitigation efforts. These circumstances have introduced significant uncertainty to the future global sustainable food development. Additionally, a notable global challenge is the persistence of hidden hunger, primarily characterized by the insufficient consumption of high-quality animal protein. Addressing this issue would necessitate increased environmental costs to attain high-quality food security. The future food system presents a significant challenge in coordinating food security, food quality and environmental quality. This article presents a comprehensive review and proposes a three-step strategy for future agricultural development based on food security, quality, and environmental aspects. This is a novel food system transfer strategy, as it concurrently addresses both global food security and environmental thresholds. It involves the construction of an efficient food system that operates within the constraints of environmental limits. The objective is to align with global SDG indicators and to maintain natural resource consumption and pollutant emissions within planetary boundaries.

● Cash crops and livestock production in Yangtze River Basin has grown rapidly.● The agricultural inputs discharge multiple pollutants loads on water bodies in the YRB.● Multiple pollutants impact on efficient utilization of nitrogen and phosphorus in agriculture.● An explicitly multi-pollutant approach accounting for interactions is need.The rapid increase in the proportion of cash crops and livestock production in the Yangtze River Basin has led to commensurate increases in fertilizer and pesticide inputs. Excessive application of chemical fertilizer, organophosphorus pesticides and inappropriate disposal of agricultural waste induced water pollution and potentially threaten Agriculture Green Development (AGD). To ensure food security and the food supply capacity of the Yangtze River Basin, it is important to balance green and development, while ensuring the quality of water bodies. Multiple pollutants affect the transfer, adsorption, photolysis and degradation of each other throughout the soil-plant-water system. This paper considers the impact of multi-pollutants on the nitrogen and phosphorus cycles especially for crops, which are related to achieving food security and AGD. It presents prospective on theory, modeling and multi-pollutant control in the Yangtze River Basin for AGD that are of potential value for other developing regions.

Abstract As the malignancy with the highest global incidence, breast cancer represents a significant threat to women’s health. Recent advances have shed light on the importance of mitochondrial function in cancer, particularly in metabolic reprogramming within tumors. Recognizing this, we developed a novel risk signature based on mitochondrial-related genes to improve prognosis prediction and risk stratification in breast cancer patients. In this study, transcriptome data and clinical features of breast cancer samples were extracted from two sources: the TCGA, serving as the training set, and the METABRIC, used as the independent validation set. We developed the signature using LASSO-Cox regression and assessed its prognostic efficacy via ROC curves. Furthermore, the signature was integrated with clinical features to create a Nomogram model, whose accuracy was validated through clinical calibration curves and decision curve analysis. To further elucidate prognostic variations between high and low-risk groups, we conducted functional enrichment and immune infiltration analyses. Additionally, the study encompassed a comparison of mutation landscapes and drug sensitivity, providing a comprehensive understanding of the differing characteristics in these groups. Conclusively, we established a risk signature comprising 8 mitochondrial-related genes—ACSL1, ALDH2, MTHFD2, MRPL13, TP53AIP1, SLC1A1, ME3, and BCL2A1. This signature was identified as an independent risk predictor for breast cancer patient survival, exhibiting a significant high hazard ratio (HR = 3.028, 95%CI 2.038–4.499, P

AbstractThladiantha nudiflora Hemsl. ex F.B.Forbes & Hemsl. 1887 (Cucurbitaceae) has been widely known as a traditional medicine plant. In this study, we sequenced, assembled, and annotated the complete chloroplast genome of T. nudiflora. The chloroplast genome of T. nudiflora is 156,824 base pair (bp) in length, containing a large single-copy region of 86,566 bp and a small single-copy region of 18,070 bp, separated by a pair of inverted repeats of 26,094 bp. The chloroplast genome contains 132 genes, including 87 protein-coding, 37 transfer RNA, and eight ribosomal RNA genes. Phylogenetic analysis of the chloroplast genome revealed that species of the genus Thladiantha were clustered together in the phylogenetic trees. This study will not only shed light on T. nudiflora’s evolutionary position but also provide valuable chloroplast genomic information for future studies into the origins and diversification of the genus Thladiantha and the Cucurbitaceae family.

Emotional disorders, such as anxiety and depression, represent a major societal problem; however, the underlying neurological mechanism remains unknown. The ventral lateral septum (LSv) is implicated in regulating processes related to mood and motivation. In this study, we found that LSv GABAergic neurons were significantly activated in mice experiencing chronic social defeat stress (CSDS) after exposure to a social stressor. We then controlled LSv GABAergic neuron activity using a chemogenetic approach. The results showed that although manipulation of LSv GABAergic neurons had little effect on anxiety-like behavioral performances, the activation of LSv GABAergic neurons during CSDS worsened social anxiety during a social interaction (SI) test. Moreover, LSv GABAergic neurons showed strong projections to the paraventricular nucleus (PVN) of the hypothalamus, which is a central hub for stress reactions. Remarkably, while activation of GABAergic LSv–PVN projections induced social anxiety under basal conditions, activation of this pathway during CSDS alleviated social anxiety during the SI test. On the other hand, the chemogenetic manipulation of LSv GABAergic neurons or LSvGABA–PVN projections had no significant effect on despair-like behavioral performance in the tail suspension test. Overall, LS GABAergic neurons, particularly the LSv GABAergic–PVN circuit, has a regulatory role in pathological anxiety and is thus a potential therapeutic target for the treatment of emotional disorders.

Aims: Mendelian randomization (MR) is considered to overcome the bias of observational studies, but there is no current meta-analysis of MR studies on rheumatoid arthritis (RA). The purpose of this study was to summarize the relationship between potential pathogenic factors and RA risk based on existing MR studies. Methods: PubMed, Web of Science, and Embase were searched for MR studies on influencing factors in relation to RA up to October 2022. Meta-analyses of MR studies assessing correlations between various potential pathogenic factors and RA were conducted. Random-effect and fixed-effect models were used to synthesize the odds ratios of various pathogenic factors and RA. The quality of the study was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines. Results: A total of 517 potentially relevant articles were screened, 35 studies were included in the systematic review, and 19 studies were eligible to be included in the meta-analysis. Pooled estimates of 19 included studies (causality between 15 different risk factors and RA) revealed that obesity, smoking, coffee intake, lower education attainment, and Graves’ disease (GD) were related to the increased risk of RA. In contrast, the causality contribution from serum mineral levels (calcium, iron, copper, zinc, magnesium, selenium), alcohol intake, and chronic periodontitis to RA is not significant. Conclusion: Obesity, smoking, education attainment, and GD have real causal effects on the occurrence and development of RA. These results may provide insights into the genetic susceptibility and potential biological pathways of RA. Cite this article: Bone Joint Res 2023;12(9):601–614.

● A provincial stage-specific greenhouse gas (GHG) accounting model for the Chinese food system was developed. ● From 1992 to 2017, the net GHG emission from the Chinese food system increased by 38% from 785 to 1080 Tg CO2-eq. ● In 2017, top GHG emission regions were located in the central and southern China, the North China Plain and Northeast China, while GHG sink regions were Tibet, Qinghai and Xinjiang. ● Total GHG emission from the Chinese food system could be reduced to 355 Tg CO2-eq in a low-carbon scenario, with enhancing mitigation technologies, transforming diet and its related conditions and increasing agricultural activities contributing 60%, 25% and 15% of the GHG reductions, respectively. In China, there has been insufficient study of whole food system greenhouse gas (GHG) accounting, which limits the development of mitigation strategies and may preclude the achievement of carbon peak and carbon neutrality goals. The paper presents the development of a carbon extension of NUFER (NUtrient flows in Food chain, Environment and Resources use model), a food system GHG emission accounting model that covers land use and land-use change, agricultural production, and post-production subsectors. The spatiotemporal characteristics of GHG emissions were investigated for the Chinese food system (CFS) from 1992 to 2017, with a focus on GHG emissions from the entire system. The potential to achieve a low-carbon food system in China was explored. The net GHG emissions from the CFS increased from 785 Tg CO2 equivalent (CO2-eq) in 1992 to 1080 Tg CO2-eq in 2017. Agricultural activities accounted for more than half of the total emissions during the study period, while agricultural energy was the largest contributor to the GHG increase. In 2017, highest emitting regions were located in central and southern China (Guangdong and Hunan), the North China Plain (Shandong, Henan and Jiangsu) and Northeast China (Heilongjiang and Inner Mongolia) and contributed to over half of the total GHG emissions. Meanwhile, Xinjiang, Qinghai and Tibet are shown as carbon sink areas. It was found that food-system GHG emissions could be reduced to 355 Tg CO2-eq, where enhancing endpoint mitigation technologies, transforming social-economic and diet conditions, and increasing agricultural productivities can contribute to 60%, 25% and 15%, respectively. Synergistic mitigation effects were found to exist in agricultural activities.