Influenza Virus Z-RNAs Induce ZBP1-Mediated Necroptosis.

Influenza A virus (IAV) is a lytic RNA virus that triggers receptor-interacting serine/threonine-protein kinase 3 (RIPK3)-mediated pathways of apoptosis and mixed lineage kinase domain-like pseudokinase (MLKL)-dependent necroptosis in infected cells. ZBP1 initiates RIPK3-driven cell death by sensing IAV RNA and activating RIPK3. Here, we show that replicating IAV generates Z-RNAs, which activate ZBP1 in the nucleus of infected cells. ZBP1 then initiates RIPK3-mediated MLKL activation in the nucleus, resulting in nuclear envelope disruption, leakage of DNA into the cytosol, and eventual necroptosis. Cell death induced by nuclear MLKL was a potent activator of neutrophils, a cell type known to drive inflammatory pathology in virulent IAV disease. Consequently, MLKL-deficient mice manifest reduced nuclear disruption of lung epithelia, decreased neutrophil recruitment into infected lungs, and increased survival following a lethal dose of IAV. These results implicate Z-RNA as a new pathogen-associated molecular pattern and describe a ZBP1-initiated nucleus-to-plasma membrane "inside-out" death pathway with potentially pathogenic consequences in severe cases of influenza.

Cellular Differentiation of Human Monocytes Is Regulated by Time-Dependent Interleukin-4 Signaling and the Transcriptional Regulator NCOR2.

Human in vitro generated monocyte-derived dendritic cells (moDCs) and macrophages are used clinically, e.g., to induce immunity against cancer. However, their physiological counterparts, ontogeny, transcriptional regulation, and heterogeneity remains largely unknown, hampering their clinical use. High-dimensional techniques were used to elucidate transcriptional, phenotypic, and functional differences between human in vivo and in vitro generated mononuclear phagocytes to facilitate their full potential in the clinic. We demonstrate that monocytes differentiated by macrophage colony-stimulating factor (M-CSF) or granulocyte macrophage colony-stimulating factor (GM-CSF) resembled in vivo inflammatory macrophages, while moDCs resembled in vivo inflammatory DCs. Moreover, differentiated monocytes presented with profound transcriptomic, phenotypic, and functional differences. Monocytes integrated GM-CSF and IL-4 stimulation combinatorically and temporally, resulting in a mode- and time-dependent differentiation relying on NCOR2. Finally, moDCs are phenotypically heterogeneous and therefore necessitate the use of high-dimensional phenotyping to open new possibilities for better clinical tailoring of these cellular therapies.

VARIDT 3.0: the phenotypic and regulatory variability of drug transporter.

The phenotypic and regulatory variability of drug transporter (DT) are vital for the understanding of drug responses, drug-drug interactions, multidrug resistances, and so on. The ADME property of a drug is collectively determined by multiple types of variability, such as: microbiota influence (MBI), transcriptional regulation (TSR), epigenetics regulation (EGR), exogenous modulation (EGM) and post-translational modification (PTM). However, no database has yet been available to comprehensively describe these valuable variabilities of DTs. In this study, a major update of VARIDT was therefore conducted, which gave 2072 MBIs, 10 610 TSRs, 46 748 EGRs, 12 209 EGMs and 10 255 PTMs. These variability data were closely related to the transportation of 585 approved and 301 clinical trial drugs for treating 572 diseases. Moreover, the majority of the DTs in this database were found with multiple variabilities, which allowed a collective consideration in determining the ADME properties of a drug. All in all, VARIDT 3.0 is expected to be a popular data repository that could become an essential complement to existing pharmaceutical databases, and is freely accessible without any login requirement at: https://idrblab.org/varidt/.

The Saururus chinensis genome provides insights into the evolution of pollination strategies and herbaceousness in magnoliids.

Saururus chinensis, an herbaceous magnoliid without perianth, represents a clade of early-diverging angiosperms that have gone through woodiness-herbaceousness transition and pollination obstacles: the characteristic white leaves underneath inflorescence during flowering time are considered a substitute for perianth to attract insect pollinators. Here, using the newly sequenced S. chinensis genome, we revisited the phylogenetic position of magnoliids within mesangiosperms, and recovered a sister relationship for magnoliids and Chloranthales. By considering differentially expressed genes, we identified candidate genes that are involved in the morphogenesis of the white leaves in S. chinensis. Among those genes, we verified - in a transgenic experiment with Arabidopsis - that increasing the expression of the "pseudo-etiolation in light" gene (ScPEL) can inhibit the biosynthesis of chlorophyll. ScPEL is thus likely responsible for the switches between green and white leaves, suggesting that changes in gene expression may underlie the evolution of pollination strategies. Despite being an herbaceous plant, S. chinensis still has vascular cambium and maintains the potential for secondary growth as a woody plant, because the necessary machinery, i.e., the entire gene set involved in lignin biosynthesis, is well preserved. However, similar expression levels of two key genes (CCR and CAD) between the stem and other tissues in the lignin biosynthesis pathway are possibly associated with the herbaceous nature of S. chinensis. In conclusion, the S. chinensis genome provides valuable insights into the adaptive evolution of pollination in Saururaceae and reveals a possible mechanism for the evolution of herbaceousness in magnoliids.

Alterations of resting-state network dynamics in Alzheimer's disease based on leading eigenvector dynamics analysis.

Alzheimer's disease (AD) is a neurodegenerative disease, and mild cognitive impairment (MCI) is considered a transitional stage between healthy aging and dementia. Early detection of MCI can help slow down the progression of AD. At present, there are few studies exploring the characteristics of abnormal dynamic brain activity in AD. This article uses a method called leading eigenvector dynamics analysis (LEiDA) to study resting-state functional magnetic resonance imaging (rs-fMRI) data of AD, MCI, and cognitively normal (CN) participants. By identifying repetitive states of phase coherence, intergroup differences in brain dynamic activity indicators are examined, and the neurobehavioral scales were used to assess the relationship between abnormal dynamic activities and cognitive function. The results showed that in the indicators of occurrence probability and lifetime, the globally synchronized state of the patient group decreased. The activity state of the limbic regions significantly detected the difference between AD and the other two groups. Compared to CN, AD and MCI have varying degrees of increase in default and visual region activity states. In addition, in the analysis related to the cognitive scales, it was found that individuals with poorer cognitive abilities were less active in the globally synchronized state and more active in limbic region activity state and visual region activity state. Taken together, these findings reveal abnormal dynamic activity of resting-state networks in patients with AD and MCI, provide new insights into the dynamic analysis of brain networks, and contribute to a deeper understanding of abnormal spatial dynamic patterns in AD patients.NEW & NOTEWORTHY Alzheimer's disease (AD) is a neurodegenerative disease, but few studies have explored the characteristics of abnormal dynamic brain activity in AD patients. Here, our report reveals the abnormal dynamic activity of the patients' resting-state network, providing new insights into the dynamic analysis of brain networks and helping to gain a deeper understanding of the abnormal spatial dynamic patterns in AD patients.

Interleukin-21 receptor signaling promotes metabolic dysfunction-associated steatohepatitis-driven hepatocellular carcinoma by inducing immunosuppressive IgA+ B cells.

BACKGROUND: Dysregulation of immune surveillance is tightly linked to the development of metabolic dysfunction-associated steatohepatitis (MASH)-driven hepatocellular carcinoma (HCC); however, its underlying mechanisms remain unclear. Herein, we aimed to determine the role of interleukin-21 receptor (IL-21R) in MASH-driven HCC. METHODS: The clinical significance of IL-21R was assessed in human HCC specimens using immunohistochemistry staining. Furthermore, the expression of IL-21R in mice was assessed in the STAM model. Thereafter, two different MASH-driven HCC mouse models were applied between IL-21R-deficient mice and wild type controls to explore the role of IL-21R in MASH-driven HCC. To further elucidate the potential mechanisms by which IL-21R affected MASH-driven HCC, whole transcriptome sequencing, flow cytometry and adoptive lymphocyte transfer were performed. Finally, flow cytometry, enzyme-linked immunosorbent assay, immunofluorescent staining, chromatin immunoprecipitation assay and western blotting were conducted to explore the mechanism by which IL-21R induced IgA+ B cells. RESULTS: HCC patients with high IL-21R expression exhibited poor relapse-free survival, advanced TNM stage and severe steatosis. Additionally, IL-21R was demonstrated to be upregulated in mouse liver tumors. Particularly, ablation of IL-21R impeded MASH-driven hepatocarcinogenesis with dramatically reduction of lipid accumulation. Moreover, cytotoxic CD8+ T lymphocyte activation was enhanced in the absence of IL-21R due to the reduction of immunosuppressive IgA+ B cells. Mechanistically, the IL-21R-STAT1-c-Jun/c-Fos regulatory axis was activated in MASH-driven HCC and thus promoted the transcription of Igha, resulting in the induction of IgA+ B cells. CONCLUSIONS: IL-21R plays a cancer-promoting role by inducing IgA+ B cells in MASH-driven hepatocarcinogenesis. Targeting IL-21R signaling represents a potential therapeutic strategy for cancer therapy.

Diabetes mellitus and Alzheimer's disease: Vacuolar adenosine triphosphatase as a potential link.

Globally, the incidence of diabetes mellitus (DM) and Alzheimer's disease (AD) is increasing year by year, causing a huge economic and social burden, and their pathogenesis and aetiology have been proven to have a certain correlation. In recent years, more and more studies have shown that vacuolar adenosine triphosphatases (v-ATPases) in eukaryotes, which are biomolecules regulating lysosomal acidification and glycolipid metabolism, play a key role in DM and AD. This article describes the role of v-ATPase in DM and AD, including its role in glycolysis, insulin secretion and insulin resistance (IR), as well as its relationship with lysosomal acidification, autophagy and ß-amyloid (Aß). In DM, v-ATPase is involved in the regulation of glucose metabolism and IR. v-ATPase is closely related to glycolysis. On the one hand, v-ATPase affects the rate of glycolysis by affecting the secretion of insulin and changing the activities of key glycolytic enzymes hexokinase (HK) and phosphofructokinase 1 (PFK-1). On the other hand, glucose is the main regulator of this enzyme, and the assembly and activity of v-ATPase depend on glucose, and glucose depletion will lead to its decomposition and inactivation. In addition, v-ATPase can also regulate free fatty acids, thereby improving IR. In AD, v-ATPase can not only improve the abnormal brain energy metabolism by affecting lysosomal acidification and autophagy but also change the deposition of Aß by affecting the production and degradation of Aß. Therefore, v-ATPase may be the bridge between DM and AD.

Universal Entanglement Spectrum in One-Dimensional Gapless Symmetry Protected Topological States.

Quantum entanglement marks a definitive feature of topological states. However, the entanglement spectrum remains insufficiently explored for topological states without a bulk energy gap. Using a combination of field theory and numerical techniques, we accurately calculate and analyze the entanglement spectrum of gapless symmetry protected topological states in one dimension. We highlight that the universal entanglement spectrum not only encodes the nontrivial edge degeneracy, generalizing the Li-Haldane conjecture to gapless topological states, but also contains the operator content of the underlying boundary conformal field theory. This implies that the bulk wave function can act as a fingerprint of both quantum criticality and topology in gapless symmetry protected topological states. We also identify a symmetry enriched conformal boundary condition that goes beyond the conventional conformal boundary condition.

Non-Hermitian Strongly Interacting Dirac Fermions.

Exotic quantum phases and phase transition in the strongly interacting Dirac systems have attracted tremendous interests. On the other hand, non-Hermitian physics, usually associated with dissipation arising from the coupling to environment, emerges as a frontier of modern physics in recent years. In this Letter, we investigate the interplay between non-Hermitian physics and strong correlation in Dirac-fermion systems. We generalize the projector quantum Monte-Carlo (PQMC) algorithm to the non-Hermitian interacting fermionic systems. Employing PQMC simulation, we decipher the ground-state phase diagram of the honeycomb Hubbard model with spin resolved non-Hermitian asymmetric hopping processes. The antiferromagnetic (AFM) ordering induced by Hubbard interaction is enhanced by the non-Hermitian asymmetric hopping. Combining PQMC simulation and renormalization group analysis, we reveal that the quantum phase transition between Dirac semi-metal and AFM phases belongs to Hermitian chiral XY universality class, implying that a Hermitian Gross-Neveu transition is emergent at the quantum critical point although the model is non-Hermitian.

Emergence of Competing Orders and Possible Quantum Spin Liquid in SU(N) Fermions.

In the past few decades, tremendous efforts have been made toward understanding the exotic physics emerging from competition between various ordering tendencies in strongly correlated systems. Employing state-of-the-art quantum Monte Carlo simulation, we investigate an interacting SU(N) fermionic model with varying interaction strength and value of N, and we unveil the ground-state phase diagram of the model exhibiting a plethora of exotic phases. For small values of N-namely, N=2, 3-the ground state is an antiferromagnetic (AFM) phase, whereas in the large-N limit, a staggered valence bond solid (VBS) order is dominant. For intermediate values of N such as N=4, 5, remarkably, our study reveals that distinct VBS orders appear in the weak and strong coupling regimes. More fantastically, the competition between staggered and columnar VBS ordering tendencies gives rise to a Mott insulating phase without spontaneous symmetry breaking (SSB), existing in a large interacting parameter regime, which is consistent with a gapped quantum spin liquid. Our study not only provides a platform to investigate the fundamental physics of quantum many-body systems-it also offers a novel route toward searching for exotic states of matter such as quantum spin liquid in realistic quantum materials.

Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer.

OBJECTIVE: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). METHODS: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). RESULTS: A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. CONCLUSION: The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

Construction of a Metal-Silica Interface for Semihydrogenation of Alkynes.

Fabricating optimum surface structures represents an attractive approach for synthesizing supported catalysts with high activity and specific selectivity. New active sites could be flexibly constructed via the strong metal-support interaction under the redox condition. Herein, we demonstrated the formation of a new Rh-Si surface on a silica-modified carbon nanotube supported Rh catalyst under the high-temperature reduction condition as well as a thin amorphous silica coating layer and weak chemisorption toward the CO molecule. The electronic interactions between Rh and Si, along with the particular structure, guarantee desirable catalytic performance for the semihydrogenation of phenylacetylene under mild conditions. This facile approach might be extensively used in constructing new active sites with robust activity and specific selectivity in diverse heterogeneous catalysis systems.

New mitochondrial DNA synthesis enables NLRP3 inflammasome activation.

Dysregulated NLRP3 inflammasome activity results in uncontrolled inflammation, which underlies many chronic diseases. Although mitochondrial damage is needed for the assembly and activation of the NLRP3 inflammasome, it is unclear how macrophages are able to respond to structurally diverse inflammasome-activating stimuli. Here we show that the synthesis of mitochondrial DNA (mtDNA), induced after the engagement of Toll-like receptors, is crucial for NLRP3 signalling. Toll-like receptors signal via the MyD88 and TRIF adaptors to trigger IRF1-dependent transcription of CMPK2, a rate-limiting enzyme that supplies deoxyribonucleotides for mtDNA synthesis. CMPK2-dependent mtDNA synthesis is necessary for the production of oxidized mtDNA fragments after exposure to NLRP3 activators. Cytosolic oxidized mtDNA associates with the NLRP3 inflammasome complex and is required for its activation. The dependence on CMPK2 catalytic activity provides opportunities for more effective control of NLRP3 inflammasome-associated diseases.

Author Correction: Inflammation-induced IgA+ cells dismantle anti-liver cancer immunity.

In this Article, the sentence: "After 7 months of HFD, MUP-uPA mice developed HCC15, which contained numerous (usually 50-100 per tumour) non-recurrent coding mutations in pathways that are mutated in human HCC (Fig. 2d and Extended Data Fig. 6a).", should have read: "After 7 months of HFD, MUP-uPA mice developed HCC15, which contained numerous (usually 50-100 per tumour) non-recurrent mutations in pathways that are mutated in human HCC (Fig. 2d and Extended Data Fig. 6a).". This has been corrected online. In Extended Data Fig. 6a and b, which show the number of point mutations identified per sample and the mutational signatures, all sequence variants (including non-coding mutations) are shown. Fig. 2d also presents all variants compared to human mutations. In the Supplementary Information to this Amendment, we now provide the comparisons of all variants and coding variants to human mutations.

Self-harm and interpersonal violence due to high temperature from the global burden of disease study 2019: A 30-year assessment.

BACKGROUND: The impact of global warming on health due to climate change is increasingly studied, but the global burden of self-harm and interpersonal violence attributable to high temperature is still limited. This study aimed to systematically assess the burden of self-harm and interpersonal violence attributable to high temperature globally or by region and climate zone from 1990 to 2019. METHODS: We obtained the global, regional, and national deaths, disability-adjusted life years (DALYs), age-standardized mortality rates (ASMR), and age-standardized disability-adjusted life year rates (ASDR) of self-harm and interpersonal violence due to high temperature from 1990 to 2019 through the Global Burden of Disease Study (GBD) 2019. The burden of self-harm and interpersonal violence due to high temperature was estimated by age, sex, climate zone, the socio-demographic index (SDI), and the healthcare access and quality index (HAQ). Average annual percentage changes (AAPCs) in ASMR and ASDR were calculated for 1990-2019 using the Joinpoint model. RESULTS: From 1990 to 2019, the global deaths and DALYs related to self-harm and interpersonal violence due to high temperature increased from 20,002 (95% UI, 9243 to 41,928) and 1,107,216 (95% UI, 512,062 to 2,319,477) to 26,459 (95% UI, 13,574 to 47,265) and 1,382,487 (95% UI, 722,060 to 2,474,441), respectively. However, the ASMR and ASDR showed varying degrees of decreasing trends, with decreases of 13.36% and 12.66%, respectively. The ASMR was high and declining in low and low-middle SDI regions, particularly in tropical and subtropical regions. In addition, SDI and HAQ index were negatively correlated with ASMR in 204 countries and regions. CONCLUSIONS: The global burden of self-harm and interpersonal violence attributed to high temperature has decreased over the past 30 years, but the number of deaths and DALYs continues to rise. Climate change continues to make heat stress a significant risk factor for self-harm and interpersonal violence worldwide.

Frequent gene mutations and the correlations with clinicopathological features in clear cell renal cell carcinoma: preliminary study based on Chinese population and TCGA database.

BACKGROUND: Large-scale sequencing plays important roles in revealing the genomic map of ccRCC and predicting prognosis and therapeutic response to targeted drugs. However, the relevant clinical data is still sparse in Chinese population. METHODS: Fresh tumor specimens were collected from 66 Chinese ccRCC patients, then the genomic RNAs were subjected to whole transcriptome sequencing (WTS). We comprehensively analyzed the frequently mutated genes from our hospital's cohort as well as TCGA-KIRC cohort. RESULTS: VHL gene is the most frequently mutated gene in ccRCC. In our cohort, BAP1 and PTEN are significantly associated with a higher tumor grade and DNM2 is significantly associated with a lower tumor grade. The mutant type (MT) groups of BAP1 or PTEN, BAP1 or SETD2, BAP1 or TP53, BAP1 or MTOR, BAP1 or FAT1 and BAP1 or AR had a significantly correlation with higher tumor grade in our cohort. Moreover, we identified HMCN1 was a hub mutant gene which was closely related to worse prognosis and may enhance anti-tumor immune responses. CONCLUSIONS: In this preliminary research, we comprehensively analyzed the frequently mutated genes in the Chinese population and TCGA database, which may bring new insights to the diagnosis and medical treatment of ccRCC.

Activation of NF-κB and p300/CBP potentiates cancer chemoimmunotherapy through induction of MHC-I antigen presentation.

Many cancers evade immune rejection by suppressing major histocompatibility class I (MHC-I) antigen processing and presentation (AgPP). Such cancers do not respond to immune checkpoint inhibitor therapies (ICIT) such as PD-1/PD-L1 [PD-(L)1] blockade. Certain chemotherapeutic drugs augment tumor control by PD-(L)1 inhibitors through potentiation of T-cell priming but whether and how chemotherapy enhances MHC-I-dependent cancer cell recognition by cytotoxic T cells (CTLs) is not entirely clear. We now show that the lysine acetyl transferases p300/CREB binding protein (CBP) control MHC-I AgPPM expression and neoantigen amounts in human cancers. Moreover, we found that two distinct DNA damaging drugs, the platinoid oxaliplatin and the topoisomerase inhibitor mitoxantrone, strongly up-regulate MHC-I AgPP in a manner dependent on activation of nuclear factor kappa B (NF-κB), p300/CBP, and other transcription factors, but independently of autocrine IFNγ signaling. Accordingly, NF-κB and p300 ablations prevent chemotherapy-induced MHC-I AgPP and abrogate rejection of low MHC-I-expressing tumors by reinvigorated CD8+ CTLs. Drugs like oxaliplatin and mitoxantrone may be used to overcome resistance to PD-(L)1 inhibitors in tumors that had "epigenetically down-regulated," but had not permanently lost MHC-I AgPP activity.

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study.

BACKGROUND: Nonprofit organizations are increasingly using social media to improve their communication strategies with the broader population. However, within the domain of human service nonprofits, there is hesitancy to fully use social media tools, and there is limited scope among organizational personnel in applying their potential beyond self-promotion and service advertisement. There is a pressing need for greater conceptual clarity to support education and training on the varied reasons for using social media to increase organizational outcomes. OBJECTIVE: This study leverages the potential of Twitter (subsequently rebranded as X [X Corp]) to examine the online communication content within a sample (n=133) of nonprofit sexual assault (SA) centers in Canada. To achieve this, we developed a typology using a qualitative and supervised machine learning model for the automatic classification of tweets posted by these centers. METHODS: Using a mixed methods approach that combines machine learning and qualitative analysis, we manually coded 10,809 tweets from 133 SA centers in Canada, spanning the period from March 2009 to March 2023. These manually labeled tweets were used as the training data set for the supervised machine learning process, which allowed us to classify 286,551 organizational tweets. The classification model based on supervised machine learning yielded satisfactory results, prompting the use of unsupervised machine learning to classify the topics within each thematic category and identify latent topics. The qualitative thematic analysis, in combination with topic modeling, provided a contextual understanding of each theme. Sentiment analysis was conducted to reveal the emotions conveyed in the tweets. We conducted validation of the model with 2 independent data sets. RESULTS: Manual annotation of 10,809 tweets identified seven thematic categories: (1) community engagement, (2) organization administration, (3) public awareness, (4) political advocacy, (5) support for others, (6) partnerships, and (7) appreciation. Organization administration was the most frequent segment, and political advocacy and partnerships were the smallest segments. The supervised machine learning model achieved an accuracy of 63.4% in classifying tweets. The sentiment analysis revealed a prevalence of neutral sentiment across all categories. The emotion analysis indicated that fear was predominant, whereas joy was associated with the partnership and appreciation tweets. Topic modeling identified distinct themes within each category, providing valuable insights into the prevalent discussions surrounding SA and related issues. CONCLUSIONS: This research contributes an original theoretical model that sheds light on how human service nonprofits use social media to achieve their online organizational communication objectives across 7 thematic categories. The study advances our comprehension of social media use by nonprofits, presenting a comprehensive typology that captures the diverse communication objectives and contents of these organizations, which provide content to expand training and education for nonprofit leaders to connect and engage with the public, policy experts, other organizations, and potential service users.

Bridging and Bonding Social Capital by Analyzing the Demographics, User Activities, and Social Network Dynamics of Sexual Assault Centers on Twitter: Mixed Methods Study.

BACKGROUND: Social media platforms have gained popularity as communication tools for organizations to engage with clients and the public, disseminate information, and raise awareness about social issues. From a social capital perspective, relationship building is seen as an investment, involving a complex interplay of tangible and intangible resources. Social media-based social capital signifies the diverse social networks that organizations can foster through their engagement on social media platforms. Literature underscores the great significance of further investigation into the scope and nature of social media use, particularly within sectors dedicated to service delivery, such as sexual assault organizations. OBJECTIVE: This study aims to fill a research gap by investigating the use of Twitter by sexual assault support agencies in Canada. It seeks to understand the demographics, user activities, and social network structure within these organizations on Twitter, focusing on building social capital. The research questions explore the demographic profile, geographic distribution, and Twitter activity of these organizations as well as the social network dynamics of bridging and bonding social capital. METHODS: This study used purposive sampling to investigate sexual assault centers in Canada with active Twitter accounts, resulting in the identification of 124 centers. The Twitter handles were collected, yielding 113 unique handles, and their corresponding Twitter IDs were obtained and validated. A total of 294,350 tweets were collected from these centers, covering >93.54% of their Twitter activity. Preprocessing was conducted to prepare the data, and descriptive analysis was used to determine the center demographics and age. Furthermore, geolocation mapping was performed to visualize the center locations. Social network analysis was used to explore the intricate relationships within the network of sexual assault center Twitter accounts, using various metrics to assess the network structure and connectivity dynamics. RESULTS: The results highlight the substantial presence of sexual assault organizations on Twitter, particularly in provinces such as Ontario, British Columbia, and Quebec, underscoring the importance of tailored engagement strategies considering regional disparities. The analysis of Twitter account creation years shows a peak in 2012, followed by a decline in new account creations in subsequent years. The monthly tweet activity shows November as the most active month, whereas July had the lowest activity. The study also reveals variations in Twitter activity, account creation patterns, and social network dynamics, identifying influential social queens and marginalized entities within the network. CONCLUSIONS: This study presents a comprehensive landscape of the demographics and activities of sexual assault centers in Canada on Twitter. This study suggests that future research should explore the long-term consequences of social media use and examine stakeholder perceptions, providing valuable insights to improve communication practices within the nonprofit human services sector and further the missions of these organizations.

Haplotype-resolved genome of a heterozygous wild peach reveals the PdaWRKY4-PdaCYP716A1 module mediates resistance to aphids by regulating betulin biosynthesis.

Wild species of domesticated crops provide valuable genetic resources for resistance breeding. Prunus davidiana, a wild relative of peach with high heterozygosity and diverse stress tolerance, exhibits high resistance against aphids. However, the highly heterozygous genome of P. davidiana makes determining the underlying factors influencing resistance traits challenging. Here, we present the 501.7 Mb haplotype-resolved genome assembly of P. davidiana. Genomic comparisons of the two haplotypes revealed 18,152 structural variations, 2,699 Pda_hap1-specific and 2,702 Pda_hap2-specific genes, and 1,118 allele-specific expressed genes. Genome composition indicated 4.1% of the P. davidiana genome was non-peach origin, out of which 94.5% was derived from almond. Based on the haplotype genome, the aphid resistance quantitative trait locus (QTL) was mapped at the end of Pda03. From the aphid resistance QTL, PdaWRKY4 was identified as the major dominant gene, with a 9-bp deletion in its promoter of the resistant phenotype. Specifically, PdaWRKY4 regulates aphid resistance by promoting PdaCYP716A1-mediated anti-aphid metabolite betulin biosynthesis. Moreover, we employed a genome design to develop a breeding workflow for rapidly and precisely producing aphid-resistant peaches. In conclusion, this study identifies a novel aphid resistance gene and provides insights into genome design for the development of resistant fruit cultivars.