Endocytosis in the axon initial segment maintains neuronal polarity.

Neurons are highly polarized cells that face the fundamental challenge of compartmentalizing a vast and diverse repertoire of proteins in order to function properly1. The axon initial segment (AIS) is a specialized domain that separates a neuron's morphologically, biochemically and functionally distinct axon and dendrite compartments2,3. How the AIS maintains polarity between these compartments is not fully understood. Here we find that in Caenorhabditis elegans, mouse, rat and human neurons, dendritically and axonally polarized transmembrane proteins are recognized by endocytic machinery in the AIS, robustly endocytosed and targeted to late endosomes for degradation. Forcing receptor interaction with the AIS master organizer, ankyrinG, antagonizes receptor endocytosis in the AIS, causes receptor accumulation in the AIS, and leads to polarity deficits with subsequent morphological and behavioural defects. Therefore, endocytic removal of polarized receptors that diffuse into the AIS serves as a membrane-clearance mechanism that is likely to work in conjunction with the known AIS diffusion-barrier mechanism to maintain neuronal polarity on the plasma membrane. Our results reveal a conserved endocytic clearance mechanism in the AIS to maintain neuronal polarity by reinforcing axonal and dendritic compartment membrane boundaries.

ZFX Mediates Non-canonical Oncogenic Functions of the Androgen Receptor Splice Variant 7 in Castrate-Resistant Prostate Cancer.

Androgen receptor splice variant 7 (AR-V7) is crucial for prostate cancer progression and therapeutic resistance. We show that, independent of ligand, AR-V7 binds both androgen-responsive elements (AREs) and non-canonical sites distinct from full-length AR (AR-FL) targets. Consequently, AR-V7 not only recapitulates AR-FL's partial functions but also regulates an additional gene expression program uniquely via binding to gene promoters rather than ARE enhancers. AR-V7 binding and AR-V7-mediated activation at these unique targets do not require FOXA1 but rely on ZFX and BRD4. Knockdown of ZFX or select unique targets of AR-V7/ZFX, or BRD4 inhibition, suppresses growth of castration-resistant prostate cancer cells. We also define an AR-V7 direct target gene signature that correlates with AR-V7 expression in primary tumors, differentiates metastatic prostate cancer from normal, and predicts poor prognosis. Thus, AR-V7 has both ARE/FOXA1 canonical and ZFX-directed non-canonical regulatory functions in the evolution of anti-androgen therapeutic resistance, providing information to guide effective therapeutic strategies.

Interrogating bromodomain inhibitor resistance in KMT2A-rearranged leukemia through combinatorial CRISPR screens.

Bromo- and extra-terminal domain inhibitors (BETi) have exhibited therapeutic activities in many cancers. However, the mechanisms controlling BETi response and resistance are not well understood. We conducted genome-wide loss-of-function CRISPR screens using BETi-treated KMT2A-rearranged (KMT2A-r) cell lines. We revealed that Speckle-type POZ protein (SPOP) gene (Speckle Type BTB/POZ Protein) deficiency caused significant BETi resistance, which was further validated in cell lines and xenograft models. Proteomics analysis and a kinase-vulnerability CRISPR screen indicated that cells treated with BETi are sensitive to GSK3 perturbation. Pharmaceutical inhibition of GSK3 reversed the BETi-resistance phenotype. Based on this observation, a combination therapy regimen inhibiting both BET and GSK3 was developed to impede KMT2A-r leukemia progression in patient-derived xenografts in vivo. Our results revealed molecular mechanisms underlying BETi resistance and a promising combination treatment regimen of ABBV-744 and CHIR-98014 by utilizing unique ex vivo and in vivo KMT2A-r PDX models.

Metabolic adaptation to tyrosine kinase inhibition in leukemia stem cells.

Tyrosine kinase inhibitors (TKIs) are very effective in treating chronic myelogenous leukemia (CML), but primitive, quiescent leukemia stem cells persist as a barrier to the cure. We performed a comprehensive evaluation of metabolic adaptation to TKI treatment and its role in CML hematopoietic stem and progenitor cell persistence. Using a CML mouse model, we found that glycolysis, glutaminolysis, the tricarboxylic acid cycle, and oxidative phosphorylation (OXPHOS) were initially inhibited by TKI treatment in CML-committed progenitors but were restored with continued treatment, reflecting both selection and metabolic reprogramming of specific subpopulations. TKI treatment selectively enriched primitive CML stem cells with reduced metabolic gene expression. Persistent CML stem cells also showed metabolic adaptation to TKI treatment through altered substrate use and mitochondrial respiration maintenance. Evaluation of transcription factors underlying these changes helped detect increased HIF-1 protein levels and activity in TKI-treated stem cells. Treatment with an HIF-1 inhibitor in combination with TKI treatment depleted murine and human CML stem cells. HIF-1 inhibition increased mitochondrial activity and reactive oxygen species (ROS) levels, reduced quiescence, increased cycling, and reduced the self-renewal and regenerating potential of dormant CML stem cells. We, therefore, identified the HIF-1-mediated inhibition of OXPHOS and ROS and maintenance of CML stem cell dormancy and repopulating potential as a key mechanism of CML stem cell adaptation to TKI treatment. Our results identify a key metabolic dependency in CML stem cells persisting after TKI treatment that can be targeted to enhance their elimination.

TREG cells and CXCR3+ circulating TFH cells concordantly shape the neutralizing antibody responses in individuals who have recovered from mild COVID-19.

Regulatory T (TREG) cells are involved in the antiviral immune response in patients with COVID-19; however, whether TREG cells are involved in the neutralizing antibody (nAb) response remains unclear. Here, we found that individuals who recovered from mild but not severe COVID-19 had significantly greater frequencies of TREG cells and lower frequencies of CXCR3+ circulating TFH (cTFH) cells than healthy controls. Furthermore, TREG and CXCR3+ cTFH cells were negatively and positively correlated with the nAb responses, respectively, and TREG cells was inversely associated with CXCR3+ cTFH cells in individuals who recovered from mild COVID-19 but not in those with severe disease. Mechanistically, TREG cells inhibited memory B-cell differentiation and antibody production by limiting the activation and proliferation of cTFH cells, especially CXCR3+ cTFH cells, and functional molecule expression. This study provides novel insight showing that mild COVID-19 elicits a concerted nAb responses which are shaped by both TREG and TFH cells.

Auxin biosynthesis gene FveYUC4 is critical for leaf and flower morphogenesis in woodland strawberry.

Auxin plays an essential role in plant growth and development, particularly in fruit development. The YUCCA (YUC) genes encode flavin monooxygenases that catalyze a rate-limiting step in auxin biosynthesis. Mutations that disrupt YUC gene function provide useful tools for dissecting general and specific functions of auxin during plant development. In woodland strawberry (Fragaria vesca), two ethyl methanesulfonate mutants, Y422 and Y1011, have been identified that exhibit severe defects in leaves and flowers. In particular, the width of the leaf blade is greatly reduced, and each leaflet in the mutants has fewer and deeper serrations. In addition, the number and shape of the floral organs are altered, resulting in smaller fruits. Mapping by sequencing revealed that both mutations reside in the FveYUC4 gene, and were therefore renamed as yuc4-1 and yuc4-2. Consistent with a role for FveYUC4 in auxin synthesis, free auxin and its metabolites are significantly reduced in the yuc4 leaves and flowers. This role of FveYUC4 in leaf and flower development is supported by its high and specific expression in young leaves and flower buds using GUS reporters. Furthermore, germline transformation of pYUC4::YUC4, which resulted in elevated expression of FveYUC4 in yuc4 mutants, not only rescued the leaf and flower defects but also produced parthenocarpic fruits. Taken together, our data demonstrate that FveYUC4 is essential for leaf and flower morphogenesis in woodland strawberry by providing auxin hormone at the proper time and in the right tissues.

Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening.

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

Ferrostatin-1 Inhibits Toll-Like Receptor 4/NF-κB Signaling to Alleviate Intervertebral Disc Degeneration in Rats.

Ferrostatin-1 (Fer-1), an inhibitor of ferroptosis, is implicated in intervertebral disc degeneration (IDD). The current study explored the role of Fer-1 in IDD via the toll-like receptor 4 (TLR4)/NF-κB signaling pathway. IDD-related gene expression microarray GSE124272 and high-throughput sequencing data set GSE175710 were obtained through the Gene Expression Omnibus database. Differentially expressed genes in IDD were identified, followed by implementation of protein-protein interaction network analysis and receiver operating characteristic curve analysis. The main pathways in IDD were obtained through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional analyses, and target genes of Fer-1 were obtained through PubChem and PharmMapper websites. Finally, GPX4, FTH, and TLR4 expression was determined in a IDD rat model. Three key co-expression modules involved in IDD were obtained through Weighted Gene Co-Expression Network Analysis. Thirteen differentially expressed genes were found to be associated with IDD, and eight key genes (TLR4, BCL2A1, CXCL1, IL1R1, NAMPT, SOCS3, XCL1, and IRAK3) were found to affect IDD. These eight key genes had the diagnostic potential for IDD. The NF-κB signaling pathway was shown to play a predominant role in IDD development. Network pharmacologic analysis indicated a role of Fer-1 in suppressing ferroptosis and ameliorating IDD via the TLR4/NF-κB signaling pathway, which was verified by an in vivo animal experiment. The study showed that Fer-1 down-regulates TLR4 to inactivate NF-κB signaling pathway, suppressing ferroptosis and ultimately alleviating IDD in rats.

Multi-omics analysis reveals spatiotemporal regulation and function of heteromorphic leaves in Populus.

Despite the high economic and ecological importance of forests, our knowledge of the adaptive evolution of leaf traits remains very limited. Euphrates poplar (Populus euphratica), which has high tolerance to arid environment, has evolved four heteromorphic leaf forms, including narrow (linear and lanceolate) and broad (ovate and broad-ovate) leaves on different crowns. Here, we revealed the significant functional divergence of four P. euphratica heteromorphic leaves at physiological and cytological levels. Through global analysis of transcriptome and DNA methylation across tree and leaf developmental stages, we revealed that gene expression and DNA epigenetics differentially regulated key processes involving development and functional adaptation of heteromorphic leaves, such as hormone signaling pathways, cell division, and photosynthesis. Combined analysis of gene expression, methylation, ATAC-seq, and Hi-C-seq revealed longer interaction of 3D genome, hypomethylation, and open chromatin state upregulates IAA-related genes (such as PIN-FORMED1 and ANGUSTIFOLIA3) and promotes the occurrence of broad leaves while narrow leaves were associated with highly concentrated heterochromatin, hypermethylation, and upregulated abscisic acid pathway genes (such as Pyrabactin Resistance1-like10). Therefore, development of P. euphratica heteromorphic leaves along with functional divergence was regulated by differentially expressed genes, DNA methylation, chromatin accessibility, and 3D genome remodeling to adapt to the arid desert. This study advances our understanding of differential regulation on development and functional divergence of heteromorphic leaves in P. euphratica at the multi-omics level and provides a valuable resource for investigating the adaptive evolution of heteromorphic leaves in Populus.

Phosphorylation of WRKY16 by MPK3-1 is essential for its transcriptional activity during fiber initiation and elongation in cotton (Gossypium hirsutum).

Cotton, one of the most important crops in the world, produces natural fiber materials for the textile industry. WRKY transcription factors play important roles in plant development and stress responses. However, little is known about whether and how WRKY transcription factors regulate fiber development of cotton so far. In this study, we show that a fiber-preferential WRKY transcription factor, GhWRKY16, positively regulates fiber initiation and elongation. GhWRKY16-silenced transgenic cotton displayed a remarkably reduced number of fiber protrusions on the ovule and shorter fibers compared to the wild-type. During early fiber development, GhWRKY16 directly binds to the promoters of GhHOX3, GhMYB109, GhCesA6D-D11, and GhMYB25 to induce their expression, thereby promoting fiber initiation and elongation. Moreover, GhWRKY16 is phosphorylated by the mitogen-activated protein kinase GhMPK3-1 at residues T-130 and S-260. Phosphorylated GhWRKY16 directly activates the transcription of GhMYB25, GhHOX3, GhMYB109, and GhCesA6D-D11 for early fiber development. Thus, our data demonstrate that GhWRKY16 plays a crucial role in fiber initiation and elongation, and that GhWRKY16 phosphorylation by GhMPK3-1 is essential for the transcriptional activation on downstream genes during the fiber development of cotton.

Effect of frozen-thawed embryo transfer with a poor-quality embryo and a good-quality embryo on pregnancy and neonatal outcomes.

BACKGROUND: To evaluate the impact of embryo quality and quantity, specifically a poor quality embryo (PQE) in combination with a good quality embryo (GQE), by double embryo transfer (DET) on the live birth rate (LBR) and neonatal outcomes in patients undergoing frozen-thawed embryo transfer (FET) cycles. METHODS: A study on a cohort of women who underwent a total of 1462 frozen-thawed cleavage or blastocyst embryo transfer cycles with autologous oocytes was conducted between January 2018 and December 2021. To compare the outcomes between single embryo transfer (SET) with a GQE and DET with a GQE and a PQE, propensity score matching (PSM) was applied to control for potential confounders, and a generalized estimating equation (GEE) model was used to determine the association between the effect of an additional PQE and the outcomes. Subgroup analysis was also performed for patients stratified by female age. RESULTS: After PS matching, DET-GQE + PQE did not significantly alter the LBR (adjusted odds ratio [OR] 1.421, 95% CI 0.907-2.228) compared with SET-GQE in cleavage-stage embryo transfer but did increase the multiple birth rate (MBR, [OR] 3.917, 95% CI 1.189-12.911). However, in patients who underwent blastocyst-stage embryo transfer, adding a second PQE increased the live birth rate by 7.8% ([OR] 1.477, 95% CI 1.046-2.086) and the multiple birth rate by 19.6% ([OR] 28.355, 95% CI 3.926-204.790), and resulted in adverse neonatal outcomes. For patients who underwent cleavage-stage embryo transfer, transferring a PQE with a GQE led to a significant increase in the MBR ([OR] 4.724, 95% CI 1.121-19.913) in women under 35 years old but not in the LBR ([OR] 1.227, 95% CI 0.719-2.092). The increases in LBR and MBR for DET-GQE + PQE compared with SET-GQE in women older than 35 years were nonsignificant toward. For patients who underwent blastocyst-stage embryo transfer, DET-GQE + PQE had a greater LBR ([OR] 1.803, 95% CI 1.165-2.789), MBR ([OR] 24.185, 95% CI 3.285-178.062) and preterm birth rate (PBR, [OR] 4.092, 95% CI 1.153-14.518) than did SET-GQE in women under 35 years old, while no significant impact on the LBR ([OR] 1.053, 95% CI 0.589-1.884) or MBR (0% vs. 8.3%) was observed in women older than 35 years. CONCLUSIONS: The addition of a PQE has no significant benefit on the LBR but significantly increases the MBR in patients who underwent frozen-thawed cleavage-stage embryo transfer. However, for patients who underwent blastocyst-stage embryo transfer, DET-GQE + PQE resulted in an increase in both the LBR and MBR, which may lead to adverse neonatal outcomes. Thus, the benefits and risks of double blastocyst-stage embryo transfer should be balanced. In patients younger than 35 years, SET-GQE achieved satisfactory LBR either in cleavage-stage embryo transfer or blastocyst-stage embryo transfer, while DET-GQE + PQE resulted in a dramatically increased MBR. Considering the low LBR in women older than 35 years who underwent single cleavage-stage embryo transfer, selective single blastocyst-stage embryo transfer appears to be a more promising approach for reducing the risk of multiple live births and adverse neonatal outcomes.

Expression of a single-chain monellin (MNEI) mutant with enhanced stability in transgenic mice milk.

Monellin is a sweet protein that may be used as a safe and healthy sweetener. However, due to its low stability, the application of monellin is currently very limited. Here, we describe a wild-type, a double-sites mutant (E2N/E23A) and a triple-sites mutant (N14A/E23Q/S76Y) of single-chain monellin (MNEI) expressed in transgenic mice milk. Based on enzyme-linked immunoassay (ELISA), Western blot, and sweetness intensity testing, their sweetness and stability were compared. After boiling for 2 min at different pH conditions (2.5, 5.1, 6.8, and 8.2), N14A/E23Q/S76Y-MNEI showed significantly higher sweetness and stability than the wild-type and E2N/E23A-MNEI. These results suggest that N14A/E23Q/S76Y-MNEI shows remarkable potential as a sweetener in the future.

Structural basis for DNMT3A-mediated de novo DNA methylation.

DNA methylation by de novo DNA methyltransferases 3A (DNMT3A) and 3B (DNMT3B) at cytosines is essential for genome regulation and development. Dysregulation of this process is implicated in various diseases, notably cancer. However, the mechanisms underlying DNMT3 substrate recognition and enzymatic specificity remain elusive. Here we report a 2.65-ångström crystal structure of the DNMT3A-DNMT3L-DNA complex in which two DNMT3A monomers simultaneously attack two cytosine-phosphate-guanine (CpG) dinucleotides, with the target sites separated by 14 base pairs within the same DNA duplex. The DNMT3A-DNA interaction involves a target recognition domain, a catalytic loop, and DNMT3A homodimeric interface. Arg836 of the target recognition domain makes crucial contacts with CpG, ensuring DNMT3A enzymatic preference towards CpG sites in cells. Haematological cancer-associated somatic mutations of the substrate-binding residues decrease DNMT3A activity, induce CpG hypomethylation, and promote transformation of haematopoietic cells. Together, our study reveals the mechanistic basis for DNMT3A-mediated DNA methylation and establishes its aetiological link to human disease.

Dynamic accuracy measurement method for star trackers using a time-synchronized high-accuracy turntable.

Star trackers are typically used in a spacecraft to provide absolute attitude information to the on-board attitude control system so as to promote high accuracy. The performance of the star tracker is rather important. Attitude incorrectness provided by star trackers may lead to bad navigation with big deviations, even failure of satellites. Therefore, how to realize and verify the accuracy is crucial. As a matter of fact, it is difficult to validate accuracy of star trackers on the ground, especially for star trackers under highly dynamic conditions. In this paper, an accuracy measurement method for star trackers under dynamic conditions is proposed, utilizing a high-accuracy swing table to provide reference to compare. To this end, a swing table, star tracker, and the test equipment are synchronized, in order to reduce systematic errors. As the motion trajectory of the swing table can be set beforehand, the initial attitude of the star tracker can be predicted through a set of coordinate transformations. As a result, the star tracker is able to keep tracking, regardless of the angular velocity of the swing table. This makes the statistical sample points more sufficient and the results more reliable. Moreover, it can evaluate the angular velocity of star trackers up to 20°/s. In comparison with the conventional method with simulated stars, this method utilizes real navigation stars as observation targets making the measurement results much closer to the on-orbit performance. Lastly, but much more importantly, it can also verify the performance of a star tracker in one experiment, such as sensitivity, static performance, capture probability, and so on. Experimental results demonstrate that the proposed method is effective, especially for highly dynamic star trackers. Such a measurement environment is close to the in-orbit conditions, and it can satisfy the stringent requirement for star trackers under high dynamics.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

HOXA9 Regulome and Pharmacological Interventions in Leukemia.

HOXA9, an important transcription factor (TF) in hematopoiesis, is aberrantly expressed in numerous cases of both acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) and is a strong indicator of poor prognosis in patients. HOXA9 is a proto-oncogene which is both sufficient and necessary for leukemia transformation. HOXA9 expression in leukemia correlates with patient survival outcomes and response to therapy. Chromosomal transformations (such as NUP98-HOXA9), mutations, epigenetic dysregulation (e.g., MLL- MENIN -LEDGF complex or DOT1L/KMT4), transcription factors (such as USF1/USF2), and noncoding RNA (such as HOTTIP and HOTAIR) regulate HOXA9 mRNA and protein during leukemia. HOXA9 regulates survival, self-renewal, and progenitor cell cycle through several of its downstream target TFs including LMO2, antiapoptotic BCL2, SOX4, and receptor tyrosine kinase FLT3 and STAT5. This dynamic and multilayered HOXA9 regulome provides new therapeutic opportunities, including inhibitors targeting DOT1L/KMT4, MENIN, NPM1, and ENL proteins. Recent findings also suggest that HOXA9 maintains leukemia by actively repressing myeloid differentiation genes. This chapter summarizes the recent advances understanding biochemical mechanisms underlying HOXA9-mediated leukemogenesis, the clinical significance of its abnormal expression, and pharmacological approaches to treat HOXA9-driven leukemia.

The Molecular and Biological Function of MEF2D in Leukemia.

Myocyte enhancer factor 2 (MEF2) is a key transcription factor (TF) in skeletal, cardiac, and neural tissue development and includes four isoforms: MEF2A, MEF2B, MEF2C, and MEF2D. These isoforms significantly affect embryonic development, nervous system regulation, muscle cell differentiation, B- and T-cell development, thymocyte selection, and effects on tumorigenesis and leukemia. This chapter describes the multifaceted roles of MEF2 family proteins, covering embryonic development, nervous system regulation, and muscle cell differentiation. It further elucidates the contribution of MEF2 to various blood and immune cell functions. Specifically, in B-cell precursor acute lymphoblastic leukemia (BCP-ALL), MEF2D is aberrantly expressed and forms a fusion protein with BCL9, CSF1R, DAZAP1, HNRNPUL1, and SS18. These fusion proteins are closely related to the pathogenesis of leukemia. In addition, it specifically introduces the regulatory effect of MEF2D fusion protein on the proliferation and growth of B-cell acute lymphoblastic leukemia (B-ALL) cells. Finally, we detail the positive feedback loop between MEF2D and IRF8 that significantly promotes the progression of acute myeloid leukemia (AML) and the importance of the ZMYND8-BRD4 interaction in regulating the IRF8 and MYC transcriptional programs. The MEF2D-CEBPE axis is highlighted as a key transcriptional mechanism controlling the block of leukemic cell self-renewal and differentiation in AML. This chapter starts with the structure and function of MEF2 family proteins, specifically summarizing and analyzing the role of MEF2D in B-ALL and AML, mediating the complex molecular mechanisms of transcriptional regulation and exploring their implications for human health and disease.

Impact of Continuous Nursing on Quality of Life and Psychological Well-being in Advanced Lung Cancer Patients.

Objectives: This study aimed to analyze the psychological status and quality of life (QoL) of patients with advanced lung cancer and assess the impact of continuous nursing intervention on these parameters. Methods: A total of 160 advanced lung cancer patients were randomly assigned to a control group or a study group, with 80 patients in each. The control group received the routine nursing intervention, while the study group received the continuous nursing intervention, including health record establishment, regular follow-ups, diet guidance, health knowledge education, psychological counseling, and work and rest guidance. Inflammatory markers (IL-6, TNF-α, PGE2, and SP), Spitzer Quality of Life Index (SQLI), anxiety and depression self-evaluation scales, Visual Analogue Scale (VAS) for pain, and patient satisfaction were measured before and after 4 weeks of intervention. Results: Post-intervention, the study group showed a significant reduction in serum IL-6 and TNF-α levels (P < .001), improved SQLI scores (P = .002), and lower anxiety and depression scores (P < .001) compared to the control group. A significant negative correlation between psychological status and QoL was observed (P < .001). The study group also reported lower VAS pain scores (P < .001) and higher patient satisfaction (P = .000) after the intervention. Conclusions: Continuous nursing intervention has significantly improved psychological well-being, alleviated pain, and enhanced the overall quality of life for patients facing advanced lung cancer. These results indicate that a comprehensive and sustained nursing intervention strategy can serve as an effective approach to improve the well-being of individuals navigating advanced lung cancer during chemotherapy.

Unraveling the Molecular Basis of Color Variation in Dioscorea alata Tubers: Integrated Transcriptome and Metabolomics Analysis.

Dioscorea alata L. (Dioscoreaceae) is a widely cultivated tuber crop with variations in tuber color, offering potential value as health-promoting foods. This study focused on the comparison of D. alata tubers possessing two distinct colors, white and purple, to explore the underlying mechanisms of color variation. Flavonoids, a group of polyphenols known to influence plant color and exhibit antioxidant properties, were of particular interest. The total phenol and total flavonoid analyses revealed that purple tubers (PTs) have a significantly higher content of these metabolites than white tubers (WTs) and a higher antioxidant activity than WTs, suggesting potential health benefits of PT D. alata. The transcriptome analysis identified 108 differentially expressed genes associated with the flavonoid synthesis pathway, with 57 genes up-regulated in PTs, including CHS, CHI, DFR, FLS, F3H, F3'5'H, LAR, ANS, and ANR. The metabolomics analysis demonstrated that 424 metabolites, including 104 flavonoids and 8 tannins, accumulated differentially in PTs and WTs. Notably, five of the top ten up-regulated metabolites were flavonoids, including 6-hydroxykaempferol-7-O-glucoside, pinocembrin-7-O-(6″-O-malonyl)glucoside, 6-hydroxykaempferol-3,7,6-O-triglycoside, 6-hydroxykaempferol-7-O-triglycoside, and cyanidin-3-O-(6″-O-feruloyl)sophoroside-5-O-glucoside, with the latter being a precursor to anthocyanin synthesis. Integrating transcriptome and metabolomics data revealed that the 57 genes regulated 20 metabolites within the flavonoid synthesis pathway, potentially influencing the tubers' color variation. The high polyphenol content and antioxidant activity of PTs indicate their suitability as nutritious and health-promoting food sources. Taken together, the findings of this study provide insights into the molecular basis of tuber color variation in D. alata and underscore the potential applications of purple tubers in the food industry and human health promotion. The findings contribute to the understanding of flavonoid biosynthesis and pigment accumulation in D. alata tubers, opening avenues for future research on enhancing the nutritional quality of D. alata cultivars.