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Abstract In the present work, we investigate the productions of $$X_0(2900)$$ X 0 ( 2900 ) and its spin partners in the $$B^+$$ B + decay processes, where $$X_0(2900)$$ X 0 ( 2900 ) is regarded as a $$\bar{D}^*K^*$$ D ¯ ∗ K ∗ molecular state. We infer that the initial $$B^+$$ B + meson and the final $$D^+ X_0(2900)$$ D + X 0 ( 2900 ) are connected through the $$D_{s1}^{\prime +}(2460) \bar{D}^{*0} $$ D s 1 ′ + ( 2460 ) D ¯ ∗ 0 mesons by exchanging a $$K^{*0}$$ K ∗ 0 meson. The contributions of such a meson loop to the process $$B^+ \rightarrow D^+ X_0(2900)$$ B + → D + X 0 ( 2900 ) are evaluated and our estimations indicate that the measured branching fraction of $$B^+\rightarrow D^+ X_0(2900)$$ B + → D + X 0 ( 2900 ) could be well reproduced in a reasonable range of model parameters, indicating that $$X_0(2900)$$ X 0 ( 2900 ) could be interpreted as a $$\bar{D}^*K^*$$ D ¯ ∗ K ∗ molecular state. In addition, the production processes $$B^+ \rightarrow D^+ \tilde{X}_{1,2}$$ B + → D + X ~ 1 , 2 , $$B^+ \rightarrow D^{*+} X_0(2900)$$ B + → D ∗ + X 0 ( 2900 ) , and $$B^+ \rightarrow D^{*+}\tilde{X}_{1,2}$$ B + → D ∗ + X ~ 1 , 2 are investigated, and we find that the fit fraction of $$\tilde{X}_1$$ X ~ 1 in the process $$B^+ \rightarrow D^{*+} D^{*-} K^+$$ B + → D ∗ + D ∗ - K + is about 6%, which should be accessible by the LHCb and Belle II Collaborations.

Neomicrocalamus and Temochloa are closely-related genera for which ‘inflorescence’ structures were incompletely understood and difficult to reconcile. After re-examining the inflorescence morphology, the so-called ‘spikelets’ of both genera as described should instead be recognised as pseudospikelets with mostly inactive axillary buds. The new bamboo taxa, comprising two varieties of a new species, are placed in Temochloa, representing a new genus record for China and Vietnam.

Abstract We investigate the growth of operator size in the Lindbladian Sachdev-Ye-Kitaev model with q-body interaction terms and linear jump terms at finite dissipation strength. We compute the operator size as well as its distribution numerically at finite q and analytically at large q. With dissipative (productive) jump terms, the size converges to a value smaller (larger) than half the number of Majorana fermions. At weak dissipation, the evolution of operator size displays a quadratic-exponential-plateau behavior. The plateau value is determined by the ratios between the coupling of the interaction and the linear jump term in the large q limit. The operator size distribution remains localized in the finite size region even at late times, contrasting with the unitary case. Moreover, we also derived the time-independent orthogonal basis for operator expansion which exhibits the operator size concentration at finite dissipation. Finally, we observe that the uncertainty relation for operator size growth is saturated at large q, leading to classical dynamics of the operator size growth with dissipation.

Abstract The purpose of signal control is to allocate time for competing traffic flows to ensure safety. Artificial intelligence has made transportation researchers more interested in adaptive traffic signal control, and recent literature confirms that deep reinforcement learning (DRL) can be effectively applied to adaptive traffic signal control. Deep neural networks enhance the learning potential of reinforcement learning. This study applies the DRL method, Double Deep Q‐Network, to train local agents. Each local agent learns independently to accommodate the regional traffic flows and dynamics. After completing the learning, a global agent is created to integrate and unify the action policies selected by each local agent to achieve the purpose of traffic signal coordination. Traffic flow conditions are simulated through the simulation of urban mobility. The benefits of the proposed approach include improving the efficiency of intersections and minimizing the overall average waiting time of vehicles. The proposed multi‐agent reinforcement learning model significantly improves the average vehicle waiting time and queue length compared with the results from PASSER‐V and pre‐timed signal setting strategies.

Abstract In the framework of double holography, we investigate the entanglement behavior of a subregion of the defect on the boundary of a CFT3. The entanglement entropy of this defect subregion is determined by the quantum extremal surface (QES) anchored at the two endpoints of the subregion from the brane perspective. We further analyze the entanglement entropy of the quantum matter within this QES, which can be extracted from the total entanglement entropy. We find there are two phases of the QES. To numerically distinguish these phases, we design a strategy for approaching the QES by progressively reducing the width of a semi-ellipse-like region within the CFT3, which is bounded by the defect. During this process, we discover an entanglement phase transition driven by the degree of freedom on the brane. In the shrinking phase, the entanglement wedge of the defect subregion sharply decreases to zero as the removal of the CFT3. In contrast, in the stable phase, the wedge almost remains constant. In this phase, the formulas of entanglement measures can be derived based on defect and CFT3 central charges in the semi-classical limit. For entanglement entropy, the classical geometry only contributes a subleading term with logarithmic divergence, but the matter entanglement exhibits a dominant linear divergence, even in the semi-classical limit. For the reflected entropy within the defect subregion, classical geometry contributes a leading term with logarithmic divergence, while the quantum matter within the entanglement wedge only contributes a finite term.

Abstract Although multiple myeloma (MM) responds well to immunotherapeutic treatment, certain portions of MM are still unresponsive or relapse after immunotherapy. Other immune molecules are needed for the immunotherapy of MM. Here, we revealed that leukocyte immunoglobulin-like receptor B4 (LILRB4) was highly expressed in multiple myeloma cell lines and patient samples and that the expression of LILRB4 was adversely correlated with the overall survival of MM patients. Knockdown of LILRB4 efficiently delayed the growth of MM cells both in vitro and in vivo. Mechanistically, IKZF1 transactivated LILRB4 expression to trigger the downstream of STAT3-PFKFB1 pathways to support MM cell proliferation. Blockade of LILRB4 signaling by blocking antibodies can effectively inhibit MM progression. Our data show that targeting LILRB4 is potentially an additional therapeutic strategy for the immunotherapeutic treatment of MM.

Abstract We investigate the evolution of entanglement within an open, strongly coupled system interacting with a heat bath as its environment, in the frameworks of both the doubly holographic model and the Sachdev-Ye-Kitaev (SYK) model. Generally, the entanglement within the system initially increases as due to internal interactions; however, it eventually dissipates into the environment. In the doubly holographic setup, we consider an end-of-the-world brane in the bulk to represent an eternal black hole coupled with its radiation and the evolution of the global thermofield double (TFD) state. For small black holes, the reflected entropy between the bipartition exhibits a ramp-plateau-slump behavior, where the plateau arises due to the phase transition of the entanglement wedge cross-section before the Page time. Similarly, the mutual information between the bipartition displays a ramp-slop-stabilizing behavior. In quantum mechanics, we consider a double copy of the SYK-plus-bath system in a global TFD state, resembling an eternal black hole interacting with an environment. The Rényi mutual information within the double-copied SYK clusters exhibits a ramp-plateau-slope-stabilizing behavior. The dynamic behaviors of the entanglement quantities observed in these two models are attributable to the competition between the internal interaction of the system and the external interaction with the baths. Our study provides a fine-grained picture of the entanglement dynamics inside black holes before their Page time.

Abstract Objectives To noninvasively detect prostate cancer and predict the Gleason grade using single-modality T2-weighted imaging with a deep-learning approach. Methods Patients with prostate cancer, confirmed by histopathology, who underwent magnetic resonance imaging examinations at our hospital during September 2015–June 2022 were retrospectively included in an internal dataset. An external dataset from another medical center and a public challenge dataset were used for external validation. A deep-learning approach was designed for prostate cancer detection and Gleason grade prediction. The area under the curve (AUC) was calculated to compare the model performance. Results For prostate cancer detection, the internal datasets comprised data from 195 healthy individuals (age: 57.27 ± 14.45 years) and 302 patients (age: 72.20 ± 8.34 years) diagnosed with prostate cancer. The AUC of our model for prostate cancer detection in the validation set (n = 96, 19.7%) was 0.918. For Gleason grade prediction, datasets comprising data from 283 of 302 patients with prostate cancer were used, with 227 (age: 72.06 ± 7.98 years) and 56 (age: 72.78 ± 9.49 years) patients being used for training and testing, respectively. The external and public challenge datasets comprised data from 48 (age: 72.19 ± 7.81 years) and 91 patients (unavailable information on age), respectively. The AUC of our model for Gleason grade prediction in the training set (n = 227) was 0.902, whereas those of the validation (n = 56), external validation (n = 48), and public challenge validation sets (n = 91) were 0.854, 0.776, and 0.838, respectively. Conclusion Through multicenter dataset validation, our proposed deep-learning method could detect prostate cancer and predict the Gleason grade better than human experts. Critical relevance statement Precise prostate cancer detection and Gleason grade prediction have great significance for clinical treatment and decision making. Key Points Prostate segmentation is easier to annotate than prostate cancer lesions for radiologists. Our deep-learning method detected prostate cancer and predicted the Gleason grade, outperforming human experts. Non-invasive Gleason grade prediction can reduce the number of unnecessary biopsies. Graphical Abstract

Abstract Liquid–liquid phase separation (LLPS) has emerged as a pivotal biological phenomenon involved in various cellular processes, including the formation of membrane‐less organelles and the regulation of biomolecular condensates through precise spatiotemporal coordination of signaling pathways in cells. Dysregulation of LLPSs results in aberrant biomolecular condensates, which are widely implicated in tumorigenesis and cancer progression. Here, we comprehensively summarize the multifaceted roles of LLPS in tumor biology from the perspective of cancer hallmarks, including genomic stability, metabolic reprogramming progression, ferroptosis, and metastasis, to unveil the intricate mechanisms by which LLPS occurs in tumorigenesis. We discuss current discoveries related to therapeutic involvement and potential clinical applications of LLPS in cancer treatment, highlighting the potential of targeting LLPS‐driven processes as novel therapeutic strategies. Additionally, we discuss the challenges associated with new approaches for cancer treatment based on LLPS. This in‐depth discussion of the impact of LLPS on fundamental aspects of tumor biology provides new insights into overcoming cancer.

Trachinotus ovatus, a valuable marine fish, is primarily farmed in the South China Sea. Intensive aquaculture can lead to genetic uniformity and disease risks. Additionally, the high cost of genome sequencing restricts knowledge of genetic variation, hindering genetic analysis and breeding advancements. This study investigated the genetic diversity and structure of Trachinotus ovatus populations within the South China Sea aquaculture context, with the goal of strengthening sustainability. Additionally, the study also enhanced breeding strategies by developing a high-quality haplotype reference panel and an efficient imputation process. Through high-throughput sequencing (depth＞20X), 173 samples from three key breeding sites (SanYa, Hainan; Zhanjiang, Guangdong; and Beihai, Guangxi) were analyzed, revealing substantial genetic diversity and distinct population structures. Notably, the Beihai (BH) population exhibited significant stratification, suggesting regional genetic uniqueness. Low levels of genomic inbreeding coefficient and the identification of unique SNP loci across populations underscored the genetic richness within these Trachinotus ovatus communities. A major constructed of this work is the creation of the first high-quality haplotype reference panel for the species, demonstrating genotype imputation's viability as a cost-effective alternative for large-scale genetic studies in aquaculture. In particular, a Shapeit reference panel with 5476,550 SNPs was created, excelling in accuracy across various depths, notably achieving up to 95.8 % imputation accuracy at 1X sequencing depth. This high accuracy across populations shows the importance of genetic diversity in the panel. This research not only advances the understanding of Trachinotus ovatus genetic foundations but also provides crucial insights for conservation efforts and genetic analysis. By establishing a robust haplotype reference panel for Trachinotus ovatus helps lower the costs of future genetic research and variation studies, this study lays the foundation for sustainable aquaculture practices and breeding programs.

Abstract Recent developments in menin inhibitors for relapsed or refractory acute myeloid leukemia (AML) were highlighted at the 2023 ASH Annual Meeting. Notably, revumenib showed promising efficacy, achieving a 100% ORR when combined with decitabine/cedazuridine and venetoclax. These findings underscore the potential of menin inhibitors in transforming AML treatment, particularly in genetically defined subgroups, offering hope for improved patient outcomes. Ongoing studies, like KOMET-008, further explore the synergistic potential of menin inhibitors in combination regimens, shaping future AML management strategies.

The heart and brain are important organs of human body, which are closely related in genetic, structural and functional aspects. It is of great significance to elucidate the correlation between heart and brain and its mechanism for prevention and treatment of cardiovascular and cerebrovascular diseases. This paper reviews the genetic, structural and functional correlations between heart and brain, and discusses mechanisms of correlations from the perspective of common clinical heart diseases and brain diseases, so as to provide theoretical basis for the research and treatment of brain and heart comorbidity.

Key Clinical Message Acute chest pain can be the first manifestation of multiple endocrine neoplasia type 1(MEN1)‐associated thymic neuroendocrine neoplasms (NEN). Comprehensive treatment may be an effective strategy for MEN1‐associated NEN. Abstract Multiple endocrine neoplasia type 1(MEN1)‐associated thymic neuroendocrine neoplasms (NEN) is caused by the mutation of tumor suppressor MEN1 gene. Patients with MEN1‐associated NEN initially presenting with acute chest pain are very rare. In the manuscript, we reported a case of a 45‐year‐old man who developed MEN1‐associated NEN with acute chest pain as initial symptom. Thoracoscopic thymotomy was performed and thymic NEN was successfully removed. Genetic test showed a germline mutation of MEN1 gene in this patient. Immunohistochemical staining exhibited Syn(+), CgA(+), INSM1(+), CD56(+) and Ki67‐positive cells (2%) in MEN1‐associated NEN. Further evaluation unveiled MEN1‐associated benign tumors including digestive NEN and pituitary gland adenoma. The 99mTc‐HYNIC‐TOC scintigraphy showed that focally increased radioactivity in the mid‐upper abdomen. This patient was administered with 50Gy/25F of radiation dose to treat the postoperative lesions. Subsequently, sandostatin LAR (30 mg per week) was used as systemic therapy. He had no recurrence or metastasis for 6‐month follow‐up. Thus, acute chest pain can be the first manifestation of MEN1‐associated NEN, and comprehensive treatment including surgery, radiation and systemic treatment may be an effective strategy for MEN1‐associated NEN.

Background S100a8/9 (S100 calcium binding protein a8/9) belongs to the S100 family and has gained a lot of interest as a critical regulator of inflammatory response. Our previous study found that S100a8/9 homolog promoted aortic valve sclerosis in mice with chronic kidney disease. However, the role of S100a8/9 in pressure overload‐induced cardiac hypertrophy remains unclear. The present study was to explore the role of S100a8/9 in cardiac hypertrophy. Methods and Results Cardiomyocyte‐specific S100a9 loss or gain of function was achieved using an adeno‐associated virus system, and the model of cardiac hypertrophy was established by aortic banding‐induced pressure overload. The results indicate that S100a8/9 expression was increased in response to pressure overload. S100a9 deficiency alleviated pressure overload‐induced hypertrophic response, whereas S100a9 overexpression accelerated cardiac hypertrophy. S100a9‐overexpressed mice showed increased FGF23 (fibroblast growth factor 23) expression in the hearts after exposure to pressure overload, which activated calcineurin/NFAT (nuclear factor of activated T cells) signaling in cardiac myocytes and thus promoted hypertrophic response. A specific antibody that blocks FGFR4 (FGF receptor 4) largely abolished the prohypertrophic response of S100a9 in mice. Conclusions In conclusion, S100a8/9 promoted the development of cardiac hypertrophy in mice. Targeting S100a8/9 may be a promising therapeutic approach to treat cardiac hypertrophy.

Abstract Smart city construction is crucial for regional economic development, and the micro-level impact of such construction on business operations cannot be ignored. Based on the panel data of Shanghai and Shenzhen A-share listed companies from 2008 to 2020, this paper investigates the relationship between smart city construction and firm performance and its mechanism of action. The study findings show that (1) smart city construction significantly improves enterprise performance; (2) the improvements are significant across all industries and regions; and (3) the impact of smart city construction on small and medium-sized enterprises (SMEs) and nonstate enterprises is more significant than that on large enterprises and state-owned enterprises. These findings provide a theoretical framework and fresh perspectives for encouraging coordinated regional development and new urbanization construction.

Abstract Background RAS mutations affect prognosis in patients with metastatic colorectal cancer (mCRC) and have been identified as strong negative predictive markers for anti-epidermal growth factor receptor monoclonal antibody (anti-EGFR mAb) therapy, but many tumors containing wild-type RAS genes still do not respond to these therapies. Some additional biomarkers may have prognostic or predictive roles, but conclusions remain controversial. Methods We performed a meta-analysis and systematic review of randomized controlled trials comparing anti-EGFR mAb therapy with alternative therapy that investigated the prognostic and predictive impact of additional biomarkers in RAS wild-type (wt) mCRC patients. Hazard ratios (HRs) and 95% confidence intervals (CIs) for progression-free survival (PFS) and overall survival (OS) and odds ratios (ORs) for objective response rate (ORR) were calculated. The prognostic value of biomarkers was investigated by separately pooling HR and OR for different treatment groups in an individual study. The predictive value was assessed by pooling study interactions between treatment effects and biomarker subgroups. Results Thirty publications reporting on eighteen trials were selected, including a total of 13,507 patients. In prognostic analysis, BRAF mutations were associated with poorer PFS [HRs = 3.76 (2.47–5.73) and 2.69 (1.82–3.98)] and OS [HRs = 2.66 (1.95–3.65) and 2.45 (1.55–3.88)] in both the experimental and control arms; low miR-31-3p expression appeared to have longer PFS and OS. In terms of predictive effect, a lack of response to anti-EGFR therapy was observed in patients with BRAF mutant tumors (P interaction

Hepatocellular carcinoma (HCC) is a highly aggressive liver malignancy and one of the most lethal cancers globally, with limited effective therapeutic options. Bile acids (BAs), as primary metabolites of hepatic cholesterol, undergo enterohepatic circulation involving secretion into the intestine and reabsorption into the liver, and their composition is modulated in this process. Recent clinical observations have revealed a correlation between alteration in the BAs profile and HCC incidence, and the effect of various species of BAs on HCC development has been investigated. The regulatory effect of different BA species on cell proliferation, migration, and apoptosis in tumor cells, as well as their interaction with gut microbiota, inflammation, and immunity have been identified to be involved in HCC progression. In this review, we summarize the current understanding of the diverse functions of BAs in HCC pathogenesis and therapy, from elucidating the fundamental mechanisms underlying both tumor-promoting and tumor-suppressive consequences of various BA species to exploring potential strategies for leveraging BAs for HCC therapy. We also discuss ongoing efforts to target specific BA species in HCC treatment while highlighting new frontiers in BA biology that may inspire further exploration regarding their connection to HCC.

The GATA gene family belongs to a kind of transcriptional regulatory protein featuring a zinc finger motif, which is essential for plant growth and development. However, the identification of the GATA gene family in tetraploid potato is still not performed. In the present research, a total of 88 GATA genes in the tetraploid potato C88.v1 genome were identified by bioinformatics methods. These StGATA genes had an uneven distribution on 44 chromosomes, and the corresponding StGATA proteins were divided into four subfamilies (I-IV) based on phylogenetic analysis. The cis-elements of StGATA genes were identified, including multiple cis-elements related to light-responsive and hormone-responsive. The collinearity analysis indicates that segmental duplication is a key driving force for the expansion of GATA gene family in tetraploid potato, and that the GATA gene families of tetraploid potato and Arabidopsis share a closer evolutionary relationship than rice. The transcript profiling analysis showed that all 88 StGATA genes had tissue-specific expression, indicating that the StGATA gene family members participate in the development of multiple potato tissues. The RNA-seq analysis was also performed on the tuber flesh of two potato varieties with different color, and 18 differentially expressed GATA transcription factor genes were screened, of which eight genes were validated through qRT-PCR. In this study, we identified and characterized StGATA transcription factors in tetraploid potato for the first time, and screened differentially expressed genes in potato flesh with different color. It provides a theoretical basis for further understanding the StGATA gene family and its function in anthocyanin biosynthesis.

Abstract Krylov complexity measures the spread of the wavefunction in the Krylov basis, which is constructed using the Hamiltonian and an initial state. We investigate the evolution of the maximally entangled state in the Krylov basis for both chaotic and non-chaotic systems. For this purpose, we derive an Ehrenfest theorem for the Krylov complexity, which reveals its close relation to the spectrum. Our findings suggest that neither the linear growth nor the saturation of Krylov complexity is necessarily associated with chaos. However, for chaotic systems, we observe a universal rise-slope-ramp-plateau behavior in the transition probability from the initial state to one of the Krylov basis states. Moreover, a long ramp in the transition probability is a signal for spectral rigidity, characterizing quantum chaos. Also, this ramp is directly responsible for the late-time peak of Krylov complexity observed in the literature. On the other hand, for non-chaotic systems, this long ramp is absent. Therefore, our results help to clarify which features of the wave function time evolution in Krylov space characterize chaos. We exemplify this by considering the Sachdev-Ye-Kitaev model with two-body or four-body interactions.