The effector PHYL1JWB from Candidatus Phytoplasma ziziphi induces abnormal floral development by destabilising flower development proteins.

Phytoplasmas can induce complex and substantial phenotypic changes in their hosts in ways that favour their colonisation, but the mechanisms underlying these changes remain largely unknown. Jujube witches' broom (JWB) disease is a typical phytoplasma disease causing great economic loss in Chinese jujube (Ziziphus jujuba Mill.). Here, we reported an effector, PHYL1JWB from Candidatus Phytoplasma ziziphi, which implicated in inducing abnormal floral organogenesis. Utilising a combination of in vivo and in vitro methods, we investigated the influence of PHYL1JWB on the proteins associated with floral development. Our findings reveal that PHYL1JWB facilitates the proteasome-mediated degradation of essential flower morphogenetic regulators, including AP1, SEP1, SEP2, SEP3, SEP4, CAL, and AGL6, through a distinctive pathway that is dependent on the activity of the 26S proteasome, thus obviating the requirement for lysine ubiquitination of the substrates. Further, the Y2H analysis showed that the leucine at position 75th in second α helix of PHYL1JWB is fundamental for the interactions of PHYL1JWB with AP1 and SEP1-4 in jujube and Arabidopsis. Our research carry profound implications for elucidating the contribution of PHYL1JWB to the aberrant floral development in diseased jujube, and help to establish a robust theoretical underpinning for the prophylaxis and therapy of JWB disease.

Topologically Localized Vibronic Excitations in Second-Layer Graphene Nanoribbons.

It is of fundamental importance to characterize the intrinsic properties, like the topological end states, in the on-surface synthesized graphene nanoribbons (GNRs), but the strong electronic interaction with the metal substrate usually smears out their characteristic features. Here, we report our approach to investigate the vibronic excitations of the topological end states in self-decoupled second-layer GNRs, which are grown using an on-surface squeezing-induced spillover strategy. The vibronic progressions show highly spatially localized distributions at the second-layer GNR ends, which can be ascribed to the decoupling-extended lifetime of charging through resonant electron tunneling at the topological end states. In combination with theoretical calculations, we assign the vibronic progressions to specific vibrational modes that mediate the vibronic excitations. The spatial distribution of each resolved excitation shows evident characteristics beyond the conventional Franck-Condon picture. Our work by direct growth of second-layer GNRs provides an effective way to explore the interplay between the intrinsic electronic, vibrational, and topological properties.

Associations of 24-hour movement guidelines adherence with fruit and vegetable intake in university students.

Background: Unhealthy eating habits, such as low vegetable and fruit intake, are associated with many health problems. 24-h movement behaviors have been reported to be positively associated with numerous health-related outcomes. Despite the importance of these two modifiable lifestyle behaviors in building healthy habits in university students, there is a paucity of relevant research in this population. Therefore, this study aims to examine the correlation between compliance with 24-h movement guideline (24-h MG) and intake of fruits and vegetables (IFV) in Chinese university students. Methods: This study investigated the relationship between the compliance with 24-h MG and IFV in 1,793 Chinese university students using a convenience sampling method online. Physical activity (PA) and sedentary behavior (SB) were assessed by the International Physical Activity Questionnaire-Short Form, while sleep was measured using the Pittsburgh Sleep Quality Index. The Chinese version of the Health Promoting Lifestyle Profile II was used to measure IFV. Generalized linear models were applied to examine the correlation between compliance with the 24-h MG and eating habits. Results: The proportion of participants who routinely consumed vegetables and fruits was 24.6% and 43.1%, respectively, while the proportion of meeting the three 24-h MG and a combination of any two guidelines was 27.8% and 40.1%, respectively. Meeting all three guidelines was associated with a greater IFV intake compared to not meeting either guideline. Meeting all three guidelines (OR = 2.42 [1.63, 3.58]) and the combination of moderate to vigorous PA (MVPA) and sleep (OR = 2.06 [1.37, 3.10]) were positively associated with the frequency of vegetable consumption (p < 0.05). As well, meeting all three guidelines (OR = 2.06 [1.37, 3.10]), the combination of MVPA and sleep (OR = 1.72 [1.04, 2.84]), and sleep only (OR = 1.88 [1.21, 2.92]) were positively associated with fruits consumption (p < 0.05). Conclusion: Almost a third of the university students met the three 24-h MG, and compliance with all three guidelines was associated with a higher frequency of IFV. Furthermore, meeting the sleep guideline alone or in conjunction with the PA, and meeting the entire 24-h MG was associated with greater consumption of fruits.

Synchronized crystallization in tin-lead perovskite solar cells.

Tin-lead halide perovskites with a bandgap near 1.2 electron-volt hold great promise for thin-film photovoltaics. However, the film quality of solution-processed Sn-Pb perovskites is compromised by the asynchronous crystallization behavior between Sn and Pb components, where the crystallization of Sn-based perovskites tends to occur faster than that of Pb. Here we show that the rapid crystallization of Sn is rooted in its stereochemically active lone pair, which impedes coordination between the metal ion and Lewis base ligands in the perovskite precursor. From this perspective, we introduce a noncovalent binding agent targeting the open metal site of coordinatively unsaturated Sn(II) solvates, thereby synchronizing crystallization kinetics and homogenizing Sn-Pb alloying. The resultant single-junction Sn-Pb perovskite solar cells achieve a certified power conversion efficiency of 24.13 per cent. The encapsulated device retains 90 per cent of the initial efficiency after 795 h of maximum power point operation under simulated one-sun illumination.

Comprehensive analysis identifies ubiquitin ligase FBXO42 as a tumor-promoting factor in neuroblastoma.

Neuroblastoma, the deadliest solid tumor in children, exhibits alarming mortality rates, particularly among high-risk cases. To enhance survival rates, a more precise risk stratification for patients is imperative. Utilizing proteomic data from 34 cases with or without N-Myc amplification, we identified 28 differentially expressed ubiquitination-related proteins (URGs). From these, a prognostic signature comprising 6 URGs was constructed. A nomogram incorporating clinical-pathological parameters yielded impressive AUC values of 0.88, 0.93, and 0.95 at 1, 3, and 5 years, respectively. Functional experiments targeting the E3 ubiquitin ligase FBXO42, a component of the prognostic signature, revealed its TP53-dependent promotion of neuroblastoma cell proliferation. In conclusion, our ubiquitination-related prognostic model robustly predicts patient outcomes, guiding clinical decisions. Additionally, the newfound pro-proliferative role of FBXO42 offers a novel foundation for understanding the molecular mechanisms of neuroblastoma.

Immunogen characterization reveals an intrinsic hindrance in eliciting neutralizing antibodies against JN.1 variant.

The immune evasion of emerging SARS-CoV-2 variants significantly undermines current vaccination efforts, calling for an updated vaccine composition. To identify optimal booster candidates against circulating JN.1, a panel of variant spikes were characterized. The omicron spikes exhibited reduced plasma membrane expression, accompanied by lower cell-cell fusion but increased viral entry. Regimens with DNA prime-DNA boost or DNA prime-adenoviral vectored vaccine boost by intramuscular immunization elicited neutralizing antibody (NAbs) and T cell responses against all variants except BA.2.86 and JN.1. Intranasal immunization induced high IgA and NAb titers in bronchoalveolar lavage against all variants except BA.2.86 and JN.1. T cell responses were generally comparable for all immunogens tested. JN.1 completely escaped NAbs in one immunized cohort, and breakthrough infections marginally boosted antibody titers. Overall, this study indicates intrinsic difficulty in eliciting NAbs against the JN.1 strain, whereas vaccines based on XBB and EG.5.1 are relatively superior in generating cross-reactive NAbs.

Recent Advances in representative small-molecule DRD2 inhibitors: Synthetic Routes and clinical applications.

The dopamine D2 receptor (DRD2) represents a pivotal target for therapeutic intervention in the treatment of neuropsychiatric disorders, including schizophrenia, bipolar disorder, and Parkinson's disease. The successful discovery of numerous effective DRD2 inhibitors has led to their clinical application and ongoing evaluation in various clinical trials. This review explores the synthetic approaches and clinical applications of prototypical small-molecule DRD2 inhibitors that have received approval or are currently undergoing clinical trials, highlighting their therapeutic potential and challenges. The synthesis of these inhibitors employs various chemical strategies, including modifications of phenothiazine and butyrophenone structures, which have yielded significant antipsychotic agents like chlorpromazine and haloperidol. Additionally, newer classes of inhibitors, such as aripiprazole, exhibit partial agonist activity at DRD2, offering a unique therapeutic profile. Clinically, DRD2 inhibitors demonstrate efficacy in managing positive symptoms of schizophrenia, manic episodes in bipolar disorder, and dopaminergic imbalance in Parkinson's disease. However, the emergence of adverse effects, including tardive dyskinesia, extrapyramidal symptoms and metabolic syndrome, presents substantial challenges. Advances in the development of second-generation antipsychotics aim to balance efficacy with a better side effect profile by targeting additional neurotransmitter receptors. This review aims to deliver an overview of the synthesis and clinical applications of representative small-molecule DRD2 inhibitors across various clinical phases, thereby offering strategic insights for the advancement of DRD2 inhibitor development.

CircUGP2 Suppresses Intrahepatic Cholangiocarcinoma Progression via p53 Signaling Through Interacting With PURB to Regulate ADGRB1 Transcription and Sponging miR-3191-5p.

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer and its prognosis remains poor. Although growing numbers of studies have verified the involvement of circular RNAs (circRNAs) in various cancer types, their specific functions in ICC remain elusive. Herein, a circRNA, circUGP2 is identified by circRNA sequencing, which is downregulated in ICC tissues and correlated with patients' prognosis. Moreover, circUGP2 overexpression suppresses tumor progression in vitro and in vivo. Mechanistically, circUGP2 functions as a transcriptional co-activator of PURB over the expression of ADGRB1. It can also upregulate ADGRB1 expression by sponging miR-3191-5p. As a result, ADGRB1 prevents MDM2-mediated p53 polyubiquitination and thereby activates p53 signaling to inhibit ICC progression. Based on these findings, circUGP2 plasmid is encapsulated into a lipid nanoparticle (LNP) system, which has successfully targeted tumor site and shows superior anti-tumor effects. In summary, the present study has identified the role of circUGP2 as a tumor suppressor in ICC through regulating ADGRB1/p53 axis, and the application of LNP provides a promising translational strategy for ICC treatment.

Assessment of the Corneal Biomechanical Features of Sturge-Weber Syndrome Using Dynamic Ultrahigh-speed Scheimpflug Imaging.

PURPOSE: To evaluate the corneal biomechanical characteristics of eyes with Sturge-Weber syndrome (SWS) secondary glaucoma (SSG) by analyzing corneal biomechanical parameters obtained using the Corneal Visualization Scheimpflug Technology instrument (Corvis ST). METHODS: In patients with SWS, eyes affected by SSG were designated as the SSG group while the contralateral eyes were designated as the SWS contralateral group (SC group). Patients from the myopia clinic served as the control group. Dynamic corneal response parameters (DCRs) including the stress-strain index (SSI)-a critical material stiffness parameter that excludes interference from IOP and central corneal thickness (CCT)-were analyzed. RESULTS: For CCT, no significant difference was observed between the SSG and SC groups. However, significant differences were found between the SSG and control groups and between the SC and control groups. Parameters such as HC Time, A1 Deformation Amp., A2 Deformation Amp., length of Whole Eye Movement (WEM), DA Ratio Max (2 mm), PachySlope, DA Ratio Max (1 mm), and ARTh showed significant differences between the SSG group and control group. In the SSG group, 4 of night eyes had an SSI of less than 0.85. CONCLUSIONS: Some DCRs indicated a stiffer cornea in the SSG group, possibly due to a thicker cornea in this group. On analyzing SSI, it was found that corneal material properties change, becoming less stiff in some of the patients with SSG. In conclusion, our study provides a preliminary exploration of the biomechanical properties of SWS secondary glaucoma.

Multi-Dimensional Fragmentomics Enables Early and Accurate Detection of Colorectal Cancer.

Colorectal cancer (CRC) is frequently diagnosed in advanced stages, highlighting the need for developing approaches for early detection. Liquid biopsy using cell-free DNA (cfDNA) fragmentomics is a promising approach, but the clinical application is hindered by complexity and cost. This study aimed to develop an integrated model using cfDNA fragmentomics for accurate, cost-effective early-stage CRC detection. Plasma cfDNA was extracted and sequenced from a training cohort of 360 participants, including 176 CRC patients and 184 healthy controls. An ensemble stacked model comprising five machine learning models was employed to distinguish CRC patients from healthy controls using five cfDNA fragmentomic features. The model was validated in an independent cohort of 236 participants (117 CRC patients and 119 controls) and a prospective cohort of 242 participants (129 CRC patients and 113 controls). The ensemble stacked model showed remarkable discriminatory power between CRC patients and controls, outperforming all base models and achieving a high area under the ROC curve (AUC) of 0.986 in the validation cohort. It reached 94.88% sensitivity and 98% specificity for detecting CRC in the validation cohort, with sensitivity increasing as cancer progressed. The model also demonstrated consistently high accuracy in within-run and between-run tests and across various conditions in healthy individuals. In the prospective cohort, it achieved 91.47% sensitivity and 95.58% specificity. This integrated model capitalizes on the multiplex nature of cfDNA fragmentomics to achieve high sensitivity and robustness, offering significant promise for early CRC detection and broad patient benefit.

Roseibium algae sp. nov., isolated from a marine alga (Grateloupia sp.).

A novel Gram-stain-negative, rod-shaped, non-spore-forming, aerobic, motile bacterium with a single polar or subpolar flagellum, designated strain H3510T, was isolated from marine alga collected on sea shore of Yantai, PR China. The organism grew optimally at 28 °C and pH 7.0 and in presence of 3.0 % (w/v) NaCl. The strain exhibited positive catalase activity but negative oxidase and nitrate reduction activities. The predominant cellular fatty acids were C18 : 1 ω7c and/or C18 : 1 ω6c, 11-methyl C18 : 1 ω7c, and C16 : 0. Additionally, the major polar lipids were phosphatidylglycerol, phosphatidylmonomethylethanolamine, diphosphatidylglycerol, and phosphatidylethanolamine; the respiratory quinone was ubiquinone 10 (Q-10). The genomic DNA G+C content of strain H3510T was 54.2%. The novel strain showed the closest relationship with Roseibium polysiphoniae KMM 9699T with 98.2 % 16S rRNA gene sequence similarity. The calculated values for average nucleotide identity and DNA-DNA hybridization between strain H3510T and the phylogenetically related Roseibium species were in the range of 71.3-74.9 % and 13.7-19.9 %, respectively. Based on polyphasic analyses, strain H3510T was identified as representing a novel species of the genus Roseibium, for which the name Roseibium algae sp. nov. is proposed. The type strain is H3510T (=KCTC 8206T=MCCC 1K04325T). The heterologously expressed inositol 2-dehydrogenase gene from strain H3510T displayed high oxidation activity on myo-inositol and showed potential in the production of rare stereoisomers of inositol, such as scyllo-inositol.

A novel mutation alters GNE bifunctional enzyme activity and leads to familial inherited GNE diseases.

Distal myopathies are a group of rare heterogeneous diseases that are mostly caused by genetic factors. At least 20 genes have been associated with distal myopathies. We performed whole-exome sequencing to identify the genetic cause of disease in a family with distal myopathy. Following the American College of Medical Genetics and Genomics (ACMG) guidelines, we analyzed the sequencing results and screened suspicious mutations based on mutation frequency, functional impact, and disease inheritance pattern. The harmfulness of the mutations was predicted using bioinformatics methods, and the pathogenic mutations were determined. We identified a novel amino acid mutation (NP_005467.1:p.S663L) on the GNE gene that may cause familial distal myopathy. This mutation is the result of the simultaneous mutation of two adjacent nucleotides (c.1988C > T, c.1989C > A) in the codon. First, we measured the mRNA and protein expression of the GNE gene in the lymphoblastoid cell lines (LCLs) of the probands and their family members. Second, GNE vectors carrying the novel mutation, two other known pathogenic mutations, and the wild-type gene were constructed and transfected into HEK293T cells. The enzymatic activity of these GNE variants was investigated and showed that the p.S663L mutation significantly reduced the activity of the bifunctional GNE enzyme without altering the expression level of the GNE protein. Furthermore, the mutation may also alter the immunogenicity of the 3' end of the GNE protein, potentially affecting its oligomer formation. In this study, a novel GNE gene mutation that may cause distal myopathy was identified, expanding the spectrum of genetic mutations associated with this disease.

Reformulating lipid nanoparticles for organ-targeted mRNA accumulation and translation.

Fully targeted mRNA therapeutics necessitate simultaneous organ-specific accumulation and effective translation. Despite some progress, delivery systems are still unable to fully achieve this. Here, we reformulate lipid nanoparticles (LNPs) through adjustments in lipid material structures and compositions to systematically achieve the pulmonary and hepatic (respectively) targeted mRNA distribution and expression. A combinatorial library of degradable-core based ionizable cationic lipids is designed, following by optimisation of LNP compositions. Contrary to current LNP paradigms, our findings demonstrate that cholesterol and phospholipid are dispensable for LNP functionality. Specifically, cholesterol-removal addresses the persistent challenge of preventing nanoparticle accumulation in hepatic tissues. By modulating and simplifying intrinsic LNP components, concurrent mRNA accumulation and translation is achieved in the lung and liver, respectively. This targeting strategy is applicable to existing LNP systems with potential to expand the progress of precise mRNA therapy for diverse diseases.

Simultaneous grading diagnosis of liver fibrosis, inflammation, and steatosis using multimodal quantitative ultrasound and artificial intelligence framework.

Noninvasive, accurate, and simultaneous grading of liver fibrosis, inflammation, and steatosis is valuable for reversing the progression and improving the prognosis quality of chronic liver diseases (CLDs). In this study, we established an artificial intelligence framework for simultaneous grading diagnosis of these three pathological types through fusing multimodal tissue characterization parameters dug by quantitative ultrasound methods derived from ultrasound radiofrequency signals, B-mode images, shear wave elastography images, and clinical ultrasound systems, using the liver biopsy results as the classification criteria. One hundred forty-two patients diagnosed with CLD were enrolled in this study. The results show that for the classification of fibrosis grade ≥ F1, ≥ F2, ≥ F3, and F4, the highest AUCs were respectively 0.69, 0.82, 0.84, and 0.88 with single clinical indicator alone, and were 0.81, 0.83, 0.89, and 0.91 with the proposed method. For the classification of inflammation grade ≥ A2 and A3, the highest AUCs were respectively 0.66 and 0.76 with single clinical indicator alone and were 0.80 and 0.93 with the proposed method. For the classification of steatosis grade ≥ S1 and ≥ S2, the highest AUCs were respectively 0.71 and 0.90 with single clinical indicator alone and were 0.75 and 0.92 with the proposed method. The proposed method can effectively improve the grading diagnosis performance compared with the present clinical indicators and has potential applications for noninvasive, accurate, and simultaneous diagnosis of CLDs.

Computed tomography radiomics study of invasion and instability of lung adenocarcinoma manifesting as ground glass nodule.

Background: Ground-glass nodule (GGN) is the most common manifestation of lung adenocarcinoma on computed tomography (CT). Clinically, the success rate of preoperative diagnosis of GGN by puncture biopsy and other means is still low. The aim of this study is to investigate the clinical and radiomics characteristics of lung adenocarcinoma presenting as GGN on CT images using radiomics analysis methods, establish a radiomics model, and predict the classification of pathological tissue and instability of GGN type lung adenocarcinoma. Methods: This study retrospectively collected 249 patients with 298 GGN lesions who were pathologically confirmed of having lung adenocarcinoma. The images were imported into the Siemens scientific research prototype software to outline the region of interest and extract the radiomics features. Logistic model A (a radiomics model to identify the infiltration of lung adenocarcinoma manifesting as GGNs) was established using features after the dimensionality reduction process. The receiver operating characteristic (ROC) curve of the model on training set and the verification set was drawn, and the area under the curve (AUC) was calculated. Second, a total of 112 lesions were selected from 298 lesions originating from CT images of at least two occasions, and the time between the first CT and the preoperative CT was defined as not less than 90 days. The mass doubling time (MDT) of all lesions was calculated. According to the different MDT diagnostic thresholds instability was predicted. Finally, their AUCs were calculated and compared. Results: There were statistically significant differences in age and lesion location distribution between the "noninvasive" lesion group and the invasive lesion group (P<0.05), but there were no statistically significant differences in sex (P>0.05). Model A had an AUC of 0.89, sensitivity of 0.75, and specificity of 0.86 in the training set and an AUC of 0.87, sensitivity of 0.63, and specificity of 0.90 in the validation set. There was no significant difference statistically in MDT between "noninvasive" lesions and invasive lesions (P>0.05). The AUCs of radiomics models B1, B2 and B3 were 0.89, 0.80, and 0.81, respectively; the sensitivities were 0.71, 0.54, and 0.76, respectively; the specificities were 0.83, 0.77, and 0.60, respectively; and the accuracies were 0.78, 0.65, and 0.69, respectively. Conclusions: There were statistically significant differences in age and location of lesions between the "noninvasive" lesion group and the invasive lesion group. The radiomics model can predict the invasiveness of lung adenocarcinoma manifesting as GGNs. There was no significant difference in MDT between "noninvasive" lesions and invasive lesions. The radiomics model can predict the instability of lung adenocarcinoma manifesting as GGN. When the threshold of MDT was set at 813 days, the model had higher specificity, accuracy, and diagnostic efficiency.

CCT6A promotes cell proliferation in colon cancer by targeting BIRC5 associated with p53 status.

Chaperonin-containing TCP1 (CCT) is a multi-subunit complex, known to participate the correct folding of many proteins. Currently, the mechanism underlying CCT subunits in cancer progression is incompletely understood. Based on data analysis, the expression of CCT subunit 6 A (CCT6A) is found higher than the other subunits of CCT and correlated with an unfavorable prognosis in colon cancer. Here, we find CCT6A silencing suppresses colon cancer proliferation and survival phenotype in vitro and in vivo. CCT6A plays a role in cellular process, including the cell cycle, p53, and apoptosis signaling pathways. Further investigations have shown direct binding between CCT6A and both Wtp53 and Mutp53, and BIRC5 is found to act downstream of CCT6A. The highlight is that CCT6A inhibition significantly reduces BIRC5 expression independent of Wtp53 levels in Wtp53 cells. Conversely, in Mutp53 cells, downregulation of BIRC5 by CCT6A inhibition mainly depends on Mutp53 levels. Additionally, combined CCT6A inhibition and Wtp53 overexpression in Mutp53 cell lines effectively suppresses cell proliferation. It is concluded CCT6A is a potential oncogene that influences BIRC5 through distinct pathways in Wtp53 and Mutp53 cells.

Genome analysis through image processing with deep learning models.

Genomic sequences are traditionally represented as strings of characters: A (adenine), C (cytosine), G (guanine), and T (thymine). However, an alternative approach involves depicting sequence-related information through image representations, such as Chaos Game Representation (CGR) and read pileup images. With rapid advancements in deep learning (DL) methods within computer vision and natural language processing, there is growing interest in applying image-based DL methods to genomic sequence analysis. These methods involve encoding genomic information as images or integrating spatial information from images into the analytical process. In this review, we summarize three typical applications that use image processing with DL models for genome analysis. We examine the utilization and advantages of these image-based approaches.

High-throughput preparation, scale up and solidification of andrographolide nanosuspension using hummer acoustic resonance technology.

The aim of this study was to rapidly develop a sufficiently robust andrographolide nanosuspension (AG-NS) system using hummer acoustic resonance (HAR) technology. The system can effectively improve the dissolution properties of AG, while having high stability and scale-up adaptability. The formulation of AG-NS was optimized in a high-throughput manner using HAR technology and the preparation process was optimized stepwise. Optimal AG-NS with Z-Ave = 223.99 ± 3.16 nm, PDI=0.095 ± 0.007 and zeta potential = -33.20 ± 0.58 mV was successfully prepared with Polyvinylpyrrolidone K30 and Sodium dodecyl sulfate. The optimal prescription was successfully scaled up 100 and 150 times using HAR technology, which was the initial exploration of its commercial scale production. AG-NS was solidified using freeze drying and fluid bed technology, respectively. The optimal AG-NS and its solidified products were exhaustively characterized using various analytical techniques. The high energy input of HAR technology and drying process converted part of the drug into the amorphous state. The in-vitro drug dissolution studies demonstrated relatively higher drug dissolution for AG-NS and its solidified products compared to controls at both the dissolution media (pH 1.2 buffer and pH 6.8 buffer). AG-NS and its solidified products successfully maintained their physical stability in short-term stability and accelerated stability experiments, respectively.

The impact of digital industry agglomeration on firms' carbon emissions: new micro-evidence from Chinese manufacturing firms.

In the backdrop of the rapid evolution of the digital economy, the intricate relationship between digital industry agglomeration (DIA) and manufacturing firms' carbon emissions has become crucial for countries to achieve sustainable development. This study delves into this complex dynamic by analyzing data from Chinese-listed manufacturing companies spanning the years 2014 to 2021. A regional-level DIA Index is calculated to explore its impact on manufacturing firms' carbon emissions. The main finding reveals a U-shaped relationship, with an inhibitory effect on carbon emissions in most provinces to the left of the inflection point. Notably, Guangdong Province experiences a promotional phase to the right of the inflection point, where agglomeration intensifies carbon emissions. The robustness tests, including Utest, instrumental variable examination, and propensity score matching, support the credibility of these findings. Mechanism analysis reveals the mediating role of manufacturing firms' technological innovations in this relationship. Specifically, DIA is related to manufacturing firms' technological innovation in an inverted U shape, and technological innovation inhibits these firms' carbon emissions. This micro-evidence not only contributes to a nuanced understanding of the relationship between DIA and carbon emissions but also provides valuable insights to guide policies for sustainable development within the dynamic context of the digital economy.

Unveiling Atomic-Scaled Local Chemical Order of High-Entropy Intermetallic Catalyst for Alkyl-Substitution-Dependent Alkyne Semihydrogenation.

High-entropy intermetallic (HEI) nanocrystals, composed of multiple elements with an ordered structure, are of immense interest in heterogeneous catalysis due to their unique geometric and electronic structures and the cocktail effect. Despite tremendous efforts dedicated to regulating the metal composition and structures with advanced synthetic methodologies to improve the performance, the surface structure, and local chemical order of HEI and their correlation with activity at the atomic level remain obscure yet challenging. Herein, by determining the three-dimensional (3D) atomic structure of quinary PdFeCoNiCu (PdM) HEI using atomic-resolution electron tomography, we reveal that the local chemical order of HEI regulates the surface electronic structures, which further mediates the alkyl-substitution-dependent alkyne semihydrogenation. The 3D structures of HEI PdM nanocrystals feature an ordered (intermetallic) core enclosed by a disordered (solid-solution) shell rather than an ordered surface. The lattice mismatch between the core and shell results in apparent near-surface distortion. The chemical order of the intermetallic core increases with annealing temperature, driving the electron redistribution between Pd and M at the surface, but the surface geometrical (chemically disordered) configurations and compositions are essentially unchanged. We investigate the catalytic performance of HEI PdM with different local chemical orders toward semihydrogenation across a broad range of alkynes, finding that the electron density of surface Pd and the hindrance effect of alkyl substitutions on alkynes are two key factors regulating selective semihydrogenation. We anticipate that these findings on surface atomic structure will clarify the controversy regarding the geometric and/or electronic effects of HEI catalysts and inspire future studies on tuning local chemical order and surface engineering toward enhanced catalysts.