Heat-dependent properties of methane diffusion in coal: an experimental study and mechanistic analysis.

Coalbed methane thermodynamic extraction, as an emerging ECBM recovery method, can effectively improve gas recovery rates. And clarifying methane diffusion and migration law in coal under thermal stimulation is crucial for the selection of its process parameters. Based on laboratory methane adsorption-release experiments, the evolution law of methane diffusion characteristics with temperature and pressure was studied, and the control mechanism of heat-dependent methane diffusion behavior was explored. The results show that both thermal stimulation and high adsorption pressure accelerated the methane diffusion rate in coal. Adsorption pressure had little effect on methane diffusion percentage, but thermal stimulation promoted a significant increase in diffusion percentage and improved the net methane yield. The influence mechanisms of adsorption pressure and thermal stimulation on methane diffusion characteristics are elucidated in relation to the amount and proportion of methane-activated molecules in the diffusion process. The constant diffusion coefficient of methane is heat-dependent, based on which a diffusion model is derived to accurately predict the methane release process in coal. Additionally, temperature has a more important effect on transient diffusion coefficient than pressure. Thermal stimulation leads to a net increase rather than a decrease in diffusion coefficient in the early diffusion stages and can also accelerate the attenuation of diffusion coefficient, with this intensifying effect becoming more pronounced at higher temperatures. The research results can provide some reference for the determination of coal seam gas content and the selection of heat injection process parameters.

SLInterpreter: An Exploratory and Iterative Human-AI Collaborative System for GNN-based Synthetic Lethal Prediction.

Synthetic Lethal (SL) relationships, though rare among the vast array of gene combinations, hold substantial promise for targeted cancer therapy. Despite advancements in AI model accuracy, there is still a significant need among domain experts for interpretive paths and mechanism explorations that align better with domain-specific knowledge, particularly due to the high costs of experimentation. To address this gap, we propose an iterative Human-AI collaborative framework with two key components: 1) HumanEngaged Knowledge Graph Refinement based on Metapath Strategies, which leverages insights from interpretive paths and domain expertise to refine the knowledge graph through metapath strategies with appropriate granularity. 2) Cross-Granularity SL Interpretation Enhancement and Mechanism Analysis, which aids experts in organizing and comparing predictions and interpretive paths across different granularities, uncovering new SL relationships, enhancing result interpretation, and elucidating potential mechanisms inferred by Graph Neural Network (GNN) models. These components cyclically optimize model predictions and mechanism explorations, enhancing expert involvement and intervention to build trust. Facilitated by SLInterpreter, this framework ensures that newly generated interpretive paths increasingly align with domain knowledge and adhere more closely to real-world biological principles through iterative Human-AI collaboration. We evaluate the framework's efficacy through a case study and expert interviews.

The effect of the loop on the thermodynamic and kinetic of single base pair in pseudoknot.

RNA pseudoknots are RNA molecules with specialized three-dimensional structures that play important roles in various biological processes. To understand the functions and mechanisms of pseudoknots, it is essential to elucidate their structures and folding pathways. The most fundamental step in RNA folding is the opening and closing of a base pair. The effect of flexible loops on the base pair in pseudoknots remains unclear. In this work, we use molecular dynamics simulations and Markov state model to study the configurations, thermodynamic and kinetic of single base pair in pseudoknots. We find that the presence of the loop leads to a trap state. In addition, the rate-limiting step for the formation of base pair is the disruption of the trap state, rather than the open state to the closed state, which is quite different from the previous studies on non-pseudoknot RNA. For the thermodynamic parameters in pseudoknots, we find that the entropy difference upon opening the base pair between this simulation and the nearest-neighbor model results from the different entropy of different lengths of loop in solution. The thermodynamic parameters of the stack in pseudoknot are close to the nearest-neighbor parameters. The bases on the loop have different distribution patterns in different states, and the slow transition states of the loop are determined by the orientation of the bases.

Optimizing Distributions for Associated Entropic Vectors via Generative Convolutional Neural Networks.

The complete characterization of the almost-entropic region yields rate regions for network coding problems. However, this characterization is difficult and open. In this paper, we propose a novel algorithm to determine whether an arbitrary vector in the entropy space is entropic or not, by parameterizing and generating probability mass functions by neural networks. Given a target vector, the algorithm minimizes the normalized distance between the target vector and the generated entropic vector by training the neural network. The algorithm reveals the entropic nature of the target vector, and obtains the underlying distribution, accordingly. The proposed algorithm was further implemented with convolutional neural networks, which naturally fit the structure of joint probability mass functions, and accelerate the algorithm with GPUs. Empirical results demonstrate improved normalized distances and convergence performances compared with prior works. We also conducted optimizations of the Ingleton score and Ingleton violation index, where a new lower bound of the Ingleton violation index was obtained. An inner bound of the almost-entropic region with four random variables was constructed with the proposed method, presenting the current best inner bound measured by the volume ratio. The potential of a computer-aided approach to construct achievable schemes for network coding problems using the proposed method is discussed.

Molecular Mechanism of the ß3AR Agonist Activity of a ß-Blocker.

Development of subtype-selective drugs for G protein-coupled receptors poses a significant challenge due to high similarity between subtypes, as exemplified by the three ß-adrenergic receptors (ßARs). The ß3AR agonists show promise for treating the overactive bladder or preterm birth, but their potential is hindered by off-target activation of ß1AR and ß2AR. Interestingly, several ß-blockers, which are antagonists of the ß1ARs and ß2ARs, have been reported to exhibit agonist activity at the ß3AR. However, the molecular mechanism remains elusive. Understanding the underlying mechanism should facilitate the development of ß3AR agonist drugs with improved selectivity and reduced off-target effects. In this work, we determined the structures of human ß3AR in complex with the endogenous agonist epinephrine or with a synthetic ß3AR agonist carazolol, which is also a high-affinity ß-blocker. Structure comparison, mutagenesis studies and molecular dynamics simulations revealed that the differences on the flexibility of D3.32 directly contribute to carazolol's distinct activities as an antagonist for the ß2AR and an agonist for the ß3AR. The process is also indirectly influenced by the extracellular loops (ECL), especially ECL1. Taken together, these results provide key guidance for development of selective ß3AR agonists, paving the way for new therapeutic opportunities.

SPX family response to low phosphorus stress and the involvement of ZmSPX1 in phosphorus homeostasis in maize.

Phosphorus (P) is a crucial macronutrient for plant growth and development, and low-Pi stress poses a significant limitation to maize production. While the role of the SPX domain in encoding proteins involved in phosphate (Pi) homeostasis and signaling transduction has been extensively studied in other model plants, the molecular and functional characteristics of the SPX gene family members in maize remain largely unexplored. In this study, we identified six SPX members, and the phylogenetic analysis of ZmSPXs revealed a close relationship with SPX genes in rice. The promoter regions of ZmSPXs were abundant in biotic and abiotic stress-related elements, particularly associated with various hormone signaling pathways, indicating potential intersections between Pi signaling and hormone signaling pathways. Additionally, ZmSPXs displayed tissue-specific expression patterns, with significant and differential induction in anthers and roots, and were localized to the nucleus and cytoplasm. The interaction between ZmSPXs and ZmPHRs was established via yeast two-hybrid assays. Furthermore, overexpression of ZmSPX1 enhanced root sensitivity to Pi deficiency and high-Pi conditions in Arabidopsis thaliana. Phenotypic identification of the maize transgenic lines demonstrated the negative regulatory effect on the P concentration of stems and leaves as well as yield. Notably, polymorphic sites including 34 single-nucleotide polymorphisms (SNPs) and seven insertions/deletions (InDels) in ZmSPX1 were significantly associated with 16 traits of low-Pi tolerance index. Furthermore, significant sites were classified into five haplotypes, and haplotype5 can enhance biomass production by promoting root development. Taken together, our results suggested that ZmSPX family members possibly play a pivotal role in Pi stress signaling in plants by interacting with ZmPHRs. Significantly, ZmSPX1 was involved in the Pi-deficiency response verified in transgenic Arabidopsis and can affect the Pi concentration of maize tissues and yield. This work lays the groundwork for deeper exploration of the maize SPX family and could inform the development of maize varieties with improved Pi efficiency.

Mining for QTL controlling maize low-phosphorus response genes combined with deep resequencing of RIL parental genomes and in silico GWAS analysis.

KEY MESSAGE: Extensive and comprehensive phenotypic data from a maize RIL population under both low- and normal-Pi treatments were used to conduct QTL mapping. Additionally, we integrated parental resequencing data from the RIL population, GWAS results, and transcriptome data to identify candidate genes associated with low-Pi stress in maize. Phosphorus (Pi) is one of the essential nutrients that greatly affect the maize yield. However, the genes underlying the QTL controlling maize low-Pi response remain largely unknown. In this study, a total of 38 traits at both seedling and maturity stages were evaluated under low- and normal-Pi conditions using a RIL population constructed from X178 (tolerant) and 9782 (sensitive), and most traits varied significantly between low- and normal-Pi treatments. Twenty-nine QTLs specific to low-Pi conditions were identified after excluding those with common intervals under both low- and normal-Pi conditions. Furthermore, 45 additional QTLs were identified based on the index value ((Trait_under_LowPi-Trait_under_NormalPi)/Trait_under_NormalPi) of each trait. These 74 QTLs collectively were classified as Pi-dependent QTLs. Additionally, 39 Pi-dependent QTLs were clustered in nine HotspotQTLs. The Pi-dependent QTL interval contained 19,613 unique genes, 6,999 of which exhibited sequence differences with non-synonymous mutation sites between X178 and 9782. Combined with in silico GWAS results, 277 consistent candidate genes were identified, with 124 genes located within the HotspotQTL intervals. The transcriptome analysis revealed that 21 genes, including the Pi transporter ZmPT7 and the strigolactones pathway-related gene ZmPDR1, exhibited consistent low-Pi stress response patterns across various maize inbred lines or tissues. It is noteworthy that ZmPDR1 in maize roots can be sharply up-regulated by low-Pi stress, suggesting its potential importance as a candidate gene for responding to low-Pi stress through the strigolactones pathway.

Small-bowel trichobezoars with intestinal obstruction in children: three case reports and literature review.

Trichobezoars are conglomerates of hair within the gastro-intestinal tract, commonly detected in the stomach, and they can present with the Rapunzel syndrome. Isolated small-bowel trichobezoars are extremely rare. Three female patients presented with abdominal pain and bilious vomiting, and underwent various imaging examinations. Two were diagnosed with small-bowel trichobezoars with intestinal obstruction and one with intestinal obstruction only. All three underwent surgery. Two underwent laparoscopic exploration and one underwent a laparotomy. One and two patients had isolated small-bowel trichobezoars in the ileum and jejunum, respectively. Two patients were followed up by a psychiatrist, and all recovered well without recurrence. These three cases emphasise the importance of a comprehensive medical history and imaging in patients with small-bowel obstruction to determine the possibility of bezoars.

Experimental Study on Emergency Psychophysiological and Behavioral Reactions to Coal Mining Accidents.

Effective emergency responses are crucial for preventing coal mine accidents and mitigating injuries. This paper aims to investigate the characteristics of emergency psychophysiological reactions to coal mine accidents and to explore the potential of key indicators for identifying emergency behavioral patterns. Initially, virtual reality technology facilitated a simulation experiment for emergency escape during coal mine accidents. Subsequently, the characteristics of emergency reactions were analyzed through correlation analysis, hypothesis testing, and analysis of variance. The significant changes in physiological indicators were then taken as input features and fed into the three classifiers of machine learning algorithms. These classifications ultimately led to the identification of behavioral patterns, including agility, defensiveness, panic, and rigidity, that individuals may exhibit during a coal mine accident emergency. The study results revealed an intricate relationship between the mental activities induced by accident stimuli and the resulting physiological changes and behavioral performances. During the virtual reality simulation of a coal mine accident, subjects were observed to experience significant physiological changes in electrodermal activity, heart rate variability, electromyogram, respiration, and skin temperature. The random forest classification model, based on SCR + RANGE + IBI + SDNN + LF/HF, outperformed all other models, achieving accuracies of up to 92%. These findings hold promising implications for early warning systems targeting abnormal psychophysiological and behavioral reactions to emergency accidents, potentially serving as a life-saving measure in perilous situations and fostering the sustainable growth of the coal mining industry.

Genome-wide association studies dissect low-phosphorus stress response genes underling field and seedling traits in maize.

Phosphorus (P) is an essential element for plant growth, and its deficiency can cause decreased crop yield. This study systematically evaluated the low-phosphate (Pi) response traits in a large population at maturity and seedling stages, and explored candidate genes and their interrelationships with specific traits. The results revealed a greater sensitivity of seedling maize to low-Pi stress compared to that at maturity stage. The phenotypic response patterns to low-Pi stress at different stages were independent. Chlorophyll content was found to be a potential indicator for screening low-Pi-tolerant materials in the field. A total of 2900 and 1446 significantly associated genes at the maturity and seedling stages were identified, respectively. Among these genes, 972 were uniquely associated with maturity traits, while 330 were specifically detected at the seedling stage under low-Pi stress. Moreover, 768 and 733 genes were specifically associated with index values (low-Pi trait/normal-Pi trait) at maturity and seedling stage, respectively. Genetic network diagrams showed that the low-Pi response gene Zm00001d022226 was specifically associated with multiple primary P-related traits under low-Pi conditions. A total of 963 out of 2966 genes specifically associated with traits under low-Pi conditions or index values were found to be induced by low-Pi stress. Notably, ZmSPX4.1 and ZmSPX2 were sharply up-regulated in response to low-Pi stress across different lines or tissues. These findings advance our understanding of maize's response to low-Pi stress at different developmental stages, shedding light on the genes and pathways implicated in this response.

Machine Learning of Reactive Potentials.

In the past two decades, machine learning potentials (MLPs) have driven significant developments in chemical, biological, and material sciences. The construction and training of MLPs enable fast and accurate simulations and analysis of thermodynamic and kinetic properties. This review focuses on the application of MLPs to reaction systems with consideration of bond breaking and formation. We review the development of MLP models, primarily with neural network and kernel-based algorithms, and recent applications of reactive MLPs (RMLPs) to systems at different scales. We show how RMLPs are constructed, how they speed up the calculation of reactive dynamics, and how they facilitate the study of reaction trajectories, reaction rates, free energy calculations, and many other calculations. Different data sampling strategies applied in building RMLPs are also discussed with a focus on how to collect structures for rare events and how to further improve their performance with active learning.

Exploring the phosphorus-starch content balance mechanisms in maize grains using GWAS population and transcriptome data.

Examining the connection between P and starch-related signals can help elucidate the balance between nutrients and yield. This study utilized 307 diverse maize inbred lines to conduct multi-year and multi-plot trials, aiming to explore the relationship among P content, starch content, and 100-kernel weight (HKW) of mature grains. A significant negative correlation was found between P content and both starch content and HKW, while starch content showed a positive correlation with HKW. The starch granules in grains with high-P and low-starch content (HPLS) were significantly smaller compared to grains with low-P high-starch content (LPHS). Additionally, mian04185-4 (HPLS) exhibited irregular and loosely packed starch granules. A significant decrease in ZmPHOs genes expression was detected in the HPLS line ZNC442 as compared to the LPHS line SCML0849, while no expression difference was observed in AGPase encoding genes between these two lines. The down-regulated genes in ZNC442 grains were enriched in nucleotide sugar and fatty acid anabolic pathways, while up-regulated genes were enriched in the ABC transporters pathway. An accelerated breakdown of fat as the P content increased was also observed. This implied that HPLS was resulted from elevated lipid decomposition and inadequate carbon sources. The GWAS analysis identified 514 significantly associated genes, out of which 248 were differentially expressed. Zm00001d052392 was found to be significantly associated with P content/HKW, exhibiting high expression in SCML0849 but almost no expression in ZNC442. Overall, these findings suggested new approaches for achieving a P-yield balance through the manipulation of lipid metabolic pathways in grains.

Mechanical Constraints in Tumor Guide Emergent Spatial Patterns of Glioblastoma Cancer Stem Cells.

The mechanical constraints in the overcrowding glioblastoma (GBM) microenvironment have been implicated in the regulation of tumor heterogeneity and disease progression. Especially, such mechanical cues can alter cellular DNA transcription and give rise to a subpopulation of tumor cells called cancer stem cells (CSCs). These CSCs with stem-like properties are critical drivers of tumorigenesis, metastasis, and treatment resistance. Yet, the biophysical and molecular machinery underlying the emergence of CSCs in tumor remained unexplored. This work employed a two-dimensional micropatterned multicellular model to examine the impact of mechanical constraints arisen from geometric confinement on the emergence and spatial patterning of CSCs in GBM tumor. Our study identified distinct spatial distributions of GBM CSCs in different geometric patterns, where CSCs mostly emerged in the peripheral regions. The spatial pattern of CSCs was found to correspond to the gradients of mechanical stresses resulted from the interplay between the cell-ECM and cell-cell interactions within the confined environment. Further mechanistic study highlighted a Piezo1-RhoA-focal adhesion signaling axis in regulating GBM cell mechanosensing and the subsequent CSC phenotypic transformation. These findings provide new insights into the biophysical origin of the unique spatial pattern of CSCs in GBM tumor and offer potential avenues for targeted therapeutic interventions.

Antibodies expand the scope of angiotensin receptor pharmacology.

G-protein-coupled receptors (GPCRs) are key regulators of human physiology and are the targets of many small-molecule research compounds and therapeutic drugs. While most of these ligands bind to their target GPCR with high affinity, selectivity is often limited at the receptor, tissue and cellular levels. Antibodies have the potential to address these limitations but their properties as GPCR ligands remain poorly characterized. Here, using protein engineering, pharmacological assays and structural studies, we develop maternally selective heavy-chain-only antibody ('nanobody') antagonists against the angiotensin II type I receptor and uncover the unusual molecular basis of their receptor antagonism. We further show that our nanobodies can simultaneously bind to angiotensin II type I receptor with specific small-molecule antagonists and demonstrate that ligand selectivity can be readily tuned. Our work illustrates that antibody fragments can exhibit rich and evolvable pharmacology, attesting to their potential as next-generation GPCR modulators.

Regulation and Role of Adiponectin Secretion in Rat Ovarian Granulosa Cells.

Adiponectin is an important adipokine involved in glucose and lipid metabolism, but its secretion and potential role in regulating glucose utilization during ovarian development remains unclear. This study aims to investigate the mechanism and effects of follicle-stimulating hormones (FSHs) on adiponectin secretion and its following impact on glucose transport in the granulosa cells of rat ovaries. A range of experimental techniques were utilized to test our research, including immunoblotting, immunohistochemistry, immunofluorescence, ELISA, histological staining, real-time quantitative PCR, and transcriptome analysis. The immunohistochemistry results indicated that adiponectin was primarily located in the granulosa cells of rat ovaries. In primary granulosa cells cultured in vitro, both Western blot and immunofluorescence assays demonstrated that FSH significantly induced adiponectin secretion within 2 h of incubation, primarily via the PKA signaling pathway rather than the PI3K/AKT pathway. Concurrently, the addition of the AdipoR1/AdipoR2 dual agonist AdipoRon to the culture medium significantly stimulated the protein expression of GLUT1 in rat granulosa cells, resulting in enhanced glucose absorption. Consistent with these in vitro findings, rats injected with eCG (which shares structural and functional similarities with FSH) exhibited significantly increased adiponectin levels in both the ovaries and blood. Moreover, there was a notable elevation in mRNA and protein levels of AdipoRs and GLUTs following eCG administration. Transcriptomic analysis further revealed a positive correlation between the expression of the intraovarian adiponectin system and glucose transporter. The present study represents a novel investigation, demonstrating that FSH stimulates adiponectin secretion in ovarian granulosa cells through the PKA signaling pathway. This mechanism potentially influences glucose transport (GLUT1) and utilization within the ovaries.

Toripalimab Plus Bevacizumab as First-line Treatment for Advanced Hepatocellular Carcinoma: A Prospective, Multicenter, Single-Arm, Phase II Trial.

PURPOSE: This phase II, multicenter, prospective, single-arm study aimed to evaluate the efficacy and safety of toripalimab plus bevacizumab for treating advanced hepatocellular carcinoma (HCC). PATIENTS AND METHODS: Treatment-naïve patients with advanced HCC received toripalimab 240 mg plus bevacizumab 15 mg/kg every 3 weeks. The primary endpoints included safety and tolerability and objective response rate (ORR) assessed by the investigator per Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. RESULTS: Fifty-four patients were enrolled between April 17, 2020, and December 11, 2020. As assessed by the investigator according to RECIST v1.1, the ORR was 31.5% [95% confidence interval (CI), 19.5-45.6] and the lower bound of the 95% CI was above the prespecified boundary of 10%. The independent review committee (IRC) assessed ORR according to the modified RECIST (mRECIST), which was 46.3% (95% CI, 32.6-60.4). The median progression-free survival was 8.5 (95% CI, 5.5-11.0) and 9.8 months (95% CI, 5.6 to not evaluable) as assessed by the investigator according to RECIST v1.1 and IRC according to mRECIST criteria, respectively. The median overall survival (OS) was not reached, and the 12- and 24-month OS rates were 77.3% and 63.5%, respectively. Grade 3 or higher treatment-emergent adverse events (TEAEs) occurred in 27 patients (50.0%). The most common TEAEs were proteinuria (59.3%), hypertension (38.9%), increased aspartate aminotransferase (33.3%), increased amylase (29.6%), decreased platelet count (27.8%), and increased bilirubin levels (27.8%). CONCLUSIONS: Toripalimab plus bevacizumab showed a favorable efficacy and safety profile, supporting further studies on this combination regimen as a first-line treatment for advanced HCC.

The molecular subtypes of autoimmune diseases.

Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS "inflammation & EGF" subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.

Preliminary exploration of animal models of congenital choledochal cysts.

BACKGROUND: Various animal models have been used to explore the pathogenesis of choledochal cysts (CCs), but with little convincing results. Current surgical techniques can achieve satisfactory outcomes for treatment of CCs. Consequently, recent studies have focused more on clinical issues rather than basic research. Therefore, we need appropriate animal models to further basic research. AIM: To establish an appropriate animal model that may contribute to the investigation of the pathogenesis of CCs. METHODS: Eighty-four specific pathogen-free female Sprague-Dawley rats were randomly allocated to a surgical group, sham surgical group, or control group. A rat model of CC was established by partial ligation of the bile duct. The reliability of the model was confirmed by measurements of serum biochemical indices, morphology of common bile ducts of the rats as well as molecular biology experiments in rat and human tissues. RESULTS: Dilation classified as mild (diameter, ≥ 1 mm to < 3 mm), moderate (≥ 3 mm to < 10 mm), and severe (≥ 10 mm) was observed in 17, 17, and 2 rats in the surgical group, respectively, while no dilation was observed in the control and sham surgical groups. Serum levels of alanine aminotransferase, aspartate aminotransferase, total bilirubin, direct bilirubin, and total bile acids were significantly elevated in the surgical group as compared to the control group 7 d after surgery, while direct bilirubin, total bilirubin, and gamma-glutamyltransferase were further increased 14 d after surgery. Most of the biochemical indices gradually decreased to normal ranges 28 d after surgery. The protein expression trend of signal transducer and activator of transcription 3 in rat model was consistent with the human CC tissues. CONCLUSION: The model of partial ligation of the bile duct of juvenile rats could morphologically simulate the cystic or fusiform CC, which may contribute to investigating the pathogenesis of CC.

Clinical characteristics of choledochal cysts with intrahepatic bile duct dilatations: an observational study.

Purpose: Whether a dilated intrahepatic bile duct (IHBD) has any effect on the prognosis of choledochal cyst (CC) remains controversial. We aimed to summarize the clinical characteristics and prognosis of CC with IHBD dilatation. Methods: One hundred ninety-two children diagnosed with CC were identified, including 127 without IHBD dilatation (group A) and 65 with IHBD dilatation (group B). A retrospective analysis was performed to explore the clinical characteristics and prognosis of CC with IHBD dilatation based on clinical indices, symptoms, and complications. Results: Compared with group A, incidences of jaundice and fever were higher in group B (P = 0.010 and P = 0.033). Preoperative total bilirubin, direct bilirubin, and indirect bilirubin were increased in group B compared to group A (P = 0.005, P < 0.001, and P = 0.014), as were preoperative ALT, AST, γ-GT, and total bile acid (P = 0.006, P = 0.025, P < 0.001, and P = 0.024). The risk of liver fibrosis or cirrhosis was significantly increased for group B compared with group A (P = 0.012) and also occurred earlier in group B (P = 0.006). In the dilated IHBDs, 95.4% (62 of 65) recovered to normal, and more than half of dilated IHBDs (37 of 65) recovered to normal in 1 week. Conclusion: Most IHBDs can recover to normal postoperatively in a short time, and proactive treatment is recommended for CC patients with IHBD dilatation for significant abnormal liver functions.

Molecular Tuning of Reactivity of Zeolite Protons in HZSM-5.

In acidic HZSM-5 zeolite, the reactivity of a methanol molecule interacting with the zeolite proton is amenable to modification via coadsorbing a stochiometric amount of an electron density donor E to form the [(E)(CH3OH)(HZ)] complex. The rate of the methanol in this complex undergoing dehydration to dimethyl ether was determined for a series of E with proton affinity (PA) ranging from 659 kJ mol-1 for C6F6 to 825 kJ mol-1 for C4H8O and was found to follow the expression: Ln(Rate) - Ln(RateN2) = ß(PA - PAN2)γ, where E = N2 is the reference and ß and γ are constants. This trend is probably due to the increased stability of the solvated proton in the [(E)(CH3OH)(HZ)] complex with increasing PA. Importantly, this is also observed in steady-state flow reactions when stoichiometric quantities of E are preadsorbed on the zeolite. As demonstrated with E being D2O, the effect on methanol reactivity diminishes when E is present in excess of the [(E)(CH3OH)(HZ)] complex. It is proposed that the methanol dehydration reaction involves [(E)(CH3OH)(CH3OH)(HZ)] as the transition state, which is supported by the isotopologue distribution of the initial dimethyl ether formed when a flow of CH3OH was passed over ZSM-5 containing one CD3OH per zeolite proton. The implication of this on the mechanism of catalytic methanol dehydration on HZSM-5 is discussed.