Polar Aromatic Two-dimensional Dion-Jacobson Halide Perovskites for Efficient Photocatalytic H2 Evolution.

Polar materials with spontaneous polarization (Ps) have emerged as highly promising photocatalysts for efficient photocatalytic H2 evolution owing to the Ps-enhanced photogenerated carrier separation. However, traditional inorganic polar materials often suffer from limitations such as wide band gaps and poor carrier transport, which hinders their photocatalytic H2 evolution efficiency. Here, we rationally synthesized a series of isostructural two-dimensional (2D) aromatic Dion-Jacobson (DJ) perovskites, namely (2-(2-Aminoethyl)pyridinium)PbI4 (2-APDPI), (3-(2-Aminoethyl)pyridinium)PbI4 (3-APDPI), and (4-(2-Aminoethyl)pyridinium)PbI4 (4-APDPI), where 2-APDPI and 4-APDPI crystalize in polar space groups with piezoelectric constants (d33) of approximately 40 pm V-1 and 3-APDPI adopts a centrosymmetric structure. Strikingly, owing to the Ps-facilitated separation of photogenerated carriers, polar 2-APDPI and 4-APDPI exhibit a 3.9- and 2.8-fold increase, respectively, in photocatalytic H2 evolution compared to the centrosymmetric 3-APDPI. As a pioneering study, this work provides an efficient approach for exploring new polar photocatalysts and highlights their potential in promoting photocatalytic H2 evolution.

Hepatocyte CHRNA4 mediates the MASH-promotive effects of immune cell-produced acetylcholine and smoking exposure in mice and humans.

Metabolic dysfunction-associated steatohepatitis (MASH) is a leading risk factor for liver cirrhosis and hepatocellular carcinoma. Here, we report that CHRNA4, a subunit of nicotinic acetylcholine receptors (nAChRs), is an accelerator of MASH progression. CHRNA4 also mediates the MASH-promotive effects induced by smoking. Chrna4 was expressed specifically in hepatocytes and exhibited increased levels in mice and patients with MASH. Elevated CHRNA4 levels were positively correlated with MASH severity. We further revealed that during MASH development, acetylcholine released from immune cells or nicotine derived from smoking functioned as an agonist to activate hepatocyte-intrinsic CHRNA4, inducing calcium influx and activation of inflammatory signaling. The communication between immune cells and hepatocytes via the acetylcholine-CHRNA4 axis led to the production of a variety of cytokines, eliciting inflammation in liver and promoting the pathogenesis of MASH. Genetic and pharmacological inhibition of CHRNA4 protected mice from diet-induced MASH. Targeting CHRNA4 might be a promising strategy for MASH therapeutics.

Direct OC-CHO coupling towards highly C2+ products selective electroreduction over stable Cu0/Cu2+ interface.

Electroreduction of CO2 to valuable multicarbon (C2+) products is a highly attractive way to utilize and divert emitted CO2. However, a major fraction of C2+ selectivity is confined to less than 90% by the difficulty of coupling C-C bonds efficiently. Herein, we identify the stable Cu0/Cu2+ interfaces derived from copper phosphate-based (CuPO) electrocatalysts, which can facilitate C2+ production with a low-energy pathway of OC-CHO coupling verified by in situ spectra studies and theoretical calculations. The CuPO precatalyst shows a high Faradaic efficiency (FE) of 69.7% towards C2H4 in an H-cell, and exhibits a significant FEC2+ of 90.9% under industrially relevant current density (j = -350 mA cm-2) in a flow cell configuration. The stable Cu0/Cu2+ interface breaks new ground for the structural design of electrocatalysts and the construction of synergistic active sites to improve the activity and selectivity of valuable C2+ products.

AutoFibroNet: A deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD.

BACKGROUND: Liver fibrosis is the strongest histological risk factor for liver-related complications and mortality in metabolic dysfunction-associated fatty liver disease (MAFLD). Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) is a powerful tool for label-free two-dimensional and three-dimensional tissue visualisation that shows promise in liver fibrosis assessment. AIM: To investigate combining multi-photon microscopy (MPM) and deep learning techniques to develop and validate a new automated quantitative histological classification tool, named AutoFibroNet (Automated Liver Fibrosis Grading Network), for accurately staging liver fibrosis in MAFLD. METHODS: AutoFibroNet was developed in a training cohort that consisted of 203 Chinese adults with biopsy-confirmed MAFLD. Three deep learning models (VGG16, ResNet34, and MobileNet V3) were used to train pre-processed images and test data sets. Multi-layer perceptrons were used to fuse data (deep learning features, clinical features, and manual features) to build a joint model. This model was then validated in two further independent cohorts. RESULTS: AutoFibroNet showed good discrimination in the training set. For F0, F1, F2 and F3-4 fibrosis stages, the area under the receiver operating characteristic curves (AUROC) of AutoFibroNet were 1.00, 0.99, 0.98 and 0.98. The AUROCs of F0, F1, F2 and F3-4 fibrosis stages for AutoFibroNet in the two validation cohorts were 0.99, 0.83, 0.80 and 0.90 and 1.00, 0.83, 0.80 and 0.94, respectively, showing a good discriminatory ability in different cohorts. CONCLUSION: AutoFibroNet is an automated quantitative tool that accurately identifies histological stages of liver fibrosis in Chinese individuals with MAFLD.

Scalable synthesis of coordinatively unsaturated metal-nitrogen sites for large-scale CO2 electrolysis.

Practical electrochemical CO2-to-CO conversion requires a non-precious catalyst to react at high selectivity and high rate. Atomically dispersed, coordinatively unsaturated metal-nitrogen sites have shown great performance in CO2 electroreduction; however, their controllable and large-scale fabrication still remains a challenge. Herein, we report a general method to fabricate coordinatively unsaturated metal-nitrogen sites doped within carbon nanotubes, among which cobalt single-atom catalysts can mediate efficient CO2-to-CO formation in a membrane flow configuration, achieving a current density of 200 mA cm-2 with CO selectivity of 95.4% and high full-cell energy efficiency of 54.1%, outperforming most of CO2-to-CO conversion electrolyzers. By expanding the cell area to 100 cm2, this catalyst sustains a high-current electrolysis at 10 A with 86.8% CO selectivity and the single-pass conversion can reach 40.4% at a high CO2 flow rate of 150 sccm. This fabrication method can be scaled up with negligible decay in CO2-to-CO activity. In situ spectroscopy and theoretical results reveal the crucial role of coordinatively unsaturated metal-nitrogen sites, which facilitate CO2 adsorption and key *COOH intermediate formation.

Isolation of Highly Reactive Cobalt Phthalocyanine via Electrochemical Activation for Enhanced CO2 Reduction Reaction.

Electrochemical CO2 -to-CO conversion offers an attractive and efficient route to recycle CO2 greenhouse gas. Molecular catalysts, like CoPc, are proved to be possible replacement for precious metal-based catalysts. These molecules, a combination of metal center and organic ligand molecule, may evolve into single atom structure for enhanced performance; besides, the manipulation of molecules' behavior also plays an important role in mechanism research. Here, in this work, the structure evolution of CoPc molecules is investigated via electrochemical-induced activation process. After numbers of cyclic voltammetry scanning, CoPc molecular crystals become cracked and crumbled, meanwhile the released CoPc molecules migrate to the conductive substrate. Atomic-scale HAADF-STEM proves the migration of CoPc molecules, which is the main reason for the enhancement in CO2 -to-CO performance. The as-activated CoPc exhibits a maximum FECO of 99% in an H-type cell and affords a long-term durability at 100 mA cm-2 for 29.3 h in a membrane electrode assembly reactor. Density-functional theory (DFT) calculation also demonstrates a favorable CO2 activation energy with such an activated CoPc structure. This work provides a different perspective for understanding molecular catalysts as well as a reliable and universal method for practical utilization.

Tuning the Microenvironment in Monolayer MgAl Layered Double Hydroxide for CO2 -to-Ethylene Electrocatalysis in Neutral Media.

The electrocatalytic reduction of carbon dioxide provides a feasibility to achieve a carbon-neutral energy cycle. However, there are a number of bottleneck issues to be resolved before industrial application, such as the low conversion efficiency, selectivity and reaction rate, etc. Engineering local environment is a critical way to address these challenges. Here, a monolayer MgAl-LDH was proposed to optimize the local environment of Cu for stimulating industrial-current-density CO2 -to-C2 H4 electroreduction in neutral media. In situ spectroscopic results and theoretical study demonstrated that the Cu electrode modified by MgAl-LDH (MgAl-LDH/Cu) displayed a much higher surface pH value compared to the bare Cu, which could be attributed to the decreased energy barrier for hydrolysis on MgAl-LDH sites with more OH- ions on the surface of the electrode. As a result, MgAl-LDH/Cu achieved a C2 H4 Faradaic efficiency of 55.1 % at a current density up to 300 mA cm-2 in 1.0 M KHCO3 electrolyte.

Novel urinary protein panels for the non-invasive diagnosis of non-alcoholic fatty liver disease and fibrosis stages.

BACKGROUND & AIMS: There is an unmet clinical need for non-invasive tests to diagnose non-alcoholic fatty liver disease (NAFLD) and individual fibrosis stages. We aimed to test whether urine protein panels could be used to identify NAFLD, NAFLD with fibrosis (stage F ≥ 1) and NAFLD with significant fibrosis (stage F ≥ 2). METHODS: We collected urine samples from 100 patients with biopsy-confirmed NAFLD and 40 healthy volunteers, and proteomics and bioinformatics analyses were performed in this derivation cohort. Diagnostic models were developed for detecting NAFLD (UPNAFLD model), NAFLD with fibrosis (UPfibrosis model), or NAFLD with significant fibrosis (UPsignificant fibrosis model). Subsequently, the derivation cohort was divided into training and testing sets to evaluate the efficacy of these diagnostic models. Finally, in a separate independent validation cohort of 100 patients with biopsy-confirmed NAFLD and 45 healthy controls, urinary enzyme-linked immunosorbent assay analyses were undertaken to validate the accuracy of these new diagnostic models. RESULTS: The UPfibrosis model and the UPsignificant fibrosis model showed an AUROC of .863 (95% CI: .725-1.000) and 0.858 (95% CI: .712-1.000) in the training set; and .837 (95% CI: .711-.963) and .916 (95% CI: .825-1.000) in the testing set respectively. The UPNAFLD model showed an excellent diagnostic performance and the area under the receiver operator characteristic curve (AUROC) exceeded .90 in the derivation cohort. In the independent validation cohort, the AUROC for all three of the above diagnostic models exceeded .80. CONCLUSIONS: Our newly developed models constructed from urine protein biomarkers have good accuracy for non-invasively diagnosing liver fibrosis in NAFLD.

Positive Valent Metal Sites in Electrochemical CO2 Reduction Reaction.

The discovery of high-performance catalysts for the electrochemical CO2 reduction reaction (CO2 RR) has faced an enormous challenge for years. The lack of cognition about the surface active structures or centers of catalysts in complex conditions limits the development of advanced catalysts for CO2 RR. Recently, the positive valent metal sites (PVMS) are demonstrated as a kind of potential active sites, which can facilitate carbon dioxide (CO2 ) activation and conversation but are always unstable under reduction potentials. Many advanced technologies in theory and experiment have been utilized to understand and develop excellent catalysts with PVMS for CO2 RR. Here, we present an introduction of some typical catalysts with PVMS in CO2 RR and give some understanding of the activity and stability for these related catalysts.

N-terminal propeptide of type 3 collagen-based sequential algorithm can identify high-risk steatohepatitis and fibrosis in MAFLD.

BACKGROUND AND AIMS: With metabolic dysfunction-associated fatty liver disease (MAFLD) incidence and prevalence sharply increasing globally, there is an urgent need for non-invasive diagnostic tests to accurately screen high-risk MAFLD patients for liver inflammation and fibrosis. We aimed to develop a novel sequential algorithm based on N-terminal propeptide of type 3 collagen (PRO-C3) for disease risk stratification in patients with MAFLD. METHODS: A derivation and independent validation cohort of 327 and 142 patients with biopsy-confirmed MAFLD were studied. We compared the diagnostic performances of various non-invasive scores in different disease states, and a novel sequential algorithm was constructed by combining the best performing non-invasive scores. RESULTS: For patients with high-risk progressive steatohepatitis (i.e., steatohepatitis + NAFLD activity score ≥ 4 + F ≥ 2), the AUROC of FAST score was 0.801 (95% confidence interval (CI): 0.739-0.863), and the negative predictive value (NPV) was 0.951. For advanced fibrosis (≥ F3) and cirrhosis (F4), the AUROCs of ADAPT and Agile 4 were 0.879 (95%CI 0.825-0.933) and 0.943 (95%CI 0.892-0.994), and the NPV were 0.972 and 0.992. Sequential algorithm of ADAPT + Agile 4 combination was better than other combinations for risk stratification of patients with severe fibrosis (AUROC = 0.88), with similar results in the validation cohort. Meanwhile, in all subgroup analyses (stratifying by sex, age, diabetes, NAS, BMI and ALT), ADAPT + Agile 4 had a good diagnostic performance. CONCLUSIONS: The new sequential algorithm reliably identifies liver inflammation and fibrosis in MAFLD, making it easier to exclude low-risk patients and recommending high-risk MAFLD patients for clinical trials and emerging pharmacotherapies.

Oxygen Evolution Electrocatalysts for the Proton Exchange Membrane Electrolyzer: Challenges on Stability.

Hydrogen generated by proton exchange membrane (PEM) electrolyzer holds a promising potential to complement the traditional energy structure and achieve the global target of carbon neutrality for its efficient, clean, and sustainable nature. The acidic oxygen evolution reaction (OER), owing to its sluggish kinetic process, remains a bottleneck that dominates the efficiency of overall water splitting. Over the past few decades, tremendous efforts have been devoted to exploring OER activity, whereas most show unsatisfying stability to meet the demand for industrial application of PEM electrolyzer. In this review, systematic considerations of the origin and strategies based on OER stability challenges are focused on. Intrinsic deactivation of the material and the extrinsic balance of plant-induced destabilization are summarized. Accordingly, rational strategies for catalyst design including doping and leaching, support effect, coordination effect, strain engineering, phase and facet engineering are discussed for their contribution to the promoted OER stability. Moreover, advanced in situ/operando characterization techniques are put forward to shed light on the OER pathways as well as the structural evolution of the OER catalyst, giving insight into the deactivation mechanisms. Finally, outlooks toward future efforts on the development of long-term and practical electrocatalysts for the PEM electrolyzer are provided.

Activity Self-Optimization Steered by Dynamically Evolved Fe3+@Fe2+ Double-Center on Fe2O3 Catalyst for NH3-SCR.

Identification of the active centers dynamically stable under the reaction condition is of paramount importance but challenging because of the limited knowledge of steady-state chemistry on catalysts at the atomic level. Herein, focusing on the Fe2O3 catalyst for the selective catalytic reduction of NO with NH3 (NH3-SCR) as a model system, we reveal quantitatively the self-evolving Fe3+@Fe2+ (∼1:1) double-centers under the in-situ condition by the first-principles microkinetic simulations, which enables the accurate prediction of the optimal industry operating temperature (590 K). The cooperation of this double-center achieves the self-optimization of catalytic activity and rationalizes the intrinsic origin of Fe2O3 catalyzing NH3-SCR at middle-high temperatures instead of high temperatures. Our findings demonstrate the atomic-level self-evolution of active sites and the dynamically adjusted activity variation of the catalyst under the in-situ condition during the reaction process and provide insights into the reaction mechanism and catalyst optimization.

Molecularly Distorted Local Structure in Bi2 CuO4 Oxide to Stabilize Lattice Oxygen for Efficient Formate Electrosynthesis.

The electrochemical CO2 reduction reaction (CO2 RR) provides an economically feasible way for converting green energy into valuable chemical feedstocks and fuels. Great progress has been achieved in the understanding and synthesis of oxidized-based precatalysts; however, their dynamical changes of local structure under operando conditions still hinder their further applications. Here a molecularly distorted Bi2 CuO4 precatalyst for efficient CO2 -to-formate conversion is reported. X-ray absorption fine structure (XAFS) results and theoretical calculations suggest that the distorted structure with molecularly like [CuO4 ]6- unit rotation is more conducive to the structural stability of the sample. Operando XAFS and scanning transmission electron microscopy (STEM) results prove that quite a bit of lattice oxygen can remain in the distorted sample after CO2 RR. Electrochemical measurements of the distorted sample show an excellent activity and selectivity with a high formate partial current density of 194.6 mA cm-2 at an extremely low overpotential of -400 mV. Further in situ surface-enhanced infrared absorption spectroscopy (SEIRAS) and density functional theory (DFT) calculations illustrate that the retained oxygen can optimize the adsorption of *OCHO intermediate for the enhanced CO2 RR performance.

Low skeletal muscle mass is associated with more severe histological features of non-alcoholic fatty liver disease in male.

BACKGROUND/PURPOSE OF THE STUDY: Although low skeletal muscle mass is associated with non-alcoholic fatty liver disease (NAFLD), it is currently uncertain whether there are associations between weight-adjusted appendicular skeletal muscle (ASM%), severity of histological features of NAFLD, and the patatin-like phospholipase domain-containing 3 (PNPLA3) rs738409 polymorphism. Our aim was to test for a possible influence of the PNPLA3 rs738409 variant on the association between ASM% and severity of NAFLD histological features. METHODS: We enrolled 401 Chinese male with biopsy-proven NAFLD. Using a bioelectrical-impedance body composition analyzer (BIA, Inbody 720, Japan Inc., Tokyo), we calculated the ASM% as the percentage of total appendicular skeletal muscle mass (ASM, kg)/total body mass (kg) × 100. RESULTS: Compared to those with high ASM%, patients with low ASM% (≤ 30.6, i.e., the median value of distribution of the whole sample) had a greater severity of individual histological features of NAFLD. These patients also had a higher risk of severe steatosis and non-alcoholic steatohepatitis (NASH) (adjusted-odds ratio [OR] 2.34, 95% CI 1.39-3.93, and adjusted-OR 2.22, 95% CI 1.30-3.77) even after adjusting for age, body mass index, diabetes, and serum creatinine levels. Carriage of the G allele of PNPLA3 rs738409 plus low ASM% was associated with a higher risk of severe steatosis and presence of liver fibrosis (OR 3.02, 95% CI 1.46-6.26, p = 0.003 and OR 2.18, 95% CI 1.03-4.60, p = 0.041 respectively), and there was a non-significant but borderline increased risk of NASH (OR 2.00, 95% CI 0.98-4.06, p = 0.056). CONCLUSIONS: Low ASM% and the presence of a G allele within PNPLA3 rs738409 is associated with more severe histological features of NAFLD.

Machine learning algorithms based on proteomic data mining accurately predicting the recurrence of hepatitis B-related hepatocellular carcinoma.

BACKGROUND AND AIM: Over 10% of hepatocellular carcinoma (HCC) cases recur each year, even after surgical resection. Currently, there is a lack of knowledge about the causes of recurrence and the effective prevention. Prediction of HCC recurrence requires diagnostic markers endowed with high sensitivity and specificity. This study aims to identify new key proteins for HCC recurrence and to build machine learning algorithms for predicting HCC recurrence. METHODS: The proteomics data for analysis in this study were obtained from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) database. We analyzed different proteins based on cases with or without recurrence of HCC. Survival analysis, Cox regression analysis, and area under the ROC curves (AUROC > 0.7) were used to screen for more significant differential proteins. Predictive models for HCC recurrence were developed using four machine learning algorithms. RESULTS: A total of 690 differentially expressed proteins between 50 relapsed and 77 non-relapsed hepatitis B-related HCC patients were identified. Seven of these proteins had an AUROC > 0.7 for 5-year survival in HCC, including BAHCC1, ESF1, RAP1GAP, RUFY1, SCAMP3, STK3, and TMEM230. Among the machine learning algorithms, the random forest algorithm showed the highest AUROC values (AUROC: 0.991, 95% CI 0.962-0.999) for identifying HCC recurrence, followed by the support vector machine (AUROC: 0.893, 95% Cl 0.824-0.956), the logistic regression (AUROC: 0.774, 95% Cl 0.672-0.868), and the multi-layer perceptron algorithm (AUROC: 0.571, 95% Cl 0.459-0.682). CONCLUSIONS: Our study identifies seven novel proteins for predicting HCC recurrence and the random forest algorithm as the most suitable predictive model for HCC recurrence.

Operando High-Valence Cr-Modified NiFe Hydroxides for Water Oxidation.

High-valence metal-doped multimetal (oxy)hydroxides outperform noble metal electrocatalysts for the oxygen evolution reaction (OER) owing to the modified energetics between 3d metals and high-valence dopants. However, the rational design of sufficient and subtle modulators is still challenging. With a multimetal layered double hydroxide (LDH) as the OER catalyst, this study introduces a series of operando high-valence dopants (Cr, Ru, Ce, and V), which can restrict the 3+ valence states in the LDH template to prevent phase separation and operando transfer to the >3+ valence states for sufficient electronic interaction during the OER process. Through density functional theory simulations, ultrathin Cr-doped NiFe (NiFeCr) LDH is synthesized with strong electronic interaction between Cr dopants and NiFe bimetallic sites, evidenced by X-ray absorption spectroscopy. The resulting NiFeCr-LDH catalyzes the OER with ultralow overpotentials of 189 and 284 mV, obtaining current densities of 10 and 1000 mA cm-2 , respectively. Further, a NiFeCr-LDH anode is coupled in the anion exchange membrane electrolyzers to promote alkaline water splitting and CO2 -to-CO electrolysis, which achieves low full cell voltages at high current densities.

In Operando Identification of In Situ Formed Metalloid Zincδ+ Active Sites for Highly Efficient Electrocatalyzed Carbon Dioxide Reduction.

Electrochemical CO2 -to-CO conversion provides a possible way to address problems associated with the greenhouse effect; however, developing low-cost electrocatalysts to mediate high-efficiency CO2 reduction remains a challenge on account of the limited understanding of the nature of the real active sites. Herein, we reveal the Znδ+ metalloid sites as the real active sites of stable nonstoichiometric ZnOx structure derived from Zn2 P2 O7 through operando X-ray absorption fine structure analysis in conjunction with evolutionary-algorithm-based global optimization. Furthermore, theoretical and experimental results demonstrated that Znδ+ metalloid active sites could facilitate the activation of CO2 and the hydrogenation of *CO2 , thus accelerating the CO2 -to-CO conversion. Our work establishes a critical fundamental understanding of the origin of the real active center in the zinc-based electrocatalysts for CO2 reduction reaction.

Boosting Photocatalytic Water Oxidation Over Bifunctional Rh0 -Rh3+ Sites.

Photocatalytic water splitting provides an economically feasible way for converting solar energy into hydrogen. Great efforts have been devoted to developing efficient photocatalysts; however, the surface catalytic reactions, especially for the sluggish oxygen evolution reaction (OER), still remain a challenge, which limits the overall photocatalytic energy efficiency. Herein, we design a Rhn cluster cocatalyst, with Rh0 -Rh3+ sites anchoring the Mo-doped BiVO4 model photocatalytic system. The resultant photocatalyst enables a high visible-light photocatalytic oxygen production activity of 7.11 mmol g-1 h-1 and an apparent quantum efficiency of 29.37 % at 420 nm. The turnover frequency (TOF) achieves 416.73 h-1 , which is 378 times higher than that of the photocatalyst only with Rh3+ species. Operando X-ray absorption characterization shows the OER process on the Rh0 -Rh3+ sites. The DFT calculations further illustrate a bifunctional OER mechanism over the Rh0 -Rh3+ sites, in which the oxygen intermediate attacks the Rh3+ sites with assistance of a hydrogen atom transfer to the Rh0 sites, thus breaking the scaling relationship of various oxygen intermediates.

Graphite carbon nitride doped with a benzene ring for enhanced photocatalytic H2 evolution.

Graphitic carbon nitride (g-C3N4) has been identified as a promising material for photocatalytic hydrogen (H2) production, but it shows a low activity. Herein, g-C3N4 doped with a benzene ring (B-CNx) was synthesized via a simple thermal polycondensation method, exhibits 5.4 times higher H2 evolution rate than the pristine one, and achieves a high apparent quantum yield of 4.11% at 420 nm.

[Application of multiplex rt-PCR assay for screening rare or cryptic chromosome translocations in de novo patients with acute myeloid leukemia].

This study was aimed to investigate the clinical feasibility of using multiplex PT-PCR assay for screening rare/cryptic chromosome translocations in patients with de novo acute myeloid leukemia. For 126 patients with de novo AML-M4/M5 without common chromosome translocations including t(15;17), t(8;21) and t(16;16), 3 parallel multiplex RT-PCR assays were set up to detect 6 mll-related gene rearrangements (mll/af10, mll/af17, mll/ell, mll/af9, mll/af6 and mll/enl) with low detection rate and 4 rare fusion genes (dek/can, tls/erg, aml1/mds (evi1) and npm/mlf1). The results showed that 11 patients with positive result from 126 patients were detected which involved in 5 molecular abnormalities. Among them, 10 cases were AML-M5 (16.67%), 1 cases AML-M4 (1.51%). The marker chromosomes were observed in 2 cases out of 11 cases through conventional karyotyping analysis, the karyotyping analysis in 1 case was not performed because this case had 1 mitotic figure only, no any cytogenetic aberrations were found in other 8 cases through R-band karyotyping analysis. It is concluded that multiplex RT-PCR designed in this study can quickly, effectively and accurately identify the rare/cryptic chromosome translocations and can be used in clinical detection.