Self-Supported WO3@RuO2 Nanowires for Electrocatalytic Acidic Water Oxidation.

Developing catalysts with high catalytic activity and stability in acidic media is crucial for advancing hydrogen production in proton exchange membrane water electrolyzers (PEMWEs). To this end, a self-supported WO3@RuO2 nanowire structure was grown in situ on a titanium mesh using hydrothermal and ion-exchange methods. Despite a Ru loading of only 0.098 wt %, it achieves an overpotential of 246 mV for the oxygen evolution reaction (OER) at a current density of 10 mA·cm-2 in acidic 0.5 M H2SO4 while maintaining excellent stability over 50 h, much better than that of the commercial RuO2. After the establishment of the WO3@RuO2 heterostructure, a reduced overpotential of the rate-determining step from M-O* to M-OOH* is confirmed by the DFT calculation. Meanwhile, its enhanced OER kinetics are also greatly improved by this self-supported system in the absence of the organic binder, leading to a reduced interface resistance between active sites and electrolytes. This work presents a promising approach to minimize the use of noble metals for large-scale PEMWE applications.

Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.

AIM: This study aims to utilize machine learning (ML) and logistic regression (LR) models to predict surgical outcomes among patients with traumatic brain injury (TBI) based on admission examination, assisting in making optimal surgical treatment decision for these patients. METHOD: We conducted a retrospective review of patients hospitalized in our department for moderate-to-severe TBI. Patients admitted between October 2011 and October 2022 were assigned to the training set, while patients admitted between November 2022 and May 2023 were designated as the external validation set. Five ML algorithms and LR model were employed to predict the postoperative Glasgow Outcome Scale (GOS) status at discharge using clinical and routine blood data collected upon admission. The Shapley (SHAP) plot was utilized for interpreting the models. RESULTS: A total of 416 patients were included in this study, and they were divided into the training set (n = 396) and the external validation set (n = 47). The ML models, using both clinical and routine blood data, were able to predict postoperative GOS outcomes with area under the curve (AUC) values ranging from 0.860 to 0.900 during the internal cross-validation and from 0.801 to 0.890 during the external validation. In contrast, the LR model had the lowest AUC values during the internal and external validation (0.844 and 0.567, respectively). When blood data was not available, the ML models achieved AUCs of 0.849 to 0.870 during the internal cross-validation and 0.714 to 0.861 during the external validation. Similarly, the LR model had the lowest AUC values (0.821 and 0.638, respectively). Through repeated cross-validation analysis, we found that routine blood data had a significant association with higher mean AUC values in all ML and LR models. The SHAP plot was used to visualize the contributions of all predictors and highlighted the significance of blood data in the lightGBM model. CONCLUSION: The study concluded that ML models could provide rapid and accurate predictions for postoperative GOS outcomes at discharge following moderate-to-severe TBI. The study also highlighted the crucial role of routine blood tests in improving such predictions, and may contribute to the optimization of surgical treatment decision-making for patients with TBI.

Covalent Organic Framework Ionomer Steering the CO2 Electroreduction Pathway on Cu at Industrial-Grade Current Density.

CO2 electroreduction holds great promise for addressing global energy and sustainability challenges. Copper (Cu) shows great potential for effective conversion of CO2 toward specific value-added and/or high-energy-density products. However, its limitation lies in relatively low product selectivity. Herein, we present that the CO2 reduction reaction (CO2RR) pathway on commercially available Cu can be rationally steered by modulating the microenvironment in the vicinity of the Cu surface with two-dimensional sulfonated covalent organic framework nanosheet (COF-NS)-based ionomers. Specifically, the selectivity toward methane (CH4) can be enhanced to more than 60% with the total current density up to 500 mA cm-2 in flow cells in both acidic (pH = 2) and alkaline (pH = 14) electrolytes. The COF-NS, characterized by abundant apertures, can promote the accumulation of CO2 and K+ near the catalyst surface, alter the adsorption energy and surface coverage of *CO, facilitate the dissociation of H2O, and finally modulate the reaction pathway for the CO2RR. Our approach demonstrates the rational modulation of reaction interfaces for the CO2RR utilizing porous open framework ionomers, showcasing their potential practical applications.

Machine learning models for predicting in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury.

AIM: This study aims to develop prediction models for in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury (TBI). METHOD: We conducted a retrospective review of patients hospitalized for moderate-to-severe TBI in our department from 2011 to 2020. Five machine learning (ML) algorithms and the conventional logistic regression (LR) model were employed to predict in-hospital mortality and the Glasgow Outcome Scale (GOS) functional outcomes. These models utilized clinical and routine blood data collected upon admission. RESULTS: This study included a total of 196 patients who received only non-surgical treatment after moderate-to-severe TBI. When predicting mortality, ML models achieved area under the curve (AUC) values of 0.921 to 0.994 using clinical and routine blood data, and 0.877 to 0.982 using only clinical data. In comparison, LR models yielded AUCs of 0.762 and 0.730 respectively. When predicting the GOS outcome, ML models achieved AUCs of 0.870 to 0.915 using clinical and routine blood data, and 0.858 to 0.927 using only clinical data. In comparison, the LR model yielded AUCs of 0.798 and 0.787 respectively. Repeated internal validation showed that the contributions of routine blood data for prediction models may depend on different prediction algorithms and different outcome measurements. CONCLUSION: The study reported ML-based prediction models that provided rapid and accurate predictions on short-term outcomes after non-surgical treatment among patients with moderate-to-severe TBI. The study also highlighted the superiority of ML models over conventional LR models and proposed the complex contributions of routine blood data in such predictions.

Correlation between intraosseous thermal change and drilling impulse data during osteotomy within autonomous dental implant robotic system: An in vitro study.

OBJECTIVES: This study aims at examining the correlation of intraosseous temperature change with drilling impulse data during osteotomy and establishing real-time temperature prediction models. MATERIALS AND METHODS: A combination of in vitro bovine rib model and Autonomous Dental Implant Robotic System (ADIR) was set up, in which intraosseous temperature and drilling impulse data were measured using an infrared camera and a six-axis force/torque sensor respectively. A total of 800 drills with different parameters (e.g., drill diameter, drill wear, drilling speed, and thickness of cortical bone) were experimented, along with an independent test set of 200 drills. Pearson correlation analysis was done for linear relationship. Four machining learning (ML) algorithms (e.g., support vector regression [SVR], ridge regression [RR], extreme gradient boosting [XGboost], and artificial neural network [ANN]) were run for building prediction models. RESULTS: By incorporating different parameters, it was found that lower drilling speed, smaller drill diameter, more severe wear, and thicker cortical bone were associated with higher intraosseous temperature changes and longer time exposure and were accompanied with alterations in drilling impulse data. Pearson correlation analysis further identified highly linear correlation between drilling impulse data and thermal changes. Finally, four ML prediction models were established, among which XGboost model showed the best performance with the minimum error measurements in test set. CONCLUSION: The proof-of-concept study highlighted close correlation of drilling impulse data with intraosseous temperature change during osteotomy. The ML prediction models may inspire future improvement on prevention of thermal bone injury and intelligent design of robot-assisted implant surgery.

Genome-wide DNA methylation analysis identifies potent CpG signature for temzolomide response in non-G-CIMP glioblastomas with unmethylated MGMT promoter: MGMT-dependent roles of GPR81.

PURPOSES: To identify potent DNA methylation candidates that could predict response to temozolomide (TMZ) in glioblastomas (GBMs) that do not have glioma-CpGs island methylator phenotype (G-CIMP) but have an unmethylated promoter of O-6-methylguanine-DNA methyltransferase (unMGMT). METHODS: The discovery-validation approach was planned incorporating a series of G-CIMP-/unMGMT GBM cohorts with DNA methylation microarray data and clinical information, to construct multi-CpG prediction models. Different bioinformatic and experimental analyses were performed for biological exploration. RESULTS: By analyzing discovery sets with radiotherapy (RT) plus TMZ versus RT alone, we identified a panel of 64 TMZ efficacy-related CpGs, from which a 10-CpG risk signature was further constructed. Both the 64-CpG panel and the 10-CpG risk signature were validated showing significant correlations with overall survival of G-CIMP-/unMGMT GBMs when treated with RT/TMZ, rather than RT alone. The 10-CpG risk signature was further observed for aiding TMZ choice by distinguishing differential outcomes to RT/TMZ versus RT within each risk subgroup. Functional studies on GPR81, the gene harboring one of the 10 CpGs, indicated its distinct impacts on TMZ resistance in GBM cells, which may be dependent on the status of MGMT expression. CONCLUSIONS: The 64 TMZ efficacy-related CpGs and in particular the 10-CpG risk signature may serve as promising predictive biomarker candidates for guiding optimal usage of TMZ in G-CIMP-/unMGMT GBMs.

Hybrid Crosslinked Solid Polymer Electrolyte via In-Situ Solidification Enables High-Performance Solid-State Lithium Metal Batteries.

Solid-state lithium-metal batteries constructed by in-situ solidification of cyclic ether are considered to be a critical strategy for the next generation of solid-state batteries with high energy density and safety. However, the poor thermal/electrochemical stability of linear polyethers and severe interfacial reactions limit its further development. Herein, in-situ ring-opening hybrid crosslinked polymerization is proposed for organic/inorganic hybrid polymer electrolyte (HCPE) with superior ionic conductivity of 2.22 × 10-3 S cm-1 at 30 °C, ultrahigh Li+ transference number of 0.88, and wide electrochemical stability window of 5.2 V. These allow highly stable lithium stripping/plating cycling for over 1000 h at 1 mA cm-2 , which also reveal a well-defined interfacial stabilization mechanism. Thus, HCPE endows assembled solid-state lithium-metal batteries with excellent long-cycle performance over 600 cycles at 2 C (25 °C) and superior capacity retention of 92.1%. More importantly, the proposed noncombustible HCPE opens up a new frontier to promote the practical application of high safety and high energy density solid-state batteries via in-situ solidification.

One new 12, 8-guaianolide sesquiterpene lactone with antihyperglycemic activity from the roots of Cichorium intybus.

Three 12, 8-guaianolide sesquiterpene lactones, including a new compound intybusin F (1), and a new natural product cichoriolide I (2), along with six known 12, 6-guaianolide compounds (4-9) were isolated from the roots of Cichorium intybus L. Their structures were determined by extensive spectroscopic analysis. The absolute configurations of new compounds were elucidated based on analysis of the experimental and calculated electronic circular dichroism spectra. Compounds 1, 2, 4, 7, 8 showed significant effects on facilitating the glucose uptake in oleic acid plus high glucose-stimulated HepG2 cells at 50 µM. In addition, compounds 1, 2, 3, 6, 7 exhibited obvious inhibitory effects against NO production, of them, compounds 1, 2, 7 can significantly decrease the secretion of inflammatory cytokines (TNF-α, IL-6 and COX-2) levels in this hyperglycemic HepG2 cell model.

The phylogeny and taxonomy of Glypholecia (Acarosporaceae, lichenized Ascomycota), including a new species from northwestern China.

Glypholeciaqinghaiensis An C. Yin, Q. Y. Zhong & Li S. Wang is described as new to science. It is characterized by its squamulose thallus, compound apothecia, ellipsoid ascospores, and the presence of rhizines on the lower surface of the thallus. A phylogenetic tree of Glypholecia species was constructed based on nrITS and mtSSU sequences. Two species G.qinghaiensis and G.scabra are confirmed in China.

Machine learning algorithms for improved prediction of in-hospital outcomes after moderate-to-severe traumatic brain injury: a Chinese retrospective cohort study.

AIM: Controversy remains high over the superiority of advanced machine learning (ML) algorithms to conventional logistic regression (LR) in the prediction of prognosis after traumatic brain injury (TBI). This study aimed to compare the performance of ML and LR models in predicting in-hospital prognosis after TBI. METHOD: In a single-center retrospective cohort of adult patients hospitalized for moderate-to-severe TBI (Glasgow coma score ≤12) in our hospital from 2011 to 2020, LR and three ML algorithms (XGboost, lightGBM, and FT-transformer) were run to build prediction models for in-hospital mortality and the Glasgow Outcome Scale (GOS) functional outcomes using either all 19 clinical and laboratory features or the 10 non-laboratory ones collected at admission to the neurological intensive care unit. The Shapley (SHAP) value was used for model interpretation. RESULT: In total, 482 patients had an in-hospital mortality rate of 11.0%. A total of 23.0% of the patients had good functional scores (GOS ≥ 4) at discharge. All ML models performed better than the LR model in predicting in-hospital prognosis after TBI, among which the lightGBM model showed the best performance: When predicting mortality, the lightGBM model yielded an area under the curve (AUC) of 0.953 using all 19 features (the LR model: 0.813) and an AUC of 0.935 using 10 non-laboratory features (the LR model: 0.803); when predicting GOS functional outcomes, it yielded an AUC of 0.913 using all 19 features (the LR model: 0.832) and an AUC of 0.889 using non-laboratory data (the LR model: 0.818). The SHAP method identified key contributors to explain the lightGBM models. Finally, the integration of the lightGBM models with different prediction purposes was found to provide refined prognostic information, particularly for patients who survived moderate-to-severe TBI. CONCLUSION: The study supported the superiority of ML to LR in predicting prognosis after moderate-to-severe TBI and highlighted its potential use for clinical application.

Evidence for structural control of mare volcanism in lunar compressional tectonic settings.

One of the long-standing enigmas for lunar tectonic-thermal evolution is the spatiotemporal association of contractional wrinkle ridges and basaltic volcanism in a compressional regime. Here, we show that most of the 30 investigated volcanic (eruptive) centers are linked to contractional wrinkle ridges developed above preexisting basin basement-involved ring/rim normal faults. Based on the tectonic patterns associated with the basin formation and mass loading and considering that during the subsequent compression the stress was not purely isotropic, we hypothesize that tectonic inversion produced not only thrust faults but also reactivated structures with strike-slip and even extensional components, thus providing a valid mechanism for magma transport through fault planes during ridge faulting and folding of basaltic layers. Our findings suggest that lunar syn-tectonic mare emplacement along reactivated inherited faults provides important records of basin-scale structure-involved volcanism, which is more complex than previously considered.

Controllable Crystallization of Two-Dimensional Bi Nanocrystals with Morphology-Boosted CO2 Electroreduction in Wide pH Environments.

Two-dimensional low-melting-point (LMP) metal nanocrystals are attracting increasing attention with broad and irreplaceable applications due to their unique surface and topological structures. However, the chemical synthesis, especially the fine control over the nucleation (reduction) and growth (crystallization), of such LMP metal nanocrystals remains elusive as limited by the challenges of low standard redox potential, low melting point, poor crystalline symmetry, etc. Here, a controllable reduction-melting-crystallization (RMC) protocol to synthesize free-standing and surfactant-free bismuth nanocrystals with tunable dimensions, morphologies, and surface structures is presented. Especially, ultrathin bismuth nanosheets with flat or jagged surfaces/edges can be prepared with high selectivity. The jagged bismuth nanosheets, with abundant surface steps and defects, exhibit boosted electrocatalytic CO2 reduction performances in acidic, neutral, and alkaline aqueous solutions, achieving the maximum selectivity of near unity at the current density of 210 mA cm-2 for formate evolution under ambient conditions. This work creates the RMC pathway for the synthesis of free-standing two-dimensional LMP metal nanomaterials and may find broader applicability in more interdisciplinary applications.

Boosting CO2 Electroreduction on Bismuth Nanoplates with a Three-Dimensional Nitrogen-Doped Graphene Aerogel Matrix.

Electrochemical CO2 reduction reaction (CO2RR), which uses renewable electricity to produce high-value-added chemicals, offers an alternative clean path to the carbon cycle. However, bismuth-based catalysts show great potential for the conversion of CO2 and water to formate, but their overall efficiency is still hampered by the weak CO2 adsorption, low electrical conductivity, and slow mass transfer of CO2 molecules. Herein, we report that a rationally modulated nitrogen-doped graphene aerogel matrix (NGA) can significantly enhance the CO2RR performance of bismuth nanoplates (BiNPs) by both modulating the electronic structure of bismuth and regulating the interface for chemical reaction and mass transfer environments. In particular, the NGA prepared by reducing graphene oxide (GO) with hydrazine hydrate (denoted as NGAhdrz) exhibits significantly enhanced strong metal-support interaction (SMSI), increased specific surface area, strengthened CO2 adsorption, and modulated wettability. As a result, the Bi/NGAhdrz exhibits significantly boosted CO2RR properties, with a Faradaic efficiency (FE) of 96.4% at a current density of 51.4 mA cm-2 for formate evolution at a potential of -1.0 V versus reversible hydrogen electrode (vs RHE) in aqueous solution under ambient conditions.

Ultrathin Dendritic Pd-Ag Nanoplates for Efficient and Durable Electrocatalytic Reduction of CO2 to Formate.

CO2 reduction reactions (CO2 RR) powered by renewable electricity can directly convert CO2 to hydrocarbons and fix the sustainable but intermittent energy (e. g., sunlight, wind, etc.) in stable and portable chemical fuels. Advanced catalysts boosting CO2 RR with high activity, selectivity, and durability at low overpotentials are of great importance but still elusive. Here, we report that the ultrathin Pd-Ag dendritic nanoplates (PdAg DNPs) exhibited boosted activity, selectivity, and stability for producing formate from CO2 at a very low overpotential in aqueous solutions under ambient conditions. As a result, the PdAg DNPs exhibited a Faradaic efficiency (FE) for formate of 91% and a cathodic energy efficiency (EE) of ∼90% at the potential of -0.2 V versus reversible hydrogen electrode (vs. RHE), showing significantly enhanced durability as compared with pure Pd catalysts. Our strategy represents a rational catalyst design by engineering the surface geometrical and electronic structures of metal nanocrystals and may find more applicability in future electrocatalysis.

Hypersonic tracking control under actuator saturations via readjusting prescribed performance functions.

Prescribed performance control (PPC) has been shown to be an effective tool in pursuing prescribed transient and steady-state specifications. Unfortunately, the existing PPC is incapable of handling the peaking of errors caused by actuator saturations, which is due to the short of the ability of readjusting the prescribed performance functions. In this article, we propose a novel PPC scheme, namely the readjusting-performance-function-based approach, for hypersonic flight vehicles subject to actuator saturations. A new sort of performance functions containing readjusting terms are developed to impose prescribed constraints on the velocity tracking error and the altitude tracking error. More specially, the prescribed performance functions can be adaptively readjusted to guarantee that tracking errors are always within them. This eliminates the singular problem that is usually encountered by traditional PPC. To deal with the actuator saturation problem, a novel compensated system (CS) is exploited for the velocity dynamics. Then, the CS is further extended to the altitude subsystem by reforming it as a high-order formulation. Besides the aforementioned baseline controllers, optimal control protocols are also addressed based on adaptive dynamic programming. Finally, comparison simulation results are given to verify the advantages.

In-situ constructing self-supported NiO/RuO2 heterostructure for reinforced alkaline hydrogen evolution reaction.

Rationally designing a strongly coupled heterostructure with rich functional sites and high catalytic stability is essential for efficient energy conversion. This work synthesizes a self-supported NiO/RuO2 heterostructure for hydrogen production via facile dealloying following an in-situ electrochemical oxidation method. It only requires 88 ± 1 mV to drive a current density of -100 mA/cm2 in the alkaline electrolyte during hydrogen evolution reaction (HER), outperforming NiO, RuO2, and Pt foil. The higher anodic potential applied to the dealloyed ribbons results in lower overpotentials and faster reaction kinetics. Meanwhile, the catalytic activity and stability of the individual NiO can be significantly improved once coupled with a small amount of heterogeneous RuO2. The strong synergistic effect between NiO and RuO2 contributes to exposing abundant active sites, optimizing electronic structure, facilitating charge transfer at the interface, and most importantly, maintaining structural stability. These advantages make the self-supported NiO/RuO2 heterostructure a promising candidate for replacing the Pt-based catalysts.

Inverse micelle fabrication of ordered mesoporous manganese oxide and degradation of tetracycline hydrochloride.

Ordered mesoporous manganese oxides (MnOx) were synthesized using the modified inverse micelle method. The crystal structure and surface morphology were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The element content and changes in surface valence of catalysts were analyzed by X-ray photoelectron spectroscopy (XPS). The MnOx were used to activate peroxymonosulfate (PMS) to degrade tetracycline hydrochloride (TCH). The catalytic activity of MnOx was enhanced at a calcination temperature of 350 °C (MM-3). The degradation efficiency of TCH in MM-3/PMS system was 87.89% in 180 min. Appropriate dosages of catalyst and PMS improve the degradation efficiency of TCH. This system showed a wide range of pH application (3-9). In the presence of coexisting ions and humic acid, the degradation efficiency of TCH was still above 80%. The results of free radical capture experiment and electron paramagnetic resonance (EPR) test proved that the system activates PMS to produce three types of free radicals: SO4-, OH and 1O2. Therefore, MM-3 is a promising catalyst for the degradation of TCH in practical wastewater treatment.

Element immiscibility assisted Ru@Ni3B as an efficient electrocatalyst toward alkaline and acidic hydrogen evolution reaction.

Based on the element immiscibility of Ni-Ru, xRu@Ni3B (x = 0, 0.2, 0.5, 1.0) were facilely synthesized through a one-step dealloying method. Of them, 1.0Ru@Ni3B requires overpotentials of 40 ± 0.2 and 72 ± 0.3 mV to reach a current density of -20 mA cm-2 for acidic and alkaline hydrogen evolution reaction, respectively, which are close to or even better than those of metallic Pt foil. In addition, it could maintain superior catalytic and chemical stability after 24 hours of testing. This work provides a promising strategy for improving the atomic utilization efficiency of highly active noble metals toward the hydrogen evolution reaction (HER).

Controlled Synthesis of Intermetallic Au2 Bi Nanocrystals and Au2 Bi/Bi Hetero-Nanocrystals with Promoted Electrocatalytic CO2 Reduction Properties.

The electrocatalytic properties of metal nanoparticles (NPs) strongly depend on their compositions and structures. Rational design of alloys and/or heterostructures provides additional approaches to modifying their surface geometric and electronic structures for optimized electrocatalytic performance. Here, a solution synthesis of freestanding intermetallic Au2 Bi NPs, the heterostructures of Au2 Bi/Bi hetero-NPs, and their promoted electrocatalytic CO2 reduction reaction (CO2 RR) performances were reported. It was revealed that the formation and in-situ conversion of heterogeneous seeds (e. g., Au) were of vital importance for the formation of intermetallic Au2 Bi and Au2 Bi/Bi hetero-NPs. It was also found that the Au components would act as the structure promoter moderating the binding strength for key intermediates on Bi surfaces. The alloying of Bi with Au and the formation of heterogeneous Au2 Bi/Bi interfaces would create more surface active sites with modulated electronic structures and stronger adsorption strengths for key intermediates, promoting the CO2 -to-HCOOH conversion with high activity and selectivity. This work presents a novel route for preparing intermetallic nanomaterials with modulated surface geometric/electric structures and promoting their electrocatalytic activities with alloying effects and interfacial effects. Such strategy may find wide application in catalyst design and synthesis for more electrocatalytic reactions.

Achieving Total Enteroscopy by Consecutive Bidirectional Double-balloon Enteroscopy Procedures.

OBJECTIVE: To investigate the feasibility and safety of achieving total enteroscopy by consecutive bidirectional double-balloon enteroscopy (DBE) procedures. METHODS: The demographic data, indication, initial insertion route, examination time for each insertion and the entire procedure, total enteroscopy rate, diagnostic yield and adverse events of patients who attempted to achieve total enteroscopy by consecutive bidirectional DBE procedures from January 2014 to December 2019 were retrospectively analyzed. RESULTS: A total of 189 patients were included, and the total enteroscopy rate was 87.3%. Initiating the DBE procedure via the retrograde approach as the initial insertion route achieved a higher total enterosocpy rate (90.9% vs. 78.9%, P=0.023), with shorter overall examination time (134.2±36.2 vs. 156.9±47.6 min, P=0.017) and shorter examination time for the opposite insertion route (23.8±19.9 vs. 53.1±27.6 min, P=0.000) compared with anteograde approach as the initial insertion route. The overall diagnostic yield was 37.6%. The diagnostic yield for successfully achieving total enteroscopy was higher, when compared to the yield for not successfully achieving total enteroscopy (39.4% vs. 25%, P=0.029). The overall rate of adverse events was 2.1% (4/189). There was no significant difference in adverse event rate between the overall examination time ≥2 h group and <2 h group (2.1% vs. 2.0%, P=0.593). CONCLUSION: Consecutive bidirectional DBE procedure is an effective and safe strategy for achieving total enteroscopy with a considerable success rate. This may be a promising option and alternative to traditional methods, and helpful to more promptly establish a definite diagnosis. The retrograde approach, as the initial insertion route, is preferred in clinical practice.