Revealing the origin of dendritic deposition regulated solid electrolyte interphase enabled by cation receptor in Zn-ion batteries.

Aqueous Zn-metal batteries open up promising prospects for large-scale energy storage due to the advantages of ample components, cost-effectiveness, and safety features. However, the notorious dendritic development and unavoidable hydrogen evolution reaction of Zn have grown to be one of the main barriers inhibiting its further commercialization. Despite substantial studies, the mechanism of nucleation and deposition of Zn2+ ions on zinc layer surfaces remains elusive. Here, inspired by additive, the SnCl2 additive is introduced to initiate the in-situ formation of the ZnS-rich solid electrolyte interphase (SEI) layer on the Zn anode, which creates a protective "shielding effect" that hinders direct contact between water and the zinc surface, suppressing the random growth of Zn dendrites in the whole process. The mechanism of Zn nucleation was revealed by employing high-resolution transmission electron microscopy, consecutive electron diffraction coupled with finite element method (FEM) simulations. Moreover, spontaneously formed 3D architecture consists of micorsized hemispherical Sn particles not only suppresses the Zn dendrite growth by reducing the local current density, but also enables the lateral growth of Zn crystals by increasing the average surface energy. Such an electrolyte enables a long cycle life of over 2000 h in the Zn||Zn cell. Importantly, the assembled Zn||MnVO full cells with SnCl2 electrolyte also delivers substantial capacity (171.1mA h g-1 at 1 A h g-1), presenting a promising application. These discoveries not only deepen the comprehension of fundamental scientific knowledge regarding the microscopic reaction mechanism of the Zn anode but also offer significant insights for optimizing performance.

Deep Learning Enhanced in Situ Atomic Imaging of Ion Migration at Crystalline-Amorphous Interfaces.

Improving the performance of energy storage, neuromorphic computing, and more applications requires an in-depth understanding of ion transport at interfaces, which are often hindered by facile atomic reconfiguration at working conditions and limited characterization capability. Here, we construct an in situ double-tilt electric manipulator inside an aberration-corrected scanning transmission electron microscope. Coupled with deep learning-based image enhancement, atomic images are enhanced 3-fold compared to traditional methods to observe the potassium ion migration and microstructure evolution at the crystalline-amorphous interface in antimony selenide. Potassium ions form stable anisotropic insertion sites outside the (Sb4Se6) chain, with a few potassium ions present within the moieties. Combined experiments and density functional theory calculations reveal a reaction pathway of forming a novel metastable state during potassium ion insertion, followed by recovery and unexpected chirality changes at the interface upon potassium ion extraction. Our unique methodology paves the way for facilitating the improvement and rational design of nanostructured materials.

Non-invasive metabolic biomarkers in initial cognitive impairment in patients with diabetes: A systematic review and meta-analysis.

AIM: Diabetic cognitive impairment (DCI), considered one of the most severe and commonly overlooked complications of diabetes, has shown inconsistent findings regarding the metabolic profiles in DCI patients. This systematic review and meta-analysis aimed to identify dysregulated metabolites as potential biomarkers for early DCI, providing valuable insights into the underlying pathophysiological mechanisms. MATERIALS AND METHODS: A systematic search of four databases, namely PubMed, Embase, Web of Science and Cochrane, was conducted up to March 2024. Subsequently, a qualitative review of clinical studies was performed followed by a meta-analysis of metabolite markers. Finally, the sources of heterogeneity were explored through subgroup and sensitivity analyses. RESULTS: A total of 774 unique publications involving 4357 participants and the identification of multiple metabolites were retrieved. Of these, 13 clinical studies reported metabolite differences between the DCI and control groups. Meta-analysis was conducted for six brain metabolites and two metabolite ratios. The results revealed a significant increase in myo-inositol (MI) concentration and decreases in glutamate (Glu), Glx (glutamate and glutamine) and N-acetylaspartate/creatine (NAA/Cr) ratios in DCI, which have been identified as the most sensitive metabolic biomarkers for evaluating DCI progression. Notably, brain metabolic changes associated with cognitive impairment are more pronounced in type 2 diabetes mellitus than in type 1 diabetes mellitus, and the hippocampus emerged as the most sensitive brain region regarding metabolic changes associated with DCI. CONCLUSIONS: Our results suggest that MI, Glu, and Glx concentrations and NAA/Cr ratios within the hippocampus may serve as metabolic biomarkers for patients with early-stage DCI.

Fluorescent probe for imaging intercellular tension: molecular force approach.

Cellular mechanical force plays a crucial role in numerous biological processes, including wound healing, cell development, and metastasis. To enable imaging of intercellular tension, molecular tension probes were designed, which offer a simple and efficient method for preparing Au-DNA intercellular tension probes with universal applicability. The proposed approach utilizes gold nanoparticles linked to DNA hairpins, enabling sensitive visualization of cellular force in vitro. Specifically, the designed Au-DNA intercellular tension probe includes a molecular spring flanked by a fluorophore-quencher pair, which is anchored between cells. As intercellular forces open the hairpin, the fluorophore is de-quenched, allowing for visualization of cellular force. The effectiveness of this approach was demonstrated by imaging the cellular force in living cells using the designed Au-DNA intercellular tension probe.

A novel surgical scheme for hepatectomy in hepatocellular carcinoma patients with clinically significant portal hypertension.

OBJECTIVE: Clinically significant portal hypertension (CSPH) seriously affects the feasibility and safety of surgical treatment for hepatocellular carcinoma (HCC) patients. The aim of this study was to establish a new surgical scheme defining risk classification of post-hepatectomy liver failure (PHLF) to facilitate the surgical decision-making and identify suitable candidates for individual hepatectomy among HCC patients with CSPH. BACKGROUNDS: Hepatectomy is the preferred treatment for HCC. Surgeons must maintain a balance between the expected oncological outcomes of HCC removal and short-term risks of severe PHLF and morbidity. CSPH aggravates liver decompensation and increases the risk of severe PHLF thus complicating hepatectomy for HCC. METHODS: Multivariate logistic regression and stochastic forest algorithm were performed, then the independent risk factors of severe PHLF were included in a nomogram to determine the risk of severe PHLF. Further, a conditional inference tree (CTREE) through recursive partitioning analysis validated supplement the misdiagnostic threshold of the nomogram. RESULTS: This study included 924 patients, of whom 137 patients (14.8%) suffered from mild-CSPH and 66 patients suffered from (7.1%) with severe-CSPH confirmed preoperatively. Our data showed that preoperative prolonged prothrombin time, total bilirubin, indocyanine green retention rate at 15 min, CSPH grade, and standard future liver remnant volume were independent predictors of severe PHLF. By incorporating these factors, the nomogram achieved good prediction performance in assessing severe PHLF risk, and its concordance statistic was 0.891, 0.850 and 0.872 in the training cohort, internal validation cohort and external validation cohort, respectively, and good calibration curves were obtained. Moreover, the calculations of total points of diagnostic errors with 95% CI were concentrated in 110.5 (range 76.9-178.5). It showed a low risk of severe PHLF (2.3%), indicating hepatectomy is feasible when the points fall below 76.9, while the risk of severe PHLF is extremely high (93.8%) and hepatectomy should be rigorously restricted at scores over 178.5. Patients with points within the misdiagnosis threshold were further examined using CTREE according to a hierarchic order of factors represented by the presence of CSPH grade, ICG-R15, and sFLR. CONCLUSION: This new surgical scheme established in our study is practical to stratify risk classification in assessing severe PHLF, thereby facilitating surgical decision-making and identifying suitable candidates for individual hepatectomy.

Constructing Nano-Interlayer Inhibiting Interfacial Degradation toward High-Voltage PEO-Based All-Solid-State Lithium Batteries.

The interfacial instability between PEO-based solid electrolyte (SPE) and high-voltage cathode materials inhibits the longevity of high-energy-density all-solid-state polymer lithium metal batteries (ASSPLBs). Herein, for the first time it is demonstrated, that contact loss caused by gas generation from interfacial side reactions between the high-voltage cathode and solid polymer electrolyte (SPE) can also arise in ASSPLBs. To alleviate the interfacial side reactions, a LiNb0.6Ti0.5O3 (LNTO) layer is well coated on LiNi0.83Co0.07Mn0.1O2 (NCM83), denoted as (CNCM83). The LNTO layer with low electronic conductivity reduces the decomposition drive force of SPE. Furthermore, Ti and Nb in the LNTO layer spontaneously migrate inside the NCM83 surface to form a strong Ti/Nb─O bond, stalling oxygen evolution in high-voltage cathodes. The interfacial degradation phenomena, including SPE decomposition, detrimental phase transition and intragranular cracks of NCM83, and void formation between cathode and SPE, are effectively mitigated by the LNTO layer. Therefore, the growth rate of interfacial resistance (RCEI) decreases from 37.6 Ω h-0.5 for bare NCM83 to 2.4 Ω h-0.5 for CNCM83 at 4.2 V. Moreover, 4.2 V PEO-based ASSPLBs achieve impressive cyclability with high capacity retention of 135 mAh g-1 (75%) even after 300 cycles at 0.5 C.

Chronic myeloid leukaemia: Biology and therapy.

Chronic myeloid leukaemia (CML) is caused by BCR::ABL1. Tyrosine kinase-inhibitors (TKIs) are the initial therapy. Several organizations have reported milestones to evaluate response to initial TKI-therapy and suggest when a change of TKI should be considered. Achieving treatment-free remission (TFR) is increasingly recognized as the optimal therapy goal. Which TKI is the best initial therapy for which persons and what depth and duration of molecular remission is needed to achieve TFR are controversial. In this review we discuss these issues and suggest future research directions.

Mechanical homeostasis imbalance in hepatic stellate cells activation and hepatic fibrosis.

Chronic liver disease or repeated damage to hepatocytes can give rise to hepatic fibrosis. Hepatic fibrosis (HF) is a pathological process of excessive sedimentation of extracellular matrix (ECM) proteins such as collagens, glycoproteins, and proteoglycans (PGs) in the hepatic parenchyma. Changes in the composition of the ECM lead to the stiffness of the matrix that destroys its inherent mechanical homeostasis, and a mechanical homeostasis imbalance activates hepatic stellate cells (HSCs) into myofibroblasts, which can overproliferate and secrete large amounts of ECM proteins. Excessive ECM proteins are gradually deposited in the Disse gap, and matrix regeneration fails, which further leads to changes in ECM components and an increase in stiffness, forming a vicious cycle. These processes promote the occurrence and development of hepatic fibrosis. In this review, the dynamic process of ECM remodeling of HF and the activation of HSCs into mechanotransduction signaling pathways for myofibroblasts to participate in HF are discussed. These mechanotransduction signaling pathways may have potential therapeutic targets for repairing or reversing fibrosis.

Circular RNA hsa_circ_0005218 promotes the early recurrence of hepatocellular carcinoma by targeting the miR-31-5p/CDK1 pathway.

Increasing evidence has manifested that circular RNAs (circRNAs) exhibited critical function in regulating various signaling pathways related to hepatocellular carcinoma (HCC) recurrence. However, the role and mechanism of the circRNAs in the HCC early recurrence remain elusive. In this study, high-throughput RNA-sequencing (RNA-seq) analysis was conducted to identify the expression profile of circRNAs in HCC tissues and circ_0005218 was identified as one circRNA that significantly up-regulated in early recurrent HCC tissues. And patients with high expression of circ_0005218 showed worsen overall survival (OS) and disease-free survival (DFS). Moreover, the promotion effects of circ_0005218 on HCC cells in term of proliferation, invasion and metastasis were confirmed both in vitro and vivo by gain- and loss-of function assays. In addition, dual-luciferase reporter assays showed that circ_0005218 could competitively bind to micro-RNA (miR)-31-5p. Furthermore, we showed that suppression of CDK1 by miR-31-5p could be partially rescued by up-regulating circ_0005218. Taken together, the present study indicates that circ_0005218 absorbed miR-31-5p as a sponge to weaken its suppression on CDK1 expression, and thus boost HCC cell invasion and migration, which would act as a potential biomarker to predict the HCC early recurrence and as a new therapeutic target for treatment of HCC.

Immobilization of Cd2+ and Pb2+ by biomineralization of the carbonate mineralized bacterial consortium JZ1.

Microbially induced carbonate precipitation (MICP) has been proven to effectively immobilize Cd2+ and Pb2+ using a single bacterium. However, there is an urgent need for studies of Cd2+ and Pb2+ immobilized by a bacterial consortium. In this study, a stable consortium designated JZ1 was isolated from soil that was contaminated with cadmium and lead, and the dominant genus Sporosarcina (99.1%) was found to have carbonate mineralization function. The results showed that 91.52% and 99.38% of Cd2+ and Pb2+ were mineralized by the consortium JZ1 with 5 g/L CaCl2 at an initial concentration of 5 mg/L Cd2+ and 150 mg/L Pb2+, respectively. The bioprecipitates were characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDS). Moreover, the kinetic studies indicated that the urea hydrolysis reaction fit well with the Michaelis-Menten equation, and the kinetic parameters Km and Vmax were estimated to be 38.69 mM and 58.98 mM/h, respectively. When the concentration of urea increased from 0.1 to 0.3 M, the mineralization rate increased by 1.58-fold. This study can provide a novel microbial resource for the biomineralization of Cd and Pb in soil and water environments.

NUT Carcinoma of the Lung：A Case report and Literature Analysis.

NUT carcinoma is a rare, highly aggressive cancer that feature as the rearrangement of the nuclear protein in the testis (NUT) gene on chromosome 15q14, and its pathogenesis and treatment is not yet clear. In this case, we report a 40-year-old male patient who was diagnosed with primary pulmonary NUT carcinoma in The Second Affiliated Hospital of Zhengzhou University. A tumor was found at the right hilus pulmonis when his physical examination with chest pain for half a month. Histopathology confirmed by fluorescence in situ hybridization technique for the NUT carcinoma. After chemotherapy, radiotherapy, immunotherapy, and targeted therapy were given, the patient died. The overall survival time was 4.7 months. Combined with the existing literature, we retrospective report the clinical and pathological characteristics and treatment strategies of the rare lung NUT carcinoma.

Developmental artificial neural network model to evaluate the preoperative safe limit of future liver remnant volume for HCC combined with clinically significant portal hypertension.

Background & aims: Finding a way to comprehensively integrate the presence and grade of clinically significant portal hypertension, amount of preserved liver function and extent of hepatectomy into the guidelines for choosing appropriate candidates to hepatectomy remained challenging. This study sheds light on these issues to facilitate precise surgical decisions for clinicians. Methods: Independent risk factors associated with grade B/C post-hepatectomy liver failure were identified by stochastic forest algorithm and logistic regression in hepatitis B virus-related hepatocellular carcinoma patients. Results: The artificial neural network model was generated by integrating preoperative pre-ALB, prothrombin time, total bilirubin, AST, indocyanine green retention rate at 15 min, standard future liver remnant volume and clinically significant portal hypertension grade. In addition, stratification of patients into three risk groups emphasized significant distinctions in the risk of grade B/C post-hepatectomy liver failure. Conclusion: The authors' artificial neural network model could provide a reasonable therapeutic option for clinicians to select optimal candidates with clinically significant portal hypertension for hepatectomy and supplement the hepatocellular carcinoma surgical treatment algorithm.

Hepatectomy involves removing the tumor from the liver and is considered the most effective treatment for hepatocellular carcinoma (HCC). Clinically significant portal hypertension is characterized by the presence of gastric and/or esophageal varices and a platelet count <100 × 10⁹/l with the presence of splenomegaly, which would aggravate the risk of post-hepatectomy liver failure, and is therefore regarded as a contraindication to hepatectomy. Over the past few decades, with improvement in surgical techniques and perioperative care, the morbidity of postoperative complications and mortality have decreased greatly. Current HCC guidelines recommend the expansion of hepatectomy to HCC patients with clinically significant portal hypertension. However, determining how to select optimal candidates for hepatectomy remains challenging. The authors' artificial neural network is a mathematical tool developed by simulating the properties of neurons with large-scale information distribution and parallel structure. Here the authors retrospectively enrolled 871 hepatitis B virus-related HCC patients and developed an artificial neural network model to predict the risk of post-hepatectomy liver failure, which could provide a reasonable therapeutic option and facilitate precise surgical decisions for clinicians.

Comparison of Dexmedetomidine Versus Propofol in Mechanically Ventilated Patients With Sepsis: A Meta-Analysis of Randomized Controlled Trials.

Purpose: The aim of the present study was to evaluate the effects of dexmedetomidine compared with propofol in mechanically ventilated patients with sepsis. Methods: We searched PubMed, EMBASE, and Cochrane Library for randomized controlled trials comparing the effects of dexmedetomidine versus propofol in septic patients requiring mechanical ventilation from inception to December 2021. The primary outcome was 28/30-day mortality and secondary outcomes were ventilator-free days and the length of ICU stay. Pooled relative risk (RR), mean deviation (MD), along with 95% confidence intervals (CI) were used to express outcomes by the software of Review Manager 5.3. Results: Seven studies with a total of 1,212 patients were eligible for meta-analysis. The results primarily showed that dexmedetomidine had no significant effects on the 28/30-day mortality (RR = 1.04 [0.85-1.26], p = 0.70, I2 = 3%). As for secondary outcomes, the administration of dexmedetomidine was not associated with longer-ventilator-free days (MD = 0.50 [-2.15, 3.15], p = 0.71, I2 = 24%) compared with propofol. However, our results revealed dexmedetomidine could shorten the length of ICU stay (MD = -0.76 [-1.34, -0.18], p = 0.01, I2 = 33%). Conclusion: Administration of dexmedetomidine for sedation in septic patients who required mechanical ventilation had no effect on 28/30-day mortality and ventilator-free days, but it could shorten the length of ICU stay.

Effect of Basicity on the Microstructure of Sinter and Its Application Based on Deep Learning.

The influence of the evolution rule of basicity (0.6∼2.4) on the mineral composition and microstructure of sinter is studied by using a polarizing microscope, and the comprehensive application analysis of the drum index, vertical sintering speed, and yield of sinter shows that, over the course of an increase in basicity (0.6∼1.0), the mineral structure changed from the original porphyritic-granular structure to a porphyritic structure. At the same time, there was no calcium ferrite phase in the bonding phase at a basicity of less than 1.0; therefore, the downward trend of the three indicators is obvious. When the basicity was further increased to approximately 1.6, the main structure of the mineral phase changed from a corrosion structure to an interweaving corrosion structure. Because of the existence of a porphyritic-granular structure, the structure of the mineral phase was extremely inhomogeneous and most complex near the basicity of 1.6; although a small amount of calcium ferrite displayed an acicular structure, the drum index appeared to show a very low value. With an increase in basicity to 2.0, the mineral phase structure was dominated by an interweaving corrosion structure with a uniform framework, and the content of calcium ferrite reached the highest value. Moreover, a clear acicular structure developed, and the drum index also increased to the highest value. At a basicity of more than 2.0, a mineral structure began to appear and the corrosion, porphyritic-granular structure, and the drum index also showed a slightly declining trend. Therefore, in the actual production process, basicity should be avoided as far as possible at around 1.0 and 1.6 and it should be controlled at around 2.0. At the same time, based on the mineral facies data set of this paper, the convolutional neural network is used to carry out a simple prediction model experiment on the basicity corresponding to the mineral facies photos, and the effect is quite good, which provides a new idea and method for the follow-up study of mineral facies.

Al2O3 buffer-facilitated epitaxial growth of high-quality ZnO/ZnS core/shell nanorod arrays.

II-VI semiconductor heterojunctions show huge potential for application in nanodevice fabrication due to their type-II alignments owing to the better spatial separation of electrons and holes. However, the hetero-epitaxial growth of high-quality heterostructures is still a challenge, especially for materials with large lattice mismatch. In this work, well-aligned single-crystalline ZnO/ZnS core/shell nanorod arrays were obtained by introducing an Al2O3 buffer layer. It is interesting that the nature of the ZnS layer varies with the thickness of the Al2O3 layer. When Al2O3 is less than 2 nm, the interaction between the substrate and epilayer is strong enough to penetrate through the buffer layer, enabling the growth of ZnS on Al2O3-coated ZnO nanorod arrays. On the basis of detailed characterization, a rational growth mechanism of the core/shell heterostructure is proposed, in which the Al2O3 interlayer can eliminate voids due to the Kirkendall effect around the interface and accommodate a misfit dislocation between the inner ZnO and outer ZnS, resulting in more sufficient strain relaxation in the epitaxy. In addition, cathodoluminescence measurements demonstrate that the optical properties of the ZnO/ZnS heterostructure could be effectively improved by taking advantage of the thin Al2O3. The I-V curves characterized by PeakForce tunneling atomic force microscopy reveal that the heterostructure shows a typical rectifying behavior and good photoresponse to ultraviolet light. These findings may provide a reasonable and effective strategy for the growth of highly lattice-mismatched heterostructure arrays buffered by the Al2O3 layer, broadening the options for fabricating heterojunctions and promoting their applications in optoelectronic devices.

Artificial neural network model to predict post-hepatectomy early recurrence of hepatocellular carcinoma without macroscopic vascular invasion.

BACKGROUND: The accurate prediction of post-hepatectomy early recurrence (PHER) of hepatocellular carcinoma (HCC) is vital in determining postoperative adjuvant treatment and monitoring. This study aimed to develop and validate an artificial neural network (ANN) model to predict PHER in HCC patients without macroscopic vascular invasion. METHODS: Nine hundred and three patients who underwent curative liver resection for HCC participated in this study. They were randomly divided into derivation (n = 679) and validation (n = 224) cohorts. The ANN model was developed in the derivation cohort and subsequently verified in the validation cohort. RESULTS: PHER morbidity in the derivation and validation cohorts was 34.8 and 39.2%, respectively. A multivariable analysis revealed that hepatitis B virus deoxyribonucleic acid load, γ-glutamyl transpeptidase level, α-fetoprotein level, tumor size, tumor differentiation, microvascular invasion, satellite nodules, and blood loss were significantly associated with PHER. These factors were incorporated into an ANN model, which displayed greater discriminatory abilities than a Cox's proportional hazards model, preexisting recurrence models, and commonly used staging systems for predicting PHER. The recurrence-free survival curves were significantly different between patients that had been stratified into two risk groups. CONCLUSION: When compared to other models and staging systems, the ANN model has a significant advantage in predicting PHER for HCC patients without macroscopic vascular invasion.

Combining Aspartate Aminotransferase-to-Platelet Ratio Index with Future Liver Remnant to Assess Preoperative Hepatic Functional Reserve in Patients with Hepatocellular Carcinoma.

BACKGROUND: Accurate preoperative assessment of hepatic functional reserve is essential for conducting a safe hepatectomy. In recent years, aspartate aminotransferase-to-platelet ratio index (APRI) has been used as a noninvasive model for assessing fibrosis stage, hepatic functional reserve, and prognosis after hepatectomy with a high level of accuracy. The purpose of this research was to evaluate the clinical value of combining APRI with standardized future liver remnant (sFLR) for predicting severe post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). METHODS: Six hundred thirty-seven HCC patients who had undergone hepatectomy were enrolled in this study. The performance of the Child-Pugh (CP) grade, model for end-stage liver disease (MELD), APRI, sFLR, and APRI-sFLR in predicting severe PHLF was assessed using the area under the ROC curve (AUC). RESULTS: Severe PHLF was found to have developed in 101 (15.9%) patients. Multivariate logistic analyses identified that prealbumin, cirrhosis, APRI score, sFLR, and major resection were significantly associated with severe PHLF. The AUC values of the CP, MELD, APRI, and sFLR were 0.626, 0.604, 0.725, and 0.787, respectively, indicating that the APRI and sFLR showed significantly greater discriminatory abilities than CP and MELD (P < 0.05 for all). After APRI was combined with sFLR, the AUC value of APRI-sFLR for severe PHLF was 0.816, which greatly improved the prediction accuracy, compared with APRI or sFLR alone (P < 0.05 for all). Stratified analysis using the status of cirrhosis and extent of resection yielded similar results. Moreover, the incidence and grade of PHLF were significantly different among the three risk groups. CONCLUSION: The combination of APRI and sFLR can be considered to be a predictive factor with increased accuracy for severe PHLF in HCC patients, compared with CP grade, MELD, APRI, or sFLR alone.

Broad-Spectral-Range Sustainability and Controllable Excitation of Hyperbolic Phonon Polaritons in α-MoO3.

Hyperbolic phonon polaritons (HPhPs) in orthorhombic-phase molybdenum trioxide (α-MoO3 ) show in-plane hyperbolicity, great wavelength compression, and ultralong lifetime, therefore holding great potential in nanophotonic applications. However, its polaritonic response in the far-infrared (FIR) range remains unexplored due to challenges in experimental characterization. Here, monochromated electron energy loss spectroscopy (EELS) in a scanning transmission electron microscope (STEM) is used to probe HPhPs in α-MoO3 in both mid-infrared (MIR) and FIR frequencies and correlate their behaviors with microstructures and orientations. It is found that low structural symmetry leads to various phonon modes and multiple Reststrahlen bands (RBs) over a broad spectral range (over 70 meV) and in different directions (55-63 meV and 119-125 meV along the b-axis, 68-106 meV along the c-axis, and 101-121 meV along the a-axis). These HPhPs can be selectively excited by controlling the direction of swift electrons. These findings provide new opportunities in nanophotonic and optoelectronic applications, such as directed light propagation, hyperlenses, and heat transfer.

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for hepatocellular carcinoma and is the leading cause of postoperative mortality. Recommendations for hepatectomy for hepatocellular carcinoma are based on the risk of severe posthepatectomy liver failure, and accurately predicting posthepatectomy liver failure risk before undertaking major hepatectomy is of great significance. Thus, herein, we aimed to establish and validate an artificial neural network model to predict severe posthepatectomy liver failure in patients with hepatocellular carcinoma who underwent hemihepatectomy. METHODS: Three hundred and fifty-three patients who underwent hemihepatectomy for hepatocellular carcinoma were included. We randomly divided the patients into a development set (n = 265, 75%) and a validation set (n = 88, 25%). Multivariate logistic analysis facilitated identification of independent variables that we incorporated into the artificial neural network model to predict severe posthepatectomy liver failure in the development set and then verified in the validation set. RESULTS: The morbidity of patients with severe posthepatectomy liver failure in the development and validation sets was 24.9% and 23.9%, respectively. Multivariate analysis revealed that platelet count, prothrombin time, total bilirubin, aspartate aminotransferase, and standardized future liver remnant were all significant predictors of severe posthepatectomy liver failure. Incorporating these factors, the artificial neural network model showed satisfactory area under the receiver operating characteristic curve for the development set of 0.880 (95% confidence interval, 0.836-0.925) and for the validation set of 0.876 (95% confidence interval, 0.801-0.950) in predicting severe posthepatectomy liver failure and achieved well-fitted calibration ability. The predictive performance of the artificial neural network model for severe posthepatectomy liver failure outperformed the traditional logistic regression model and commonly used scoring systems. Moreover, stratification into 3 risk groups highlighted significant differences between the incidences and grades of posthepatectomy liver failure. CONCLUSION: The artificial neural network model accurately predicted the risk of severe posthepatectomy liver failure in patients with hepatocellular carcinoma who underwent hemihepatectomy. Our artificial neural network model might help surgeons identify intermediate and high-risk patients to facilitate earlier interventions.

General Decomposition Pathway of Organic-Inorganic Hybrid Perovskites through an Intermediate Superstructure and its Suppression Mechanism.

Organic-inorganic hybrid perovskites (OIHPs) have generated considerable excitement due to their promising photovoltaic performance. However, the commercialization of perovskite solar cells (PSCs) is still plagued by the structural degradation of the OIHPs. Here, the decomposition mechanism of OIHPs under electron beam irradiation is investigated via transmission electron microscopy, and a general decomposition pathway for both tetragonal CH3 NH3 PbI3 and cubic CH3 NH3 PbBr3 is uncovered through an intermediate superstructure state of CH3 NH3 PbX2.5 , X = I, Br, with ordered vacancies into final lead halides. Such decomposition can be suppressed via carbon coating by stabilization of the perovskite structure framework. These findings reveal the general degradation pathway of OIHPs and suggest an effective strategy to suppress it, and the atomistic insight learnt may be useful for improving the stability of PSCs.