The early change in pH values after out-of-hospital cardiac arrest is not associated with neurological outcome at hospital discharge.

Background: The association between pH values and outcome for patients after out-of-hospital cardiac arrest (OHCA) was not fully elucidated; besides, the relationship of change in pH values and neurological outcome was unknown. The aim was to explore the association of pH values as well as change in pH values and neurological outcome for OHCA cardiac patients. Methods: The adult patients with non-traumatic out-of-hospital cardiac arrest, shock-refractory ventricular fibrillation or pulseless ventricular tachycardia, and at least two arterial blood gases analysis recorded after admission were included. The change in pH values is calculated as the difference between the second and first pH value, and divided by time interval got the rate of change in pH values. The primary outcome was modified Rankin Score (mRS), dichotomized to good (mRS 0-3) and poor (mRS 4-6) outcomes at hospital discharge. The independent relationship of the first pH value, second pH value, and changes in pH values with neurological outcome was investigated with multivariable logistic regression models, respectively. Results: A total of 1388 adult patients were included for analysis, of which 514 (37%) had good neurological outcome. The median first pH value and second pH value after admission were 7.21 (interquartile range [IQR] 7.09-7.29) and 7.28 (IQR 7.20-7.36), respectively. The median absolute, relative change, and rate of changes in pH values were 0.08 (IQR 0.01-0.16), 1.10% (IQR 0.11-2.22%), and 0.02 (IQR 0-0.06) per hour, respectively. After adjusting for confounders, the higher first pH value (odds ratio [OR] 3.81, confidence interval [CI] 1.60-9.24, P = 0.003) and higher second pH value (OR 9.54, CI 3.45-26.87, P < 0.001) after admission were associated with good neurological outcome, respectively. The absolute (OR 1.58, CI 0.58-4.30, P = 0.368) and relative (OR 1.03, CI 0.96-1.11, P = 0.399) change as well as the rate of change (OR 0.98, CI 0.33-2.71, P = 974) in pH values were not associated with neurological outcome. Conclusions: For OHCA patients, abnormality in pH values was very common, with a more acidic pH value indicating poor neurological outcome. However, the change in pH values was not associated with outcomes.

Ultrasmall Fe3O4 nanoparticles self-assembly induced dual-mode T1/T2-weighted magnetic resonance imaging and enhanced tumor synergetic theranostics.

Individual theranostic agents with dual-mode MRI responses and therapeutic efficacy have attracted extensive interest due to the real-time monitor and high effective treatment, which endow the providential treatment and avoid the repeated medication with side effects. However, it is difficult to achieve the integrated strategy of MRI and therapeutic drug due to complicated synthesis route, low efficiency and potential biosafety issues. In this study, novel self-assembled ultrasmall Fe3O4 nanoclusters were developed for tumor-targeted dual-mode T1/T2-weighted magnetic resonance imaging (MRI) guided synergetic chemodynamic therapy (CDT) and chemotherapy. The self-assembled ultrasmall Fe3O4 nanoclusters synthesized by facilely modifying ultrasmall Fe3O4 nanoparticles with 2,3-dimercaptosuccinic acid (DMSA) molecule possess long-term stability and mass production ability. The proposed ultrasmall Fe3O4 nanoclusters shows excellent dual-mode T1 and T2 MRI capacities as well as favorable CDT ability due to the appropriate size effect and the abundant Fe ion on the surface of ultrasmall Fe3O4 nanoclusters. After conjugation with the tumor targeting ligand Arg-Gly-Asp (RGD) and chemotherapy drug doxorubicin (Dox), the functionalized Fe3O4 nanoclusters achieve enhanced tumor accumulation and retention effects and synergetic CDT and chemotherapy function, which serve as a powerful integrated theranostic platform for cancer treatment.

Growth of millimeter-sized 2D metal iodide crystals induced by ion-specific preference at water-air interfaces.

Conventional liquid-phase methods lack precise control in synthesizing and processing materials with macroscopic sizes and atomic thicknesses. Water interfaces are ubiquitous and unique in catalyzing many chemical reactions. However, investigations on two-dimensional (2D) materials related to water interfaces remain limited. Here we report the growth of millimeter-sized 2D PbI2 single crystals at the water-air interface. The growth mechanism is based on an inherent ion-specific preference, i.e. iodine and lead ions tend to remain at the water-air interface and in bulk water, respectively. The spontaneous accumulation and in-plane arrangement within the 2D crystal of iodide ions at the water-air interface leads to the unique crystallization of PbI2 as well as other metal iodides. In particular, PbI2 crystals can be customized to specific thicknesses and further transformed into millimeter-sized mono- to few-layer perovskites. Additionally, we have developed water-based techniques, including water-soaking, spin-coating, water-etching, and water-flow-assisted transfer to recycle, thin, pattern, and position PbI2, and subsequently, perovskites. Our water-interface mediated synthesis and processing methods represents a significant advancement in achieving simple, cost-effective, and energy-efficient production of functional materials and their integrated devices.

Development and Validation of a Deep Learning Model to Reduce the Interference of Rectal Artifacts in MRI-based Prostate Cancer Diagnosis.

Purpose To develop an MRI-based model for clinically significant prostate cancer (csPCa) diagnosis that can resist rectal artifact interference. Materials and Methods This retrospective study included 2203 male patients with prostate lesions who underwent biparametric MRI and biopsy between January 2019 and June 2023. Targeted adversarial training with proprietary adversarial samples (TPAS) strategy was proposed to enhance model resistance against rectal artifacts. The automated csPCa diagnostic models trained with and without TPAS were compared using multicenter validation datasets. The impact of rectal artifacts on the diagnostic performance of each model at the patient and lesion levels was compared using the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUPRC). The AUC between models was compared using the DeLong test, and the AUPRC was compared using the bootstrap method. Results The TPAS model exhibited diagnostic performance improvements of 6% at the patient level (AUC: 0.87 vs 0.81, P < .001) and 7% at the lesion level (AUPRC: 0.84 vs 0.77, P = .007) compared with the control model. The TPAS model demonstrated less performance decline in the presence of rectal artifact-pattern adversarial noise than the control model (ΔAUC: -17% vs -19%, ΔAUPRC: -18% vs -21%). The TPAS model performed better than the control model in patients with moderate (AUC: 0.79 vs 0.73, AUPRC: 0.68 vs 0.61) and severe (AUC: 0.75 vs 0.57, AUPRC: 0.69 vs 0.59) artifacts. Conclusion This study demonstrates that the TPAS model can reduce rectal artifact interference in MRI-based csPCa diagnosis, thereby improving its performance in clinical applications. Keywords: MR-Diffusion-weighted Imaging, Urinary, Prostate, Comparative Studies, Diagnosis, Transfer Learning Clinical trial registration no. ChiCTR23000069832 Supplemental material is available for this article. Published under a CC BY 4.0 license.

Cooperation of Different Active Sites to Promote CO2 Electroreduction to Multi-carbon Products at Ampere-Level.

Electroreduction of CO2 to C2+ products provides a promising strategy for reaching the goal of carbon neutrality. However, achieving high selectivity of C2+ products at high current density remains a challenge. In this work, we designed and prepared a multi-sites catalyst, in which Pd was atomically dispersed in Cu (Pd-Cu). It was found that the Pd-Cu catalyst had excellent performance for producing C2+ products from CO2 electroreduction. The Faradaic efficiency (FE) of C2+ products could be maintained at approximately 80.8 %, even at a high current density of 0.8 A cm-2 for at least 20 hours. In addition, the FE of C2+ products was above 70 % at 1.4 A cm-2. Experiments and density functional theory (DFT) calculations revealed that the catalyst had three distinct catalytic sites. These three active sites allowed for efficient conversion of CO2, water dissociation, and CO conversion, ultimately leading to high yields of C2+ products.

Vapor Phase Growth of Air-Stable Hybrid Perovskite FAPbBr3 Single-Crystalline Nanosheets.

Organic-inorganic hybrid perovskites have attracted tremendous attention owing to their fascinating optoelectronic properties. However, their poor air stability seriously hinders practical applications, which becomes more serious with thickness down to the nanoscale. Here we report a one-step vapor phase growth of HC(NH2)2PbBr3 (FAPbBr3) single-crystalline nanosheets of tunable size up to 50 µm and thickness down to 20 nm. The FAPbBr3 nanosheets demonstrate high stability for over months of exposure to air with no degradation in surface roughness and photoluminescence efficiency. Besides, the FAPbBr3 photodetectors exhibit superior overall performance as compared to previous devices based on nonlayered perovskite nanosheets, such as an ultralow dark current of 24 pA, an ultrahigh responsivity of 1033 A/W, an external quantum efficiency over 3000%, a rapid response time around 25 ms, and a high on/off ratio of 104. This work provides a strategy to tackle the challenges of hybrid perovskites toward integrated optoelectronics with requirements of nanoscale thickness, high stability, and excellent performance.

A systematic evaluation of computation methods for cell segmentation.

Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including training data and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, which substantially reduces the time and effort for training cell segmentation models.

Highly Reliable Van Der Waals Memory Boosted by a Single 2D Charge Trap Medium.

Charge trap materials that can store carriers efficiently and controllably are desired for memory applications. 2D materials are promising for highly compacted and reliable memory mainly due to their ease of constructing atomically uniform interfaces, however, remain unexplored as being charge trap media. Here it is discovered that 2D semiconducting PbI2 is an excellent charge trap material for nonvolatile memory and artificial synapses. It is simple to construct PbI2 -based charge trap devices since no complicated synthesis or additional defect manufacturing are required. As a demonstration, MoS2 /PbI2 device exhibits a large memory window of 120 V, fast write speed of 5 µs, high on-off ratio around 106 , multilevel memory of over 8 distinct states, high reliability with endurance up to 104 cycles and retention over 1.2 × 104 s. It is envisioned that PbI2 with ionic activity caused by the natively formed iodine vacancies is unique to combine with unlimited 2D materials for versatile van der Waals devices with high-integration and multifunctionality.

Optimizing copper nanoparticles with a carbon shell for enhanced electrochemical CO2 reduction to ethanol.

The electrochemical reduction of carbon dioxide (CO2RR) holds great promise for sustainable energy utilization and combating global warming. However, progress has been impeded by challenges in developing stable electrocatalysts that can steer the reaction toward specific products. This study proposes a carbon shell coating protection strategy by an efficient and straightforward approach to prevent electrocatalyst reconstruction during the CO2RR. Utilizing a copper-based metal-organic framework as the precursor for the carbon shell, we synthesized carbon shell-coated electrocatalysts, denoted as Cu-x-y, through calcination in an N2 atmosphere (where x and y represent different calcination temperatures and atmospheres: N2, H2, and NH3). It was found that the faradaic efficiency of ethanol over the catalysts with a carbon shell could reach ∼67.8%. In addition, the catalyst could be stably used for more than 16 h, surpassing the performance of Cu-600-H2 and Cu-600-NH3. Control experiments and theoretical calculations revealed that the carbon shell and Cu-C bonds played a pivotal role in stabilizing the catalyst, tuning the electron environment around Cu atoms, and promoting the formation and coupling process of CO*, ultimately favoring the reaction pathway leading to ethanol formation. This carbon shell coating strategy is valuable for developing highly efficient and selective electrocatalysts for the CO2RR.

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.

New classes arise frequently in our ever-changing world, e.g., emerging topics in social media and new types of products in e-commerce. A model should recognize new classes and meanwhile maintain discriminability over old classes. Under severe circumstances, only limited novel instances are available to incrementally update the model. The task of recognizing few-shot new classes without forgetting old classes is called few-shot class-incremental learning (FSCIL). In this work, we propose a new paradigm for FSCIL based on meta-learning by LearnIng Multi-phase Incremental Tasks (Limit), which synthesizes fake FSCIL tasks from the base dataset. The data format of fake tasks is consistent with the 'real' incremental tasks, and we can build a generalizable feature space for the unseen tasks through meta-learning. Besides, Limit also constructs a calibration module based on transformer, which calibrates the old class classifiers and new class prototypes into the same scale and fills in the semantic gap. The calibration module also adaptively contextualizes the instance-specific embedding with a set-to-set function. Limit efficiently adapts to new classes and meanwhile resists forgetting over old classes. Experiments on three benchmark datasets (CIFAR100, miniImageNet, and CUB200) and large-scale dataset, i.e., ImageNet ILSVRC2012 validate that Limit achieves state-of-the-art performance.

Accumulation of advanced glycation end products promotes atrophic nonunion incidence in mice through a CtBP1/2-dependent mechanism.

Atrophic nonunion (AN) is a complex and poorly understood pathological condition resulting from impaired fracture healing. Advanced glycation end products (AGEs) have been implicated in the pathogenesis of several bone disorders, including osteoporosis and osteoarthritis. However, the role of AGEs in the development of AN remains unclear. This study found that mice fed a high-AGE diet had a higher incidence of atrophic nonunion (AN) compared to mice fed a normal diet following tibial fractures. AGEs induced two C-terminal binding proteins (CtBPs), CtBP1 and CtBP2, which were necessary for the development of AN in response to AGE accumulation. Feeding a high-AGE diet after fracture surgery in CtBP1/2-/- and RAGE-/- (receptor of AGE) mice did not result in a significant occurrence of AN. Molecular investigation revealed that CtBP1 and CtBP2 formed a heterodimer that was recruited by histone deacetylase 1 (HDAC1) and runt-related transcription factor 2 (Runx2) to assemble a complex. The CtBP1/2-HDAC1-Runx2 complex was responsible for the downregulation of two classes of bone development and differentiation genes, including bone morphogenic proteins (BMPs) and matrix metalloproteinases (MMPs). These findings demonstrate that AGE accumulation promotes the incidence of AN in a CtBP1/2-dependent manner, possibly by modulating genes related to bone development and fracture healing. These results provide new insights into the pathogenesis of AN and suggest new therapeutic targets for its prevention and treatment.

Adjacent Copper Single Atoms Promote C-C Coupling in Electrochemical CO2 Reduction for the Efficient Conversion of Ethanol.

The electrochemical CO2 reduction reaction (CO2RR) using renewable electricity is one of the most promising strategies for reaching the goal of carbon neutrality. Multicarbonous (C2+) products have broad applications, and ethanol is a valuable chemical and fuel. Many Cu-based catalysts have been reported to be efficient for the electrocatalytic CO2RR to C2+ products, but they generally offer limited selectivity and current density toward ethanol. Herein, we proposed a silica-mediated hydrogen-bonded organic framework (HOF)-templated approach to preparing ultrahigh-density Cu single-atom catalysts (SACs) on thin-walled N-doped carbon nanotubes (TWN). The content of Cu in the catalysts prepared by this method could be up to 13.35 wt %. It was found that the catalysts showed outstanding performance for the electrochemical CO2RR to ethanol, and the Faradaic efficiency (FE) of ethanol increased with the increase in Cu-N3 site density. The FE of ethanol over the catalysts with 13.35 wt % Cu could reach ∼81.9% with a partial current density of 35.6 mA cm-2 using an H-type cell, which is the best result for electrochemical CO2RR to ethanol to date. In addition, the catalyst could be stably used for more than 25 h. Experimental and density functional theory (DFT) studies revealed that the adjacent Cu-N3 active sites (one Cu atom coordinates with three N) were the active sites for the reaction, and their high density was crucial for the high FE of ethanol because the adjacent Cu-N3 sites with a short distance could promote the C-C coupling synergistically.

Structure, Stability, and Superconductivity of Two-Dimensional Janus NbSH Monolayers: A First-Principle Investigation.

Two-dimensional Janus materials have unique structural characteristics due to their lack of out-of-plane mirror symmetry, resulting in many excellent physical and chemical properties. Using first-principle calculations, we performed a detailed investigation of the possible stable structures and properties of two-dimensional Janus NbSH. We found that both Janus 1T and 2H structures are semiconductors, unlike their metallic counterparts MoSH. Furthermore, we predicted a new stable NbSH monolayer using a particle swarm optimization method combined with first-principle calculations. Interestingly, the out-of-plane mirror symmetry is preserved in this newly found 2D structure. Furthermore, the newly found NbSH is metallic and exhibits intrinsic superconducting behavior. The superconducting critical temperature is about 6.1 K under normal conditions, which is found to be very sensitive to stress. Even under a small compressive strain of 1.08%, the superconducting critical temperature increases to 9.3 K. In addition, the superconductivity was found to mainly originate from Nb atomic vibrations. Our results show the diversity of structures and properties of the two-dimensional Janus transition metal sulfhydrate materials and provide some guidelines for further investigations.

A novel and superior Lasso-plate technique in treatment for coronoid process fracture in the terrible triad of elbow.

The treatment of ulna coronal process fractures in the terrible triad of elbow, especially type I and II Regan-Morrey coronoid fractures, still have been controversial. The purpose of this retrospective study was to evaluate the novel Lasso-plate technique to have a more reliable fixation and a well clinical outcomes for type I and II Regan-Morrey coronoid fractures in a terrible triad of the elbow (TTE). Patients with simple TTE, closed fracture, aged > 18 years, duration of injury < 2 weeks, type I and II Regan-Morrey coronoid process fracture fixed by the Lasso-plate technique or ORIF were enrolled in the study. Total 144 patients with type I and II Regan-Morrey coronoid fracture in TTE were included in the Lasso-plate group or ORIF (open reduction and internal fixation) group in the Xi'an Honghui Hospital from January 2017 to December 2020. Eighty-six patients in Lasso-plate group underwent surgery using a novel Lasso-plate technique. And other 58 patients in ORIF group underwent surgery using ORIF. The data of two groups, including the X-ray films, Computed tomography (CT), the range of elbow motion, Mayo Elbow Performance Score (MEPS) and the surgical complications, were extracted from the hospital's patient records. All patients in both groups were followed up at least 12 months. The mean operation time (88.2 ± 12.3 min) in Lasso-plate group is shorter than that of ORIF group (109.1 ± 13.0 min). There was one patient with injury of deep branch of radial nerve and one patient with superficial surgical incision infection in Lasso-plate group. There were two patients with surgical incision infection in ORIF group. There were three heterotopic ossifications in Lasso-plate group and eight heterotopic ossifications in ORIF group. There were 5 elbow joints stiffness in Lasso-plate group and 12 in ORIF group. At 12 months follow up, the mean range of flexion-extension motion in Lasso-plate group was 122.9° ± 13.4° versus 113.2° ± 18.1° in ORIF group (p < 0.01), the mean 89.7 ± 5.6 MEPS in Lasso-plate group versus mean 83.7 ± 6.1 MEPSin ORIF group. The fixation of coronoid process fracture in TTE by the Lasso-plate technique, especially type I and II Regan-Morrey coronoid fracture, could be easier to master and operate, could provide the sufficient stability of elbow joint to enable early functional exercise, along with a better clinical outcome, a lower surgical complication. For the treatment of TTE, we recommend the fixation of type I and II Regan-Morrey coronoid fracture with the Lasso-plate technique, which would result in a better clinical outcome.

Thermal failure analysis and control algorithm improvement for the active controlled mount with consideration of thermal-magnetic coupling.

This paper proposes an improved narrowband filtered-x least mean square(FxLMS) algorithm to overcome the thermal failure problems of the active controlled mount(ACM). Firstly, the temperature-rising model and the thermal demagnetization model of the ACM are respectively developed. Combining these two models with the powertrain mounting system model, an analytical method is established for the thermal-magnetic coupling analysis of the ACM. Then a numerical simulation is carried out to obtain the permanent magnet(PM) temperature and the coil current. The ACM failure problem is discussed according to the working point trajectory. Finally, an improved algorithm is proposed. This algorithm is able to overcome the thermal failure problems by sacrificing part of the vibration isolation performance. The effectiveness of this algorithm is validated by numerical simulations and a comparison with conventional algorithms.

On the electroluminescence overshoot of quantum-dot light-emitting diodes.

The charge-carrier dynamics is a fundamental question in quantum-dot light-emitting diodes (QLEDs), determining the electroluminescence (EL) properties of the devices. By means of a hole-confined QLED design, the distribution and storage/residing of the charge carriers in the devices are deciphered by the transient electroluminescence (TrEL) spectroscopic technology. It is demonstrated that the holes stored in the quantum dots (QDs) are responsible for the EL overshoot during the rising edge of the TrEL response. Moreover, the earlier electroluminescence turn-on behavior is observed due to the holes residing in the hole-confined structure. The hole storage effect should be attributed to the ultralow hole mobility of QD films and large barrier for hole escape from the cores of the QDs. Our findings provide a deep understanding of the charge transport and storage at the most critical interface between QDs and hole-transport layer, where the excitons are formed.

A Droplet Method for Synthesis of Multiclass Ultrathin Metal Halides.

2D metal halides have attracted increasing research attention in recent years; however, it is still challenging to synthesize them via liquid-phase methods. Here it is demonstrated that a droplet method is simple and efficient for the synthesis of multiclass 2D metal halides, including trivalent (BiI3 , SbI3 ), divalent (SnI2 , GeI2 ), and monovalent (CuI) ones. In particular, 2D SbI3 is first experimentally achieved, of which the thinnest thickness is ≈6 nm. The nucleation and growth of these metal halide nanosheets are mainly determined by the supersaturation of precursor solutions that are dynamically varying during the solution evaporation. After solution drying, the nanosheets can fall on the surface of many different substrates, which further enables the feasible fabrication of related heterostructures and devices. With SbI3 /WSe2 being a good demonstration, the photoluminescence intensity and photo responsivity of WSe2 is obviously enhanced after interfacing with SbI3 . The work opens a new pathway for 2D metal halides toward widespread investigation and applications.

Efficient Quantum-Dot Light-Emitting Diodes Enabled via a Charge Manipulating Structure.

Charge carriers are the basic physical element in an electrically driven quantum-dot light-emitting diode (QLED), which acts as a converter transforming electric energy to light energy. Therefore, it is widely sought after to manage the charge carriers for achieving efficient energy conversion; however, to date, there has been a lack of understanding and efficient strategies. Here, an efficient QLED is achieved by manipulating the charge distribution and dynamics with an n-type 1,3,5-tris(N-phenylbenzimidazole-2-yl)benzene (TPBi) layer embedded into the hole-transport layer. Compared with the control QLED, the maximum current efficiency of the TPBi-containing device is enhanced over 30%, reaching 25.0 cd/A, corresponding to a 100% internal quantum efficiency considering the ∼90% photoluminescence quantum yield of the QD film. Our results suggest that there is still a great deal of room to further improve the efficiency in a standard QLED by subtly manipulating the charge carriers.

Downregulation of circ-YES1 suppresses NSCLC migration and proliferation through the miR-142-3p-HMGB1 axis.

BACKGROUND: Circular RNAs (circRNAs) are a new family of abundant regulatory RNAs with roles in various types of cancer. While the hsa_circ_0046701 (circ-YES1) function in non-small cell lung cancer (NSCLC) is unclear. METHODS: Circ-YES1 expression in normal pulmonary epithelial and NSCLC cells was examined. The small interfering RNA for circ-YES1 was prepared, cell proliferation and migration were assessed. Tumorigenesis in nude mice was assayed to validate the role of circ-YES1. Bioinformatics analyses and luciferase reporter assays were utilized to identify downstream targets of circ-YES1. RESULTS: Compared to normal pulmonary epithelial cells, the circ-YES1 expression increased in NSCLC cells, and cell proliferation and migration were suppressed after circ-YES1 knockdown. Both high mobility group protein B1 (HMGB1) and miR-142-3p were found to be downstream targets of circ-YES1, and miR-142-3p inhibition and HMGB1 overexpression reversed the effects of circ-YES1 knockdown on cell proliferation and migration. Similarly, HMGB1 overexpression reversed the miR-142-3p overexpression effects on these two processes. The imaging experiment results revealed that circ-YES1 knockdown impeded tumor development and metastasis in a nude mouse xenograft model. CONCLUSION: Taken together, our results show that circ-YES1 promotes tumor development through the miR-142-3p-HMGB1 axis and support the development of circ-YES1 probability as a new therapeutic NSCLC target.