A Predictive Model for Graft Failure in Femtosecond Laser-Assisted Penetrating Keratoplasty Among Chinese Patients: A 2-Year Study.

INTRODUCTION: Graft failure is a major challenge in femtosecond laser-assisted penetrating keratoplasty (Fs-PKP). This study focuses on the development and validation of a clinical predictive model aimed at identifying the risk of graft failure in individuals undergoing Fs-PKP in China, offering a tailored approach to improve surgical outcomes. METHODS: This retrospective cohort study at Nanjing First Hospital involved 238 patients and followed the TRIPOD statement. The cohort was divided into a training set (n = 166) and a validation set (n = 72) in a 7:3 ratio. It analyzed 23 predictor variables related to recipient, donor, and surgical factors, defining graft failure as "visually significant and irreversible corneal stromal edema, haze, or scarring." A comprehensive nomogram was created using univariate and multivariate Cox regression analyses and assessed by concordance index (C-index), time-dependent receiver operating characteristics (ROC) curve, calibration plots, and decision curve analysis (DCA). RESULTS: Five critical risk factors were identified: recipients' history of systemic autoimmune disorders, ocular trauma, prior penetrating keratoplasty (PKP) history, donors' diabetes history, and the endothelial cell density of the donor cornea. The nomogram showed a C-index of 0.72 (95% CI 0.65-0.79) in the training group and 0.66 (95% CI 0.55-0.76) in the validation group, indicating robust predictive accuracy. Time-dependent ROC curves, calibration plots, and DCA consistently validated the model's reliability, predictive power, and clinical utility across both training and validation cohorts. CONCLUSIONS: Our study developed and validated a model incorporating five key factors, enhancing preoperative prediction and management for Chinese patients with Fs-PKP graft failure.

Distributed Fixed-Time Control for Leader-Steered Rigid Shape Formation With Prescribed Performance.

Resorting to the principle of rigid body kinematics, a novel framework for a multirobot network is proposed to form and maintain an invariant rigid geometric shape. Unlike consensus-based formation, this approach can perform both translational and rotational movements of the formation geometry, ensuring that the entire formation motion remains consistent with the leader. To achieve the target formation shape and motion, a distributed control protocol for multiple Euler-Lagrange robotic vehicles subject to nonholonomic constraints is developed. The proposed protocol includes a novel prescribed performance control (PPC) algorithm that addresses the second-order dynamics of the robotic vehicles by employing a combination of nonsingular sliding manifold and adaptive law. Finally, the effectiveness of the proposed formation framework and control protocol is demonstrated through the numerical simulations and practical experiments with a team of four robotic vehicles.

Cooperative Active Learning-Based Dual Control for Exploration and Exploitation in Autonomous Search.

In this article, a multi-estimator based computationally efficient algorithm is developed for autonomous search in an unknown environment with an unknown source. Different from the existing approaches that require massive computational power to support nonlinear Bayesian estimation and complex decision-making process, an efficient cooperative active-learning-based dual control for exploration and exploitation (COAL-DCEE) is developed for source estimation and path planning. Multiple cooperative estimators are deployed for environment learning process, which is helpful to improving the search performance and robustness against noisy measurements. The number of estimators used in COAL-DCEE is much smaller than that of the particles required for Bayesian estimation in information-theoretic approaches. Consequently, the computational load is significantly reduced. As an important feature of this study, the convergence and performance of COAL-DCEE are established in relation to the characteristics of sensor noises and turbulence disturbances. Numerical and experimental studies have been carried out to verify the effectiveness of the proposed framework. Compared with the existing approaches, COAL-DCEE not only provides convergence guarantee but also yields comparable search performance using much less computational power.

Water storage capacity is inversely associated with xylem embolism resistance in tropical karst tree species.

Tropical karst habitats are characterized by limited and patchy soil, large rocky outcrops and porous substrates, resulting in high habitat heterogeneity and soil moisture fluctuations. Xylem hydraulic efficiency and safety can determine the drought adaptation and spatial distribution of woody plants growing in karst environments. In this study, we measured sapwood-specific hydraulic conductivity (Ks), vulnerability to embolism, wood density, saturated water content, and vessel and pit anatomical characteristics in the branch stems of 12 evergreen tree species in a tropical karst seasonal rainforest in southwestern China. We aimed to characterize the effects of structural characteristics on hydraulic efficiency and safety. Our results showed that there was no significant correlation between Ks and hydraulic safety across the tropical karst woody species. Ks was correlated with hydraulic vessel diameter (r = 0.80, P < 0.05) and vessel density (r = -0.60, P < 0.05), while the stem water potential at 50 and 88% loss of hydraulic conductivity (P50 and P88) were both significantly correlated with wood density (P < 0.05) and saturated water content (P = 0.052 and P < 0.05, respectively). High stem water storage capacity was associated with low cavitation resistance possibly because of its buffering the moisture fluctuations in karst environments. However, both Ks and P50/P88 were decoupled from the anatomical traits of pit and pit membranes. This may explain the lack of tradeoff between hydraulic safety and efficiency in tropical karst evergreen tree species. Our results suggest that diverse hydraulic trait combination may facilitate species coexistence in karst environments with high spatial heterogeneity.

Broadband optical nonlinearity and all-optical switching features in low-defect GaN.

GaN is a one of promising materials for nonlinear optical applications. In this work, the broadband nonlinear optical response and potential applications for all-optical switching (AOS) are evaluated in low-defect GaN. In the pump-probe experiments, the ultrafast optical switching times are consistent with pulse widths accompanied with relative weak free-carrier absorption response, and the modulation contrast can reach ∼60% by varying the polarization orientations between the pump and probe lights. In the visible region, the broadband two-photon absorption effect exhibits excellent values for the imaginary part of figure of merit (FOM), providing the possibility of AOS based on nonlinear absorption (magnitude). While in the near-infrared region and under the presence of three-photon absorption, not only the real part of FOM based on Kerr effect is evaluated, but also the maximum light intensity for the usage of AOS based on nonlinear refraction (phase) is determined. The broadband nonlinear optical and AOS features in low-defect GaN will be highly favorable for the applications in the field of integrated nonlinear photonics and photonic circuits.

Modulating the nonlinear absorption response of SnOx thin films via phase engineering.

Phase (composition) is known to play a key role in determining the electronic and optical properties of amorphous oxide semiconductors. In this work, modulating the ultrafast nonlinear optical (NLO) response of SnO2 and SnO thin films by tuning oxygen partial pressure during film sputtering is explored. Femtosecond Z-scan results demonstrate that intermediate phases have no profound impact on the two-photon absorption (TPA) response of SnO2 and SnO films. Interestingly, the magnitude of the effective nonlinear absorption coefficient (ßeff) of both intermediate SnO2-x and SnOx are enhanced after the change of Sn2+/Sn4+ composition ratio, as measured by picosecond Z-scan technique. Femtosecond degenerate pump-probe measurements show that intermediate phases accelerate the carrier trapping and improve the defect-related carrier absorption in SnOx (SnO-rich) film, while intermediate phase suppress the TPA response of SnO2-x (SnO2-rich) films, therefore carrier-induced absorption dominates the NLO behavior of SnO2-x film on picosecond regime. Our results indicate a simple and effective way to modulate the NLO response of transparent conductive oxide SnO2 and SnO.

Dicoumarin with dimethyl thiocarbamate in the fluorescent detecting for Au3+ in water and cells.

Gold ions have high activity and cytotoxicity completely different from elemental gold. It is necessary and critical to develop Au3+ detection tools that are easy to operate, intuitive, inexpensive, and non-destructive testing. Here, we propose a novel two-photon fluorescent probe named DA for detecting Au3+, which is a rare combination of dicoumarin with dimethylthiocarbamate for the first time. Based on the PET mechanism, DA turns-on the fluorescence to yellow-green after specifically binds to Au3+, and the reaction is completed within 5 min. The detection limit is as low as 27.60 nM. Simultaneously, DA achieved qualitative and quantitative detection of Au3+ in environmental water samples, and fluorescence imaging of Au3+ in biological cells.

Improved Ultrafast Carrier Relaxation and Charge Transfer Dynamics in CuI Films and Their Heterojunctions via Sn Doping.

CuI is one of the promising hole transport materials for perovskite solar cells. However, its tendency to form defects is currently limiting its use for device applications. Here, we report the successful improvement of CuI through Sn doping and the direct measurement of the carrier relaxation and interfacial charge-transfer processes in Sn-doped CuI films and their heterostructures. Femtosecond-transient absorption (fs-TA) measurements reveal that Sn doping effectively passivates the trap states within the bandgap of CuI. The I-V characteristics of heterostructures demonstrate drastic improvement in transport characteristics upon Sn doping. Fs-TA measurements further confirm that the CuSnI/ZnO heterojunction has a type-II configuration with ultrafast charge transfer (<280 fs). The charge transfer time of a CuI/ZnO heterostructure is ∼2.8 times slower than that of the CuSnI/ZnO heterostructure, indicating that Sn doping suppresses the interfacial states that retard the charge transfer. These results elucidate the effect of Sn doping on the performance of CuI-based heterostructures.

A ratiometric fluorescent probe based on two-isophorone fluorophore for detecting cysteine.

The key biological thiol, cysteine (Cys), which can participate in many physiological and pathological processes in the human body, has also been proved to have considerable effects on redox homeostasis and the regulation of cell activity in vivo. A large number of studies have shown that abnormal Cys concentration is inseparable from the occurrence of many diseases. Therefore, it is of considerable research value to develop a method to specifically detect Cys. In this study, a new ratiometric fluorescent probe of two-isophorone fluorophore, TIFC, was proposed to successfully detect intracellular Cys by ratiometric fluorescence signals and the results showed that TIFC has good selectivity and sensitivity. The results of biological imaging experiments also demonstrated that probe TIFC can exhibit a rapid ratiometric response to Cys in vivo and has low cytotoxicity, enabling high biocompatible fluorescence imaging in osteoblasts. Therefore, TIFC has the potential of rapid ratio-response to Cys for the preliminary diagnosis of related diseases.

Enhancement of Two-Photon Absorption in Boron-Dipyrromethene (BODIPY) Derivatives.

The linear and nonlinear optical properties of two BODIPY derivatives, 1,7-Diphenyl-3,5-bis(9,9-dimethyl-9H-fluoren-2-yl)-boron-diuoride-azadipyrromethene (ZL-61) and 1,7-Diphenyl-3,5-bis(4-(1,2,2-triphenylvinyl)phenyl)-boron-diuoride-azadipyrromethene (ZL-22), were comprehensively investigated based on experimental and theoretical studies. It was found that both compounds show a strong two-photon absorption response in the near-infrared regime, and the two-photon-absorption cross-section values of ZL-61 and ZL-22 were determined to be 8321 GM and 1864 GM at 800 nm, respectively. The improvement of the two-photon absorption cross section in ZL-61 was attributed to the enhancement of the donor group, which was confirmed by transient absorption measurements and DFT calculation. Our results indicate that these BODIPY derivatives are a promising candidate for optical limiting and two-photon imaging applications.

D-π-A type conjugated indandione derivatives: ultrafast broadband nonlinear absorption responses and transient dynamics.

The ultrafast nonlinear optical response of two 1,3-indandione derivatives (INB3 and INT3) was systematically investigated by the femtosecond Z-scan and pump-probe technique at multiple visible and near infrared wavelengths. Both compounds show strong broadband nonlinear absorption (NLA) and different wavelength-dependent two-photon absorption (TPA) characteristics in the range of 650-1100 nm. The TPA cross section of trithiophene-based compound INT3 was found to be larger than that of triphenylamine-based compound INB3 in the red region (650-800 nm), which is attributed to its longer π-conjugated structure and better molecular planarity. Interestingly, the effective NLA of INB3 was found to be larger than INT3 in the NIR region (800-1100 nm), which is related to the excited state absorption (ESA) induced by TPA. The ultrafast dynamics of both compounds were investigated by femtosecond transient absorption spectroscopy, which revealed a broadband ESA including several relaxation processes. This work extends nonlinear optical research on indandione derivatives, and the results suggest that these derivatives are promising candidates for optical limiting applications.

Correction: D-π-A type conjugated indandione derivatives: ultrafast broadband nonlinear absorption responses and transient dynamics.

[This corrects the article DOI: 10.1039/D2RA00349J.].

LINC01006 and miR-3199 Serve as Novel Markers of Poor Prognosis in Colon Cancer and Regulate Cell Proliferation, Migration and Invasion.

PURPOSE: Colon cancer is the most commonly diagnosed gastrointestinal cancer. This research intended to evaluate the prognostic values of LINC01006 and miR-3199 for colon cancer and their effects on cell physiology. PATIENTS AND METHODS: LINC01006 and miR-3199 expression levels were determined by RT-qPCR. Patients' 5-year cumulative survival rate was analyzed by Kaplan-Meier curves with the Log rank test. Chi-square test and multivariate Cox regression analysis were used to access the clinical significance. CCK-8 assay, transwell assay, and TUNEL assays were used to monitor the change of cell proliferation, invasion, migration, and apoptosis. RESULTS: The expression level of LINC01006 was increased while miR-3199 was decreased in colon tissues and cells compared to normal ones. This dysregulated expression was correlated with T stage (P = 0.002) and N stage (P = 0.009). High LINC01006 level (HR = 4.048, 95%: 1.502-10.911, P = 0.006) or low miR-3199 level (HR = 3.421, 95% CI: 1.254-9.330, P = 0.016) was outstanding for predicting poor prognosis in patients with colon cancer. Downregulation of LINC01006 reduced cell proliferation, invasion, and migration but induced cell apoptosis (P < 0.05). CONCLUSION: LINC01006 knockdown showed anti-proliferative, anti-metastatic, and apoptotic-induced effects on colon cancer cells. This study contributes to research on promising prognostic biomarkers of colon cancer and might give way to further investigation of alternative tumor targets.

Distributed Generalized Nash Equilibrium Seeking and Its Application to Femtocell Networks.

In this article, distributed algorithms are developed to search the generalized Nash equilibrium (NE) with global constraints. Relations between the variational inequality and the NE are investigated via the Karush-Kuhn-Tucker (KKT) optimal conditions, which provide the underlying principle for developing the distributed algorithms. Two time-varying consensus schemes are proposed for each agent to estimate the actions of others, by which a distributed framework is established. The algorithm with fixed-gains is designed with certain system knowledge, while the adaptive algorithm is proposed to address the problem when the system parameters are not available. The asymptotic convergence to the NE is established through the Lyapunov theory and the consensus theory. The power control problem in a femtocell network is formulated as a Nash game and is solved by the proposed algorithms. The simulation results are provided to verify the effectiveness of theoretical development.

Consensus-Based Cooperative Algorithms for Training Over Distributed Data Sets Using Stochastic Gradients.

In this article, distributed algorithms are proposed for training a group of neural networks with private data sets. Stochastic gradients are utilized in order to eliminate the requirement for true gradients. To obtain a universal model of the distributed neural networks trained using local data sets only, consensus tools are introduced to derive the model toward the optimum. Most of the existing works employ diminishing learning rates, which are often slow and impracticable for online learning, while constant learning rates are studied in some recent works, but the principle for choosing the rates is not well established. In this article, constant learning rates are adopted to empower the proposed algorithms with tracking ability. Under mild conditions, the convergence of the proposed algorithms is established by exploring the error dynamics of the connected agents, which provides an upper bound for selecting the constant learning rates. Performances of the proposed algorithms are analyzed with and without gradient noises, in the sense of mean square error (MSE). It is proved that the MSE converges with bounded errors determined by the gradient noises, and the MSE converges to zero if the gradient noises are absent. Simulation results are provided to validate the effectiveness of the proposed algorithms.

Novel fluorescent probe based on dicoumarin for rapid on-site detection of Hg2+ in loess.

It is momentous to exploit rapid, specific and on-site detection methods for mercury ion (Hg2+) in loess, as the severe toxicity of Hg2+ and the fragile ecological environment of Loess Plateau. In this paper, a novel fluorescent probe DC-Hg (Dicoumarin-Hg) was synthesized by 3-hydroxybiscoumarin and phenyl thiochloroformate at room temperature. DC-Hg could exclusively combine with Hg2+ to 'turn-on' yellow fluorescence at 530 nm among various other metal ions. The relationship between the remarkable increase in intensity and concentration of Hg2+ was associated with photoinduced electron transfer (PET), which was founded by Job's plot and 1H NMR. The limit detection of DC-Hg showed to 85.25 nM in aqueous medium, which could be applied to varying situations. For the loess samples, they were only extracted by hand-shake and filtration for quickly complete the treatment operation on site, and the results proved that DC-Hg could satisfactorily detect the Hg2+ in mercury pollution areas.

Distributed Multiobjective Optimization for Network Resource Allocation of Multiagent Systems.

In this article, a distributed multiobjective optimization problem is formulated for the resource allocation of network-connected multiagent systems. The framework encompasses a group of distributed decision makers in the subagents, where each of them possesses a local preference index. Novel distributed algorithms are proposed to solve such a problem in a distributed manner. The weighted Lp preference index is utilized in each agent since it can provide a robust Pareto solution to the problem. By using distributed fixed-time optimization methods, the Lp preference index is constructed online without specifying the unknown parameters. Then, it is proved that the problem admits a unique Pareto solution. By exploiting consensus and gradient descent techniques, asymptotic convergence to the optimal solution is established via Lyapunov theories. Distinct from most of the current works, the proposed framework does not require any prior information in the formulation process, and private data can be well protected using this distributed approach. Numerical examples are included to validate the effectiveness of the proposed algorithms.

Tunable Non-linear Refraction Properties and Ultrafast Excited State Dynamics of Dicyanomethylene Dihydrofuran Derivative.

The third order non-linear optical response of a dicyanomethylene dihydrofuran compound (DCDHF-2V) was investigated using a Z-scan technique in picosecond and nanosecond time regimes. The results show that DCDHF-2V has excellent excited state non-linear refraction properties on both time regimes, and the non-linear refraction index is also solvent-dependent in the nanosecond regime. The excited state relaxation dynamics of DCDHF-2V were demystified via femtosecond transient absorption spectroscopy. The TA spectra reveal that the solvent viscosities have a substantial impact on the excited state relaxation of DCDHF-2V. The exotic photophysical phenomena in DCDHF-2V reported herein can shed new light on future development of small organic non-linear optical materials with large non-linear coefficients and fast response.

Comparison of long-term outcomes of laparoscopic and open sphincter-preserving total mesorectal excision for low rectal cancer.

PURPOSE: The purpose of this study was to compare the long-term outcomes of laparoscopic and open sphincter-preserving total mesorectal excision (TME) for low rectal cancer (LRC) using propensity score matching (PSM). METHODS: The clinical and follow-up data of 169 patients with LRC who underwent sphincter-preserving TME at our institution between January 2011 and January 2014 were retrospectively analyzed. Patients were divided into laparoscopic and open group based on the surgical approach. PSM including age, sex, body mass index, clinical stage, and American Society of Anesthesiologists score with a 1:1 ratio was subsequently performed. Sixty-eight patients in each group were ultimately included, and short- and long-term outcomes were compared between groups. RESULTS: Compared with the open group, the laparoscopic group had less intraoperative blood loss, more rapid postoperative recovery, and lower incidence of 30-day postoperative complications. However, there were no significant differences in severity of postoperative 30-day complications between the two groups. Both groups had no intraoperative or 30-day postoperative mortality. Regarding survival outcome, tumor recurrence rate, tumor recurrence site, 5-year overall survival, and 5-year disease-free survival, there were no significant differences between groups. CONCLUSION: Laparoscopic sphincter-preserving TME can achieve long-term outcomes similar to those of open TME for LRC.

Dual-Branch Network with a Subtle Motion Detector for Microaction Recognition in Videos.

By involving only subtle motions of body parts, video-based microaction recognition is a very important but challenging problem. Most existing action recognition methods are developed for general actions, and the current state-of-the-art methods usually largely rely on high-layer features learned from convolutional neural networks (CNNs). High-layer CNN features usually contain more semantic information but less detailed information. However, detailed information can be important for microactions due to the motion subtleness of such actions. In this paper, we propose to more effectively learn midlayer CNN features for enhancing microaction recognition. More specifically, we develop a new dual-branch network for microaction recognition: one branch uses the high-layer CNN features for classification, and the second branch further explores the midlayer CNN features for classification. In the second branch, we introduce a novel subtle motion detector consisting of three modules: 1) a discriminative spatial-temporal feature learning module, which further learns the subtle motion features corresponding to the discriminative spatial-temporal regions, 2) a parallel multiplier attention module, which further refines the features learned in channels and spatial-temporal domains, and 3) an activation fusion module, which fuses the max and average activations from midlayer CNN features for classification. In the experiments, we build a new microaction video dataset, where the micromotions of interest are mixed with other larger general motions such as walking. Comprehensive experimental results verify that the proposed method yields new state-of-the-art performance in two microaction video datasets, while its performance on two generalaction video datasets is also very promising.