Drip-Dry Strategy Assisted Blu-Ray Disc Biosensor for Fast Point of Care Testing.

Discs and numerous other consumer products have been developed for point of care testing (POCT) to replace traditional large and expensive biochemical devices in certain scenarios. Herein, we propose a drip-dry strategy (2D strategy) assisted Blu-ray disc (BD) biosensor, termed BDB, for rapid and portable POCT within 30 min with the cost of a single test < $1. The platform utilizes the covered area formed by the deposition of the substance to be measured on the activated BD surface after the evaporation of water and realizes the quantitative detection of the target through the error readout of free disc quality diagnosis software. As a proof of concept, we first demonstrated the feasibility of direct quantitative detection of substances in solution in a single system through the detection of pure proteins avoiding colorimetric reagent used in traditional optical detection. For the complex mixed systems, we then innovatively utilize the principle that soluble targets promote/inhibit the dissolution of insoluble precipitates to achieve specific detection of targets and successfully apply BDB to the indirect quantitative detection of glutathione (GSH) with LOD of 0.447 mM in the range of 2-16 mM and organophosphorus pesticides (OPs) with LOD of 2.122 × 10-7 M in the range of 1.289 × 10-7-1.289 × 10-4 M. The BDB is widely applicable, easy to operate, and less time-consuming, which is anticipated to provide an alternative method for early, on-site detection or screening.

Gesture-Controlled Robotic Arm for Agricultural Harvesting Using a Data Glove with Bending Sensor and OptiTrack Systems.

This paper presents a gesture-controlled robotic arm system designed for agricultural harvesting, utilizing a data glove equipped with bending sensors and OptiTrack systems. The system aims to address the challenges of labor-intensive fruit harvesting by providing a user-friendly and efficient solution. The data glove captures hand gestures and movements using bending sensors and reflective markers, while the OptiTrack system ensures high-precision spatial tracking. Machine learning algorithms, specifically a CNN+BiLSTM model, are employed to accurately recognize hand gestures and control the robotic arm. Experimental results demonstrate the system's high precision in replicating hand movements, with a Euclidean Distance of 0.0131 m and a Root Mean Square Error (RMSE) of 0.0095 m, in addition to robust gesture recognition accuracy, with an overall accuracy of 96.43%. This hybrid approach combines the adaptability and speed of semi-automated systems with the precision and usability of fully automated systems, offering a promising solution for sustainable and labor-efficient agricultural practices.

Disrupted cerebellar structural connectome in spinocerebellar ataxia type 3 and its association with transcriptional profiles.

Spinocerebellar ataxia type 3 (SCA3) is primarily characterized by progressive cerebellar degeneration, including gray matter atrophy and disrupted anatomical and functional connectivity. The alterations of cerebellar white matter structural network in SCA3 and the underlying neurobiological mechanism remain unknown. Using a cohort of 20 patients with SCA3 and 20 healthy controls, we constructed cerebellar structural networks from diffusion MRI and investigated alterations of topological organization. Then, we mapped the alterations with transcriptome data from the Allen Human Brain Atlas to identify possible biological mechanisms for regional selective vulnerability to white matter damage. Compared with healthy controls, SCA3 patients exhibited reduced global and nodal efficiency, along with a widespread decrease in edge strength, particularly affecting edges connected to hub regions. The strength of inter-module connections was lower in SCA3 group and negatively correlated with the Scale for the Assessment and Rating of Ataxia score, International Cooperative Ataxia Rating Scale score, and cytosine-adenine-guanine repeat number. Moreover, the transcriptome-connectome association study identified the expression of genes involved in synapse-related and metabolic biological processes. These findings suggest a mechanism of white matter vulnerability and a potential image biomarker for the disease severity, providing insights into neurodegeneration and pathogenesis in this disease.

Tunable and Non-Invasive Printing of Transmissive Interference Colors with 2D Material Inks.

Interference colors hold significant importance in optics and arts. Current methods for printing interference colors entail complex procedures and large-scale printing systems for the scarcity of inks that exhibit both sensitivity and tunability to external fields. The production of highly transparent inks capable of rendering transmissive colors has presented ongoing challenges. Here, a type of paramagnetic ink based on 2D materials that exhibit polychrome in one magnetic field is invented. By precisely manipulating the doping ratio of magnetic elements within titanate nanosheets, the magneto-optical sensitivity named Cotton-Mouton coefficient is engineerable from 728 to a record high value of 3272 m-1 T-2, with negligible influence on its intrinsic wide optical bandgap. Combined with the sensitive and controllable magneto-responsiveness of the ink, modulate and non-invasively print transmissive interference colors using small permanent magnets are precised. This work paves the way for preparing transmissive interference colors in an energy-saving and damage-free manner, which can expand its use in widespread areas.

Clinical efficacy of precision liver resection for primary liver cancer.

AIM: Precision liver resection is considered the gold standard in liver surgery. Therefore, optimizing the resection of lesions and minimizing unnecessary time of liver ischemia and hypoxia have become focal points. METHODS: A total of 96 patients with primary liver cancer admitted to Cangzhou People's Hospital from January 2017 and December 2019 were included in this retrospective study, and divided into two groups according to the different surgical treatment, with 50 cases in the control group (conventional hepatic resection) and 46 cases in the observation group (precision liver resection). The surgical indicators, liver function, alpha-fetoprotein (AFP), complications, and three-year follow-up results were analyzed in the two groups. RESULTS: The operation time, intraoperative bleeding, hospital stay, and time of anal venting in the observation group were shorter than those in the control group (P<0.05). One week after surgery, AST, TBiL, ALT, and γ-GT levels decreased in both groups, with more significant decreases in the observation group than those in the control group (P<0.05). PCT and hs-CRP levels in the observation group were significantly lower than those in the control group (P<0.05) observation. The incidences of pleural effusion, bile leak, abdominal infection, pulmonary infection, as well as the total complication rates in the observation group were lower in the observation group than those in the control group (P<0.05). The follow-up data revealed that the observation group exhibited a lower recurrence rate observationand higher survival rate than the control group within 3 years, but these differences were not significant (P>0.05). CONCLUSION: Precision liver resection can effectively treat primary liver cancer, reduce the incidence of complications, and promote patient recovery after surgery.

Systematic Review and Critical Appraisal of Prediction Models for Readmission in Coronary Artery Disease Patients: Assessing Current Efficacy and Future Directions.

Purpose: Coronary artery disease (CAD) patients frequently face readmissions due to suboptimal disease management. Prediction models are pivotal for detecting early unplanned readmissions. This review offers a unified assessment, aiming to lay the groundwork for enhancing prediction models and informing prevention strategies. Methods: A search through five databases (PubMed, Web of Science, EBSCOhost, Embase, China National Knowledge Infrastructure) up to September 2023 identified studies on prediction models for coronary artery disease patient readmissions for this review. Two independent reviewers used the CHARMS checklist for data extraction and the PROBAST tool for bias assessment. Results: From 12,457 records, 15 studies were selected, contributing 30 models targeting various CAD patient groups (AMI, CABG, ACS) from primarily China, the USA, and Canada. Models utilized varied methods such as logistic regression and machine learning, with performance predominantly measured by the c-index. Key predictors included age, gender, and hospital stay duration. Readmission rates in the studies varied from 4.8% to 45.1%. Despite high bias risk across models, several showed notable accuracy and calibration. Conclusion: The study highlights the need for thorough external validation and the use of the PROBAST tool to reduce bias in models predicting readmission for CAD patients.

Locally Strained 2D Materials: Preparation, Properties, and Applications.

2D materials are promising for strain engineering due to their atomic thickness and exceptional mechanical properties. In particular, non-uniform and localized strain can be induced in 2D materials by generating out-of-plane deformations, resulting in novel phenomena and properties, as witnessed in recent years. Therefore, the locally strained 2D materials are of great value for both fundamental studies and practical applications. This review discusses techniques for introducing local strains to 2D materials, and their feasibility, advantages, and challenges. Then, the unique effects and properties that arise from local strain are explored. The representative applications based on locally strained 2D materials are illustrated, including memristor, single photon emitter, and photodetector. Finally, concluding remarks on the challenges and opportunities in the emerging field of locally strained 2D materials are provided.

Separation of lignin derivatives from hemp fiber using supercritical CO2, ethanol, and water at different temperatures.

The process of lignin extraction often involves intricate chemical transformations, influencing its potential for high-value utilization. By investigating the process of lignin derivatives extraction from hemp fibers using supercritical CO2, ethanol, and water, we identified the relationship between the chemical structure of lignin derivatives and temperature. This discovery contributes to controlling the chemical structure of lignin derivatives through temperature modulation. We observed that lignin derivatives extracted within the temperature range of 100-120 °C exhibited the lowest average molecular weight and polydispersity index, presenting a disordered microstructure with the highest hydroxyl content. Lignin derivatives extracted between 140 and 160 °C showed an increase in average molecular weight and polydispersity index, decreased hydroxyl content, and a gradual transformation of microstructure into spherical particles. At 180 °C, the average molecular weight and polydispersity index of lignin derivatives decreased, the microstructure of lignin derivatives showed fewer spherical particles, while its hydroxyl content exhibited a partial recovery. Chemical analysis revealed a lower degree of condensation in lignin derivatives at 100-120 °C. Between 120 and 160 °C, the degree of condensation increased. At 180 °C, extensive degradation occurred in lignin derivatives. This research advances innovative techniques for lignin derivative separation, contributing to their utilization in higher-value applications.

Increasing Sufu gene dosage reveals its unorthodox role in promoting polydactyly and medulloblastoma tumorigenesis.

Suppressor of fused (SUFU) is widely regarded as a key negative regulator of the sonic hedgehog (SHH) morphogenic pathway and a known tumor suppressor of medulloblastoma (MB). However, we report here that SUFU expression was markedly increased in 75% of specimens compiled in a tissue array comprising 49 unstratified MBs. The SUFU and GLI1 expression levels in this MB array showed strong positive correlation, which was also identified in a large public data set containing 736 MBs. We further report that increasing Sufu gene dosage in mice caused preaxial polydactyly, which was associated with the expansion of the Gli3 domain in the anterior limb bud and heightened Shh signaling responses during embryonic development. Increasing Sufu gene dosage also led to accelerated cerebellar development and, when combined with ablation of the Shh receptor encoded by Patched1 (Ptch1), promoted MB tumorigenesis. These data reveal multifaceted roles of SUFU in promoting MB tumorigenesis by enhancing SHH signaling. This revelation clarifies potentially counterintuitive clinical observation of high SUFU expression in MBs and may pave way for novel strategies to reduce or reverse MB progression.

Removal of nitrate by FeSiBC metallic glasses: high efficiency and superior reusability.

The development of sustainable technologies for efficient nitrate removal has attracted increasing attention, because excessive nitrate emissions can result in serious environmental, economic, and health effects. Herein, we propose to utilize FeSiBC metallic glass (MG) powders as a potential solution for nitrate removal. In terms of removal efficiency and reusability, our results show that the MG powders, as special zero-valent iron carriers, are 2-3 orders of magnitude more efficient in nitrate removal than the previous studies, while maintaining more than 50% nitrate removal efficiency after 9 cycles of reaction. Moreover, the optimal FeSiBC MG dosage, pH value, and temperature for nitrate removal are determined. The mechanism of nitrate removal is also revealed. The present study offers a promising approach to remediate nitrate, one of the world's most widespread water pollutants.

3DCNN predicting brain age using diffusion tensor imaging.

Neuroimaging-based brain age prediction using deep learning is gaining popularity. However, few studies have attempted to leverage diffusion tensor imaging (DTI) to predict brain age. In this study, we proposed a 3D convolutional neural network model (3DCNN) and trained it on fractional anisotropy (FA) data from six publicly available datasets (n = 2406, age = 17-60) to estimate brain age. Implementing a two-loop nested cross-validation scheme with a tenfold cross-validation procedure, we achieved a robust prediction performance of a mean absolute error (MAE) of 2.785 and a correlation coefficient of 0.932. We also employed Grad-Cam++ to visualize the salient features of the proposed model. We identified a few highly salient fiber tracts, including the genu of corpus callosum and the left cerebellar peduncle, among others that play a pivotal role in our model. In sum, our model reliably predicted brain age and provided novel insight into age-related changes in brains' axonal structure.

Harnessing microcomb-based parallel chaos for random number generation and optical decision making.

Optical chaos is vital for various applications such as private communication, encryption, anti-interference sensing, and reinforcement learning. Chaotic microcombs have emerged as promising sources for generating massive optical chaos. However, their inter-channel correlation behavior remains elusive, limiting their potential for on-chip parallel chaotic systems with high throughput. In this study, we present massively parallel chaos based on chaotic microcombs and high-nonlinearity AlGaAsOI platforms. We demonstrate the feasibility of generating parallel chaotic signals with inter-channel correlation <0.04 and a high random number generation rate of 3.84 Tbps. We further show the application of our approach by demonstrating a 15-channel integrated random bit generator with a 20 Gbps channel rate using silicon photonic chips. Additionally, we achieved a scalable decision-making accelerator for up to 256-armed bandit problems. Our work opens new possibilities for chaos-based information processing systems using integrated photonics, and potentially can revolutionize the current architecture of communication, sensing and computations.

Understanding and combatting misinformation across 16 countries on six continents.

The spread of misinformation online is a global problem that requires global solutions. To that end, we conducted an experiment in 16 countries across 6 continents (N = 34,286; 676,605 observations) to investigate predictors of susceptibility to misinformation about COVID-19, and interventions to combat the spread of this misinformation. In every country, participants with a more analytic cognitive style and stronger accuracy-related motivations were better at discerning truth from falsehood; valuing democracy was also associated with greater truth discernment, whereas endorsement of individual responsibility over government support was negatively associated with truth discernment in most countries. Subtly prompting people to think about accuracy had a generally positive effect on the veracity of news that people were willing to share across countries, as did minimal digital literacy tips. Finally, aggregating the ratings of our non-expert participants was able to differentiate true from false headlines with high accuracy in all countries via the 'wisdom of crowds'. The consistent patterns we observe suggest that the psychological factors underlying the misinformation challenge are similar across different regional settings, and that similar solutions may be broadly effective.

Non-invasive detection of haemoglobin, platelets, and total bilirubin using hyperspectral cameras.

Hyperspectral imaging has emerged as a promising high-resolution and real-time imaging technology with potential applications in medical diagnostics and surgical guidance. In this study, we developed a high-speed hyperspectral camera by integrating a Fabry-Perot cavity filter on each CMOS pixel. We used it to non-invasively detect three blood components (haemoglobin, platelet, and total bilirubin). Specifically, we acquired transmission images of the subject's fingers, extracted spectral signals at each wavelength, and used dynamic spectroscopy to obtain non-invasive blood absorption spectra. The prediction models were established using the PLSR method and were modelled and validated based on the standard clinical-biochemical test values. The experimental results demonstrated excellent performance. The best predictions were obtained for haemoglobin, with a high related coefficient (R) of 0.85 or more in both the calibration and prediction sets and a mean absolute percentage error (MAPE) of only 5.7%. The results for total bilirubin were also ideal, with R values exceeding 0.8 in both sets and a MAPE of 10.6%. Although the prediction results for platelets were slightly less satisfactory, the error was still less than 15%, indicating that the results were also acceptable. Overall, our study highlights the potential of hyperspectral imaging technology for the development of portable and affordable devices for blood analysis, which can be used in various settings.

Degradation behavior of ZE21C magnesium alloy suture anchors and their effect on ligament-bone junction repair.

Current materials comprising suture anchors used to reconstruct ligament-bone junctions still have limitation in biocompatibility, degradability or mechanical properties. Magnesium alloys are potential bone implant materials, and Mg2+ has been shown to promote ligament-bone healing. Here, we used Mg-2 wt.% Zn-0.5 wt.% Y-1 wt.% Nd-0.5 wt.% Zr (ZE21C) alloy and Ti6Al4V (TC4) alloy to prepare suture anchors to reconstruct the patellar ligament-tibia in SD rats. We studied the degradation behavior of the ZE21C suture anchor via in vitro and in vivo experiments and assessed its reparative effect on the ligament-bone junction. In vitro, the ZE21C suture anchor degraded gradually, and calcium and phosphorus products accumulated on its surface during degradation. In vivo, the ZE21C suture anchor could maintain its mechanical integrity within 12 weeks of implantation in rats. The tail of the ZE21C suture anchor in high stress concentration degraded rapidly during the early implantation stage (0-4weeks), while bone healing accelerated the degradation of the anchor head in the late implantation stage (4-12weeks). Radiological, histological, and biomechanical assays indicated that the ZE21C suture anchor promoted bone healing above the suture anchor and fibrocartilaginous interface regeneration in the ligament-bone junction, leading to better biomechanical strength than the TC4 group. Hence, this study provides a basis for further research on the clinical application of degradable magnesium alloy suture anchors.

Diatomite-like KFeS2 for Use in High-Performance Electrodes for Energy Storage and Oxygen Evolution.

Bifunctional materials possess remarkable properties that allow them to store and convert electrical energy easily. In this paper, diatomite-like potassium iron disulfide (KFeS2) was synthesized by a multistep sacrificial template method, and its morphological, electrochemical, and oxygen evolution reaction (OER) properties were investigated. KFeS2 was found to be porous, hollow, and cake-like, which suggests a high specific surface area (SSA) and abundant electrochemically active sites. A very high specific capacitance of 651 F g-1 at 1.0 A g-1 was also obtained due to the substance's unique structure and high porosity. Additionally, the diatomite-like KFeS2 possessed a very low overpotential ƞ10 of 254 mV at a current density of 10 mA cm-2 and a small Tafel slope of about 48.4 mV dec-1. Thus, the diatomite-like KFeS2 demonstrates broad application prospects for both energy storage and conversion.