Effectiveness of keratinized mucosa augmentation procedures around dental implants based on risk assessment: A 5-year retrospective cohort study.

PURPOSE: To compare the effectiveness of keratinized mucosa (KM) augmentation with different techniques for the treatment of dental implants based on risk assessment. METHODS: Thirty-nine patients who underwent KM augmentation at implant sites in the posterior mandible were included. Three techniques were used based on anatomy-guided risk assessment: an apically positioned flap (APF) alone, an APF plus a free gingival graft (APF plus FGG), and an APF plus a collagen matrix (APF plus CM). Clinically effective KM augmentation was defined as remaining KM ≥ 2 mm after the intervention. The effective rate, implant/prosthesis survival rates, and bone/soft tissue parameters were analyzed. The correlation between local anatomical characteristics and different techniques was also determined. The associations between the effectiveness of KM augmentation and related factors were analyzed using a linear model. RESULTS: Overall, 74 sites received KM augmentation in the posterior mandible, for an effective rate of 94.6% at the 1-year follow-up and 93.2% at the 5-year follow-up. The KM width in the APF plus FGG group (3.85 ± 1.22 mm) was greater than that in the APF alone (3.05 ± 0.90 mm) (P = 0.016) and APF plus CM (3.21 ± 1.17 mm) groups (P = 0.038) at 5 years post-surgery. There was no significant difference in the effective/ineffective outcomes at the 1-year or 5-year follow-up among the three groups. CONCLUSIONS: Comparable effective outcomes were achieved with three KM augmentation techniques following the decision-making criterion based on risk assessment.

Predictive machine learning models based on VASARI features for WHO grading, isocitrate dehydrogenase mutation, and 1p19q co-deletion status: a multicenter study.

The objective of our study was to develop predictive models using Visually Accessible Rembrandt Images (VASARI) magnetic resonance imaging (MRI) features combined with machine learning techniques to predict the World Health Organization (WHO) grade, isocitrate dehydrogenase (IDH) mutation status, and 1p19q co-deletion status of high-grade gliomas. To achieve this, we retrospectively included 485 patients with high-grade glioma from the First Affiliated Hospital of Xinjiang Medical University, of which 312 patients were randomly divided into a training set (n=218) and a test set (n=94) in a 7:3 ratio. Twenty-five VASARI MRI features were selected from an initial set of 30, and three machine learning models - Multilayer Perceptron (MP), Bernoulli Naive Bayes (BNB), and Logistic Regression (LR) - were trained using the training set. The most informative features were identified using recursive feature elimination. Model performance was assessed using the test set and an independent validation set of 173 patients from Beijing Tiantan Hospital. The results indicated that the MP model exhibited the highest predictive accuracy on the training set, achieving an area under the curve (AUC) close to 1, indicating perfect discrimination. However, its performance decreased in the test and validation sets; particularly for predicting the 1p19q co-deletion status, the AUC was only 0.703, suggesting potential overfitting. On the other hand, the BNB model demonstrated robust generalization on the test and validation sets, with AUC values of 0.8292 and 0.8106, respectively, for predicting IDH mutation status and 1p19q co-deletion status, indicating high accuracy, sensitivity, and specificity. The LR model also showed good performance with AUCs of 0.7845 and 0.8674 on the test and validation sets, respectively, for predicting IDH mutation status, although it was slightly inferior to the BNB model for the 1p19q co-deletion status. In conclusion, integrating VASARI MRI features with machine learning techniques shows promise for the non-invasive prediction of glioma molecular markers, which could guide treatment strategies and improve prognosis in glioma patients. Nonetheless, further model optimization and validation are necessary to enhance its clinical utility.

Sulfur filling activates vacancy-induced C-C bond cleavage in polyol electrooxidation.

Using the electrochemical polyol oxidation reaction (POR) to produce formic acid over nickel-based oxides/hydroxides (NiO x H y ) is an attractive strategy for the electrochemical upgrading of biomass-derived polyols. The key step in the POR, i.e. the cleavage of the C-C bond, depends on an oxygen-vacancy-induced mechanism. However, a high-energy oxygen vacancy is usually ineffective for Schottky-type oxygen-vacancy-rich ß-Ni(OH)2 (VSO-ß-Ni(OH)2). As a result, both ß-Ni(OH)2 and VSO-ß-Ni(OH)2 cannot continuously catalyze oxygen-vacancy-induced C-C bond cleavage during PORs. Here, we report a strategy of oxygen-vacancy-filling with sulfur to synthesize a ß-Ni(OH)2 (S-VO-ß-Ni(OH)2) catalyst, whose oxygen vacancies are protected by filling with sulfur atoms. During PORs over S-VO-ß-Ni(OH)2, the pre-electrooxidation-induced loss of sulfur and structural self-reconstruction cause the in-situ generation of stable Frenkel-type oxygen vacancies for activating vacancy-induced C-C bond cleavage, thus leading to excellent POR performances. This work provides an intelligent approach for guaranteeing the sustaining action of the oxygen-vacancy-induced catalytic mechanism in electrooxidation reactions.

Enhanced diversity on connector hubs following sleep deprivation: Evidence from diffusion and functional magnetic resonance imaging.

Sleep deprivation has been demonstrated to exert widespread and intricate impacts on the brain network. The human brain network is a modular network composed of interconnected nodes. This network consists of provincial hubs and connector hubs, with provincial hubs having diverse connectivities within their own modules, while connector hubs distribute their connectivities across different modules. The latter is crucial for integrating information from various modules and ensuring the normal functioning of the modular brain. However, there has been a lack of systematic investigation into the impact of sleep deprivation on brain connector hubs. In this study, we utilized functional connectivity from resting-state functional magnetic resonance imaging, as well as structural connectivity from diffusion-weighted imaging, to systematically explore the variation of connector hub properties in the cerebral cortex after one night of sleep deprivation. The normalized participation coefficients (PCnorm) were utilized to identify connector hubs. In both the functional and structural networks, connector hubs exhibited a significant increase in average PCnorm, indicating the diversity enhancement of the connector hub following sleep deprivation. This enhancement is associated with increased network cost, reduced modularity, and decreased small-worldness, but enhanced global efficiency. This may potentially signify a compensatory mechanism within the brain following sleep deprivation. The significantly affected connector hubs were primarily observed in both the Control Network and Salience Network. We believe that the observed results reflect the increasing demand on the brain to invest more effort at preventing performance deterioration after sleep loss, in exchange for increased communication efficiency, especially involving systems responsible for neural resource allocation and cognitive control. These results have been replicated in an independent dataset. In conclusion, this study has enhanced our understanding of the compensatory mechanism in the brain response to sleep deprivation. This compensation is characterized by an enhancement in the connector hubs responsible for inter-modular communication, especially those related to neural resource and cognitive control. As a result, this compensation comes with a higher network cost but leads to an improvement in global communication efficiency, akin to a more random-like network manner.

Design and regulation of defective electrocatalysts.

Electrocatalysts are the key components of electrochemical energy storage and conversion devices. High performance electrocatalysts can effectively reduce the energy barrier of the chemical reactions, thereby improving the conversion efficiency of energy devices. The electrocatalytic reaction mainly experiences adsorption and desorption of molecules (reactants, intermediates and products) on a catalyst surface, accompanied by charge transfer processes. Therefore, surface control of electrocatalysts plays a pivotal role in catalyst design and optimization. In recent years, many studies have revealed that the rational design and regulation of a defect structure can result in rearrangement of the atomic structure on the catalyst surface, thereby efficaciously promoting the electrocatalytic performance. However, the relationship between defects and catalytic properties still remains to be understood. In this review, the types of defects, synthesis methods and characterization techniques are comprehensively summarized, and then the intrinsic relationship between defects and electrocatalytic performance is discussed. Moreover, the application and development of defects are reviewed in detail. Finally, the challenges existing in defective electrocatalysts are summarized and prospected, and the future research direction is also suggested. We hope that this review will provide some principal guidance and reference for researchers engaged in defect and catalysis research, better help researchers understand the research status and development trends in the field of defects and catalysis, and expand the application of high-performance defective electrocatalysts to the field of electrocatalytic engineering.

Paper-Recorded ECG Digitization Method with Automatic Reference Voltage Selection for Telemonitoring and Diagnosis.

In electrocardiograms (ECGs), multiple forms of encryption and preservation formats create difficulties for data sharing and retrospective disease analysis. Additionally, photography and storage using mobile devices are convenient, but the images acquired contain different noise interferences. To address this problem, a suite of novel methodologies was proposed for converting paper-recorded ECGs into digital data. Firstly, this study ingeniously removed gridlines by utilizing the Hue Saturation Value (HSV) spatial properties of ECGs. Moreover, this study introduced an innovative adaptive local thresholding method with high robustness for foreground-background separation. Subsequently, an algorithm for the automatic recognition of calibration square waves was proposed to ensure consistency in amplitude, rather than solely in shape, for digital signals. The original signal reconstruction algorithm was validated with the MIT-BIH and PTB databases by comparing the difference between the reconstructed and the original signals. Moreover, the mean of the Pearson correlation coefficient was 0.97 and 0.98, respectively, while the mean absolute errors were 0.324 and 0.241, respectively. The method proposed in this study converts paper-recorded ECGs into a digital format, enabling direct analysis using software. Automated techniques for acquiring and restoring ECG reference voltages enhance the reconstruction accuracy. This innovative approach facilitates data storage, medical communication, and remote ECG analysis, and minimizes errors in remote diagnosis.

Genetic-Dependent Brain Signatures of Resilience: Interactions among Childhood Abuse, Genetic Risks and Brain Function.

Resilience to emotional disorders is critical for adolescent mental health, especially following childhood abuse. Yet, brain signatures of resilience remain undetermined due to the differential susceptibility of the brain's emotion processing system to environmental stresses. Analyzing brain's responses to angry faces in a longitudinally large-scale adolescent cohort (IMAGEN), we identified two functional networks related to the orbitofrontal and occipital regions as candidate brain signatures of resilience. In girls, but not boys, higher activation in the orbitofrontal-related network was associated with fewer emotional symptoms following childhood abuse, but only when the polygenic burden for depression was high. This finding defined a genetic-dependent brain (GDB) signature of resilience. Notably, this GDB signature predicted subsequent emotional disorders in late adolescence, extending into early adulthood and generalizable to another independent prospective cohort (ABCD). Our findings underscore the genetic modulation of resilience-brain connections, laying the foundation for enhancing adolescent mental health through resilience promotion.

Cannabinoid receptor 2 plays a key role in renal fibrosis through inhibiting lipid metabolism in renal tubular cells.

AIMS: Renal fibrosis is a common feature in various chronic kidney diseases (CKD). Tubular cell damage is a main characterization which results from dysregulated fatty acid oxidation (FAO) and lipid accumulation. Cannabinoid Receptor 2 (CB2) contributes to renal fibrosis, however, its role in FAO dysregulation in tubular cells is not clarified. In this study, we found CB2 plays a detrimental role in lipid metabolism in tubular cells. METHODS: CB2 knockout mice were adopted to establish a folic acid-induced nephropathy (FAN) model. CB2-induced FAO dysfunction, lipid deposition, and fibrogenesis were assessed in vivo and vitro. To explore molecular mechanisms, ß-catenin inhibitors and peroxisome proliferator-activated receptor alpha (PPARα) activators were also used in CB2-overexpressed cells. The mediative role of ß-catenin in CB2-inhibited PPARα and peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α) activation was analyzed. RESULTS: CB2 activates ß-catenin signaling, resulting in the suppression of PPARα/PGC-1α axis. This decreased FAO functions and led to lipid droplet formation in tubular cells. CB2 gene ablation effectively mitigated FAO dysfunction, lipid deposition and uremic toxins accumulation in FAN mice, consequently retarding renal fibrosis. Additionally, inhibition to ß-catenin or PPARα activation could greatly inhibit lipid accumulation and fibrogenesis induced by CB2. CONCLUSIONS: This study highlights CB2 disrupts FAO in tubular cells through ß-catenin activation and subsequent inhibition on PPARα/PGC-1α activity. Targeted inhibition on CB2 offers a perspective therapeutic strategy to fight against renal fibrosis.

AlphaFold2-guided engineering of split-GFP technology enables labeling of endogenous tubulins across species while preserving function.

Dynamic properties are essential for microtubule (MT) physiology. Current techniques for in vivo imaging of MTs present intrinsic limitations in elucidating the isotype-specific nuances of tubulins, which contribute to their versatile functions. Harnessing the power of the AlphaFold2 pipeline, we engineered a strategy for the minimally invasive fluorescence labeling of endogenous tubulin isotypes or those harboring missense mutations. We demonstrated that a specifically designed 16-amino acid linker, coupled with sfGFP11 from the split-sfGFP system and integration into the H1-S2 loop of tubulin, facilitated tubulin labeling without compromising MT dynamics, embryonic development, or ciliogenesis in Caenorhabditis elegans. Extending this technique to human cells and murine oocytes, we visualized MTs with the minimal background fluorescence and a pathogenic tubulin isoform with fidelity. The utility of our approach across biological contexts and species set an additional paradigm for studying tubulin dynamics and functional specificity, with implications for understanding tubulin-related diseases known as tubulinopathies.

Advancements in microenvironment-based therapies: transforming the landscape of multiple myeloma treatment.

Multiple myeloma (MM) is the most prevalent malignant monoclonal disease of plasma cells. There is mounting evidence that interactions with the bone marrow (BM) niche are essential for the differentiation, proliferation, survival, migration, and treatment resistance of myeloma cells. For this reason, gaining a deeper comprehension of how BM microenvironment compartments interact with myeloma cells may inspire new therapeutic ideas that enhance patient outcomes. This review will concentrate on the most recent findings regarding the mechanisms of interaction between microenvironment and MM and highlight research on treatment targeting the BM niche.

Contrastive machine learning reveals Parkinson's disease specific features associated with disease severity and progression.

Parkinson's disease (PD) exhibits heterogeneity in terms of symptoms and prognosis, likely due to diverse neuroanatomical alterations. This study employs a contrastive deep learning approach to analyze Magnetic Resonance Imaging (MRI) data from 932 PD patients and 366 controls, aiming to disentangle PD-specific neuroanatomical alterations. The results reveal that these neuroanatomical alterations in PD are correlated with individual differences in dopamine transporter binding deficit, neurodegeneration biomarkers, and clinical severity and progression. The correlation with clinical severity is verified in an external cohort. Notably, certain proteins in the cerebrospinal fluid are strongly associated with PD-specific features, particularly those involved in the immune function. The most notable neuroanatomical alterations are observed in both subcortical and temporal regions. Our findings provide deeper insights into the patterns of brain atrophy in PD and potential underlying molecular mechanisms, paving the way for earlier patient stratification and the development of treatments to slow down neurodegeneration.

Design, modeling, and control of a long stroke compliant tip-tilt-piston micropositioning stage driven by voice coil motors.

In this paper, a long-stroke parallel compliant tip-tilt-piston micropositioning stage driven by voice coil motors (VCMs) is proposed. The stage is equipped with three sets of driving arms, which include a spherical hinge, VCM, and parallelogram guide mechanism, evenly spaced at 120° intervals. The spherical hinge is composed of orthogonal leaf-spring beams, and the VCM is embedded into the parallelogram mechanism to form a compact design. The compliance matrix method and the geometric method facilitated the determination of compliance in all six degree-of-freedom directions of the spherical hinge and the derivation of kinematic equations for decoupling the motion of the stage. In addition, finite element analysis was utilized to determine the maximum stroke and stress of the stage. To validate the proposed design, a stage prototype was constructed and subjected to experimental testing. Furthermore, a feedback controller was designed, integrating proportional integral controller, notch filter, and sliding mode controller feedforward. The experimental results indicate that the stage can achieve a long stroke of ±50.75 mrad × ±44.2 mrad × ±4.425 mm, with the natural frequencies in the three-axis direction of 22.3 × 25.5 × 25.5 Hz3. In addition, the maximum relative tracking error was maintained below 5.25%, highlighting the effectiveness of the control technique in achieving a high tracking performance.

Clinical Characteristics and Outcomes of Hyperphosphatemia in Patients with Chronic Kidney Disease Stages 1-2.

INTRODUCTION: There was limited research on the epidemiology of hyperphosphatemia in early-stage chronic kidney disease (CKD) patients. We aimed to explore the clinical characteristics and prognostic value of hyperphosphatemia in patients with CKD stages 1-2. METHODS: We enrolled adult patients with CKD stages 1-2 from 24 regional central hospitals across China. Hyperphosphatemia was defined as a serum phosphate level exceeding 1.45 mmol/L. The study outcomes included all-cause and cardiovascular (CV) mortality. Cox proportional hazard models were used to investigate the association of hyperphosphatemia with all-cause and CV mortality. RESULTS: Among 99,266 patients with CKD stages 1-2 across China, the prevalence of hyperphosphatemia was 8.3%. The prevalence of hyperphosphatemia was increased with the level of urinary protein and was higher in younger and female patients. Among 63,121 patients with survival information, during a median of 5.2 years follow-up period, there were 436 (8.0%) and 4,695 (8.1%) deaths in those with and without hyperphosphatemia, respectively. After adjusting for potential confounders, compared with patients without hyperphosphatemia, patients with hyperphosphatemia were associated with a higher risk of all-cause mortality (hazard ratio: 1.28, 95% CI: 1.16-1.41). Although nearly 60.3% of hyperphosphatemia could be relieved without phosphate-lowering drug therapy among patients with CKD stages 1-2, transient hyperphosphatemia was also associated with an increased risk of all-cause mortality (p = 0.048). CONCLUSIONS: Hyperphosphatemia was not rare in patients with CKD stages 1-2 and was associated with an increased risk of mortality. Clinicians should closely monitor serum phosphorus levels in patients with CKD, even in those with normal kidney function.

Initial therapeutic evidence of a borosilicate bioactive glass (BSG) and Fe3O4 magnetic nanoparticle scaffold on implant-associated Staphylococcal aureus bone infection.

Implant-associated Staphylococcus aureus (S. aureus) osteomyelitis is a severe challenge in orthopedics. While antibiotic-loaded bone cement is a standardized therapeutic approach for S. aureus osteomyelitis, it falls short in eradicating Staphylococcus abscess communities (SACs) and bacteria within osteocyte-lacuna canalicular network (OLCN) and repairing bone defects. To address limitations, we developed a borosilicate bioactive glass (BSG) combined with ferroferric oxide (Fe3O4) magnetic scaffold to enhance antibacterial efficacy and bone repair capabilities. We conducted comprehensive assessments of the osteoinductive, immunomodulatory, antibacterial properties, and thermal response of this scaffold, with or without an alternating magnetic field (AMF). Utilizing a well-established implant-related S. aureus tibial infection rabbit model, we evaluated its antibacterial performance in vivo. RNA transcriptome sequencing demonstrated that BSG + 5%Fe3O4 enhanced the immune response to bacteria and promoted osteogenic differentiation and mineralization of MSCs. Notably, BSG + 5%Fe3O4 upregulated gene expression of NOD-like receptor and TNF pathway in MSCs, alongside increased the expression of osteogenic factors (RUNX2, ALP and OCN) in vitro. Flow cytometry on macrophage exhibited a polarization effect towards M2, accompanied by upregulation of anti-inflammatory genes (TGF-ß1 and IL-1Ra) and downregulation of pro-inflammatory genes (IL-6 and IL-1ß) among macrophages. In vivo CT imaging revealed the absence of osteolysis and periosteal response in rabbits treated with BSG + 5%Fe3O4 + AMF at 42 days. Histological analysis indicated complete controls of SACs and bacteria within OLCN by day 42, along with new bone formation, signifying effective control of S. aureus osteomyelitis. Further investigations will focus on the in vivo biosafety and biological mechanism of this scaffold within infectious microenvironment.

Benmelstobart, anlotinib and chemotherapy in extensive-stage small-cell lung cancer: a randomized phase 3 trial.

Immunochemotherapy is the first-line standard for extensive-stage small-cell lung cancer (ES-SCLC). Combining the regimen with anti-angiogenesis may improve efficacy. ETER701 was a multicenter, double-blind, randomized, placebo-controlled phase 3 trial that investigated the efficacy and safety of benmelstobart (a novel programmed death-ligand 1 (PD-L1) inhibitor) with anlotinib (a multi-target anti-angiogenic small molecule) and standard chemotherapy in treatment-naive ES-SCLC. The ETER701 trial assessed two primary endpoints: Independent Review Committee-assessed progression-free survival per RECIST 1.1 and overall survival (OS). Here the prespecified final progression-free survival and interim OS analysis is reported. Patients randomly received benmelstobart and anlotinib plus etoposide/carboplatin (EC; n = 246), placebo and anlotinib plus EC (n = 245) or double placebo plus EC ('EC alone'; n = 247), followed by matching maintenance therapy. Compared with EC alone, median OS was prolonged with benmelstobart and anlotinib plus EC (19.3 versus 11.9 months; hazard ratio 0.61; P = 0.0002), while improvement of OS was not statistically significant with anlotinib plus EC (13.3 versus 11.9 months; hazard ratio 0.86; P = 0.1723). The incidence of grade 3 or higher treatment-related adverse events was 93.1%, 94.3% and 87.0% in the benmelstobart and anlotinib plus EC, anlotinib plus EC, and EC alone groups, respectively. This study of immunochemotherapy plus multi-target anti-angiogenesis as first-line treatment achieved a median OS greater than recorded in prior randomized studies in patients with ES-SCLC. The safety profile was assessed as tolerable and manageable. Our findings suggest that the addition of anti-angiogenesis therapy to immunochemotherapy may represent an efficacious and safe approach to the management of ES-SCLC. ClinicalTrials.gov identifier: NCT04234607 .

Identifying behaviour-related and physiological risk factors for suicide attempts in the UK Biobank.

Suicide is a global public health challenge, yet considerable uncertainty remains regarding the associations of both behaviour-related and physiological factors with suicide attempts (SA). Here we first estimated polygenic risk scores (PRS) for SA in 334,706 UK Biobank participants and conducted phenome-wide association analyses considering 2,291 factors. We identified 246 (63.07%) behaviour-related and 200 (10.41%, encompassing neuroimaging, blood and metabolic biomarkers, and proteins) physiological factors significantly associated with SA-PRS, with robust associations observed in lifestyle factors and mental health. Further case-control analyses involving 3,558 SA cases and 149,976 controls mirrored behaviour-related associations observed with SA-PRS. Moreover, Mendelian randomization analyses supported a potential causal effect of liability to 58 factors on SA, such as age at first intercourse, neuroticism, smoking, overall health rating and depression. Notably, machine-learning classification models based on behaviour-related factors exhibited high discriminative accuracy in distinguishing those with and without SA (area under the receiver operating characteristic curve 0.909 ± 0.006). This study provides comprehensive insights into diverse risk factors for SA, shedding light on potential avenues for targeted prevention and intervention strategies.

The impact of REM sleep loss on human brain connectivity.

Brain function is vulnerable to the consequences of inadequate sleep, an adverse trend that is increasingly prevalent. The REM sleep phase has been implicated in coordinating various brain structures and is hypothesized to have potential links to brain variability. However, traditional imaging research have encountered challenges in attributing specific brain region activity to REM sleep, remained understudied at the whole-brain connectivity level. Through the spilt-night paradigm, distinct patterns of REM sleep phases were observed among the full-night sleep group (n = 36), the early-night deprivation group (n = 41), and the late-night deprivation group (n = 36). We employed connectome-based predictive modeling (CPM) to delineate the effects of REM sleep deprivation on the functional connectivity of the brain (REM connectome) during its resting state. The REM sleep-brain connectome was characterized by stronger connectivity within the default mode network (DMN) and between the DMN and visual networks, while fewer predictive edges were observed. Notably, connections such as those between the cingulo-opercular network (CON) and the auditory network, as well as between the subcortex and visual networks, also made significant contributions. These findings elucidate the neural signatures of REM sleep loss and reveal common connectivity patterns across individuals, validated at the group level.

A rare combination of correct transposition of the great arteries and isolated levocardia: Imaging characterization.

Congenitally correct transposition of the great arteries (cc-TGA) is an extremely rare congenital cardiac malposition. It can be detected antenatally by echocardiography. This case report describes a 58-year-old female patient who presented with tachycardia. The combination of cc-TGA and isolated levocardia is incidentally diagnosed by transthoracic echocardiography and cardiac magnetic resonance imaging.

Self-powered and speed-adjustable sensor for abyssal ocean current measurements based on triboelectric nanogenerators.

The monitoring of currents in the abyssal ocean is an essential foundation of deep-sea research. The state-of-the-art current meter has limitations such as the requirement of a power supply for signal transduction, low pressure resistance, and a narrow measurement range. Here, we report a fully integrated, self-powered, highly sensitive deep-sea current measurement system in which the ultra-sensitive triboelectric nanogenerator harvests ocean current energy for the self-powered sensing of tiny current motions down to 0.02 m/s. Through an unconventional magnetic coupling structure, the system withstands immense hydrostatic pressure exceeding 45 MPa. A variable-spacing structure broadens the measuring range to 0.02-6.69 m/s, which is 67% wider than that of commercial alternatives. The system successfully operates at a depth of 4531 m in the South China Sea, demonstrating the record-deep operations of triboelectric nanogenerator-based sensors in deep-sea environments. Our results show promise for sustainable ocean current monitoring with higher spatiotemporal resolution.

A semi-automated cell tracking protocol for quantitative analyses of neutrophil swarming to sterile and S. aureus contaminated bone implants in a mouse femur model.

Implant-associated osteomyelitis remains a major orthopaedic problem. As neutrophil swarming to the surgical site is a critical host response to prevent infection, visualization and quantification of this dynamic behavior at the native microenvironment of infection will elucidate previously unrecognized mechanisms central to understanding the host response. We recently developed longitudinal intravital imaging of the bone marrow (LIMB) to visualize host cells and fluorescent S. aureus on a contaminated transfemoral implant in live mice, which allows for direct visualization of bacteria colonization of the implant and host cellular responses using two-photon laser scanning microscopy. To the end of rigorous and reproducible quantitative outcomes of neutrophil swarming kinetics in this model, we developed a protocol for robust segmentation, tracking, and quantifications of neutrophil dynamics adapted from Trainable Weka Segmentation and TrackMate, two readily available Fiji/ImageJ plugins. In this work, Catchup mice with tdTomato expressing neutrophils received a transfemoral pin with or without ECFP/EGFP-expressing USA300 methicillin-resistant Staphylococcus aureus (MRSA) to obtain 30-minute LIMB videos at 2-, 4-, and 6-hours post-implantation. The developed semi-automated neutrophil tracking protocol was executed independently by two users to quantify the distance, displacement, speed, velocity, and directionality of the target cells. The results revealed high inter-user reliability for all outcomes (ICC > 0.96; p > 0.05). Consistent with the established paradigm on increased neutrophil swarming during active infection, the results also demonstrated increased neutrophil speed and velocity at all measured time points, and increased displacement at later time points (6 hours) in infected versus uninfected mice (p < 0.05). Neutrophils and bacteria also exhibit directionality during migration in the infected mice. The semi-automated cell tracking protocol provides a streamlined approach to robustly identify and track individual cells across diverse experimental settings and eliminates inter-observer variability.