Bibliometric analysis of microRNAs and Parkinson's disease from 2014 to 2023.

Background: Parkinson's disease (PD) is a neurodegenerative disorder characterized by the degeneration of dopaminergic neurons. Recent research has emphasized a significant correlation between microRNAs (miRNAs) and PD. To identify key research areas, provide a comprehensive overview of current research in various fields, and propose potential directions for future studies, a bibliometric analysis was conducted on the involvement of miRNAs in Parkinson's disease from 2014 to 2023. Methods: Relevant literature records were collected from the Web of Science Core Collection on February 29, 2024. Subsequently, the data underwent analysis using the Bibliometrix R package and VOSviewer (version 1.6.19). Results: The annual scientific publications on miRNAs and Parkinson's disease demonstrated an increasing trend, with an annual growth rate of 12.67%. China, the United States, and India emerged as the top three most productive countries/regions. The University of Barcelona had the highest annual publications, followed by Central South University and the Helmholtz Association. The INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES held the top position in terms of H-index and total citations, reflecting its extensive influence and prolific publication output. Kim, J., Junn, E., Hébert, S.S., and Doxakis, E. were the most frequently co-cited authors in the field. Based on the analysis of keywords, the most frequently occurring terms included "alpha-synuclein," "neurodegenerative disease," "exosome," "neuroinflammation," "oxidative stress," "autophagy," and "amyotrophic lateral sclerosis," which have emerged as prominent research topics. Concurrently, there has been notable interest in topics such as "ceRNA," "lncRNAs," "mitochondrial dysfunction," and "circular RNA." Conclusion: This study focused on identifying emerging trends and critical research topics in the bibliometric analysis of microRNAs related to Parkinson's disease. These findings highlight the diverse research landscape and evolving trend of miRNA-related research in PD. The field of miRNA research in Parkinson's disease is actively exploring the underlying mechanisms of miRNA function, identifying potential diagnostic markers, and developing innovative therapeutic strategies. The results of our study offer significant contributions to researchers' ability to track contemporary developments and guide the trajectory of future research in this domain.

Transmembrane channel-like 4 and 5 proteins at microvillar tips are potential ion channels and lipid scramblases.

Microvilli-membrane bound actin protrusions on the surface of epithelial cells-are sites of critical processes including absorption, secretion, and adhesion. Increasing evidence suggests microvilli are mechanosensitive, but underlying molecules and mechanisms remain unknown. Here, we localize transmembrane channel-like proteins 4 and 5 (TMC4 and 5) and calcium and integrin binding protein 3 (CIB3) to microvillar tips in intestinal epithelial cells, near glycocalyx insertion sites. We find that TMC5 colocalizes with CIB3 in cultured cells and that a TMC5 fragment forms a complex with CIB3 in vitro. Homology and AlphaFold2 models reveal a putative ion permeation pathway in TMC4 and 5, and molecular dynamics simulations predict both proteins can conduct ions and perform lipid scrambling. These findings raise the possibility that TMC4 and 5 interact with CIB3 at microvillar tips to form a mechanosensitive complex, akin to TMC1 and 2, and CIB2 and 3, within the mechanotransduction channel complex at the tips of inner ear stereocilia.

LINC01503 promotes the cell proliferation, migration and invasion of triple-negative breast cancer as a ceRNA to elevate SPNS2 expression by sponging miR-335-5p.

Objective: Triple-negative breast cancer (TNBC) is a common cancer with high aggressiveness and high mortality in women. Recently, a plenty of studies have indicated that long non-coding RNAs (lncRNAs) exert the crucial function in human cancers, TNBC is included. The carcinogenicity of lncRNA long intergenic non-protein coding RNA 1503 (LINC01503) has been confirmed in several cancers, nevertheless, its function in TNBC still unclear. Therefore, our study aimed to reveal the underlying mechanism of LINC01503 in TNBC. Methods: In our study, RT-qPCR was performed to detect the expression of LINC01503 in TNBC cells. The proliferative, invasive, migratory and apoptotic abilities of TNBC cells were detected by functional assay such as CCK-8, clone formation, EdU staining, transwell, and flow cytometry. RIP, RNA pull down, and luciferase assay revealed interactions between LINC01503, miR-335-5p, and sphingolipid transporter protein 2 (SPNS2). Finally, rescue experiments were performed to validate the previous results. Results: LINC01503 expression was singularly high in TNBC cells. LINC01503 knockdown could restrain cell proliferation, invasion and migration, but accelerated cell apoptosis in TNBC. What's more, miR-335-5p could be sponged by LINC01503 in TNBC. We also found that overexpressed miR-335-5p could inhibit cell proliferation, migration and invasion and facilitates cell apoptosis. Moreover, SPNS2 was the target gene of miR-335-5p and it functioned as an oncogene in TNBC cells. Finally, we found that overexpressed SPNS2 or inhibited miR-335-5p could reverse the suppressive function of silencing LINC01503 on TNBC progression. Conclusion: LINC01503 could facilitate cell proliferation, migration and invasion of TNBC by sponging miR-335-5p to elevate SPNS2 expression.

Functional variants of the pentraxin 3 gene are associated with the metastasis and progression of prostate cancer.

Age, ethnic background and genetic components have been identified as the established risks for prostate cancer (PCa). Pentraxin 3 (PTX3), originally identified as a pattern-recognition molecule for defence against infectious agents, has multiple functions in tissue repair and in the regulation of cancer-associated inflammation. In this study, we sought to investigate the impact of PTX3 gene variants on the development of PCa. Genotypes of four common single-nucleotide polymorphisms (SNPs) of PTX3 gene, including rs1840680, rs2305619, rs3816527 and rs2120243, were profiled among 705 PCa patients and 705 ethnicity-matched controls. In this study, we found that patients who carry at least one minor allele (C) of rs3816527 (AC and CC) tended to develop advanced forms of diseases (clinical large T stage, OR, 1.593, p = 0.032; pathologically-confirmed nodal spread, OR, 1.987, p = 0.011; metastatic tumour, OR, 3.896, p = 0.032) as compared with those homologous for the major allele (AA). Further stratification analysis showed that such association of rs3816527 with lymphatic and distal metastasis of PCa was accentuated in the younger age group (≤65 at diagnosis) but not seen in the older age group (>65 at diagnosis), suggesting an age-specific effect of PTX3 variants. Prediction of PTX3 protein structure implied that polymorphism may alter the quaternary organization and oligomerization of PTX3 protein. Moreover, our gene silencing experiments and survey of public datasets revealed that elevation of PTX3 levels in PCa was required for cell migration and associated with tumour metastasis. Our results highlight an association of PTX3 rs3816527 with the progression of PCa.

Mediation analysis for TNF-α as a mediator between multiple metal exposure and kidney function.

The association between metal mixtures and kidney function has been reported. However, reports on the mechanism of metal toxicity were limited. Oxidative stress was reported as a possible cause. This study aimed to determine the association between of kidney function and metals, such as arsenic (As), cadmium (Cd), cobalt (Co), copper (Cu), lead (Pb), selenium (Se), and zinc (Zn), and to explore the possible mediating role of tumor necrosis factor alpha (TNF-α) between metal toxicity and kidney function. In this study, we recruited 421 adults from a health examination. The concentration of blood metals was analyzed using inductively coupled plasma mass spectrometry. We used linear regression models to assess the association between metals and TNF-α. Then, mediation analysis was applied to investigate the relationship between metal exposure, TNF-α, and kidney function. In univariate linear regression, blood As, Cd, Co, Cu, Pb, and Zn levels significantly increased TNF-α and decreased kidney function. Higher blood As and Pb levels significantly increased TNF-α in multivariable linear regressions after adjusting for covariates. We found that blood levels of As (coefficients = -0.021, p = 0.011), Pb (coefficients = -0.060, p < 0.001), and Zn (coefficients = -0.230, p < 0.001) showed a significant negative association with eGFR in the multiple-metal model. Furthermore, mediation analysis showed that TNF-α mediated 41.7 %, 38.8 %, and 20.8 % of blood Cd, As and Pb, respectively. Among the essential elements, TNF-α mediated 24.5 %, 21.5 % and 19.9 % in the effects of blood Co, Cu, and Zn on kidney function, respectively. TNF-α, acting as a mediator, accounted for 20.1 % of the contribution between the WQS score of metal mixtures and the eGFR (p < 0.001). This study suggested that TNF-α may be a persuasive pathway mediating the association between metals and kidney function. Inflammation and kidney injury could be the underlying mechanisms of metal exposure. However, there is still a need to clarify the biochemical mechanism in follow-up studies.

Merlin: A Vision Language Foundation Model for 3D Computed Tomography.

Over 85 million computed tomography (CT) scans are performed annually in the US, of which approximately one quarter focus on the abdomen. Given the current shortage of both general and specialized radiologists, there is a large impetus to use artificial intelligence to alleviate the burden of interpreting these complex imaging studies while simultaneously using the images to extract novel physiological insights. Prior state-of-the-art approaches for automated medical image interpretation leverage vision language models (VLMs) that utilize both the image and the corresponding textual radiology reports. However, current medical VLMs are generally limited to 2D images and short reports. To overcome these shortcomings for abdominal CT interpretation, we introduce Merlin - a 3D VLM that leverages both structured electronic health records (EHR) and unstructured radiology reports for pretraining without requiring additional manual annotations. We train Merlin using a high-quality clinical dataset of paired CT scans (6+ million images from 15,331 CTs), EHR diagnosis codes (1.8+ million codes), and radiology reports (6+ million tokens) for training. We comprehensively evaluate Merlin on 6 task types and 752 individual tasks. The non-adapted (off-the-shelf) tasks include zero-shot findings classification (31 findings), phenotype classification (692 phenotypes), and zero-shot cross-modal retrieval (image to findings and image to impressions), while model adapted tasks include 5-year chronic disease prediction (6 diseases), radiology report generation, and 3D semantic segmentation (20 organs). We perform internal validation on a test set of 5,137 CTs, and external validation on 7,000 clinical CTs and on two public CT datasets (VerSe, TotalSegmentator). Beyond these clinically-relevant evaluations, we assess the efficacy of various network architectures and training strategies to depict that Merlin has favorable performance to existing task-specific baselines. We derive data scaling laws to empirically assess training data needs for requisite downstream task performance. Furthermore, unlike conventional VLMs that require hundreds of GPUs for training, we perform all training on a single GPU. This computationally efficient design can help democratize foundation model training, especially for health systems with compute constraints. We plan to release our trained models, code, and dataset, pending manual removal of all protected health information.

Linking the relationship between dietary folic acid intake and risk of osteoporosis among middle-aged and older people: A nationwide population-based study.

Among middle-aged and older people, balanced and nutritious diets are the foundation for maintaining bone health and preventing osteoporosis. This study is aimed at investigating the link between dietary folic acid intake and the risk of osteoporosis among middle-aged and older people. A total of 20,686 people from the National Health and Nutritional Examination Survey (NHANES) 2007-2010 are screened and included, and 5312 people aged ≥45 years with integral data are ultimately enrolled in evaluation. Demographics and dietary intake-related data are gathered and analyzed, and the odds ratio (OR) and 95% confidence interval (CI) of each tertile category of dietary folic acid intake and each unit increase in folic acid are assessed via multivariate logistic regression models. On this basis, the receiver operating characteristic (ROC) curve is used to identify the optimal cutoff value of dietary folic acid intake for indicating the risk of osteoporosis. Of 5312 people with a mean age of 62.4 ± 11.0 years old, a total of 513 people with osteoporosis are screened, and the dietary folic acid intake amount of the osteoporosis group is significantly lower than that of the non-osteoporosis group (p < .001). The lowest tertile category is then used to act as a reference category, and a higher dietary folic acid intake amount is observed to be positively related to lower odds for risk of osteoporosis. This trend is also not changed in adjustments for combinations of different covariates (p all < .05). Based on this, a dietary folic acid intake of 475.5 µg/day is identified as an optimal cutoff value for revealing osteoporosis. Collectively, this nationwide population-based study reveals that a higher daily dietary folic acid intake has potential protective effects on osteoporosis in middle-aged and older people.

Predicting cardiovascular disease risk using photoplethysmography and deep learning.

Cardiovascular diseases (CVDs) are responsible for a large proportion of premature deaths in low- and middle-income countries. Early CVD detection and intervention is critical in these populations, yet many existing CVD risk scores require a physical examination or lab measurements, which can be challenging in such health systems due to limited accessibility. We investigated the potential to use photoplethysmography (PPG), a sensing technology available on most smartphones that can potentially enable large-scale screening at low cost, for CVD risk prediction. We developed a deep learning PPG-based CVD risk score (DLS) to predict the probability of having major adverse cardiovascular events (MACE: non-fatal myocardial infarction, stroke, and cardiovascular death) within ten years, given only age, sex, smoking status and PPG as predictors. We compare the DLS with the office-based refit-WHO score, which adopts the shared predictors from WHO and Globorisk scores (age, sex, smoking status, height, weight and systolic blood pressure) but refitted on the UK Biobank (UKB) cohort. All models were trained on a development dataset (141,509 participants) and evaluated on a geographically separate test (54,856 participants) dataset, both from UKB. DLS's C-statistic (71.1%, 95% CI 69.9-72.4) is non-inferior to office-based refit-WHO score (70.9%, 95% CI 69.7-72.2; non-inferiority margin of 2.5%, p<0.01) in the test dataset. The calibration of the DLS is satisfactory, with a 1.8% mean absolute calibration error. Adding DLS features to the office-based score increases the C-statistic by 1.0% (95% CI 0.6-1.4). DLS predicts ten-year MACE risk comparable with the office-based refit-WHO score. Interpretability analyses suggest that the DLS-extracted features are related to PPG waveform morphology and are independent of heart rate. Our study provides a proof-of-concept and suggests the potential of a PPG-based approach strategies for community-based primary prevention in resource-limited regions.

[Comparison of open reduction hollow nail anchoring system with loop plate fixation under arthroscopy for the treatment of posterior cruciate ligament avulsion fractures].

OBJECTIVE: To compare clinical effect between open reduction and fixation with cannulated screw and threaded rivet via posteromedial approach versus arthroscopic Endobutton plate fixation in treating posterior cruciate ligament avulsion fractures. METHODS: Clinical data of 38 patients with posterior cruciate ligament avulsion fractures from July 2020 to December 2021 were analyzed retrospectively, and divided into open reduction and internal fixation group (posterior medial approach hollow anchor system fixation) and arthroscopic fixation group (Endobutton with loop plate fixation under arthroscopy). There were 20 patients in open reduction and internal fixation group, including 16 males and 4 females, aged from 26 to 74 years old with an average of (42.9±18.8) years old;13 patients on the left side and 7 patients on the right side;12 patients were classified to typeⅡand 8 patiens with type Ⅲ according to Meyers-McKeever fractures classification;14 patients were gradeⅡand 6 patients were grade Ⅲ in back drawer test. There were 18 patients in arthroscopic fixation group, including 11 males and 7 females;aged from 24 to 70 years old with an average of (53.5±13.4) years old;11 patients on the left side and 7 patients on the right side;10 patients were classified to typeⅡand 8 patiens with type Ⅲ according to Meyers-McKeever fractures classification;11 patients were gradeⅡand 7 patients were grade Ⅲ in back drawer test. Operation time, blood loss, and quality of immediate reduction were compared between two groups. Knee range of motion, knee back drawer test, and International Knee Documentation Committee(IKDC) grading, KT2000 stability evaluation and Lysholm function score of knee joint were compared at 6 months after operation. RESULTS: All patients were followed up for 8 to 16 months with an average of (12.3±1.9) months. There were no complications such as incision infection, fracture malunion or non-union, and internal fixation loosening occurred. The avulsion fractures of knee joint were reached to imaging healing standard at 6 months after operation. Operation time and blood loss in open reduction and internal fixation group were (56.4±7.1) min and (63.2±10.2) ml, while (89.9±7.4) min and (27.7±8.7) ml in arthroscopic fixation group, respectively, and had significant difference between two groups (P<0.05). There were no differences in immediate reduction quality (χ2=0.257, P=0.612), knee joint range of motion at 6 months after opertaion (t=0.492, P=0.626), knee joint rear drawer test ( χ2=0.320, P=0.572), IKDC classification of knee joint (χ2=0.127, P=0.938), KT2000 stability evaluation (χ2=0.070, P=0.791), and knee Lysholm function score (t=0.092, P=0.282) between two groups. CONCLUSION: Posterior medial approach with hollow anchoring system fixation and arthroscopic Endobutton with loop plate fixation for the treatment of posterior cruciate ligament tibial occlusion avulsion fracture could achieve satisfactory clinical results, and arthroscopic surgery has less bleeding, but also has a longer learning curve and longer operation time than traditional incision surgery. The surgeon needs to make a choice according to clinical situation of patient and their own surgical inclination.

De-icing performance evolution with increasing hydrophobicity by regulating surface topography.

It is of great significance to grasp the role of surface topography in de-icing, which however remains unclear yet. Herein, four textured surfaces are developed by regulating surface topography while keeping surface chemistry and material constituents same. Specifically, nano-textures are maintained and micro-textures are gradually enlarged. The resultant ice adhesion strength is proportional to a topography parameter, i.e. areal fraction of the micro-textures, owing to the localized bonding strengthening, which is verified by ice detachment simulation using finite element method. Moreover, the decisive topography parameter is demonstrated to be determined by the interfacial strength distribution between ice and test surface. Such parameters vary from paper to paper due to different interfacial strength distributions corresponding to respective situations. Furthermore, since hydrophobic and de-icing performance may rely on different topography parameters, there is no certain relationship between hydrophobicity and de-icing.

The role of surface topography in de-icing is verified to be determined by the interfacial strength distribution between ice and surface experimentally and numerically, unveiling the relationship between hydrophobicity and de-icing.

ETV2 induces endothelial, but not hematopoietic, lineage specification in birds.

Cardiovascular system develops from the lateral plate mesoderm. Its three primary cell lineages (hematopoietic, endothelial, and muscular) are specified by the sequential actions of conserved transcriptional factors. ETV2, a master regulator of mammalian hemangioblast development, however, is absent in the chicken genome and acts downstream of NPAS4L in zebrafish. Here, we investigated the epistatic relationship between NPAS4L and ETV2 in avian hemangioblast development. We showed that ETV2 is deleted in all 363 avian genomes analyzed. Mouse ETV2 induced LMO2, but not NPAS4L or SCL, expression in chicken mesoderm. Squamate (lizards, geckos, and snakes) genomes contain both NPAS4L and ETV2 In Madagascar ground gecko, both genes were expressed in developing hemangioblasts. Gecko ETV2 induced only LMO2 in chicken mesoderm. We propose that both NPAS4L and ETV2 were present in ancestral amniote, with ETV2 acting downstream of NPAS4L in endothelial lineage specification. ETV2 may have acted as a pioneer factor by promoting chromatin accessibility of endothelial-specific genes and, in parallel with NPAS4L loss in ancestral mammals, has gained similar function in regulating blood-specific genes.

Effects of physical training on depression and related quality of life in pre-frail and frail older adults: a systematic review and meta-analysis.

OBJECTIVES: To investigate the effects of physical training on depression and related quality of life in pre-frail and frail individuals. DESIGN: A systematic review and meta-analysis. PARTICIPANTS: Pre-frail and frail older adults. METHODS: Five electronic databases, including PubMed, Cochrane, Medline, CINAHL, and Wiley were searched through December 2023. Randomized controlled trials (RCT) comparing physical training with usual care, health education, or light-intensity exercise were included. Outcomes included depression and depression-related quality of life. The quality of the included studies was assessed using Physiotherapy Evidence Database (PEDro) score, and the Cochrane Risk of Bias Tool was used to assess the risk of bias. Meta-analysis was performed using the RevMan5.4. The certainty of the evidence was evaluated by The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. RESULTS: Ten articles with 589 participants met the inclusion criteria and were included. The pooled analysis indicated that depression (SMD = -0.55, 95%CI = -0.92, -0.17, p = 0.004) and mental health status in life (SMD = 1.05, 95%CI = 0.59, 1.50, p < 0.00001) improved significantly in the experimental group. The results of subgroup analysis revealed that the beneficial effects of physical training were significant only in frail older adults but not in pre-frail older adults. CONCLUSION: This meta-analysis showed that the positive effects of physical training on depression and related quality of life were evident for people with frailty. However, no positive results were observed in pre-frail older adults, indicating the need for further investigation in this subgroup.

PixRevive: Latent Feature Diffusion Model for Compressed Video Quality Enhancement.

In recent years, the rapid prevalence of high-definition video in Internet of Things (IoT) systems has been directly facilitated by advances in imaging sensor technology. To adapt to limited uplink bandwidth, most media platforms opt to compress videos to bitrate streams for transmission. However, this compression often leads to significant texture loss and artifacts, which severely degrade the Quality of Experience (QoE). We propose a latent feature diffusion model (LFDM) for compressed video quality enhancement, which comprises a compact edge latent feature prior network (ELPN) and a conditional noise prediction network (CNPN). Specifically, we first pre-train ELPNet to construct a latent feature space that captures rich detail information for representing sharpness latent variables. Second, we incorporate these latent variables into the prediction network to iteratively guide the generation direction, thus resolving the problem that the direct application of diffusion models to temporal prediction disrupts inter-frame dependencies, thereby completing the modeling of temporal correlations. Lastly, we innovatively develop a Grouped Domain Fusion module that effectively addresses the challenges of diffusion distortion caused by naive cross-domain information fusion. Comparative experiments on the MFQEv2 benchmark validate our algorithm's superior performance in terms of both objective and subjective metrics. By integrating with codecs and image sensors, our method can provide higher video quality.

Isolation and characterizations of multidrug-resistant human cancer cells by a biodegradable nano-sensor.

Multidrug resistance (MDR) remains a significant challenge in cancer therapy, with inherent and acquired resistance distinct. While conventional drug selection processes enable the isolation of cancer cells with acquired multidrug resistance, identifying cancer cells with inherent drug resistance remains challenging. Herein, we proposed a molecular beacon (MB)-based strategy to identify and isolate the inherent MDR cancer cells. A lipid/PLGA core-shell nanoparticulate system (DNCP) was designed to deliver MB for intracellular MDR1 mRNA imaging. DNCP-MB - possess a surface potential of -8 mV and a size of 150 nm - demonstrated effective delivery of MB, remarkable selectivity towards the selected intracellular mRNA targets, and low cytotoxicity. Following DNCP transfection, fluorescence-activated cell sorting (FACS) was employed to differentiate MCF-7 cells into two distinct sub-populations: the Top 10 cells with a high level of MDR gene expression and the Bottom 10 cells with a low level of MDR gene expression, which represent inherent drug-resistant and non-drug-resistant cells, respectively. Intriguingly, we observed a positive correlation between elevated MDR1 mRNA expression and increased migration, enhanced proliferation rate, and tighter spheroid formation. Moreover, we conducted RNA sequencing analysis on the Top 10, Bottom 10, and MCF-7/ADR cells. The findings revealed a notable disparity in the gene ontology enrichment analysis of differentially expressed genes between the Top 10 and Bottom 10 cells when compared to the Bottom 10 and MCF-7/ADR cells. This novel approach provides a promising avenue for isolating inherent drug-resistant cells and holds significant potential in unraveling the mechanisms underlying inherent drug resistance.

Tungsten and Boron Codoping toward High Ionic Conductivity and Stable Sodium Solid Electrolyte for All-Solid-State Sodium Batteries.

Sodium solid electrolytes with high ionic conductivity and good interfacial stability with sodium metal are crucial to realize high-performance all-solid-state sodium batteries. In this work, W and B-codoped Na3Sb1-xWxS4-xBx solid electrolytes are prepared by melt-quenching with further annealing. The synthesized Na3Sb0.95W0.05S3.95B0.05 solid electrolyte possesses a high ionic conductivity of 11.06 mS cm-1 under 25 °C and shows significantly improved interface compatibility with metal sodium. Specifically, Na/Na3Sb0.95W0.05S3.95B0.05/Na symmetric cell can stable cycle for 500 h under a current density of 0.05 mA cm-2. In addition, the resultant TiS2/Na3Sb0.95W0.05S3.95B0.05/Na battery exhibits an initial charge capacity of 164.1 mAh g-1 at 0.1 C with a capacity retention of 76.4% after 100 cycles. This work provides a new strategy to realize the high ionic conductivity of sodium solid electrolytes with improved interfacial stability with sodium anode.

An intentional approach to managing bias in general purpose embedding models.

Advances in machine learning for health care have brought concerns about bias from the research community; specifically, the introduction, perpetuation, or exacerbation of care disparities. Reinforcing these concerns is the finding that medical images often reveal signals about sensitive attributes in ways that are hard to pinpoint by both algorithms and people. This finding raises a question about how to best design general purpose pretrained embeddings (GPPEs, defined as embeddings meant to support a broad array of use cases) for building downstream models that are free from particular types of bias. The downstream model should be carefully evaluated for bias, and audited and improved as appropriate. However, in our view, well intentioned attempts to prevent the upstream components-GPPEs-from learning sensitive attributes can have unintended consequences on the downstream models. Despite producing a veneer of technical neutrality, the resultant end-to-end system might still be biased or poorly performing. We present reasons, by building on previously published data, to support the reasoning that GPPEs should ideally contain as much information as the original data contain, and highlight the perils of trying to remove sensitive attributes from a GPPE. We also emphasise that downstream prediction models trained for specific tasks and settings, whether developed using GPPEs or not, should be carefully designed and evaluated to avoid bias that makes models vulnerable to issues such as distributional shift. These evaluations should be done by a diverse team, including social scientists, on a diverse cohort representing the full breadth of the patient population for which the final model is intended.

Developing a Machine Learning Algorithm to Predict the Probability of Medical Staff Work Mode Using Human-Smartphone Interaction Patterns: Algorithm Development and Validation Study.

BACKGROUND: Traditional methods for investigating work hours rely on an employee's physical presence at the worksite. However, accurately identifying break times at the worksite and distinguishing remote work outside the worksite poses challenges in work hour estimations. Machine learning has the potential to differentiate between human-smartphone interactions at work and off work. OBJECTIVE: In this study, we aimed to develop a novel approach called "probability in work mode," which leverages human-smartphone interaction patterns and corresponding GPS location data to estimate work hours. METHODS: To capture human-smartphone interactions and GPS locations, we used the "Staff Hours" app, developed by our team, to passively and continuously record participants' screen events, including timestamps of notifications, screen on or off occurrences, and app usage patterns. Extreme gradient boosted trees were used to transform these interaction patterns into a probability, while 1-dimensional convolutional neural networks generated successive probabilities based on previous sequence probabilities. The resulting probability in work mode allowed us to discern periods of office work, off-work, breaks at the worksite, and remote work. RESULTS: Our study included 121 participants, contributing to a total of 5503 person-days (person-days represent the cumulative number of days across all participants on which data were collected and analyzed). The developed machine learning model exhibited an average prediction performance, measured by the area under the receiver operating characteristic curve, of 0.915 (SD 0.064). Work hours estimated using the probability in work mode (higher than 0.5) were significantly longer (mean 11.2, SD 2.8 hours per day) than the GPS-defined counterparts (mean 10.2, SD 2.3 hours per day; P<.001). This discrepancy was attributed to the higher remote work time of 111.6 (SD 106.4) minutes compared to the break time of 54.7 (SD 74.5) minutes. CONCLUSIONS: Our novel approach, the probability in work mode, harnessed human-smartphone interaction patterns and machine learning models to enhance the precision and accuracy of work hour investigation. By integrating human-smartphone interactions and GPS data, our method provides valuable insights into work patterns, including remote work and breaks, offering potential applications in optimizing work productivity and well-being.

Evaluating the toxic mechanism of 1,2-diacetylbenzene in neural cells/tissues: The favorable impact of silibinin.

1,2-diacetylbenzene (1,2-DAB) is a neurotoxic component of aromatic solvents commonly used in industrial applications that induces neuropathological changes in animals. This study unraveled the toxic impact of 1,2-DAB in nerve tissues, explant cultures, and neuron-glial cultures, and explored whether herbal products can mitigate its toxicity. The effects of DAB on axonal transport were studied in retinal explant cultures grown in a micro-patterned dish. The mitochondrial movement in the axons was captured using time-lapse video recordings. The results showed that 1,2-DAB, but not 1,3-DAB inhibited axonal outgrowth and mitochondrial movement in a dose-dependent manner. The toxicity of 1,2-DAB was further studied in spinal cord tissues and cultures. 1,2-DAB selectively induced modifications of microtubules and neurofilaments in spinal cord tissues. 1,2-DAB also potently induced cell damage in both neuronal and glial cultures. Further, 1,2-DAB-induced cellular ATP depletion precedes cell damage in glial cells. Interestingly, treatment with the herbal products silibinin or silymarin effectively mitigated 1,2-DAB-induced toxicity in spinal cord tissues and neuronal/glial cultures. Collectively, the molecular toxicity of 1,2-DAB in neural tissues involves protein modification, ATP depletion, and axonal transport defects, leading to cell death. Silibinin and silymarin show promising neuroprotective effects against 2-DAB-induced toxicity.

Robotic partial nephrectomy for renal tumor: The pentafecta outcomes of a single surgeon experience.

PURPOSE: This study investigated the oncological and functional surgical outcomes for patients with renal tumor who underwent robot-assisted partial nephrectomy (PN) by a single surgeon in Taiwan from 2006 to 2019. METHODS: This retrospective study assessed patients who underwent robot-assisted PN for renal tumor. Patient data were analyzed for age, sex, body mass index, operative time and total ischemic time, surgical margin (positive/negative), and surgical complications. To evaluate functional and oncological outcomes, achievement of trifecta, and pentafecta criteria was used. Trifecta criteria were defined as a negative surgical margin, no postoperative complications, warm ischemia time <25 min. Pentafecta criteria were the trifecta criteria, >90% preservation of estimated glomerular filtration rate (eGFR) preservation, and no stage progression of chronic kidney disease at 1-year follow-up. RESULTS: Of 101 patients who received robot-assisted PN, the most common type of renal tumor was clear cell renal cell carcinoma (RCC) (38%), followed by angiomyolipoma (26%). Patient characteristics were mean age 54.59 ± 13.8 years; mean RENAL Nephrometry score 6.63 ± 2.16; mean operative time 102.34 ± 50.06 min; and warm ischemia time 20.01 ± 14.12 min. The mean eGFR was 104.43 ± 31.73 mL/min/1.73 m2 preoperatively and 89.39 ± 32.3 mL/min/1.73 m2 postoperatively. Pathologic evaluation showed malignant tumors in 57 patients, among whom achievement of trifecta criteria occurred for 39 (68.42%) and pentafecta criteria for 18 (31.57%). Operation time was the only predictor for pentafecta achievement. CONCLUSION: Robotic PN is a safe and effective approach for patients with renal tumor that can preserve most renal function and achieve oncological control. Pentafecta criteria can be used to more clearly define the surgical outcome of RAPN.