Impact of neoadjuvant chemotherapy on short-term outcomes after simple and complex minimally invasive minor hepatectomy for colorectal liver metastases: A propensity-score matched and coarsened exact matched study.

BACKGROUND: In the last three decades, minimally invasive liver resection has been replacing conventional open approach in liver surgery. More recently, developments in neoadjuvant chemotherapy have led to increased multidisciplinary management of colorectal liver metastases with both medical and surgical treatment modalities. However, the impact of neoadjuvant chemotherapy on the surgical outcomes of minimally invasive liver resections remains poorly understood. METHODS: A multicenter, international, database of 4998 minimally invasive minor hepatectomy for colorectal liver metastases was used to compare surgical outcomes in patients who received neoadjuvant chemotherapy with surgery alone. To correct for baseline imbalance, propensity score matching, coarsened exact matching and inverse probability treatment weighting were performed. RESULTS: 2546 patients met the inclusion criteria. After propensity score matching there were 759 patients in both groups and 383 patients in both groups after coarsened exact matching. Baseline characteristics were equal after both matching strategies. Neoadjuvant chemotherapy was not associated with statistically significant worse surgical outcomes of minimally invasive minor hepatectomy. CONCLUSION: Neoadjuvant chemotherapy had no statistically significant impact on short-term surgical outcomes after simple and complex minimally invasive minor hepatectomy for colorectal liver metastases.

PDCD4 restricts PRRSV replication in an eIF4A-dependent manner and is antagonized by the viral nonstructural protein 9.

As obligate parasites, viruses have evolved multiple strategies to evade the host immune defense. Manipulation of the host proteasome system to degrade specific detrimental factors is a common viral countermeasure. To identify host proteins targeted for proteasomal degradation by porcine reproductive and respiratory syndrome virus (PRRSV), we conducted a quantitative proteomics screen of PRRSV-infected Marc-145 cells under the treatment with proteasome inhibitor MG132. The data revealed that the expression levels of programmed cell death 4 (PDCD4) were strongly downregulated by PRRSV and significantly rescued by MG132. Further investigation confirmed that PRRSV infection induced the translocation of PDCD4 from the nucleus to the cytoplasm, and the viral nonstructural protein 9 (Nsp9) promoted PDCD4 proteasomal degradation in the cytoplasm by activating the Akt-mTOR-S6K1 pathway. The C-terminal domain of Nsp9 was responsible for PDCD4 degradation. As for the role of PDCD4 during PRRSV infection, we demonstrated that PDCD4 knockdown favored viral replication, while its overexpression significantly attenuated replication, suggesting that PDCD4 acts as a restriction factor for PRRSV. Mechanistically, we discovered eukaryotic translation initiation factor 4A (eIF4A) was required for PRRSV. PDCD4 interacted with eIF4A through four sites (E249, D253, D414, and D418) within its two MA3 domains, disrupting eIF4A-mediated translation initiation in the 5'-untranslated region of PRRSV, thereby inhibiting PRRSV infection. Together, our study reveals the antiviral function of PDCD4 and the viral strategy to antagonize PDCD4. These results will contribute to our understanding of the immune evasion strategies employed by PRRSV and offer valuable insights for developing new antiviral targets.IMPORTANCEPorcine reproductive and respiratory syndrome virus (PRRSV) infection results in major economic losses in the global swine industry and is difficult to control effectively. Here, using a quantitative proteomics screen, we identified programmed cell death 4 (PDCD4) as a host protein targeted for proteasomal degradation by PRRSV. We demonstrated that PDCD4 restricts PRRSV replication by interacting with eukaryotic translation initiation factor 4A, which is required for translation initiation in the viral 5'-untranslated region. Additionally, four sites within two MA3 domains of PDCD4 are identified to be responsible for its antiviral function. Conversely, PRRSV nonstructural protein 9 promotes PDCD4 proteasomal degradation in the cytoplasm by activating the Akt-mTOR-S6K1 pathway, thus weakening the anti-PRRSV function. Our work unveils PDCD4 as a previously unrecognized host restriction factor for PRRSV and reveals that PRRSV develops countermeasures to overcome PDCD4. This will provide new insights into virus-host interactions and the development of new antiviral targets.

Sishen Wan enhances intestinal barrier function via regulating endoplasmic reticulum stress to improve mice with diarrheal irritable bowel syndrome.

BACKGROUND: Diarrheal irritable bowel syndrome (IBS-D), characterized primarily by the presence of diarrhea and abdominal pain, is a clinical manifestation resulting from a multitude of causative factors. Furthermore, Sishen Wan (SSW) has demonstrated efficacy in treating IBS-D. Nevertheless, its mechanism of action remains unclear. METHODS: A model of IBS-D was induced by a diet containing 45 % lactose and chronic unpredictable mild stress. Additionally, the impact of SSW was assessed by measuring body weight, visceral sensitivity, defecation parameters, intestinal transport velocity, intestinal neurotransmitter levels, immunohistochemistry, and transmission electron microscopy analysis. Immunofluorescent staining was used to detect the expression of Mucin 2 (MUC2) and Occludin in the colon. Western blotting was used to detect changes in proteins related to tight junction (TJ), autophagy, and endoplasmic reticulum (ER) stress in the colon. Finally, 16S rRNA amplicon sequencing was used to monitor the alteration of gut microbiota after SSW treatment. RESULTS: Our study revealed that SSW administration resulted in reduced visceral sensitivity, improved defecation parameters, decreased intestinal transport velocity, and reduced intestinal permeability in IBS-D mice. Furthermore, SSW promotes the secretion of colonic mucus by enhancing autophagy and inhibiting ER stress. SSW treatment caused remodeling of the gut microbiome by increasing the abundance of Blautia, Muribaculum and Ruminococcus torques group. CONCLUSION: SSW can improve intestinal barrier function by promoting autophagy and inhibiting ER stress, thus exerting a therapeutic effect on IBS-D.

Vision matters for shape representation: Evidence from sculpturing and drawing in the blind.

Shape is a property that could be perceived by vision and touch, and is classically considered to be supramodal. While there is mounting evidence for the shared cognitive and neural representation space between visual and tactile shape, previous research tended to rely on dissimilarity structures between objects and had not examined the detailed properties of shape representation in the absence of vision. To address this gap, we conducted three explicit object shape knowledge production experiments with congenitally blind and sighted participants, who were asked to produce verbal features, 3D clay models, and 2D drawings of familiar objects with varying levels of tactile exposure, including tools, large nonmanipulable objects, and animals. We found that the absence of visual experience (i.e., in the blind group) led to stronger differences in animals than in tools and large objects, suggesting that direct tactile experience of objects is essential for shape representation when vision is unavailable. For tools with rich tactile/manipulation experiences, the blind produced overall good shapes comparable to the sighted, yet also showed intriguing differences. The blind group had more variations and a systematic bias in the geometric property of tools (making them stubbier than the sighted), indicating that visual experience contributes to aligning internal representations and calibrating overall object configurations, at least for tools. Taken together, the object shape representation reflects the intricate orchestration of vision, touch and language.

Regulating charge transfer for enhanced PAA activation over sulfur-doped magnetic CoFe2O4: A novel strategy for simultaneous micropollutants degradation and bacteria inactivation.

Micropollutants and bacteria are prevalent pollutants in wastewater, posing significant risks to ecosystems and human health. As peracetic acid (PAA) is being increasingly used as a disinfectant, activation of PAA by low-cost and high-performance activators is a promising strategy for wastewater treatment. In this study, the sulfur-doped magnetic CoFe2O4 (SCFO) is successfully developed for efficient PAA activation to simultaneously decontaminate and disinfect wastewater. PAA/SCFO-0.3 exhibits exceptional performance, degrading 100 % of 8 µM sulfamethoxazole (SMX) with a first-pseudo reaction rate of 1.275 min-1, and achieving 5.3-log inactivation of Escherichia coli (E. coli) within 3 min at a PAA dosage of 0.2 mM and catalyst dosage of 0.025 g/L (initial pH 6.5). Scavenging experiments and electron paramagnetic resonance (EPR) analysis identify CH3C(O)O• and CH3C(O)OO• as the dominant reactive species for SMX degradation. The sulfur species in SCFO-0.3 facilitate Co2+ regeneration and regulate charge transfer, promoting PAA activation for SMX degradation. Moreover, the PAA/SCFO-0.3 system demonstrates operational feasibility over a broad range of water matrices and has excellent stability and reusability (maintaining 93 % removal of SMX after 5 cycles), demonstrating its potential for industrial applications. This study provides insights into enhancing PAA activation through sulfur doping in transition metal catalysts and highlights the practical applicability of the PAA/SCFO-0.3 system as an advanced alternative to conventional disinfection for simultaneous decontamination and disinfection in wastewater.

Mid-infrared single-photon upconversion spectroscopy enabled by nonlocal wavelength-to-time mapping.

Ultrasensitive spectroscopy is an essential component in mid-infrared (MIR) technology. However, the drawbacks of MIR detectors pose challenges to robust MIR spectroscopy at the single-photon level. We propose an MIR single-photon frequency upconversion spectroscopy nonlocally mapping the MIR information to the time domain. Broadband MIR photons from spontaneous parametric downconversion are frequency-upconverted to the near-infrared band with quantum correlation preservation. Via the group delay of fiber, the MIR spectral information within a 1.18-micrometer bandwidth of 2.76 to 3.94 micrometers is then successfully projected to arrival times of correlated photon pairs. Under the conditions of 6.4 × 106 photons per second illumination, the transmission spectra of polymers with single-photon sensitivity are demonstrated using single-pixel detectors. The developed approach circumvents scanning and frequency selection instability, which stands out for its inherent compatibility for evolving environments and scalability for various wavelengths. Because of its high sensitivity and robustness, characterization of biochemical samples and weak measurement of quantum systems are possible to foresee.

Implantable Collamer Lens Procedure Planning: A Review of Global Approaches.

More than 2 million implantable collamer lenses (ICLs) have been implanted worldwide. With a central port to improve aqueous flow through the ICL, the latest iteration of this phakic intraocular lens (pIOL) has been shown to have stable outcomes with very low rates of adverse events. However, correct planning and ICL size selection continue to be important to achieve an optimal vault. Shallow or excessive vaults are not complications in and of themselves but may increase the risk of complications. Historically, surgeons have relied on measurements of anterior chamber depth (ACD) and manual, caliper-measured white-to-white (WTW) distance to select the ICL size. New diagnostic and imaging technologies such as optical coherence tomography (OCT) and ultrasound biomicroscopy (UBM) provide additional opportunities for visualization and measurement of the intraocular dimensions involved in phakic intraocular lens implantation, including sulcus-to-sulcus (STS) and angle-to-angle (ATA) diameters. This paper reviews various approaches to ICL planning and sizing that have been published in the peer-reviewed literature, all of which produce acceptable results for predicting vault and size selection. Surgeons may also want to identify a methodology for patient evaluation and ICL size selection that best aligns with their personal preferences, diagnostic technology, and familiarity with analytical optimization tools.

Phakic intraocular lenses (pIOLs) are one method for correcting nearsightedness, with or without astigmatism. This category of refractive surgery has been growing rapidly in the US and around the world. Implantation of the implantable collamer lens (ICL), one type of pIOL, is safe and effective, with stable outcomes and low adverse event rates. When complications do occur, they are typically associated with an inappropriate vault, or distance between the implant and the natural lens. Preoperative planning and accurate ICL sizing are required to achieve an optimal vault and varies, depending on the diagnostic technology available to the surgeon. This paper reviews the current approaches to ICL planning and sizing in order to provide guidance to surgeons implanting this pIOL.

Fluorescent Paper Based on CQDs/Rhodamine B: A Ratio and Sensitive Detection Platform for On-Site Fe3+ Sensing.

Fluorescent sensors with single reading are generally subject to unpredictable disturbs from environmental and artificial factors. In order to overcome this barrier of detection reliability, a paper-based optical sensor with proportional fluorescence was established and further combined with a smartphone for visual, on-site and quantitative detection of Fe3+, which affects the color, smell and taste of water, and endangers the health of plants and animals. The ratio fluorescent probe was fabricated by rhodamine B and carbon quantum dots derived from xylan. The red fluorescence of rhodamine B was inert to Fe3+, which was referred to as background. And blue emitting carbon quantum dots functioned as signal report units, which would be quenched by Fe3+ and make the fluorescence of the ratio probe change from purple to red. The quantitative detection of Fe3+ was conducted by investigating the RGB value of fluorescent images with a smartphone. With the increase of Fe3+ concentration, the R/B (red/blue) value of the fluorescent paper gradually increased. The linear detection range was 10-180 µM, and the limit of detection was 198.2 nM. The application of ratio fluorescent paper with a smartphone provides a facile method for the rapid detection of ions.

Intermittent fasting and health outcomes: an umbrella review of systematic reviews and meta-analyses of randomised controlled trials.

Background: Benefits of Intermittent fasting (IF) on health-related outcomes have been found in a range of randomised controlled trials (RCTs). Our umbrella review aimed to systematically analyze and synthesize the available causal evidence on IF and its impact on specific health-related outcomes while evaluating its evidence quality. Methods: We comprehensively searched the PubMed, Embase, Web of Science, and Cochrane databases (from inception up to 8 January 2024) to identify related systematic reviews and meta-analyses of RCTs investigating the association between IF and human health outcomes. We recalculated the effect sizes for each meta-analysis as mean difference (MD) or standardized mean difference (SMD) with corresponding 95% confidence intervals (CIs). Subgroup analyses were performed for populations based on three specific status: diabetes, overweight or obesity, and metabolic syndrome. The quality of systematic reviews was evaluated using A Measurement Tool to Assess Systematic Reviews (AMSTAR), and the certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system. This study is registered with PROSPERO (CRD42023382004). Findings: A total of 351 associations from 23 meta-analyses with 34 health outcomes were included in the study. A wide range of outcomes were investigated, including anthropometric measures (n = 155), lipid profiles (n = 83), glycemic profiles (n = 57), circulatory system index (n = 41), appetite (n = 9), and others (n = 6). Twenty-one (91%) meta-analyses with 346 associations were rated as high confidence according to the AMSTAR criteria. The summary effects estimates were significant at p < 0.05 in 103 associations, of which 10 (10%) were supported by high certainty of evidence according to GRADE. Specifically, compared with non-intervention diet in adults with overweight or obesity, IF reduced waist circumference (WC) (MD = -1.02 cm; 95% CI: -1.99 to -0.06; p = 0.038), fat mass (MD = -0.72 kg; 95% CI: -1.32 to -0.12; p = 0.019), fasting insulin (SMD = -0.21; 95% CI: -0.40 to -0.02; p = 0.030), low-density lipoprotein cholesterol (LDL-C) (SMD = -0.20; 95% CI: -0.38 to -0.02; p = 0.027), total cholesterol (TC) (SMD = -0.29; 95% CI: -0.48 to -0.10; p = 0.003), and triacylglycerols (TG) (SMD = -0.23; 95% CI: -0.39 to -0.06; p = 0.007), but increased fat free mass (FFM) (MD = 0.98 kg; 95% CI: 0.18-1.78; p = 0.016). Of note, compared with the non-intervention diet, modified alternate-day fasting (MADF) reduced fat mass (MD = -0.70 kg; 95% CI: -1.38 to -0.02; p = 0.044). In people with overweight or obesity, and type 2 diabetes, IF increases high-density lipoprotein cholesterol (HDL-C) levels compared to continuous energy restriction (CER) (MD = 0.03 mmol/L; 95% CI: 0.01-0.05; p = 0.010). However, IF was less effective at reducing systolic blood pressure (SBP) than a CER diet in adults with overweight or obesity (SMD = 0.21; 95% CI: 0.05-0.36; p = 0.008). Interpretation: Our findings suggest that IF may have beneficial effects on a range of health outcomes for adults with overweight or obesity, compared to CER or non-intervention diet. Specifically, IF may decreased WC, fat mass, LDL-C, TG, TC, fasting insulin, and SBP, while increasing HDL-C and FFM. Notably, it is worth noting that the SBP lowering effect of IF appears to be weaker than that of CER. Funding: This work was supported by the National Key Research and Development Program of China (Q-JW), the Natural Science Foundation of China (Q-JW and T-TG), Outstanding Scientific Fund of Shengjing Hospital of China Medical University (Q-JW), and 345 Talent Project of Shengjing Hospital of China Medical University (T-TG).

Unveiling Shared Immune Responses in Porcine Alveolar Macrophages during ASFV and PRRSV Infection Using Single-Cell RNA-seq.

African swine fever virus (ASFV) and porcine reproductive and respiratory syndrome virus (PRRSV) infections lead to severe respiratory diseases in pigs, resulting in significant economic losses for the global swine industry. While numerous studies have focused on specific gene functions or pathway activities during infection, an investigation of shared immune responses in porcine alveolar macrophages (PAMs) after ASFV and PRRSV infections was lacking. In this study, we conducted a comparison using two single-cell transcriptomic datasets generated from PAMs under ASFV and PRRSV infection. Pattern recognition receptors (PRRs) RIG-I (DDX58), MDA5 (IFIH1), and LGP2 (DHX58) were identified as particularly recognizing ASFV and PRRSV, triggering cellular defense responses, including the upregulation of four cytokine families (CCL, CXCL, IL, and TNF) and the induction of pyroptosis. Through weighted gene co-expression network analysis and protein-protein interaction analysis, we identified thirteen gene and protein interactions shared by both scRNA-seq analyses, suggesting the ability to inhibit both ASFV and PRRSV viral replication. We discovered six proteins (PARP12, PARP14, HERC5, DDX60, RSAD2, and MNDA) in PAMs as inhibitors of ASFV and PRRSV replication. Collectively, our findings showed detailed characterizations of the immune responses in PAMs during ASFV and PRRSV infections, which may facilitate the treatments of these viral diseases.

Tracing the path of disruption: 13C isotope applications in traumatic brain injury-induced metabolic dysfunction.

Cerebral metabolic dysfunction is a critical pathological hallmark observed in the aftermath of traumatic brain injury (TBI), as extensively documented in clinical investigations and experimental models. An in-depth understanding of the bioenergetic disturbances that occur following TBI promises to reveal novel therapeutic targets, paving the way for the timely development of interventions to improve patient outcomes. The 13C isotope tracing technique represents a robust methodological advance, harnessing biochemical quantification to delineate the metabolic trajectories of isotopically labeled substrates. This nuanced approach enables real-time mapping of metabolic fluxes, providing a window into the cellular energetic state and elucidating the perturbations in key metabolic circuits. By applying this sophisticated tool, researchers can dissect the complexities of bioenergetic networks within the central nervous system, offering insights into the metabolic derangements specific to TBI pathology. Embraced by both animal studies and clinical research, 13C isotope tracing has bolstered our understanding of TBI-induced metabolic dysregulation. This review synthesizes current applications of isotope tracing and its transformative potential in evaluating and addressing the metabolic sequelae of TBI.

Role and mechanism of miRNA in cardiac microvascular endothelial cells in cardiovascular diseases.

The occurrence and development of myocardial dysfunction are associated with damage in the cardiac microvascular endothelial cells (CMECs), which can regulate nutrient exchange and oxy-gen-carbon cycling to protect cardiomyocytes. Interventions targeting microRNAs (miRNAs) can effectively mitigate CMEC injury and thus improve cardiovascular diseases. MiRNAs are a class of noncoding single-strand RNA molecules typically 21-23 nucleotides in length that are encoded by endogenous genes. They are critical regulators of organism development, cell differentiation, metabolism, and apoptosis. Current clinical trials on miRNA drugs indicate that patient-specific miRNA levels are now being used as one of the criteria for predicting heart disease. However, the cellular process of various miRNAs in CMECs in cardiovascular diseases has not been fully elucidated. These mechanisms are a field that immediately requires further investigation. Accordingly, this review summarizes the roles and mechanisms of various miRNAs in CMECs in cardiovascular disease and includes the process of CMEC crosstalk between miRNAs and other cell types in the heart. Our study serves as a theoretical basis for the formal introduction of miRNA use into the treatment of cardiovascular diseases in the future.

Establishment and application of a screening method for α-glucosidase inhibitors based on dual sensing and affinity chromatography.

α-Glucosidase plays a direct role in the metabolic pathways of starch and glycogen, any dysfunction in its activity could result in metabolic disease. Concurrently, this enzyme serves as a target for diverse drugs and inhibitors, contributing to the regulation of glucose metabolism in the human body. Here, an integrated analytical method was established to screen inhibitors of α-glucosidase. This step-by-step screening model was accomplished through the biosensing and affinity chromatography techniques. The newly proposed sensing program had a good linear relationship within the enzyme activity range of 0.25 U mL-1 to 1.25 U mL-1, which can quickly identify active ingredients in complex samples. Then the potential active ingredients can be captured, separated, and identified by an affinity chromatography model. The combination of the two parts was achieved by an immobilized enzyme technology and a microdevice for reaction, and the combination not only ensured efficiency and accuracy for inhibitor screening but also eliminated the occurrence of false positive results in the past. The emodin, with a notable inhibitory effect on α-glucosidase, was successfully screened from five traditional Chinese medicines using this method. The molecular docking results also demonstrated that emodin was well embedded into the active pocket of α-glucosidase. In summary, the strategy provided an efficient method for developing new enzyme inhibitors from natural products.

Immune cells: potential carriers or agents for drug delivery to the central nervous system.

Drug delivery systems (DDS) have recently emerged as a promising approach for the unique advantages of drug protection and targeted delivery. However, the access of nanoparticles/drugs to the central nervous system (CNS) remains a challenge mainly due to the obstruction from brain barriers. Immune cells infiltrating the CNS in the pathological state have inspired the development of strategies for CNS foundation drug delivery. Herein, we outline the three major brain barriers in the CNS and the mechanisms by which immune cells migrate across the blood-brain barrier. We subsequently review biomimetic strategies utilizing immune cell-based nanoparticles for the delivery of nanoparticles/drugs to the CNS, as well as recent progress in rationally engineering immune cell-based DDS for CNS diseases. Finally, we discuss the challenges and opportunities of immune cell-based DDS in CNS diseases to promote their clinical development.

Facile preparation of fatigue-resistant Mxene-reinforced chitosan cryogel for accelerated hemostasis and wound healing.

The development of highly effective chitosan-based hemostatic materials that can be utilized for deep wound hemostasis remains a considerable challenge. In this study, a hemostatic antibacterial chitosan/N-hydroxyethyl acrylamide (NHEMAA)/Ti3C2Tx (CSNT) composite cryogel was facilely prepared through the physical interactions between the three components and the spontaneous condensation of NHEMAA. Because of the formation of strong crosslinked network, the CSNT cryogel showed a developed pore structure (~ 99.07 %) and superfast water/blood-triggered shape recovery, enabling it to fill the wound after contacting the blood. Its capillary effect, amino groups, negative charges, and affinity with lipid collectively induced rapid hemostasis, which was confirmed by in vitro and in vivo analysis. In addition, CSNT cryogel showed excellent photothermal antibacterial activities, high biosafety, and in vivo wound healing ability. Furthermore, the presence of chitosan effectively prevented the oxidation of MXene, thus enabling the long-term storage of the MXene-reinforced cryogel. Thus, our hemostatic cryogel demonstrates promising potential for clinical application and commercialization, as it combines high resilience, rapid hemostasis, efficient sterilization, long-term storage, and easy mass production.

Neutrophil profiling illuminates anti-tumor antigen-presenting potency.

Neutrophils, the most abundant and efficient defenders against pathogens, exert opposing functions across cancer types. However, given their short half-life, it remains challenging to explore how neutrophils adopt specific fates in cancer. Here, we generated and integrated single-cell neutrophil transcriptomes from 17 cancer types (225 samples from 143 patients). Neutrophils exhibited extraordinary complexity, with 10 distinct states including inflammation, angiogenesis, and antigen presentation. Notably, the antigen-presenting program was associated with favorable survival in most cancers and could be evoked by leucine metabolism and subsequent histone H3K27ac modification. These neutrophils could further invoke both (neo)antigen-specific and antigen-independent T cell responses. Neutrophil delivery or a leucine diet fine-tuned the immune balance to enhance anti-PD-1 therapy in various murine cancer models. In summary, these data not only indicate the neutrophil divergence across cancers but also suggest therapeutic opportunities such as antigen-presenting neutrophil delivery.

Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer.

Purpose: To develop deep-learning radiomics model for predicting biochemical recurrence (BCR) of advanced prostate cancer (PCa) based on pretreatment apparent diffusion coefficient (ADC) maps. Methods: Data were collected retrospectively from 131 patients diagnosed with advanced PCa, randomly divided into training (n = 93) and test (n = 38) datasets. Pre-treatment ADC images were segmented using a pre-trained artificial intelligence (AI) model to identify suspicious PCa areas. Three models were constructed, including a clinical model, a conventional radiomics model and a deep-radiomics model. The receiver operating characteristic (ROC), precision-recall (PR) curve and decision curve analysis (DCA) were used to assess predictive performance in test dataset. The net reclassification index (NRI) and integrated discrimination improvement (IDI) were employed to compare the performance enhancement of the deep-radiomics model in relation to the other two models. Results: The deep-radiomics model exhibited a significantly higher area under the curve (AUC) of ROC than the other two (P = 0.033, 0.026), as well as PR curve (AUC difference 0.420, 0.432). The DCA curve demonstrated superior performance for the deep-radiomics model across all risk thresholds than the other two. Taking the clinical model as reference, the NRI and IDI was 0.508 and 0.679 for the deep-radiomics model with significant difference. Compared with the conventional radiomics model, the NRI and IDI was 0.149 and 0.164 for the deep-radiomics model without significant difference. Conclusion: The deep-radiomics model exhibits promising potential in predicting BCR in advanced PCa, compared to both the clinical model and the conventional radiomics model.

Quantitative measurement of the ureter on three-dimensional magnetic resonance urography images using deep learning.

BACKGROUND: Accurate measurement of ureteral diameters plays a pivotal role in diagnosing and monitoring urinary tract obstruction (UTO). While three-dimensional magnetic resonance urography (3D MRU) represents a significant advancement in imaging, the traditional manual methods for assessing ureteral diameters are characterized by labor-intensive procedures and inherent variability. In the realm of medical image analysis, deep learning has led to a paradigm shift, yet the development of a comprehensive automated tool for the precise segmentation and measurement of ureters in MR images is an unaddressed challenge. PURPOSE: The ureter was quantitatively measured on 3D MRU images using a deep learning model. METHODS: A retrospective cohort of 445 3D MRU scans (443 patients, 52 ± 18 years; 217 female patients) was collected and split into training, validation, and internal testing cohorts. A 3D V-Net model was trained for urinary tract segmentation, and a post-processing algorithm was developed for ureteral measurements. The accuracy of the segmentation was evaluated using the Dice similarity coefficient (DSC) and volume intraclass correlation coefficient (ICC), with ground truth segmentations provided by experienced radiologists. The external cohort comprised 50 scans (50 patients, 55 ± 21 years; 30 female patients), and the model-predicted ureteral diameter measurements were compared with manual measurements to assess system performance. The various diameter parameters of ureter among the different measurement methods (ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction) were assessed with Friedman tests and post hoc Dunn test. The effectiveness of the UTO diagnosis was assessed by receiver operating characteristic (ROC) curves and their respective areas under the curve (AUC) between different methods. RESULTS: In both the internal test and external cohorts, the mean DSC values for bilateral ureters exceeded 0.70. The ICCs for the bilateral ureter volume obtained by comparing the model and manual segmentation were all greater than 0.96 (p  < â€¯0.05), except for the right ureter in the internal test cohort, for which the ICC was 0.773 (p  < â€¯0.05). The mean DSCs for interobserver and intraobserver reliability were all above 0.97. The maximum diameter of the ureter exhibited no statistically significant differences either in the dilated (p = 0.08) or in the non-dilated (p = 0.32) ureters across the three measurement methods. The AUCs of ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction in diagnosing UTO were 0.988 (95% CI: 0.934, 1.000), 0.961 (95% CI: 0.893, 0.991), and 0.979 (95% CI: 0.919, 0.998), respectively. There was no statistical difference between AUCs of the different methods (p > 0.05). CONCLUSION: The proposed deep learning model and post-processing algorithm provide an effective means for the quantitative evaluation of urinary diseases using 3D MRU images.

Development and validation of predictive models for myopia onset and progression using extensive 15-year refractive data in children and adolescents.

BACKGROUND: Global myopia prevalence poses a substantial public health burden with vision-threatening complications, necessitating effective prevention and control strategies. Precise prediction of spherical equivalent (SE), myopia, and high myopia onset is vital for proactive clinical interventions. METHODS: We reviewed electronic medical records of pediatric and adolescent patients who underwent cycloplegic refraction measurements at the Eye & Ear, Nose, and Throat Hospital of Fudan University between January 2005 and December 2019. Patients aged 3-18 years who met the inclusion criteria were enrolled in this study. To predict the SE and onset of myopia and high myopia in a specific year, two distinct models, random forest (RF) and the gradient boosted tree algorithm (XGBoost), were trained and validated based on variables such as age at baseline, and SE at various intervals. Outputs included SE, the onset of myopia, and high myopia up to 15 years post-initial examination. Age-stratified analyses and feature importance assessments were conducted to augment the clinical significance of the models. RESULTS: The study enrolled 88,250 individuals with 408,255 refraction records. The XGBoost-based SE prediction model consistently demonstrated robust and better performance than RF over 15 years, maintaining an R2 exceeding 0.729, and a Mean Absolute Error ranging from 0.078 to 1.802 in the test set. Myopia onset prediction exhibited strong area under the curve (AUC) values between 0.845 and 0.953 over 15 years, and high myopia onset prediction showed robust AUC values (0.807-0.997 over 13 years, with the 14th year at 0.765), emphasizing the models' effectiveness across age groups and temporal dimensions on the test set. Additionally, our classification models exhibited excellent calibration, as evidenced by consistently low brier score values, all falling below 0.25. Moreover, our findings underscore the importance of commencing regular examinations at an early age to predict high myopia. CONCLUSIONS: The XGBoost predictive models exhibited high accuracy in predicting SE, onset of myopia, and high myopia among children and adolescents aged 3-18 years. Our findings emphasize the importance of early and regular examinations at a young age for predicting high myopia, thereby providing valuable insights for clinical practice.

Algorithmic and sensor-based research on Chinese children's and adolescents' screen use behavior and light environment.

Background: Myopia poses a global health concern and is influenced by both genetic and environmental factors. The incidence of myopia tends to increase during infectious outbreaks, such as the COVID-19 pandemic. This study examined the screen-time behaviors among Chinese children and adolescents and investigated the efficacy of artificial intelligence (AI)-based alerts in modifying screen-time practices. Methods: A cross-sectional analysis was performed using data from 6,716 children and adolescents with AI-enhanced tablets that monitored and recorded their behavior and environmental light during screen time. Results: The median daily screen time of all participants was 58.82 min. Among all age groups, elementary-school students had the longest median daily screen time, which was 87.25 min and exceeded 4 h per week. Children younger than 2 years engaged with tablets for a median of 41.84 min per day. Learning accounted for 54.88% of participants' screen time, and 51.03% (3,390/6,643) of the participants used tablets for 1 h at an average distance <50 cm. The distance and posture alarms were triggered 807,355 and 509,199 times, respectively. In the study, 70.65% of the participants used the tablet under an illuminance of <300 lux during the day and 61.11% under an illuminance of <100 lux at night. The ambient light of 85.19% of the participants exceeded 4,000 K color temperature during night. Most incorrect viewing habits (65.49% in viewing distance; 86.48% in viewing posture) were rectified swiftly following AI notifications (all p < 0.05). Conclusion: Young children are increasingly using digital screens, with school-age children and adolescents showing longer screen time than preschoolers. The study highlighted inadequate lighting conditions during screen use. AI alerts proved effective in prompting users to correct their screen-related behavior promptly.