Oral behaviors and anxiety are significant predictors of jaw function limitation in patients with anterior disc displacement without reduction.

OBJECTIVE: We aimed to describe jaw function characteristics in patients with anterior disc displacement without reduction (ADDWoR) using the jaw function limitation scale (JFLS), and to investigate the effects of biopsychosocial risk factors on limited jaw function. DESIGN: In this cross-sectional study of 636 patients with ADDWoR (females, 568; males, 68), we used the JFLS to assess jaw function. Behavioral, psychological, sociodemographic, and biomedical data were collected. Multivariate logistic regression analysis was used to determine risk factors affecting limited jaw function. A receiver operating characteristic curve was used to evaluate the predictive effect of these risk factors. RESULTS: ADDWoR-associated limitations included restricted jaw mobility and mastication, which exceeded median global functional limitations scale scores, especially mouth opening to bite an apple and chewing tough food. Females had greater limitations in jaw mobility, verbal and emotional communication, and overall. Multivariate logistic regression analysis findings indicated that oral behaviors, anxiety, sex, pain intensity, and maximal mouth opening (MMO) were predictive of limited jaw function (area under the curve, 72 %). CONCLUSION: Patients with ADDWoR reported mastication and jaw mobility restrictions, with females having more pronounced limitations, and specific risk factors identified as significant predictors of jaw function limitations. Along with pain relief and improvement in MMO, appropriate psychological counseling and oral behavioral correction facilitates recovery of jaw function in such patients.

Classification and Regression Machine Learning Models for Predicting the Combined Toxicity and Interactions of Antibiotics and Fungicides Mixtures.

Antibiotics and triazole fungicides coexist in varying concentrations in natural aquatic environments, resulting in complex mixtures. These mixtures can potentially affect aquatic ecosystems. Accurately distinguishing synergistic and antagonistic mixtures and predicting mixture toxicity are crucial for effective mixture risk assessment. We tested the toxicities of 75 binary mixtures of antibiotics and fungicides against Auxenochlorella pyrenoidosa. Both regression and classification models for these mixtures were developed using machine learning models: random forest (RF), k-nearest neighbors (KNN), and kernel k-nearest neighbors (KKNN). The KKNN model emerged as the best regression model with high values of determination coefficient (R2 = 0.977), explained variance in prediction leave-one-out (Q2LOO = 0.894), and explained variance in external prediction (Q2F1 = 0.929, Q2F2 = 0.929, and Q2F3 = 0.923). The RF model, the leading classifier, exhibited high accuracy (accuracy = 1 for the training set and 0.905 for the test set) in distinguishing the synergistic and antagonistic mixtures. These results provide crucial value for the risk assessment of mixtures.

Subpocket Similarity-Based Hit Identification for Challenging Targets: Application to the WDR Domain of LRRK2.

We herewith applied a priori a generic hit identification method (POEM) for difficult targets of known three-dimensional structure, relying on the simple knowledge of physicochemical and topological properties of a user-selected cavity. Searching for local similarity to a set of fragment-bound protein microenvironments of known structure, a point cloud registration algorithm is first applied to align known subpockets to the target cavity. The resulting alignment then permits us to directly pose the corresponding seed fragments in a target cavity space not typically amenable to classical docking approaches. Last, linking potentially connectable atoms by a deep generative linker enables full ligand enumeration. When applied to the WD40 repeat (WDR) central cavity of leucine-rich repeat kinase 2 (LRRK2), an unprecedented binding site, POEM was able to quickly propose 94 potential hits, five of which were subsequently confirmed to bind in vitro to LRRK2-WDR.

Metagenomic and flavoromic profiling reveals the correlation between the microorganisms and volatile flavor compounds in Monascus-fermented cheese.

The Monascus-fermented cheese (MC) is a unique cheese product that undergoes multi-strain fermentation, imparting it with distinct flavor qualities. To clarify the role of microorganisms in the formation of flavor in MC, this study employed SPME (arrow)-GC-MS, GC-O integrated with PLS-DA to investigate variations in cheese flavors represented by volatile flavor compounds across 90-day ripening periods. Metagenomic datasets were utilized to identify taxonomic and functional changes in the microorganisms. The results showed a total of 26 characteristic flavor compounds in MC at different ripening periods (VIP＞1, p < 0.05), including butanoic acid, hexanoic acid, butanoic acid ethyl ester, hexanoic acid butyl ester, 2-heptanone and 2-octanone. According to NR database annotation, the genera Monascus, Lactococcus, Aspergillus, Lactiplantibacillus, Staphylococcus, Flavobacterium, Bacillus, Clostridium, Meyerozyma, and Enterobacter were closely associated with flavor formation in MC. Ester compounds were linked to Monascus, Meyerozyma, Staphylococcus, Lactiplantibacillus, and Bacillus. Acid compounds were linked to Lactococcus, Lactobacillus, Staphylococcus, and Bacillus. The production of methyl ketones was closely related to the genera Monascus, Staphylococcus, Lactiplantibacillus, Lactococcus, Bacillus, and Flavobacterium. This study offers insights into the microorganisms of MC and its contribution to flavor development, thereby enriching our understanding of this fascinating dairy product.

Current treatment of biliary Sphincter of Oddi Dysfunction.

The sphincter of Oddi is a delicate neuromuscular structure located at the junction of the biliary-pancreatic system and the duodenum. Sphincter of Oddi Dysfunction (SOD) can result in various clinical manifestations, including biliary-type pain and recurrent idiopathic pancreatitis. The management of SOD has been challenging. With the publication of the landmark Evaluating Predictors and Interventions in Sphincter of Oddi Dysfunction (EPISOD) trial and the Rome IV consensus, our clinical practice in the treatment of SOD has changed significantly in recent years. Currently, the management of type II SOD remains controversial and there is a lack of non-invasive therapy options, particularly for patients not responding to endoscopic treatment. In this mini review, we aimed to discuss the current knowledge on the treatment of biliary SOD.

Exosome may be the next generation of promising cell-free vaccines.

Traditional vaccines have limits against some persistent infections and pathogens. The development of novel vaccine technologies is particularly critical for the future. Exosomes play an important role in physiological and pathological processes. Exosomes present many advantages, such as inherent capacity being biocompatible, non-toxic, which make them a more desirable candidate for vaccines. However, research on exosomes are in their infancy and the barriers of low yield, low purity, and weak targeting of exosomes limit their applications in vaccines. Accordingly, further exploration is necessary to improve these problems and subsequently facilitate the functional studies of exosomes. In this study, we reviewed the origin, classification, functions, modifications, separation and purification, and characterization methods of exosomes. Meanwhile, we focused on the role and mechanism of exosomes for cancer and COVID-19 vaccines.

NGEF is a potential prognostic biomarker and could serve as an indicator for immunotherapy and chemotherapy in lung adenocarcinoma.

BACKGROUND: Neuronal guanine nucleotide exchange factor (NGEF) plays a key role in several cancers; however, its role in lung adenocarcinoma (LUAD) remains unclear. The aim of this study was to evaluate the efficacy of NGEF as a prognostic biomarker and potential therapeutic target for LUAD. METHODS: NGEF expression data for multiple cancers and LUAD were downloaded from multiple databases. The high- and low-NGEF expression groups were constructed based on median NGEF expression in LUAD samples, and then performed Kaplan-Meier survival analysis. Differentially expressed genes (DEGs) from the two NGEF expression groups were screened and applied to construct a protein-protein interaction network. The primary pathways were obtained using gene set enrichment analysis. The associations between NGEF expression and clinical characteristics, immune infiltration, immune checkpoint inhibitors (ICIs), sensitivity to chemotherapy, and tumor mutation burden (TMB) were investigated using R. Levels of NGEF expression in the lung tissue was validated using single-cell RNA sequencing, quantitative polymerase chain reaction (qPCR), immunohistochemical staining, and western blot analysis. RESULTS: The expression of NGEF mRNA was upregulated in multiple cancers. mRNA and protein expression levels of NGEF were higher in patients with LUAD than in controls, as validated using qPCR and western blot. High NGEF expression was an independent prognostic factor for LUAD and was associated with advanced tumor stage, large tumor size, more lymph node metastasis, and worse overall survival (OS). A total of 182 overlapping DEGs were screened between The Cancer Genome Atlas and GSE31210, among which the top 20 hub genes were identified. NGEF expression was mainly enriched in the pathways of apoptosis, cell cycle, and DNA replication. Moreover, elevated NGEF expression were associated with a high fraction of activated memory CD4+ T cells and M0 macrophages; elevated expression levels of the ICIs: programmed cell death 1 and programmed cell death 1 ligand 1 expression; higher TMB; and better sensitivity to bortezomib, docetaxel, paclitaxel, and parthenolide, but less sensitivity to axitinib and metformin. CONCLUSION: NGEF expression is upregulated in LUAD and is significantly associated with tumor stages, OS probability, immune infiltration, immunotherapy response, and chemotherapy response. NGEF may be a potential diagnostic and prognostic biomarker and therapeutic target in LUAD.

A review regarding the article 'The potential relationship between cardiovascular diseases and monkeypox'.

Cardiovascular involvement in the context of viral infections is a well-documented phenomenon, for their potential to induce myocarditis, pericarditis, and other cardiac complications. While monkeypox is predominantly known for its predilection for the skin and mucous membranes, manifesting as characteristic skin lesions, emerging research suggests that the monkeypox virus can also infiltrate endothelial cells, thereby disseminating systemically and potentially impacting various organ systems, including the cardiovascular system. This has led to the identification of several inflammatory conditions, such as myocarditis and pericarditis, which can complicate the clinical course of monkeypox virus infection. Notably, an increase in cardiac biomarkers, often associated with symptoms of chest pain, has been observed in case reports detailing monkeypox-induced myocarditis. From a clinical cardiology perspective, it is imperative to deepen our understanding of monkeypox to better recognize and manage its cardiovascular implications. Conditions like myocarditis, viral pericarditis, heart failure, and arrhythmias have been known to arise, significantly impacting patients' health and quality of life. A thorough comprehension of the intricate pathophysiological mechanisms underlying these cardiovascular manifestations is crucial for enhancing diagnostic accuracy and refining management strategies. The social implications of cardiovascular complications from viral infections are multifaceted, extending beyond direct health concerns to include psychological distress, social stigma, and broader public health considerations. The clinical management of these complications is challenging and necessitates a multidisciplinary approach, often requiring specialized care. The resultant strain on healthcare resources underscores the importance of preparedness and strategic resource allocation to effectively address these complex health issues.

NeuroDM: Decoding and visualizing human brain activity with EEG-guided diffusion model.

BACKGROUND AND OBJECTIVE: Brain-Computer Interface (BCI) technology has recently been advancing rapidly, bringing significant hope for improving human health and quality of life. Decoding and visualizing visually evoked electroencephalography (EEG) signals into corresponding images plays a crucial role in the practical application of BCI technology. The recent emergence of diffusion models provides a good modeling basis for this work. However, the existing diffusion models still have great challenges in generating high-quality images from EEG, due to the low signal-to-noise ratio and strong randomness of EEG signals. The purpose of this study is to address the above-mentioned challenges by proposing a framework named NeuroDM that can decode human brain responses to visual stimuli from EEG-recorded brain activity. METHODS: In NeuroDM, an EEG-Visual-Transformer (EV-Transformer) is used to extract the visual-related features with high classification accuracy from EEG signals, then an EEG-Guided Diffusion Model (EG-DM) is employed to synthesize high-quality images from the EEG visual-related features. RESULTS: We conducted experiments on two EEG datasets (one is a forty-class dataset, and the other is a four-class dataset). In the task of EEG decoding, we achieved average accuracies of 99.80% and 92.07% on two datasets, respectively. In the task of EEG visualization, the Inception Score of the images generated by NeuroDM reached 15.04 and 8.67, respectively. All the above results outperform existing methods. CONCLUSIONS: The experimental results on two EEG datasets demonstrate the effectiveness of the NeuroDM framework, achieving state-of-the-art performance in terms of classification accuracy and image quality. Furthermore, our NeuroDM exhibits strong generalization capabilities and the ability to generate diverse images.

Specific plasma microRNA profiles could be potential non-invasive biomarkers for biochemical pregnancy loss following embryo transfer.

BACKGROUND: Plasma microRNAs act as biomarkers for predicting and diagnosing diseases. Reliable non-invasive biomarkers for biochemical pregnancy loss have not been established. We aim to analyze the dynamic microRNA profiles during the peri-implantation period and investigate if plasma microRNAs could be non-invasive biomarkers predicting BPL. METHODS: In this study, we collected plasma samples from patients undergoing embryo transfer (ET) on ET day (ET0), 11 days after ET (ET11), and 14 days after ET (ET14). Patients were divided into the NP (negative pregnancy), BPL (biochemical pregnancy loss), and CP (clinical pregnancy) groups according to serum hCG levels at day11~14 and ultrasound at day28~35 following ET. MicroRNA profiles at different time-points were detected by miRNA-sequencing. We analyzed plasma microRNA signatures for BPL at the peri-implantation stage, we characterized the dynamic microRNA changes during the implantation period, constructed a microRNA co-expression network, and established predictive models for BPL. Finally, the sequencing results were confirmed by Taqman RT-qPCR. RESULTS: BPL patients have distinct plasma microRNA profiles compared to CP patients at multiple time-points during the peri-implantation period. Machine learning models revealed that plasma microRNAs could predict BPL. RT-qPCR confirmed that miR-181a-2-3p, miR-9-5p, miR-150-3p, miR-150-5p, and miR-98-5p, miR-363-3p were significantly differentially expressed between patients with different reproductive outcomes. CONCLUSION: Our study highlights the non-invasive value of plasma microRNAs in predicting BPL.

Intrahepatic cholangiocarcinoma with FGFR alterations: A series of Chinese cases with an emphasis on their clinicopathologic and genetic features.

Intrahepatic Cholangiocarcinoma (iCCA) with FGFR alterations is relatively rare, and its identification is important in the era of targeted therapy. We collected a large series of FGFR-altered cases in the Chinese population and characterized their clinicopathological and genetic features. Among the 18 FGFR-altered cases out of 260 iCCAs, 10 were males and 8 were females, ranging in age from 35 to 74 years (mean, 57.3 years; median, 58 years). Pathologically, they include 9 cases of large duct (LD, 50 %) and small duct (SD, 50 %) types each. All of them (100 %, 18/18) showed microsatellite stable (MSS) and low tumor mutation burden (TMB). Genetically, FGFR alterations involved FGFR1 (20 %), FGFR2 (70 %), and FGFR3 (10 %), with FGFR2 rearrangement accounting for the most (11/18). The most frequently altered genes/biological processes were development/proliferation-related pathways (44 %), chromatin organization (20 %), and tumor suppressors (32 %). Our study further revealed the clinicopathological and genetic features of FGFR-altered iCCA and demonstrated that its occurrence may show regional or ethnic variability and is less common in the Chinese population. A significant number of LD-type iCCA cases also have FGFR alterations rather than the SD type.

An Aging-Related lncRNA Signature Establishing for Breast Cancer Prognosis and Immunotherapy Responsiveness Prediction.

Purpose: Emerging evidence demonstrates the vital role of aging and long non-coding RNAs (lncRNAs) in breast cancer (BC) progression. Our study intended to develop a prognostic risk model based on aging-related lncRNAs (AG-lncs) to foresee BC patients' outcomes. Patients and Methods: 307 aging-related genes (AGs) were sequenced from the TCGA project. Then, 697 AG-lncs were identified by the co-expression analysis with AGs. Using multivariate and univariate Cox regression analysis, and LASSO, 6 AG-lncs, including al136531.1, mapt-as1, al451085.2, otud6b-as1, tnfrsf14-as1, and linc01871, were validated to compute the risk score and establish a risk signature. Expression levels of al136531.1, mapt-as1, al451085.2, tnfrsf14-as1, and linc01871 were higher in low-risk BC patients, whereas otud6b-as1 expression was higher in high-risk BC patients. In the training and testing set, high-risk patients performed shorter PFI, OS, and DFS than low-risk patients. Results: Our risk signature had the highest concordance index among other established prognostic signatures and displayed ideal predictive ability for 1-, 3- and 5-year patient OS in the nomogram. Additionally, BC patients with different risk score levels showed different immune statuses and responses to immunotherapy via GSEA, ssGSEA, ESTIMATE algorithm, and TIDE algorithm analysis. Of note, the qRT-PCR analysis validated that these 6 AG-lncs expressed quite differentially in BC tissues at various clinical stages. Conclusion: The risk signature of 6 AG-lncs might offer a novel prognostic biomarker and promisingly enhance BC immunotherapy's effectiveness.

PVALB Was Identified as an Independent Prognostic Factor for HCC Closely Related to Immunity, and Its Absence Accelerates Tumor Progression by Regulating NK Cell Infiltration.

Purpose: Hepatocellular carcinoma is the most common primary liver cancer, with poor prognosis. Complex immune microenvironment of the liver is linked to the development of HCC. PVALB is a calcium-binding protein which has been described as a cancer suppressor gene in thyroid cancer and glioma. Nevertheless, the role of PVALB in HCC is unknown. Materials and Methods: We obtained data from TCGA and GSE54236 datasets. MCP-counter, WGCNA and LASSO model were applied to identify PVALB. With UALCAN, MethSurv, and other websites, we probed the expression, methylation and survival of PVALB. LinkedOmics and GSEA were adopted for functional analysis, while TIMER, TISIDB, Kaplan-Meier plotter, TIDE databases were utilized to evaluate the relevance of PVALB to the tumor immune microenvironment and predict immunotherapy efficacy. TargetScan, DIANA, LncRNASNP2 databases and relevant experiments were employed to construct ceRNA network. Finally, molecular docking and drug sensitivity of PVALB were characterized by GeneMANIA, CTD, and so on. Results: PVALB was recognized as a gene associated with HCC and NK cell. Its expression was down-regulated in HCC tissue, which lead to adverse prognosis. Besides, the hypomethylation of PVALB was related to its reduced expression. Notably, PVALB was tightly linked to immune, and its reduced expression attenuated the anticancer effect of NK cells via the Fas/FasL pathway, leading to a adverse outcome. The lnc-YY1AP1-3/hsa-miR-6735-5p/PVALB axis may regulate the PVALB expression. Finally, we found immunotherapy might be a viable treatment option. Conclusion: In a word, PVALB is a prognostic indicator, whose low expression facilitates HCC progression by impacting NK cell infiltration.

Identification of a robust biomarker LAPTM4A for glioma based on comprehensive computational biology and experimental verification.

BACKGROUND: Glioma, a highly invasive and deadly form of human neoplasm, presents a pressing need for the exploration of potential therapeutic targets. While the lysosomal protein transmembrane 4A (LATPM4A) has been identified as a risk factor in pancreatic cancer patients, its role in glioma remains unexplored. METHODS: The analysis of differentially expressed genes (DEG) was conducted from The Cancer Genome Atlas (TCGA) glioma dataset and the Genotype Tissue Expression (GTEx) dataset. Through weighted gene co-expression network analysis (WGCNA), the key glioma-related genes were identified. Among these, by using Kaplan-Meier (KM) analysis and univariate/multivariate COX methods, LAPTM4A emerged as the most influential gene. Moreover, the bioinformatics methods and experimental verification were employed to analyze its relationships with diagnosis, clinical parameters, epithelial-mesenchymal transition (EMT), metastasis, immune cell infiltration, immunotherapy, drug sensitivity, and ceRNA network. RESULTS: Our findings revealed that LAPTM4A was up-regulated in gliomas and was associated with clinicopathological features, leading to poor prognosis. Furthermore, functional enrichment analysis demonstrated that LATPM4A played a role in the immune system and cancer progression. In vitro experiments indicated that LAPTM4A may influence metastasis through the EMT pathway in glioma. Additionally, we found that LAPTM4A was associated with the tumor microenvironment (TME) and immunotherapy. Notably, drug sensitivity analysis revealed that patients with high LAPTM4A expression were sensitive to doxorubicin, which contributed to a reduction in LAPTM4A expression. Finally, we uncovered the FGD5-AS1-hsa-miR-103a-3p-LAPTM4A axis as a facilitator of glioma progression. CONCLUSIONS: In conclusion, our study identifies LATPM4A as a promising biomarker for prognosis and immune characteristics in glioma.

Quantum Light Generation Based on GaN Microring toward Fully On-Chip Source.

An integrated quantum light source is increasingly desirable in large-scale quantum information processing. Despite recent remarkable advances, a new material platform is constantly being explored for the fully on-chip integration of quantum light generation, active and passive manipulation, and detection. Here, for the first time, we demonstrate a gallium nitride (GaN) microring based quantum light generation in the telecom C-band, which has potential toward the monolithic integration of quantum light source. In our demonstration, the GaN microring has a free spectral range of 330 GHz and a near-zero anomalous dispersion region of over 100 nm. The generation of energy-time entangled photon pair is demonstrated with a typical raw two-photon interference visibility of 95.5±6.5%, which is further configured to generate a heralded single photon with a typical heralded second-order autocorrelation g_{H}^{(2)}(0) of 0.045±0.001. Our results pave the way for developing a chip-scale quantum photonic circuit.

Probing the CRL4DCAF12 interactions with MAGEA3 and CCT5 di-Glu C-terminal degrons.

Damaged DNA-binding protein-1 (DDB1)- and CUL4-associated factor 12 (DCAF12) serves as the substrate recognition component within the Cullin4-RING E3 ligase (CRL4) complex, capable of identifying C-terminal double-glutamic acid degrons to promote the degradation of specific substrates through the ubiquitin proteasome system. Melanoma-associated antigen 3 (MAGEA3) and T-complex protein 1 subunit epsilon (CCT5) proteins have been identified as cellular targets of DCAF12. To further characterize the interactions between DCAF12 and both MAGEA3 and CCT5, we developed a suite of biophysical and proximity-based cellular NanoBRET assays showing that the C-terminal degron peptides of both MAGEA3 and CCT5 form nanomolar affinity interactions with DCAF12 in vitro and in cells. Furthermore, we report here the 3.17 Šcryo-EM structure of DDB1-DCAF12-MAGEA3 complex revealing the key DCAF12 residues responsible for C-terminal degron recognition and binding. Our study provides new insights and tools to enable the discovery of small molecule handles targeting the WD40-repeat domain of DCAF12 for future proteolysis targeting chimera design and development.

Demonstration of 651†nm InGaN-based red light-emitting diode with an external quantum efficiency over 6% by InGaN/AlN strain release interlayer.

This work reports a high-performance InGaN-based red-emitting LED with a strain-release interlayer (SRI) consisting of an InGaN stress-release layer (SRL) and an AlN dislocation confinement layer (DCL) in unintentionally doped GaN (u-GaN). The SRL introduces a tensile strain which could decrease the in-plane compressive stress of the u-GaN layer, while the DCL could reduce the dislocation density and thus improve the crystal quality of the u-GaN layer. Consequently, a high-efficiency InGaN-based red-emitting LED with a peak wavelength of 651 nm and an external quantum efficiency of 6.04% is realized. In addition, the room-temperature photoluminescence (PL) mapping emission wavelength is uniform across a 4-inch wafer with a standard deviation of 3.3 nm. Therefore, the proposed SRI offers good potential for mass-producing high-performance and long-wavelength InGaN-based red-emitting LEDs.

An artificial intelligence model for detecting pathological lymph node metastasis in prostate cancer using whole slide images: a retrospective, multicentre, diagnostic study.

Background: The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. Methods: In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. Findings: In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64-73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953-0.998) to 0.992 (0.982-1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908-1.000]) surpassed that of two junior pathologists (0.862 [0.746-0.939], P = 0.023; 0.879 [0.767-0.950], P = 0.041) by 10-12% and showed no difference to that of two senior pathologists (both 0.983 [0.908-1.000], both P > 0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both P = 0.041) to the level of senior pathologists (both P > 0.99), and substantially reduced the four pathologists' slide reviewing time (-31%, P < 0.0001; -34%, P < 0.0001; -29%, P < 0.0001; and -27%, P = 0.00031). Interpretation: ProCaLNMD demonstrated high diagnostic capabilities for identifying LNM in prostate cancer, reducing the likelihood of missed diagnoses by pathologists and decreasing the slide reviewing time, highlighting its potential for clinical application. Funding: National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, the Guangdong Provincial Clinical Research Centre for Urological Diseases, and the Science and Technology Projects in Guangzhou.

Basilic vein variation encountered during surgery for arm vein port: A case report.

BACKGROUND: Venous variations are uncommon and usually hard to identify, and basilic vein variation is particularly rare. Basilic vein variation usually presents without any clinical symptoms and is often regarded as a benign alteration. This case was a patient with congenital basilic vein variation encountered during surgery for an infusion port. CASE SUMMARY: We documented and analyzed an uncommon anatomical variation in the basilic vein encountered during arm port insertion. This peculiarity has hitherto remained undescribed in the literature. We offer remedial strategies for addressing this anomaly in the future and precautionary measures to circumvent its occurrence. We conducted a comprehensive review of analogous cases in the literature, offering pertinent therapeutic recommendations and solutions, with the aim of enhancing the efficacy and safety of future arm port implantations. CONCLUSION: Venous variation is rare and requires detailed intraoperative and postoperative examination to ensure accuracy, so as not to affect subsequent treatment.

Mechanism of the Synergistic Toxicity of Ampicillin and Cefazoline on Selenastrum capricornutum.

Ampicillin (AMP) and cefazolin (CZO) are commonly used ß-lactam antibiotics which are extensively globally produced. Additionally, AMP and CZO are known to have relatively high ecotoxicity. Notably, the mix of AMP and CZO creates a synergistic effect that is more harmful to the environment, and how exposure to AMP-CZO can induce synergism in algae remains virtually unknown. To yield comprehensive mechanistic insights into chemical toxicity, including dose-response relationships and variations in species sensitivity, the integration of multiple endpoints with de novo transcriptomics analyses were used in this study. We employed Selenastrum capricornutum to investigate its toxicological responses to AMP and CZO at various biological levels, with the aim of elucidating the underlying mechanisms. Our assessment of multiple endpoints revealed a significant growth inhibition in response to AMP at the relevant concentrations. This inhibition was associated with increased levels of reactive oxygen species (ROS) and perturbations in nitrogen metabolism, carbohydrate metabolism, and energy metabolism. Growth inhibition in the presence of CZO and the AMP-CZO combination was linked to reduced viability levels, elevated ROS production, decreased total soluble protein content, inhibited photosynthesis, and disruptions in the key signaling pathways related to starch and sucrose metabolism, ribosome function, amino acid biosynthesis, and the production of secondary metabolites. It was concluded from the physiological level that the synergistic effect of Chlorophyll a (Chla) and Superoxide dismutase (SOD) activity strengthened the growth inhibition of S. capricornutum in the AMP-CZO synergistic group. According to the results of transcriptomic analysis, the simultaneous down-regulation of LHCA4, LHCA1, LHCA5, and sodA destroyed the functions of the photosynthetic system and the antioxidant system, respectively. Such information is invaluable for environmental risk assessments. The results provided critical knowledge for a better understanding of the potential ecological impacts of these antibiotics on non-target organisms.