Clinical-imaging metrics for the diagnosis of prostate cancer in PI-RADS 3 lesions.

OBJECTIVE: To explore the feasibility and efficacy of clinical-imaging metrics in the diagnosis of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in prostate imaging-reporting and data system (PI-RADS) category 3 lesions. METHODS: A retrospective analysis was conducted on lesions diagnosed as PI-RADS 3. They were categorized into benign, non-csPCa and csPCa groups. Apparent diffusion coefficient (ADC), T2-weighted imaging signal intensity (T2WISI), coefficient of variation of ADC and T2WISI, prostate-specific antigen density (PSAD), ADC density (ADCD), prostate-specific antigen lesion volume density (PSAVD) and ADC lesion volume density (ADCVD) were measured and calculated. Univariate and multivariate analyses were used to identify risk factors associated with PCa and csPCa. Receiver operating characteristic curve (ROC) and decision curves were utilized to assess the efficacy and net benefit of independent risk factors. RESULTS: Among 202 patients, 133 had benign prostate disease, 25 non-csPCa and 44 csPCa. Age, PSA and lesion location showed no significant differences (P > 0.05) among the groups. T2WISI and coefficient of variation of ADC (ADCcv) were independent risk factors for PCa in PI-RADS 3 lesions, yielding an area under the curve (AUC) of 0.68. ADC was an independent risk factor for csPCa in PI-RADS 3 lesions, yielding an AUC of 0.65. Decision curve analysis showed net benefit for patients at certain probability thresholds. CONCLUSIONS: T2WISI and ADCcv, along with ADC, respectively showed considerable promise in enhancing the diagnosis of PCa and csPCa in PI-RADS 3 lesions.

Non-invasively identifying candidates of active surveillance for prostate cancer using magnetic resonance imaging radiomics.

Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying patients who may benefit from AS relies on unpleasant prostate biopsies, which entail the risk of bleeding and infection. In the current study, we aimed to develop a radiomics model based on prostate magnetic resonance images to identify AS candidates non-invasively. A total of 956 PCa patients with complete biopsy reports from six hospitals were included in the current multicenter retrospective study. The National Comprehensive Cancer Network (NCCN) guidelines were used as reference standards to determine the AS candidacy. To discriminate between AS and non-AS candidates, five radiomics models (i.e., eXtreme Gradient Boosting (XGBoost) AS classifier (XGB-AS), logistic regression (LR) AS classifier, random forest (RF) AS classifier, adaptive boosting (AdaBoost) AS classifier, and decision tree (DT) AS classifier) were developed and externally validated using a three-fold cross-center validation based on five classifiers: XGBoost, LR, RF, AdaBoost, and DT. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE) were calculated to evaluate the performance of these models. XGB-AS exhibited an average of AUC of 0.803, ACC of 0.693, SEN of 0.668, and SPE of 0.841, showing a better comprehensive performance than those of the other included radiomic models. Additionally, the XGB-AS model also presented a promising performance for identifying AS candidates from the intermediate-risk cases and the ambiguous cases with diagnostic discordance between the NCCN guidelines and the Prostate Imaging-Reporting and Data System assessment. These results suggest that the XGB-AS model has the potential to help identify patients who are suitable for AS and allow non-invasive monitoring of patients on AS, thereby reducing the number of annual biopsies and the associated risks of bleeding and infection.

Inflammatory proteins mediate male erectile dysfunction via plasma metabolites.

Background: There are no clear conclusions as to whether inflammatory proteins and plasma metabolites influence erectile dysfunction (ED). Aim: In this research, we used Mendelian randomization (MR) analysis to discover a causal relationship between inflammatory proteins, plasma metabolites, and ED. Methods: Raw data with ED, inflammatory proteins, and plasma metabolites were obtained from the MRC IEU OpenGWAS and FinnGen database. After a series of screenings, the remaining single nucleotide polymorphisms were selected as instrumental variables or MR analysis to assess the relationship between genetically predicted inflammatory proteins or plasma metabolites and the pathogenesis of ED. Outcomes: The relationship between inflammatory factors and ED was fully analyzed and elaborated. Results: In the inverse variance-weighted method, there exists a significant causal relationship between 4 types of genetically predicted inflammatory proteins and 50 types of plasma metabolites with the incidence of ED. The primary discovery is that 3 inflammatory proteins, fibroblast growth factor 5, interleukin-22 receptor subunit alpha-1, and protein S100-A12, can impact the risk of ED through plasma metabolites. Clinical Implications: ED metabolites and inflammatory proteins are also closely associated with cardiovascular diseases, warranting further exploration. Strengths and Limitations: Our analysis is based on a European population, limiting its generalizability, the genome-wide association study dataset for ED has a relatively small number of cases, and we hope for larger genome-wide association study datasets for future validation. Conclusion: This study has identified that inflammatory proteins can influence ED through plasma metabolites.

Association between gut microbiota and common overlapping gastrointestinal disorders: a bidirectional two-sample Mendelian randomization study.

Background: The main functional gastrointestinal disorders (FGIDs) include functional dyspepsia (FD) and irritable bowel syndrome (IBS), which often present overlapping symptoms with gastroesophageal reflux disease (GERD), posing a challenge for clinical diagnosis and treatment. The gut microbiota is closely associated with FGIDs and GERD, although the causal relationship has not been fully elucidated. Therefore, we aimed to investigate the potential causal relationship using bidirectional two-sample Mendelian randomization (MR) analysis. Materials and methods: The genetic data of the 211 gut microbiota were obtained from the MiBioGen consortium (N = 14,306, from phylum to genus level) and species level of gut microbiota were acquired from the Dutch Microbiome Project (N = 7,738). For FD and IBS, we utilized the FinnGen consortium, whereas, for GERD data analysis, we obtained the IEU OpenGWAS project. The inverse-variance weighted (IVW) method was used as the primary method to calculate causal effect values. Sensitivity analyses were also performed to confirm the robustness of the primary findings of the MR analyses. Moreover, a reverse MR analysis was conducted to assess the likelihood of reverse causality. Results: Combining the results of the preliminary and sensitivity analyses, we identified that 8 gut microbial taxa were associated with FD. Genus Lachnospiraceae NK4A136 group (p = 3.63 × 10-3) and genus Terrisporobacter (p = 1.13 × 10-3) were strongly associated with FD. At the same time, we found that 8 gut microbial taxa were associated with IBS. Family Prevotellaceae (p = 2.44 × 10-3) and species Clostridium leptum (p = 7.68 × 10-3) display a robust correlation with IBS. In addition, 5 gut microbial taxa were associated with GERD using the IVW approach. In the reverse MR analysis, 2 gut microbial taxa were found to be associated with FD, 5 gut microbial taxa were found to be associated with IBS, and 21 gut microbial taxa were found to be associated with GERD. Conclusion: The study reveals the potential causal effects of specific microbial taxa on FD, IBS, and GERD and may offer novel insights into the diagnosis and treatment of these conditions.

High-activity recombinant human carboxypeptidase B expression in Pichia pastoris through rational protein engineering and enhancing secretion from the Golgi apparatus to the plasma membrane.

Human carboxypeptidase B1 (hCPB1) is vital for recombinant insulin production, holding substantial value in the pharmaceutical industry. Current challenges include limited hCPB1 enzyme activity. In this study, recombinant hCPB1 efficient expression in Pichia pastoris was achieved. To enhance hCPB1 secretion, we conducted signal peptides screening and deleted the Vps10 sortilin domain, reducing vacuolar mis-sorting. Overexpression of Sec4p increased the fusion of secretory vesicles with the plasma membrane and improved hCPB1 secretion by 20%. Rational protein engineering generated twenty-two single-mutation mutants and identified the A178L mutation resulted in a 30% increase in hCPB1 specific activity. However, all combinational mutations that increased specific activities decreased protein expression levels. Therefore, computer-aided global protein design with PROSS was employed for the aim of improving specific activities and preserving good protein expression. Among the six designed mutants, hCPB1-P6 showed a remarkable 114% increase in the catalytic rate constant (kcat), a 137% decrease in the Michaelis constant (Km), and a 490% increase in catalytic efficiency. Most mutations occurred on the surface of hCPB1-P6, with eight sites mutated to proline. In a 5 L fermenter, hCPB1-P6 was produced by the secretion-enhanced P. pastoris chassis to 199.6 ± 20 mg L-1 with a specific activity of 96 ± 0.32 U mg-1, resulting in a total enzyme activity of 19137 ± 1131 U L-1, demonstrating significant potential for industrial applications.

Enhancing the expression of chondroitin 4-O-sulfotransferase for one-pot enzymatic synthesis of chondroitin sulfate A.

Chondroitin sulfate (CS) stands as a pivotal compound in dietary supplements for osteoarthritis treatment, propelling significant interest in the biotechnological pursuit of environmentally friendly and safe CS production. Enzymatic synthesis of CS for instance CSA has been considered as one of the most promising methods. However, the bottleneck consistently encountered is the active expression of chondroitin 4-O-sulfotransferase (C4ST) during CSA biosynthesis. This study meticulously delved into optimizing C4ST expression through systematic enhancements in transcription, translation, and secretion mechanisms via modifications in the 5' untranslated region, the N-terminal encoding sequence, and the Komagataella phaffii chassis. Ultimately, the active C4ST expression escalated to 2713.1 U/L, representing a striking 43.7-fold increase. By applying the culture broth supernatant of C4ST and integrating the 3'-phosphoadenosine-5'-phosphosulfate (PAPS) biosynthesis module, we constructed a one-pot enzymatic system for CSA biosynthesis, achieving a remarkable sulfonation degree of up to 97.0 %. The substantial enhancement in C4ST expression and the development of an engineered one-pot enzymatic synthesis system promises to expedite large-scale CSA biosynthesis with customizable sulfonation degrees.

Coordinated optimization of the polymerization and transportation processes to enhance the yield of exopolysaccharide heparosan.

Heparosan as the precursor for heparin biosynthesis has attracted intensive attention while Escherichia coli Nissle 1917 (EcN) has been applied as a chassis for heparosan biosynthesis. Here, after uncovering the pivotal role of KfiB in heparosan biosynthesis, we further demonstrate KfiB is involved in facilitating KpsT to translocate the nascent heparosan polysaccharide chain. As a result, an artificial expression cassette KfiACB was constructed with optimized RBS elements, resulting in 0.77 g/L heparosan in shake flask culture. Moreover, in view of the intracellular accumulation of heparosan, we further investigated the effects of overexpression of the ABC transport system proteins on heparosan biosynthesis. By co-overexpressing KfiACB with KpsTME, the heparosan production in flask cultures was increased to 1.03 g/L with an extracellular concentration of 0.96 g/L. Eventually, the engineered strain EcN/pET-kfiACB3-galU-kfiD-glmM/pCDF-kpsTME produced 12.2 g/L heparosan in 5-L fed-batch cultures while the extracellular heparosan was about 11.2 g/L. The results demonstrate the high-efficiency of the strategy for co-optimizing the polymerization and transportation for heparosan biosynthesis. Moreover, this strategy should be also available for enhancing the production of other polysaccharides.

Construction of 5-Aminolevulinic Acid Microbial Cell Factories through Identification of Novel Synthases and Metabolic Pathway Screens and Transporters.

5-Aminolevulinic acid (5-ALA) plays a pivotal role in the biosynthesis of heme and chlorophyll and has garnered great attention for its agricultural applications. This study explores the multifaceted construction of 5-ALA microbial cell factories. Evolutionary analysis-guided screening identified a novel 5-ALA synthase from Sphingobium amiense as the best synthase. An sRNA library facilitated global gene screening that demonstrated that trpC and ilvA repression enhanced 5-ALA production by 74.3% and 102%, respectively. Subsequently, efflux of 5-ALA by the transporter Gdx increased 5-ALA biosynthesis by 25.7%. To mitigate oxidative toxicity, DNA-binding proteins from starved cells were employed, enhancing cell density and 5-ALA titer by 21.1 and 4.1%, respectively. Combining these strategies resulted in an Escherichia coli strain that produced 5-ALA to 1.51 g·L-1 in shake flask experiments and 6.19 g·L-1 through fed-batch fermentation. This study broadens the repertoire of available 5-ALA synthases and transporters and provides a new platform for optimizing 5-ALA bioproduction.

Enzymatic construction of a library of even- and odd-numbered heparosan oligosaccharides and their N-sulfonated derivatives.

Low-molecular-weight heparins (LMWHs), especially the specific-sized heparin oligosaccharides, are attractive for the therapeutic applications, while their synthesis remains challenging. In the present study, unsaturated even-numbered heparosan oligosaccharides were firstly prepared by cleaving high-molecular-weight heparosan using recombinant heparinase III (HepIII). The conversion rates of the unsaturated disaccharides, tetrasaccharides, hexasaccharides, octasaccharides, and decasaccharides were 33.9 %, 47.9 %, 78.7 %, 71.8 %, and 53.4 %, respectively. After processing the aforementioned heparosan oligosaccharides with the Δ4,5 unsaturated glycuronidase, saturated odd-numbered heparosan trisaccharides, pentasaccharides, heptasaccharides, and nonasaccharides were produced. It was observed that among them, the pentasaccharides were the smallest units of saturated odd-numbered oligosaccharides recognized by HepIII. These oligosaccharides were further catalyzed with bifunctional heparan sulfate N-deacetylase/N-sulfotransferase (NDST) under optimized reaction conditions. It was found that the tetrasaccharide was defined as the smallest recognition unit for NDST, obtaining the N-sulfonated heparosan tetrasaccharides, pentasaccharides, and hexasaccharides with a single sulfonate group, as well as N-sulfonated heparosan heptasaccharides, octasaccharides, and nonasaccharides with multiple sulfonate groups. These results provide an easy pathway for constructing a library of specific-sized N-sulfonated heparosan oligosaccharides that can be used as the substrates for the enzymatic synthesis of LMWHs and heparin oligosaccharides, shedding new light on the substrate preference of NDST.

Identification macrophage signatures in prostate cancer by single-cell sequencing and machine learning.

BACKGROUND: The tumor microenvironment (TME) encompasses a variety of cells that influence immune responses and tumor growth, with tumor-associated macrophages (TAM) being a crucial component of the TME. TAM can guide prostate cancer in different directions in response to various external stimuli. METHODS: First, we downloaded prostate cancer single-cell sequencing data and second-generation sequencing data from multiple public databases. From these data, we identified characteristic genes associated with TAM clusters. We then employed machine learning techniques to select the most accurate TAM gene set and developed a TAM-related risk label for prostate cancer. We analyzed the tumor-relatedness of the TAM-related risk label and different risk groups within the population. Finally, we validated the accuracy of the prognostic label using single-cell sequencing data, qPCR, and WB assays, among other methods. RESULTS: In this study, the TAM_2 cell cluster has been identified as promoting the progression of prostate cancer, possibly representing M2 macrophages. The 9 TAM feature genes selected through ten machine learning methods and demonstrated their effectiveness in predicting the progression of prostate cancer patients. Additionally, we have linked these TAM feature genes to clinical pathological characteristics, allowing us to construct a nomogram. This nomogram provides clinical practitioners with a quantitative tool for assessing the prognosis of prostate cancer patients. CONCLUSION: This study has analyzed the potential relationship between TAM and PCa and established a TAM-related prognostic model. It holds promise as a valuable tool for the management and treatment of PCa patients.

Short-term exposure to extreme temperature and outpatient visits for respiratory diseases among children in the northern city of China: a time-series study.

BACKGROUND: Although studies have indicated that extreme temperature is strongly associated with respiratory diseases, there is a dearth of studies focused on children, especially in China. We aimed to explore the association between extreme temperature and children's outpatient visits for respiratory diseases and seasonal modification effects in Harbin, China. METHODS: A distributed lag nonlinear model (DLNM) was used to explore the effect of extreme temperature on daily outpatient visits for respiratory diseases among children, as well as lag effects and seasonal modification effects. RESULTS: Extremely low temperatures were defined as the 1st percentile and 2.5th percentile of temperature. Extremely high temperatures were defined as the 97.5th percentile and 99th percentile of temperature. At extremely high temperatures, both 26 °C (97.5th) and 27 °C (99th) showed adverse effects at lag 0-6 days, with relative risks (RRs) of 1.34 [95% confidence interval (CI): 1.21-1.48] and 1.38 (95% CI: 1.24-1.53), respectively. However, at extremely low temperatures, both - 26 °C (1st) and - 23 °C (2.5th) showed protective effects on children's outpatient visits for respiratory diseases at lag 0-10 days, with RRs of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.95), respectively. We also found seasonal modification effects, with the association being stronger in the warm season than in the cold season at extremely high temperatures. CONCLUSIONS: Our study indicated that extremely hot temperatures increase the risk of children's outpatient visits for respiratory diseases. Efforts to reduce the exposure of children to extremely high temperatures could potentially alleviate the burden of pediatric respiratory diseases, especially during the warm season.

Deep Learning Based on ResNet-18 for Classification of Prostate Imaging-Reporting and Data System Category 3 Lesions.

RATIONALE AND OBJECTIVES: To explore the classification and prediction efficacy of the deep learning model for benign prostate lesions, non-clinically significant prostate cancer (non-csPCa) and clinically significant prostate cancer (csPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions. MATERIALS AND METHODS: From January 2015 to December 2021, lesions diagnosed with PI-RADS 3 by multi-parametric MRI or bi-parametric MRI were retrospectively included. They were classified as benign prostate lesions, non-csPCa, and csPCa according to the pathological results. T2-weighted images of the lesions were divided into a training set and a test set according to 8:2. ResNet-18 was used for model training. All statistical analyses were performed using Python open-source libraries. The receiver operating characteristic curve (ROC) was used to evaluate the predictive effectiveness of the model. T-SNE was used for image semantic feature visualization. The class activation mapping was used to visualize the area focused by the model. RESULTS: A total of 428 benign prostate lesion images, 158 non-csPCa images and 273 csPCa images were included. The precision in predicting benign prostate disease, non-csPCa and csPCa were 0.882, 0.681 and 0.851, and the area under the ROC were 0.875, 0.89 and 0.929, respectively. Semantic feature analysis showed strong classification separability between csPCa and benign prostate lesions. The class activation map showed that the deep learning model can focus on the area of the prostate or the location of PI-RADS 3 lesions. CONCLUSION: Deep learning model with T2-weighted images based on ResNet-18 can realize accurate classification of PI-RADS 3 lesions.

Regulatory RNAs in Bacillus subtilis: A review on regulatory mechanism and applications in synthetic biology.

Bacteria exhibit a rich repertoire of RNA molecules that intricately regulate gene expression at multiple hierarchical levels, including small RNAs (sRNAs), riboswitches, and antisense RNAs. Notably, the majority of these regulatory RNAs lack or have limited protein-coding capacity but play pivotal roles in orchestrating gene expression by modulating transcription, post-transcription or translation processes. Leveraging and redesigning these regulatory RNA elements have emerged as pivotal strategies in the domains of metabolic engineering and synthetic biology. While previous investigations predominantly focused on delineating the roles of regulatory RNA in Gram-negative bacterial models such as Escherichia coli and Salmonella enterica, this review aims to summarize the mechanisms and functionalities of endogenous regulatory RNAs inherent to typical Gram-positive bacteria, notably Bacillus subtilis. Furthermore, we explore the engineering and practical applications of these regulatory RNA elements in the arena of synthetic biology, employing B. subtilis as a foundational chassis.

Minimizing endogenous cryptic plasmids to construct antibiotic-free expression systems for Escherichia coli Nissle 1917.

The probiotic bacterium Escherichia coli Nissle 1917 (EcN) holds significant promise for use in clinical and biological industries. However, the reliance on antibiotics to maintain plasmid-borne genes has overshadowed its benefits. In this study, we addressed this issue by engineering the endogenous cryptic plasmids pMUT1 and pMUT2. The non-essential elements were removed to create more stable derivatives pMUT1NR△ and pMUT2HBC△. Synthetic promoters by integrating binding motifs on sigma factors were further constructed and applied for expression of Bacteroides thetaiotaomicron heparinase III and the biosynthesis of ectoine. Compared to traditional antibiotic-dependent expression systems, our newly constructed antibiotic-free expression systems offer considerable advantages for clinical and synthetic biology applications.

LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis.

Background The independent contribution of each Liver Imaging Reporting and Data System (LI-RADS) CT or MRI ancillary feature (AF) has not been established. Purpose To evaluate the association of LI-RADS AFs with hepatocellular carcinoma (HCC) and malignancy while adjusting for LI-RADS major features through an individual participant data (IPD) meta-analysis. Materials and Methods Medline, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched from January 2014 to January 2022 for studies evaluating the diagnostic accuracy of CT and MRI for HCC using LI-RADS version 2014, 2017, or 2018. Using a one-step approach, IPD across studies were pooled. Adjusted odds ratios (ORs) and 95% CIs were derived from multivariable logistic regression models of each AF combined with major features except threshold growth (excluded because of infrequent reporting). Liver observation clustering was addressed at the study and participant levels through random intercepts. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2. Results Twenty studies comprising 3091 observations (2456 adult participants; mean age, 59 years ± 11 [SD]; 1849 [75.3%] men) were included. In total, 89% (eight of nine) of AFs favoring malignancy were associated with malignancy and/or HCC, 80% (four of five) of AFs favoring HCC were associated with HCC, and 57% (four of seven) of AFs favoring benignity were negatively associated with HCC and/or malignancy. Nonenhancing capsule (OR = 3.50 [95% CI: 1.53, 8.01]) had the strongest association with HCC. Diffusion restriction (OR = 14.45 [95% CI: 9.82, 21.27]) and mild-moderate T2 hyperintensity (OR = 10.18 [95% CI: 7.17, 14.44]) had the strongest association with malignancy. The strongest negative associations with HCC were parallels blood pool enhancement (OR = 0.07 [95% CI: 0.01, 0.49]) and marked T2 hyperintensity (OR = 0.18 [95% CI: 0.07, 0.45]). Seventeen studies (85%) had a high risk of bias. Conclusion Most LI-RADS AFs were independently associated with HCC, malignancy, or benignity as intended when adjusting for major features. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Crivellaro in this issue.

The effect of different pterygium surgery techniques on the ocular surface parameters in different durations: a systematic review and meta-analysis.

PURPOSE: To evaluate the effects of different pterygium surgery techniques on ocular surface (OS) in different follow-up periods. METHODS: PubMed, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wan Fang, and China Biology Medicine disc were searched for studies reporting pre- and post-operative OS parameters in pterygium. RESULTS: A total of 33 articles were finally included. Three OS parameters showed relatively consistent changing trends after surgery including ocular surface disease index (OSDI), tear film break-up time (BUT), and score of corneal fluorescein staining (SCFS). They worsened significantly at 1w post-operation and then gradually improved: OSDI and BUT showed obvious improvement in 1 m post-operation (SMD = - 0.58, 95%CI = [- 1.04, - 0.13]; SMD = 0.42, 95%CI = [0.06, 0.78]); SCFS was restored to preoperative levels in 3 m after surgery (SMD = - 0.54, 95%CI = [- 1.16, 0.07]). Another parameter, Schirmer test without anesthesia (SIT), presented transient increase at 1w post-operation (SMD = 0.87, 95%CI = [0.27, 1.47]) and presented a relatively stable improvement after 1 m post-operation (SMD = 0.52, 95%CI = [0.16, 0.89]). All parameters in amniotic membrane graft (AMT) showed better improvement in early stage and they showed non-inferior improvements in the long term compared with conjunctival autograft (CAG). Limbal-conjunctival autograft (LCAG) made excellent improvement to OS in the long term while pterygium excision (PE) showed the worst OS. The type of pterygium (primary and secondary), diabetes mellitus (DM) status, and fixation method had certain effects on the results. CONCLUSIONS: OS of pterygium is deteriorated at 1w post-operation then gradually improved to preoperative levels after 1 m post-operation. Among various surgery techniques, LCAG had the best improvement to OS which especially displayed in the long-term outcomes.

The unique properties of tear film breakup process in patients with nasal unilateral pterygium.

SIGNIFICANCE: This study found that the unique properties of tear film breakup process in eyes with pterygium, combined with ocular surface parameters, further revealed specific dynamic mechanism. It suggested that the thickness of pterygium was especially valuable in deciding the necessity of surgical management. PURPOSE: This study aimed to explore the dynamic mechanism of tear film instability in eyes with pterygium. METHODS: A paired-eye controlled cross-sectional study was conducted. Seventy-eight patients with nasal pterygium were enrolled. Fluorescein tear film breakup was observed. Several key parameters related to tear film quality were defined and analyzed, including total breakup area (mathematically derived from pixel size using MATLAB), breakup velocity, fluorescein breakup time, breakup location and pattern, tear meniscus height, score of fluorescein corneal staining, and meiboscore. RESULTS: With comparable tear meniscus height, score of fluorescein corneal staining, and meiboscore between paired eyes (p > 0.05), eyes with pterygium had shorter breakup time, larger breakup area, and faster breakup velocity (p < 0.05). In eyes with pterygium, a positive correlation between meiboscore and pterygium parameters including length, thickness, and size was observed (p > 0.001). As the thickness increased, difference of breakup time and area between paired eyes increased (p = 0.02 and 0.046). Eyes with pterygium had more fixed inferonasal breakup location and often presented as dimple break (60%), whereas random break was the most common in contralateral normal eyes (62%). A unique breakup pattern named pterygium-induced local dimple break was found. It displayed as an irregular but vertical line-like shape appearing after lipid layer spreading, which was adjacent to the lower margin of pterygium and presented with unique properties including inferonasal breakup location, local breakup area, shorten breakup time, and faster breakup velocity. CONCLUSIONS: Eyes with pterygium showed a unique tear film breakup process and novel breakup pattern named pterygium-induced local dimple break . Dynamic mechanism played a significant role in tear film instability of eyes with pterygium rather than aqueous deficiency and increased evaporation.

Advances in the phytochemistry and pharmacology of plant-derived phthalides.

Phthalides are a class of unique compounds such as ligustilide, butylphthalide and butyldenephthalide, which have shown to possess multiple bioactivities in new drug research and development. Phthalides are naturally distributed in different plants that have been utilized as herbal treatments for various ailments with a long history in Asia, Europe and North America. Their extensive biological activity has led to a dramatic increase in the study of phthalide compounds in recent years. This review summarizes the latest research progress of plant-derived phthalides, and a total of 133 phthalide compounds are described based on the characteristics of chemical structures. Pharmacological properties of plant-derived phthalides are associated with hemorheological improvement, vascular function modulation and central nervous system protection. Potential treatments for a variety of diseases mainly including cardio-cerebrovascular disorders and neurological complications such as Alzheimer's disease are also concluded. In addition, key metabolic pathways have been clearly elucidated. Further investigations on the molecular mechanisms involved in biological activity are recommended for offering new insights into profound comprehension of phthalide applications.

Individual Participant Data Meta-Analysis of LR-5 in LI-RADS Version 2018 versus Revised LI-RADS for Hepatocellular Carcinoma Diagnosis.

Background A simplification of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 (v2018), revised LI-RADS (rLI-RADS), has been proposed for imaging-based diagnosis of hepatocellular carcinoma (HCC). Single-site data suggest that rLI-RADS category 5 (rLR-5) improves sensitivity while maintaining positive predictive value (PPV) of the LI-RADS v2018 category 5 (LR-5), which indicates definite HCC. Purpose To compare the diagnostic performance of LI-RADS v2018 and rLI-RADS in a multicenter data set of patients at risk for HCC by performing an individual patient data meta-analysis. Materials and Methods Multiple databases were searched for studies published from January 2014 to January 2022 that evaluated the diagnostic performance of any version of LI-RADS at CT or MRI for diagnosing HCC. An individual patient data meta-analysis method was applied to observations from the identified studies. Quality Assessment of Diagnostic Accuracy Studies version 2 was applied to determine study risk of bias. Observations were categorized according to major features and either LI-RADS v2018 or rLI-RADS assignments. Diagnostic accuracies of category 5 for each system were calculated using generalized linear mixed models and compared using the likelihood ratio test for sensitivity and the Wald test for PPV. Results Twenty-four studies, including 3840 patients and 4727 observations, were analyzed. The median observation size was 19 mm (IQR, 11-30 mm). rLR-5 showed higher sensitivity compared with LR-5 (70.6% [95% CI: 60.7, 78.9] vs 61.3% [95% CI: 45.9, 74.7]; P < .001), with similar PPV (90.7% vs 92.3%; P = .55). In studies with low risk of bias (n = 4; 1031 observations), rLR-5 also achieved a higher sensitivity than LR-5 (72.3% [95% CI: 63.9, 80.1] vs 66.9% [95% CI: 58.2, 74.5]; P = .02), with similar PPV (83.1% vs 88.7%; P = .47). Conclusion rLR-5 achieved a higher sensitivity for identifying HCC than LR-5 while maintaining a comparable PPV at 90% or more, matching the results presented in the original rLI-RADS study. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sirlin and Chernyak in this issue.

Management Strategy for Prostate Imaging Reporting and Data System Category 3 Lesions.

PURPOSE OF REVIEW: Prostate Imaging Reporting and Data System (PI-RADS) category 3 lesions present a clinical dilemma due to their uncertain nature, which complicates the development of a definitive management strategy. These lesions have an incidence rate of approximately 22-32%, with clinically significant prostate cancer (csPCa) accounting for about 10-30%. Therefore, a thorough evaluation is warranted. RECENT FINDINGS: This review highlights the need for radiology peer review, including the confirmation of dynamic contrast-enhanced (DCE) compliance, as the initial step. Additional MRI models such as VERDICT or Tofts need to be verified. Current evidence shows that imaging and clinical indicators can be used for risk stratification of PI-RADS 3 lesions. For low-risk lesions, a safety net monitoring approach involving annual repeat MRI can be employed. In contrast, lesions deemed potentially risky based on prostate-specific antigen density (PSAD), 68 Ga-PSMA PET/CT, MPS, Proclarix, or AI/machine learning models should undergo biopsy. It is recommended to establish a multidisciplinary team that takes into account factors such as age, PSAD, prostate, and lesion size, as well as previous biopsy pathological findings. Combining expert opinions, clinical-imaging indicators, and emerging methods will contribute to the development of management strategies for PI-RADS 3 lesions.