Horizontally Arranged Zn Platelet Deposition Regulated by Bi2O3/Bi toward High-Rate and Dendrite-Free 3D Zn Composite Anode.

Aqueous Zn-metal battery is considered as a promising energy-storage system. However, uncontrolled zinc dendrite growth is the main cause of short-circuit failure in aqueous Zn-based batteries. One of the most efficient and convenient strategies to alleviate this issue is to introduce appropriate zincophilic nucleation sites to guide zinc metal deposition and regulate crystal growth. Herein, this work proposes Bi2O3/Bi nanosheets anchored on the cell wall surface of the 3D porous conductive host as the Zn deposition sites to modulate Zn deposition behavior and hence inhibit the zinc dendrite growth. Density functional theory and experimental results demonstrate that Bi2O3 has a super zinc binding energy and strong adsorption energy with zinc (002) plane, as a super-zincophilic nucleation site, which results in the deposition of zinc preferentially along the horizontal direction of (002) crystal plane, fundamentally avoids the formation of Zn dendrites. Benefiting from the synergistic effect Bi2O3/Bi zincophilic sites and 3D porous structure in the B-BOGC host, the electrochemical performance of the constructed Zn-based battery is significantly improved. As a result, the Zn anode cycles for 1500 cycles at 50 mA cm-2 and 1.0 mAh cm-2. Meanwhile, the Zn@B-BOGC//MnO2 full cell can operate stably for 2000 cycles at 2.0 A g-1.

Extralong hot-spots sensor for SERS sensitive detection of phthalate plasticizers in biological tear and serum fluids.

Phthalate plasticizers (PAEs) illegally used in food pose a great threat to human health. A new and efficient sensing platform for the sensitive detection of the PAE residues in biological fluids needs to be designed and developed. Here, we report a simple and reliable surface-enhanced Raman spectroscopy (SERS) active platform with extralong hot spots of Au nanobipyramids@Ag nanorods (Au NBPs@Ag NRs) for the rapid and sensitive detection of PAEs in biological fluids. To achieve high activity, Au NBPs@Ag NRs with different shell lengths were fabricated by controlling the synthesis conditions, and the corresponding SERS properties were investigated by using crystal violet (CryV) and butyl benzyl phthalate (BBP). The experimental results showed that a longer shell length correlated to greater Raman activity, which was confirmed by finite-difference time-domain (FDTD) electromagnetic simulation. More importantly, the extralong hot spots of the Au NBPs@Ag NR SERS-active substrate showed excellent homogeneity and reproducibility for the CryV probe molecules (6.21%), and the detection limit was 10-9 M for both BBP and diethylhexyl phthalate (DEHP). Furthermore, through the standard addition method, an extralong hot spots SERS substrate could achieve highly sensitive detection of BBP and DEHP in serum and tears fluids, and the detection limit was as low as 3.52 × 10-8 M and 2.82 × 10-8 M. Therefore, the Au NBPs@Ag NR substrate with an extraordinarily long surface is efficient and versatile, and can potentially be used for high-efficiency sensing analysis in complex biological fluids.

Effects of potassium-mediated electrical communication inhibition on nitrogen removal in microbial fuel cells.

Potassium ion signaling mediates microbial communication in electroactive biofilms within microbial fuel cells (MFCs), but its role in nitrogen removal remains unclear. This study investigated the impact of inhibiting potassium signaling on nitrogen removal in MFCs using tetraethylammonium chloride (TEA) as an inhibitor. Results demonstrated that 5 mM and 10 mM TEA reduced the maximum power generation of MFCs from 77.95 mW/cm2 to 57.18 mW/cm2 and 48.23 mW/cm2, respectively. Correspondingly, total nitrogen (TN) removal efficiency was decreased from 46.57 ± 1.01% to 35.93 ± 0.63% and 38.97 ± 0.74%, respectively. This decline was attributed to inhibited potassium ion signaling, which compromised the electrochemical performance of the MFC and hindered the nitrogen removal process. The relative abundance of exoelectrogen Geobactor decreased from 15.37% to 5.17% and 8.05%, while the relative abundance of cathodic nitrifying bacteria Nitrosomonas decreased from 17.87% to 4.92% and 3.63% under 5 mM and 10 mM TEA. These findings underscore the crucial role of potassium ion signaling in enhancing the bioelectrochemical nitrogen removal process in MFCs.

Association between vitamin D level and cataract: A systematic review and meta-analysis.

PURPOSE: The association between serum vitamin D level and cataract remains controversial. This study aims to evaluate the association between vitamin D level and cataract. METHODS: In this study, articles in the PubMed, Web of Science, and EMBASE databases were searched up to 30 August 2023 and 626 articles were screened. Four studies involving a total of 10,928 subjects with cataract and 10,117 control subjects met the inclusion criteria. RESULTS: Decreased serum vitamin D level was associated with higher incidence of cataract (P = 0.047; MD: -4.87; 95%CI: [-9.67, -0.07]). In the subgroup analysis by sex, a significant association was found between serum vitamin D level and cataract in both male (P = 0.01, MD: -2.15,95%CI: [-3.83, -0.46]) and female (P < 0.01; MD: -6.67,95%CI: [-8.20, -5.14]).In the subgroup analysis by the types of cataract, significant association was found between serum vitamin D level and nuclear (P < 0.01; MD: -10.48; 95%CI: [-12.72, -8.24]) and posterior subcapsular cataract (P = 0.02; MD: -6.05; 95%CI: [-11.30, -0.80]) but not in cortical cataract (P = 0.14; MD: -6.74; 95%CI: [-15.70, 2.22]). CONCLUSION: This meta-analysis revealed potential association between serum vitamin D level and cataract, more significant in female, and the subtypes of nuclear and posterior subcapsular cataract.

Discovery of the Natural Bibenzyl Compound Erianin in Dendrobium Inhibiting the Growth and EMT of Gastric Cancer through Downregulating the LKB1-SIK2/3-PARD3 Pathway.

Erianin, a bibenzyl compound found in dendrobium extract, has demonstrated broad anticancer activity. However, its mechanism of action in gastric cancer (GC) remains poorly understood. LKB1 is a tumor-suppressor gene, and its mutation is an important driver of various cancers. Yet some studies have reported contradictory findings. In this study, we combined bioinformatics and in vitro and in vivo experiments to investigate the effect and potential mechanism of Erianin in the treatment of GC. The results show that LKB1 was highly expressed in patients' tumor tissues and GC cells, and it was associated with poor patient prognosis. Erianin could promote GC cell apoptosis and inhibit the scratch repair, migration, invasion, and epithelial-mesenchymal transition (EMT) characteristics. Erianin dose-dependently inhibited the expression of LKB1, SIK2, SIK3, and PARD3 but had no significant effect on SIK1. Erianin also inhibited tumor growth in CDX mice model. Unexpectedly, 5-FU also exhibited a certain inhibitory effect on LKB1. The combination of Erianin and 5-FU significantly improved the anti-tumor efficacy of 5-FU in the growth of GC cells and xenograft mouse models. In summary, Erianin is a potential anti-GC compound that can inhibit GC growth and EMT properties by targeting the LKB1-SIK2/3-PARD3-signaling axis. The synergistic effect of Erianin and 5-FU suggests a promising therapeutic strategy for GC treatment.

Machine learning-driven prediction of phosphorus adsorption capacity of biochar: Insights for adsorbent design and process optimization.

Phosphorus (P) pollution in aquatic environments poses significant environmental challenges, necessitating the development of effective remediation strategies, and biochar has emerged as a promising adsorbent for P removal at the cost of extensive research resources worldwide. In this study, a machine learning approach was proposed to simulate and predict the performance of biochar in removing P from water. A dataset consisting of 190 types of biochar was compiled from literature, encompassing various variables including biochar characteristics, water quality parameters, and operating conditions. Subsequently, the random forest and CatBoost algorithms were fine-tuned to establish a predictive model for P adsorption capacity. The results demonstrated that the optimized CatBoost model exhibited high prediction accuracy with an R2 value of 0.9573, and biochar dosage, initial P concentration in water, and C content in biochar were identified as the predominant factors. Furthermore, partial dependence analysis was employed to examine the impact of individual variables and interactions between two features, providing valuable insights for adsorbent design and operating condition optimization. This work presented a comprehensive framework for applying a machine learning approach to address environmental issues and provided a valuable tool for advancing the design and implementation of biochar-based water treatment systems.

Comparison of Disease Severity, Anxiety and Depression in Obsessive-Compulsive Disorder Patients with Different Insight.

BACKGROUND: Significant individual differences exist in the insight of patients with obsessive-compulsive disorder (OCD), and the clinical characteristics of OCD patients with varying levels of insight are not entirely uniform. This study aims to investigate disparities in disease severity, anxiety, and depression status among OCD patients with differing levels of insight, with the goal of generating novel treatment strategies for OCD. METHODS: A total of 114 patients diagnosed with OCD were recruited from the Department of Psychology at Affiliated Mental Health Center & Hangzhou Seventh People's Hospital to participate in this research. Based on their Total Insight and Treatment Attitude Questionnaire (ITAQ) scores, the patients were divided into two groups: Group OCD with high insight (referred to as Group OCD-HI, ITAQ score ≥20 points, n = 80) and Group OCD with low insight (referred to as Group OCD-LI, ITAQ score <20 points, n = 34). Subsequently, the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD) scores were compared between the two groups. All questionnaires for this study were completed by experienced psychiatrists. RESULTS: The Y-BOCS scores for YB1, YB2, YB4, YB5, YB6, YB9, and the total Y-BOCS scores in Group OCD-HI were significantly higher than those in Group OCD-LI (p < 0.05). Conversely, Group OCD-HI exhibited significantly lower HAMA and HAMD scores compared to Group OCD-LI (p < 0.05). Furthermore, the total ITAQ score displayed a significant negative correlation with the total Y-BOCS, HAMA, and HAMD scores (p < 0.05). CONCLUSIONS: This study revealed that certain OCD patients exhibit incomplete insight, and this lack of insight is strongly associated with increased disease severity and heightened levels of anxiety and depression. It is hoped that by enhancing the insight of OCD patients, the goal of ameliorating disease symptoms and alleviating negative emotions can be attained.

Anchoring Polar Organic Molecules in Defective Ammonium Vanadate for High-Performance Flexible Aqueous Zinc-Ion Battery.

Ammonium vanadate (NVO) often has unsatisfactory electrochemical performance due to the irreversible removal of NH4 + during the reaction. Herein, layered DMF-NVO nanoflake arrays (NFAs) grown on highly conductive carbon cloth (CC) are employed as the binder-free cathode (DMF-NVO NFAs/CC), which produces an enlarged interlayer spacing of 12.6 Å (against 9.5 Å for NH4 V4 O10 ) by effective N, N-dimethylformamide (DMF) intercalation. Furthermore, the strong attraction of highly polar carbonyl and ammonium ions in DMF can stabilize the lattice structure, and low-polar alkyl groups can interact with the weak electrostatic generated by Zn2+ , which allows Zn2+ to be freely intercalated. The DMF-NVO NFAs/CC//Zn battery exhibits an impressive high capacity of 536 mAh g-1 at 0.5 A g-1 , excellent rate capability, and cycling performance. The results of density functional theory simulation demonstrate that the intercalation of DMF can significantly reduce the band gap and the diffusion barrier of Zn2+ , and can also accommodate more Zn2+ . The assembled flexible aqueous rechargeable zinc ion batteries (FARZIBs) exhibit outstanding energy density and power density, up to 436 Wh kg-1 at 400 W kg-1 , and still remains 180 Wh kg-1 at 4000 W kg-1 . This work can provide a reference for the design of cathode materials for high-performance FARZIBs.

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for advanced hepatocellular carcinoma (Ad-HCC). As identifying patients with Ad-HCC who would obtain objective response (OR) to HAIC preoperatively remains a challenge, we aimed to develop an automatic and non-invasive model for predicting HAIC response. METHODS: A total of 458 patients with Ad-HCC who underwent HAIC were retrospectively included from three hospitals (310 for training, 77 for internal validation, and 71 for external validation). The deep learning and radiomic features were extracted from the automatically segmented liver region on contrast-enhanced computed tomography images. Then, a deep learning radiomic nomogram (DLRN) was constructed by integrating deep learning scores, radiomic scores, and significant clinical variables with multivariate logistic regression. Model performance was assessed by AUC and Kaplan-Meier estimator. RESULTS: After automatic segmentation, only a few modifications were needed (less than 30 min for 458 patients). The DLRN achieved an AUC of 0.988 in the training cohort, 0.915 in the internal validation cohort, and 0.896 in the external validation cohort, respectively, outperforming other models in HAIC response prediction. Moreover, survival risk stratification was also successfully performed by the DLRN. The overall survival (OS) of the predictive OR group was significantly longer than that of the predictive non-OR group (median OS: 26.0 vs. 12.3 months, p < 0.001). CONCLUSIONS: The DLRN provided a satisfactory performance for predicting HAIC response, which is essential to identify Ad-HCC patients for HAIC and may potentially benefit personalized pre-treatment decision-making. CLINICAL RELEVANCE STATEMENT: This study presents an accurate and automatic method for predicting response to hepatic arterial infusion chemotherapy in patients with advanced hepatocellular carcinoma, and therefore help in defining the best candidates for this treatment. KEY POINTS: • Deep learning radiomic nomogram (DLRN) based on automatic segmentation of CECT can accurately predict hepatic arterial infusion chemotherapy (HAIC) response of advanced HCC patients. • The proposed prediction model can perform survival risk stratification and is an easy-to-use tool for personalized pre-treatment decision-making for advanced HCC patients.

Fads2b Plays a Dominant Role in ∆6/∆5 Desaturation Activities Compared with Fads2a in Common Carp (Cyprinus carpio).

Highly unsaturated fatty acids (HUFAs) are essential for mammalian health, development and growth. However, most mammals, including humans, are incapable of synthesizing n-6 and n-3 HUFAs. Fish can convert C18 unsaturated fatty acids into n-6 and n-3 HUFAs via fatty acid desaturase (Fads), in which Fads2 is a key enzyme in HUFA biosynthesis. The allo-tetraploid common carp theoretically encode two duplicated fads2 genes. The expression patterns and desaturase functions of these two homologous genes are still unknown. In this study, the full length of the fads2a and fads2b were identified in common carp (Cyprinus carpio). Expression analyses indicate that both genes were mainly expressed in the liver and the expression of fads2b is higher than fads2a at different developmental stages in carp embryos. Heterogenous expression and 3D docking analyses suggested that Fads2b demonstrated stronger ∆6 and ∆5 desaturase activities than Fads2a. The core promotor regions of fads2a and fads2b were characterized and found to have different potential transcriptional binding sites. These results revealed the same desaturase functions, but different activities of two homologues of fasd2 genes in common carp. The data showed that fads2b played a more important role in HUFA synthesis through both expression and functional analyses.

[Cross subject personality assessment based on electroencephalogram functional connectivity and domain adaptation].

The research shows that personality assessment can be achieved by regression model based on electroencephalogram (EEG). Most of existing researches use event-related potential or power spectral density for personality assessment, which can only represent the brain information of a single region. But some research shows that human cognition is more dependent on the interaction of brain regions. In addition, due to the distribution difference of EEG features among subjects, the trained regression model can not get accurate results of cross subject personality assessment. In order to solve the problem, this research proposes a personality assessment method based on EEG functional connectivity and domain adaption. This research collected EEG data from 45 normal people under different emotional pictures (positive, negative and neutral). Firstly, the coherence of 59 channels in 5 frequency bands was taken as the original feature set. Then the feature-based domain adaptation was used to map the feature to a new feature space. It can reduce the distribution difference between training and test set in the new feature space, so as to reduce the distribution difference between subjects. Finally, the support vector regression model was trained and tested based on the transformed feature set by leave-one-out cross-validation. What's more, this paper compared the methods used in previous researches. The results showed that the method proposed in this paper improved the performance of regression model and obtained better personality assessment results. This research provides a new method for personality assessment.

Thyroid Disease Is Associated with Higher Age-Related Macular Degeneration Risk: Results from a Meta-Analysis of Epidemiologic Studies.

BACKGROUND: Although epidemiologic studies have suggested that thyroid disease may be a risk factor for age-related macular degeneration (AMD), this finding is still controversial. OBJECTIVES: The aim of this meta-analysis was to investigate whether an association exists between thyroid disease and medication and AMD in epidemiologic studies. METHODS: We searched PubMed, EMBASE, and Google Scholar from their inception to March 2020 for cross-sectional, case-control, and cohort studies that assessed thyroid function and AMD risk. Data from selected studies were extracted, and a meta-analysis was performed using fixed-effects or random-effects models. The statistical heterogeneity (I2) among studies and the possibility of publication bias were evaluated. If I2 >50%, a significant heterogeneity existed among studies, and a random-effects model was used to calculate the pooled RR. Otherwise, a fixed-effects model was performed. RESULTS: A total of 13 epidemiologic studies that consisted of 7 thyroid disease and 7 thyroid medication studies were included. Statistically significant heterogeneity was observed in the study results (I2thyroid disease = 80.1%; I2thyroid medication = 69.0%). A significant positive association was found between thyroid disease and AMD, with an overall relative risk (RR) of 1.25 (95% CI: 1.02, 1.54). However, there was no statistical association between thyroid medication and AMD risk (pooled RR 1.26 [95% CI: 0.92-1.72]). Egger's test indicated that there was no significant publication bias for thyroid disease (p = 0.889) or thyroid medication (p = 0.226). CONCLUSIONS: Our findings indicate that thyroid disease is associated with higher AMD risk. Thyroid disease prevention strategies may have a significant effect on the prevention of AMD and warrant further evaluation.

"Magnet" Based on Activated Silver Nanoparticles Adsorbed Bacteria to Predict Refractory Apical Periodontitis Via Surface-Enhanced Raman Scattering.

Refractory apical periodontitis (RAP) is an endodontic apical inflammatory disease caused by Enterococcus faecalis (E. faecalis). Bacterial detection using surface-enhanced Raman scattering (SERS) technology is a hot research topic, but the specific and direct detection of oral bacteria is a challenge, especially in real clinical samples. In this paper, we develop a novel SERS-based green platform for label-free detection of oral bacteria. The platform was built on silver nanoparticles with a two-step enhancement way using NaBH4 and sodium (Na+) to form "hot spots," which resulted in an enhanced SERS fingerprint of E. faecalis with fast, quantitative, lower-limit, reproducibility, and stability. In combination with machine learning, four different oral bacteria (E. faecalis, Porphyromonas gingivalis, Streptococcus mutans, and Escherichia coli) could be intelligently distinguished. The unlabeled detection method emphasized the specificity of E. faecalis in simulated saliva, serum, and even real samples from patients with clinical root periapical disease. In addition, the assay has been shown to be environmentally friendly and without secondary contamination through antimicrobial assays. The proposed label-free, rapid, safe, and green SERS detection strategy for oral bacteria provided an innovative solution for the early diagnosis and prevention of RAP and other perioral diseases.

Research progress on the pharmacological mechanism, in vivo metabolism and structural modification of Erianin.

Erianin is an important bibenzyl compound in dendrobium and has a wide spectrum of pharmacological properties. Since Erianin was discovered, abundant results have been achieved in the in vitro synthesis, structural modification, and pharmacological mechanism research. Researchers have developed a series of simple and efficient in vitro synthesis methods to improve the shortcomings of poor water solubility by replacing the chemical structure or coating it in nanomaterials. Erianin has a broad anti-tumor spectrum and significant anti-tumor effects. In addition, Erianin also has pharmacological actions like immune regulation, anti-inflammatory, and anti-angiogenesis. A comprehensive understanding of the synthesis, metabolism, structural modification, and pharmacological action pathways of Erianin is of great value for the utilization of Erianin. Therefore, this review conducts a relatively systematic look back at Erianin from the above four aspects, to give a reference for the evolvement and further appliance of Erianin.

Interpreting the Mechanism of Active Ingredients in Polygonati Rhizoma in Treating Depression by Combining Systemic Pharmacology and In Vitro Experiments.

Polygonati Rhizoma (PR) has certain neuroprotective effects as a homology of medicine and food. In this study, systematic pharmacology, molecular docking, and in vitro experiments were integrated to verify the antidepressant active ingredients in PR and their mechanisms. A total of seven compounds in PR were found to be associated with 45 targets of depression. Preliminarily, DFV docking with cyclooxygenase 2 (COX2) showed good affinity. In vitro, DFV inhibited lipopolysaccharide (LPS)-induced inflammation of BV-2 cells, reversed amoeba-like morphological changes, and increased mitochondrial membrane potential. DFV reversed the malondialdehyde (MDA) overexpression and superoxide dismutase (SOD) expression inhibition in LPS-induced BV-2 cells and decreased interleukin-1ß (IL-1ß), tumor necrosis factor-α (TNF-α), and IL-6 mRNA expression levels in a dose-dependent manner. DFV inhibited both mRNA and protein expression levels of COX2 induced by LPS, and the activation of NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) and caspase1 was suppressed, thus exerting an antidepressant effect. This study proves that DFV may be an important component basis for PR to play an antidepressant role.

Immune-like sandwich multiple hotspots SERS biosensor for ultrasensitive detection of NDKA biomarker in serum.

Developing the rapid, specific, and sensitive tumor marker NDKA biosensor has become an urgent need in the field of early diagnosis of colorectal cancer (CRC). Surface-enhanced Raman spectroscopy (SERS) with the advantages of high sensitivity, high resolution as well as providing sample fingerprint, enables rapid and sensitive detection of tumor markers. However, many SERS biosensors rely on boosting the quantity of Raman reporter molecules on individual nanoparticle surfaces, which can result in nanoparticle agglomeration, diminishing the stability and sensitivity of NDKA detection. Here, we proposed an immune-like sandwich multiple hotspots SERS biosensor for highly sensitive and stable analysis of NDKA in serum based on molecularly imprinted polymers and NDKA antibody. The SERS biosensor employs an array of gold nanoparticles, which are coated with a biocompatible polydopamine molecularly imprinted polymer as a substrate to specifically capture NDKA. Then the biosensor detects NDKA through Raman signals as a result of the specific binding of NDKA to the SERS nanotag affixed to the capture substrate along with the formation of multiple hotspots. This SERS biosensor not only avoids the aggregation of nanoparticles but also presents a solution to the obstacles encountered in immune strategies for certain proteins lacking multiple antibody or aptamer binding sites. Furthermore, the practical application of the SERS biosensor is validated by the detection of NDKA in serum with the lower limit of detection (LOD) of 0.25 pg/mL, meanwhile can detect NDKA of 10 ng/mL in mixed proteins solution, illustrating high sensitivity and specificity. This immune-like sandwich multiple hotspots biosensor makes it quite useful for the early detection of CRC and also provides new ideas for cancer biomarker sensing strategy in the future.

Novel 3D morphological characteristics for congenital biliary dilatation diagnosis: a case-control study.

BACKGROUND: Congenital biliary dilatation (CBD) necessitates the timely removal of dilated bile ducts. Accurate differentiation between CBD and secondary biliary dilatation (SBD) is crucial for treatment decisions, and identification of CBD with intrahepatic involvement is vital for surgical planning and supportive care. This study aimed to develop quantitative models based on bile duct morphology to distinguish CBD from SBD and further identify CBD with intrahepatic involvement. MATERIALS AND METHODS: The retrospective study included 131 CBD and 209 SBD patients between December 2014 and December 2021 for model development, internal validation, and testing. A separate cohort of 15 CBD and 34 SBD patients between January 2022 and December 2022 was recruited for temporally-independent validation. Quantitative shape-based (Shape) and diameter-based (Diam) morphological characteristics of bile ducts were extracted to build a CBD diagnosis model to distinguish CBD from SBD and an intrahepatic involvement identification model to classify CBD with/without intrahepatic involvement. The diagnostic performance of the models was compared with that of experienced hepatobiliary surgeons. RESULTS: The CBD diagnosis model using clinical, Shape, and Diam characteristics showed good performance with an AUROC of 0.942 (95% CI: 0.890-0.994), AUPRC of 0.917 (0.855-0.979), accuracy of 0.891, sensitivity of 0.950, and F1-score of 0.864. The model outperformed two experienced surgeons in accuracy, sensitivity, and F1-score. The intrahepatic involvement identification model using clinical, Shape, and Diam characteristics yielded outstanding performance with an AUROC of 0.944 (0.879-1.000), AUPRC of 0.982 (0.947-1.000), accuracy of 0.932, sensitivity of 0.971, and F1-score of 0.957. The models demonstrated generalizable performance on the temporally-independent validation cohort. CONCLUSIONS: This study developed two robust quantitative models for distinguishing CBD from SBD and identifying CBD with intrahepatic involvement, respectively, based on morphological characteristics of the bile ducts, showing great potential in risk stratification and surgical planning of CBD.

Altered fatty acid distribution in lysosome-associated membrane protein-2 deficient mice.

Lysosome-associated membrane protein-2 (LAMP2) deficiency causes the human Danon disease and represents a lysosomal dysfunction because of its pivotal role in regulating autophagy and lysosome biogenesis. LAMP2-deficient mice exhibit a spectrum of phenotypes, including cardioskeletal myopathy, mental retardation, and retinopathy, similar to those observed in patients with Danon disease. Its pathology is thought to involve altered energy metabolism and lipid dysregulation; however, the lipidomic profiles of LAMP2-deficient animals have not been investigated. In this study, we investigated lipid alterations in LAMP2 KO mice tissues, including those of the liver, plasma, and retina, using liquid chromatography-mass spectrometry. Our results revealed significantly increased free fatty acid (FFA) levels and decreased in triglyceride (TG) levels in LAMP2 KO liver tissues at three and six months. Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) species significantly decreased in LAMP2 KO mice livers at six months. Similarly, plasma TG and PC/PE levels decreased in LAMP2 KO mice. In contrast, plasma FFA levels were significantly lower in LAMP2 KO mice. Retina FFA levels were elevated in LAMP2 KO mice, accompanied by a partial decrease in PC/PE at six months. In summary, FFA levels increased in several tissues but not in the LAMP2 KO mice plasma, suggesting the potential consumption of FFA as an energy source in the peripheral tissues. The depletion of TG and PC/PE accelerated with age, suggesting an underlying age-dependent energy crisis condition. Our findings underscore the dysregulated distribution of fatty acids in LAMP2-deficient animals and provide new mechanistic insights into the pathology of Danon disease.

Blood-brain barrier breakdown in dementia with Lewy bodies.

BACKGROUND: Blood-brain barrier (BBB) dysfunction has been viewed as a potential underlying mechanism of neurodegenerative disorders, possibly involved in the pathogenesis and progression of Alzheimer's disease (AD). However, a relation between BBB dysfunction and dementia with Lewy bodies (DLB) has yet to be systematically investigated. Given the overlapping clinical features and neuropathology of AD and DLB, we sought to evaluate BBB permeability in the context of DLB and determine its association with plasma amyloid-ß (Aß) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: For this prospective study, we examined healthy controls (n = 24, HC group) and patients diagnosed with AD (n = 29) or DLB (n = 20) between December 2020 and April 2022. Based on DCE-MRI studies, mean rates of contrast agent transfer from intra- to extravascular spaces (Ktrans) were calculated within regions of interest. Spearman's correlation and multivariate linear regression were applied to analyze associations between Ktrans and specific clinical characteristics. RESULTS: In members of the DLB (vs HC) group, Ktrans values of cerebral cortex (p = 0.024), parietal lobe (p = 0.007), and occipital lobe (p = 0.014) were significantly higher; and Ktrans values of cerebral cortex (p = 0.041) and occipital lobe (p = 0.018) in the DLB group were significantly increased, relative to those of the AD group. All participants also showed increased Ktrans values of parietal ( ß  = 0.391; p = 0.001) and occipital ( ß  = 0.357; p = 0.002) lobes that were significantly associated with higher scores of the Clinical Dementia Rating, once adjusted for age and sex. Similarly, increased Ktrans values of cerebral cortex ( ß  = 0.285; p = 0.015), frontal lobe ( ß  = 0.237; p = 0.043), and parietal lobe ( ß = 0.265; p = 0.024) were significantly linked to higher plasma Aß1-42/Aß1-40 ratios, after above adjustments. CONCLUSION: BBB leakage is a common feature of DLB and possibly is even more severe than in the setting of AD for certain regions of the brain. BBB leakage appears to correlate with plasma Aß1-42/Aß1-40 ratio and dementia severity.

Cisplatin resistance-related transcriptome and methylome integration identifies PCDHB4 as a novel prognostic biomarker in small cell lung cancer.

Platinum-based chemo-resistance is the major issue for the treatment of small cell lung cancer (SCLC). The integrative analysis of multi-omics data is a reliable approach for discovering novel biomarkers associated with chemo-resistance. Here, multi-omics integrative analysis and Cox regression found that higher expression of PCDHB4 was associated with poorer survival of SCLC patients who received chemotherapy. PCDHB4 gene was hypomethylated and upregulated in SCLC, which was validated in the levels of promoter methylation, mRNA, and protein expression. Mechanistically, using bulk RNA-seq data, functional enrichment analysis indicated that higher PCDHB4 expression was associated with lower immune infiltration. The analysis of single-cell RNA-seq (scRNA-seq) found that SCLC cells with PCDHB4 expression exhibited the characteristics of stemness and EMT. In addition, the high expression and hypomethylation of PCDHB4 were also significantly associated with poor survival in lung squamous cell carcinoma. In summary, PCDHB4 is a potential prognostic biomarker of platinum-based chemotherapy in SCLC.