Surface profile measurement and parameter analysis of silicon wafers in the upright state.

A novel approach, to the best of our knowledge, is presented for assessing silicon wafer surface profiles using an interferometer and vertically rotatable wafer holder. This approach significantly enhances precision and reduces costs, and outperforms traditional techniques in measurement consistency and accuracy. It effectively reduces sample distortion and positional shifts owing to the removal and reinstallation of the wafers. Using this method, a global backsurface-referenced ideal range of 0.385 µm, warp of 0.193 µm, and other parameters were obtained, demonstrating its practicality in efficiently capturing key surface profile metrics for silicon wafers. This innovation promises substantial improvements in high-volume wafer surface profile testing, overcoming prevalent technological challenges in this industry.

Cellular heterogeneity and dynamics of the human uterus in healthy premenopausal women.

The human uterus is a complex and dynamic organ whose lining grows, remodels, and regenerates in every menstrual cycle or upon tissue damage. Here we applied single-cell RNA sequencing to profile more the 50,000 uterine cells from both the endometrium and myometrium of 5 healthy premenopausal individuals, and jointly analyzed the data with a previously published dataset from 15 subjects. The resulting normal uterus cell atlas contains more than 167K cells representing the lymphatic endothelium, blood endothelium, stromal, ciliated epithelium, unciliated epithelium, and immune cell populations. Focused analyses within each major cell type and comparisons with subtype labels from prior studies allowed us to document supporting evidence, resolve naming conflicts, and to propose a consensus annotation system of 39 subtypes. We release their gene expression centroids, differentially expressed genes, and mRNA patterns of literature-based markers as a shared community resource. We find many subtypes show dynamic changes over different phases of the cycle and identify multiple potential progenitor cells: compartment-wide progenitors for each major cell type, transitional cells that are upstream of other subtypes, and potential cross-lineage multipotent stromal progenitors that may be capable of replenishing the epithelial, stromal, and endothelial compartments. When compared to the healthy premenopausal samples, a postpartum and a postmenopausal uterus sample revealed substantially altered tissue composition, involving the rise or fall of stromal, endothelial, and immune cells. The cell taxonomy and molecular markers we report here are expected to inform studies of both basic biology of uterine function and its disorders. SIGNIFICANCE: We present single-cell RNA sequencing data from seven individuals (five healthy pre-menopausal women, one post-menopausal woman, and one postpartum) and perform an integrated analysis of this data alongside 15 previously published scRNA-seq datasets. We identified 39 distinct cell subtypes across four major cell types in the uterus. By using RNA velocity analysis and centroid-centroid comparisons we identify multiple computationally predicted progenitor populations for each of the major cell compartments, as well as potential cross-compartment, multi-potent progenitors. While the function and interactions of these cell populations remain to be validated through future experiments, the markers and their "dual characteristics" that we describe will serve as a rich resource to the scientific community. Importantly, we address a significant challenge in the field: reconciling multiple uterine cell taxonomies being proposed. To achieve this, we focused on integrating historical and contemporary knowledge across multiple studies. By providing detailed evidence used for cell classification we lay the groundwork for establishing a stable, consensus cell atlas of the human uterus.

Assessment of Lung Nodule Detection and Lung CT Screening Reporting and Data System Classification Using Zero Echo Time Pulmonary MRI.

BACKGROUND: The detection rate of lung nodules has increased considerably with CT as the primary method of examination, and the repeated CT examinations at 3 months, 6 months or annually, based on nodule characteristics, have increased the radiation exposure of patients. So, it is urgent to explore a radiation-free MRI examination method that can effectively address the challenges posed by low proton density and magnetic field inhomogeneities. PURPOSE: To evaluate the potential of zero echo time (ZTE) MRI in lung nodule detection and lung CT screening reporting and data system (lung-RADS) classification, and to explore the value of ZTE-MRI in the assessment of lung nodules. STUDY TYPE: Prospective. POPULATION: 54 patients, including 21 men and 33 women. FIELD STRENGTH/SEQUENCE: Chest CT using a 16-slice scanner and ZTE-MRI at 3.0T based on fast gradient echo. ASSESSMENT: Nodule type (ground-glass nodules, part-solid nodules, and solid nodules), lung-RADS classification, and nodule diameter (manual measurement) on CT and ZTE-MRI images were recorded. STATISTICAL TESTS: The percent of concordant cases, Kappa value, intraclass correlation coefficient (ICC), Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman. The p-value <0.05 is considered significant. RESULTS: A total of 54 patients (age, 54.8 ± 11.9 years; 21 men) with 63 nodules were enrolled. Compared with CT, the total nodule detection rate of ZTE-MRI was 85.7%. The intermodality agreement of ZTE-MRI and CT lung nodules type evaluation was substantial (Kappa = 0.761), and the intermodality agreement of ZTE-MRI and CT lung-RADS classification was moderate (Kappa = 0.592). The diameter measurements between ZTE-MRI and CT showed no significant difference and demonstrated a high degree of interobserver (ICC = 0.997-0.999) and intermodality (ICC = 0.956-0.985) agreements. DATA CONCLUSION: The measurement of nodule diameter by pulmonary ZTE-MRI is similar to that by CT, but the ability of lung-RADS to classify nodes from MRI images still requires further research. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Maintenance pembrolizumab therapy in patients with metastatic HER2-negative breast cancer with prior response to chemotherapy.

PURPOSE: Accumulating toxicities hinder indefinite chemotherapy for many patients with metastatic/recurrent HER2-negative breast cancer. We conducted a phase II trial of pembrolizumab monotherapy following induction chemotherapy to determine the efficacy of maintenance immunotherapy in patients with metastatic HER2-negative inflammatory breast cancer (IBC) and non-IBC triple-negative breast cancer (TNBC) and a biomarker study. PATIENTS AND METHODS: Patients with a complete response (CR), partial response (PR), or stable disease (SD) after at least 3 cycles of chemotherapy for HER2-negative breast cancer received pembrolizumab, regardless of programmed death-ligand 1 expression. Pembrolizumab (200 mg) was administered every 3 weeks until disease progression, intolerable toxicity, or 2 years of pembrolizumab exposure. The endpoints included the 4-month disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and response biomarkers in the blood. RESULTS: Of 43 treated patients, 11 had metastatic IBC and 32 non-IBC TNBC. The 4-month DCR was 58.1% (95% CI, 43.4%-72.9%). For all patients, the median PFS was 4.8 months (95% CI, 3.0-7.1 months). The toxicity profile was similar to the previous pembrolizumab monotherapy study. Patients with high T-cell clonality at baseline had a longer PFS with pembrolizumab treatment than did those with low T-cell clonality (10.4 vs. 3.6 months, p = 0.04). Patients who achieved SD also demonstrated a significant increase in T-cell clonality during therapy compared to those who didn't achieve SD (20% vs. 5.9% mean increase, respectively; p = 0.04). CONCLUSIONS: Pembrolizumab monotherapy achieved durable treatment responses. Patients with a high baseline T-cell clonality had prolonged disease control with pembrolizumab.

Machine learning approaches for practical predicting outpatient near-future AECOPD based on nationwide electronic medical records.

In this research, we aimed to harness machine learning to predict the imminent risk of acute exacerbation in chronic obstructive pulmonary disease (AECOPD) patients. Utilizing retrospective data from electronic medical records of two Taiwanese hospitals, we identified 26 critical features. To predict 3- and 6-month AECOPD occurrences, we deployed five distinct machine learning algorithms alongside ensemble learning. The 3-month risk prediction was best realized by the XGBoost model, achieving an AUC of 0.795, whereas the XGBoost was superior for the 6-month prediction with an AUC of 0.813. We conducted an explainability analysis and found that the episode of AECOPD, mMRC score, CAT score, respiratory rate, and the use of inhaled corticosteroids were the most impactful features. Notably, our approach surpassed predictions that relied solely on CAT or mMRC scores. Accordingly, we designed an interactive prediction system that provides physicians with a practical tool to predict near-term AECOPD risk in outpatients.

Cellular atlas of the human ovary using morphologically guided spatial transcriptomics and single-cell sequencing.

The reproductive and endocrine functions of the ovary involve spatially defined interactions among specialized cell populations. Despite the ovary's importance in fertility and endocrine health, functional attributes of ovarian cells are largely uncharacterized. Here, we profiled >18,000 genes in 257 regions from the ovaries of two premenopausal donors to examine the functional units in the ovary. We also generated single-cell RNA sequencing data for 21,198 cells from three additional donors and identified four major cell types and four immune cell subtypes. Custom selection of sampling areas revealed distinct gene activities for oocytes, theca, and granulosa cells. These data contributed panels of oocyte-, theca-, and granulosa-specific genes, thus expanding the knowledge of molecular programs driving follicle development. Serial samples around oocytes and across the cortex and medulla uncovered previously unappreciated variation of hormone and extracellular matrix remodeling activities. This combined spatial and single-cell atlas serves as a resource for future studies of rare cells and pathological states in the ovary.

Exercise training influence on cognitive capacity and mental health within chronic obstructive pulmonary disease - A pilot study.

Objective: Although pulmonary rehabilitation and regular exercise have improved negative emotions and cognitive capacity within cases of chronic obstructive pulmonary disease (COPD), influence by exercise training upon different cognitive and memory functions in COPD is still controversial. This investigation aimed to assess whether cognitive performance and mental health are affected by the benefits of exercise training within cases of COPD. Materials and Methods: This pilot investigation included thirty-three patients with Global Initiative for Chronic Obstructive Lung Disease stage ≥B. Based on the subjects' rights, all included patients could choose to join either the exercise group or the control group, according to their free will. Twelve patients were assigned to receive exercise treatment over a 2-month period, while the remaining 16 patients were assigned to the control group. Cognitive capacity outcomes were measured using the Wechsler Memory Scale-III Word List Test, Stroop task, and psychomotor vigilance task (PVT). Mood states were assessed through the Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI). Results: Most cases demonstrated major improvement for BDI and BAI scorings post-60-day therapy. During PVT, the omission rate decreased, while the hit rate increased, indicating an improvement in attention performance. Furthermore, this investigation found a significant increase in immediate verbal and recognition memory for word-list test. However, no major performance shifts were found on Stroop analysis. Conclusion: This investigation demonstrated that a 2-month exercise training program resulted in significant improvement in negative emotions, immediate memory, recognition memory, and attention.

Age and sex estimation in cephalometric radiographs based on multitask convolutional neural networks.

OBJECTIVES: Age and sex characteristics are evident in cephalometric radiographs (CRs), yet their accurate estimation remains challenging due to the complexity of these images. This study aimed to harness deep learning to automate age and sex estimation from CRs, potentially simplifying their interpretation. STUDY DESIGN: We compared the performance of 4 deep learning models (SVM, R-net, VGG16-SingleTask, and our proposed VGG16-MultiTask) in estimating age and sex from the testing dataset, utilizing a VGG16-based multitask deep learning model on 4,557 CRs. Gradient-weighted class activation mapping (Grad-CAM) was incorporated to identify sex. Performance was assessed using mean absolute error (MAE), specificity, sensitivity, F1 score, and the area under the curve (AUC) in receiver operating characteristic analysis. RESULTS: The VGG16-MultiTask model outperformed the others, with the lowest MAE (0.864±1.602) and highest sensitivity (0.85), specificity (0.88), F1 score (0.863), and AUC (0.93), demonstrating superior efficacy and robust performance. CONCLUSIONS: The VGG multitask model demonstrates significant potential in enhancing age and sex estimation from cephalometric analysis, underscoring the role of AI in improving biomedical interpretations.

NLRC4 methylation and its response to intravenous immunoglobulin therapy in Kawasaki disease: a case control study.

BACKGROUND: Kawasaki disease (KD) is a systemic vasculitis accompanied by many systemic physiological and biochemical changes. Elucidating its molecular mechanisms is crucial for diagnosing and developing effective treatments. NLR Family CARD Domain Containing 4 (NLRC4) encodes the key components of inflammasomes that function as pattern recognition receptors. The purpose of this study was to investigate the potential of NLRC4 methylation as a biomarker for KD. METHODS: In this study, pyrosequencing was utilized to analyze NLRC4 promoter methylation in blood samples from 44 children with initial complete KD and 51 matched healthy controls. Methylation at five CpG sites within the NLRC4 promoter region was evaluated. RESULTS: Compared to controls, NLRC4 methylation significantly decreased in KD patients (CpG1: p = 2.93E-06; CpG2: p = 2.35E-05; CpG3: p = 6.46E-06; CpG4: p = 2.47E-06; CpG5: p = 1.26E-05; average methylation: p = 5.42E-06). These changes were significantly reversed after intravenous immunoglobulin (IVIG) treatment. ROC curve analysis demonstrated remarkable diagnostic capability of mean NLRC4 gene methylation for KD (areas under ROC curve = 0.844, sensitivity = 0.75, p = 9.61E-06, 95% confidence intervals were 0.762-0.926 for mean NLRC4 methylation). In addition, NLRC4 promoter methylation was shown to be significantly negatively correlated with the levels of central granulocyte percentage, age, mean haemoglobin quantity and mean erythrocyte volume. Besides, NLRC4 promoter methylation was positively correlated with lymphocyte percentage, lymphocyte absolute value. CONCLUSIONS: Our work revealed the role of peripheral NLRC4 hypomethylation in KD pathogenesis and IVIG treatment response, could potentially serve as a treatment monitoring biomarker, although its precise functions remain to be elucidated.

Development of an Open Droplet Microchannel-Based Magnetosensor for Immunofluorometric Assay of Trimethoprim in Chicken and Pork Samples with a Wide Linear Range.

Trimethoprim (TMP), functioning as a synergistic antibacterial agent, is utilized in diagnosing and treating diseases affecting livestock and poultry. Human consumption of the medication indirectly may lead to its drug accumulation in the body and increase drug resistance due to its prolonged metabolic duration in livestock and poultry, presenting significant health hazards. Most reported immunoassay techniques, such as ELISA and immunochromatographic assay (ICA), find it challenging to achieve the dual advantages of high sensitivity, simplicity of operation, and a wide detection range. Consequently, an open droplet microchannel-based magnetosensor for immunofluorometric assay (OMM-IFA) of trimethoprim was created, featuring a gel imager to provide a signal output derived from the highly specific antibody (Ab) targeting trimethoprim. The method exhibited high sensitivity in chicken and pork samples, with LODs of 0.300 and 0.017 ng/mL, respectively, and a wide linear range, covering trimethoprim's total maximum residue limits (MRLs). Additionally, the spiked recoveries in chicken and pork specimens varied between 81.6% and 107.9%, maintaining an acceptable variation coefficient below 15%, aligning well with the findings from the ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technique. The developed method achieved a much wider linear range of about 5 orders of magnitude of 10-2-103 levels with grayscale signals as the output signal, which exhibited high sensitivity, excellent applicability and simple operability based on magnetic automation.

Encephalitis-like episodes with cortical edema and enhancement in patients with neuronal intranuclear inclusion disease.

OBJECTIVES: Neuronal intranuclear inclusion disease (NIID) exhibited significant clinical heterogeneities. However, the clinical features, radiographic changes, and prognosis of patients with encephalitis-like NIID have yet to be systematically elucidated. METHODS: Clinical data including medical history, physical examination, and laboratory examinations were collected and analyzed. Skin and sural nerve biopsies were conducted on the patient. Repeat-primed PCR (RP-PCR) and fluorescence amplicon length PCR (AL-PCR) were used to detect the expansion of CGG repeat. We also reviewed the clinical and genetic data of NIID patients with cortical enhancement. RESULTS: A 54-year-old woman presented with encephalitis-like NIID, characterized by severe headache and agitative psychiatric symptoms. The brain MRI showed cortical swelling in the temporo-occipital lobes and significant enhancement of the cortical surface and dura, but without hyperintensities along the corticomedullary junction on diffusion-weighted image (DWI). A biopsy of the sural nerve revealed a demyelinating pathological change. The intranuclear inclusions were detected in nerve and skin tissues using the p62 antibody and electron microscopy. RP-PCR and AL-PCR unveiled the pathogenic expansion of CGG repeats in the NOTCH2NLC gene. A review of the literature indicated that nine out of the 16 patients with cortical lesions and linear enhancement exhibited encephalitis-like NIID. CONCLUSION: This study indicated that patients with encephalitis-like NIID typically exhibited headache and excitatory psychiatric symptoms, often accompanied by cortical edema and enhancement of posterior lobes, and responded well to glucocorticoid treatment. Furthermore, some patients may not exhibit hyperintensities along the corticomedullary junction on DWI, potentially leading to misdiagnosis.

Violent Video Recognition by Using Sequential Image Collage.

Identifying violent activities is important for ensuring the safety of society. Although the Transformer model contributes significantly to the field of behavior recognition, it often requires a substantial volume of data to perform well. Since existing datasets on violent behavior are currently lacking, it will be a challenge for Transformers to identify violent behavior with insufficient datasets. Additionally, Transformers are known to be computationally heavy and can sometimes overlook temporal features. To overcome these issues, an architecture named MLP-Mixer can be used to achieve comparable results with a smaller dataset. In this research, a special type of dataset to be fed into the MLP-Mixer called a sequential image collage (SIC) is proposed. This dataset is created by aggregating frames of video clips into image collages sequentially for the model to better understand the temporal features of violent behavior in videos. Three different public datasets, namely, the dataset of National Hockey League hockey fights, the dataset of smart-city CCTV violence detection, and the dataset of real-life violence situations were used to train the model. The results of the experiments proved that the model trained using the proposed SIC is capable of achieving high performance in violent behavior recognition with fewer parameters and FLOPs needed compared to other state-of-the-art models.

A dynamic multi-objective evolutionary algorithm using center and multi-direction prediction strategies.

Dynamic multi-objective optimization problems have been popular because of its extensive application. The difficulty of solving the problem focuses on the moving PS as well as PF dynamically. A large number of efficient strategies have been put forward to deal with such problems by speeding up convergence and keeping diversity. Prediction strategy is a common method which is widely used in dynamic optimization environment. However, how to increase the efficiency of prediction is always a key but difficult issue. In this paper, a new prediction model is designed by using the rank sums of individuals, and the position difference of individuals in the previous two adjacent environments is defined to identify the present change type. The proposed prediction strategy depends on environment change types. In order to show the effectiveness of the proposed algorithm, the comparison is carried out with five state-of-the-art approaches on 20 benchmark instances of dynamic multi-objective problems. The experimental results indicate the proposed algorithm can get good convergence and distribution in dynamic environments.

Heterogeneity of State Stroke Center Certification and Designation Processes.

BACKGROUND: Stroke centers are critical for the timely diagnosis and treatment of acute stroke and have been associated with improved treatment and outcomes; however, variability exists in the definitions and processes used to certify and designate these centers. Our study categorizes state stroke center certification and designation processes and provides examples of state processes across the United States, specifically in states with independent designation processes that do not rely on national certification. METHODS: In this cross-sectional study from September 2022 to April 2023, we used peer-reviewed literature, primary source documents from states, and communication with state officials in all 50 states to capture each state's process for stroke center certification and designation. We categorized this information and outlined examples of processes in each category. RESULTS: Our cross-sectional study of state-level stroke center certification and designation processes across states reveals significant heterogeneity in the terminology used to describe state processes and the processes themselves. We identify 3 main categories of state processes: No State Certification or Designation Process (category A; n=12), State Designation Reliant on National Certification Only (category B; n=24), and State Has Option for Self-Certification or Independent Designation (category C; n=14). Furthermore, we describe 3 subcategories of self-certification or independent state designation processes: State Relies on Self-Certification or Independent Designation for Acute Stroke Ready Hospital or Equivalent (category C1; n=3), State Has Hybrid Model for Acute Stroke Ready Hospital or Equivalent (category C2; n=5), and State Has Hybrid Model for Primary Stroke Center and Above (category C3; n=6). CONCLUSIONS: Our study found significant heterogeneity in state-level processes. A better understanding of how these differences may impact the rigor of each process and clinical performance of stroke centers is worthy of further investigation.

New insights into functional divergence and adaptive evolution of uncultured bacteria in anammox community by complete genome-centric analysis.

Anaerobic ammonium-oxidation (anammox) bacteria play a crucial role in global nitrogen cycling and wastewater nitrogen removal, but they share symbiotic relationships with various other microorganisms. Functional divergence and adaptive evolution of uncultured bacteria in anammox community remain underexplored. Although shotgun metagenomics based on short reads has been widely used in anammox research, metagenome-assembled genomes (MAGs) are often discontinuous and highly contaminated, which limits in-depth analyses of anammox communities. Here, for the first time, we performed Pacific Biosciences high-fidelity (HiFi) long-read sequencing on the anammox granule sludge sample from a lab-scale bioreactor, and obtained 30 accurate and complete metagenome-assembled genomes (cMAGs). These cMAGs were obtained by selecting high-quality circular contigs from initial assemblies of long reads generated by HiFi sequencing, eliminating the need for Illumina short reads, binning, and reassembly. One new anammox species affiliated with Candidatus Jettenia and three species affiliated with novel families were found in this anammox community. cMAG-centric analysis revealed functional divergence in general and nitrogen metabolism among the anammox community members, and they might adopt a cross-feeding strategy in organic matter, cofactors, and vitamins. Furthermore, we identified 63 mobile genetic elements (MGEs) and 50 putative horizontal gene transfer (HGT) events within these cMAGs. The results suggest that HGT events and MGEs related to phage and integration or excision, particularly transposons containing tnpA in anammox bacteria, might play important roles in the adaptive evolution of this anammox community. The cMAGs generated in the present study could be used to establish of a comprehensive database for anammox bacteria and associated microorganisms. These findings highlight the advantages of HiFi sequencing for the studies of complex mixed cultures and advance the understanding of anammox communities.

Simultaneous SERS Sensing of Cysteine and Homocysteine in Blood Based on the CBT-Cys Click Reaction: Toward Precisive Diagnosis of Schizophrenia.

At present, there is a lack of sufficiently specific laboratory diagnostic indicators for schizophrenia. Serum homocysteine (Hcy) levels have been found to be related to schizophrenia. Cysteine (Cys) is a demethylation product in the metabolism of Hcy, and they always coexist with highly similar structures in vivo. There are few reports on the use of Cys as a diagnostic biomarker for schizophrenia in collaboration with Hcy, mainly because the rapid, economical, accurate, and high-throughput simultaneous detection of Cys and Hcy in serum is highly challenging. Herein, a click reaction-based surface-enhanced Raman spectroscopy (SERS) sensor was developed for simultaneous and selective detection of Cys and Hcy. Through the efficient and specific CBT-Cys click reaction between the probe containing cyan benzothiazole and Cys/Hcy, the tiny methylene difference between the molecular structures of Cys and Hcy was converted into the difference between the ring skeletons of the corresponding products that could be identified by plasmonic silver nanoparticle enhanced molecular fingerprint spectroscopy to realize discriminative detection. Furthermore, the SERS sensor was successfully applied to the detection in related patient serum samples, and it was found that the combined analysis of Cys and Hcy can improve the diagnostic accuracy of schizophrenia compared to a single indicator.

Pattern classification of interstitial lung diseases from computed tomography images using a ResNet-based network with a split-transform-merge strategy and split attention.

In patients with interstitial lung disease (ILD), accurate pattern assessment from their computed tomography (CT) images could help track lung abnormalities and evaluate treatment efficacy. Based on excellent image classification performance, convolutional neural networks (CNNs) have been massively investigated for classifying and labeling pathological patterns in the CT images of ILD patients. However, previous studies rarely considered the three-dimensional (3D) structure of the pathological patterns of ILD and used two-dimensional network input. In addition, ResNet-based networks such as SE-ResNet and ResNeXt with high classification performance have not been used for pattern classification of ILD. This study proposed a SE-ResNeXt-SA-18 for classifying pathological patterns of ILD. The SE-ResNeXt-SA-18 integrated the multipath design of the ResNeXt and the feature weighting of the squeeze-and-excitation network with split attention. The classification performance of the SE-ResNeXt-SA-18 was compared with the ResNet-18 and SE-ResNeXt-18. The influence of the input patch size on classification performance was also evaluated. Results show that the classification accuracy was increased with the increase of the patch size. With a 32 × 32 × 16 input, the SE-ResNeXt-SA-18 presented the highest performance with average accuracy, sensitivity, and specificity of 0.991, 0.979, and 0.994. High-weight regions in the class activation maps of the SE-ResNeXt-SA-18 also matched the specific pattern features. In comparison, the performance of the SE-ResNeXt-SA-18 is superior to the previously reported CNNs in classifying the ILD patterns. We concluded that the SE-ResNeXt-SA-18 could help track or monitor the progress of ILD through accuracy pattern classification.

Influence of Cigarette Aerosol in Alpha-Synuclein Oligomerization and Cell Viability in SH-SY5Y: Implications for Parkinson's Disease.

Although cigarette aerosol exposure is associated with various adverse health issues, its impact on Parkinson's disease (PD) remains elusive. Here, we investigated the effect of cigarette aerosol extract (CAE) on SH-SY5Y cells for the first time, both with and without α-synuclein (α-Syn) overexpression. We found that α-Syn aggravates CAE-induced cell death, oxidative stress, and mitochondrial dysfunction. Fluorescence cross-correlation spectroscopy (FCCS) revealed a dual distribution of α-Syn within the cells, with homogeneous regions indicative of monomeric α-Syn and punctated regions, suggesting the formation of oligomers. Moreover, we observed colocalization of α-Syn oligomers with lysosomes along with a reduction in autophagy activity. These findings suggest that α-Syn overexpression exacerbates CAE-induced intracellular cytotoxicity, mitochondrial dysfunction, and autophagy dysregulation, leading to elevated cell mortality. Our findings provide new insights into the pathogenic mechanisms linking exposure to cigarette aerosols with neurodegenerative diseases.

An evaluation of microplastic contamination in the marine waters and species in the coastal region of the South Yellow Sea, China.

Microplastics (MPs) contamination of marine environments poses a significant ecological risk, although impacts on species' realized niche spaces remain unclear. The current study investigates MPs distribution across pelagic habitats, benthic sediments, and key biota in the South Yellow Sea, China. Samples were collected via trawling across estuarine transects, and tissues were digested to extract MPs. Density gradient separations and vacuum-filtrations prepared particle extracts for ATR-FTIR and Micro-Raman spectroscopic characterization. Sampling along industrialized river transects reveals ubiquitous plastic particle presence, with concentrations ranging from 0 to 51.68 item/L seawater. Contamination levels reach their peak at station estuaries before dispersing offshore, indicating significant waste stream inputs. Importantly, MPs detected in demersal and pelagic fish species, as well as in bivalves, confirm exposure across trophic niches. Gastrointestinal tract and gill concentrations reached 0.6 items/g fresh tissue, reflecting significant biological uptake and in vivo retention. The greatest population of organisms occurred adjacent to polluted areas. Overall, distribution of MPs from polluted rivers to coastal food webs was evident, suggesting potential negative impacts on key ecological functions in this system. These findings underscore the need to develop upstream mitigation efforts so as to minimize MPs contamination in areas where nearshore and offshore niches intersect.

Saikosaponin D mitigate pilocarpine-induced astrocyte injury by regulating the NLRP3/caspase-1 signaling pathway.

Studies have shown that saikosaponin D (SSD) has favorable neurotherapeutic effects. Therefore, the objective of this study was to explore the efficacy and possible molecular mechanisms of SSD on pilocarpine (PP)-induced astrocyte injury. Primary astrocytes were isolated from juvenile rats and identified using immunofluorescence. The cells were treated with PP and/or SSD for 6 h and 12 h, respectively, followed by measurement of their viability through 3-(4,5-dimethylthiazol)-2,5-diphenyl-tetrazolium bromide (MTT) assay. Next, quantitative real-time polymerase chain reaction (qRT-PCR) was used to measure the expression levels of Glial fibrillary acidic protein (GFAP), C3, S100 calcium binding protein A10 (S100a10), pentraxin 3 (Ptx3), toll-like receptor 4 (TLR4), and RAG in astrocytes after different treatments. Enzyme-linked immunosorbent assay and biochemical tests were utilized to evaluate the level of inflammatory factors [interleukin (IL)-1ß, IL-6, and tumor necrosis factor alpha (TNF-α)] secreted by cells and the content of oxidative stress-related factors (malondialdehyde [MDA] and glutathione [GSH]) or enzyme activity (catalase [CAT] and glutathione peroxidase [GPX]) in cells. The JC-1 mitochondrial membrane potential (MMP) fluorescence probe was used to measure the MMP in astrocytes. Additionally, western blot was applied to test the expression of proteins related to the nod-like receptor protein 3 (NLRP3)/caspase-1 signaling pathway. PP treatment (1 mM) induced cell injury by significantly reducing the viability of astrocytes and expression of cellular markers. SSD treatment (4 µM) had no toxicity to astrocytes. Besides, SSD (4 µM) treatment could significantly up-regulate the cell viability and marker expression of PP-induced astrocytes. Furthermore, SSD could be employed to inhibit inflammation (reduce IL-1ß, IL-6, and TNF-α levels) and oxidative stress (decrease MDA level, elevate GSH level, the activity of CAT and GPX), and ameliorate mitochondrial dysfunction (upregulate JC-1 ratio) in PP-induced astrocytes. Moreover, further mechanism exploration revealed that SSD treatment significantly reduced the activity of the NLRP3/caspase-1 signaling pathway activated by PP induction. SSD increased cell viability, inhibited inflammation and oxidative stress response, and ameliorated mitochondrial dysfunction in PP-induced astrocyte injury model, thus playing a neuroprotective role. The mechanism of SSD may be related to the inhibition of the NLRP3/caspase-1 inflammasome.