Inadequate Sampling Research Articles

Identification research of chemical process leakage based on deep learning and correlation-distance graph coding

As a leak identification method in chemical processes, deep learning is limited by inadequate sample labels and highly coupled, nonlinear process variables, therefore difficult to model with a high identification accuracy. To address these problems, a fusion correlation-distance graph (CDG) coding aided deep learning method is proposed. First, the mechanism model is built based on dynamic process data with different leakage labels. Then, the weighted degree and spatial distribution of the dynamic dataset are computed through innovatively designed correlation and distance coding, aided by sliding window fusion into a correlation-distance matrix. Finally, the well-trained long short-term memory (LSTM) is constructed to learn the deep features of the leakage process and identify them. The applications in two industrial cases, CO2 capture and ammonia synthesis, show that CDG-LSTM presents state-of-the-art identification performance with R2 scores of 0.994 and 0.986. 6.6% and 18.4% improvement over LSTM. In addition, the proposed method effectively categorizes the unknown leak samples into known labels with nearby locations, providing a valuable reference for operators to determine the unknown leak locations.

Role of Conventional Pap Smear in Current Times

Abstract Cervical cancer is the fourth most common malignancy among females after breast, colon, and lung cancers and a leading cause of mortality among gynecologic malignancies. Over 85% of new cases are diagnosed in resource-limited countries. Several screening techniques have been developed to detect precancerous changes timely. The most common of which is conventional Pap smear (CPS). It is based on the cytological and morphology assessment of exfoliated cervical cells to detect preinvasive lesions of the cervix. Despite high specificity, a single Pap test has a low-to-moderate sensitivity. CPS can have false-negative and false-positive results because of inadequate sampling and slide preparation and errors in laboratory detection and interpretation. To overcome these shortcomings, liquid-based cytology (LBC) was introduced. LBC can be a better alternative to CPS because of a lower rate of unsatisfactory smears. The liquid reserve can be used for ancillary testing, such as human papillomavirus DNA tests (as reflex test and co-test). The cost of this technique is a limiting factor. In most of the developed countries, CPS is replaced by the LBC. There are several studies with conflicting results, and no method has been shown to be superior in terms of all parameters. Relevant studies were searched using PubMed/MEDLINE and Google Scholar. This article puts forward the results of various studies comparing the efficacy of CPS and LBC and highlights the advantages and disadvantages of both methods.

Fault Diagnosis Based on Tensor Computing and Meta-Learning for Smart Grid and Power Communication Network

Fault diagnosis (FD) is a critical challenge for the smart grid and the power communication network, especially when both heterogeneous networks are exponentially becoming enormous and complicated. Consequently, some conventional FD schemes based on labor seem inefficient, even disabled, because they usually cannot efficiently utilize multi-dimensional and heterogeneous big data from both networks. To deal with this challenging technical problem, a novel FD scheme based on tensor computing and meta-learning is proposed for the smart grid and the power communication network. In the proposed scheme, tensor computing is used to process tensor big data from both networks, and a new data fusion scheme is designed to complete and analyze the incomplete and sparse big data. Based on the fused data, a meta-learning approach is used to construct the FD scheme, especially when the target fault samples are inadequate and sparse. In meta-learning, the convolutional neural network is employed as a base learner to generate an FD training model, and the model-agnostic meta-learning algorithm is utilized to fine-tune and further train the pre-trained model. Simulation results and theoretical analysis indicate that the proposed DF scheme based on tensor computing can efficiently process sparse and heterogeneous big data from both networks. Furthermore, the meta-learning-based FD scheme provides an efficient way to diagnose faults with inadequate target samples. The proposed FD scheme based on tensor computing and meta-learning provides a novel solution to detect and analyze the potential faults for smart grid and power communication networks.

Contrast-enhanced endoscopic ultrasound likely does not improve diagnostic adequacy during endoscopic ultrasound guided tissue acquisition: A systematic review and meta-analysis

Background and aimsSolid pancreatic masses are sampled through tissue acquisition by endoscopic ultrasound (EUS). Inadequate samples may significantly delay diagnosis, increasing costs and carrying risks to the patients. Aim: assess the diagnostic adequacy of tissue acquisition using contrast-enhanced harmonic endoscopic ultrasound (CEH-EUS) compared to conventional EUS. MethodsFive databases (PubMed, Embase, CENTRAL, Scopus and Web of Science) were searched in November 2023. Studies comparing diagnostic adequacy, accuracy and safety using CEH-EUS versus conventional EUS for tissue acquisition of solid pancreatic masses were included. Risk of bias was assessed using the Risk of Bias tool for randomized controlled trials (RoB2) and the Risk Of Bias In Non-Randomized Studies - of Interventions (ROBINS-I) tool for non-randomized studies, level of evidence using the GRADE approach, Odds Ratios (RR) with 95 % Confidence Intervals (CI) calculated and pooled using a random-effects model. I2 quantified heterogeneity. ResultsThe search identified 3858 records; nine studies (1160 patients) were included. OR for achieving an adequate sample was 1.467 (CI: 0.850–2.533), for randomized trials 0.902 (CI: 0.541–1.505), for non-randomized 2.396 (CI: 0.916–6.264), with significant subgroup difference. OR for diagnostic accuracy was 1.326 (CI: 0.890–1977), for randomized trials 0.997 (CI: 0.593–1.977) and for non-randomized studies 1.928 (CI: 1.096–3.393), significant subgroup difference (p = 0.0467). No differences were observed for technical failures or adverse events. Heterogeneity was low, risk of bias “low” to “some concerns” for most outcomes, mostly moderate for non-randomized studies. ConclusionNon-randomized studies indicated differences in favor of contrast-enhanced EUS, randomized studies showed no difference in diagnostic adequacy, accuracy or sensitivity when using CEH-EUS.

Diagnostic accuracy of International System for Reporting Serous Fluid Cytopathology: A systematic review and meta-analysis in malignancy diagnosis.

This study conducts the first meta-analysis to assess the aggregated risk of malignancy associated with each category of the International System for Reporting Serous Fluid Cytopathology (ISRSFC) for reporting serous effusion cytology, while also evaluating diagnostic accuracy. PubMed/MEDLINE and Embase were systematically searched using the keywords "(pleural, peritoneal, and pericardial effusions) AND (serous effusion cytology) OR (International System for Reporting Serous Fluid Cytopathology)". Articles underwent risk of bias assessment using the QUADAS-2 tool. After excluding inadequate samples, a meta-analysis determined sensitivity and specificity for different cutoff points, including "atypical considered positive," "suspicious of malignancy considered positive," and "malignant considered positive." Summary receiver operating characteristic curves assessed diagnostic accuracy, and the diagnostic odds ratio was pooled. Sixteen retrospective cross-sectional studies, totaling 19,128 cases, were included. Sensitivity and specificity for the "atypical and higher risk categories" considered positive were 77% (95% confidence interval [CI], 68%-84%) and 95% (95% CI, 93%-97%) respectively. For the "suspicious for malignancy and higher risk categories" considered positive, sensitivity and specificity were 57% (95% CI, 49%-65%) and 100% (95% CI, 99%-100%) respectively. Sensitivity and specificity for the "malignant" category considered positive for malignancy were 70% (95% CI, 60%-77%) and 99% (95% CI, 98%-99%), respectively. The pooled area under the curve ranged from 85% to 89.5% for each cutoff. This meta-analysis underscores the ISRSFC's accuracy in reporting serous fluid cytology. It emphasizes the diagnostic importance of the "suspicious" and "malignant" categories in identifying malignancy, and the role of the "benign" category in ruling out malignancy.

Mapping of Forest Structural Parameters in Tianshan Mountain Using Bayesian-Random Forest Model, Synthetic Aperture Radar Sentinel-1A, and Sentinel-2 Imagery

The assessment of forest structural parameters is crucial for understanding carbon storage, habitat suitability, and timber stock. However, the labor-intensive and expensive nature of field measurements, coupled with inadequate sample sizes for large-scale modeling, poses challenges. To address the forest structure parameters in the Western Tianshan Mountains, this study used UAV-LiDAR to gather extensive sample data. This approach was enhanced by integrating Sentinel satellite and topographic data and using a Bayesian-Random Forest model to estimate forest canopy height, average height, density, and aboveground biomass (AGB). Validation against independent LiDAR-derived samples confirmed the model’s high accuracy, with coefficients of determination (R2) and root mean square errors (RMSE) indicating strong predictive performance (R2 = 0.63, RMSE = 5.06 m for canopy height; R2 = 0.64, RMSE = 2.88 m for average height; R2 = 0.68, RMSE = 62.84 for density; and R2 = 0.59, RMSE = 29.71 Mg/ha for AGB). Notably, the crucial factors include DEM, Sentinel-1 (VH and VV backscatter in dB), and Sentinel-2 (B6, B8A, and B11 bands). These factors contribute significantly to the modeling of forest structure. This technology aims to expedite and economize forest surveys while augmenting the range of forest parameters, especially in remote and rugged terrains. Using a wealth of UAV-LiDAR data, this outcome surpasses its counterparts’ by providing essential insights for exploring climate change effects on Central Asian forests, facilitating precise carbon stock quantification, and enhancing knowledge of forest ecosystems.

Differentiable Auxiliary Learning for Sketch Re-Identification

Sketch re-identification (Re-ID) seeks to match pedestrians' photos from surveillance videos with corresponding sketches. However, we observe that existing works still have two critical limitations: (i) cross- and intra-modality discrepancies hinder the extraction of modality-shared features, (ii) standard triplet loss fails to constrain latent feature distribution in each modality with inadequate samples. To overcome the above issues, we propose a differentiable auxiliary learning network (DALNet) to explore a robust auxiliary modality for Sketch Re-ID. Specifically, for (i) we construct an auxiliary modality by using a dynamic auxiliary generator (DAG) to bridge the gap between sketch and photo modalities. The auxiliary modality highlights the described person in photos to mitigate background clutter and learns sketch style through style refinement. Moreover, a modality interactive attention module (MIA) is presented to align the features and learn the invariant patterns of two modalities by auxiliary modality. To address (ii), we propose a multi-modality collaborative learning scheme (MMCL) to align the latent distribution of three modalities. An intra-modality circle loss in MMCL brings learned global and modality-shared features of the same identity closer in the case of insufficient samples within each modality. Extensive experiments verify the superior performance of our DALNet over the state-of-the-art methods for Sketch Re-ID, and the generalization in sketch-based image retrieval and sketch-photo face recognition tasks.

O198: Cytosponge: Innovative technology in Barrett’s oesophagus surveillance

Abstract Introduction British Society of Gastroenterology guidance recommends oesophagogastroduodenoscopy (OGD) for Barrett’s oesophagus surveillance with quandrantic biopsies for every 2cm length of Barrett’s. The Covid pandemic led to delays in Barrett's surveillance and prolongation of surveillance intervals. This study assessed the potential role of Cytosponge, a novel cytology sampling device, in Barrett's surveillance. Methodology All patients due Barrett's surveillance in 2022/23 were identified and screened to assess suitability for Cytosponge. Cytology results and associated early clinical outcomes were assessed. Results 193 patients (77%) were suitable for Cytosponge, and 175 of these (90%) did not require OGD. 18 patients (10%) required urgent OGD for inadequate cytology samples (3), cellular atypia (8), aberrant p53 (3) or dysplasia (4). 2 patients had high grade dysplasia on subsequent OGD, successfully treated with radiofrequency ablation. No diagnosis of oesophago-gastric cancer was made during the follow-up period. By July 2023, 282 patients with Barrett’s oesophagus had completed Cytosponge assessment; minimum follow-up was 4 months and no patients had developed ‘inter-test’ malignancy. Conclusion These data are promising and suggest that endoscopy and biopsy may not be required for all Barrett’s surveillance. Cytology samples alone may be sufficient to assess for epithelial dysplastic and neoplastic change in Barrett’s surveillance, with judicious utilisation of endoscopy resources where indicated and necessary. Patients who received a Cytosponge in 2022 will be due for endoscopic surveillance in 2024 – these data will provide valuable additional information about the role of Cytosponge in Barrett’s surveillance and whether endoscopy can be replaced altogether.

Platinum-group-element minerals (‘osmiridium’) from Waratah Bay, Victoria, Australia, and a review of other reported Victorian occurrences

Minerals consisting of the platinum-group elements iridium, osmium and ruthenium (IPGE) are widely dispersed in alluvial deposits derived from ultramafic igneous complexes originating in ophiolite belts. Rock types, such as cumulate dunite–pyroxenite–harzburgite, and their serpentinite derivatives are especially fertile sources of IPGE minerals, which are colloquially termed ‘osmiridium’. IPGE minerals have been recorded from five localities in Victoria—beach sands at Waratah Bay, and stream concentrates from Turtons Creek, Stockyard Creek and Horseshoe Creek in South Gippsland. A grain of IPGE was recently found in a gully near the Dolodrook River further north. These occurrences are all poorly documented by comparison with the northwest Tasmanian deposits, and only Waratah Bay has provided enough material to enable full characterisation. Microprobe data show that all four minerals currently defined in the Os–Ru–Ir system occur at Waratah Bay, including rutheniridosmine. Gold and chromite are also present in the alluvial samples from Waratah Bay and Turtons Creek. Attempts to correlate compositions of alluvial chromite with those from likely proximal serpentinite source rocks proved to be inconclusive due mainly to inadequate representative sampling. However, the chromite compositions are broadly characteristic of those found in the early Paleozoic ultramafic ophiolite complexes in northwestern Tasmania, in which IPGE minerals and chromite are abundant. Regional aeromagnetic trends across Bass Strait suggest that the Victorian IPGE occurrences represent disaggregated and metamorphosed extensions of the Tasmanian sequences.

Research on product design of FAHP bone marrow aspiration needle

Bone marrow aspiration is a crucial medical procedure to obtain bone marrow samples for diagnosis and treatment. However, traditional bone marrow aspiration needles face several challenges such as operational difficulties, inadequate sample acquisition, and patient discomfort. To address these issues, we aimed to design a bone marrow aspiration needle product by using fuzzy analytic hierarchical process (FAHP). The FAHP method was used to identify key factors in the design of the bone marrow aspiration needle, including technicality, usage, and application characteristics. The importance weights and priorities of each factor were determined through questionnaires and interviews with experts. A new bone marrow aspiration needle product was developed based on the results of the FAHP. The new product design considers the weights and priorities assigned to key factors, resulting in improved convenience during operation and a higher success rate of sample acquisition. This was achieved by optimising the structure and material selection of the needle. This study presents a novel bone marrow puncture needle product that effectively integrates the importance and priority of the key factors. It successfully enhances operational performance and patient experience, thereby offering an innovative solution to improve the success rate and therapeutic effect of bone marrow punctures.

Prognostic significance of lymphocytic foci composition in minor salivary gland biopsies for severe disease flare and severity in Sjögren's syndrome: a 3-year follow-up cohort study.

This was an ambispective cohort study evaluating the prognostic significance of lymphocytic foci and its lymphoid composition in minor salivary gland biopsy (MSGB) for short-term disease flare and severity in Sjögren's syndrome (SS). The inclusion criteria comprised individuals meeting the ACR/EULAR 2016 criteria who underwent MSGB with an infiltration of more than 50 lymphocytes and received clinical diagnosis between September 2017 and December 2018. Patients with inadequate biopsy samples were excluded. The number of lymphocytic foci and their lymphoid composition in MSGB were assessed using immunofluorescence staining. Major organ damage and improvements in the EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI) were measured. Statistical analyses, including Cox and linear regressions, were conducted. A total of 78 patients with at least one lymphocytic focus were included in the study. The presence of higher T-cell counts in lymphocytic foci in MSGB was associated with severe disease flare, and a logarithmic transformation of T-cell count indicated increased risk (HR 1.96, 95% CI 0.91-4.21). Improvements in the ESSDAI were associated with higher total lymphocyte count and T- and B-cell numbers in the lymphoid composition of the lymphocytic foci. Seropositive patients exhibited higher T CD4+ cell numbers. Correlation analysis showed negative associations between age and lymphocytic foci and the T-cell count. Positive correlations were observed between antinuclear antibody (ANA) titers and total lymphocyte numbers. Patients with a higher number of T cells in the lymphocytic infiltrates of lymphocytic foci may have a two-fold risk of severe disease flare. The number of B cells and T CD4+ cells in the lymphocytic infiltrates of lymphocytic foci showed a weak but positive relation with the ESSDAI improvement during follow-up. Age and seropositivity appeared to influence the lymphoid composition of the lymphocytic foci.

The Jarzynski binding free energy can effectively rank ligand-protein affinities in inadequate samplings

The use of the Jarzynski equality for estimating ligand–protein binding free energies are illustrated for cases of inadequate samplings. Data obtained from a large amount (104) of work are thus converged to an incorrect value, due to creation of a distorted Gaussian-like distribution. However, even in such cases, the Jarzynski equality can effectively rank binding affinities in the early stage of rational drug design. A combination of steered molecular dynamics calculations, Jarzynski relation and block averaging can provide such relative binding free energies having significantly better correlations in the cases of the thrombin and HIV-1 complexes examined.

Immunohistochemical Study of Estrogen and Progesterone Receptor Expression in Endometrial Carcinoma

BACKGROUND: Endometrial cancer is the fourth most common cancer affecting the women both from the point of view of incidence as well as mortality. ER/PR positivity helps to determine the need for hormonal treatment for endometrial cancer. METERIAL AND METHOD It is a reterospective study on 22 histopathologically proven cases of endometrial carcinoma between the age group 30 to 80 yr from 1 Jan 2021 to 30 June 2022. Those cases with inadequate sample or with history of pregnancy were excluded from study. ER and PR expression was seen with Immunohistochemistry kit protocol. RESULTS: Mean age of patients was 57.77 yrs. Endometrial carcinoma is more common in postmenopausal females. Bleeding per vaginum is the chief complaint. Most of the cases were well differentiated and of low grade.ER expression is positive in (15/17 88.2% )of cases of low grade /well differentiated , (4/4,100%) in moderately differentiated and not seen in high grade/ poorly differentiated endometrial carcinoma .PR expression seen in low grade/well differentiated is (14/17,82.4%) , in moderately differentiated is( 4/4,100%) and in high grade /poorly differentiated is (1/1, 100%)and not seen in high grade or poorly differentiated endometrial carcinoma .As the tumor invades deep in the myometrium ER and PR expression decreases. CONCLUSION: ER and PR are important prognostic biomarkers to predict response to anti hormonal therapy.

EUS-FNA versus EUS-FNB in Pancreatic Solid Lesions ≤ 15 mm.

A small tumor size may impact the diagnostic performance of endoscopic ultrasound-guided tissue acquisition (EUS-TA) for diagnosing solid pancreatic lesions (SPLs). We aimed to compare the diagnostic yield of EUS-guided fine-needle aspiration (FNA) and biopsy (FNB) in SPLs with a diameter ≤ 15 mm. Consecutive patients who underwent EUS-TA for SPLs ≤ 15 mm between January 2015 and December 2022 in a tertiary referral center were retrospectively evaluated. The primary endpoint was diagnostic accuracy. The final diagnosis was based on surgical pathology or disease evolution after a minimum follow-up of 6 months. Inadequate samples were all considered false negatives for the study. Secondary outcomes included sample adequacy, factors impacting accuracy, and safety. We included 368 patients (52.4% male; mean age: 60.2 years) who underwent FNA in 72 cases and FNB in 296. The mean size of SPLs was 11.9 ± 2.6 mm. More than three passes were performed in 5.7% and 61.5% of patients in the FNB and FNA groups, respectively (p < 0.0001). FNB outperformed FNA in terms of diagnostic accuracy (89.8% vs. 79.1%, p = 0.013) and sample adequacy (95.9% vs. 86.1%, p < 0.001). On multivariate analysis, using FNA (OR: 2.10, 95% CI: 1.07-4.48) and a final diagnosis (OR: 3.56, 95% CI: 1.82-6.94) of benign conditions negatively impacted accuracy. Overall, the adverse event rate was 0.8%, including one pancreatitis in the FNA group and one pancreatitis and one bleeding in the FNB group, all mild and conservatively managed. EUS-TA for SPLs ≤ 15 mm has a high diagnostic yield and safety. This study suggests the superiority of FNB over FNA, with better performance even with fewer passes performed.

Insufficient endobronchial ultrasound-guided transbronchial needle aspiration specimens. When and why? The analysis of criteria and reasons behind the insufficient specimens.

The classification terminology systems for pulmonary cytology specimens have recently emerged. Inadequate samples, classified as "nondiagnostic," raise challenges in determining the threshold of cell numbers and the risk of malignancy (ROM). The study retrospectively reviewed 248 endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) samples: 46 insufficient samples, 60 low cellularity samples, and 142 adequate samples. Characteristics as cellularity, number of benign and malignant cells, and background features were assessed. Receiver operating characteristic curve analysis was performed to establish cell sufficiency thresholds for the diagnosis. Out of the 248 samples analyzed, 108 were classified as benign, 94 as malignant, and 46 as insufficient. The study found that the cellularity thresholds for diagnosis in cell blocks and cytological samples were ≥50 cells and ≥100 cells, respectively. The thresholds for tumor cell counts were ≥1 - 10 cells for both types of cells, respectively. Considerably, some low cellularity samples were initially classified as insufficient despite meeting the diagnostic thresholds upon revision. The ROM varied across sample categories, with insufficient samples having a ROM of 10.9%, benign samples 15.7%, suspicious samples 92.0%, and malignant samples 100%. Insufficient EBUS-TBNA samples raise challenges in diagnosis and management. This study identified the root cause of insufficient samples, including factors related to humans, diagnostic methods, sampling, and laboratory processing. By understanding the root causes, diagnostic recommendations can be developed to improve the diagnostic process. The findings emphasize the importance of standardized classification and terminology systems for clear communication among healthcare professionals and institutions, ultimately improving patient care and enabling quality assurance measures.

An Enhanced Path Finder Algorithm for the estimation of the stator current envelope to detect rotor bar breakage in an induction motor

The Enhanced Path Finder Algorithm (EPFA) is used in this research to present an innovative approach for examining the state of the rotor bars in an induction motor, employing a hybrid metaheuristic algorithm. Compared to current optimization techniques, the suggested approach permits more balanced exploration and exploitation. The method addresses the drawbacks of traditional analysis of fault related frequencies, such as short data length, spectrum leakages, and inadequate sampling frequency. The primary goal of this research is to identify the twice-slip frequency component and its harmonics in the current envelope that correlates with the fault. The A signal model of the stator current envelope and the residual error function have been used to define a nonlinear least-squares problem. An induction machine model has been developed in 2D ANSYS Maxwell software where faults have been implemented and studied. Finally, the efficiency of the fault detection scheme has been verified with a practical data set.

Diagnostic analysis of pleural fluid cell blocks using relevant immunohistochemical markers in clinically suspicious cases of malignancy.

Thoracocentesis is a less invasive and expensive procedure than pleural biopsy, enabling sample collection for cytological evaluation. Cell blocks prepared from these samples provide histopathological diagnoses; further, immunohistochemistry (IHC) can be performed for subtyping malignancies, guiding the clinician in choosing the appropriate treatment modality for the patient. We aimed to determine the various histological subtypes of malignancies using cell block IHC and compare the cell block and conventional cytology methods for diagnosing malignant pleural effusion. All pleural fluid samples from the clinically suspicious cases of malignancy collected at the Department of Pathology, Government Medical College Kottayam, India, during 18 months, except duplicate and inadequate samples, were included in this prospective observational study. IHC was performed on cell blocks that were positive for malignancy. This study analyzed 630 samples, of which 121 cell blocks demonstrated the presence of malignancy. Overall, 80%, 13%, and 7% of cases were negative, suspicious, and positive for malignancy based on conventional cytology, and 81%, 0%, and 19% were negative, suspicious, and positive for malignancy based on cell blocks, respectively. Among all malignancies, adenocarcinomas from the lung (56%) were the most common, followed by adenocarcinomas from the breast (6%), squamous cell carcinomas (5%), and adenocarcinomas from the ovary (3%). Cell blocks helped detect more malignancies (19%) than conventional cytology (7%), despite a moderate agreement between both methods. Adenocarcinomas were the most common cause of malignant pleural effusions, and the most frequent site of origin was the lungs. Cell blocks helped diagnose more malignancies than conventional cytology.

An Efficient Method for Isolating and Purifying Nuclei from Mice Brain for Single-Molecule Imaging Using High-Speed Atomic Force Microscopy.

Nuclear pore complexes (NPCs) on the nuclear membrane surface have a crucial function in controlling the movement of small molecules and macromolecules between the cell nucleus and cytoplasm through their intricate core channel resembling a spiderweb with several layers. Currently, there are few methods available to accurately measure the dynamics of nuclear pores on the nuclear membranes at the nanoscale. The limitation of traditional optical imaging is due to diffraction, which prevents achieving the required resolution for observing a diverse array of organelles and proteins within cells. Super-resolution techniques have effectively addressed this constraint by enabling the observation of subcellular components on the nanoscale. Nevertheless, it is crucial to acknowledge that these methods often need the use of fixed samples. This also raises the question of how closely a static image represents the real intracellular dynamic system. High-speed atomic force microscopy (HS-AFM) is a unique technique used in the field of dynamic structural biology, enabling the study of individual molecules in motion close to their native states. Establishing a reliable and repeatable technique for imaging mammalian tissue at the nanoscale using HS-AFM remains challenging due to inadequate sample preparation. This study presents the rapid strainer microfiltration (RSM) protocol for directly preparing high-quality nuclei from the mouse brain. Subsequently, we promptly utilize HS-AFM real-time imaging and cinematography approaches to record the spatiotemporal of nuclear pore nano-dynamics from the mouse brain.

Unraveling the Phylogenetic Relationships and Taxonomic Status of a Puzzling Freshwater Mussel Genus Inversidens (Bivalvia, Unionidae) through Multilocus Phylogeny and Mitochondrial Phylogenomics

Accurate phylogenetic reconstructions are crucial for comprehending the evolutionary histories, reproductive traits, and ecological habits of organisms. The subfamily Gonideinae of freshwater mussels is currently thought to include eight tribes. However, due to inadequate taxon sampling and molecular data, the assignment of the freshwater mussel genus Inversidens at the tribe level has been unstable. Additionally, the lack of phylogenetic data has hindered efforts to understand the basic biology and implementation of conservation efforts of Inversidens rentianensis, an endemic species to China. Here, we first present the complete mitochondrial genome of Inversidens rentianensis and offer a detailed description of its anatomical morphology. Based on DNA sequence data from five genes (COI, ND1, 16S rRNA, 18S rRNA, and 28S rRNA) and complete mitochondrial genomes, we investigated the phylogenetic position of Inversidens using various analytical methods. Both the concatenated five-gene and mitogenome datasets strongly supported that Inversidens classified to the tribe Gonideini in Gonideinae and formed a basal clade within the tribe Gonideini. Molecular dating analysis suggested that Inversidens originated during the mid-Cretaceous era (102.73 Mya, 95% highest posterior density HPD=72.22‐137.03 Mya) and underwent diversification in the Late Paleogene era (37.92 Mya, 95% HPD=20.39‐60.59 Mya). Moreover, based on the Quantitative Assessment of Species for Conservation (QASCP), Inversidens rentianensis is ranked as second priority, providing valuable insights for its management and conservation efforts. Taken together, this study provides a comprehensive understanding of the systematic position and evolutionary history of Inversidens within the currently accepted subfamily Gonideinae classification framework. These findings establish a solid foundation for future investigations on the ecology, reproductive behavior patterns, and conservation biology of this taxonomic group.

Likelihood of sampling prostate cancer at systematic biopsy as a function of gland volume and number of cores.

Pre-biopsy multiparametric magnetic resonance imaging (mpMRI) of the prostate is used to conduct targeted prostate biopsy (TB), guided by ultrasound and registered (fused) to the MRI. Systematic biopsy (SB) continues to be used together with TB or in mpMRI-negative patients. There is insufficient evidence on how to use SB to inform clinical decision-making in the mpMRI era. The purpose of this study was to estimate the effect of prostate volume and number of SB cores on sampling clinically significant prostate cancer (csPCa) using a simulation method based on clinical data. SBs were simulated using data from 42 patients enrolled in a transrectal ultrasound robot-assisted biopsy trial. Linear mixed models were used to examine the relationship between the number of SB cores and prostate volume on 1) clinically significant cancer detection probability (csCDP) and 2) percent of mpMRI depicted regions of interest (ROIs) sampled with the SB. Median values and interquartile range (IQR) were 47.16 cm3 (35.61-65.57) for prostate volume, 0.57 cm3 (0.39-0.83) for ROI volume, and 4.0 (2-4) for PI-RADS v2.1 scores on MRI. csCDP increased with the increasing number of simulated SB cores and decreased substantially with larger prostate volume. Similarly, the percent of ROIs sampled increased with the increasing number of simulated SB cores and was lower for prostate volumes ≥60 cm3 compared to glands <60 cm3. The effect of the number of SBs performed on detecting csPCa varies largely with gland volume. The common 12-core SB can achieve adequate cancer detection and sampling of ROIs in smaller glands, but not in larger glands. In addition to TB or in mpMRI-negative patients, the number of SB cores can be adjusted to prostate volume. Performing 12-core SB alone in ≥60 cm3 glands results in inadequate sampling and potential PCa underdiagnosis.