PEG10 amplification at 7q21.3 potentiates large-cell transformation in cutaneous T-cell lymphoma.

Mycosis fungoides (MF), the most common form of cutaneous T-cell lymphoma, undergo large-cell transformation (LCT) in the late stage, manifesting aggressive behavior, resistance to treatments, and poor prognosis, but the mechanisms involved remain unclear. To identify the molecular driver of LCT, we collected tumor samples from 133 MF patients and performed whole-transcriptome sequencing on 49 advanced-stage MF patients, followed by integrated copy number inference and genomic hybridization. Tumors with LCT showed unique transcriptional programs and enriched expressions of genes at chr7q. Paternally expressed gene 10 (PEG10), an imprinted gene at 7q21.3, was ectopically expressed in malignant T cells from LCT, driven by 7q21.3 amplification. Mechanistically, aberrant PEG10 expression increased cell size, promoted cell proliferation, and conferred treatment resistance by a PEG10/KLF2/NF-κB axis in in vitro and in vivo models. Pharmacologically targeting PEG10 reversed the phenotypes of proliferation and treatment resistance in LCT. Our findings reveal new molecular mechanisms underlying LCT and suggest that PEG10 inhibition may serve as a promising therapeutic approach in late-stage aggressive T-cell lymphoma.

Multitask Deep Learning-Based Whole-Process System for Automatic Diagnosis of Breast Lesions and Axillary Lymph Node Metastasis Discrimination from Dynamic Contrast-Enhanced-MRI: A Multicenter Study.

BACKGROUND: Accurate diagnosis of breast lesions and discrimination of axillary lymph node (ALN) metastases largely depend on radiologist experience. PURPOSE: To develop a deep learning-based whole-process system (DLWPS) for segmentation and diagnosis of breast lesions and discrimination of ALN metastasis. STUDY TYPE: Retrospective. POPULATION: 1760 breast patients, who were divided into training and validation sets (1110 patients), internal (476 patients), and external (174 patients) test sets. FIELD STRENGTH/SEQUENCE: 3.0T/dynamic contrast-enhanced (DCE)-MRI sequence. ASSESSMENT: DLWPS was developed using segmentation and classification models. The DLWPS-based segmentation model was developed by the U-Net framework, which combined the attention module and the edge feature extraction module. The average score of the output scores of three networks was used as the result of the DLWPS-based classification model. Moreover, the radiologists' diagnosis without and with the DLWPS-assistance was explored. To reveal the underlying biological basis of DLWPS, genetic analysis was performed based on RNA-sequencing data. STATISTICAL TESTS: Dice similarity coefficient (DI), area under receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and kappa value. RESULTS: The segmentation model reached a DI of 0.828 and 0.813 in the internal and external test sets, respectively. Within the breast lesions diagnosis, the DLWPS achieved AUCs of 0.973 in internal test set and 0.936 in external test set. For ALN metastasis discrimination, the DLWPS achieved AUCs of 0.927 in internal test set and 0.917 in external test set. The agreement of radiologists improved with the DLWPS-assistance from 0.547 to 0.794, and from 0.848 to 0.892 in breast lesions diagnosis and ALN metastasis discrimination, respectively. Additionally, 10 breast cancers with ALN metastasis were associated with pathways of aerobic electron transport chain and cytoplasmic translation. DATA CONCLUSION: The performance of DLWPS indicates that it can promote radiologists in the judgment of breast lesions and ALN metastasis and nonmetastasis. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 3.

Turbid Waters and Clearer Standards: Refining Water Quality Criteria for Coastal Environments by Encompassing Metal Bioavailability from Suspended Particles.

Suspended particulate matter (SPM) carries a major fraction of metals in turbid coastal waters, markedly influencing metal bioaccumulation and posing risks to marine life. However, its effects are often overlooked in current water quality criteria for metals, primarily due to challenges in quantifying SPM's contribution. This contribution depends on the SPM concentration, metal distribution coefficients (Kd), and the bioavailability of SPM-bound metals (assimilation efficiency, AE), which can collectively be integrated as a modifying factor (MF). Accordingly, we developed a new stable isotope method to measure metal AE by individual organisms from SPM, employing the widely distributed filter-feeding clam Ruditapes philippinarum as a representative species. Assessing SPM from 23 coastal sites in China, we found average AEs of 42% for Zn, 26% for Cd, 20% for Cu, 8% for Ni, and 6% for Pb. Moreover, using stable isotope methods, we determined metal Kd of SPM from these sites, which can be well predicted by the total organic carbon and iron content (R2 = 0.977). We calculated MFs using a Monte Carlo method. The calculated MFs are in the range 9.9-43 for Pb, 8.5-37 for Zn, 2.9-9.7 for Cu, 1.4-2.7 for Ni, and 1.1-1.6 for Cd, suggesting that dissolved-metal-based criteria values should be divided by MFs to provide adequate protection to aquatic life. This study provides foundational guidelines to refine water quality criteria in turbid waters and protect coastal ecosystems.

Evaluation of a pleiotropic cytokinin polymorphism with cerebral infarction in a Chinese male population.

Cardiovascular diseases, particularly stroke, are a leading cause of morbidity and mortality worldwide. Genetic variations in genes associated with inflammation have been implicated in the pathogenesis of stroke. Interleukin-6 (IL-6), a pleiotropic cytokine with diverse biological functions, has been linked to cardiovascular diseases and stroke. The relationship between cerebral ischemia and inflammation is well-established, suggesting a potential role for IL-6 polymorphisms in stroke susceptibility. In the context of this study, the focus is on evaluating a pleiotropic cytokinin polymorphism, specifically IL-6-572GC, and its association with cerebral infarction in a Chinese male population. The investigation aims to elucidate the genetic correlation between IL-6 polymorphisms and stroke risk, particularly in the context of hemorrhagic subtype of stroke. The study utilizes a case-control design, comparing stroke patients with healthy controls while adjusting for classic risk factors associated with stroke. The methodology employed includes the detection of IL-6 polymorphisms using Real Time Taq Man Probe and PCR-RFLP methods. The results suggest an association between the IL-6-572GC genotype and an increased risk of stroke, particularly in the hemorrhagic subtype. However, the relationship between another IL-6 polymorphism, IL-6-174GC, and stroke remains inconclusive, except for a potential correlation with one allele. The findings underscore the potential role of IL-6-572GC genotype as a genetic risk factor for stroke in the Chinese male population under study. Further research involving larger cohorts is warranted to validate these results and clarify the role of IL-6-174GC polymorphism in stroke susceptibility. Understanding the genetic underpinnings of stroke can provide valuable insights for risk assessment and personalized treatment strategies in affected populations.

Detection and classification of breast lesions using multiple information on contrast-enhanced mammography by a multiprocess deep-learning system: A multicenter study.

Objective: Accurate detection and classification of breast lesions in early stage is crucial to timely formulate effective treatments for patients. We aim to develop a fully automatic system to detect and classify breast lesions using multiple contrast-enhanced mammography (CEM) images. Methods: In this study, a total of 1,903 females who underwent CEM examination from three hospitals were enrolled as the training set, internal testing set, pooled external testing set and prospective testing set. Here we developed a CEM-based multiprocess detection and classification system (MDCS) to perform the task of detection and classification of breast lesions. In this system, we introduced an innovative auxiliary feature fusion (AFF) algorithm that could intelligently incorporates multiple types of information from CEM images. The average free-response receiver operating characteristic score (AFROC-Score) was presented to validate system's detection performance, and the performance of classification was evaluated by area under the receiver operating characteristic curve (AUC). Furthermore, we assessed the diagnostic value of MDCS through visual analysis of disputed cases, comparing its performance and efficiency with that of radiologists and exploring whether it could augment radiologists' performance. Results: On the pooled external and prospective testing sets, MDCS always maintained a high standalone performance, with AFROC-Scores of 0.953 and 0.963 for detection task, and AUCs for classification were 0.909 [95% confidence interval (95% CI): 0.822-0.996] and 0.912 (95% CI: 0.840-0.985), respectively. It also achieved higher sensitivity than all senior radiologists and higher specificity than all junior radiologists on pooled external and prospective testing sets. Moreover, MDCS performed superior diagnostic efficiency with an average reading time of 5 seconds, compared to the radiologists' average reading time of 3.2 min. The average performance of all radiologists was also improved to varying degrees with MDCS assistance. Conclusions: MDCS demonstrated excellent performance in the detection and classification of breast lesions, and greatly enhanced the overall performance of radiologists.

Activating caspase-8/Bid/ROS signaling to promote apoptosis of breast cancer cells by folate-modified albumin baicalin-loaded nanoparticles.

Abnormal apoptosis can lead to uncontrolled cell growth, aberrant homeostasis or the accumulation of mutations. Therapeutic agents that re-establish the normal functions of apoptotic signaling pathways offer an attractive strategy for the treatment of breast cancer. Baicalin (BA) is one of the natural compounds with anti-proliferation and pro-apoptosis activities against numerous tumor cells. However, low bioavailability restricts the clinical application of BA. In order to improve its therapeutic efficacy and study the mechanism of actions, active targeting delivery systems were developed for targeting tumor environment and selective cell killing effects. It emphasized on the construction of folate-conjugated albumin nanoparticles loaded with baicalin (FA-BSANPs/BA) and mechanisms of which on the promotion of breast cancer apoptosis. The physicochemical properties and structural characteristics of FA-BSANPs/BA were investigated. Cell experiments were carried out to study the targeted anti-breast cancer effects of FA-BSANPs/BA and its mechanism. The results showed that FA-BSANPs/BA was successfully constructed with stable structural characteristics and sustained release effects. Cellular uptake and MTT showed that it increased targeted uptake efficiency and cytotoxicity. Flow cytometry and western blot confirmed that it promoted apoptosis by increasing the expression of caspase-8 and ROS, and decreasing the level of Bid. It is suggested that the pro-apoptotic mechanism of FA-BSANPs/BA is related to regulation of key proteins in extrinsic apoptotic pathway. In conclusion, FA-BSANPs/BA is a good delivery carrier and significantly inhibits the breast cancer growth compared with free BA. The mechanism of FA-BSANPs/BA promoting apoptosis of breast cancer may be due to its action on the caspase-8/Bid/ROS pathway.

Role of inflammatory microenvironment: potential implications for improved breast cancer nano-targeted therapy.

Tumor cells, inflammatory cells and chemical factors work together to mediate complex signaling networks, which forms inflammatory tumor microenvironment (TME). The development of breast cancer is closely related to the functional activities of TME. This review introduces the origins of cancer-related chronic inflammation and the main constituents of inflammatory microenvironment. Inflammatory microenvironment plays an important role in breast cancer growth, metastasis, drug resistance and angiogenesis through multifactorial mechanisms. It is suggested that inflammatory microenvironment contributes to providing possible mechanisms of drug action and modes of drug transport for anti-cancer treatment. Nano-drug delivery system (NDDS) becomes a popular topic for optimizing the design of tumor targeting drugs. It is seen that with the development of therapeutic approaches, NDDS can be used to achieve drug-targeted delivery well across the biological barriers and into cells, resulting in superior bioavailability, drug dose reduction as well as off-target side effect elimination. This paper focuses on the review of modulation mechanisms of inflammatory microenvironment and combination with nano-targeted therapeutic strategies, providing a comprehensive basis for further research on breast cancer prevention and control.

Circ_0016760 Serves as a Cancer Promoter in Non-small Cell Lung Cancer Through miR-876-3p/NOVA2 Axis.

Non-small cell lung cancer (NSCLC) is a serious threaten to human health globally. Circular RNAs (circRNAs) were testified to alter the progression of NSCLC. This work intended to investigate the functional role of circ_0016760 in NSCLC development and the potential mechanism. Expression of circ_0016760, microRNA (miR)-876-3p and NOVA alternative splicing regulator 2 (NOVA2) was determined via quantitative reverse transcription-PCT (qRT-PCR) or western blotting. Cell viability, clonogenicity and apoptosis were assessed by Cell Counting Kit-8 (CCK-8) assay, colony formation assay and flow cytometry, respectively. Transwell assay was performed to examine cell migration and invasion. Western blotting was also conducted to detect the levels of epithelial-to-mesenchymal transition (EMT)-related proteins. Role of circ_0016760 in vivo was evaluated via xenograft model assay. Moreover, the interaction between miR-876-3p and circ_0016760 or NOVA2 was verified by dual-luciferase reporter assay or RNA Immunoprecipitation (RIP) assay. Circ_0016760 and NOVA2 were upregulated, while miR-876-3p expression was decreased in NSCLC tissues and cells. Circ_0016760 depletion suppressed NSCLC cell proliferation and metastasis in vitro, as well as hampered tumor growth in vivo. Circ_0016760 acted as a sponge of miR-876-3p, and miR-876-3p could target NOVA2. Circ_0016760 might play vital roles in NSCLC by regulating miR-876-3p/NOVA2 axis. Circ_0016760 could promote the malignant development of NSCLC through miR-876-3p/NOVA2 axis, at least in part.

RNA interference of vATPase subunits A and E affects survival of larvae and adults in Plagiodera versicolora (Coleoptera: Chrysomelidae).

Vacuolar-type H+-ATPases (vATPases) are ATP-driven proton pumps and play essential roles in many physiological functions. Plagiodera versicolora (Coleoptera: Chrysomelidae) is a leaf-eating forest pest found in salicaceous trees worldwide. RNA interference (RNAi) is a powerful tool for functional identify and pest control. In this study, we used RNAi as an approach to knock down subunits A and E of the vATPase gene. The phylogenetic analysis showed that vATPase-A and vATPase-E from the same order were clustered together to form Coleoptera subclades, respectively. The expression levels of vATPase-A and vATPase-E were higher in gut, Malpighian tubules and 1st instar larvae. Ingest the dsvATPase-A and dsvATPase-E significantly inhibited the development of 1st to 3th instar larvae, incapacitated of mating and oviposition in adults. In addition, knockdown of vATPase subunit genes caused higher mortality in larvae and adults. The results demonstrate that RNAi efficiencies both vATPase-A and vATPase-E genes at various larvae stages and adults. Moreover, this research suggested that silencing of two vATPase subunits A and E offers a potential strategy to control P. versicolora.

A Novel Driving Noise Analysis Method for On-Road Traffic Detection.

Effective noise reduction and abnormal feature extraction are important for abnormal sound detection occurring in urban traffic operations. However, to improve the detection accuracy of continuous traffic flow and even overlapping vehicle bodies, effective methods capable to achieve accurate signal-to-noise ratio and appropriate characteristic parameters should be explored. In view of the disadvantages of traditional traffic detection methods, such as Short-Time Energy (STE) and Mel Frequency Cepstral Coefficients (MFCC), this study adopts an improved spectral subtraction method to analyze traffic noise. Through the feature fusion of STE and MFCC coefficients, an innovative feature parameter, E-MFCC, is obtained, assisting to propose a traffic noise detection solution based on Triangular Wave Analysis (TWA). APP Designer in MATLAB was used to establish a traffic detection simulation platform. The experimental results showed that compared with the accuracies of traffic detection using the traditional STE and MFCC methods as 67.77% and 76.01%, respectively, the detection accuracy of the proposed TWA is significantly improved, attaining 91%. The results demonstrated the effectiveness of the traffic detection method proposed in solving the overlapping problem, thus achieving accurate detection of road traffic volume and improving the efficiency of road operation.

High Expression of IKZF2 in Malignant T Cells Promotes Disease Progression in Cutaneous T Cell Lymphoma.

Cutaneous T cell lymphoma is a generally indolent disease derived from skin-homing mature T cells. However, in advanced stages, cutaneous T cell lymphoma may manifest aggressive clinical behaviour and lead to a poor prognosis. The mechanism of disease progression in cutaneous T cell lymphoma remains unknown. This study, based on a large clinical cohort, found that IKZF2, an essential transcription factor during T cell development and differentiation, showed stage- dependent overexpression in the malignant T cells in mycosis fungoides lesions. IKZF2 is specifically over- expressed in advanced-stage mycosis fungoides lesions, and correlates with poor prognosis. Mechanistically, overexpression of IKZF2 promotes cutaneous T cell lymphoma progression via inhibiting malignant cell apoptosis and may contribute to tumour immune escape by downregulating major histocompatibility complex II molecules and up-regulating the production of anti-inflammatory cytokine interleukin-10 by malignant T cells. These results demonstrate the important role of IKZF2 in high-risk cutaneous T cell lymphoma and pave the way for future targeted therapy.

Key Factor Regulating Inflammatory Microenvironment, Metastasis, and Resistance in Breast Cancer: Interleukin-1 Signaling.

Breast cancer is one of the top-ranked cancers for incidence and mortality worldwide. The biggest challenges in breast cancer treatment are metastasis and drug resistance, for which work on molecular evaluation, mechanism studies, and screening of therapeutic targets is ongoing. Factors that lead to inflammatory infiltration and immune system suppression in the tumor microenvironment are potential therapeutic targets. Interleukin-1 is known as a proinflammatory and immunostimulatory cytokine, which plays important roles in inflammatory diseases. Recent studies have shown that interleukin-1 cytokines drive the formation and maintenance of an inflammatory/immunosuppressive microenvironment through complex intercellular signal crosstalk and tight intracellular signal transduction, which were found to be potentially involved in the mechanism of metastasis and drug resistance of breast cancer. Some preclinical and clinical treatments or interventions to block the interleukin-1/interleukin-1 receptor system and its up- and downstream signaling cascades have also been proven effective. This study provides an overview of IL-1-mediated signal communication in breast cancer and discusses the potential of IL-1 as a therapeutic target especially for metastatic breast cancer and combination therapy and current problems, aiming at enlightening new ideas in the study of inflammatory cytokines and immune networks in the tumor microenvironment.

Infectious virus in exhaled breath of symptomatic seasonal influenza cases from a college community.

Little is known about the amount and infectiousness of influenza virus shed into exhaled breath. This contributes to uncertainty about the importance of airborne influenza transmission. We screened 355 symptomatic volunteers with acute respiratory illness and report 142 cases with confirmed influenza infection who provided 218 paired nasopharyngeal (NP) and 30-minute breath samples (coarse >5-µm and fine ≤5-µm fractions) on days 1-3 after symptom onset. We assessed viral RNA copy number for all samples and cultured NP swabs and fine aerosols. We recovered infectious virus from 52 (39%) of the fine aerosols and 150 (89%) of the NP swabs with valid cultures. The geometric mean RNA copy numbers were 3.8 × 104/30-minutes fine-, 1.2 × 104/30-minutes coarse-aerosol sample, and 8.2 × 108 per NP swab. Fine- and coarse-aerosol viral RNA were positively associated with body mass index and number of coughs and negatively associated with increasing days since symptom onset in adjusted models. Fine-aerosol viral RNA was also positively associated with having influenza vaccination for both the current and prior season. NP swab viral RNA was positively associated with upper respiratory symptoms and negatively associated with age but was not significantly associated with fine- or coarse-aerosol viral RNA or their predictors. Sneezing was rare, and sneezing and coughing were not necessary for infectious aerosol generation. Our observations suggest that influenza infection in the upper and lower airways are compartmentalized and independent.

Unravelling Metal Speciation in the Microenvironment Surrounding Phytoplankton Cells to Improve Predictions of Metal Bioavailability.

A lack of knowledge on metal speciation in the microenvironment surrounding phytoplankton cells (i.e., the phycosphere) represents an impediment to accurately predicting metal bioavailability. Phycosphere pH and O2 concentrations from a diversity of algae species were compiled. For marine algae in the light, the average increases were 0.32 pH units and 0.17 mM O2 in the phycosphere, whereas in the dark the average decreases were 0.10 pH units and 0.03 mM O2, in comparison to bulk seawater. In freshwater algae, the phycosphere pH increased by 1.28 units, whereas O2 increased by 0.38 mM in the light. Equilibrium modeling showed that the pH alteration influenced the chemical species distribution (i.e., free ion, inorganic complexes, and organic complexes) of Al, Cd, Co, Cu, Fe, Hg, Mn, Ni, Pb, Sc, Sm, and Zn in the phycosphere, and the O2 fluctuation increased oxidation rates of Cu(I), Fe(II) and Mn(II) from 2 to 938-fold. The pH/O2-induced changes in phycosphere metal chemistry were larger for freshwater algae than for marine species. Reanalyses of algal metal uptake data in the literature showed that uptake of the trivalent metals (Sc, Sm and Fe), in addition to divalent metals, can be better predicted after considering the phycosphere chemistry.

Response of Trametes hirsuta to hexavalent chromium promotes laccase-mediated decolorization of reactive black 5.

The recalcitrant azo dyes combined with heavy metals constitute a major challenge for the bioremediation of industrial effluents. This study aimed to investigate the effect and mechanism of action of a white-rot fungus Trametes hirsuta TH315 on the simultaneous removal of hexavalent chromium [Cr(VI)] and azo dye (Reactive Black 5, RB5). Here, this study discovered that toxic Cr(VI) (1 mM) greatly promoted RB5 decolorization (from 57.15% to 83.65%) by white-rot fungus Trametes hirsuta with high Cr(VI)-reducing ability (>96%), resulting in the simultaneous removal of co-contaminants. On the basis of transcriptomic and biochemical analysis, our study revealed that the oxidative stress in co-contaminants mainly caused by Cr(VI), and a number of dehydrogenases and oxidases showed up-regulation in response to Cr(VI) stress. It was noteworthy that the oxidative stress caused by Cr(VI) in co-contaminants can both significantly induce glutathione S-transferase and laccase expression. Glutathione S-transferase potentially involved in antioxidation against Cr(VI) stress. Laccase was found to play a key role in RB5 decolorization by T. hirsuta. These results suggested that the simultaneous removal of co-contaminants by T. hirsuta could be achieved with Cr(VI) exposure. Overall, the elucidation of the molecular basis in details will help to advance the general knowledge about the fungus by facing harsh environments, and put forward a further possible application of fungi on environmental remediation.

Why Does Cysteine Enhance Metal Uptake by Phytoplankton in Seawater but Not in Freshwater?

Low-molecular-weight weak ligands such as cysteine have been shown to enhance metal uptake by marine phytoplankton in the presence of strong ligands, but the effect is not observed in freshwater. We hypothesized that these contrasting results might be caused by local cysteine degradation and a Ca effect on metal-ligand exchange kinetics in the boundary layer surrounding the algal cells; newly liberated free metal ions cannot be immediately complexed in seawater by Ca-bound strong ligands but can be rapidly complexed by free ligands at low-Ca levels. The present results consistently support this hypothesis. At constant bulk Cd2+ concentrations, buffered by strong ligands: (1) at 50 mM Ca, cysteine addition significantly enhanced Cd uptake in high-Ca preacclimated euryhaline Chlamydomonas reinhardtii (cultured with cysteine as a nitrogen source to enhance local Cd2+ liberation via cysteine degradation); (2) at 0.07 mM Ca, this enhancement was not observed in the algae; (3) at 50 mM Ca, the enhancement disappeared when C. reinhardtii were cultured with ammonium (to inhibit cysteine degradation and local Cd2+ liberation); (4) cysteine addition did not enhance Cd uptake by cysteine-cultured marine Thalassiosira weissflogii when the concentration of immediately reacting strong ligands was sufficient to complex local Cd2+ liberation.

Multi-atlas active contour segmentation method using template optimization algorithm.

BACKGROUND: Brain image segmentation is the basis and key to brain disease diagnosis, treatment planning and tissue 3D reconstruction. The accuracy of segmentation directly affects the therapeutic effect. Manual segmentation of these images is time-consuming and subjective. Therefore, it is important to research semi-automatic and automatic image segmentation methods. In this paper, we propose a semi-automatic image segmentation method combined with a multi-atlas registration method and an active contour model (ACM). METHOD: We propose a multi-atlas active contour segmentation method using a template optimization algorithm. First, a multi-atlas registration method is used to obtain the prior shape information of the target tissue, and then a label fusion algorithm is used to generate the initial template. Second, a template optimization algorithm is used to reduce the multi-atlas registration errors and generate the initial active contour (IAC). Finally, a ACM is used to segment the target tissue. RESULTS: The proposed method was applied to the challenging publicly available MR datasets IBSR and MRBrainS13. In the MRBrainS13 datasets, we obtained an average thalamus Dice similarity coefficient of 0.927 ± 0.014 and an average Hausdorff distance (HD) of 2.92 ± 0.53. In the IBSR datasets, we obtained a white matter (WM) average Dice similarity coefficient of 0.827 ± 0.04 and a gray gray matter (GM) average Dice similarity coefficient of 0.853 ± 0.03. CONCLUSION: In this paper, we propose a semi-automatic brain image segmentation method. The main contributions of this paper are as follows: 1) Our method uses a multi-atlas registration method based on affine transformation, which effectively reduces the multi-atlas registration time compared to the complex nonlinear registration method. The average registration time of each target image in the IBSR datasets is 255 s, and the average registration time of each target image in the MRBrainS13 datasets is 409 s. 2) We used a template optimization algorithm to improve registration error and generate a continuous IAC. 3) Finally, we used a ACM to segment the target tissue and obtain a smooth continuous target contour.

Uptake and subcellular distribution of aluminum in a marine diatom.

Aluminum (Al) is widespread in the environment including the ocean. The effects of Al on marine organisms have attracted more and more attention in recent years. However, the mechanisms of uptake of Al by marine organisms and the subcellular distribution of Al once assimilated are unknown. Here we report the uptake and subcellular distribution of Al in a marine diatom Thalassiosira weissflogii. Short-term (< 120 min) uptake experiments showed that the Al uptake rate by the diatom was 0.033 ±â€¯0.013 fmol-1 cell-1 min-1 (internalization flux normalized to the exposure Al concentration of 2 µM = 0.034 ±â€¯0.013 nmol m-2 min-1 nM-1). Subcellular fractionation experiments showed that the internalized Al was partitioned to subcellular components in the following order: granules (69 ±â€¯5%) > debris (17 ±â€¯4%) > organelles (12 ±â€¯2%) > heat-stable peptides (HSP) (~2%) > heat-denaturable proteins (HDP) (< 1%), indicating that the majority of intracellular Al was detoxified and stored in inorganic forms. The subcellular distribution of Al in the diatom is different from that of Al in freshwater green algae, in which most of the internalized Al is partitioned to organelles. We also evaluated an artificial seawater-based EDTA rinse solution to remove Al adsorbed on the diatom cell surface. Overall, our study provides new information to understand the mechanisms of uptake of Al by marine diatoms, and the mechanisms responsible for the biological effects (both toxic and beneficial) of Al on the growth of marine phytoplankton, especially diatoms.

Chemical Conditions in the Boundary Layer Surrounding Phytoplankton Cells Modify Cadmium Bioavailability.

In this study we tested the hypothesis that metal uptake by unicellular algae may be affected by changes in metal speciation in the boundary layer surrounding the algal cells. The freshwater alga Chlamydomonas reinhardtii was preacclimated to different N nutrition regimes; changes in N nutrition are known to change the nature of extracellular metabolites (e.g., reactive oxygen species "ROS", and OH-) and thus boundary layer chemical conditions. Specifically, at a constant bulk free Cd2+ concentration, Cd uptake by N-starved algae in cysteine-buffered solution was significantly higher than that in NTA-buffered solution. This enhancement was likely due to an increase of the free Cd2+ concentration in the boundary layer, resulting from localized cysteine oxidation by ROS released from these algae. On the other hand, Cd uptake was markedly lower when the free Cd2+ concentration near cell surface decreased as a result of an increase in the boundary layer pH of nitrate-acclimated algae or enhanced localized metal complexation. The results imply that redox, acid-base and metal complexation processes in the boundary layer differ from those in bulk water, even under chemically stable bulk conditions, and the boundary layer effect may well be of significance to phytoplankton acquisition of other trace metals.