Enhancing Clinical Predictive Modeling through Model Complexity-Driven Class Proportion Tuning for Class Imbalanced Data: An Empirical Study on Opioid Overdose Prediction.

Class imbalance issues are prevalent in the medical field and significantly impact the performance of clinical predictive models. Traditional techniques to address this challenge aim to rebalance class proportions. They generally assume that the rebalanced proportions are derived from the original data, without considering the intricacies of the model utilized. This study challenges the prevailing assumption and introduces a new method that ties the optimal class proportions to model complexity. This approach allows for individualized tuning of class proportions for each model. Our experiments, centered on the opioid overdose prediction problem, highlight the performance gains achieved by this approach. Furthermore, rigorous regression analysis affirms the merits of the proposed theoretical framework, demonstrating a statistically significant correlation between hyperparameters controlling model complexity and the optimal class proportions.

Entropy and distance-guided super self-ensembling for optic disc and cup segmentation.

Segmenting the optic disc (OD) and optic cup (OC) is crucial to accurately detect changes in glaucoma progression in the elderly. Recently, various convolutional neural networks have emerged to deal with OD and OC segmentation. Due to the domain shift problem, achieving high-accuracy segmentation of OD and OC from different domain datasets remains highly challenging. Unsupervised domain adaptation has taken extensive focus as a way to address this problem. In this work, we propose a novel unsupervised domain adaptation method, called entropy and distance-guided super self-ensembling (EDSS), to enhance the segmentation performance of OD and OC. EDSS is comprised of two self-ensembling models, and the Gaussian noise is added to the weights of the whole network. Firstly, we design a super self-ensembling (SSE) framework, which can combine two self-ensembling to learn more discriminative information about images. Secondly, we propose a novel exponential moving average with Gaussian noise (G-EMA) to enhance the robustness of the self-ensembling framework. Thirdly, we propose an effective multi-information fusion strategy (MFS) to guide and improve the domain adaptation process. We evaluate the proposed EDSS on two public fundus image datasets RIGA+ and REFUGE. Large amounts of experimental results demonstrate that the proposed EDSS outperforms state-of-the-art segmentation methods with unsupervised domain adaptation, e.g., the Dicemean score on three test sub-datasets of RIGA+ are 0.8442, 0.8772 and 0.9006, respectively, and the Dicemean score on the REFUGE dataset is 0.9154.

Chimeric antigen receptor-natural killer cell therapy: current advancements and strategies to overcome challenges.

Chimeric antigen receptor-natural killer (CAR-NK) cell therapy is a novel immunotherapy targeting cancer cells via the generation of chimeric antigen receptors on NK cells which recognize specific cancer antigens. CAR-NK cell therapy is gaining attention nowadays owing to the ability of CAR-NK cells to release potent cytotoxicity against cancer cells without side effects such as cytokine release syndrome (CRS), neurotoxicity and graft-versus-host disease (GvHD). CAR-NK cells do not require antigen priming, thus enabling them to be used as "off-the-shelf" therapy. Nonetheless, CAR-NK cell therapy still possesses several challenges in eliminating cancer cells which reside in hypoxic and immunosuppressive tumor microenvironment. Therefore, this review is envisioned to explore the current advancements and limitations of CAR-NK cell therapy as well as discuss strategies to overcome the challenges faced by CAR-NK cell therapy. This review also aims to dissect the current status of clinical trials on CAR-NK cells and future recommendations for improving the effectiveness and safety of CAR-NK cell therapy.

Anisotropic materials with abnormal Poisson's ratios and acoustic velocities.

Isotropic materials are required to adhere to various mechanical principles due to their limited thermal stability. For instance, it is essential for Poisson's ratio to be within the range of -1 to 0.5, and the longitudinal wave velocity must exceed the transverse wave velocity. Nevertheless, perfect crystals, as anisotropic materials, have the ability to defy conventional rules. Through the integration of high-throughput processes and first-principles calculations, a comprehensive exploration of known materials was conducted, resulting in the establishment of a database featuring an extreme anisotropic mechanism. This included the identification of abnormal Poisson's ratios (with the directional Poisson's ratio ranging from -3.00 to 3.67), the discovery of extreme negative linear compressibility, the determination of the upper and lower limits of the sound velocity, and other associated properties. Several materials with abnormal Poisson's ratios (<-1 or >0.5) were listed, and their peculiar mechanical behavior, wherein the volume decreased counterintuitively with uniaxial tension, was discussed. Finally, this study focused on the velocities of longitudinal and transverse waves, with specific emphasis on materials exhibiting transverse wave velocities that exceeded the longitudinal wave velocities.

Genome-wide identification of GRF transcription factors and their expression profile in stem meristem of broomcorn millet (Panicum miliaceum L.).

To understand the genome-wide information of the GRF family genes in broomcorn millet and their expression profile in the vegetative meristems, bioinformatic methods and transcriptome sequencing were used to analyze the characteristics, physical and chemical properties, phylogenetic relationship, chromosome distribution, gene structure, cis-acting elements and expression profile in stem meristem for the GRF family members. The results showed that the GRF gene family of millet contains 21 members, and the PmGRF gene is unevenly distributed on 12 chromosomes. The lengths of PmGRF proteins vary from 224 to 618 amino acids, and the isoelectric points are between 4.93-9.69. Each member of the family has 1-4 introns and 2-5 exons. The protein PmGRF13 is localized in both the nucleus and chloroplast, and the rest PmGRF proteins are located in the nucleus. Phylogenetic analysis showed that the 21 GRF genes were divided into 4 subfamilies (A,B,C and D) in broomcorn millet. The analysis of cis-acting elements showed that there were many cis-acting elements involved in light response, hormone response, drought induction, low temperature response and other environmental stress responses in the 2000 bp sequence upstream of the GRF genes. Transcriptome sequencing and qRT-PCR analyses showed that the expression levels of PmGRF3 and PmGRF12 in the dwarf variety Zhang778 were significantly higher than those of the tall variety Longmi12 in the internode and node meristems at the jointing stage, while the expression patterns of PmGRF4, PmGRF16 and PmGRF21 were reverse. In addition, the expression levels of PmGRF2 and PmGRF5 in the internode of Zhang778 were significantly higher than Longmi12. The other GRF genes were not or insignificantly expressed. These results indicated that seven genes, PmGRF2, PmGRF3, PmGRF4, PmGRF5, PmGRF12, PmGRF16 and PmGRF21, were related to the formation of plant height in broomcorn millet.

Salvage haploidentical transplantation for graft failure after first haploidentical allogeneic stem cell transplantation: an updated experience.

Graft failure is a fatal complication following allogeneic stem cell transplantation where a second transplantation is usually required for salvage. However, there are no recommended regimens for second transplantations for graft failure, especially in the haploidentical transplant setting. We recently reported encouraging outcomes using a novel method (haploidentical transplantation from a different donor after conditioning with fludarabine and cyclophosphamide). Herein, we report updated outcomes in 30 patients using this method. The median time of the second transplantation was 96.5 (33-215) days after the first transplantation. Except for one patient who died at +19d and before engraftment, neutrophil engraftments were achieved in all patients at 11 (8-24) days, while platelet engraftments were achieved in 22 (75.8%) patients at 17.5 (9-140) days. The 1-year OS and DFS were 60% and 53.3%, and CIR and TRM was 6.7% and 33.3%, respectively. Compared with the historical group, neutrophil engraftment (100% versus 58.5%, p < 0.001) and platelet engraftment (75.8% versus 32.3%, p < 0.001) were better in the novel regimen group, and OS was also improved (60.0% versus 26.4%, p = 0.011). In conclusion, salvage haploidentical transplantation from a different donor using the novel regimen represents a promising option to rescue patients with graft failure after the first haploidentical transplantation.

Novel Isoalantolactone-Based Derivatives as Potent NLRP3 Inflammasome Inhibitors: Design, Synthesis, and Biological Characterization.

The NLRP3 inflammasome has been recognized as a promising therapeutic target in drug discovery for inflammatory diseases. Our initial research identified a natural sesquiterpene isoalantolactone (IAL) as the active scaffold targeting NLRP3 inflammasome. To improve its activity and metabolic stability, a total of 64 IAL derivatives were designed and synthesized. Among them, compound 49 emerged as the optimal lead, displaying the most potent inhibitory efficacy on nigericin-induced IL-1ß release in THP-1 cells, with an IC50 value of 0.29 µM, approximately 27-fold more potent than that of IAL (IC50: 7.86 µM), and exhibiting higher metabolic stability. Importantly, 49 remarkably improved DSS-induced ulcerative colitis in vivo. Mechanistically, we demonstrated that 49 covalently bound to cysteine 279 in the NACHT domain of NLRP3, thereby inhibiting the assembly and activation of NLRP3 inflammasome. These results provided compelling evidence to further advance the development of more potent NLRP3 inhibitors based on this scaffold.

Safe Viewing of Solar Eclipses.

This JAMA Patient Page describes solar eclipses and how to view them safely.

SwinUNet: a multiscale feature learning approach to cardiovascular magnetic resonance parametric mapping for myocardial tissue characterization.

Objective.Cardiovascular magnetic resonance (CMR) can measure T1 and T2 relaxation times for myocardial tissue characterization. However, the CMR procedure for T1/T2 parametric mapping is time-consuming, making it challenging to scan heart patients routinely in clinical practice. This study aims to accelerate CMR parametric mapping with deep learning.Approach. A deep-learning model, SwinUNet, was developed to accelerate T1/T2 mapping. SwinUNet used a convolutional UNet and a Swin transformer to form a hierarchical 3D computation structure, allowing for analyzing CMR images spatially and temporally with multiscale feature learning. A comparative study was conducted between SwinUNet and an existing deep-learning model, MyoMapNet, which only used temporal analysis for parametric mapping. The T1/T2 mapping performance was evaluated globally using mean absolute error (MAE) and structural similarity index measure (SSIM). The clinical T1/T2 indices for characterizing the left-ventricle myocardial walls were also calculated and evaluated using correlation and Bland-Altman analysis.Main results. We performed accelerated T1 mapping with ≤4 heartbeats and T2 mapping with 2 heartbeats in reference to the clinical standard, which required 11 heartbeats for T1 mapping and 3 heartbeats for T2 mapping. SwinUNet performed well in all the experiments (MAE < 50 ms, SSIM > 0.8, correlation > 0.75, and Bland-Altman agreement limits < 100 ms for T1 mapping; MAE < 1 ms, SSIM > 0.9, correlation > 0.95, and Bland-Altman agreement limits < 1.5 ms for T2 mapping). When the maximal acceleration was used (2 heartbeats), SwinUNet outperformed MyoMapNet and gave measurement accuracy similar to the clinical standard.Significance. SwinUNet offers an optimal solution to CMR parametric mapping for assessing myocardial diseases quantitatively in clinical cardiology.

BGF-Net: Boundary guided filter network for medical image segmentation.

How to fuse low-level and high-level features effectively is crucial to improving the accuracy of medical image segmentation. Most CNN-based segmentation models on this topic usually adopt attention mechanisms to achieve the fusion of different level features, but they have not effectively utilized the guided information of high-level features, which is often highly beneficial to improve the performance of the segmentation model, to guide the extraction of low-level features. To address this problem, we design multiple guided modules and develop a boundary-guided filter network (BGF-Net) to obtain more accurate medical image segmentation. To the best of our knowledge, this is the first time that boundary guided information is introduced into the medical image segmentation task. Specifically, we first propose a simple yet effective channel boundary guided module to make the segmentation model pay more attention to the relevant channel weights. We further design a novel spatial boundary guided module to complement the channel boundary guided module and aware of the most important spatial positions. Finally, we propose a boundary guided filter to preserve the structural information from the previous feature map and guide the model to learn more important feature information. Moreover, we conduct extensive experiments on skin lesion, polyp, and gland segmentation datasets including ISIC 2016, CVC-EndoSceneStil and GlaS to test the proposed BGF-Net. The experimental results demonstrate that BGF-Net performs better than other state-of-the-art methods.

Retinal vessel segmentation based on multi-scale feature and style transfer.

Retinal vessel segmentation is very important for diagnosing and treating certain eye diseases. Recently, many deep learning-based retinal vessel segmentation methods have been proposed; however, there are still many shortcomings (e.g., they cannot obtain satisfactory results when dealing with cross-domain data or segmenting small blood vessels). To alleviate these problems and avoid overly complex models, we propose a novel network based on a multi-scale feature and style transfer (MSFST-NET) for retinal vessel segmentation. Specifically, we first construct a lightweight segmentation module named MSF-Net, which introduces the selective kernel (SK) module to increase the multi-scale feature extraction ability of the model to achieve improved small blood vessel segmentation. Then, to alleviate the problem of model performance degradation when segmenting cross-domain datasets, we propose a style transfer module and a pseudo-label learning strategy. The style transfer module is used to reduce the style difference between the source domain image and the target domain image to improve the segmentation performance for the target domain image. The pseudo-label learning strategy is designed to be combined with the style transfer module to further boost the generalization ability of the model. Moreover, we trained and tested our proposed MSFST-NET in experiments on the DRIVE and CHASE_DB1 datasets. The experimental results demonstrate that MSFST-NET can effectively improve the generalization ability of the model on cross-domain datasets and achieve improved retinal vessel segmentation results than other state-of-the-art methods.

Severe Intraocular Inflammation Following Intravitreal Faricimab.

Importance: Monitoring for and reporting potential cases of intraocular inflammation (IOI) in clinical practice despite limited occurrences in clinical trials, including experiences with relatively new intravitreal agents, such as brolucizumab, pegcetacoplan, or faricimab, helps balance potential benefits and risks of these agents. Objective: To provide descriptions of 3 initially culture-negative cases of acute, severe, posterior-segment IOI events occurring within the same month following intravitreal faricimab injections at a single institution. Design, Setting, and Participants: In this case series, 3 patients manifesting acute, severe IOI following intravitreal injection of faricimab were identified between September 20, 2023, and October 20, 2023. Exposure: Faricimab, 6 mg (0.05 mL of 120 mg/mL solution), for neovascular age-related macular degeneration among patients previously treated with aflibercept; 1 patient also had prior exposure to bevacizumab. Main Outcomes and Measures: Visual acuity, vitreous taps for bacterial or fungal cultures, and retinal imaging. Results: All 3 patients received intravitreal faricimab injections between September 20 and October 20, 2023, from 2 different lot numbers (expiration dates, July 2025) at 3 locations of 1 institution among 3 of 19 retina physicians. Visual acuities with correction were 20/63 OS for patient 1, 20/40 OD for patient 2, and 20/20 OS for patient 3 prior to injection. All 3 patients developed acute, severe inflammation involving the anterior and posterior segment within 3 to 4 days after injection, with visual acuities of hand motion OS, counting fingers OD, and hand motion OS, respectively. Two patients were continuing faricimab treatment while 1 patient was initiating faricimab treatment. All received intravitreal ceftazidime, 2.2 mg/0.1 mL, and vancomycin, 1 mg/0.1 mL, immediately following vitreous taps. All vitreous tap culture results were negative. One patient underwent vitrectomy 1 day following presentation. Intraoperative vitreous culture grew 1 colony of Staphylococcus epidermidis, judged a likely contaminant by infectious disease specialists. All symptoms resolved within 1 month; visual acuities with correction were 20/100 OS for patient 1, 20/50 OD for patient 2, and 20/30 OS for patient 3. Conclusions and Relevance: In this case series, 3 patients with acute, severe IOI within 1 month at 3 different locations among 3 ophthalmologists of 1 institution following intravitreal faricimab could represent some unknown storage or handling problem. However, this cluster suggests such inflammatory events may be more common than anticipated from faricimab trial reports, emphasizing the continued need for vigilance to detect and report such cases following regulatory approval.

Mesenchymal stromal cells plus basiliximab improve the response of steroid-refractory acute graft-versus-host disease as a second-line therapy: a multicentre, randomized, controlled trial.

BACKGROUND: For patients with steroid-refractory acute graft-versus-host disease (SR-aGVHD), effective second-line regimens are urgently needed. Mesenchymal stromal cells (MSCs) have been used as salvage regimens for SR-aGVHD in the past. However, clinical trials and an overall understanding of the molecular mechanisms of MSCs combined with basiliximab for SR-aGVHD are limited, especially in haploidentical haemopoietic stem cell transplantation (HID HSCT). METHODS: The primary endpoint of this multicentre, randomized, controlled trial was the 4-week complete response (CR) rate of SR-aGVHD. A total of 130 patients with SR-aGVHD were assigned in a 1:1 randomization schedule to the MSC group (receiving basiliximab plus MSCs) or control group (receiving basiliximab alone) (NCT04738981). RESULTS: Most enrolled patients (96.2%) received HID HSCT. The 4-week CR rate of SR-aGVHD in the MSC group was obviously better than that in the control group (83.1% vs. 55.4%, P = 0.001). However, for the overall response rates at week 4, the two groups were comparable. More patients in the control group used ≥ 6 doses of basiliximab (4.6% vs. 20%, P = 0.008). We collected blood samples from 19 consecutive patients and evaluated MSC-derived immunosuppressive cytokines, including HO1, GAL1, GAL9, TNFIA6, PGE2, PDL1, TGF-ß and HGF. Compared to the levels before MSC infusion, the HO1 (P = 0.0072) and TGF-ß (P = 0.0243) levels increased significantly 1 day after MSC infusion. At 7 days after MSC infusion, the levels of HO1, GAL1, TNFIA6 and TGF-ß tended to increase; however, the differences were not statistically significant. Although the 52-week cumulative incidence of cGVHD in the MSC group was comparable to that in the control group, fewer patients in the MSC group developed cGVHD involving ≥3 organs (14.3% vs. 43.6%, P = 0.006). MSCs were well tolerated, no infusion-related adverse events (AEs) occurred and other AEs were also comparable between the two groups. However, patients with malignant haematological diseases in the MSC group had a higher 52-week disease-free survival rate than those in the control group (84.8% vs. 65.9%, P = 0.031). CONCLUSIONS: For SR-aGVHD after allo-HSCT, especially HID HSCT, the combination of MSCs and basiliximab as the second-line therapy led to significantly better 4-week CR rates than basiliximab alone. The addition of MSCs not only did not increase toxicity but also provided a survival benefit.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer.

BACKGROUND: Pathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30-40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60-70% show residual disease (RD). The role of the tumor microenvironment in NAC response in patients with TNBC remains unclear. In this study, we developed a machine learning-based two-step pipeline to distinguish between various histological components in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of TNBC tissue biopsies and to identify histological features that can predict NAC response. METHODS: H&E-stained WSIs of treatment-naïve biopsies from 85 patients (51 with pCR and 34 with RD) of the model development cohort and 79 patients (41 with pCR and 38 with RD) of the validation cohort were separated through a stratified eightfold cross-validation strategy for the first step and leave-one-out cross-validation strategy for the second step. A tile-level histology label prediction pipeline and four machine-learning classifiers were used to analyze 468,043 tiles of WSIs. The best-trained classifier used 55 texture features from each tile to produce a probability profile during testing. The predicted histology classes were used to generate a histology classification map of the spatial distributions of different tissue regions. A patient-level NAC response prediction pipeline was trained with features derived from paired histology classification maps. The top graph-based features capturing the relevant spatial information across the different histological classes were provided to the radial basis function kernel support vector machine (rbfSVM) classifier for NAC treatment response prediction. RESULTS: The tile-level prediction pipeline achieved 86.72% accuracy for histology class classification, while the patient-level pipeline achieved 83.53% NAC response (pCR vs. RD) prediction accuracy of the model development cohort. The model was validated with an independent cohort with tile histology validation accuracy of 83.59% and NAC prediction accuracy of 81.01%. The histological class pairs with the strongest NAC response predictive ability were tumor and tumor tumor-infiltrating lymphocytes for pCR and microvessel density and polyploid giant cancer cells for RD. CONCLUSION: Our machine learning pipeline can robustly identify clinically relevant histological classes that predict NAC response in TNBC patients and may help guide patient selection for NAC treatment.

Correction: An E-selectin targeting and MMP-2-responsive dextran-curcumin polymeric prodrug for targeted therapy of acute kidney injury.

Correction for 'An E-selectin targeting and MMP-2-responsive dextran-curcumin polymeric prodrug for targeted therapy of acute kidney injury' by Jing-Bo Hu et al., Biomater. Sci., 2018, 6, 3397-3409, https://doi.org/10.1039/C8BM00813B.

Effects of organic carbon and subsurface dams on saltwater intrusion and nitrate pollution in sandy coastal aquifers.

This study explores the impact of a novel approach on the levels of SWI (saltwater intrusion) and NO3- (nitrate) contamination. Some numerical simulations were conducted utilizing a coupled model that incorporates variably saturation and density, as well as convection diffusion reaction within a sandy coastal aquifer. We verified the reliability of the model for SWI based on comparison lab experiments and for chemical reactions based on a comparison of previous in situ observations. Cutoff walls and subsurface dams cannot simultaneously control SWI and reduce NO3- contamination. A novel approach that combines subsurface dams and permeable CH2O (organic carbon) walls (PC-Wall) is proposed. Subsurface dams are utilized to prevent SWI, while PC-Walls are employed to mitigate NO3- pollution. Results demonstrate that the construction of a PC-Wall with a concentration of 1.0 mM facilitated a transition from nitrification (Ni)-dominated to denitrification (Dn)-dominated. An increase in CH2O concentration to 1.0 mM caused a significant 1942.5 % rise in mDn (the mass of NO3- removed through Dn). Increment of the distance between the PC-Wall and the ocean from 35 to 45 m could result in a 103.7 % mDn increase and reduce mN (the compound mass of NO3- remaining in the aquifer) by 11.7 %. The study offers a detailed comprehension of the intricate hydrodynamics of SWI and NO3- pollution. In addition, it provides design guidance for engineering to mitigate contamination by NO3- and controlling SWI, thus fostering the management of groundwater quality.

TRPV4-mediated Ca2+ deregulation causes mitochondrial dysfunction via the AKT/α-synuclein pathway in dopaminergic neurons.

Mutations in the gene encoding the transient receptor potential vanilloid member 4 (TRPV4), a Ca2+ permeable nonselective cation channel, cause TRPV4-related disorders. TRPV4 is widely expressed in the brain; however, the pathogenesis underlying TRPV4-mediated Ca2+ deregulation in neurodevelopment remains unresolved and an effective therapeutic strategy remains to be established. These issues were addressed by isolating mutant dental pulp stem cells from a tooth donated by a child diagnosed with metatropic dysplasia with neurodevelopmental comorbidities caused by a gain-of-function TRPV4 mutation, c.1855C > T (p.L619F). The mutation was repaired using CRISPR/Cas9 to generate corrected isogenic stem cells. These stem cells were differentiated into dopaminergic neurons and the pharmacological effects of folic acid were examined. In mutant neurons, constitutively elevated cytosolic Ca2+ augmented AKT-mediated α-synuclein (α-syn) induction, resulting in mitochondrial Ca2+ accumulation and dysfunction. The TRPV4 antagonist, AKT inhibitor, or α-syn knockdown, normalizes the mitochondrial Ca2+ levels in mutant neurons, suggesting the importance of mutant TRPV4/Ca2+/AKT-induced α-syn in mitochondrial Ca2+ accumulation. Folic acid was effective in normalizing mitochondrial Ca2+ levels via the transcriptional repression of α-syn and improving mitochondrial reactive oxygen species levels, adenosine triphosphate synthesis, and neurite outgrowth of mutant neurons. This study provides new insights into the neuropathological mechanisms underlying TRPV4-related disorders and related therapeutic strategies.

Banff Digital Pathology Working Group: Image Bank, Artificial Intelligence Algorithm, and Challenge Trial Developments.

The Banff Digital Pathology Working Group (DPWG) was established with the goal to establish a digital pathology repository; develop, validate, and share models for image analysis; and foster collaborations using regular videoconferencing. During the calls, a variety of artificial intelligence (AI)-based support systems for transplantation pathology were presented. Potential collaborations in a competition/trial on AI applied to kidney transplant specimens, including the DIAGGRAFT challenge (staining of biopsies at multiple institutions, pathologists' visual assessment, and development and validation of new and pre-existing Banff scoring algorithms), were also discussed. To determine the next steps, a survey was conducted, primarily focusing on the feasibility of establishing a digital pathology repository and identifying potential hosts. Sixteen of the 35 respondents (46%) had access to a server hosting a digital pathology repository, with 2 respondents that could serve as a potential host at no cost to the DPWG. The 16 digital pathology repositories collected specimens from various organs, with the largest constituent being kidney (n = 12,870 specimens). A DPWG pilot digital pathology repository was established, and there are plans for a competition/trial with the DIAGGRAFT project. Utilizing existing resources and previously established models, the Banff DPWG is establishing new resources for the Banff community.

The sulfate assimilation and reduction of marine microalgae and the regulation of illumination.

To examine the sulfate assimilation and reduction process and the regulation of illumination, diatom Phaeodactylum tricornutum and dinoflagellate Amphidinium carterae were selected for continuous simulation incubation under different photon flux densities (PFDs) (54, 108 and 162 µmol photons m-2 s-1), and concentration variations of related sulfur compounds sulfate, dimethylsulfoniopropionate (DMSP), dimethylsulfide (DMS) and acrylic acid (AA) in the culture system were observed. The optimal PFD for the growth of two microalgae was 108 µmol photons m-2 s-1. However, the maximum sulfate absorption occurred at 162 µmol photons m-2 s-1 for P. tricornutum and at 54 µmol photons m-2 s-1 for A. carterae. With the increase of PFD, the release of DMSP by P. tricornutum decreased while A. carterae increased. The largest release amount of DMS was 0.59 ± 0.05 fmol cells-1 for P. tricornutum and 2.61 ± 0.89 fmol cells-1 for A. carterae under their optimum growth light condition. The sulfate uptake of P. tricornutum was inhibited by the addition of amino acids, cysteine had a greater inhibitory effect than methionine, and the absorption process was controlled by light. The intermediate products of sulfur metabolism had an up-control effect on the sulfate uptake process of P. tricornutum. However, the addition of amino acids had no obvious effect on the sulfate absorption of A. carterae.