Bidirectional dynamic frame prediction network for total-body [68Ga]Ga-PSMA-11 and [68Ga]Ga-FAPI-04 PET images.

PURPOSE: Total-body dynamic positron emission tomography (PET) imaging with total-body coverage and ultrahigh sensitivity has played an important role in accurate tracer kinetic analyses in physiology, biochemistry, and pharmacology. However, dynamic PET scans typically entail prolonged durations ([Formula: see text]60 minutes), potentially causing patient discomfort and resulting in artifacts in the final images. Therefore, we propose a dynamic frame prediction method for total-body PET imaging via deep learning technology to reduce the required scanning time. METHODS: On the basis of total-body dynamic PET data acquired from 13 subjects who received [68Ga]Ga-FAPI-04 (68Ga-FAPI) and 24 subjects who received [68Ga]Ga-PSMA-11 (68Ga-PSMA), we propose a bidirectional dynamic frame prediction network that uses the initial and final 10 min of PET imaging data (frames 1-6 and frames 25-30, respectively) as inputs. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were employed as evaluation metrics for an image quality assessment. Moreover, we calculated parametric images (68Ga-FAPI: [Formula: see text], 68Ga-PSMA: [Formula: see text]) based on the supplemented sequence data to observe the quantitative accuracy of our approach. Regions of interest (ROIs) and statistical analyses were utilized to evaluate the performance of the model. RESULTS: Both the visual and quantitative results illustrate the effectiveness of our approach. The generated dynamic PET images yielded PSNRs of 36.056 ± 0.709 dB for the 68Ga-PSMA group and 33.779 ± 0.760 dB for the 68Ga-FAPI group. Additionally, the SSIM reached 0.935 ± 0.006 for the 68Ga-FAPI group and 0.922 ± 0.009 for the 68Ga-PSMA group. By conducting a quantitative analysis on the parametric images, we obtained PSNRs of 36.155 ± 4.813 dB (68Ga-PSMA, [Formula: see text]) and 43.150 ± 4.102 dB (68Ga-FAPI, [Formula: see text]). The obtained SSIM values were 0.932 ± 0.041 (68Ga-PSMA) and 0.980 ± 0.011 (68Ga-FAPI). The ROI analysis conducted on our generated dynamic PET sequences also revealed that our method can accurately predict temporal voxel intensity changes, maintaining overall visual consistency with the ground truth. CONCLUSION: In this work, we propose a bidirectional dynamic frame prediction network for total-body 68Ga-PSMA and 68Ga-FAPI PET imaging with a reduced scan duration. Visual and quantitative analyses demonstrated that our approach performed well when it was used to predict one-hour dynamic PET images. https://github.com/OPMZZZ/BDF-NET .

Site-specific drug release of monomethyl fumarate to treat oxidative stress disorders.

Treatment of diseases of oxidative stress through activation of the antioxidant nuclear factor E2-related factor 2 (NRF2) is limited by systemic side effects. We chemically functionalize the NRF2 activator monomethyl fumarate to require Baeyer-Villiger oxidation for release of the active drug at sites of oxidative stress. This prodrug reverses chronic pain in mice with reduced side effects and could be applied to other disorders of oxidative stress.

Influence of NH3 flow rate on the photoelectric properties of high Al content p-AlGaN.

High Al content (60%) p-AlGaN with different NH3 flow rates was grown using metal-organic chemical vapor deposition (MOCVD), and changes in its photoelectric properties were studied using the Hall effect tester (Hall) and cathodoluminescence (CL) spectrometer. The results show that the film resistivity increases from 3.8â€…Ω·cm to 46.5â€…Ω·cm with increasing NH3 flow rate. The impurity peak intensity of p-AlGaN grown under high NH3 flow conditions is particularly high, indicating numerous point defects. The results of high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) show a large number of Ga interstitial atoms (Gai) at the interface. As Gai acts as a donor, this may be the main reason for the increase in resistivity. And under high NH3 flow conditions, a lattice distortion and a high density of dislocation occur between p-AlGaN and p-GaN, which can lead to enhanced carrier scattering and decreased mobility. Additional validation via LED growth experiments indicates that the luminescence intensity of samples with low ammonia concentration increased by more than 13000 times.

Clinical Outcome of Induction Treatment in the Era of Novel Agents and the Impact of the Number of High-Risk Cytogenetic Abnormalities (HRA) on Prognosis of Patients With Newly Diagnosed Multiple Myeloma (NDMM): Insights From a Multicenter Study.

BACKGROUND: In the era of novel agents, the clinical outcomes of induction treatment and the impact of the number of high-risk cytogenetic abnormalities (HRA) in newly diagnosed multiple myeloma (NDMM) need to be explored. OBJECTIVE: Through this study, we aim to analyze the effectiveness of different induction treatments and explore the survival outcomes of patients with varying numbers of HRA. METHODS: A total of 734 patients from seven medical centers were included in our study. RESULTS: Patients in the CD38 monoclonal antibody or IMiDs plus proteasome inhibitors (PI) groups had significantly superior overall survival (OS) and progression-free survival (PFS) compared to those receiving IMiDs or PI alone. Additionally, the CD38 monoclonal antibody conferred a PFS advantage over IMiDs plus PI. Patients with ≥ 2 high-risk cytogenetic abnormalities (HRA) exhibited an extremely poor prognosis and should be considered ultra-high-risk individuals in multiple myeloma (MM). The CD38 monoclonal antibody, transplantation, and achieving minimal residual disease (MRD) negativity only partly mitigated the poor prognosis in patients with HRA. Furthermore, patients with 1q21 gain/amplification (1q21+) only had a significantly worse prognosis compared to patients without HRA, and those with 1q21+ plus del17p or t(4;14) exhibited an inferior prognosis compared to those with 1q21+ alone. CONCLUSION: Our results suggested that double-hit multiple myeloma was associated with extremely poor survival outcomes, and more effective treatments needed to be explored for this particular subtype of MM.

Plant diversity increases diversity and network complexity rather than alters community assembly processes of leaf-associated fungi in a subtropical forest.

Plant diversity significantly impacts ecosystem processes and functions, yet its influence on the community assembly of leaf fungi remains poorly understood. In this study, we investigated leaf epiphytic and endophytic fungal communities in a Chinese subtropical tree species richness experiment, ranging from 1 to 16 species, using amplicon sequencing to target the internal transcribed spacer 1 region of the rDNA. We found that the community assembly of epiphytic and endophytic fungi was predominantly governed by stochastic processes, with a higher contribution of dispersal limitation on epiphytic than on endophytic fungal communities but a higher contribution of selection on endophytic than on epiphytic fungal communities. The plant-epiphytic fungus interaction network was more complex (e.g., more highly connected and strongly nested but less specialized and modularized) than the plant-endophytic fungus interaction network. Additionally, tree species richness was positively correlated with the network complexity and diversity of epiphytic (α-, ß- and γ-diversity) and endophytic (ß- and γ-diversity) fungi, but was not associated with the contribution of the stochastic and deterministic processes on the community assembly of epiphytic and endophytic fungi. This study highlights that tree species diversity enhances the diversity and network complexity, rather than alters the ecological processes in community assembly of leaf-associated fungi.

SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI.

Diffusion models have emerged as a leading methodology for image generation and have proven successful in the realm of magnetic resonance imaging (MRI) reconstruction. However, existing reconstruction methods based on diffusion models are primarily formulated in the image domain, making the reconstruction quality susceptible to inaccuracies in coil sensitivity maps (CSMs). k-space interpolation methods can effectively address this issue but conventional diffusion models are not readily applicable in k-space interpolation. To overcome this challenge, we introduce a novel approach called SPIRiT-Diffusion, which is a diffusion model for k-space interpolation inspired by the iterative self-consistent SPIRiT method. Specifically, we utilize the iterative solver of the self-consistent term (i.e., k-space physical prior) in SPIRiT to formulate a novel stochastic differential equation (SDE) governing the diffusion process. Subsequently, k-space data can be interpolated by executing the diffusion process. This innovative approach highlights the optimization model's role in designing the SDE in diffusion models, enabling the diffusion process to align closely with the physics inherent in the optimization model-a concept referred to as model-driven diffusion. We evaluated the proposed SPIRiT-Diffusion method using a 3D joint intracranial and carotid vessel wall imaging dataset. The results convincingly demonstrate its superiority over image-domain reconstruction methods, achieving high reconstruction quality even at a substantial acceleration rate of 10. Our code are available at https://github.com/zhyjSIAT/SPIRiT-Diffusion.

A dynamic approach for MR T2-weighted pelvic imaging.

OBJECTIVE: T2-weighted 2D fast spin echo sequence serves as the standard sequence in clinical pelvic MR imaging protocols. However, motion artifacts and blurring caused by peristalsis present significant challenges. Patient preparation such as administering antiperistaltic agents is often required before examination to reduce artifacts, which discomfort the patients. This work introduce a novel dynamic approach for T2 weighted pelvic imaging to address peristalsis-induced motion issue without any patient preparation. Approach: A rapid dynamic data acquisition strategy with complementary sampling trajectory is designed to enable highly undersampled motion-resistant data sampling, and an unrolling method based on deep equilibrium model is leveraged to reconstruct images from the dynamic sampled k-space data. Moreover, the fix-point convergence of the equilibrium model ensures the stability of the reconstruction. The high acceleration factor in each temporal phase, which is much higher than that in traditional static imaging, has the potential to effectively freeze pelvic motion, thereby transforming the imaging problem from conventional motion prevention or removal to motion reconstruction. Main results: Experiments on both retrospective and prospective data have demonstrated the superior performance of the proposed dynamic approach in reducing motion artifacts and accurately depicting structural details compared to standard static imaging. Significance: The proposed dynamic approach effectively captures motion states through dynamic data acquisition and deep learning-based reconstruction, addressing motion-related challenges in pelvic imaging.

White rot fungi as a multifaceted biocontrol agent: Metabolic disruption and algal inhibition in Microcystis aeruginosa.

Microcystis aeruginosa is a prevalent cyanobacterium linked to water eutrophication and harmful algal blooms. While bacterial control strategies are well-studied, the effects of white rot fungi on Microcystis aeruginosa are less understood. This study examines the impact of whole fungal liquid, its centrifuged supernatant, and sterilized solutions on the algae's physiological and biochemical traits. Metabolomics and multivariate analysis identified significant changes in 47 metabolic markers, including carbohydrates, amino acids, and fatty acids, across treatments. The complete fungal liquid exhibited the strongest algicidal effect, likely due to synergistic solubilization mechanisms mediated by extracellular enzymes such as manganese peroxidase, catalase, and laccase. Notably, algicidal activity persisted even after sterilization, suggesting the presence of non-proteinaceous compounds like polysaccharides or lipids. The metabolic disturbances included downregulation of the TCA cycle and reduced fatty acid synthesis, leading to inhibited photosynthesis and compromised nucleic acid integrity in the algal cells. This research enhances our understanding of how white rot fungi disrupt Microcystis aeruginosa metabolism, providing a theoretical basis for their potential use in bioremediation of eutrophic aquatic environments.

A neolignan enantiomer from Piper hancei with anti-neuroinflammatory effect by attenuating NF-κB signaling pathway.

BACKGROUND: In the traditional "Yao" ethno-medicine system, Piper hancei Maxim. is used to treat rheumatism, wind-cold, and inflammation. Previous studies indicate that lignans obtained from P. hancei stems have anti-neuroinflammatory potential in LPS-stimulated microglial cells. However, identification of the lignan enantiomers and the precise mechanism by which they work to reduce inflammation is yet to be explored. PURPOSE: To identify the active anti-neuroinflammatory lignan enantiomers isolated from P. hancei stems and to elucidate the mechanism of action both in vitro and in vivo. METHODS: The lignan enantiomers from P. hancei stems were isolated and elucidated using various chromatographic and spectroscopic methods. The anti-neuroinflammatory potential of all the compounds was initially screened by measuring nitric oxide (NO) inhibition in LPS-stimulated BV-2 microglial cells. Then anti-neuroinflammatory efficacy of the most active compound was assessed with LPS-stimulated microglial cell model, microglia-induced neuronal injury SH-SY5Y cell model, and LPS-intracerebroventricular injection neuroinflammation mouse model. The underlying mechanism was further explored by qRT-PCR analysis, Western blot analysis, and immunofluorescence staining experiments to understand the intervention pathway. RESULTS: Phytochemical analysis of P. hancei stems resulted in the isolation of 13 pairs of neolignan enantiomers (1-13), including 4 new pairs named piperhancin D-G (1-4). All right-handed (+) and left-handed (-) enantiomers of each pair (1-13) were isolated successfully. Notably, (+)-futoquinol (5) demonstrated significant anti-neuroinflammatory activity without cytotoxicity, unlike its inactive enantiomer (-)-5 in LPS-stimulated microglial cells. The representative compound (+)-5 effectively suppressed pro-inflammatory cytokines in LPS stimulated BV-2 cells and mouse brains, and alleviated microglia-induced neuronal damage in SH-SY5Y cells. Behavioral tests showed that (+)-5 alleviated the LPS-induced cognitive dysfunction in mice. Furthermore, the compound was able to reduce LPS-induced neuronal damage and microglial activation in mouse brains. A mechanistic study demonstrated that (+)-5 hindered the nuclear translocation of NF-κB p65 and downregulated the pro-inflammatory mediators to relieve neuroinflammation. CONCLUSION: This is the first example of both in vitro and in vivo study on the anti-neuroinflammatory effects and underlying mechanism of the neolignan enantiomers isolated from P. hancei. Notably, (+)-futoquinol (5) emerged as a potential lead for further drug development to treat neurodegenerative diseases.

Multisite Skin Biopsies vs Cerebrospinal Fluid for Prion Seeding Activity in the Diagnosis of Prion Diseases.

Importance: Recent studies have revealed that autopsy skin samples from cadavers with prion diseases (PRDs) exhibited a positive prion seeding activity similar to cerebrospinal fluid (CSF). It is worthwhile to validate the findings with a large number of biopsy skin samples and compare the clinical value of prion seeding activity between skin biopsies and concurrent CSF specimens. Objective: To compare the prion seeding activity of skin biopsies and CSF samples and to determine the effectiveness of combination of the skin biopsies from multiple sites and numerous dilutions on the diagnosis for various types of PRDs. Design, Setting, and Participants: In the exploratory cohort, patients were enrolled from September 15, 2021, to December 15, 2023, and were followed up every 3 months until April 2024. The confirmatory cohort enrolled patients from December 16, 2023, to June 31, 2024. The exploratory cohort was conducted at a single center, the neurology department at Xuanwu Hospital. The confirmatory cohort was a multicenter study involving 4 hospitals in China. Participants included those diagnosed with probable sporadic Creutzfeldt-Jakob disease or genetically confirmed PRDs. Patients with uncertain diagnoses or those lost to follow-up were excluded. All patients with PRDs underwent skin sampling at 3 sites (the near-ear area, upper arm, lower back, and inner thigh), and a portion of them had CSF samples taken simultaneously. In the confirmatory cohort, a single skin biopsy site and CSF samples were simultaneously collected from a portion of patients with PRDs. Exposures: The skin and CSF prion seeding activity was assessed using the real-time quaking-induced conversion (RT-QUIC) assay, with rHaPrP90-231, a Syrian hamster recombinant prion protein, as the substrate. In the exploratory cohort, skin samples were tested at dilutions of 10-2 through 10-4. In the confirmatory cohort, skin samples were tested at a dilution of 10-2. A total of four 15-µL wells of CSF were used in the RT-QUIC assay. Main Outcomes and Measures: Correlations between RT-QUIC results from the skin and CSF and the final diagnosis of enrolled patients. Results: In the exploratory cohort, the study included 101 patients (mean [SD] age, 60.9 [10.2] years; 63 female [62.4%]) with PRD and 23 patients (mean [SD] age, 63.4 [9.1] years; 13 female [56.5%]) without PRD. A total of 94 patients had CSF samples taken simultaneously with the skin biopsy samples. In the confirmatory cohort, a single skin biopsy site and CSF sample were taken simultaneously in 43 patients with PRDs. Using an experimental condition of 10-2 dilution, the RT-QUIC positive rates of skin samples from different sites were comparable with those of the CSF (skin: 18 of 26 [69.2%] to 74 of 93 [79.6%] vs CSF: 71 of 94 [75.5%]). When tested at 3 different dilutions, all skin sample positivity rates increased to over 80.0% (79 of 93 for the near-ear area, 21 of 26 for the upper arm, 77 of 92 for the lower back, and 78 of 92 for the inner thigh). Combining samples from skin sites near the ear, inner thigh, and lower back in pairs yielded positivity rates exceeding 92.1% (93 of 101), significantly higher than CSF alone (71 of 94 [75.5%]; P =.002). When all skin sample sites were combined and tested at 3 dilution concentrations for RT-QUIC, the sensitivity reached 95.0% (96 of 101). In the confirmatory cohort, the RT-QUIC positive rate of a single skin biopsy sample was slightly higher than that of the CSF (34 of 43 [79.1%] vs 31 of 43 [72.1%]; P = .45). Conclusions and Relevance: Results of this diagnostic study suggest that the sensitivity of an RT-QUIC analysis of a combination of 2 or more skin sites was superior to that of CSF in diagnosing PRDs.

MG-Net: A fetal brain tissue segmentation method based on multiscale feature fusion and graph convolution attention mechanisms.

BACKGROUND AND OBJECTIVE: Fetal brain tissue segmentation provides foundational support for comprehensively understanding the neurodevelopment of normal and congenital disease-affected fetuses. Manual labeling is very time-consuming, and automated segmentation methods can greatly improve the efficiency of doctors. At the same time, fetal brain tissue undergoes various changes throughout the pregnancy, leading to a continuous change in tissue contrast, which greatly increases the difficulty of training segmentation methods. This study aims to develop an automated segmentation model that can efficiently and accurately segment fetal brain tissue, improving the workflow for medical professionals. METHODS: We propose a novel deep learning-based segmentation model that incorporates three innovative components: Firstly, a new Dual Dilated Attention Block (DDAB) is proposed in the encoder part to enhance the feature extraction of local spatial and structural contextual information. Secondly, a Multi-scale Deformable Transformer (MSDT) is integrated into the bottleneck to improve the feature extraction of global information on local spatial and structural contextual information. Thirdly, we use a novel block based on Graph Convolution Attention (GCAB) in the decoder, which effectively enhances the features at the decoder.The code is available at https://github.com/unicoco7/MG-Net/. RESULTS: We trained and tested on the FeTA 2021 and FeTA 2022 datasets, and evaluated using seven popular metrics, including Dice, IoU, MAE, BoundaryF, PRE, SEN, and SPE. Compared to the current state-of-the-art 3D segmentation models such as nnFormer, SwinUNETR, and 3DUX-net, our proposed method has surpassed all of them in metrics like Dice, IoU, and MAE. Specifically, on the FeTA 2021 dataset, our model achieved a Dice of 0.8666, an IoU of 0.7646, and an MAE of 0.0027; on the FeTA 2022 dataset, it achieved a Dice of 0.8552, an IoU of 0.7470, and an MAE of 0.0005. CONCLUSION: In this paper, we propose a model for three-dimensional fetal brain tissue segmentation based on multi-scale feature fusion and graph convolution attention mechanism, and conduct experimental evaluation on the FeTA 2021 and FeTA 2022 datasets. Understanding the boundaries of fetal brain tissue is crucial for doctors' diagnosis, so the proposed model is expected to improve the speed and accuracy of doctors' diagnoses.

Study on the impact of bowtie filter on photon-counting CT imaging.

Objective.The aim of this study was to investigate the impact of the bowtie filter on the image quality of the photon-counting detector (PCD) based CT imaging.Approach.Numerical simulations were conducted to investigate the impact of bowtie filters on image uniformity using two water phantoms, with tube potentials ranging from 60 to 140 kVp with a step of 5 kVp. Subsequently, benchtop PCD-CT imaging experiments were performed to verify the observations from the numerical simulations. Additionally, various correction methods were validated through these experiments.Main results.It was found that the use of a bowtie filter significantly alters the uniformity of PCD-CT images, depending on the size of the object and the x-ray spectrum. Two notable effects were observed: the capping effect and the flattening effect. Furthermore, it was demonstrated that the conventional beam hardening correction method could effectively mitigate such non-uniformity in PCD-CT images, provided that dedicated calibration parameters were used.Significance.It was demonstrated that the incorporation of a bowtie filter results in varied image artifacts in PCD-CT imaging under different conditions. Certain image correction methods can effectively mitigate and reduce these artifacts, thereby enhancing the overall quality of PCD-CT images.

Acquired factor XIII deficiency presenting with multiple intracranial hemorrhages and right hip hematoma: A case report.

BACKGROUND: Factor XIII (FXIII) deficiency is a rare yet profound coagulopathy. FXIII plays a pivotal role in hemostasis, and deficiencies in this factor can precipitate unchecked or spontaneous hemorrhaging. Immunological assays for detecting FXIII inhibitors are indispensable for diagnosing acquired FXIII deficiency; however, the availability of suitable testing facilities is limited, resulting in prolonged turnaround times for these assays. CASE SUMMARY: In this case study, a 53-year-old male devoid of significant medical history presented with recurrent intracranial hemorrhages and a hematoma in the right hip. Subsequent genetic analysis revealed a homozygous mutation in the ACE gene, confirming the diagnosis of acquired FXIII deficiency. CONCLUSION: This case underscores the significance of considering acquired deficiencies in clotting factors when evaluating patients with unexplained bleeding episodes.

Combining the probabilistic finite element model and artificial neural network to study nutrient levels in the human intervertebral discs.

BACKGROUND: Diffusion distance and diffusivity are known to affect nutrient transport rates, but the probabilistic analysis of these two factors remains vacant. There is a lack of effective tools to evaluate disc nutrient levels. METHODS: Five-hundred-disc samples with different combinations of morphological and water content parameters were generated, which were used to evaluate nutrient levels in unloaded and loaded states. Spearman correlation coefficients between inputs and responses were calculated. Artificial neural networks were trained to predict nutrient concentrations based on the dataset generated by the probabilistic finite element model. FINDINGS: In unloaded and loaded states, the minimum oxygen concentration of nucleus pulposus was negatively correlated with disc height (r = -0.83, p < 0.01 and r = -0.76, p < 0.01, respectively), and the minimum glucose concentration of annulus fibrosus was positively correlated with its water content (r = 0.68, p < 0.01 and r = 0.73, p < 0.01, respectively). The maximum lactate concentration of cartilage endplate was affected by endplate thickness (r = 0.94, p < 0.01 and r = 0.95, p < 0.01, respectively). For trained neural networks, nutrient concentrations could be well predicted, with coefficients of determination greater than 0.95 and mean absolute percentage errors less than 5 %. INTERPRETATION: This study underscores the importance of disc height, annulus fibrosus water content, and endplate thickness in regulating nutrient levels, and precise control of these parameters should be prioritized in the design of tissue-engineered discs. Moreover, artificial neural networks might be a promising tool for evaluating nutrient levels.

Total-Body PET/CT: A Role of Artificial Intelligence?

The purpose of this paper is to provide an overview of the cutting-edge applications of artificial intelligence (AI) technology in total-body positron emission tomography/computed tomography (PET/CT) scanning technology and its profound impact on the field of medical imaging. The introduction of total-body PET/CT scanners marked a major breakthrough in medical imaging, as their superior sensitivity and ultralong axial fields of view allowed for high-quality PET images of the entire body to be obtained in a single scan, greatly enhancing the efficiency and accuracy of diagnoses. However, this advancement is accompanied by the challenges of increasing data volumes and data complexity levels, which pose severe challenges for traditional image processing and analysis methods. Given the excellent ability of AI technology to process massive and high-dimensional data, the combination of AI technology and ultrasensitive PET/CT can be considered a complementary match, opening a new path for rapidly improving the efficiency of the PET-based medical diagnosis process. Recently, AI technology has demonstrated extraordinary potential in several key areas related to total-body PET/CT, including radiation dose reductions, dynamic parametric imaging refinements, quantitative analysis accuracy improvements, and significant image quality enhancements. The accelerated adoption of AI in clinical practice is of particular interest and is directly driven by the rapid progress made by AI technologies in terms of interpretability; i.e., the decision-making processes of algorithms and models have become more transparent and understandable. In the future, we believe that AI technology will fundamentally reshape the use of PET/CT, not only playing a more critical role in clinical diagnoses but also facilitating the customization and implementation of personalized healthcare solutions, providing patients with safer, more accurate, and more efficient healthcare experiences.

Isolation and purification of lactic acid bacteria and yeasts based on a multi-channel magnetic flow device and rapid qualitative and quantitative detection.

Rapid isolation and identification of lactic acid bacteria and yeasts during fermentation is of great significance for quality control and regulation of fermented foods. In this study, we prepared a multi-channel magnetic flow device for rapid separation and purification of lactic acid bacteria and yeast, and based on SERS spectrum, we made rapid qualitative and quantitative analysis of Lactobacillus plantarum, Lactococcus lactis and Saccharomyces cerevisiae. The results showed that the synthesized Synthesized Fe3O4-Van antibiotic magnetic beads are paramagnetic; Fe3O4-Van antibiotic magnetic beads achieved capture efficiencies of more than 98.5 % for both L. plantarum and L. lactis at 102-104 CFU/mL, respectively. Separation and purification efficiency of single S. cerevisiae, L. plantarum and L. lactis by multi-channel magnetic flow device all reached more than 98 % with good isolation and purification results. The SERS spectra of the three microorganisms were classified and analyzed using linear discriminant analysis (LDA), and the accuracy of the established LDA model was 100 %, which completely differentiated the SERS spectra of the three microorganisms,and realized the qualitative identification of L. plantarum, L. lactis, and S. cerevisiae, and finally, quantitative model was established with the logarithmic values (lg C) of different concentrations of L. plantarum, L. lactis, and S. cerevisiae as the horizontal coordinates, and the Raman intensities at their strongest characteristic peaks of 512 cm-1, 1669 cm-1, and 1125 cm-1, respectively, were used as vertical coordinates to establish a quantitative model, with the lowest detection limit of 10 CFU/mL, and the digital quantification of lactic acid bacteria and yeast were achieved. It provided an effective means for real-time monitoring and tracking of the dynamics of lactic acid bacteria and yeast in the fermentation process and the quality control of fermented foods.

Activated carbon fiber loaded nano zero-valent iron for Microcystis aeruginosa removal: Performance and mechanisms.

Cyanobacterial blooms caused by Microcystis aeruginosa threaten environmental safety and daily life. In this study, an activated carbon fiber-supported nano zero-valent iron composite (ACF-nZVI) was developed to remove Microcystis aeruginosa. The results showed that nZVI was evenly distributed on the activated carbon fibers, preventing aggregation and oxidation. ACF-nZVI achieved a removal efficiency of more than 90 % within a pH range of 3-7. During the reaction, H2O2, which was generated by Fe0, was activated to form ·OH and ·O-2, which dismantled antioxidant enzymes and induced lipid peroxidation. Additionally, ACF-nZVI destroyed the cell wall and membrane, resulting in protein and humus leakage and causing 92.34 % cell damage and death. In this study, an environmentally friendly and stable nanomaterial was developed, offering a novel approach for the safe, cost-effective, and efficient removal of cyanobacteria.

Bortezomib, lenalidomide, and dexamethasone versus bortezomib, doxorubicin, and dexamethasone in newly diagnosed multiple myeloma.

Bortezomib, lenalidomide, and dexamethasone (VRD), and bortezomib, doxorubicin, and dexamethasone (PAD), are commonly used in induction regimens for patients with newly diagnosed multiple myeloma (NDMM) in China. This real-world study enrolled 390 patients, 195 receiving VRD and 195 receiving PAD induction. The primary endpoint was progression-free survival (PFS) and stringent complete remission/complete remission. Across the entire cohort, VRD demonstrated significantly improved five-year overall survival (OS) (74% vs. 59%, p = 0.0024) and five-year PFS (67% vs. 37%, p = 0.0018) compared to PAD. Notably, the median OS and PFS were not reached for VRD-treated patients, while they were 77 months (60-not reached [NR]) and 46 months (36-NR), respectively, for PAD. In patients with standard-risk cytogenetics, VRD showed superior five-year OS (83% vs. 58%, p = 0.0038) and PFS (78% vs. 48%, p = 0.0091) compared to PAD. However, these differences were not statistically significant in high-risk patients. For transplanted patients, VRD was associated with superior five-year OS (91% vs. 67%, p = 0.014) and PFS (79% vs. 47%, p = 0.015) compared to PAD. In non-transplanted patients, VRD showed a trend towards improved five-year OS (p = 0.085) and PFS (p = 0.073) compared to the PAD group. In conclusion, VRD displayed superior OS and PFS outcomes in standard-risk patients and those who underwent transplantation. These findings suggest potential advantages of VRD over PAD in real-world clinical settings for NDMM treatment. However, due to the imbalance in transplantation rates between the VRD and PAD groups, limitations in testing for high-risk cytogenetic abnormalities (HRA), and the difference between the received cycles and salvage therapies, the conclusions of this study should be interpreted with caution.

Transcriptome analysis reveals the promoting effects of exogenous melatonin on the selenium uptake in grape under selenium stress.

Introduction: Exogenous melatonin (MT) can promote horticultural crops growth under stress conditions. Methods: In this study, the effects of exogenous MT on the accumulation of selenium (Se) in grape were studied under Se stress. Results and discussion: Under Se stress, exogenous MT increased the biomass, content of photosynthetic pigments and antioxidant enzyme activity of grapevines. Compared with Se treatment, MT increased the root biomass, shoot biomass, chlorophyll a content, chlorophyll b content, carotenoids, superoxide dismutase activity, and peroxidase activity by 18.11%, 7.71%, 25.70%, 25.00%, 25.93%, 5.73%, and 9.41%, respectively. Additionally, MT increased the contents of gibberellin, auxin, and MT in grapevines under Se stress, while it decreased the content of abscisic acid. MT increased the contents of total Se, organic Se and inorganic Se in grapevines. Compared with Se treatment, MT increased the contents of total Se in the roots and shoots by 48.82% and 135.66%, respectively. A transcriptome sequencing analysis revealed that MT primarily regulated the cellular, metabolic, and bioregulatory processes of grapevine under Se stress, and the differentially expressed genes (DEGs) were primarily enriched in pathways, such as aminoacyl-tRNA biosynthesis, spliceosome, and flavonoid biosynthesis. These involved nine DEGs and nine metabolic pathways in total. Moreover, a field experiment showed that MT increased the content of Se in grapes and improved their quality. Therefore, MT can alleviate the stress of Se in grapevines and promote their growth and the accumulation of Se.