Label-Free Fiber-Optic Raman Spectroscopy for Intravascular Coronary Atherosclerosis and Plaque Detection.

The rupture of atherosclerotic plaques remains one of the leading causes of morbidity and mortality worldwide. The plaques have certain pathological characteristics including a fibrous cap, inflammation, and extensive lipid deposition in a lipid core. Various invasive and noninvasive imaging techniques can interrogate structural aspects of atheroma; however, the composition of the lipid core in coronary atherosclerosis and plaques cannot be accurately detected. Fiber-optic Raman spectroscopy has the capability of in vivo rapid and accurate biomarker detection as an emerging omics technology. Previous studies demonstrated that an intravascular Raman spectroscopic technique may assess and manage the therapeutic and medication strategies intraoperatively. The Raman spectral information identified plaque depositions consisting of lipids, triglycerides, and cholesterol esters as the major components by comparing normal region and early plaque formation region with histology. By focusing on the composition of plaques, we could identify the subgroups of plaques accurately and rapidly by Raman spectroscopy. Collectively, this fiber-optic Raman spectroscopy opens up new opportunities for coronary atherosclerosis and plaque detection, which would assist optimal surgical strategy and instant postoperative decision-making. In this paper, we will review the advancement of label-free fiber-optic Raman probe spectroscopy and its applications of coronary atherosclerosis and atherosclerotic plaque detection.

Black phosphorus quantum dot-modified ADSCs as a novel therapeutic for periodontitis bone loss coupling of osteogenesis and osteoimmunomodulation.

Alveolar bone defect repair remains a persistent clinical challenge for periodontitis treatment. The use of peripheral functional seed cells is a hot topic in periodontitis. Herein, we explored the cellular behaviors and osteogenic ability of adipose-derived mesenchymal stem cells (ADSCs) treated with black phosphorus quantum dots (BPQDs). Additionally, macrophage polarization, osteogenic effects and angiogenesis were investigated through the paracrine pathway regulated by BPQD-modified ADSCs. Our results demonstrated that BPQDs showed good biocompatibility with ADSCs and BPQD-modified ADSCs could improve the bone repair in vivo inflammatory microenvironment by regulating osteogenesis and osteoimmunomodulation. The BPQDs increased the osteogenic differentiation of ADSCs via the Wnt/ß-catenin and BMP2/SMAD5/Runx2 signaling pathway. In addition, BPQD-modified ADSCs promoted the osteogenic effect of BMSCs and facilitated the polarization of macrophages from M1 towards M2 phenotype transformation through the paracrine pathway in the periodontitis microenvironment. This strategy provides a novel idea for treatment of alveolar bone defects for periodontitis in the foreseeable future.

Ecological consequences of biochar and hydrochar amendments in soil: assessing environmental impacts and influences.

Anthropogenic activities have caused irreversible consequences on our planet, including climate change and environmental pollution. Nevertheless, reducing greenhouse gas (GHG) emissions and capturing carbon can mitigate global warming. Biochar and hydrochar are increasingly used for soil remediation due to their stable adsorption qualities. As soil amendments, these materials improve soil quality and reduce water loss, prevent cracking and shrinkage, and interact with microbial communities, resulting in a promising treatment method for reducing gas emissions from the top layer of soil. However, during long-term studies, contradictory results were found, suggesting that higher biochar application rates led to higher soil CO2 effluxes, biodiversity loss, an increase in invasive species, and changes in nutrient cycling. Hydrochar, generated through hydrothermal carbonization, might be less stable when introduced into the soil, which could lead to heightened GHG emissions due to quicker carbon breakdown and increased microbial activity. On the other hand, biochar, created via pyrolysis, demonstrates stability and can beneficially impact GHG emissions. Biochar could be the preferred red option for carbon sequestration purposes, while hydrochar might be more advantageous for use as a gas adsorbent. This review paper highlights the ecological impact of long-term applications of biochar and hydrochar in soil. In general, using these materials as soil amendments helps establish a sustainable pool of organic carbon, decreasing atmospheric GHG concentration and mitigating the impacts of climate change.

Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy.

Molecular genetics is highly related with prognosis of high-grade glioma. Accordingly, the latest WHO guideline recommends that molecular subgroups of the genes, including IDH, 1p/19q, MGMT, TERT, EGFR, Chromosome 7/10, CDKN2A/B, need to be detected to better classify glioma and guide surgery and treatment. Unfortunately, there is no preoperative or intraoperative technology available for accurate and comprehensive molecular subgrouping of glioma. Here, we develop a deep learning-assisted fiber-optic Raman diagnostic platform for accurate and rapid molecular subgrouping of high-grade glioma. Specifically, a total of 2,354 fingerprint Raman spectra was obtained from 743 tissue sites (astrocytoma: 151; oligodendroglioma: 150; glioblastoma (GBM): 442) of 44 high-grade glioma patients. The convolutional neural networks (ResNet) model was then established and optimized for molecular subgrouping. The mean area under receiver operating characteristic curves (AUC) for identifying the molecular subgroups of high-grade glioma reached 0.904, with mean sensitivity of 83.3%, mean specificity of 85.0%, mean accuracy of 83.3%, and mean time expense of 10.6 s. The diagnosis performance using ResNet model was shown to be superior to PCA-SVM and UMAP models, suggesting that high dimensional information from Raman spectra would be helpful. In addition, for the molecular subgroups of GBM, the mean AUC reached 0.932, with mean sensitivity of 87.8%, mean specificity of 83.6%, and mean accuracy of 84.1%. Furthermore, according to saliency maps, the specific Raman features corresponding to tumor-associated biomolecules (e.g. nucleic acid, tyrosine, tryptophan, cholesteryl ester, fatty acid, and collagen) were found to contribute to the accurate molecular subgrouping. Collectively, this study opens up new opportunities for accurate and rapid molecular subgrouping of high-grade glioma, which would assist optimal surgical resection and instant post-operative decision-making.

Enhanced effect of limb remote ischemic postconditioning combined with paeoniflorin on alleviating cerebral ischemic injury via neutrophil NADPH pathway.

BACKGROUND: Limb remote ischemic postconditioning (LRIP) and paeoniflorin (PF) both can ameliorate cerebral ischemia reperfusion (I/R) injury. At present, whether LRIP combined with PF can achieve better therapeutic effect is unknown. PURPOSE: This study explored the alleviating effect and mechanism of LRIP in combination with PF on cerebral I/R injury in rats. METHODS: Middle cerebral artery occlusion (MCAO) surgery was performed on rats except Sham group. Then PF (2.5 mg/kg, 5 mg/kg, 10 mg/kg) was administrated by intraperitoneal injection 10 min before the start of reperfusion. LRIP was operated on the left femoral artery at 0 h of reperfusion. Behavioral testing was used to assess neurological impairment, while TTC staining was used to examine infarct volume. Protein expression of MyD88, TRAF6, p38-MAPK and phosphorylation of p47phox in neutrophils from rat peripheral blood were tested by Western blot. Rat bone marrow neutrophils were extracted and incubated for 24 h with serum from rats after LRIP combined with PF. p38 MAPK inhibitor group was administrated SB203580 while the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase inhibitor group was administrated Apocynin. Neutrophils were stimulated by fMLP (10 µM). Reactive oxygen species (ROS) production and protein expression of MyD88, TRAF6, p38 MAPK, and p47phox (ser 304 and ser 345) were detected. RESULTS: LRIP combined with PF (5 mg/kg) reduced cerebral infarct volume, ameliorated neurological deficit score (NDS), decreased fMLP-stimulated ROS release and downregulated the protein expression of MyD88, TRAF6, p38-MAPK and phosphorylation of p47phox (ser 304 and ser 345) in neutrophils. CONCLUSION: The protective effect of LRIP combined with PF on cerebral I/R injury was better than either alone. Taken together, we provided solid evidence to demonstrate that the combination of LRIP and PF had potential to alleviate cerebral I/R injury, which was regulated by MyD88-TRAF6-p38 MAPK pathway and neutrophil NADPH oxidase pathway.

Optimization of sulfate reduction and methanogenesis via phase separation in a two-phase internal circulation reactor for the treatment of high-sulfate organic wastewater.

To enhance the performance of the internal circulation (IC) reactor when treating high-sulfate organic wastewater, a laboratory-scale two-phase IC reactor with distinct phase separation capabilities was designed, and the sulfate reduction and methanogenesis processes were optimized by segregating the reactor into two specialized reaction zones. The results demonstrated that the first and second reaction areas of the two-phase IC reactor could be maintained at 4.5-6.0 and 7.5-8.5, respectively, turning them into the specialized phase for sulfate reduction and methanogenesis. Through phase separation, the two-phase IC reactor achieved a COD degradation and sulfate reduction efficiency of more than 80% when the influent sulfate concentration exceeded 5,000 mg/L, which were 32.32% and 16.04% higher than that before phase separation. Functional analyses indicated a greater activity of both the dissimilatory and assimilatory sulfate reduction pathways in the acidogenic phase, largely due to a rise in the relative abundance of the genera Desulfovibrio, Bacteroides, and Lacticaseibacillus, the primary carriers of sulfate reduction functional genes. In contrast, all the acetoclastic, hydrogenotrophic, and methylotrophic methanogenesis pathways were inhibited in the acidogenic phase but thrived in the methanogenic phase, coinciding with shifts in the genus Methanothrix, which harbors the mcrA, mcrB, and mcrG genes essential for the final transformation step of all three methanogenesis pathways.

A Dynamic Window Method Based on Reinforcement Learning for SSVEP Recognition.

Steady-state visual evoked potential (SSVEP) is one of the most used brain-computer interface (BCI) paradigms. Conventional methods analyze SSVEPs at a fixed window length. Compared with these methods, dynamic window methods can achieve a higher information transfer rate (ITR) by selecting an appropriate window length. These methods dynamically evaluate the credibility of the result by linear discriminant analysis (LDA) or Bayesian estimation and extend the window length until credible results are obtained. However, the hypotheses introduced by LDA and Bayesian estimation may not align with the collected real-world SSVEPs, which leads to an inappropriate window length. To address the issue, we propose a novel dynamic window method based on reinforcement learning (RL). The proposed method optimizes the decision of whether to extend the window length based on the impact of decisions on the ITR, without additional hypotheses. The decision model can automatically learn a strategy that maximizes the ITR through trial and error. In addition, compared with traditional methods that manually extract features, the proposed method uses neural networks to automatically extract features for the dynamic selection of window length. Therefore, the proposed method can more accurately decide whether to extend the window length and select an appropriate window length. To verify the performance, we compared the novel method with other dynamic window methods on two public SSVEP datasets. The experimental results demonstrate that the novel method achieves the highest performance by using RL.

Comparing the Early Changes in Classified Higher-Order Aberrations Before and After Non-Toric and Toric Implantable Collamer Lens V4c Implantation.

PURPOSE: This study aimed to compare early changes in classified higher-order aberrations (HOAs) pre- and postsurgery in patients who received nontoric versus toric implantable collamer lenses (ICL; ICL Model V4c; STAAR Surgical, Monrovia, CA, USA). METHODS: This prospective study included 124 eyes of 64 patients: 49 eyes were treated using a nontoric implantable collamer lens (ICL), and 75 eyes were treated using a toric implantable collamer lenses (TICL). Refractive parameters and ocular aberrations were examined before and 1 month after surgery. RESULTS: At one month, the safety indices were 1.24 ± 0.17 in the ICL group and 1.20 ± 0.25 in the TICL group (p = 0.39). The efficacy indices were 1.07 ± 0.17 in the ICL group and 1.15 ± 0.26 in the TICL group (p = 0.02). The root mean square (RMS) values of whole-eye total HOAs, trefoil, corneal total HOAs, spherical aberration, and intraocular spherical aberration significantly increased postoperatively in both groups. The RMS of intraocular total HOAs in the TICL group significantly increased 1 month postoperatively. No statistically significant differences were observed in HOA changes between the ICL and TICL groups. CONCLUSIONS: The dominant increases in short-term aberrations after ICL and TICL V4c implantation were in corneal trefoil and intraocular spherical aberrations, which were related to the corneal incision and implanted lens. The HOA changes post-surgery were not statistically different between the two lens types.

Expression of SDF-1/CXCR4 and related inflammatory factors in sodium fluoride-treated hepatocytes.

At present, the mechanism of fluorosis-induced damage to the hepatic system is unclear. Studies have shown that excess fluoride causes some degree of damage to the liver, including inflammation. The SDF-1/CXCR4 signaling axis has been reported to have an impact on the regulation of inflammation in human cells. In this study, we investigated the role of the SDF-1/CXCR4 signaling axis and related inflammatory factors in fluorosis through in vitro experiments on human hepatic astrocytes (LX-2) cultured with sodium fluoride. CCK-8 assays showed that the median lethal dose at 24 h was 2 mmol/l NaF, and these conditions were used for subsequent enzyme-linked immunosorbent assays (ELISAs) and quantitative real-time polymerase chain reaction (qPCR) analysis. The protein expression levels of SDF-1/CXCR4 and the related inflammatory factors nuclear factor-κB (NF-κB), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) and interleukin 1ß (IL-1ß) were detected by ELISAs from the experimental and control groups. The mRNA expression levels of these inflammatory indicators were also determined by qPCR in both groups. Moreover, the expression levels of these factors were significantly higher in the experimental group than in the control group at both the protein and mRNA levels (P < 0.05). Excess fluorine may stimulate the SDF-1/CXCR4 signaling axis, activating the inflammatory NF-κB signaling pathway and increasing the expression levels of the related inflammatory factors IL-6, TNF-α and IL-1ß. Identification of this mechanism is important for elucidating the pathogenesis of fluorosis-induced liver injury.

fMRI-based spatio-temporal parcellations of the human brain.

PURPOSE OF REVIEW: Human brain parcellation based on functional magnetic resonance imaging (fMRI) plays an essential role in neuroscience research. By segmenting vast and intricate fMRI data into functionally similar units, researchers can better decipher the brain's structure in both healthy and diseased states. This article reviews current methodologies and ideas in this field, while also outlining the obstacles and directions for future research. RECENT FINDINGS: Traditional brain parcellation techniques, which often rely on cytoarchitectonic criteria, overlook the functional and temporal information accessible through fMRI. The adoption of machine learning techniques, notably deep learning, offers the potential to harness both spatial and temporal information for more nuanced brain segmentation. However, the search for a one-size-fits-all solution to brain segmentation is impractical, with the choice between group-level or individual-level models and the intended downstream analysis influencing the optimal parcellation strategy. Additionally, evaluating these models is complicated by our incomplete understanding of brain function and the absence of a definitive "ground truth". SUMMARY: While recent methodological advancements have significantly enhanced our grasp of the brain's spatial and temporal dynamics, challenges persist in advancing fMRI-based spatio-temporal representations. Future efforts will likely focus on refining model evaluation and selection as well as developing methods that offer clear interpretability for clinical usage, thereby facilitating further breakthroughs in our comprehension of the brain.

Rapid and Precise Diagnosis of Retroperitoneal Liposarcoma with Deep-Learned Label-Free Molecular Microscopy.

The retroperitoneal liposarcoma (RLPS) is a rare malignancy whose only curative therapy is surgical resection. However, well-differentiated liposarcomas (WDLPSs), one of its most common types, can hardly be distinguished from normal fat during operation without an effective margin assessment method, jeopardizing the prognosis severely with a high recurrence risk. Here, we combined dual label-free nonlinear optical modalities, stimulated Raman scattering (SRS) microscopy and second harmonic generation (SHG) microscopy, to image two predominant tissue biomolecules, lipids and collagen fibers, in 35 RLPSs and 34 normal fat samples collected from 35 patients. The produced dual-modal tissue images were used for RLPS diagnosis based on deep learning. Dramatically decreasing lipids and increasing collagen fibers during tumor progression were reflected. A ResNeXt101-based model achieved 94.7% overall accuracy and 0.987 mean area under the ROC curve (AUC) in differentiating among normal fat, WDLPSs, and dedifferentiated liposarcomas (DDLPSs). In particular, WDLPSs were detected with 94.1% precision and 84.6% sensitivity superior to existing methods. The ablation experiment showed that such performance was attributed to both SRS and SHG microscopies, which increased the sensitivity of recognizing WDLPS by 16.0 and 3.6%, respectively. Furthermore, we utilized this model on RLPS margins to identify the tumor infiltration. Our method holds great potential for accurate intraoperative liposarcoma detection.

Immediate versus delayed sequential bilateral ICL implantation: A retrospective comparison of vault height and visual outcomes.

PURPOSE: To compare the visual outcomes and risks of suboptimal vault-related complications between immediate sequential bilateral ICL surgery (ISBICLS) and delayed sequential bilateral ICL surgery (DSBICLS). DESIGN: A retrospective cohort study. METHODS: Patients who underwent bilateral ICL implantation between November 2014 and December 2021 at the Eye and ENT Hospital of Fudan University (Shanghai, China) were included and divided into two groups: (1) ISBICLS: both eye surgeries performed on the same day, and (2) DSBICLS: second eye surgery performed < 7 days following the first one. Propensity score matching (PSM) was performed to compare the visual outcomes. Multivariable logistic regression models were used to estimate the odds ratios (ORs) of the suboptimal vaults. RESULTS: Finally, 10,985 eyes were included. After PSM, 204 first surgery eyes and 162 s surgery eyes with complete postoperative data were matched. The safety and efficacy indices did not statistically differ between groups (all > 1.00), except that ISBICLS first surgery eyes achieved better efficacy index than DSBICLS group (1.03 ± 0.26 vs. 1.08 ± 0.23, P = 0.034). Excessive vault was observed in eight (4.06 %) ISBICLS first eyes, one (0.50 %) DSBICLS first eye, and none in the second surgery eye in either group. An insufficient vault was observed in one second eye and one DSBICLS second eye. We found no evidence of differences in the rate of excessive vault (OR = 0.831, 95 % CI: 0.426-1.622, P = 0.588) or insufficient vault (OR = 0.609, 95 % CI:0.062-5.850, P = 0.668). CONCLUSION: ISBICLS provided safety, efficacy, and refraction predictability comparable to DSBICLS without increasing the risk of suboptimal vault-related complications.

Association between electroencephalogram alpha-band oscillations and executive and processing functions in patients with cerebral small vessel diseases.

Electroencephalogram (EEG) alpha-band oscillations may reflect executive and processing function in patients with cerebral small vessel disease (CSVD). We aimed to assess such association and its relationship with CSVD severity, and to identify specific alpha-band parameters and the cut-off values for cognitive screening. We analysed the dispersion of amplitude-frequency characteristics of EEG alpha-band and different alpha-band parameters (PFα , ΔPFα , PPα , NCL) in different brain locations. We also assessed patients' executive and processing functions using verbal fluency test (VFT) and color trails test (CTT), and CSVD severity using total burden and Fazekas scores. 129 patients were recruited in the study. After adjusting for age, gender and education, PFα(F3), PFα(F4) and NCL were significantly associated with VFT-composite performance (p < 0.05). CTT-1 time and error were associated with PFα(F3), PFα(F4), ΔPFα(O1;F3) and CSVD severity (p < 0.05), whereas CTT-2 time was only associated with CSVD severity. Moreover, the correlations between alpha-band oscillations and cognitive function were higher in low than in high disease-severity group (ρ: -0.58 vs. -0.38, p < 0.05). The AUC of selected alpha-band parameters were higher than 0.8 for VFT and CTT. Specific alpha-band parameters in the frontal lobe were identified to correspond to executive and processing function. Assessing EEG alpha-band oscillations may assist in screening cognitive impairment.

A group of emerging heterocyclic nitrogenous disinfection byproducts: Formation and cytotoxicity of halopyridinols in drinking water.

Recently, a new group of halopyridinol disinfection byproducts (DBPs) was reported in drinking water. The in vivo developmental and acute toxicity assays have shown that they were more toxic than a few commonly known aliphatic DBPs such as bromoform and iodoacetic acid. However, many pyridinol DBPs with the same main structures but different halogen substitutions were still unknown due to complicated water quality conditions and various disinfection methods applied in drinking water treatment plants. Studies on their transformation mechanisms in drinking water disinfection were quite limited. In this study, comprehensive detection and identification of halopyridinols were conducted, and five new halopyridinols were first reported, including 2-chloro-3-pyridinol, 2,6-dichloro-3-pyridinol, 2-bromo-5-chloro-3-pyridinol, 2,4,6-trichloro-3-pyridinol and 2,5,6-trichloro-3-pyridinol. Formation conditions and mechanisms of the halopyridinols were explored, and results showed that chlorination promoted their formation compared with chloramination. Halopyridinols were intermediate DBPs that could undergo further transformation/degradation with increasing contact time, disinfectant dose, bromide concentration, and pH. The in vitro cytotoxicity of the halopyridinols was evaluated using human hepatocellular carcinoma cells. Results showed that the cytotoxicity of 3,5,6-trichloro-2-pyridinol was the highest (EC50 = 474.3 µM), which was 13.0 and 1.6 times higher than that of 2-bromo-3-pyridinol (EC50 = 6214.5 µM) and tribromomethane (EC50 = 753.6 µM), respectively.

Magnetic Graphene Oxide Nanocomposites Boosts Craniomaxillofacial Bone Regeneration by Modulating circAars/miR-128-3p/SMAD5 Signaling Axis.

Background: The ability of nanomaterials to induce osteogenic differentiation is limited, which seriously imped the repair of craniomaxillofacial bone defect. Magnetic graphene oxide (MGO) nanocomposites with the excellent physicochemical properties have great potential in bone tissue engineering. In this study, we aim to explore the craniomaxillofacial bone defect repairment effect of MGO nanocomposites and its underlying mechanism. Methods: The biocompatibility of MGO nanocomposites was verified by CCK8, live/dead staining and cytoskeleton staining. The function of MGO nanocomposites induced osteogenic differentiation of BMSCs was investigated by ALP activity detection, mineralized nodules staining, detection of osteogenic genes and proteins, and immune-histochemical staining. BMSCs with or without MGO osteogenic differentiation induction were collected and subjected to high-throughput circular ribonucleic acids (circRNAs) sequencing, and then crucial circRNA circAars was screened and identified. Bioinformatics analysis, Dual-luciferase reporter assay, RNA binding protein immunoprecipitation (RIP), fluorescence in situ hybridization (FISH) and osteogenic-related examinations were used to further explore the ability of circAars to participate in MGO nanocomposites regulation of osteogenic differentiation of BMSCs and its potential mechanism. Furthermore, critical-sized calvarial defects were constructed and were performed to verify the osteogenic differentiation induction effects and its potential mechanism induced by MGO nanocomposites. Results: We verify the good biocompatibility and osteogenic differentiation improvement effects of BMSCs mediated by MGO nanocomposites. Furthermore, a new circRNA-circAars, we find and identify, is obviously upregulated in BMSCs mediated by MGO nanocomposites. Silencing circAars could significantly decrease the osteogenic ability of MGO nanocomposites. The underlying mechanism involved circAars sponging miR-128-3p to regulate the expression of SMAD5, which played an important role in the repair craniomaxillofacial bone defects mediated by MGO nanocomposites. Conclusion: We found that MGO nanocomposites regulated osteogenic differentiation of BMSCs via the circAars/miR-128-3p/SMAD5 pathway, which provided a feasible and effective strategy for the treatment of craniomaxillofacial bone defects.

Searching for Two-Neutrino and Neutrinoless Double Beta Decay of

^{134}Xe is a candidate isotope for neutrinoless double beta decay (0νßß) search. In addition, the two-neutrino case (2νßß) allowed by the standard model of particle physics has not yet been observed. With the 656-kg natural xenon in the fiducial volume of the PandaX-4T detector, which contains 10.4% of ^{134}Xe, and its initial 94.9-day exposure, we have established the most stringent constraints on 2νßß and 0νßß of ^{134}Xe half-lives, with limits of 2.8×10^{22} yr and 3.0×10^{23} yr at 90% confidence level, respectively. The 2νßß (0νßß) limit surpasses the previously reported best result by a factor of 32 (2.7), highlighting the potential of large monolithic natural xenon detectors for double beta decay searches.

VirusPredictor: XGBoost-based software to predict virus-related sequences in human data.

MOTIVATION: Discovering disease causative pathogens, particularly viruses without reference genomes, poses a technical challenge as they are often unidentifiable through sequence alignment. Machine learning prediction of patient high-throughput sequences unmappable to human and pathogen genomes may reveal sequences originating from uncharacterized viruses. Currently, there is a lack of software specifically designed for accurately predicting such viral sequences in human data. RESULTS: We developed a fast XGBoost method and software VirusPredictor leveraging an in-house viral genome database. Our two-step XGBoost models first classify each query sequence into one of three groups: infectious virus, endogenous retrovirus (ERV) or non-ERV human. The prediction accuracies increased as the sequences became longer, i.e. 0.76, 0.93, and 0.98 for 150-350 (Illumina short reads), 850-950 (Sanger sequencing data), and 2000-5000 bp sequences, respectively. Then, sequences predicted to be from infectious viruses are further classified into one of six virus taxonomic subgroups, and the accuracies increased from 0.92 to >0.98 when query sequences increased from 150-350 to >850 bp. The results suggest that Illumina short reads should be de novo assembled into contigs (e.g. ∼1000 bp or longer) before prediction whenever possible. We applied VirusPredictor to multiple real genomic and metagenomic datasets and obtained high accuracies. VirusPredictor, a user-friendly open-source Python software, is useful for predicting the origins of patients' unmappable sequences. This study is the first to classify ERVs in infectious viral sequence prediction. This is also the first study combining virus sub-group predictions. AVAILABILITY AND IMPLEMENTATION: www.dllab.org/software/VirusPredictor.html.

Applications of charcoal, activated charcoal, and biochar in aquaculture - A review.

Environmental pollution and poor feed quality pose potential threats to aquatic organisms and human health, representing challenges for the aquaculture industry. In light of the rising demand for aquatic organisms, there is an urgent need to improve aquacultural production and protect the products from contamination. Char, a carbonaceous material derived through pyrolysis of organic carbon-rich biomass, has proven advantages in soil, air, and water remediation. While char's performance and the associated physicochemical characteristics depend strongly on the pyrolysis temperature, residence time, and feedstock type, char generally shows advantages in pollutant removal from the environment and livestock. This enables it to enhance the health and growth performance of livestock. Given the growing attention to char application in aquaculture in recent years, this review summarises major studies on three applications: aquacultural water treatment, sediment remediation, and char-feed supplement. Most of these studies have demonstrated char's positive effects on pollutant removal from organisms and aquacultural environments. Moreover, adopting char as fish feed can improve fish growth performance and the condition of their intestinal villi. However, due to insufficient literature, further investigation is needed into the mechanistic aspects of pollutants removal in aquatic organisms by char as a feed additive, such as the transportation of char inside aquatic organisms, the positive and negative effects of char on these products, and how char alters the gut microbiota community of these products. This paper presents an overview of the current application of char in aquaculture and highlights the research areas that require further investigation to enrich future studies.

Applications of Data Characteristic AI-Assisted Raman Spectroscopy in Pathological Classification.

Raman spectroscopy has been widely used for label-free biomolecular analysis of cells and tissues for pathological diagnosis in vitro and in vivo. AI technology facilitates disease diagnosis based on Raman spectroscopy, including machine learning (PCA and SVM), manifold learning (UMAP), and deep learning (ResNet and AlexNet). However, it is not clear how to optimize the appropriate AI classification model for different types of Raman spectral data. Here, we selected five representative Raman spectral data sets, including endometrial carcinoma, hepatoma extracellular vesicles, bacteria, melanoma cell, diabetic skin, with different characteristics regarding sample size, spectral data size, Raman shift range, tissue sites, Kullback-Leibler (KL) divergence, and significant Raman shifts (i.e., wavenumbers with significant differences between groups), to explore the performance of different AI models (e.g., PCA-SVM, SVM, UMAP-SVM, ResNet or AlexNet). For data set of large spectral data size, Resnet performed better than PCA-SVM and UMAP. By building data characteristic-assisted AI classification model, we optimized the network parameters (e.g., principal components, activation function, and loss function) of AI model based on data size and KL divergence etc. The accuracy improved from 85.1 to 94.6% for endometrial carcinoma grading, from 77.1 to 90.7% for hepatoma extracellular vesicles detection, from 89.3 to 99.7% for melanoma cell detection, from 88.1 to 97.9% for bacterial identification, from 53.7 to 85.5% for diabetic skin screening, and mean time expense of 5 s.

Multi-Dimensional Medical Image Fusion With Complex Sparse Representation.

In the field of medical imaging, the fusion of data from diverse modalities plays a pivotal role in advancing our understanding of pathological conditions. Sparse representation (SR), a robust signal modeling technique, has demonstrated noteworthy success in multi-dimensional (MD) medical image fusion. However, a fundamental limitation appearing in existing SR models is their lack of directionality, restricting their efficacy in extracting anatomical details from different imaging modalities. To tackle this issue, we propose a novel directional SR model, termed complex sparse representation (ComSR), specifically designed for medical image fusion. ComSR independently represents MD signals over directional dictionaries along specific directions, allowing precise analysis of intricate details of MD signals. Besides, current studies in medical image fusion mostly concentrate on addressing either 2D or 3D fusion problems. This work bridges this gap by proposing a MD medical image fusion method based on ComSR, presenting a unified framework for both 2D and 3D fusion tasks. Experimental results across six multi-modal medical image fusion tasks, involving 93 pairs of 2D source images and 20 pairs of 3D source images, substantiate the superiority of our proposed method over 11 state-of-the-art 2D fusion methods and 4 representative 3D fusion methods, in terms of both visual quality and objective evaluation. The source code of our fusion method is available at https://github.com/Imagefusions/imagefusions/tree/main.